From 1d7a8dd87b05f508fd05a0d01d5821d600fa2fd8 Mon Sep 17 00:00:00 2001 From: Joshua Karns Date: Thu, 30 May 2019 14:12:06 -0400 Subject: [PATCH] More refactoring --- .gitignore | 5 +- src/__main__.py | 10 +- src/app.py | 6 +- src/data_structures/bands.py | 1 + src/data_structures/cache.py | 37 +- src/data_structures/lines.py | 2 +- src/data_structures/xsc.py | 18 +- src/graphing/hapi_series.py | 11 +- src/hapi.py | 8048 +++++++---------- src/metadata/config.py | 172 +- src/metadata/hapi_metadata.py | 32 +- src/metadata/isotopologue_meta.py | 132 +- src/metadata/molecule_meta.py | 15 +- src/metadata/xsc_meta.py | 10 +- src/test/__init__.py | 19 +- src/test/band_display_test.py | 3 +- src/test/config_editor_test.py | 4 +- src/test/fail_test.py | 1 + src/test/graph_display_test.py | 8 +- src/test/hapi_sources_test.py | 40 +- src/test/molecule_info_test.py | 33 +- src/test/test.py | 1 + src/test/throw_test.py | 1 + src/utils/colors.py | 9 +- src/utils/dsl.py | 43 +- src/utils/fetch_error.py | 2 +- src/utils/hapi_api.py | 13 +- src/utils/hapiest_util.py | 2 +- src/utils/log.py | 31 +- src/widgets/about_widget.py | 1 + src/widgets/config_editor_widget.py | 5 +- src/widgets/cross_section_fetch_widget.py | 5 +- src/widgets/fetch_widget.py | 32 +- .../graphing/band_display_window_gui.py | 10 +- src/widgets/graphing/band_legend.py | 4 +- .../graphing/graph_display_window_gui.py | 29 +- src/widgets/graphing/graphing_widget.py | 131 +- src/widgets/hapi_source_widget.py | 3 +- src/widgets/hapi_table_view.py | 12 +- src/widgets/main_window_gui.py | 3 +- src/widgets/molecule_info_widget.py | 2 +- src/widgets/select_widget.py | 10 +- src/windows/graph_display_window.py | 23 +- src/windows/main_window.py | 1 + src/worker/hapi_worker.py | 2 +- src/worker/work_request.py | 43 +- src/worker/work_result.py | 1 + 47 files changed, 3771 insertions(+), 5255 deletions(-) diff --git a/.gitignore b/.gitignore index f4c4864..2698f11 100644 --- a/.gitignore +++ b/.gitignore @@ -2,6 +2,7 @@ data/* src/*.pyc *.pyc src/__pycache__/ +*/__pycache__/* test_data/* Config.toml .idea/* @@ -16,8 +17,10 @@ build/ *.toc *.synctex *.aux +*.pdf build/* dist/* /binaries/Linux/bin/* /binaries/Mac OSX/bin/* -/binaries/Windows/bin/* \ No newline at end of file +/binaries/Windows/bin/* +/venv/* \ No newline at end of file diff --git a/src/__main__.py b/src/__main__.py index 97ec321..9494fd6 100644 --- a/src/__main__.py +++ b/src/__main__.py @@ -1,6 +1,6 @@ """ This is the main module. It basically checks that there is a hapi api key, asks for one if there -is not one, and launches the main GUI. Thats about it. +is not one, and launches the main GUI. That's about it. """ from multiprocessing import freeze_support import sys @@ -11,9 +11,15 @@ from startup import fix_cwd, check_version from app import run + check_version() fix_cwd() if __name__ == '__main__': freeze_support() - sys.exit(run()) + try: + sys.exit(run()) + except TypeError as err: + print(f"Encountered type error:\n {str(err)}") + except Exception as err: + print(f"Encountered an error: \n {str(err)}") diff --git a/src/app.py b/src/app.py index ec3f34d..117258f 100644 --- a/src/app.py +++ b/src/app.py @@ -26,8 +26,8 @@ def obtain_apikey(): from widgets.apikey_help_widget import ApiKeyHelpWidget, ApiKeyValidator - if Config.hapi_api_key == '0000' or \ - ApiKeyValidator.APIKEY_REGEX.match(Config.hapi_api_key) is None: + if Config.hapi_api_key == '0000' or ApiKeyValidator.APIKEY_REGEX.match( + Config.hapi_api_key) is None: app = QtWidgets.QApplication(sys.argv) _ = ApiKeyHelpWidget() app.exec_() @@ -47,7 +47,7 @@ def verify_internet_connection_and_obtain_api_key(): try: with urllib.request.urlopen( f"{CrossSectionApi.BASE_URL}/{CrossSectionApi.API_ROUTE}/{Config.hapi_api_key}" \ - f"{CrossSectionApi.XSC_META_ROUTE}"): + f"{CrossSectionApi.XSC_META_ROUTE}"): pass return True except HTTPError as _: diff --git a/src/data_structures/bands.py b/src/data_structures/bands.py index 8643b3a..77cdc8b 100644 --- a/src/data_structures/bands.py +++ b/src/data_structures/bands.py @@ -2,6 +2,7 @@ class Band: + def __init__(self, nu: List[float], sw: List[float], band_id: str): self.x = nu self.y = sw diff --git a/src/data_structures/cache.py b/src/data_structures/cache.py index 3ab7789..2cbeca3 100644 --- a/src/data_structures/cache.py +++ b/src/data_structures/cache.py @@ -32,19 +32,14 @@ class Cache: def __init__(self, path: str, web_fetch_routine: Callable[[], Union[str, bytes, Any]], lifetime: timedelta): """ - :param path: The path, starting from the cache root, of the file that the cache should be located or stored. :param web_fetch_routine: A function which will return a string on success, and something - else otherwise. The - something else can be retrieved using the err function. web_fetch_routine should - not throw any - exceptions, and should return a string or bytes on success, and anything else - will be considered a - failure. + else otherwise. The something else can be retrieved using the err function. + web_fetch_routine should not throw any exceptions, and should return a string or bytes on + success, and anything else will be considered a failure. :param lifetime: A duration, after which, the cached results should be thrown out and - re-retrieved. Therefore it - is the lifetime of the cached data! + re-retrieved. """ self.path = "{}/{}/{}".format(Config.data_folder, Cache.CACHE_ROOT, path) @@ -60,11 +55,9 @@ def __init__(self, path: str, web_fetch_routine: Callable[[], Union[str, bytes, def __load_from_file(self) -> bool: """ Attempts to load the cache from a file. If the containing directories don't exist they're - created, and then the - __load_from_web function will be called. + created, and then the __load_from_web function will be called. :return: Returns False if the function failed to load the file. This either means it - doesn't exist or something - weird happened + doesn't exist or something weird happened """ import os.path @@ -82,8 +75,8 @@ def __load_from_file(self) -> bool: text = file.read() # This reads whole contents of the file. parsed = json.loads(text) # This means the lifetime of the cache has expired (parsed['timestamp'] contains - # the unix timestamp of - # when the file was written added to the number of seconds before expiration). + # the unix timestamp of when the file was written added to the number of seconds + # before expiration). if int(time.time()) > parsed['timestamp']: return False self.cached = parsed['cached'] @@ -110,10 +103,8 @@ def __load_from_web(self) -> bool: return False try: with open(self.path, 'w+') as file: - file.write(json.dumps({ - 'timestamp': int(time.time()) + self.lifetime, - 'cached': self.cached - })) + file.write(json.dumps( + {'timestamp': int(time.time()) + self.lifetime, 'cached': self.cached})) except Exception as e: print('Failed to write to CrossSectionMeta cache: {}'.format(str(e))) return True @@ -133,8 +124,7 @@ def ok(self) -> bool: def data(self) -> str: """ :return: The cached data, if it exists. If `self.ok()` returns true this should return a - str. Otherwise, it - will return None. + str. Otherwise, it will return None. """ return self.cached @@ -150,9 +140,8 @@ def __init__(self, path: str, web_fetch_routine: Callable[[], Union[str, Any]], def data(self) -> Any: """ - :return: The cached data as parsed JSON. Will return None if there is no cached data ( - i.e. something went wrong) - or if the data is invalid JSON. + :return: The cached data as parsed JSON. Will return None if there is no cached data (i.e. + something went wrong) or if the data is invalid JSON. """ try: res = json.loads(self.cached) diff --git a/src/data_structures/lines.py b/src/data_structures/lines.py index 97230b8..fbe8afa 100644 --- a/src/data_structures/lines.py +++ b/src/data_structures/lines.py @@ -37,7 +37,6 @@ class Lines: ``` This is the schema hapi version < 2.0 uses already. - """ def __init__(self, table: Dict[str, Any]): @@ -84,6 +83,7 @@ def set_page(self, page_number): class Line: + def __init__(self, line_index: int, line: List[Union[int, float, str]], lines: 'Lines'): self.line_index = line_index self.line = line diff --git a/src/data_structures/xsc.py b/src/data_structures/xsc.py index cef93f4..643fd26 100644 --- a/src/data_structures/xsc.py +++ b/src/data_structures/xsc.py @@ -10,8 +10,7 @@ class CrossSection: """ def __init__(self, nu: Iterable[float], abscoef: Iterable[float], step: float, numin: float, - numax: float, - molecule: str, len: int, pressure: float, temp: float): + numax: float, molecule: str, len: int, pressure: float, temp: float): self.nu = tuple(nu) self.abscoef = tuple(abscoef) self.step = step @@ -74,9 +73,8 @@ def __init__(self, molecule_id: int, wn_range: Tuple[float, float] = None, def get_cross_sections(self) -> List[str]: if self.molecule_id not in CrossSectionMeta.molecule_metas: return [] - return [item['filename'] - for item in CrossSectionMeta.molecule_metas[self.molecule_id] - if self.xsc_is_conformant(item)] + return [item['filename'] for item in CrossSectionMeta.molecule_metas[self.molecule_id] if + self.xsc_is_conformant(item)] def xsc_is_conformant(self, xsc) -> bool: """ @@ -86,8 +84,8 @@ def xsc_is_conformant(self, xsc) -> bool: conditions of this filter, otherwise false. """ return (self.pressure_range is None or ( - self.pressure_range[0] < xsc['pressure'] < self.pressure_range[1])) \ - and (self.temp_range is None or ( - self.temp_range[0] < xsc['temperature'] < self.temp_range[1])) \ - and (self.wn_range is None or ( - xsc['numin'] < self.wn_range[0] and xsc['numax'] > self.wn_range[1])) + self.pressure_range[0] < xsc['pressure'] < self.pressure_range[1])) and ( + self.temp_range is None or ( + self.temp_range[0] < xsc['temperature'] < self.temp_range[1])) and ( + self.wn_range is None or ( + xsc['numin'] < self.wn_range[0] and xsc['numax'] > self.wn_range[1])) diff --git a/src/graphing/hapi_series.py b/src/graphing/hapi_series.py index 85583c5..1a319c6 100644 --- a/src/graphing/hapi_series.py +++ b/src/graphing/hapi_series.py @@ -16,10 +16,8 @@ def __init__(self, x=(), y=(), use_scatter_plot=True, name=""): self.series = self.create_series() for i in range(0, len(x)): # Since qt won't graph a chart using a log scale if there is a negative or zero - # value, - # make sure everything is > 0. - # This shouldn't be a problem since all of the graph types work with positive - # quantities. + # value, make sure everything is > 0. This shouldn't be a problem since all of + # the graph types work with positive quantities. if y[i] < 1e-138: self.append(x[i], 1e-138) else: @@ -50,8 +48,9 @@ def isVisible(self) -> bool: def internal_copy(self): """ Makes a copy of the underlying series. This is needed because after removing a series - from a chart, - Qt deallocates the QLineSeries. + from a chart, Qt deallocates the QLineSeries (the qt documents say the QChart gains + ownership of the QLineSeries, which gives the QChart the responsibility of managing the + memory. """ new_series = self.create_series() for point in self.series.pointsVector(): diff --git a/src/hapi.py b/src/hapi.py index 48071e0..78bce74 100644 --- a/src/hapi.py +++ b/src/hapi.py @@ -97,7 +97,7 @@ cSqrt2Ln2 = 1.1774100225 # initialize global variables -VARIABLES = { } +VARIABLES = {} VARIABLES['DEBUG'] = False if VARIABLES['DEBUG']: @@ -171,7 +171,7 @@ def setAttribute(Object, Attribute, Value): # = prototype for a Query instance # there should be a getAttrbute/setSettribute functions defined # For Django: Query=QuerySet (as an example) -Query = { } +Query = {} # prototype for cache storage # there must be function for record/retrieve @@ -180,7 +180,7 @@ def setAttribute(Object, Attribute, Value): # if there is already table with such query, copy it # if there is already tble with such query AND table_name, # return it as is => IT MAY DEPEND ON CERTAIN QUERY TYPE!! -TABLES = { } # hash/dictionary +TABLES = {} # hash/dictionary # ---------- CONNECTION MANAGEMENT------------- @@ -257,21 +257,13 @@ def getRawDataRemote(Query, Connection=GLOBAL_CONNECTION): NODE_NAME = 'local' -GLOBAL_NODENAMES = { - 0: 'hitran-main', - 1: 'local' - } +GLOBAL_NODENAMES = {0: 'hitran-main', 1: 'local'} -GLOBAL_NODELIST = { - 0: { # main HITRAN node - 'host': VARIABLES['GLOBAL_HOST'], - 'ACCESS_KEY': '9b6a7975-2a84-43d8-920e-f4dea9db6805' # guest - }, - 1: { # local node prototype - 'host': LOCAL_HOST, - 'ACCESS_KEY': '6cfd7040-24a6-4197-81f9-6e25e50005b2', # admin - } - } +GLOBAL_NODELIST = {0: { # main HITRAN node + 'host': VARIABLES['GLOBAL_HOST'], 'ACCESS_KEY': '9b6a7975-2a84-43d8-920e-f4dea9db6805' # guest +}, 1: { # local node prototype + 'host': LOCAL_HOST, 'ACCESS_KEY': '6cfd7040-24a6-4197-81f9-6e25e50005b2', # admin +}} def createNode(NodeID, NodeList=GLOBAL_NODELIST): @@ -279,7 +271,7 @@ def createNode(NodeID, NodeList=GLOBAL_NODELIST): node = NodeList.get(NodeID) if node: raise Exception('node %s already exists' % NodeName) - NodeList[NodeID] = { } + NodeList[NodeID] = {} pass @@ -347,15 +339,8 @@ def checkAccess(DBName, TableName, NodeName, UserName, Requisites, NodeList=GLOB # Default key is 'admin', it's created seamlessly for a local admin. GLOBAL_PRIVILEGES = { - 'admin': { - 'ACCESS_KEY': '6cfd7040-24a6-4197-81f9-6e25e50005b2', - 'LEVEL': 'ADMIN' - }, - 'guest': { - 'ACCESS_KEY': '9b6a7975-2a84-43d8-920e-f4dea9db6805', - 'LEVEL': 'USER' - } - } + 'admin': {'ACCESS_KEY': '6cfd7040-24a6-4197-81f9-6e25e50005b2', 'LEVEL': 'ADMIN'}, + 'guest': {'ACCESS_KEY': '9b6a7975-2a84-43d8-920e-f4dea9db6805', 'LEVEL': 'USER'}} def addUser(): @@ -471,991 +456,621 @@ def checkPrivileges(Path, UserName=GLOBAL_USER, Requisites=GLOBAL_REQUISITES, VARIABLES['BACKEND_DATABASE_NAME'] = BACKEND_DATABASE_NAME_DEFAULT # For this node local DB is schema-dependent! -LOCAL_TABLE_CACHE = { - 'sampletab': { # table - 'header': { # header - 'order': ('column1', 'column2', 'column3'), - 'format': { - 'column1': '%10d', - 'column2': '%20f', - 'column3': '%30s' - }, - 'default': { - 'column1': 0, - 'column2': 0.0, - 'column3': '' - }, - 'number_of_rows': 3, - 'size_in_bytes': None, - 'table_name': 'sampletab', - 'table_type': 'strict' - }, # /header - 'data': { - 'column1': [1, 2, 3], - 'column2': [10.5, 11.5, 12.5], - 'column3': ['one', 'two', 'three'] - }, # /data - } # /table - } # hash-map of tables +LOCAL_TABLE_CACHE = {'sampletab': { # table + 'header': { # header + 'order': ('column1', 'column2', 'column3'), + 'format': {'column1': '%10d', 'column2': '%20f', 'column3': '%30s'}, + 'default': {'column1': 0, 'column2': 0.0, 'column3': ''}, 'number_of_rows': 3, + 'size_in_bytes': None, 'table_name': 'sampletab', 'table_type': 'strict'}, # /header + 'data': {'column1': [1, 2, 3], 'column2': [10.5, 11.5, 12.5], + 'column3': ['one', 'two', 'three']}, # /data +} # /table +} # hash-map of tables # FORMAT CONVERSION LAYER # converts between TRANSPORT_FORMAT and OBJECT_FORMAT -HITRAN_FORMAT_160 = { - 'M': { 'pos': 1, 'len': 2, 'format': '%2d' }, - 'I': { 'pos': 3, 'len': 1, 'format': '%1d' }, - 'nu': { 'pos': 4, 'len': 12, 'format': '%12f' }, - 'S': { 'pos': 16, 'len': 10, 'format': '%10f' }, - 'R': { 'pos': 26, 'len': 0, 'format': '%0f' }, - 'A': { 'pos': 26, 'len': 10, 'format': '%10f' }, - 'gamma_air': { 'pos': 36, 'len': 5, 'format': '%5f' }, - 'gamma_self': { 'pos': 41, 'len': 5, 'format': '%5f' }, - 'E_': { 'pos': 46, 'len': 10, 'format': '%10f' }, - 'n_air': { 'pos': 56, 'len': 4, 'format': '%4f' }, - 'delta_air': { 'pos': 60, 'len': 8, 'format': '%8f' }, - 'V': { 'pos': 68, 'len': 15, 'format': '%15s' }, - 'V_': { 'pos': 83, 'len': 15, 'format': '%15s' }, - 'Q': { 'pos': 98, 'len': 15, 'format': '%15s' }, - 'Q_': { 'pos': 113, 'len': 15, 'format': '%15s' }, - 'Ierr': { 'pos': 128, 'len': 6, 'format': '%6s' }, - 'Iref': { 'pos': 134, 'len': 12, 'format': '%12s' }, - 'flag': { 'pos': 146, 'len': 1, 'format': '%1s' }, - 'g': { 'pos': 147, 'len': 7, 'format': '%7f' }, - 'g_': { 'pos': 154, 'len': 7, 'format': '%7f' } - } +HITRAN_FORMAT_160 = {'M': {'pos': 1, 'len': 2, 'format': '%2d'}, + 'I': {'pos': 3, 'len': 1, 'format': '%1d'}, + 'nu': {'pos': 4, 'len': 12, 'format': '%12f'}, + 'S': {'pos': 16, 'len': 10, 'format': '%10f'}, + 'R': {'pos': 26, 'len': 0, 'format': '%0f'}, + 'A': {'pos': 26, 'len': 10, 'format': '%10f'}, + 'gamma_air': {'pos': 36, 'len': 5, 'format': '%5f'}, + 'gamma_self': {'pos': 41, 'len': 5, 'format': '%5f'}, + 'E_': {'pos': 46, 'len': 10, 'format': '%10f'}, + 'n_air': {'pos': 56, 'len': 4, 'format': '%4f'}, + 'delta_air': {'pos': 60, 'len': 8, 'format': '%8f'}, + 'V': {'pos': 68, 'len': 15, 'format': '%15s'}, + 'V_': {'pos': 83, 'len': 15, 'format': '%15s'}, + 'Q': {'pos': 98, 'len': 15, 'format': '%15s'}, + 'Q_': {'pos': 113, 'len': 15, 'format': '%15s'}, + 'Ierr': {'pos': 128, 'len': 6, 'format': '%6s'}, + 'Iref': {'pos': 134, 'len': 12, 'format': '%12s'}, + 'flag': {'pos': 146, 'len': 1, 'format': '%1s'}, + 'g': {'pos': 147, 'len': 7, 'format': '%7f'}, + 'g_': {'pos': 154, 'len': 7, 'format': '%7f'}} # This should be generating from the server's response -HITRAN_DEFAULT_HEADER = { - "table_type": "column-fixed", - "size_in_bytes": -1, - "table_name": "###", - "number_of_rows": -1, - "order": [ - "molec_id", - "local_iso_id", - "nu", - "sw", - "a", - "gamma_air", - "gamma_self", - "elower", - "n_air", - "delta_air", - "global_upper_quanta", - "global_lower_quanta", - "local_upper_quanta", - "local_lower_quanta", - "ierr", - "iref", - "line_mixing_flag", - "gp", - "gpp" - ], - "format": { - "a": "%10.3E", - "gamma_air": "%5.4f", - "gp": "%7.1f", - "local_iso_id": "%1d", - "molec_id": "%2d", - "sw": "%10.3E", - "local_lower_quanta": "%15s", - "local_upper_quanta": "%15s", - "gpp": "%7.1f", - "elower": "%10.4f", - "n_air": "%4.2f", - "delta_air": "%8.6f", - "global_upper_quanta": "%15s", - "iref": "%12s", - "line_mixing_flag": "%1s", - "ierr": "%6s", - "nu": "%12.6f", - "gamma_self": "%5.3f", - "global_lower_quanta": "%15s" - }, - "default": { - "a": 0.0, - "gamma_air": 0.0, - "gp": "FFF", - "local_iso_id": 0, - "molec_id": 0, - "sw": 0.0, - "local_lower_quanta": "000", - "local_upper_quanta": "000", - "gpp": "FFF", - "elower": 0.0, - "n_air": 0.0, - "delta_air": 0.0, - "global_upper_quanta": "000", - "iref": "EEE", - "line_mixing_flag": "EEE", - "ierr": "EEE", - "nu": 0.0, - "gamma_self": 0.0, - "global_lower_quanta": "000" - }, - "description": { - "a": "Einstein A-coefficient in s-1", - "gamma_air": "Air-broadened Lorentzian half-width at half-maximum at p = 1 atm " - "and T = 296 K", - "gp": "Upper state degeneracy", - "local_iso_id": "Integer ID of a particular Isotopologue, unique only to a given " - "molecule, in order or abundance (1 = most abundant)", - "molec_id": "The HITRAN integer ID for this molecule in all its isotopologue " - "forms", - "sw": "Line intensity, multiplied by isotopologue abundance, at T = 296 K", - "local_lower_quanta": "Rotational, hyperfine and other quantum numbers and labels for " - "the lower state of a transition", - "local_upper_quanta": "Rotational, hyperfine and other quantum numbers and labels for " - "the upper state of a transition", - "gpp": "Lower state degeneracy", - "elower": "Lower-state energy", - "n_air": "Temperature exponent for the air-broadened HWHM", - "delta_air": "Pressure shift induced by air, referred to p=1 atm", +HITRAN_DEFAULT_HEADER = {"table_type": "column-fixed", "size_in_bytes": -1, "table_name": "###", + "number_of_rows": -1, "order": ["molec_id", "local_iso_id", "nu", "sw", "a", "gamma_air", + "gamma_self", "elower", "n_air", "delta_air", "global_upper_quanta", "global_lower_quanta", + "local_upper_quanta", "local_lower_quanta", "ierr", "iref", "line_mixing_flag", "gp", + "gpp"], "format": {"a": "%10.3E", "gamma_air": "%5.4f", "gp": "%7.1f", + "local_iso_id": "%1d", "molec_id": "%2d", "sw": "%10.3E", + "local_lower_quanta": "%15s", "local_upper_quanta": "%15s", "gpp": "%7.1f", + "elower": "%10.4f", "n_air": "%4.2f", "delta_air": "%8.6f", + "global_upper_quanta": "%15s", "iref": "%12s", "line_mixing_flag": "%1s", "ierr": "%6s", + "nu": "%12.6f", "gamma_self": "%5.3f", "global_lower_quanta": "%15s"}, + "default": {"a": 0.0, "gamma_air": 0.0, "gp": "FFF", "local_iso_id": 0, "molec_id": 0, + "sw": 0.0, "local_lower_quanta": "000", "local_upper_quanta": "000", + "gpp": "FFF", "elower": 0.0, "n_air": 0.0, "delta_air": 0.0, + "global_upper_quanta": "000", "iref": "EEE", "line_mixing_flag": "EEE", "ierr": "EEE", + "nu": 0.0, "gamma_self": 0.0, "global_lower_quanta": "000"}, + "description": {"a": "Einstein A-coefficient in s-1", + "gamma_air": "Air-broadened Lorentzian half-width at half-maximum at p = 1 atm " + "and T = 296 K", "gp": "Upper state degeneracy", + "local_iso_id": "Integer ID of a particular Isotopologue, unique only to a given " + "molecule, in order or abundance (1 = most abundant)", + "molec_id": "The HITRAN integer ID for this molecule in all its isotopologue " + "forms", + "sw": "Line intensity, multiplied by isotopologue abundance, at T = 296 K", + "local_lower_quanta": "Rotational, hyperfine and other quantum numbers and labels for " + "the lower state of a transition", + "local_upper_quanta": "Rotational, hyperfine and other quantum numbers and labels for " + "the upper state of a transition", "gpp": "Lower state degeneracy", + "elower": "Lower-state energy", "n_air": "Temperature exponent for the air-broadened HWHM", + "delta_air": "Pressure shift induced by air, referred to p=1 atm", "global_upper_quanta": "Electronic and vibrational quantum numbers and labels for the " "upper state of a transition", - "iref": "Ordered list of reference identifiers for transition parameters", - "line_mixing_flag": "A flag indicating the presence of additional data and code " - "relating to line-mixing", - "ierr": "Ordered list of indices corresponding to uncertainty estimates of" - " transition parameters", - "nu": "Transition wavenumber", - "gamma_self": "Self-broadened HWHM at 1 atm pressure and 296 K", + "iref": "Ordered list of reference identifiers for transition parameters", + "line_mixing_flag": "A flag indicating the presence of additional data and code " + "relating to line-mixing", + "ierr": "Ordered list of indices corresponding to uncertainty estimates of" + " transition parameters", "nu": "Transition wavenumber", + "gamma_self": "Self-broadened HWHM at 1 atm pressure and 296 K", "global_lower_quanta": "Electronic and vibrational quantum numbers and labels for the " - "lower state of a transition" - }, - } - -PARAMETER_META = \ - { - "global_iso_id": { - "id": 1, - "name": "global_iso_id", - "name_html": "Global isotopologue ID", - "table_name": "", - "description": "Unique integer ID of a particular isotopologue: every global " - "isotopologue ID is unique to a particular species, even between " - "different molecules. 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"default_fmt": "%7.4f", "default_units": "", "data_type": "float", "selectable": 1, + "has_reference": 1, "has_error": 1}, + "delta_He": {"id": 44, "name": "delta_He", "name_html": "δHe", + "table_name": "prm_delta_He", + "description": "Pressure shift induced by He, referred to p=1 atm", + "description_html": "Pressure shift induced by He, referred to p=1 atm", + "default_fmt": "%9.6f", "default_units": "cm-1.atm-1", "data_type": "float", + "selectable": 1, "has_reference": 1, "has_error": 1}, + "gamma_CO2": {"id": 45, + "name": "gamma_CO2", + "name_html": + "γCO2 ", + "table_name": "prm_gamma_CO2", + "description": "Lorentzian " + "lineshape " + "HWHM due to " + "pressure " + "broadening " + "by CO2 at 1" + " atm pressure", + "description_html": "Lorentzian " + "lineshape " + "HWHM due to " + "pressure " + "broadening by " + "CO2 at 1 atm pressure", + "default_fmt": "%6.4f", + "default_units": "cm-1.atm-1", + "data_type": "float", + "selectable": 1, + "has_reference": 1, + "has_error": 1}, + "n_CO2": {"id": 46, "name": "n_CO2", "name_html": "nCO2", + "table_name": "prm_n_CO2", + "description": "Temperature exponent for the CO2-broadened HWHM", + "description_html": "Temperature exponent for the CO2-broadened HWHM", + "default_fmt": "%7.4f", "default_units": "", "data_type": "float", "selectable": 1, + "has_reference": 1, "has_error": 1}, + "delta_CO2": {"id": 47, "name": "delta_CO2", + "name_html": + "δCO2", + "table_name": "prm_delta_CO2", + "description": "Pressure shift induced by " + "CO2, referred to p=1 atm", + "description_html": "Pressure shift induced by " + "CO2, referred to " + "p=1 atm", + "default_fmt": "%9.6f", + "default_units": "cm-1.atm-1", + "data_type": "float", "selectable": 1, + "has_reference": 1, "has_error": 1}, + "gamma_HT_0_self_50": {"default_fmt": "%6.4f", }, "n_HT_self_50": {"default_fmt": "%9.6f", }, + "gamma_HT_2_self_50": {"default_fmt": "%6.4f", }, + "delta_HT_0_self_50": {"default_fmt": "%9.6f", }, + "deltap_HT_self_50": {"default_fmt": "%9.6f", }, + "delta_HT_2_self_50": {"default_fmt": "%9.6f", }, + "gamma_HT_0_self_150": {"default_fmt": "%6.4f", }, "n_HT_self_150": {"default_fmt": "%9.6f", }, + "gamma_HT_2_self_150": {"default_fmt": "%6.4f", }, + "delta_HT_0_self_150": {"default_fmt": "%9.6f", }, + "deltap_HT_self_150": {"default_fmt": "%9.6f", }, + "delta_HT_2_self_150": {"default_fmt": "%9.6f", }, + "gamma_HT_0_self_296": {"default_fmt": "%6.4f", }, "n_HT_self_296": {"default_fmt": "%9.6f", }, + "gamma_HT_2_self_296": {"default_fmt": "%6.4f", }, + "delta_HT_0_self_296": {"default_fmt": "%9.6f", }, + "deltap_HT_self_296": {"default_fmt": "%9.6f", }, + "delta_HT_2_self_296": {"default_fmt": "%9.6f", }, + "gamma_HT_0_self_700": {"default_fmt": "%6.4f", }, "n_HT_self_700": {"default_fmt": "%9.6f", }, + "gamma_HT_2_self_700": {"default_fmt": "%6.4f", }, + "delta_HT_0_self_700": {"default_fmt": "%9.6f", }, + "deltap_HT_self_700": {"default_fmt": "%9.6f", }, + "delta_HT_2_self_700": {"default_fmt": "%9.6f", }, "nu_HT_self": {"default_fmt": "%6.4f", }, + "kappa_HT_self": {"default_fmt": "%9.6f", }, "eta_HT_self": {"default_fmt": "%9.6f", }, + "gamma_HT_0_air_50": {"default_fmt": "%6.4f", }, "n_HT_air_50": {"default_fmt": "%9.6f", }, + "gamma_HT_2_air_50": {"default_fmt": "%6.4f", }, + "delta_HT_0_air_50": {"default_fmt": "%9.6f", }, "deltap_HT_air_50": {"default_fmt": "%9.6f", }, + "delta_HT_2_air_50": {"default_fmt": "%9.6f", }, + "gamma_HT_0_air_150": {"default_fmt": "%6.4f", }, "n_HT_air_150": {"default_fmt": "%9.6f", }, + "gamma_HT_2_air_150": {"default_fmt": "%6.4f", }, + "delta_HT_0_air_150": {"default_fmt": "%9.6f", }, + "deltap_HT_air_150": {"default_fmt": "%9.6f", }, + "delta_HT_2_air_150": {"default_fmt": "%9.6f", }, + "gamma_HT_0_air_296": {"default_fmt": "%6.4f", }, "n_HT_air_296": {"default_fmt": "%9.6f", }, + "gamma_HT_2_air_296": {"default_fmt": "%6.4f", }, + "delta_HT_0_air_296": {"default_fmt": "%9.6f", }, + "deltap_HT_air_296": {"default_fmt": "%9.6f", }, + "delta_HT_2_air_296": {"default_fmt": "%9.6f", }, + "gamma_HT_0_air_700": {"default_fmt": "%6.4f", }, "n_HT_air_700": {"default_fmt": "%9.6f", }, + "gamma_HT_2_air_700": {"default_fmt": "%6.4f", }, + "delta_HT_0_air_700": {"default_fmt": "%9.6f", }, + "deltap_HT_air_700": {"default_fmt": "%9.6f", }, + "delta_HT_2_air_700": {"default_fmt": "%9.6f", }, "nu_HT_air": {"default_fmt": "%6.4f", }, + "kappa_HT_air": {"default_fmt": "%9.6f", }, "eta_HT_air": {"default_fmt": "%9.6f", }, } def transport2object(TransportData): @@ -1546,7 +1161,7 @@ def subsetOfRowObject(ParameterNames, RowObject): # if par_name in ParameterNames: # RowObjectNew.append((par_name,par_value,par_format)) # return RowObjectNew - dct = { } + dct = {} for par_name, par_value, par_format in RowObject: dct[par_name] = (par_name, par_value, par_format) RowObjectNew = [] @@ -1605,27 +1220,11 @@ def putRowObjectToString(RowObject): # Parameter nicknames are hard-coded. -PARAMETER_NICKNAMES = { - "a": "A", - "gamma_air": "gair", - "gp": "g", - "local_iso_id": "I", - "molec_id": "M", - "sw": "S", - "local_lower_quanta": "Q_", - "local_upper_quanta": "Q", - "gpp": "g_", - "elower": "E_", - "n_air": "nair", - "delta_air": "dair", - "global_upper_quanta": "V", - "iref": "Iref", - "line_mixing_flag": "f", - "ierr": "ierr", - "nu": "nu", - "gamma_self": "gsel", - "global_lower_quanta": "V_" - } +PARAMETER_NICKNAMES = {"a": "A", "gamma_air": "gair", "gp": "g", "local_iso_id": "I", + "molec_id": "M", "sw": "S", "local_lower_quanta": "Q_", "local_upper_quanta": "Q", + "gpp": "g_", "elower": "E_", "n_air": "nair", "delta_air": "dair", + "global_upper_quanta": "V", "iref": "Iref", "line_mixing_flag": "f", "ierr": "ierr", + "nu": "nu", "gamma_self": "gsel", "global_lower_quanta": "V_"} def putTableHeaderToString(TableName): @@ -1669,8 +1268,8 @@ def getRowObjectFromString(input_string, TableName): pos += lng # Do the same but now for extra (comma-separated) parameters if 'extra' in set(LOCAL_TABLE_CACHE[TableName]['header']): - csv_chunks = input_string.split(LOCAL_TABLE_CACHE[TableName]['header']. \ - get('extra_separator', ',')) + csv_chunks = input_string.split( + LOCAL_TABLE_CACHE[TableName]['header'].get('extra_separator', ',')) # Disregard the first "column-fixed" container if it presents: if LOCAL_TABLE_CACHE[TableName]['header'].get('order', []): pos = 1 @@ -1723,7 +1322,7 @@ def cache2storage(TableName): OutfileData.write(raw_string + '\n') # write table header TableHeader = getTableHeader(TableName) - OutfileHeader.write(json.dumps(TableHeader, indent = 2)) + OutfileHeader.write(json.dumps(TableHeader, indent=2)) def storage2cache(TableName): @@ -1738,9 +1337,9 @@ def storage2cache(TableName): print('HEADER:') print(header_text) raise Exception('Invalid header') - LOCAL_TABLE_CACHE[TableName] = { } + LOCAL_TABLE_CACHE[TableName] = {} LOCAL_TABLE_CACHE[TableName]['header'] = Header - LOCAL_TABLE_CACHE[TableName]['data'] = { } + LOCAL_TABLE_CACHE[TableName]['data'] = {} # Check if Header['order'] and Header['extra'] contain # parameters with same names, raise exception if true. intersct = set(Header.get('order', [])).intersection(set(Header.get('extra', []))) @@ -1748,8 +1347,8 @@ def storage2cache(TableName): raise Exception('Parameters with the same names: {}'.format(intersct)) # initialize empty data to avoid problems glob_order = []; - glob_format = { }; - glob_default = { } + glob_format = {}; + glob_default = {} if "order" in LOCAL_TABLE_CACHE[TableName]['header'].keys(): glob_order += LOCAL_TABLE_CACHE[TableName]['header']['order'] glob_format.update(LOCAL_TABLE_CACHE[TableName]['header']['format']) @@ -1806,7 +1405,7 @@ def getTableNamesFromStorage(StorageName): # See getFullTableAndHeaderName function for explanation def scanForNewParfiles(StorageName): file_names = listdir(StorageName) - headers = { } # without extensions! + headers = {} # without extensions! parfiles_without_header = [] for file_name in file_names: # create dictionary of unique headers @@ -1832,13 +1431,13 @@ def createHeader(TableName): fp = open(VARIABLES['BACKEND_DATABASE_NAME'] + '/' + fname, 'w') if os.path.isfile(TableName): raise Exception('File \"%s\" already exists!' % fname) - fp.write(json.dumps(HITRAN_DEFAULT_HEADER, indent = 2)) + fp.write(json.dumps(HITRAN_DEFAULT_HEADER, indent=2)) fp.close() def loadCache(): print('Using ' + VARIABLES['BACKEND_DATABASE_NAME'] + '\n') - LOCAL_TABLE_CACHE = { } # ????? + LOCAL_TABLE_CACHE = {} # ????? table_names = getTableNamesFromStorage(VARIABLES['BACKEND_DATABASE_NAME']) parfiles_without_header = scanForNewParfiles(VARIABLES['BACKEND_DATABASE_NAME']) # create headers for new parfiles @@ -1892,15 +1491,15 @@ def databaseCommit(): # necessary conditions for hitranonline: SAMPLE_CONDITIONS = ( -'AND', ('SET', 'internal_iso_id', [1, 2, 3, 4, 5, 6]), ('>=', 'nu', 0), ('<=', 'nu', 100)) + 'AND', ('SET', 'internal_iso_id', [1, 2, 3, 4, 5, 6]), ('>=', 'nu', 0), ('<=', 'nu', 100)) # sample hitranonline protocol # http://hitran.cloudapp.net/lbl/5?output_format_id=1&iso_ids_list=5&numin=0&numax=100&access=api # &key=e20e4bd3-e12c-4931-99e0-4c06e88536bd CONDITION_OPERATIONS = set( - ['AND', 'OR', 'NOT', 'RANGE', 'IN', '<', '>', '<=', '>=', '==', '!=', 'LIKE', 'STR', '+', - '-', '*', '/', 'MATCH', 'SEARCH', 'FINDALL']) + ['AND', 'OR', 'NOT', 'RANGE', 'IN', '<', '>', '<=', '>=', '==', '!=', 'LIKE', 'STR', '+', '-', + '*', '/', 'MATCH', 'SEARCH', 'FINDALL']) # Operations used in Condition verification @@ -2066,7 +1665,7 @@ def operationLIST(args): # GROUPING ---------------------------------------------- -GROUP_INDEX = { } +GROUP_INDEX = {} # GROUP_INDEX has the following structure: # GROUP_INDEX[KEY] = VALUE # KEY = table line values @@ -2075,15 +1674,8 @@ def operationLIST(args): # FUNC_NAME = {'FLAG':LOGICAL,'NAME':STRING} # name and default value -GROUP_FUNCTION_NAMES = { - 'COUNT': 0, - 'SUM': 0, - 'MUL': 1, - 'AVG': 0, - 'MIN': +1e100, - 'MAX': -1e100, - 'SSQ': 0, - } +GROUP_FUNCTION_NAMES = {'COUNT': 0, 'SUM': 0, 'MUL': 1, 'AVG': 0, 'MIN': +1e100, 'MAX': -1e100, + 'SSQ': 0, } def clearGroupIndex(): @@ -2100,10 +1692,10 @@ def getValueFromGroupIndex(GroupIndexKey, FunctionName): if not GroupIndexKey: return GROUP_FUNCTION_NAMES[FunctionName] if FunctionName not in GROUP_INDEX[GroupIndexKey]['FUNCTIONS']: - GROUP_INDEX[GroupIndexKey]['FUNCTIONS'][FunctionName] = { } + GROUP_INDEX[GroupIndexKey]['FUNCTIONS'][FunctionName] = {} GROUP_INDEX[GroupIndexKey]['FUNCTIONS'][FunctionName]['FLAG'] = True - GROUP_INDEX[GroupIndexKey]['FUNCTIONS'][FunctionName]['VALUE'] = \ - GROUP_FUNCTION_NAMES[FunctionName] + GROUP_INDEX[GroupIndexKey]['FUNCTIONS'][FunctionName]['VALUE'] = GROUP_FUNCTION_NAMES[ + FunctionName] return GROUP_INDEX[GroupIndexKey]['FUNCTIONS'][FunctionName]['VALUE'] @@ -2114,8 +1706,8 @@ def setValueToGroupIndex(GroupIndexKey, FunctionName, Value): def initializeGroup(GroupIndexKey): if GroupIndexKey not in GROUP_INDEX: print('GROUP_DESC[COUNT]=' + str(GROUP_DESC['COUNT'])) - GROUP_INDEX[GroupIndexKey] = { } - GROUP_INDEX[GroupIndexKey]['FUNCTIONS'] = { } + GROUP_INDEX[GroupIndexKey] = {} + GROUP_INDEX[GroupIndexKey]['FUNCTIONS'] = {} GROUP_INDEX[GroupIndexKey]['ROWID'] = len(GROUP_INDEX) - 1 for FunctionName in GROUP_FUNCTION_NAMES: # initialize function flags (UpdateFlag) @@ -2159,76 +1751,47 @@ def groupSSQ(): pass -OPERATORS = { \ - # List - 'LIST': lambda args: operationLIST(args), - # And - '&': lambda args: operationAND(args), - '&&': lambda args: operationAND(args), - 'AND': lambda args: operationAND(args), - # Or - '|': lambda args: operationOR(args), - '||': lambda args: operationOR(args), - 'OR': lambda args: operationOR(args), - # Not - '!': lambda args: operationNOT(args[0]), - 'NOT': lambda args: operationNOT(args[0]), +OPERATORS = {# List + 'LIST': lambda args: operationLIST(args), # And + '&': lambda args: operationAND(args), '&&': lambda args: operationAND(args), + 'AND': lambda args: operationAND(args), # Or + '|': lambda args: operationOR(args), '||': lambda args: operationOR(args), + 'OR': lambda args: operationOR(args), # Not + '!': lambda args: operationNOT(args[0]), 'NOT': lambda args: operationNOT(args[0]), # Between 'RANGE': lambda args: operationRANGE(args[0], args[1], args[2]), - 'BETWEEN': lambda args: operationRANGE(args[0], args[1], args[2]), - # Subset + 'BETWEEN': lambda args: operationRANGE(args[0], args[1], args[2]), # Subset 'IN': lambda args: operationSUBSET(args[0], args[1]), - 'SUBSET': lambda args: operationSUBSET(args[0], args[1]), - # Less - '<': lambda args: operationLESS(args), - 'LESS': lambda args: operationLESS(args), - 'LT': lambda args: operationLESS(args), - # More - '>': lambda args: operationMORE(args), - 'MORE': lambda args: operationMORE(args), - 'MT': lambda args: operationMORE(args), - # Less or equal + 'SUBSET': lambda args: operationSUBSET(args[0], args[1]), # Less + '<': lambda args: operationLESS(args), 'LESS': lambda args: operationLESS(args), + 'LT': lambda args: operationLESS(args), # More + '>': lambda args: operationMORE(args), 'MORE': lambda args: operationMORE(args), + 'MT': lambda args: operationMORE(args), # Less or equal '<=': lambda args: operationLESSOREQUAL(args), 'LESSOREQUAL': lambda args: operationLESSOREQUAL(args), - 'LTE': lambda args: operationLESSOREQUAL(args), - # More or equal + 'LTE': lambda args: operationLESSOREQUAL(args), # More or equal '>=': lambda args: operationMOREOREQUAL(args), 'MOREOREQUAL': lambda args: operationMOREOREQUAL(args), - 'MTE': lambda args: operationMOREOREQUAL(args), - # Equal - '=': lambda args: operationEQUAL(args), - '==': lambda args: operationEQUAL(args), - 'EQ': lambda args: operationEQUAL(args), - 'EQUAL': lambda args: operationEQUAL(args), - 'EQUALS': lambda args: operationEQUAL(args), - # Not equal + 'MTE': lambda args: operationMOREOREQUAL(args), # Equal + '=': lambda args: operationEQUAL(args), '==': lambda args: operationEQUAL(args), + 'EQ': lambda args: operationEQUAL(args), 'EQUAL': lambda args: operationEQUAL(args), + 'EQUALS': lambda args: operationEQUAL(args), # Not equal '!=': lambda args: operationNOTEQUAL(args[0], args[1]), '<>': lambda args: operationNOTEQUAL(args[0], args[1]), '~=': lambda args: operationNOTEQUAL(args[0], args[1]), 'NE': lambda args: operationNOTEQUAL(args[0], args[1]), - 'NOTEQUAL': lambda args: operationNOTEQUAL(args[0], args[1]), - # Plus - '+': lambda args: operationSUM(args), - 'SUM': lambda args: operationSUM(args), - # Minus + 'NOTEQUAL': lambda args: operationNOTEQUAL(args[0], args[1]), # Plus + '+': lambda args: operationSUM(args), 'SUM': lambda args: operationSUM(args), # Minus '-': lambda args: operationDIFF(args[0], args[1]), - 'DIFF': lambda args: operationDIFF(args[0], args[1]), - # Mul - '*': lambda args: operationMUL(args), - 'MUL': lambda args: operationMUL(args), - # Div + 'DIFF': lambda args: operationDIFF(args[0], args[1]), # Mul + '*': lambda args: operationMUL(args), 'MUL': lambda args: operationMUL(args), # Div '/': lambda args: operationDIV(args[0], args[1]), - 'DIV': lambda args: operationDIV(args[0], args[1]), - # Regexp match + 'DIV': lambda args: operationDIV(args[0], args[1]), # Regexp match 'MATCH': lambda args: operationMATCH(args[0], args[1]), - 'LIKE': lambda args: operationMATCH(args[0], args[1]), - # Regexp search - 'SEARCH': lambda args: operationSEARCH(args[0], args[1]), - # Regexp findal - 'FINDALL': lambda args: operationFINDALL(args[0], args[1]), - # Group count - 'COUNT': lambda args: groupCOUNT(GroupIndexKey), - } + 'LIKE': lambda args: operationMATCH(args[0], args[1]), # Regexp search + 'SEARCH': lambda args: operationSEARCH(args[0], args[1]), # Regexp findal + 'FINDALL': lambda args: operationFINDALL(args[0], args[1]), # Group count + 'COUNT': lambda args: groupCOUNT(GroupIndexKey), } # new evaluateExpression function, # accounting for groups @@ -2342,7 +1905,7 @@ def evaluateExpression(root, VarDictionary, GroupIndexKey=None): def getVarDictionary(RowObject): # get VarDict from RowObject # VarDict: par_name => par_value - VarDictionary = { } + VarDictionary = {} for par_name, par_value, par_format in RowObject: VarDictionary[par_name] = par_value return VarDictionary @@ -2405,7 +1968,7 @@ def evaluateExpressionPAR(ParameterNames, VarDictionary=None): def getContextFormat(RowObject): # Get context format from the whole RowObject - ContextFormat = { } + ContextFormat = {} for par_name, par_value, par_format in RowObject: ContextFormat[par_name] = par_format return ContextFormat @@ -2550,18 +2113,18 @@ def outputTable(TableName, Conditions=None, File=None, Header=True): # Create table "prototype-based" way def createTable(TableName, RowObjectDefault): # create a Table based on a RowObjectDefault - LOCAL_TABLE_CACHE[TableName] = { } + LOCAL_TABLE_CACHE[TableName] = {} header_order = [] - header_format = { } - header_default = { } - data = { } + header_format = {} + header_default = {} + data = {} for par_name, par_value, par_format in RowObjectDefault: header_order.append(par_name) header_format[par_name] = par_format header_default[par_name] = par_value data[par_name] = [] # header_order = tuple(header_order) # XXX ? - LOCAL_TABLE_CACHE[TableName]['header'] = { } + LOCAL_TABLE_CACHE[TableName]['header'] = {} LOCAL_TABLE_CACHE[TableName]['header']['order'] = header_order LOCAL_TABLE_CACHE[TableName]['header']['format'] = header_format LOCAL_TABLE_CACHE[TableName]['header']['default'] = header_default @@ -2787,7 +2350,7 @@ def select(TableName, DestinationTableName=QUERY_BUFFER, ParameterNames=None, Co raise Exception('%s: no such table. Check tableList() for more info.' % TableName) if not ParameterNames: ParameterNames = LOCAL_TABLE_CACHE[TableName]['header']['order'] - LOCAL_TABLE_CACHE[DestinationTableName] = { } # clear QUERY_BUFFER for the new result + LOCAL_TABLE_CACHE[DestinationTableName] = {} # clear QUERY_BUFFER for the new result RowObjectDefault = getDefaultRowObject(TableName) VarDictionary = getVarDictionary(RowObjectDefault) ContextFormat = getContextFormat(RowObjectDefault) @@ -2798,9 +2361,9 @@ def select(TableName, DestinationTableName=QUERY_BUFFER, ParameterNames=None, Co selectInto(DestinationTableName, TableName, ParameterNames, Conditions) if DestinationTableName != QUERY_BUFFER: if File: - outputTable(DestinationTableName, File = File) + outputTable(DestinationTableName, File=File) elif Output: - outputTable(DestinationTableName, File = File) + outputTable(DestinationTableName, File=File) # SORTING =========================================================== @@ -2814,7 +2377,7 @@ def arrangeTable(TableName, DestinationTableName=None, RowIDList=None): if DestinationTableName != TableName: dropTable(DestinationTableName) LOCAL_TABLE_CACHE[DestinationTableName]['header'] = LOCAL_TABLE_CACHE[TableName]['header'] - LOCAL_TABLE_CACHE[DestinationTableName]['data'] = { } + LOCAL_TABLE_CACHE[DestinationTableName]['data'] = {} LOCAL_TABLE_CACHE[DestinationTableName]['header']['number_of_rows'] = len(RowIDList) # print 'AT: RowIDList = '+str(RowIDList) for par_name in LOCAL_TABLE_CACHE[DestinationTableName]['header']['order']: @@ -2911,7 +2474,7 @@ def sort(TableName, DestinationTableName=None, ParameterNames=None, Accending=Tr index_sorted = quickSort(index, TableName, ParameterNames, Accending) arrangeTable(TableName, DestinationTableName, index_sorted) if Output: - outputTable(DestinationTableName, File = File) + outputTable(DestinationTableName, File=File) # /SORTING ========================================================== @@ -3002,7 +2565,7 @@ def group(TableName, DestinationTableName=QUERY_BUFFER, ParameterNames=None, setRowObject(RowIDGroup, RowObjectNew, DestinationTableName) # Output result if required if Output and DestinationTableName == QUERY_BUFFER: - outputTable(DestinationTableName, File = File) + outputTable(DestinationTableName, File=File) # /GROUPING ========================================================= @@ -3184,8 +2747,8 @@ def mergeParlist(*arg): # Define parameter groups to simplify the usage of fetch_ PARLIST_DOTPAR = ['par_line', ] PARLIST_ID = ['trans_id', ] -PARLIST_STANDARD = ['molec_id', 'local_iso_id', 'nu', 'sw', 'a', 'elower', 'gamma_air', - 'delta_air', 'gamma_self', 'n_air', 'n_self', 'gp', 'gpp'] +PARLIST_STANDARD = ['molec_id', 'local_iso_id', 'nu', 'sw', 'a', 'elower', 'gamma_air', 'delta_air', + 'gamma_self', 'n_air', 'n_self', 'gp', 'gpp'] PARLIST_LABELS = ['statep', 'statepp'] PARLIST_LINEMIXING = ['y_air', 'y_self'] @@ -3194,37 +2757,34 @@ def mergeParlist(*arg): PARLIST_VOIGT_H2 = ['gamma_H2', 'delta_H2', 'deltap_H2', 'n_H2'] PARLIST_VOIGT_CO2 = ['gamma_CO2', 'delta_CO2', 'n_CO2'] PARLIST_VOIGT_HE = ['gamma_He', 'delta_He', 'n_He'] -PARLIST_VOIGT_ALL = mergeParlist(PARLIST_VOIGT_AIR, PARLIST_VOIGT_SELF, - PARLIST_VOIGT_H2, PARLIST_VOIGT_CO2, - PARLIST_VOIGT_HE) +PARLIST_VOIGT_ALL = mergeParlist(PARLIST_VOIGT_AIR, PARLIST_VOIGT_SELF, PARLIST_VOIGT_H2, + PARLIST_VOIGT_CO2, PARLIST_VOIGT_HE) PARLIST_SDVOIGT_AIR = ['gamma_air', 'delta_air', 'deltap_air', 'n_air', 'SD_air'] PARLIST_SDVOIGT_SELF = ['gamma_self', 'delta_self', 'deltap_self', 'n_self', 'SD_self'] PARLIST_SDVOIGT_H2 = [] PARLIST_SDVOIGT_CO2 = [] PARLIST_SDVOIGT_HE = [] -PARLIST_SDVOIGT_ALL = mergeParlist(PARLIST_SDVOIGT_AIR, PARLIST_SDVOIGT_SELF, - PARLIST_SDVOIGT_H2, PARLIST_SDVOIGT_CO2, - PARLIST_SDVOIGT_HE) +PARLIST_SDVOIGT_ALL = mergeParlist(PARLIST_SDVOIGT_AIR, PARLIST_SDVOIGT_SELF, PARLIST_SDVOIGT_H2, + PARLIST_SDVOIGT_CO2, PARLIST_SDVOIGT_HE) PARLIST_GALATRY_AIR = ['gamma_air', 'delta_air', 'deltap_air', 'n_air', 'beta_g_air'] PARLIST_GALATRY_SELF = ['gamma_self', 'delta_self', 'deltap_self', 'n_self', 'beta_g_self'] PARLIST_GALATRY_H2 = [] PARLIST_GALATRY_CO2 = [] PARLIST_GALATRY_HE = [] -PARLIST_GALATRY_ALL = mergeParlist(PARLIST_GALATRY_AIR, PARLIST_GALATRY_SELF, - PARLIST_GALATRY_H2, PARLIST_GALATRY_CO2, - PARLIST_GALATRY_HE) - -PARLIST_HT_SELF = ['gamma_HT_0_self_50', 'n_HT_self_50', 'gamma_HT_2_self_50', - 'delta_HT_0_self_50', 'deltap_HT_self_50', 'delta_HT_2_self_50', - 'gamma_HT_0_self_150', 'n_HT_self_150', 'gamma_HT_2_self_150', - 'delta_HT_0_self_150', 'deltap_HT_self_150', 'delta_HT_2_self_150', - 'gamma_HT_0_self_296', 'n_HT_self_296', 'gamma_HT_2_self_296', - 'delta_HT_0_self_296', 'deltap_HT_self_296', 'delta_HT_2_self_296', - 'gamma_HT_0_self_700', 'n_HT_self_700', 'gamma_HT_2_self_700', - 'delta_HT_0_self_700', 'deltap_HT_self_700', 'delta_HT_2_self_700', - 'nu_HT_self', 'kappa_HT_self', 'eta_HT_self'] +PARLIST_GALATRY_ALL = mergeParlist(PARLIST_GALATRY_AIR, PARLIST_GALATRY_SELF, PARLIST_GALATRY_H2, + PARLIST_GALATRY_CO2, PARLIST_GALATRY_HE) + +PARLIST_HT_SELF = ['gamma_HT_0_self_50', 'n_HT_self_50', 'gamma_HT_2_self_50', 'delta_HT_0_self_50', + 'deltap_HT_self_50', 'delta_HT_2_self_50', 'gamma_HT_0_self_150', + 'n_HT_self_150', 'gamma_HT_2_self_150', 'delta_HT_0_self_150', + 'deltap_HT_self_150', 'delta_HT_2_self_150', 'gamma_HT_0_self_296', + 'n_HT_self_296', 'gamma_HT_2_self_296', 'delta_HT_0_self_296', + 'deltap_HT_self_296', 'delta_HT_2_self_296', 'gamma_HT_0_self_700', + 'n_HT_self_700', 'gamma_HT_2_self_700', 'delta_HT_0_self_700', + 'deltap_HT_self_700', 'delta_HT_2_self_700', 'nu_HT_self', 'kappa_HT_self', + 'eta_HT_self'] # PARLIST_HT_AIR = ['gamma_HT_0_air_50','n_HT_air_50','gamma_HT_2_air_50', # 'delta_HT_0_air_50','deltap_HT_air_50','delta_HT_2_air_50', # 'gamma_HT_0_air_150','n_HT_air_150','gamma_HT_2_air_150', @@ -3234,44 +2794,27 @@ def mergeParlist(*arg): # 'gamma_HT_0_air_700','n_HT_air_700','gamma_HT_2_air_700', # 'delta_HT_0_air_700','deltap_HT_air_700','delta_HT_2_air_700', # 'nu_HT_air','kappa_HT_air','eta_HT_air'] -PARLIST_HT_AIR = ['gamma_HT_0_air_296', 'n_HT_air_296', 'gamma_HT_2_air_296', - 'delta_HT_0_air_296', 'deltap_HT_air_296', 'delta_HT_2_air_296', - 'nu_HT_air', 'kappa_HT_air', 'eta_HT_air'] +PARLIST_HT_AIR = ['gamma_HT_0_air_296', 'n_HT_air_296', 'gamma_HT_2_air_296', 'delta_HT_0_air_296', + 'deltap_HT_air_296', 'delta_HT_2_air_296', 'nu_HT_air', 'kappa_HT_air', + 'eta_HT_air'] PARLIST_HT_ALL = mergeParlist(PARLIST_HT_SELF, PARLIST_HT_AIR) -PARLIST_ALL = mergeParlist(PARLIST_ID, PARLIST_DOTPAR, PARLIST_STANDARD, - PARLIST_LABELS, PARLIST_LINEMIXING, PARLIST_VOIGT_ALL, - PARLIST_SDVOIGT_ALL, PARLIST_GALATRY_ALL, PARLIST_HT_ALL) - -PARAMETER_GROUPS = { - 'par_line': PARLIST_DOTPAR, - '160-char': PARLIST_DOTPAR, - '.par': PARLIST_DOTPAR, - 'id': PARLIST_ID, - 'standard': PARLIST_STANDARD, - 'labels': PARLIST_LABELS, - 'linemixing': PARLIST_LINEMIXING, - 'voigt_air': PARLIST_VOIGT_AIR, - 'voigt_self': PARLIST_VOIGT_SELF, - 'voigt_h2': PARLIST_VOIGT_H2, - 'voigt_co2': PARLIST_VOIGT_CO2, - 'voigt_he': PARLIST_VOIGT_HE, - 'voigt': PARLIST_VOIGT_ALL, - 'sdvoigt_air': PARLIST_SDVOIGT_AIR, - 'sdvoigt_self': PARLIST_SDVOIGT_SELF, - 'sdvoigt_h2': PARLIST_SDVOIGT_H2, - 'sdvoigt_co2': PARLIST_SDVOIGT_CO2, - 'sdvoigt_he': PARLIST_SDVOIGT_HE, - 'sdvoigt': PARLIST_SDVOIGT_ALL, - 'galatry_air': PARLIST_GALATRY_AIR, - 'galatry_self': PARLIST_GALATRY_SELF, - 'galatry_h2': PARLIST_GALATRY_H2, - 'galatry_co2': PARLIST_GALATRY_CO2, - 'galatry_he': PARLIST_GALATRY_HE, - 'galatry': PARLIST_GALATRY_ALL, - 'ht': PARLIST_HT_ALL, - 'all': PARLIST_ALL - } +PARLIST_ALL = mergeParlist(PARLIST_ID, PARLIST_DOTPAR, PARLIST_STANDARD, PARLIST_LABELS, + PARLIST_LINEMIXING, PARLIST_VOIGT_ALL, PARLIST_SDVOIGT_ALL, + PARLIST_GALATRY_ALL, PARLIST_HT_ALL) + +PARAMETER_GROUPS = {'par_line': PARLIST_DOTPAR, '160-char': PARLIST_DOTPAR, '.par': PARLIST_DOTPAR, + 'id': PARLIST_ID, 'standard': PARLIST_STANDARD, 'labels': PARLIST_LABELS, + 'linemixing': PARLIST_LINEMIXING, 'voigt_air': PARLIST_VOIGT_AIR, + 'voigt_self': PARLIST_VOIGT_SELF, 'voigt_h2': PARLIST_VOIGT_H2, + 'voigt_co2': PARLIST_VOIGT_CO2, 'voigt_he': PARLIST_VOIGT_HE, + 'voigt': PARLIST_VOIGT_ALL, 'sdvoigt_air': PARLIST_SDVOIGT_AIR, + 'sdvoigt_self': PARLIST_SDVOIGT_SELF, 'sdvoigt_h2': PARLIST_SDVOIGT_H2, + 'sdvoigt_co2': PARLIST_SDVOIGT_CO2, 'sdvoigt_he': PARLIST_SDVOIGT_HE, + 'sdvoigt': PARLIST_SDVOIGT_ALL, 'galatry_air': PARLIST_GALATRY_AIR, + 'galatry_self': PARLIST_GALATRY_SELF, 'galatry_h2': PARLIST_GALATRY_H2, + 'galatry_co2': PARLIST_GALATRY_CO2, 'galatry_he': PARLIST_GALATRY_HE, + 'galatry': PARLIST_GALATRY_ALL, 'ht': PARLIST_HT_ALL, 'all': PARLIST_ALL} def prepareParlist(pargroups=[], params=[], dotpar=True): @@ -3282,7 +2825,7 @@ def prepareParlist(pargroups=[], params=[], dotpar=True): # parlist_default += PARAMETER_GROUPS['id'] # Make a dictionary of "assumed" parameters. - ASSUMED_PARAMS = { } + ASSUMED_PARAMS = {} if 'par_line' in set(parlist_default): ASSUMED_PARAMS = HITRAN_DEFAULT_HEADER['format'] @@ -3309,11 +2852,8 @@ def prepareParlist(pargroups=[], params=[], dotpar=True): def prepareHeader(parlist): - HEADER = { - 'table_name': '', 'number_of_rows': -1, 'format': { }, - 'default': { }, 'table_type': 'column-fixed', - 'size_in_bytes': -1, 'order': [], 'description': { } - } + HEADER = {'table_name': '', 'number_of_rows': -1, 'format': {}, 'default': {}, + 'table_type': 'column-fixed', 'size_in_bytes': -1, 'order': [], 'description': {}} # Add column-fixed 160-character part, if specified in parlist. if 'par_line' in set(parlist): @@ -3325,7 +2865,7 @@ def prepareHeader(parlist): # Insert all other parameters in the "extra" section of the header. plist = [v for v in parlist if v != 'par_line'] HEADER['extra'] = [] - HEADER['extra_format'] = { } + HEADER['extra_format'] = {} HEADER['extra_separator'] = ',' for param in plist: # param = param.lower() @@ -3337,7 +2877,7 @@ def prepareHeader(parlist): def queryHITRAN(TableName, iso_id_list, numin, numax, pargroups=[], params=[], dotpar=True, head=False): - ParameterList = prepareParlist(pargroups = pargroups, params = params, dotpar = dotpar) + ParameterList = prepareParlist(pargroups=pargroups, params=params, dotpar=dotpar) TableHeader = prepareHeader(ParameterList) TableHeader['table_name'] = TableName DataFileName = VARIABLES['BACKEND_DATABASE_NAME'] + '/' + TableName + '.data' @@ -3347,18 +2887,16 @@ def queryHITRAN(TableName, iso_id_list, numin, numax, pargroups=[], params=[], d iso_id_list_str = ','.join(iso_id_list_str) print('\nData is fetched from %s\n' % VARIABLES['GLOBAL_HOST']) if pargroups or params: # custom par search - url = VARIABLES['GLOBAL_HOST'] + '/lbl/api?' + \ - 'iso_ids_list=' + iso_id_list_str + '&' + \ - 'numin=' + str(numin) + '&' + \ - 'numax=' + str(numax) + '&' + \ - 'head=' + str(head) + '&' + \ - 'fixwidth=0&sep=[comma]&' + \ - 'request_params=' + ','.join(ParameterList) + url = VARIABLES[ + 'GLOBAL_HOST'] + '/lbl/api?' + 'iso_ids_list=' + iso_id_list_str + '&' + \ + 'numin=' + str( + numin) + '&' + 'numax=' + str(numax) + '&' + 'head=' + str( + head) + '&' + 'fixwidth=0&sep=[comma]&' + 'request_params=' + ','.join(ParameterList) else: # old-fashioned .par search - url = VARIABLES['GLOBAL_HOST'] + '/lbl/api?' + \ - 'iso_ids_list=' + iso_id_list_str + '&' + \ - 'numin=' + str(numin) + '&' + \ - 'numax=' + str(numax) + url = VARIABLES[ + 'GLOBAL_HOST'] + '/lbl/api?' + 'iso_ids_list=' + iso_id_list_str + '&' + \ + 'numin=' + str( + numin) + '&' + 'numax=' + str(numax) # raise Exception(url) # Download data by chunks. if VARIABLES['DISPLAY_FETCH_URL']: @@ -3380,7 +2918,7 @@ def queryHITRAN(TableName, iso_id_list, numin, numax, pargroups=[], params=[], d fp.write(chunk.decode('utf-8')) print(' %d bytes written to %s' % (CHUNK, DataFileName)) with open(HeaderFileName, 'w') as fp: - fp.write(json.dumps(TableHeader, indent = 2)) + fp.write(json.dumps(TableHeader, indent=2)) print('Header written to %s' % HeaderFileName) print('END DOWNLOAD') # Set comment @@ -3444,21 +2982,16 @@ def getLinelist(local_name, query, api_key): # ---------------- FILTER --------------------------------------------- def filter(TableName, Conditions): - select(TableName = TableName, Conditions = Conditions, Output = False) + select(TableName=TableName, Conditions=Conditions, Output=False) # ---------------------- ISO.PY --------------------------------------- ISO_ID_INDEX = { - 'M': 0, - 'I': 1, - 'iso_name': 2, - 'abundance': 3, - 'mass': 4, - 'mol_name': 5 + 'M': 0, 'I': 1, 'iso_name': 2, 'abundance': 3, 'mass': 4, 'mol_name': 5 - } +} # id M I iso_name abundance mass mol_name @@ -3576,28 +3109,21 @@ def filter(TableName, Conditions): 96: [42, 1, '(12C)(19F)4', 0.9893, 87.993616, 'CF4'], 116: [43, 1, '(12C)4H2', 0.955998, 50.01565, 'C4H2'], 109: [44, 1, 'H(12C)3(14N)', 0.9646069, 51.01089903687, 'HC3N'], - 103: [45, 1, 'H2', 0.999688, 2.01565, 'H2'], - 115: [45, 2, 'HD', 0.00022997, 3.021825, 'H2'], + 103: [45, 1, 'H2', 0.999688, 2.01565, 'H2'], 115: [45, 2, 'HD', 0.00022997, 3.021825, 'H2'], 97: [46, 1, '(12C)(32S)', 0.939624, 43.971036, 'CS'], 98: [46, 2, '(12C)(34S)', 0.0416817, 45.966787, 'CS'], 99: [46, 3, '(13C)(32S)', 0.0105565, 44.974368, 'CS'], 100: [46, 4, '(12C)(33S)', 0.00741668, 44.970399, 'CS'], - 114: [47, 1, '(32S)(16O)3', 0.9423964, 79.95682, 'SO3'], - 101: [1001, 1, 'H', None, None, 'H'], - 102: [1002, 1, 'He', None, None, 'He'], - 104: [1018, 1, 'Ar', None, None, 'Ar'], + 114: [47, 1, '(32S)(16O)3', 0.9423964, 79.95682, 'SO3'], 101: [1001, 1, 'H', None, None, 'H'], + 102: [1002, 1, 'He', None, None, 'He'], 104: [1018, 1, 'Ar', None, None, 'Ar'], - } +} ISO_INDEX = { - 'id': 0, - 'iso_name': 1, - 'abundance': 2, - 'mass': 3, - 'mol_name': 4 + 'id': 0, 'iso_name': 1, 'abundance': 2, 'mass': 3, 'mol_name': 4 - } +} # M I id iso_name abundance mass # mol_name @@ -3723,11 +3249,10 @@ def filter(TableName, Conditions): (46, 3): [99, '(13C)(32S)', 0.0105565, 44.974368, 'CS'], (46, 4): [100, '(12C)(33S)', 0.00741668, 44.970399, 'CS'], (47, 1): [114, '(32S)(16O)3', 0.9423964, 79.95682, 'SO3'], - (1001, 1): [101, 'H', None, None, 'H'], - (1002, 1): [102, 'He', None, None, 'He'], + (1001, 1): [101, 'H', None, None, 'H'], (1002, 1): [102, 'He', None, None, 'He'], (1018, 1): [104, 'Ar', None, None, 'Ar'], - } +} def print_iso(): @@ -3739,25 +3264,23 @@ def print_iso(): ab = ab if ab else -1 ma = ma if ma else -1 print('%4i %4i : %5i %25s %10f %10f %15s' % ( - i[0], i[1], ISO[i][ISO_INDEX['id']], ISO[i][ISO_INDEX['iso_name']], ab, ma, - ISO[i][ISO_INDEX['mol_name']])) + i[0], i[1], ISO[i][ISO_INDEX['id']], ISO[i][ISO_INDEX['iso_name']], ab, ma, + ISO[i][ISO_INDEX['mol_name']])) def print_iso_id(): - print( - 'The dictionary \"ISO_ID\" contains information on \"global\" IDs of isotopologues in ' - 'HITRAN\n') - print( - ' id M I iso_name abundance mass ' - 'mol_name') + print('The dictionary \"ISO_ID\" contains information on \"global\" IDs of isotopologues in ' + 'HITRAN\n') + print(' id M I iso_name abundance mass ' + 'mol_name') for i in ISO_ID: ab = ISO_ID[i][ISO_ID_INDEX['abundance']] ma = ISO_ID[i][ISO_ID_INDEX['mass']] ab = ab if ab else -1 ma = ma if ma else -1 print('%5i : %4i %4i %25s %15.10f %10f %15s' % ( - i, ISO_ID[i][ISO_ID_INDEX['M']], ISO_ID[i][ISO_ID_INDEX['I']], - ISO_ID[i][ISO_ID_INDEX['iso_name']], ab, ma, ISO_ID[i][ISO_ID_INDEX['mol_name']])) + i, ISO_ID[i][ISO_ID_INDEX['M']], ISO_ID[i][ISO_ID_INDEX['I']], + ISO_ID[i][ISO_ID_INDEX['iso_name']], ab, ma, ISO_ID[i][ISO_ID_INDEX['mol_name']])) profiles = 'profiles' @@ -3794,8 +3317,7 @@ def print_slit_functions(): plotting = 'plotting' python = 'python' -python_tutorial_text = \ - """ +python_tutorial_text = """ THIS TUTORIAL IS TAKEN FROM http://www.stavros.io/tutorials/python/ AUTHOR: Stavros Korokithakis @@ -4270,8 +3792,7 @@ def print_python_tutorial(): pydoc.pager(python_tutorial_text) -data_tutorial_text = \ - """ +data_tutorial_text = """ ACCESS YOUR DATA! @@ -4646,8 +4167,7 @@ def print_data_tutorial(): pydoc.pager(data_tutorial_text) -spectra_tutorial_text = \ - """ +spectra_tutorial_text = """ CALCULATE YOUR SPECTRA! @@ -5151,8 +4671,7 @@ def print_spectra_tutorial(): pydoc.pager(spectra_tutorial_text) -plotting_tutorial_text = \ - """ +plotting_tutorial_text = """ PLOTTING THE SPECTRA WITH MATPLOTLIB @@ -5548,8 +5067,7 @@ def fetch_by_ids(TableName, iso_id_list, numin, numax, ParameterGroups=[], Param """ if type(iso_id_list) not in set([list, tuple]): iso_id_list = [iso_id_list] - queryHITRAN(TableName, iso_id_list, numin, numax, - pargroups = ParameterGroups, params = Parameters) + queryHITRAN(TableName, iso_id_list, numin, numax, pargroups=ParameterGroups, params=Parameters) iso_names = [ISO_ID[i][ISO_ID_INDEX['iso_name']] for i in iso_id_list] Comment = 'Contains lines for ' + ','.join(iso_names) Comment += ('\n in %.3f-%.3f wavenumber range' % (numin, numax)) @@ -5580,8 +5098,8 @@ def fetch(TableName, M, I, numin, numax, ParameterGroups=[], Parameters=[]): fetch('HOH',1,1,4000,4100) --- """ - queryHITRAN(TableName, [ISO[(M, I)][ISO_INDEX['id']]], numin, numax, - pargroups = ParameterGroups, params = Parameters) + queryHITRAN(TableName, [ISO[(M, I)][ISO_INDEX['id']]], numin, numax, pargroups=ParameterGroups, + params=Parameters) iso_name = ISO[(M, I)][ISO_INDEX['iso_name']] Comment = 'Contains lines for ' + iso_name Comment += ('\n in %.3f-%.3f wavenumber range' % (numin, numax)) @@ -5695,27 +5213,24 @@ def AtoB(aa, A, B, npt): # --------------- ISOTOPOLOGUE HASH ---------------------- -TIPS_ISO_HASH = { } +TIPS_ISO_HASH = {} # --------------- STATISTICAL WEIGHT HASH ---------------------- -TIPS_GSI_HASH = { } +TIPS_GSI_HASH = {} # --------------- INTERPOLATION NODES ---------------------- -Tdat = __FloatType__([60., 85., 110., 135., 160., 185., 210., 235., - 260., 285., 310., 335., 360., 385., 410., 435., 460., 485., - 510., 535., 560., 585., 610., 635., 660., 685., 710., 735., - 760., 785., 810., 835., 860., 885., 910., 935., 960., 985., - 1010., 1035., 1060., 1085., 1110., 1135., 1160., 1185., 1210., 1235., - 1260., 1285., 1310., 1335., 1360., 1385., 1410., 1435., 1460., 1485., - 1510., 1535., 1560., 1585., 1610., 1635., 1660., 1685., 1710., 1735., - 1760., 1785., 1810., 1835., 1860., 1885., 1910., 1935., 1960., 1985., - 2010., 2035., 2060., 2085., 2110., 2135., 2160., 2185., 2210., 2235., - 2260., 2285., 2310., 2335., 2360., 2385., 2410., 2435., 2460., 2485., - 2510., 2535., 2560., 2585., 2610., 2635., 2660., 2685., 2710., 2735., - 2760., 2785., 2810., 2835., 2860., 2885., 2910., 2935., 2960., 2985., - 3010.]) +Tdat = __FloatType__( + [60., 85., 110., 135., 160., 185., 210., 235., 260., 285., 310., 335., 360., 385., 410., 435., + 460., 485., 510., 535., 560., 585., 610., 635., 660., 685., 710., 735., 760., 785., 810., 835., + 860., 885., 910., 935., 960., 985., 1010., 1035., 1060., 1085., 1110., 1135., 1160., 1185., + 1210., 1235., 1260., 1285., 1310., 1335., 1360., 1385., 1410., 1435., 1460., 1485., 1510., + 1535., 1560., 1585., 1610., 1635., 1660., 1685., 1710., 1735., 1760., 1785., 1810., 1835., + 1860., 1885., 1910., 1935., 1960., 1985., 2010., 2035., 2060., 2085., 2110., 2135., 2160., + 2185., 2210., 2235., 2260., 2285., 2310., 2335., 2360., 2385., 2410., 2435., 2460., 2485., + 2510., 2535., 2560., 2585., 2610., 2635., 2660., 2685., 2710., 2735., 2760., 2785., 2810., + 2835., 2860., 2885., 2910., 2935., 2960., 2985., 3010.]) TIPS_NPT = len(Tdat) @@ -5730,481 +5245,369 @@ def AtoB(aa, A, B, npt): M = 1 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.16824E+02, 0.27771E+02, 0.40408E+02, - 0.54549E+02, 0.70054E+02, 0.86817E+02, 0.10475E+03, 0.12380E+03, - 0.14391E+03, 0.16503E+03, 0.18714E+03, 0.21021E+03, 0.23425E+03, - 0.25924E+03, 0.28518E+03, 0.31209E+03, 0.33997E+03, 0.36883E+03, - 0.39870E+03, 0.42959E+03, 0.46152E+03, 0.49452E+03, 0.52860E+03, - 0.56380E+03, 0.60015E+03, 0.63766E+03, 0.67637E+03, 0.71631E+03, - 0.75750E+03, 0.79999E+03, 0.84380E+03, 0.88897E+03, 0.93553E+03, - 0.98353E+03, 0.10330E+04, 0.10840E+04, 0.11365E+04, 0.11906E+04, - 0.12463E+04, 0.13037E+04, 0.13628E+04, 0.14237E+04, 0.14863E+04, - 0.15509E+04, 0.16173E+04, 0.16856E+04, 0.17559E+04, 0.18283E+04, - 0.19028E+04, 0.19793E+04, 0.20581E+04, 0.21391E+04, 0.22224E+04, - 0.23080E+04, 0.24067E+04, 0.24975E+04, 0.25908E+04, 0.26867E+04, - 0.27853E+04, 0.28865E+04, 0.29904E+04, 0.30972E+04, 0.32068E+04, - 0.33194E+04, 0.34349E+04, 0.35535E+04, 0.36752E+04, 0.38001E+04, - 0.39282E+04, 0.40597E+04, 0.41945E+04, 0.43327E+04, 0.44745E+04, - 0.46199E+04, 0.47688E+04, 0.49215E+04, 0.50780E+04, 0.52384E+04, - 0.54027E+04, 0.55710E+04, 0.57434E+04, 0.59200E+04, 0.61008E+04, - 0.62859E+04, 0.64754E+04, 0.66693E+04, 0.68679E+04, 0.70710E+04, - 0.72788E+04, 0.74915E+04, 0.77090E+04, 0.79315E+04, 0.81590E+04, - 0.83917E+04, 0.86296E+04, 0.88728E+04, 0.91214E+04, 0.93755E+04, - 0.96351E+04, 0.99005E+04, 0.10171E+05, 0.10448E+05, 0.10731E+05, - 0.11020E+05, 0.11315E+05, 0.11617E+05, 0.11924E+05, 0.12238E+05, - 0.12559E+05, 0.12886E+05, 0.13220E+05, 0.13561E+05, 0.13909E+05, - 0.14263E+05, 0.14625E+05, 0.14995E+05, 0.15371E+05, 0.15755E+05, - 0.16147E+05]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.16824E+02, 0.27771E+02, 0.40408E+02, 0.54549E+02, 0.70054E+02, 0.86817E+02, 0.10475E+03, + 0.12380E+03, 0.14391E+03, 0.16503E+03, 0.18714E+03, 0.21021E+03, 0.23425E+03, 0.25924E+03, + 0.28518E+03, 0.31209E+03, 0.33997E+03, 0.36883E+03, 0.39870E+03, 0.42959E+03, 0.46152E+03, + 0.49452E+03, 0.52860E+03, 0.56380E+03, 0.60015E+03, 0.63766E+03, 0.67637E+03, 0.71631E+03, + 0.75750E+03, 0.79999E+03, 0.84380E+03, 0.88897E+03, 0.93553E+03, 0.98353E+03, 0.10330E+04, + 0.10840E+04, 0.11365E+04, 0.11906E+04, 0.12463E+04, 0.13037E+04, 0.13628E+04, 0.14237E+04, + 0.14863E+04, 0.15509E+04, 0.16173E+04, 0.16856E+04, 0.17559E+04, 0.18283E+04, 0.19028E+04, + 0.19793E+04, 0.20581E+04, 0.21391E+04, 0.22224E+04, 0.23080E+04, 0.24067E+04, 0.24975E+04, + 0.25908E+04, 0.26867E+04, 0.27853E+04, 0.28865E+04, 0.29904E+04, 0.30972E+04, 0.32068E+04, + 0.33194E+04, 0.34349E+04, 0.35535E+04, 0.36752E+04, 0.38001E+04, 0.39282E+04, 0.40597E+04, + 0.41945E+04, 0.43327E+04, 0.44745E+04, 0.46199E+04, 0.47688E+04, 0.49215E+04, 0.50780E+04, + 0.52384E+04, 0.54027E+04, 0.55710E+04, 0.57434E+04, 0.59200E+04, 0.61008E+04, 0.62859E+04, + 0.64754E+04, 0.66693E+04, 0.68679E+04, 0.70710E+04, 0.72788E+04, 0.74915E+04, 0.77090E+04, + 0.79315E+04, 0.81590E+04, 0.83917E+04, 0.86296E+04, 0.88728E+04, 0.91214E+04, 0.93755E+04, + 0.96351E+04, 0.99005E+04, 0.10171E+05, 0.10448E+05, 0.10731E+05, 0.11020E+05, 0.11315E+05, + 0.11617E+05, 0.11924E+05, 0.12238E+05, 0.12559E+05, 0.12886E+05, 0.13220E+05, 0.13561E+05, + 0.13909E+05, 0.14263E+05, 0.14625E+05, 0.14995E+05, 0.15371E+05, 0.15755E+05, 0.16147E+05]) # --------------- H2O 181: M = 1, I = 2 --------------------- M = 1 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.15960E+02, 0.26999E+02, 0.39743E+02, - 0.54003E+02, 0.69639E+02, 0.86543E+02, 0.10463E+03, 0.12384E+03, - 0.14412E+03, 0.16542E+03, 0.18773E+03, 0.21103E+03, 0.23531E+03, - 0.26057E+03, 0.28681E+03, 0.31406E+03, 0.34226E+03, 0.37130E+03, - 0.40135E+03, 0.43243E+03, 0.46456E+03, 0.49777E+03, 0.53206E+03, - 0.56748E+03, 0.60405E+03, 0.64179E+03, 0.68074E+03, 0.72093E+03, - 0.76238E+03, 0.80513E+03, 0.84922E+03, 0.89467E+03, 0.94152E+03, - 0.98982E+03, 0.10396E+04, 0.10909E+04, 0.11437E+04, 0.11982E+04, - 0.12543E+04, 0.13120E+04, 0.13715E+04, 0.14328E+04, 0.14959E+04, - 0.15608E+04, 0.16276E+04, 0.16964E+04, 0.17672E+04, 0.18401E+04, - 0.19151E+04, 0.19922E+04, 0.20715E+04, 0.21531E+04, 0.22370E+04, - 0.23232E+04, 0.24118E+04, 0.25030E+04, 0.25967E+04, 0.26929E+04, - 0.27918E+04, 0.28934E+04, 0.29978E+04, 0.31050E+04, 0.32151E+04, - 0.33281E+04, 0.34441E+04, 0.35632E+04, 0.36854E+04, 0.38108E+04, - 0.39395E+04, 0.40715E+04, 0.42070E+04, 0.43459E+04, 0.44883E+04, - 0.46343E+04, 0.47840E+04, 0.49374E+04, 0.50946E+04, 0.52558E+04, - 0.54209E+04, 0.55900E+04, 0.57632E+04, 0.59407E+04, 0.61224E+04, - 0.63084E+04, 0.64988E+04, 0.66938E+04, 0.68933E+04, 0.70975E+04, - 0.73064E+04, 0.75202E+04, 0.77389E+04, 0.79625E+04, 0.81913E+04, - 0.84252E+04, 0.86644E+04, 0.89089E+04, 0.91588E+04, 0.94143E+04, - 0.96754E+04, 0.99422E+04, 0.10215E+05, 0.10493E+05, 0.10778E+05, - 0.11068E+05, 0.11365E+05, 0.11668E+05, 0.11977E+05, 0.12293E+05, - 0.12616E+05, 0.12945E+05, 0.13281E+05, 0.13624E+05, 0.13973E+05, - 0.14330E+05, 0.14694E+05, 0.15066E+05, 0.15445E+05, 0.15831E+05, - 0.16225E+05]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.15960E+02, 0.26999E+02, 0.39743E+02, 0.54003E+02, 0.69639E+02, 0.86543E+02, 0.10463E+03, + 0.12384E+03, 0.14412E+03, 0.16542E+03, 0.18773E+03, 0.21103E+03, 0.23531E+03, 0.26057E+03, + 0.28681E+03, 0.31406E+03, 0.34226E+03, 0.37130E+03, 0.40135E+03, 0.43243E+03, 0.46456E+03, + 0.49777E+03, 0.53206E+03, 0.56748E+03, 0.60405E+03, 0.64179E+03, 0.68074E+03, 0.72093E+03, + 0.76238E+03, 0.80513E+03, 0.84922E+03, 0.89467E+03, 0.94152E+03, 0.98982E+03, 0.10396E+04, + 0.10909E+04, 0.11437E+04, 0.11982E+04, 0.12543E+04, 0.13120E+04, 0.13715E+04, 0.14328E+04, + 0.14959E+04, 0.15608E+04, 0.16276E+04, 0.16964E+04, 0.17672E+04, 0.18401E+04, 0.19151E+04, + 0.19922E+04, 0.20715E+04, 0.21531E+04, 0.22370E+04, 0.23232E+04, 0.24118E+04, 0.25030E+04, + 0.25967E+04, 0.26929E+04, 0.27918E+04, 0.28934E+04, 0.29978E+04, 0.31050E+04, 0.32151E+04, + 0.33281E+04, 0.34441E+04, 0.35632E+04, 0.36854E+04, 0.38108E+04, 0.39395E+04, 0.40715E+04, + 0.42070E+04, 0.43459E+04, 0.44883E+04, 0.46343E+04, 0.47840E+04, 0.49374E+04, 0.50946E+04, + 0.52558E+04, 0.54209E+04, 0.55900E+04, 0.57632E+04, 0.59407E+04, 0.61224E+04, 0.63084E+04, + 0.64988E+04, 0.66938E+04, 0.68933E+04, 0.70975E+04, 0.73064E+04, 0.75202E+04, 0.77389E+04, + 0.79625E+04, 0.81913E+04, 0.84252E+04, 0.86644E+04, 0.89089E+04, 0.91588E+04, 0.94143E+04, + 0.96754E+04, 0.99422E+04, 0.10215E+05, 0.10493E+05, 0.10778E+05, 0.11068E+05, 0.11365E+05, + 0.11668E+05, 0.11977E+05, 0.12293E+05, 0.12616E+05, 0.12945E+05, 0.13281E+05, 0.13624E+05, + 0.13973E+05, 0.14330E+05, 0.14694E+05, 0.15066E+05, 0.15445E+05, 0.15831E+05, 0.16225E+05]) # --------------- H2O 171: M = 1, I = 3 --------------------- M = 1 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.95371E+02, 0.16134E+03, 0.23750E+03, - 0.32273E+03, 0.41617E+03, 0.51722E+03, 0.62540E+03, 0.74036E+03, - 0.86185E+03, 0.98970E+03, 0.11238E+04, 0.12642E+04, 0.14097E+04, - 0.15599E+04, 0.17159E+04, 0.18777E+04, 0.20453E+04, 0.22188E+04, - 0.23983E+04, 0.25840E+04, 0.27760E+04, 0.29743E+04, 0.31792E+04, - 0.33907E+04, 0.36091E+04, 0.38346E+04, 0.40672E+04, 0.43072E+04, - 0.45547E+04, 0.48100E+04, 0.50732E+04, 0.53446E+04, 0.56244E+04, - 0.59128E+04, 0.62100E+04, 0.65162E+04, 0.68317E+04, 0.71567E+04, - 0.74915E+04, 0.78363E+04, 0.81914E+04, 0.85571E+04, 0.89335E+04, - 0.93211E+04, 0.97200E+04, 0.10131E+05, 0.10553E+05, 0.10988E+05, - 0.11435E+05, 0.11895E+05, 0.12368E+05, 0.12855E+05, 0.13356E+05, - 0.13870E+05, 0.14399E+05, 0.14943E+05, 0.15502E+05, 0.16076E+05, - 0.16666E+05, 0.17272E+05, 0.17895E+05, 0.18534E+05, 0.19191E+05, - 0.19865E+05, 0.20557E+05, 0.21267E+05, 0.21996E+05, 0.22744E+05, - 0.23512E+05, 0.24299E+05, 0.25106E+05, 0.25935E+05, 0.26784E+05, - 0.27655E+05, 0.28547E+05, 0.29462E+05, 0.30400E+05, 0.31361E+05, - 0.32345E+05, 0.33353E+05, 0.34386E+05, 0.35444E+05, 0.36527E+05, - 0.37637E+05, 0.38772E+05, 0.39934E+05, 0.41124E+05, 0.42341E+05, - 0.43587E+05, 0.44861E+05, 0.46165E+05, 0.47498E+05, 0.48862E+05, - 0.50256E+05, 0.51682E+05, 0.53139E+05, 0.54629E+05, 0.56152E+05, - 0.57708E+05, 0.59299E+05, 0.60923E+05, 0.62583E+05, 0.64279E+05, - 0.66011E+05, 0.67779E+05, 0.69585E+05, 0.71429E+05, 0.73312E+05, - 0.75234E+05, 0.77195E+05, 0.79197E+05, 0.81240E+05, 0.83325E+05, - 0.85452E+05, 0.87622E+05, 0.89835E+05, 0.92093E+05, 0.94395E+05, - 0.96743E+05]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.95371E+02, 0.16134E+03, 0.23750E+03, 0.32273E+03, 0.41617E+03, 0.51722E+03, 0.62540E+03, + 0.74036E+03, 0.86185E+03, 0.98970E+03, 0.11238E+04, 0.12642E+04, 0.14097E+04, 0.15599E+04, + 0.17159E+04, 0.18777E+04, 0.20453E+04, 0.22188E+04, 0.23983E+04, 0.25840E+04, 0.27760E+04, + 0.29743E+04, 0.31792E+04, 0.33907E+04, 0.36091E+04, 0.38346E+04, 0.40672E+04, 0.43072E+04, + 0.45547E+04, 0.48100E+04, 0.50732E+04, 0.53446E+04, 0.56244E+04, 0.59128E+04, 0.62100E+04, + 0.65162E+04, 0.68317E+04, 0.71567E+04, 0.74915E+04, 0.78363E+04, 0.81914E+04, 0.85571E+04, + 0.89335E+04, 0.93211E+04, 0.97200E+04, 0.10131E+05, 0.10553E+05, 0.10988E+05, 0.11435E+05, + 0.11895E+05, 0.12368E+05, 0.12855E+05, 0.13356E+05, 0.13870E+05, 0.14399E+05, 0.14943E+05, + 0.15502E+05, 0.16076E+05, 0.16666E+05, 0.17272E+05, 0.17895E+05, 0.18534E+05, 0.19191E+05, + 0.19865E+05, 0.20557E+05, 0.21267E+05, 0.21996E+05, 0.22744E+05, 0.23512E+05, 0.24299E+05, + 0.25106E+05, 0.25935E+05, 0.26784E+05, 0.27655E+05, 0.28547E+05, 0.29462E+05, 0.30400E+05, + 0.31361E+05, 0.32345E+05, 0.33353E+05, 0.34386E+05, 0.35444E+05, 0.36527E+05, 0.37637E+05, + 0.38772E+05, 0.39934E+05, 0.41124E+05, 0.42341E+05, 0.43587E+05, 0.44861E+05, 0.46165E+05, + 0.47498E+05, 0.48862E+05, 0.50256E+05, 0.51682E+05, 0.53139E+05, 0.54629E+05, 0.56152E+05, + 0.57708E+05, 0.59299E+05, 0.60923E+05, 0.62583E+05, 0.64279E+05, 0.66011E+05, 0.67779E+05, + 0.69585E+05, 0.71429E+05, 0.73312E+05, 0.75234E+05, 0.77195E+05, 0.79197E+05, 0.81240E+05, + 0.83325E+05, 0.85452E+05, 0.87622E+05, 0.89835E+05, 0.92093E+05, 0.94395E+05, 0.96743E+05]) # --------------- H2O 162: M = 1, I = 4 --------------------- M = 1 I = 4 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.75792E+02, 0.12986E+03, 0.19244E+03, - 0.26253E+03, 0.33942E+03, 0.42259E+03, 0.51161E+03, 0.60619E+03, - 0.70609E+03, 0.81117E+03, 0.92132E+03, 0.10365E+04, 0.11567E+04, - 0.12820E+04, 0.14124E+04, 0.15481E+04, 0.16891E+04, 0.18355E+04, - 0.19876E+04, 0.21455E+04, 0.23092E+04, 0.24791E+04, 0.26551E+04, - 0.28376E+04, 0.30268E+04, 0.32258E+04, 0.34288E+04, 0.36392E+04, - 0.38571E+04, 0.40828E+04, 0.43165E+04, 0.45584E+04, 0.48089E+04, - 0.50681E+04, 0.53363E+04, 0.56139E+04, 0.59009E+04, 0.61979E+04, - 0.65049E+04, 0.68224E+04, 0.71506E+04, 0.74898E+04, 0.78403E+04, - 0.82024E+04, 0.85765E+04, 0.89628E+04, 0.93618E+04, 0.97736E+04, - 0.10199E+05, 0.10637E+05, 0.11090E+05, 0.11557E+05, 0.12039E+05, - 0.12535E+05, 0.13047E+05, 0.13575E+05, 0.14119E+05, 0.14679E+05, - 0.15257E+05, 0.15851E+05, 0.16464E+05, 0.17094E+05, 0.17743E+05, - 0.18411E+05, 0.19098E+05, 0.19805E+05, 0.20532E+05, 0.21280E+05, - 0.22049E+05, 0.22840E+05, 0.23652E+05, 0.24487E+05, 0.25345E+05, - 0.26227E+05, 0.27132E+05, 0.28062E+05, 0.29016E+05, 0.29997E+05, - 0.31002E+05, 0.32035E+05, 0.33094E+05, 0.34180E+05, 0.35295E+05, - 0.36438E+05, 0.37610E+05, 0.38812E+05, 0.40044E+05, 0.41306E+05, - 0.42600E+05, 0.43926E+05, 0.45284E+05, 0.46675E+05, 0.48100E+05, - 0.49559E+05, 0.51053E+05, 0.52583E+05, 0.54148E+05, 0.55750E+05, - 0.57390E+05, 0.59067E+05, 0.60783E+05, 0.62539E+05, 0.64334E+05, - 0.66170E+05, 0.68047E+05, 0.69967E+05, 0.71929E+05, 0.73934E+05, - 0.75983E+05, 0.78078E+05, 0.80217E+05, 0.82403E+05, 0.84636E+05, - 0.86917E+05, 0.89246E+05, 0.91625E+05, 0.94053E+05, 0.96533E+05, - 0.99064E+05]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.75792E+02, 0.12986E+03, 0.19244E+03, 0.26253E+03, 0.33942E+03, 0.42259E+03, 0.51161E+03, + 0.60619E+03, 0.70609E+03, 0.81117E+03, 0.92132E+03, 0.10365E+04, 0.11567E+04, 0.12820E+04, + 0.14124E+04, 0.15481E+04, 0.16891E+04, 0.18355E+04, 0.19876E+04, 0.21455E+04, 0.23092E+04, + 0.24791E+04, 0.26551E+04, 0.28376E+04, 0.30268E+04, 0.32258E+04, 0.34288E+04, 0.36392E+04, + 0.38571E+04, 0.40828E+04, 0.43165E+04, 0.45584E+04, 0.48089E+04, 0.50681E+04, 0.53363E+04, + 0.56139E+04, 0.59009E+04, 0.61979E+04, 0.65049E+04, 0.68224E+04, 0.71506E+04, 0.74898E+04, + 0.78403E+04, 0.82024E+04, 0.85765E+04, 0.89628E+04, 0.93618E+04, 0.97736E+04, 0.10199E+05, + 0.10637E+05, 0.11090E+05, 0.11557E+05, 0.12039E+05, 0.12535E+05, 0.13047E+05, 0.13575E+05, + 0.14119E+05, 0.14679E+05, 0.15257E+05, 0.15851E+05, 0.16464E+05, 0.17094E+05, 0.17743E+05, + 0.18411E+05, 0.19098E+05, 0.19805E+05, 0.20532E+05, 0.21280E+05, 0.22049E+05, 0.22840E+05, + 0.23652E+05, 0.24487E+05, 0.25345E+05, 0.26227E+05, 0.27132E+05, 0.28062E+05, 0.29016E+05, + 0.29997E+05, 0.31002E+05, 0.32035E+05, 0.33094E+05, 0.34180E+05, 0.35295E+05, 0.36438E+05, + 0.37610E+05, 0.38812E+05, 0.40044E+05, 0.41306E+05, 0.42600E+05, 0.43926E+05, 0.45284E+05, + 0.46675E+05, 0.48100E+05, 0.49559E+05, 0.51053E+05, 0.52583E+05, 0.54148E+05, 0.55750E+05, + 0.57390E+05, 0.59067E+05, 0.60783E+05, 0.62539E+05, 0.64334E+05, 0.66170E+05, 0.68047E+05, + 0.69967E+05, 0.71929E+05, 0.73934E+05, 0.75983E+05, 0.78078E+05, 0.80217E+05, 0.82403E+05, + 0.84636E+05, 0.86917E+05, 0.89246E+05, 0.91625E+05, 0.94053E+05, 0.96533E+05, 0.99064E+05]) # --------------- H2O 182: M = 1, I = 5 --------------------- M = 1 I = 5 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.82770E+02, 0.13749E+03, 0.20083E+03, - 0.27176E+03, 0.34955E+03, 0.43370E+03, 0.52376E+03, 0.61944E+03, - 0.72050E+03, 0.82679E+03, 0.93821E+03, 0.10547E+04, 0.11763E+04, - 0.13031E+04, 0.14350E+04, 0.15723E+04, 0.17150E+04, 0.18633E+04, - 0.20172E+04, 0.21770E+04, 0.23429E+04, 0.25149E+04, 0.26934E+04, - 0.28784E+04, 0.30702E+04, 0.32690E+04, 0.34750E+04, 0.36885E+04, - 0.39096E+04, 0.41386E+04, 0.43758E+04, 0.46213E+04, 0.48755E+04, - 0.51386E+04, 0.54109E+04, 0.56927E+04, 0.59841E+04, 0.62856E+04, - 0.65973E+04, 0.69197E+04, 0.72529E+04, 0.75973E+04, 0.79533E+04, - 0.83210E+04, 0.87009E+04, 0.90933E+04, 0.94985E+04, 0.99168E+04, - 0.10348E+05, 0.10794E+05, 0.11254E+05, 0.11728E+05, 0.12217E+05, - 0.12722E+05, 0.13242E+05, 0.13778E+05, 0.14331E+05, 0.14900E+05, - 0.15486E+05, 0.16091E+05, 0.16713E+05, 0.17353E+05, 0.18012E+05, - 0.18691E+05, 0.19389E+05, 0.20108E+05, 0.20847E+05, 0.21607E+05, - 0.22388E+05, 0.23191E+05, 0.24017E+05, 0.24866E+05, 0.25738E+05, - 0.26633E+05, 0.27553E+05, 0.28498E+05, 0.29468E+05, 0.30464E+05, - 0.31486E+05, 0.32536E+05, 0.33612E+05, 0.34716E+05, 0.35849E+05, - 0.37011E+05, 0.38202E+05, 0.39424E+05, 0.40676E+05, 0.41959E+05, - 0.43274E+05, 0.44622E+05, 0.46002E+05, 0.47416E+05, 0.48864E+05, - 0.50348E+05, 0.51866E+05, 0.53421E+05, 0.55012E+05, 0.56640E+05, - 0.58307E+05, 0.60012E+05, 0.61757E+05, 0.63541E+05, 0.65366E+05, - 0.67233E+05, 0.69141E+05, 0.71092E+05, 0.73087E+05, 0.75125E+05, - 0.77209E+05, 0.79338E+05, 0.81513E+05, 0.83736E+05, 0.86006E+05, - 0.88324E+05, 0.90693E+05, 0.93111E+05, 0.95580E+05, 0.98100E+05, - 0.10067E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.82770E+02, 0.13749E+03, 0.20083E+03, 0.27176E+03, 0.34955E+03, 0.43370E+03, 0.52376E+03, + 0.61944E+03, 0.72050E+03, 0.82679E+03, 0.93821E+03, 0.10547E+04, 0.11763E+04, 0.13031E+04, + 0.14350E+04, 0.15723E+04, 0.17150E+04, 0.18633E+04, 0.20172E+04, 0.21770E+04, 0.23429E+04, + 0.25149E+04, 0.26934E+04, 0.28784E+04, 0.30702E+04, 0.32690E+04, 0.34750E+04, 0.36885E+04, + 0.39096E+04, 0.41386E+04, 0.43758E+04, 0.46213E+04, 0.48755E+04, 0.51386E+04, 0.54109E+04, + 0.56927E+04, 0.59841E+04, 0.62856E+04, 0.65973E+04, 0.69197E+04, 0.72529E+04, 0.75973E+04, + 0.79533E+04, 0.83210E+04, 0.87009E+04, 0.90933E+04, 0.94985E+04, 0.99168E+04, 0.10348E+05, + 0.10794E+05, 0.11254E+05, 0.11728E+05, 0.12217E+05, 0.12722E+05, 0.13242E+05, 0.13778E+05, + 0.14331E+05, 0.14900E+05, 0.15486E+05, 0.16091E+05, 0.16713E+05, 0.17353E+05, 0.18012E+05, + 0.18691E+05, 0.19389E+05, 0.20108E+05, 0.20847E+05, 0.21607E+05, 0.22388E+05, 0.23191E+05, + 0.24017E+05, 0.24866E+05, 0.25738E+05, 0.26633E+05, 0.27553E+05, 0.28498E+05, 0.29468E+05, + 0.30464E+05, 0.31486E+05, 0.32536E+05, 0.33612E+05, 0.34716E+05, 0.35849E+05, 0.37011E+05, + 0.38202E+05, 0.39424E+05, 0.40676E+05, 0.41959E+05, 0.43274E+05, 0.44622E+05, 0.46002E+05, + 0.47416E+05, 0.48864E+05, 0.50348E+05, 0.51866E+05, 0.53421E+05, 0.55012E+05, 0.56640E+05, + 0.58307E+05, 0.60012E+05, 0.61757E+05, 0.63541E+05, 0.65366E+05, 0.67233E+05, 0.69141E+05, + 0.71092E+05, 0.73087E+05, 0.75125E+05, 0.77209E+05, 0.79338E+05, 0.81513E+05, 0.83736E+05, + 0.86006E+05, 0.88324E+05, 0.90693E+05, 0.93111E+05, 0.95580E+05, 0.98100E+05, 0.10067E+06]) # --------------- H2O 172: M = 1, I = 6 --------------------- M = 1 I = 6 TIPS_GSI_HASH[(M, I)] = __FloatType__(36.) -TIPS_ISO_HASH[(M, I)] = float32([0.49379E+03, 0.82021E+03, 0.11980E+04, - 0.16211E+04, 0.20851E+04, 0.25870E+04, 0.31242E+04, 0.36949E+04, - 0.42977E+04, 0.49317E+04, 0.55963E+04, 0.62911E+04, 0.70164E+04, - 0.77722E+04, 0.85591E+04, 0.93777E+04, 0.10228E+05, 0.11112E+05, - 0.12030E+05, 0.12983E+05, 0.13971E+05, 0.14997E+05, 0.16061E+05, - 0.17163E+05, 0.18306E+05, 0.19491E+05, 0.20719E+05, 0.21991E+05, - 0.23309E+05, 0.24673E+05, 0.26086E+05, 0.27549E+05, 0.29064E+05, - 0.30631E+05, 0.32254E+05, 0.33932E+05, 0.35669E+05, 0.37464E+05, - 0.39321E+05, 0.41242E+05, 0.43227E+05, 0.45279E+05, 0.47399E+05, - 0.49589E+05, 0.51852E+05, 0.54189E+05, 0.56602E+05, 0.59094E+05, - 0.61666E+05, 0.64320E+05, 0.67058E+05, 0.69883E+05, 0.72796E+05, - 0.75801E+05, 0.78899E+05, 0.82092E+05, 0.85382E+05, 0.88773E+05, - 0.92266E+05, 0.95863E+05, 0.99568E+05, 0.10338E+06, 0.10731E+06, - 0.11135E+06, 0.11551E+06, 0.11979E+06, 0.12419E+06, 0.12871E+06, - 0.13337E+06, 0.13815E+06, 0.14307E+06, 0.14812E+06, 0.15331E+06, - 0.15865E+06, 0.16412E+06, 0.16975E+06, 0.17553E+06, 0.18146E+06, - 0.18754E+06, 0.19379E+06, 0.20020E+06, 0.20678E+06, 0.21352E+06, - 0.22044E+06, 0.22753E+06, 0.23480E+06, 0.24226E+06, 0.24990E+06, - 0.25773E+06, 0.26575E+06, 0.27397E+06, 0.28239E+06, 0.29102E+06, - 0.29985E+06, 0.30889E+06, 0.31814E+06, 0.32762E+06, 0.33731E+06, - 0.34724E+06, 0.35739E+06, 0.36777E+06, 0.37840E+06, 0.38926E+06, - 0.40038E+06, 0.41174E+06, 0.42335E+06, 0.43523E+06, 0.44737E+06, - 0.45977E+06, 0.47245E+06, 0.48540E+06, 0.49863E+06, 0.51214E+06, - 0.52595E+06, 0.54005E+06, 0.55444E+06, 0.56914E+06, 0.58415E+06, - 0.59947E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.49379E+03, 0.82021E+03, 0.11980E+04, 0.16211E+04, 0.20851E+04, 0.25870E+04, 0.31242E+04, + 0.36949E+04, 0.42977E+04, 0.49317E+04, 0.55963E+04, 0.62911E+04, 0.70164E+04, 0.77722E+04, + 0.85591E+04, 0.93777E+04, 0.10228E+05, 0.11112E+05, 0.12030E+05, 0.12983E+05, 0.13971E+05, + 0.14997E+05, 0.16061E+05, 0.17163E+05, 0.18306E+05, 0.19491E+05, 0.20719E+05, 0.21991E+05, + 0.23309E+05, 0.24673E+05, 0.26086E+05, 0.27549E+05, 0.29064E+05, 0.30631E+05, 0.32254E+05, + 0.33932E+05, 0.35669E+05, 0.37464E+05, 0.39321E+05, 0.41242E+05, 0.43227E+05, 0.45279E+05, + 0.47399E+05, 0.49589E+05, 0.51852E+05, 0.54189E+05, 0.56602E+05, 0.59094E+05, 0.61666E+05, + 0.64320E+05, 0.67058E+05, 0.69883E+05, 0.72796E+05, 0.75801E+05, 0.78899E+05, 0.82092E+05, + 0.85382E+05, 0.88773E+05, 0.92266E+05, 0.95863E+05, 0.99568E+05, 0.10338E+06, 0.10731E+06, + 0.11135E+06, 0.11551E+06, 0.11979E+06, 0.12419E+06, 0.12871E+06, 0.13337E+06, 0.13815E+06, + 0.14307E+06, 0.14812E+06, 0.15331E+06, 0.15865E+06, 0.16412E+06, 0.16975E+06, 0.17553E+06, + 0.18146E+06, 0.18754E+06, 0.19379E+06, 0.20020E+06, 0.20678E+06, 0.21352E+06, 0.22044E+06, + 0.22753E+06, 0.23480E+06, 0.24226E+06, 0.24990E+06, 0.25773E+06, 0.26575E+06, 0.27397E+06, + 0.28239E+06, 0.29102E+06, 0.29985E+06, 0.30889E+06, 0.31814E+06, 0.32762E+06, 0.33731E+06, + 0.34724E+06, 0.35739E+06, 0.36777E+06, 0.37840E+06, 0.38926E+06, 0.40038E+06, 0.41174E+06, + 0.42335E+06, 0.43523E+06, 0.44737E+06, 0.45977E+06, 0.47245E+06, 0.48540E+06, 0.49863E+06, + 0.51214E+06, 0.52595E+06, 0.54005E+06, 0.55444E+06, 0.56914E+06, 0.58415E+06, 0.59947E+06]) # --------------- CO2 626: M = 2, I = 1 --------------------- M = 2 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.53642E+02, 0.75947E+02, 0.98292E+02, - 0.12078E+03, 0.14364E+03, 0.16714E+03, 0.19160E+03, 0.21731E+03, - 0.24454E+03, 0.27355E+03, 0.30456E+03, 0.33778E+03, 0.37343E+03, - 0.41170E+03, 0.45280E+03, 0.49692E+03, 0.54427E+03, 0.59505E+03, - 0.64948E+03, 0.70779E+03, 0.77019E+03, 0.83693E+03, 0.90825E+03, - 0.98440E+03, 0.10656E+04, 0.11522E+04, 0.12445E+04, 0.13427E+04, - 0.14471E+04, 0.15580E+04, 0.16759E+04, 0.18009E+04, 0.19334E+04, - 0.20739E+04, 0.22225E+04, 0.23798E+04, 0.25462E+04, 0.27219E+04, - 0.29074E+04, 0.31032E+04, 0.33097E+04, 0.35272E+04, 0.37564E+04, - 0.39976E+04, 0.42514E+04, 0.45181E+04, 0.47985E+04, 0.50929E+04, - 0.54019E+04, 0.57260E+04, 0.60659E+04, 0.64221E+04, 0.67952E+04, - 0.71859E+04, 0.75946E+04, 0.80222E+04, 0.84691E+04, 0.89362E+04, - 0.94241E+04, 0.99335E+04, 0.10465E+05, 0.11020E+05, 0.11598E+05, - 0.12201E+05, 0.12828E+05, 0.13482E+05, 0.14163E+05, 0.14872E+05, - 0.15609E+05, 0.16376E+05, 0.17173E+05, 0.18001E+05, 0.18861E+05, - 0.19754E+05, 0.20682E+05, 0.21644E+05, 0.22643E+05, 0.23678E+05, - 0.24752E+05, 0.25865E+05, 0.27018E+05, 0.28212E+05, 0.29449E+05, - 0.30730E+05, 0.32055E+05, 0.33426E+05, 0.34845E+05, 0.36312E+05, - 0.37828E+05, 0.39395E+05, 0.41015E+05, 0.42688E+05, 0.44416E+05, - 0.46199E+05, 0.48041E+05, 0.49942E+05, 0.51902E+05, 0.53925E+05, - 0.56011E+05, 0.58162E+05, 0.60379E+05, 0.62664E+05, 0.65019E+05, - 0.67444E+05, 0.69942E+05, 0.72515E+05, 0.75163E+05, 0.77890E+05, - 0.80695E+05, 0.83582E+05, 0.86551E+05, 0.89605E+05, 0.92746E+05, - 0.95975E+05, 0.99294E+05, 0.10271E+06, 0.10621E+06, 0.10981E+06, - 0.11351E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.53642E+02, 0.75947E+02, 0.98292E+02, 0.12078E+03, 0.14364E+03, 0.16714E+03, 0.19160E+03, + 0.21731E+03, 0.24454E+03, 0.27355E+03, 0.30456E+03, 0.33778E+03, 0.37343E+03, 0.41170E+03, + 0.45280E+03, 0.49692E+03, 0.54427E+03, 0.59505E+03, 0.64948E+03, 0.70779E+03, 0.77019E+03, + 0.83693E+03, 0.90825E+03, 0.98440E+03, 0.10656E+04, 0.11522E+04, 0.12445E+04, 0.13427E+04, + 0.14471E+04, 0.15580E+04, 0.16759E+04, 0.18009E+04, 0.19334E+04, 0.20739E+04, 0.22225E+04, + 0.23798E+04, 0.25462E+04, 0.27219E+04, 0.29074E+04, 0.31032E+04, 0.33097E+04, 0.35272E+04, + 0.37564E+04, 0.39976E+04, 0.42514E+04, 0.45181E+04, 0.47985E+04, 0.50929E+04, 0.54019E+04, + 0.57260E+04, 0.60659E+04, 0.64221E+04, 0.67952E+04, 0.71859E+04, 0.75946E+04, 0.80222E+04, + 0.84691E+04, 0.89362E+04, 0.94241E+04, 0.99335E+04, 0.10465E+05, 0.11020E+05, 0.11598E+05, + 0.12201E+05, 0.12828E+05, 0.13482E+05, 0.14163E+05, 0.14872E+05, 0.15609E+05, 0.16376E+05, + 0.17173E+05, 0.18001E+05, 0.18861E+05, 0.19754E+05, 0.20682E+05, 0.21644E+05, 0.22643E+05, + 0.23678E+05, 0.24752E+05, 0.25865E+05, 0.27018E+05, 0.28212E+05, 0.29449E+05, 0.30730E+05, + 0.32055E+05, 0.33426E+05, 0.34845E+05, 0.36312E+05, 0.37828E+05, 0.39395E+05, 0.41015E+05, + 0.42688E+05, 0.44416E+05, 0.46199E+05, 0.48041E+05, 0.49942E+05, 0.51902E+05, 0.53925E+05, + 0.56011E+05, 0.58162E+05, 0.60379E+05, 0.62664E+05, 0.65019E+05, 0.67444E+05, 0.69942E+05, + 0.72515E+05, 0.75163E+05, 0.77890E+05, 0.80695E+05, 0.83582E+05, 0.86551E+05, 0.89605E+05, + 0.92746E+05, 0.95975E+05, 0.99294E+05, 0.10271E+06, 0.10621E+06, 0.10981E+06, 0.11351E+06]) # --------------- CO2 636: M = 2, I = 2 --------------------- M = 2 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.10728E+03, 0.15189E+03, 0.19659E+03, - 0.24164E+03, 0.28753E+03, 0.33486E+03, 0.38429E+03, 0.43643E+03, - 0.49184E+03, 0.55104E+03, 0.61449E+03, 0.68263E+03, 0.75589E+03, - 0.83468E+03, 0.91943E+03, 0.10106E+04, 0.11085E+04, 0.12137E+04, - 0.13266E+04, 0.14477E+04, 0.15774E+04, 0.17163E+04, 0.18649E+04, - 0.20237E+04, 0.21933E+04, 0.23743E+04, 0.25673E+04, 0.27729E+04, - 0.29917E+04, 0.32245E+04, 0.34718E+04, 0.37345E+04, 0.40132E+04, - 0.43087E+04, 0.46218E+04, 0.49533E+04, 0.53041E+04, 0.56749E+04, - 0.60668E+04, 0.64805E+04, 0.69171E+04, 0.73774E+04, 0.78626E+04, - 0.83736E+04, 0.89114E+04, 0.94772E+04, 0.10072E+05, 0.10697E+05, - 0.11353E+05, 0.12042E+05, 0.12765E+05, 0.13523E+05, 0.14317E+05, - 0.15148E+05, 0.16019E+05, 0.16930E+05, 0.17883E+05, 0.18879E+05, - 0.19920E+05, 0.21008E+05, 0.22143E+05, 0.23328E+05, 0.24563E+05, - 0.25852E+05, 0.27195E+05, 0.28594E+05, 0.30051E+05, 0.31568E+05, - 0.33146E+05, 0.34788E+05, 0.36496E+05, 0.38271E+05, 0.40115E+05, - 0.42031E+05, 0.44021E+05, 0.46086E+05, 0.48230E+05, 0.50453E+05, - 0.52759E+05, 0.55150E+05, 0.57628E+05, 0.60195E+05, 0.62854E+05, - 0.65608E+05, 0.68459E+05, 0.71409E+05, 0.74461E+05, 0.77618E+05, - 0.80883E+05, 0.84258E+05, 0.87746E+05, 0.91350E+05, 0.95073E+05, - 0.98918E+05, 0.10289E+06, 0.10698E+06, 0.11121E+06, 0.11558E+06, - 0.12008E+06, 0.12472E+06, 0.12950E+06, 0.13443E+06, 0.13952E+06, - 0.14475E+06, 0.15015E+06, 0.15571E+06, 0.16143E+06, 0.16732E+06, - 0.17338E+06, 0.17962E+06, 0.18604E+06, 0.19264E+06, 0.19943E+06, - 0.20642E+06, 0.21360E+06, 0.22098E+06, 0.22856E+06, 0.23636E+06, - 0.24436E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.10728E+03, 0.15189E+03, 0.19659E+03, 0.24164E+03, 0.28753E+03, 0.33486E+03, 0.38429E+03, + 0.43643E+03, 0.49184E+03, 0.55104E+03, 0.61449E+03, 0.68263E+03, 0.75589E+03, 0.83468E+03, + 0.91943E+03, 0.10106E+04, 0.11085E+04, 0.12137E+04, 0.13266E+04, 0.14477E+04, 0.15774E+04, + 0.17163E+04, 0.18649E+04, 0.20237E+04, 0.21933E+04, 0.23743E+04, 0.25673E+04, 0.27729E+04, + 0.29917E+04, 0.32245E+04, 0.34718E+04, 0.37345E+04, 0.40132E+04, 0.43087E+04, 0.46218E+04, + 0.49533E+04, 0.53041E+04, 0.56749E+04, 0.60668E+04, 0.64805E+04, 0.69171E+04, 0.73774E+04, + 0.78626E+04, 0.83736E+04, 0.89114E+04, 0.94772E+04, 0.10072E+05, 0.10697E+05, 0.11353E+05, + 0.12042E+05, 0.12765E+05, 0.13523E+05, 0.14317E+05, 0.15148E+05, 0.16019E+05, 0.16930E+05, + 0.17883E+05, 0.18879E+05, 0.19920E+05, 0.21008E+05, 0.22143E+05, 0.23328E+05, 0.24563E+05, + 0.25852E+05, 0.27195E+05, 0.28594E+05, 0.30051E+05, 0.31568E+05, 0.33146E+05, 0.34788E+05, + 0.36496E+05, 0.38271E+05, 0.40115E+05, 0.42031E+05, 0.44021E+05, 0.46086E+05, 0.48230E+05, + 0.50453E+05, 0.52759E+05, 0.55150E+05, 0.57628E+05, 0.60195E+05, 0.62854E+05, 0.65608E+05, + 0.68459E+05, 0.71409E+05, 0.74461E+05, 0.77618E+05, 0.80883E+05, 0.84258E+05, 0.87746E+05, + 0.91350E+05, 0.95073E+05, 0.98918E+05, 0.10289E+06, 0.10698E+06, 0.11121E+06, 0.11558E+06, + 0.12008E+06, 0.12472E+06, 0.12950E+06, 0.13443E+06, 0.13952E+06, 0.14475E+06, 0.15015E+06, + 0.15571E+06, 0.16143E+06, 0.16732E+06, 0.17338E+06, 0.17962E+06, 0.18604E+06, 0.19264E+06, + 0.19943E+06, 0.20642E+06, 0.21360E+06, 0.22098E+06, 0.22856E+06, 0.23636E+06, 0.24436E+06]) # --------------- CO2 628: M = 2, I = 3 --------------------- M = 2 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.11368E+03, 0.16096E+03, 0.20833E+03, - 0.25603E+03, 0.30452E+03, 0.35442E+03, 0.40640E+03, 0.46110E+03, - 0.51910E+03, 0.58093E+03, 0.64709E+03, 0.71804E+03, 0.79422E+03, - 0.87607E+03, 0.96402E+03, 0.10585E+04, 0.11600E+04, 0.12689E+04, - 0.13857E+04, 0.15108E+04, 0.16449E+04, 0.17883E+04, 0.19416E+04, - 0.21054E+04, 0.22803E+04, 0.24668E+04, 0.26655E+04, 0.28770E+04, - 0.31021E+04, 0.33414E+04, 0.35956E+04, 0.38654E+04, 0.41516E+04, - 0.44549E+04, 0.47761E+04, 0.51160E+04, 0.54755E+04, 0.58555E+04, - 0.62568E+04, 0.66804E+04, 0.71273E+04, 0.75982E+04, 0.80944E+04, - 0.86169E+04, 0.91666E+04, 0.97446E+04, 0.10352E+05, 0.10990E+05, - 0.11660E+05, 0.12363E+05, 0.13101E+05, 0.13874E+05, 0.14683E+05, - 0.15531E+05, 0.16418E+05, 0.17347E+05, 0.18317E+05, 0.19332E+05, - 0.20392E+05, 0.21499E+05, 0.22654E+05, 0.23859E+05, 0.25116E+05, - 0.26426E+05, 0.27792E+05, 0.29214E+05, 0.30695E+05, 0.32236E+05, - 0.33840E+05, 0.35508E+05, 0.37242E+05, 0.39045E+05, 0.40917E+05, - 0.42862E+05, 0.44881E+05, 0.46977E+05, 0.49152E+05, 0.51407E+05, - 0.53746E+05, 0.56171E+05, 0.58683E+05, 0.61286E+05, 0.63981E+05, - 0.66772E+05, 0.69661E+05, 0.72650E+05, 0.75742E+05, 0.78940E+05, - 0.82246E+05, 0.85664E+05, 0.89196E+05, 0.92845E+05, 0.96613E+05, - 0.10050E+06, 0.10452E+06, 0.10867E+06, 0.11295E+06, 0.11736E+06, - 0.12191E+06, 0.12661E+06, 0.13145E+06, 0.13643E+06, 0.14157E+06, - 0.14687E+06, 0.15232E+06, 0.15794E+06, 0.16372E+06, 0.16968E+06, - 0.17580E+06, 0.18211E+06, 0.18859E+06, 0.19526E+06, 0.20213E+06, - 0.20918E+06, 0.21643E+06, 0.22388E+06, 0.23154E+06, 0.23941E+06, - 0.24750E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.11368E+03, 0.16096E+03, 0.20833E+03, 0.25603E+03, 0.30452E+03, 0.35442E+03, 0.40640E+03, + 0.46110E+03, 0.51910E+03, 0.58093E+03, 0.64709E+03, 0.71804E+03, 0.79422E+03, 0.87607E+03, + 0.96402E+03, 0.10585E+04, 0.11600E+04, 0.12689E+04, 0.13857E+04, 0.15108E+04, 0.16449E+04, + 0.17883E+04, 0.19416E+04, 0.21054E+04, 0.22803E+04, 0.24668E+04, 0.26655E+04, 0.28770E+04, + 0.31021E+04, 0.33414E+04, 0.35956E+04, 0.38654E+04, 0.41516E+04, 0.44549E+04, 0.47761E+04, + 0.51160E+04, 0.54755E+04, 0.58555E+04, 0.62568E+04, 0.66804E+04, 0.71273E+04, 0.75982E+04, + 0.80944E+04, 0.86169E+04, 0.91666E+04, 0.97446E+04, 0.10352E+05, 0.10990E+05, 0.11660E+05, + 0.12363E+05, 0.13101E+05, 0.13874E+05, 0.14683E+05, 0.15531E+05, 0.16418E+05, 0.17347E+05, + 0.18317E+05, 0.19332E+05, 0.20392E+05, 0.21499E+05, 0.22654E+05, 0.23859E+05, 0.25116E+05, + 0.26426E+05, 0.27792E+05, 0.29214E+05, 0.30695E+05, 0.32236E+05, 0.33840E+05, 0.35508E+05, + 0.37242E+05, 0.39045E+05, 0.40917E+05, 0.42862E+05, 0.44881E+05, 0.46977E+05, 0.49152E+05, + 0.51407E+05, 0.53746E+05, 0.56171E+05, 0.58683E+05, 0.61286E+05, 0.63981E+05, 0.66772E+05, + 0.69661E+05, 0.72650E+05, 0.75742E+05, 0.78940E+05, 0.82246E+05, 0.85664E+05, 0.89196E+05, + 0.92845E+05, 0.96613E+05, 0.10050E+06, 0.10452E+06, 0.10867E+06, 0.11295E+06, 0.11736E+06, + 0.12191E+06, 0.12661E+06, 0.13145E+06, 0.13643E+06, 0.14157E+06, 0.14687E+06, 0.15232E+06, + 0.15794E+06, 0.16372E+06, 0.16968E+06, 0.17580E+06, 0.18211E+06, 0.18859E+06, 0.19526E+06, + 0.20213E+06, 0.20918E+06, 0.21643E+06, 0.22388E+06, 0.23154E+06, 0.23941E+06, 0.24750E+06]) # --------------- CO2 627: M = 2, I = 4 --------------------- M = 2 I = 4 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.66338E+03, 0.93923E+03, 0.12156E+04, - 0.14938E+04, 0.17766E+04, 0.20676E+04, 0.23705E+04, 0.26891E+04, - 0.30267E+04, 0.33866E+04, 0.37714E+04, 0.41839E+04, 0.46267E+04, - 0.51023E+04, 0.56132E+04, 0.61618E+04, 0.67508E+04, 0.73827E+04, - 0.80603E+04, 0.87863E+04, 0.95636E+04, 0.10395E+05, 0.11284E+05, - 0.12233E+05, 0.13246E+05, 0.14326E+05, 0.15477E+05, 0.16702E+05, - 0.18005E+05, 0.19390E+05, 0.20861E+05, 0.22422E+05, 0.24077E+05, - 0.25832E+05, 0.27689E+05, 0.29655E+05, 0.31734E+05, 0.33931E+05, - 0.36250E+05, 0.38698E+05, 0.41280E+05, 0.44002E+05, 0.46869E+05, - 0.49886E+05, 0.53062E+05, 0.56400E+05, 0.59909E+05, 0.63594E+05, - 0.67462E+05, 0.71521E+05, 0.75777E+05, 0.80238E+05, 0.84911E+05, - 0.89804E+05, 0.94925E+05, 0.10028E+06, 0.10588E+06, 0.11173E+06, - 0.11785E+06, 0.12423E+06, 0.13090E+06, 0.13785E+06, 0.14510E+06, - 0.15265E+06, 0.16053E+06, 0.16873E+06, 0.17727E+06, 0.18615E+06, - 0.19540E+06, 0.20501E+06, 0.21501E+06, 0.22540E+06, 0.23619E+06, - 0.24740E+06, 0.25904E+06, 0.27112E+06, 0.28365E+06, 0.29664E+06, - 0.31012E+06, 0.32409E+06, 0.33856E+06, 0.35356E+06, 0.36908E+06, - 0.38516E+06, 0.40180E+06, 0.41902E+06, 0.43683E+06, 0.45525E+06, - 0.47429E+06, 0.49397E+06, 0.51431E+06, 0.53532E+06, 0.55702E+06, - 0.57943E+06, 0.60256E+06, 0.62644E+06, 0.65107E+06, 0.67648E+06, - 0.70269E+06, 0.72972E+06, 0.75758E+06, 0.78629E+06, 0.81588E+06, - 0.84636E+06, 0.87775E+06, 0.91008E+06, 0.94337E+06, 0.97763E+06, - 0.10129E+07, 0.10492E+07, 0.10865E+07, 0.11249E+07, 0.11644E+07, - 0.12050E+07, 0.12467E+07, 0.12896E+07, 0.13337E+07, 0.13789E+07, - 0.14255E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.66338E+03, 0.93923E+03, 0.12156E+04, 0.14938E+04, 0.17766E+04, 0.20676E+04, 0.23705E+04, + 0.26891E+04, 0.30267E+04, 0.33866E+04, 0.37714E+04, 0.41839E+04, 0.46267E+04, 0.51023E+04, + 0.56132E+04, 0.61618E+04, 0.67508E+04, 0.73827E+04, 0.80603E+04, 0.87863E+04, 0.95636E+04, + 0.10395E+05, 0.11284E+05, 0.12233E+05, 0.13246E+05, 0.14326E+05, 0.15477E+05, 0.16702E+05, + 0.18005E+05, 0.19390E+05, 0.20861E+05, 0.22422E+05, 0.24077E+05, 0.25832E+05, 0.27689E+05, + 0.29655E+05, 0.31734E+05, 0.33931E+05, 0.36250E+05, 0.38698E+05, 0.41280E+05, 0.44002E+05, + 0.46869E+05, 0.49886E+05, 0.53062E+05, 0.56400E+05, 0.59909E+05, 0.63594E+05, 0.67462E+05, + 0.71521E+05, 0.75777E+05, 0.80238E+05, 0.84911E+05, 0.89804E+05, 0.94925E+05, 0.10028E+06, + 0.10588E+06, 0.11173E+06, 0.11785E+06, 0.12423E+06, 0.13090E+06, 0.13785E+06, 0.14510E+06, + 0.15265E+06, 0.16053E+06, 0.16873E+06, 0.17727E+06, 0.18615E+06, 0.19540E+06, 0.20501E+06, + 0.21501E+06, 0.22540E+06, 0.23619E+06, 0.24740E+06, 0.25904E+06, 0.27112E+06, 0.28365E+06, + 0.29664E+06, 0.31012E+06, 0.32409E+06, 0.33856E+06, 0.35356E+06, 0.36908E+06, 0.38516E+06, + 0.40180E+06, 0.41902E+06, 0.43683E+06, 0.45525E+06, 0.47429E+06, 0.49397E+06, 0.51431E+06, + 0.53532E+06, 0.55702E+06, 0.57943E+06, 0.60256E+06, 0.62644E+06, 0.65107E+06, 0.67648E+06, + 0.70269E+06, 0.72972E+06, 0.75758E+06, 0.78629E+06, 0.81588E+06, 0.84636E+06, 0.87775E+06, + 0.91008E+06, 0.94337E+06, 0.97763E+06, 0.10129E+07, 0.10492E+07, 0.10865E+07, 0.11249E+07, + 0.11644E+07, 0.12050E+07, 0.12467E+07, 0.12896E+07, 0.13337E+07, 0.13789E+07, 0.14255E+07]) # --------------- CO2 638: M = 2, I = 5 --------------------- M = 2 I = 5 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.22737E+03, 0.32194E+03, 0.41671E+03, - 0.51226E+03, 0.60963E+03, 0.71017E+03, 0.81528E+03, 0.92628E+03, - 0.10444E+04, 0.11707E+04, 0.13061E+04, 0.14518E+04, 0.16085E+04, - 0.17772E+04, 0.19588E+04, 0.21542E+04, 0.23644E+04, 0.25903E+04, - 0.28330E+04, 0.30934E+04, 0.33726E+04, 0.36717E+04, 0.39918E+04, - 0.43342E+04, 0.47001E+04, 0.50907E+04, 0.55074E+04, 0.59515E+04, - 0.64244E+04, 0.69276E+04, 0.74626E+04, 0.80310E+04, 0.86344E+04, - 0.92744E+04, 0.99528E+04, 0.10671E+05, 0.11432E+05, 0.12236E+05, - 0.13086E+05, 0.13984E+05, 0.14932E+05, 0.15932E+05, 0.16985E+05, - 0.18096E+05, 0.19265E+05, 0.20495E+05, 0.21788E+05, 0.23148E+05, - 0.24576E+05, 0.26075E+05, 0.27648E+05, 0.29298E+05, 0.31027E+05, - 0.32839E+05, 0.34736E+05, 0.36721E+05, 0.38798E+05, 0.40970E+05, - 0.43240E+05, 0.45611E+05, 0.48087E+05, 0.50671E+05, 0.53368E+05, - 0.56180E+05, 0.59111E+05, 0.62165E+05, 0.65347E+05, 0.68659E+05, - 0.72107E+05, 0.75694E+05, 0.79425E+05, 0.83303E+05, 0.87334E+05, - 0.91522E+05, 0.95872E+05, 0.10039E+06, 0.10507E+06, 0.10994E+06, - 0.11498E+06, 0.12021E+06, 0.12563E+06, 0.13125E+06, 0.13707E+06, - 0.14309E+06, 0.14933E+06, 0.15579E+06, 0.16247E+06, 0.16938E+06, - 0.17653E+06, 0.18392E+06, 0.19156E+06, 0.19946E+06, 0.20761E+06, - 0.21604E+06, 0.22473E+06, 0.23371E+06, 0.24298E+06, 0.25254E+06, - 0.26240E+06, 0.27258E+06, 0.28307E+06, 0.29388E+06, 0.30502E+06, - 0.31651E+06, 0.32834E+06, 0.34052E+06, 0.35307E+06, 0.36599E+06, - 0.37929E+06, 0.39298E+06, 0.40706E+06, 0.42155E+06, 0.43645E+06, - 0.45178E+06, 0.46753E+06, 0.48373E+06, 0.50038E+06, 0.51748E+06, - 0.53506E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.22737E+03, 0.32194E+03, 0.41671E+03, 0.51226E+03, 0.60963E+03, 0.71017E+03, 0.81528E+03, + 0.92628E+03, 0.10444E+04, 0.11707E+04, 0.13061E+04, 0.14518E+04, 0.16085E+04, 0.17772E+04, + 0.19588E+04, 0.21542E+04, 0.23644E+04, 0.25903E+04, 0.28330E+04, 0.30934E+04, 0.33726E+04, + 0.36717E+04, 0.39918E+04, 0.43342E+04, 0.47001E+04, 0.50907E+04, 0.55074E+04, 0.59515E+04, + 0.64244E+04, 0.69276E+04, 0.74626E+04, 0.80310E+04, 0.86344E+04, 0.92744E+04, 0.99528E+04, + 0.10671E+05, 0.11432E+05, 0.12236E+05, 0.13086E+05, 0.13984E+05, 0.14932E+05, 0.15932E+05, + 0.16985E+05, 0.18096E+05, 0.19265E+05, 0.20495E+05, 0.21788E+05, 0.23148E+05, 0.24576E+05, + 0.26075E+05, 0.27648E+05, 0.29298E+05, 0.31027E+05, 0.32839E+05, 0.34736E+05, 0.36721E+05, + 0.38798E+05, 0.40970E+05, 0.43240E+05, 0.45611E+05, 0.48087E+05, 0.50671E+05, 0.53368E+05, + 0.56180E+05, 0.59111E+05, 0.62165E+05, 0.65347E+05, 0.68659E+05, 0.72107E+05, 0.75694E+05, + 0.79425E+05, 0.83303E+05, 0.87334E+05, 0.91522E+05, 0.95872E+05, 0.10039E+06, 0.10507E+06, + 0.10994E+06, 0.11498E+06, 0.12021E+06, 0.12563E+06, 0.13125E+06, 0.13707E+06, 0.14309E+06, + 0.14933E+06, 0.15579E+06, 0.16247E+06, 0.16938E+06, 0.17653E+06, 0.18392E+06, 0.19156E+06, + 0.19946E+06, 0.20761E+06, 0.21604E+06, 0.22473E+06, 0.23371E+06, 0.24298E+06, 0.25254E+06, + 0.26240E+06, 0.27258E+06, 0.28307E+06, 0.29388E+06, 0.30502E+06, 0.31651E+06, 0.32834E+06, + 0.34052E+06, 0.35307E+06, 0.36599E+06, 0.37929E+06, 0.39298E+06, 0.40706E+06, 0.42155E+06, + 0.43645E+06, 0.45178E+06, 0.46753E+06, 0.48373E+06, 0.50038E+06, 0.51748E+06, 0.53506E+06]) # --------------- CO2 637: M = 2, I = 6 --------------------- M = 2 I = 6 TIPS_GSI_HASH[(M, I)] = __FloatType__(12.) -TIPS_ISO_HASH[(M, I)] = float32([0.13267E+04, 0.18785E+04, 0.24314E+04, - 0.29888E+04, 0.35566E+04, 0.41426E+04, 0.47550E+04, 0.54013E+04, - 0.60886E+04, 0.68232E+04, 0.76109E+04, 0.84574E+04, 0.93678E+04, - 0.10348E+05, 0.11402E+05, 0.12536E+05, 0.13755E+05, 0.15065E+05, - 0.16471E+05, 0.17980E+05, 0.19598E+05, 0.21330E+05, 0.23184E+05, - 0.25166E+05, 0.27283E+05, 0.29543E+05, 0.31953E+05, 0.34521E+05, - 0.37256E+05, 0.40164E+05, 0.43256E+05, 0.46541E+05, 0.50026E+05, - 0.53723E+05, 0.57641E+05, 0.61790E+05, 0.66180E+05, 0.70823E+05, - 0.75729E+05, 0.80910E+05, 0.86378E+05, 0.92145E+05, 0.98224E+05, - 0.10463E+06, 0.11137E+06, 0.11846E+06, 0.12592E+06, 0.13375E+06, - 0.14198E+06, 0.15062E+06, 0.15969E+06, 0.16920E+06, 0.17916E+06, - 0.18959E+06, 0.20052E+06, 0.21196E+06, 0.22392E+06, 0.23642E+06, - 0.24949E+06, 0.26314E+06, 0.27740E+06, 0.29227E+06, 0.30779E+06, - 0.32398E+06, 0.34085E+06, 0.35842E+06, 0.37673E+06, 0.39579E+06, - 0.41563E+06, 0.43626E+06, 0.45772E+06, 0.48003E+06, 0.50322E+06, - 0.52730E+06, 0.55232E+06, 0.57829E+06, 0.60524E+06, 0.63320E+06, - 0.66219E+06, 0.69226E+06, 0.72342E+06, 0.75571E+06, 0.78916E+06, - 0.82380E+06, 0.85966E+06, 0.89678E+06, 0.93518E+06, 0.97490E+06, - 0.10160E+07, 0.10585E+07, 0.11023E+07, 0.11477E+07, 0.11946E+07, - 0.12430E+07, 0.12929E+07, 0.13445E+07, 0.13977E+07, 0.14526E+07, - 0.15093E+07, 0.15677E+07, 0.16280E+07, 0.16901E+07, 0.17541E+07, - 0.18200E+07, 0.18880E+07, 0.19579E+07, 0.20300E+07, 0.21042E+07, - 0.21805E+07, 0.22591E+07, 0.23400E+07, 0.24232E+07, 0.25087E+07, - 0.25967E+07, 0.26871E+07, 0.27801E+07, 0.28757E+07, 0.29739E+07, - 0.30747E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.13267E+04, 0.18785E+04, 0.24314E+04, 0.29888E+04, 0.35566E+04, 0.41426E+04, 0.47550E+04, + 0.54013E+04, 0.60886E+04, 0.68232E+04, 0.76109E+04, 0.84574E+04, 0.93678E+04, 0.10348E+05, + 0.11402E+05, 0.12536E+05, 0.13755E+05, 0.15065E+05, 0.16471E+05, 0.17980E+05, 0.19598E+05, + 0.21330E+05, 0.23184E+05, 0.25166E+05, 0.27283E+05, 0.29543E+05, 0.31953E+05, 0.34521E+05, + 0.37256E+05, 0.40164E+05, 0.43256E+05, 0.46541E+05, 0.50026E+05, 0.53723E+05, 0.57641E+05, + 0.61790E+05, 0.66180E+05, 0.70823E+05, 0.75729E+05, 0.80910E+05, 0.86378E+05, 0.92145E+05, + 0.98224E+05, 0.10463E+06, 0.11137E+06, 0.11846E+06, 0.12592E+06, 0.13375E+06, 0.14198E+06, + 0.15062E+06, 0.15969E+06, 0.16920E+06, 0.17916E+06, 0.18959E+06, 0.20052E+06, 0.21196E+06, + 0.22392E+06, 0.23642E+06, 0.24949E+06, 0.26314E+06, 0.27740E+06, 0.29227E+06, 0.30779E+06, + 0.32398E+06, 0.34085E+06, 0.35842E+06, 0.37673E+06, 0.39579E+06, 0.41563E+06, 0.43626E+06, + 0.45772E+06, 0.48003E+06, 0.50322E+06, 0.52730E+06, 0.55232E+06, 0.57829E+06, 0.60524E+06, + 0.63320E+06, 0.66219E+06, 0.69226E+06, 0.72342E+06, 0.75571E+06, 0.78916E+06, 0.82380E+06, + 0.85966E+06, 0.89678E+06, 0.93518E+06, 0.97490E+06, 0.10160E+07, 0.10585E+07, 0.11023E+07, + 0.11477E+07, 0.11946E+07, 0.12430E+07, 0.12929E+07, 0.13445E+07, 0.13977E+07, 0.14526E+07, + 0.15093E+07, 0.15677E+07, 0.16280E+07, 0.16901E+07, 0.17541E+07, 0.18200E+07, 0.18880E+07, + 0.19579E+07, 0.20300E+07, 0.21042E+07, 0.21805E+07, 0.22591E+07, 0.23400E+07, 0.24232E+07, + 0.25087E+07, 0.25967E+07, 0.26871E+07, 0.27801E+07, 0.28757E+07, 0.29739E+07, 0.30747E+07]) # --------------- CO2 828: M = 2, I = 7 --------------------- M = 2 I = 7 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.60334E+02, 0.85430E+02, 0.11058E+03, - 0.13590E+03, 0.16167E+03, 0.18821E+03, 0.21588E+03, 0.24502E+03, - 0.27595E+03, 0.30896E+03, 0.34431E+03, 0.38225E+03, 0.42301E+03, - 0.46684E+03, 0.51397E+03, 0.56464E+03, 0.61907E+03, 0.67753E+03, - 0.74027E+03, 0.80753E+03, 0.87961E+03, 0.95676E+03, 0.10393E+04, - 0.11275E+04, 0.12217E+04, 0.13222E+04, 0.14293E+04, 0.15434E+04, - 0.16648E+04, 0.17940E+04, 0.19312E+04, 0.20769E+04, 0.22315E+04, - 0.23954E+04, 0.25691E+04, 0.27529E+04, 0.29474E+04, 0.31530E+04, - 0.33702E+04, 0.35995E+04, 0.38414E+04, 0.40965E+04, 0.43654E+04, - 0.46484E+04, 0.49464E+04, 0.52598E+04, 0.55892E+04, 0.59353E+04, - 0.62988E+04, 0.66803E+04, 0.70804E+04, 0.74998E+04, 0.79394E+04, - 0.83998E+04, 0.88817E+04, 0.93859E+04, 0.99132E+04, 0.10464E+05, - 0.11040E+05, 0.11642E+05, 0.12270E+05, 0.12925E+05, 0.13609E+05, - 0.14321E+05, 0.15064E+05, 0.15838E+05, 0.16643E+05, 0.17482E+05, - 0.18355E+05, 0.19263E+05, 0.20207E+05, 0.21188E+05, 0.22208E+05, - 0.23267E+05, 0.24366E+05, 0.25508E+05, 0.26692E+05, 0.27921E+05, - 0.29195E+05, 0.30516E+05, 0.31886E+05, 0.33304E+05, 0.34773E+05, - 0.36294E+05, 0.37869E+05, 0.39499E+05, 0.41185E+05, 0.42929E+05, - 0.44732E+05, 0.46596E+05, 0.48522E+05, 0.50513E+05, 0.52569E+05, - 0.54692E+05, 0.56884E+05, 0.59146E+05, 0.61481E+05, 0.63890E+05, - 0.66375E+05, 0.68937E+05, 0.71578E+05, 0.74301E+05, 0.77107E+05, - 0.79998E+05, 0.82976E+05, 0.86043E+05, 0.89201E+05, 0.92452E+05, - 0.95799E+05, 0.99242E+05, 0.10278E+06, 0.10643E+06, 0.11018E+06, - 0.11403E+06, 0.11799E+06, 0.12206E+06, 0.12625E+06, 0.13055E+06, - 0.13497E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.60334E+02, 0.85430E+02, 0.11058E+03, 0.13590E+03, 0.16167E+03, 0.18821E+03, 0.21588E+03, + 0.24502E+03, 0.27595E+03, 0.30896E+03, 0.34431E+03, 0.38225E+03, 0.42301E+03, 0.46684E+03, + 0.51397E+03, 0.56464E+03, 0.61907E+03, 0.67753E+03, 0.74027E+03, 0.80753E+03, 0.87961E+03, + 0.95676E+03, 0.10393E+04, 0.11275E+04, 0.12217E+04, 0.13222E+04, 0.14293E+04, 0.15434E+04, + 0.16648E+04, 0.17940E+04, 0.19312E+04, 0.20769E+04, 0.22315E+04, 0.23954E+04, 0.25691E+04, + 0.27529E+04, 0.29474E+04, 0.31530E+04, 0.33702E+04, 0.35995E+04, 0.38414E+04, 0.40965E+04, + 0.43654E+04, 0.46484E+04, 0.49464E+04, 0.52598E+04, 0.55892E+04, 0.59353E+04, 0.62988E+04, + 0.66803E+04, 0.70804E+04, 0.74998E+04, 0.79394E+04, 0.83998E+04, 0.88817E+04, 0.93859E+04, + 0.99132E+04, 0.10464E+05, 0.11040E+05, 0.11642E+05, 0.12270E+05, 0.12925E+05, 0.13609E+05, + 0.14321E+05, 0.15064E+05, 0.15838E+05, 0.16643E+05, 0.17482E+05, 0.18355E+05, 0.19263E+05, + 0.20207E+05, 0.21188E+05, 0.22208E+05, 0.23267E+05, 0.24366E+05, 0.25508E+05, 0.26692E+05, + 0.27921E+05, 0.29195E+05, 0.30516E+05, 0.31886E+05, 0.33304E+05, 0.34773E+05, 0.36294E+05, + 0.37869E+05, 0.39499E+05, 0.41185E+05, 0.42929E+05, 0.44732E+05, 0.46596E+05, 0.48522E+05, + 0.50513E+05, 0.52569E+05, 0.54692E+05, 0.56884E+05, 0.59146E+05, 0.61481E+05, 0.63890E+05, + 0.66375E+05, 0.68937E+05, 0.71578E+05, 0.74301E+05, 0.77107E+05, 0.79998E+05, 0.82976E+05, + 0.86043E+05, 0.89201E+05, 0.92452E+05, 0.95799E+05, 0.99242E+05, 0.10278E+06, 0.10643E+06, + 0.11018E+06, 0.11403E+06, 0.11799E+06, 0.12206E+06, 0.12625E+06, 0.13055E+06, 0.13497E+06]) # --------------- CO2 728: M = 2, I = 8 --------------------- M = 2 I = 8 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.70354E+03, 0.99615E+03, 0.12893E+04, - 0.15846E+04, 0.18848E+04, 0.21940E+04, 0.25162E+04, 0.28554E+04, - 0.32152E+04, 0.35991E+04, 0.40099E+04, 0.44507E+04, 0.49242E+04, - 0.54332E+04, 0.59802E+04, 0.65681E+04, 0.71996E+04, 0.78776E+04, - 0.86050E+04, 0.93847E+04, 0.10220E+05, 0.11114E+05, 0.12070E+05, - 0.13091E+05, 0.14182E+05, 0.15345E+05, 0.16585E+05, 0.17906E+05, - 0.19311E+05, 0.20805E+05, 0.22393E+05, 0.24078E+05, 0.25865E+05, - 0.27760E+05, 0.29768E+05, 0.31893E+05, 0.34140E+05, 0.36516E+05, - 0.39025E+05, 0.41674E+05, 0.44469E+05, 0.47416E+05, 0.50520E+05, - 0.53789E+05, 0.57229E+05, 0.60847E+05, 0.64650E+05, 0.68645E+05, - 0.72840E+05, 0.77242E+05, 0.81859E+05, 0.86699E+05, 0.91770E+05, - 0.97081E+05, 0.10264E+06, 0.10846E+06, 0.11454E+06, 0.12090E+06, - 0.12754E+06, 0.13447E+06, 0.14171E+06, 0.14927E+06, 0.15715E+06, - 0.16536E+06, 0.17392E+06, 0.18284E+06, 0.19213E+06, 0.20179E+06, - 0.21185E+06, 0.22231E+06, 0.23319E+06, 0.24450E+06, 0.25625E+06, - 0.26845E+06, 0.28112E+06, 0.29427E+06, 0.30791E+06, 0.32206E+06, - 0.33674E+06, 0.35196E+06, 0.36772E+06, 0.38406E+06, 0.40098E+06, - 0.41850E+06, 0.43663E+06, 0.45539E+06, 0.47480E+06, 0.49488E+06, - 0.51564E+06, 0.53710E+06, 0.55928E+06, 0.58219E+06, 0.60586E+06, - 0.63029E+06, 0.65553E+06, 0.68157E+06, 0.70844E+06, 0.73616E+06, - 0.76476E+06, 0.79424E+06, 0.82464E+06, 0.85597E+06, 0.88826E+06, - 0.92153E+06, 0.95580E+06, 0.99108E+06, 0.10274E+07, 0.10648E+07, - 0.11033E+07, 0.11429E+07, 0.11837E+07, 0.12256E+07, 0.12687E+07, - 0.13131E+07, 0.13586E+07, 0.14055E+07, 0.14536E+07, 0.15031E+07, - 0.15539E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.70354E+03, 0.99615E+03, 0.12893E+04, 0.15846E+04, 0.18848E+04, 0.21940E+04, 0.25162E+04, + 0.28554E+04, 0.32152E+04, 0.35991E+04, 0.40099E+04, 0.44507E+04, 0.49242E+04, 0.54332E+04, + 0.59802E+04, 0.65681E+04, 0.71996E+04, 0.78776E+04, 0.86050E+04, 0.93847E+04, 0.10220E+05, + 0.11114E+05, 0.12070E+05, 0.13091E+05, 0.14182E+05, 0.15345E+05, 0.16585E+05, 0.17906E+05, + 0.19311E+05, 0.20805E+05, 0.22393E+05, 0.24078E+05, 0.25865E+05, 0.27760E+05, 0.29768E+05, + 0.31893E+05, 0.34140E+05, 0.36516E+05, 0.39025E+05, 0.41674E+05, 0.44469E+05, 0.47416E+05, + 0.50520E+05, 0.53789E+05, 0.57229E+05, 0.60847E+05, 0.64650E+05, 0.68645E+05, 0.72840E+05, + 0.77242E+05, 0.81859E+05, 0.86699E+05, 0.91770E+05, 0.97081E+05, 0.10264E+06, 0.10846E+06, + 0.11454E+06, 0.12090E+06, 0.12754E+06, 0.13447E+06, 0.14171E+06, 0.14927E+06, 0.15715E+06, + 0.16536E+06, 0.17392E+06, 0.18284E+06, 0.19213E+06, 0.20179E+06, 0.21185E+06, 0.22231E+06, + 0.23319E+06, 0.24450E+06, 0.25625E+06, 0.26845E+06, 0.28112E+06, 0.29427E+06, 0.30791E+06, + 0.32206E+06, 0.33674E+06, 0.35196E+06, 0.36772E+06, 0.38406E+06, 0.40098E+06, 0.41850E+06, + 0.43663E+06, 0.45539E+06, 0.47480E+06, 0.49488E+06, 0.51564E+06, 0.53710E+06, 0.55928E+06, + 0.58219E+06, 0.60586E+06, 0.63029E+06, 0.65553E+06, 0.68157E+06, 0.70844E+06, 0.73616E+06, + 0.76476E+06, 0.79424E+06, 0.82464E+06, 0.85597E+06, 0.88826E+06, 0.92153E+06, 0.95580E+06, + 0.99108E+06, 0.10274E+07, 0.10648E+07, 0.11033E+07, 0.11429E+07, 0.11837E+07, 0.12256E+07, + 0.12687E+07, 0.13131E+07, 0.13586E+07, 0.14055E+07, 0.14536E+07, 0.15031E+07, 0.15539E+07]) # --------------- CO2 727: M = 2, I = 9 --------------------- M = 2 I = 9 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.20518E+04, 0.29051E+04, 0.37601E+04, - 0.46209E+04, 0.54961E+04, 0.63969E+04, 0.73353E+04, 0.83227E+04, - 0.93698E+04, 0.10486E+05, 0.11681E+05, 0.12962E+05, 0.14337E+05, - 0.15815E+05, 0.17403E+05, 0.19110E+05, 0.20942E+05, 0.22909E+05, - 0.25018E+05, 0.27278E+05, 0.29699E+05, 0.32290E+05, 0.35060E+05, - 0.38019E+05, 0.41177E+05, 0.44545E+05, 0.48135E+05, 0.51957E+05, - 0.56023E+05, 0.60346E+05, 0.64938E+05, 0.69812E+05, 0.74981E+05, - 0.80461E+05, 0.86264E+05, 0.92406E+05, 0.98902E+05, 0.10577E+06, - 0.11302E+06, 0.12067E+06, 0.12875E+06, 0.13726E+06, 0.14622E+06, - 0.15566E+06, 0.16559E+06, 0.17604E+06, 0.18702E+06, 0.19855E+06, - 0.21066E+06, 0.22336E+06, 0.23669E+06, 0.25065E+06, 0.26528E+06, - 0.28061E+06, 0.29664E+06, 0.31342E+06, 0.33096E+06, 0.34930E+06, - 0.36845E+06, 0.38845E+06, 0.40933E+06, 0.43111E+06, 0.45383E+06, - 0.47751E+06, 0.50219E+06, 0.52790E+06, 0.55466E+06, 0.58252E+06, - 0.61151E+06, 0.64166E+06, 0.67300E+06, 0.70558E+06, 0.73943E+06, - 0.77458E+06, 0.81108E+06, 0.84896E+06, 0.88827E+06, 0.92904E+06, - 0.97131E+06, 0.10151E+07, 0.10605E+07, 0.11076E+07, 0.11563E+07, - 0.12068E+07, 0.12590E+07, 0.13130E+07, 0.13689E+07, 0.14267E+07, - 0.14865E+07, 0.15483E+07, 0.16121E+07, 0.16781E+07, 0.17462E+07, - 0.18165E+07, 0.18892E+07, 0.19641E+07, 0.20415E+07, 0.21213E+07, - 0.22036E+07, 0.22884E+07, 0.23759E+07, 0.24661E+07, 0.25590E+07, - 0.26547E+07, 0.27533E+07, 0.28549E+07, 0.29594E+07, 0.30670E+07, - 0.31778E+07, 0.32918E+07, 0.34090E+07, 0.35296E+07, 0.36536E+07, - 0.37812E+07, 0.39123E+07, 0.40470E+07, 0.41855E+07, 0.43278E+07, - 0.44739E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.20518E+04, 0.29051E+04, 0.37601E+04, 0.46209E+04, 0.54961E+04, 0.63969E+04, 0.73353E+04, + 0.83227E+04, 0.93698E+04, 0.10486E+05, 0.11681E+05, 0.12962E+05, 0.14337E+05, 0.15815E+05, + 0.17403E+05, 0.19110E+05, 0.20942E+05, 0.22909E+05, 0.25018E+05, 0.27278E+05, 0.29699E+05, + 0.32290E+05, 0.35060E+05, 0.38019E+05, 0.41177E+05, 0.44545E+05, 0.48135E+05, 0.51957E+05, + 0.56023E+05, 0.60346E+05, 0.64938E+05, 0.69812E+05, 0.74981E+05, 0.80461E+05, 0.86264E+05, + 0.92406E+05, 0.98902E+05, 0.10577E+06, 0.11302E+06, 0.12067E+06, 0.12875E+06, 0.13726E+06, + 0.14622E+06, 0.15566E+06, 0.16559E+06, 0.17604E+06, 0.18702E+06, 0.19855E+06, 0.21066E+06, + 0.22336E+06, 0.23669E+06, 0.25065E+06, 0.26528E+06, 0.28061E+06, 0.29664E+06, 0.31342E+06, + 0.33096E+06, 0.34930E+06, 0.36845E+06, 0.38845E+06, 0.40933E+06, 0.43111E+06, 0.45383E+06, + 0.47751E+06, 0.50219E+06, 0.52790E+06, 0.55466E+06, 0.58252E+06, 0.61151E+06, 0.64166E+06, + 0.67300E+06, 0.70558E+06, 0.73943E+06, 0.77458E+06, 0.81108E+06, 0.84896E+06, 0.88827E+06, + 0.92904E+06, 0.97131E+06, 0.10151E+07, 0.10605E+07, 0.11076E+07, 0.11563E+07, 0.12068E+07, + 0.12590E+07, 0.13130E+07, 0.13689E+07, 0.14267E+07, 0.14865E+07, 0.15483E+07, 0.16121E+07, + 0.16781E+07, 0.17462E+07, 0.18165E+07, 0.18892E+07, 0.19641E+07, 0.20415E+07, 0.21213E+07, + 0.22036E+07, 0.22884E+07, 0.23759E+07, 0.24661E+07, 0.25590E+07, 0.26547E+07, 0.27533E+07, + 0.28549E+07, 0.29594E+07, 0.30670E+07, 0.31778E+07, 0.32918E+07, 0.34090E+07, 0.35296E+07, + 0.36536E+07, 0.37812E+07, 0.39123E+07, 0.40470E+07, 0.41855E+07, 0.43278E+07, 0.44739E+07]) # --------------- CO2 838: M = 2, I = 10 --------------------- M = 2 I = 10 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.12066E+03, 0.17085E+03, 0.22116E+03, - 0.27190E+03, 0.32364E+03, 0.37711E+03, 0.43305E+03, 0.49219E+03, - 0.55516E+03, 0.62256E+03, 0.69492E+03, 0.77276E+03, 0.85657E+03, - 0.94685E+03, 0.10441E+04, 0.11488E+04, 0.12614E+04, 0.13826E+04, - 0.15127E+04, 0.16525E+04, 0.18024E+04, 0.19630E+04, 0.21351E+04, - 0.23191E+04, 0.25158E+04, 0.27260E+04, 0.29502E+04, 0.31892E+04, - 0.34438E+04, 0.37148E+04, 0.40031E+04, 0.43094E+04, 0.46346E+04, - 0.49797E+04, 0.53455E+04, 0.57331E+04, 0.61434E+04, 0.65775E+04, - 0.70364E+04, 0.75212E+04, 0.80330E+04, 0.85730E+04, 0.91424E+04, - 0.97423E+04, 0.10374E+05, 0.11039E+05, 0.11738E+05, 0.12474E+05, - 0.13246E+05, 0.14057E+05, 0.14908E+05, 0.15801E+05, 0.16737E+05, - 0.17717E+05, 0.18744E+05, 0.19819E+05, 0.20944E+05, 0.22120E+05, - 0.23349E+05, 0.24634E+05, 0.25975E+05, 0.27376E+05, 0.28837E+05, - 0.30361E+05, 0.31950E+05, 0.33605E+05, 0.35330E+05, 0.37126E+05, - 0.38996E+05, 0.40942E+05, 0.42965E+05, 0.45069E+05, 0.47256E+05, - 0.49528E+05, 0.51888E+05, 0.54338E+05, 0.56882E+05, 0.59521E+05, - 0.62259E+05, 0.65097E+05, 0.68040E+05, 0.71090E+05, 0.74249E+05, - 0.77522E+05, 0.80910E+05, 0.84417E+05, 0.88046E+05, 0.91801E+05, - 0.95684E+05, 0.99699E+05, 0.10385E+06, 0.10814E+06, 0.11257E+06, - 0.11715E+06, 0.12187E+06, 0.12675E+06, 0.13179E+06, 0.13699E+06, - 0.14235E+06, 0.14788E+06, 0.15358E+06, 0.15946E+06, 0.16552E+06, - 0.17176E+06, 0.17819E+06, 0.18482E+06, 0.19164E+06, 0.19867E+06, - 0.20590E+06, 0.21335E+06, 0.22101E+06, 0.22889E+06, 0.23699E+06, - 0.24533E+06, 0.25390E+06, 0.26271E+06, 0.27177E+06, 0.28108E+06, - 0.29064E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.12066E+03, 0.17085E+03, 0.22116E+03, 0.27190E+03, 0.32364E+03, 0.37711E+03, 0.43305E+03, + 0.49219E+03, 0.55516E+03, 0.62256E+03, 0.69492E+03, 0.77276E+03, 0.85657E+03, 0.94685E+03, + 0.10441E+04, 0.11488E+04, 0.12614E+04, 0.13826E+04, 0.15127E+04, 0.16525E+04, 0.18024E+04, + 0.19630E+04, 0.21351E+04, 0.23191E+04, 0.25158E+04, 0.27260E+04, 0.29502E+04, 0.31892E+04, + 0.34438E+04, 0.37148E+04, 0.40031E+04, 0.43094E+04, 0.46346E+04, 0.49797E+04, 0.53455E+04, + 0.57331E+04, 0.61434E+04, 0.65775E+04, 0.70364E+04, 0.75212E+04, 0.80330E+04, 0.85730E+04, + 0.91424E+04, 0.97423E+04, 0.10374E+05, 0.11039E+05, 0.11738E+05, 0.12474E+05, 0.13246E+05, + 0.14057E+05, 0.14908E+05, 0.15801E+05, 0.16737E+05, 0.17717E+05, 0.18744E+05, 0.19819E+05, + 0.20944E+05, 0.22120E+05, 0.23349E+05, 0.24634E+05, 0.25975E+05, 0.27376E+05, 0.28837E+05, + 0.30361E+05, 0.31950E+05, 0.33605E+05, 0.35330E+05, 0.37126E+05, 0.38996E+05, 0.40942E+05, + 0.42965E+05, 0.45069E+05, 0.47256E+05, 0.49528E+05, 0.51888E+05, 0.54338E+05, 0.56882E+05, + 0.59521E+05, 0.62259E+05, 0.65097E+05, 0.68040E+05, 0.71090E+05, 0.74249E+05, 0.77522E+05, + 0.80910E+05, 0.84417E+05, 0.88046E+05, 0.91801E+05, 0.95684E+05, 0.99699E+05, 0.10385E+06, + 0.10814E+06, 0.11257E+06, 0.11715E+06, 0.12187E+06, 0.12675E+06, 0.13179E+06, 0.13699E+06, + 0.14235E+06, 0.14788E+06, 0.15358E+06, 0.15946E+06, 0.16552E+06, 0.17176E+06, 0.17819E+06, + 0.18482E+06, 0.19164E+06, 0.19867E+06, 0.20590E+06, 0.21335E+06, 0.22101E+06, 0.22889E+06, + 0.23699E+06, 0.24533E+06, 0.25390E+06, 0.26271E+06, 0.27177E+06, 0.28108E+06, 0.29064E+06]) # --------------- CO2 838: M = 2, I = 0 ALIAS----------------- TIPS_GSI_HASH[(M, 0)] = __FloatType__(2.) @@ -6214,1381 +5617,1059 @@ def AtoB(aa, A, B, npt): M = 2 I = 11 TIPS_GSI_HASH[(M, I)] = __FloatType__(12.) -TIPS_ISO_HASH[(M, I)] = float32([0.14071E+04, 0.19923E+04, 0.25789E+04, - 0.31704E+04, 0.37733E+04, 0.43962E+04, 0.50477E+04, 0.57360E+04, - 0.64687E+04, 0.72525E+04, 0.80938E+04, 0.89984E+04, 0.99723E+04, - 0.11021E+05, 0.12150E+05, 0.13366E+05, 0.14673E+05, 0.16079E+05, - 0.17589E+05, 0.19211E+05, 0.20949E+05, 0.22812E+05, 0.24807E+05, - 0.26940E+05, 0.29221E+05, 0.31656E+05, 0.34254E+05, 0.37023E+05, - 0.39972E+05, 0.43111E+05, 0.46449E+05, 0.49996E+05, 0.53762E+05, - 0.57756E+05, 0.61991E+05, 0.66477E+05, 0.71226E+05, 0.76249E+05, - 0.81558E+05, 0.87167E+05, 0.93088E+05, 0.99334E+05, 0.10592E+06, - 0.11286E+06, 0.12016E+06, 0.12785E+06, 0.13594E+06, 0.14444E+06, - 0.15337E+06, 0.16274E+06, 0.17258E+06, 0.18290E+06, 0.19371E+06, - 0.20504E+06, 0.21691E+06, 0.22933E+06, 0.24233E+06, 0.25592E+06, - 0.27012E+06, 0.28496E+06, 0.30046E+06, 0.31663E+06, 0.33351E+06, - 0.35111E+06, 0.36946E+06, 0.38858E+06, 0.40850E+06, 0.42924E+06, - 0.45083E+06, 0.47329E+06, 0.49666E+06, 0.52095E+06, 0.54620E+06, - 0.57243E+06, 0.59967E+06, 0.62796E+06, 0.65732E+06, 0.68778E+06, - 0.71938E+06, 0.75214E+06, 0.78611E+06, 0.82131E+06, 0.85777E+06, - 0.89553E+06, 0.93463E+06, 0.97511E+06, 0.10170E+07, 0.10603E+07, - 0.11051E+07, 0.11514E+07, 0.11993E+07, 0.12488E+07, 0.12999E+07, - 0.13527E+07, 0.14073E+07, 0.14636E+07, 0.15217E+07, 0.15816E+07, - 0.16435E+07, 0.17072E+07, 0.17730E+07, 0.18408E+07, 0.19107E+07, - 0.19827E+07, 0.20569E+07, 0.21334E+07, 0.22121E+07, 0.22931E+07, - 0.23765E+07, 0.24624E+07, 0.25507E+07, 0.26416E+07, 0.27351E+07, - 0.28312E+07, 0.29301E+07, 0.30317E+07, 0.31361E+07, 0.32434E+07, - 0.33537E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.14071E+04, 0.19923E+04, 0.25789E+04, 0.31704E+04, 0.37733E+04, 0.43962E+04, 0.50477E+04, + 0.57360E+04, 0.64687E+04, 0.72525E+04, 0.80938E+04, 0.89984E+04, 0.99723E+04, 0.11021E+05, + 0.12150E+05, 0.13366E+05, 0.14673E+05, 0.16079E+05, 0.17589E+05, 0.19211E+05, 0.20949E+05, + 0.22812E+05, 0.24807E+05, 0.26940E+05, 0.29221E+05, 0.31656E+05, 0.34254E+05, 0.37023E+05, + 0.39972E+05, 0.43111E+05, 0.46449E+05, 0.49996E+05, 0.53762E+05, 0.57756E+05, 0.61991E+05, + 0.66477E+05, 0.71226E+05, 0.76249E+05, 0.81558E+05, 0.87167E+05, 0.93088E+05, 0.99334E+05, + 0.10592E+06, 0.11286E+06, 0.12016E+06, 0.12785E+06, 0.13594E+06, 0.14444E+06, 0.15337E+06, + 0.16274E+06, 0.17258E+06, 0.18290E+06, 0.19371E+06, 0.20504E+06, 0.21691E+06, 0.22933E+06, + 0.24233E+06, 0.25592E+06, 0.27012E+06, 0.28496E+06, 0.30046E+06, 0.31663E+06, 0.33351E+06, + 0.35111E+06, 0.36946E+06, 0.38858E+06, 0.40850E+06, 0.42924E+06, 0.45083E+06, 0.47329E+06, + 0.49666E+06, 0.52095E+06, 0.54620E+06, 0.57243E+06, 0.59967E+06, 0.62796E+06, 0.65732E+06, + 0.68778E+06, 0.71938E+06, 0.75214E+06, 0.78611E+06, 0.82131E+06, 0.85777E+06, 0.89553E+06, + 0.93463E+06, 0.97511E+06, 0.10170E+07, 0.10603E+07, 0.11051E+07, 0.11514E+07, 0.11993E+07, + 0.12488E+07, 0.12999E+07, 0.13527E+07, 0.14073E+07, 0.14636E+07, 0.15217E+07, 0.15816E+07, + 0.16435E+07, 0.17072E+07, 0.17730E+07, 0.18408E+07, 0.19107E+07, 0.19827E+07, 0.20569E+07, + 0.21334E+07, 0.22121E+07, 0.22931E+07, 0.23765E+07, 0.24624E+07, 0.25507E+07, 0.26416E+07, + 0.27351E+07, 0.28312E+07, 0.29301E+07, 0.30317E+07, 0.31361E+07, 0.32434E+07, 0.33537E+07]) # --------------- O3 666: M = 3, I = 1 --------------------- M = 3 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.30333E+03, 0.51126E+03, 0.75274E+03, - 0.10241E+04, 0.13236E+04, 0.16508E+04, 0.20068E+04, 0.23935E+04, - 0.28136E+04, 0.32703E+04, 0.37672E+04, 0.43082E+04, 0.48975E+04, - 0.55395E+04, 0.62386E+04, 0.69996E+04, 0.78272E+04, 0.87264E+04, - 0.97026E+04, 0.10761E+05, 0.11907E+05, 0.13146E+05, 0.14485E+05, - 0.15929E+05, 0.17484E+05, 0.19158E+05, 0.20957E+05, 0.22887E+05, - 0.24956E+05, 0.27172E+05, 0.29541E+05, 0.32072E+05, 0.34773E+05, - 0.37652E+05, 0.40718E+05, 0.43979E+05, 0.47444E+05, 0.51123E+05, - 0.55026E+05, 0.59161E+05, 0.63540E+05, 0.68172E+05, 0.73069E+05, - 0.78240E+05, 0.83698E+05, 0.89453E+05, 0.95517E+05, 0.10190E+06, - 0.10862E+06, 0.11569E+06, 0.12311E+06, 0.13091E+06, 0.13909E+06, - 0.14767E+06, 0.15666E+06, 0.16608E+06, 0.17594E+06, 0.18626E+06, - 0.19706E+06, 0.20834E+06, 0.22012E+06, 0.23242E+06, 0.24526E+06, - 0.25866E+06, 0.27262E+06, 0.28717E+06, 0.30233E+06, 0.31811E+06, - 0.33453E+06, 0.35161E+06, 0.36937E+06, 0.38784E+06, 0.40702E+06, - 0.42694E+06, 0.44762E+06, 0.46909E+06, 0.49135E+06, 0.51444E+06, - 0.53838E+06, 0.56318E+06, 0.58887E+06, 0.61548E+06, 0.64303E+06, - 0.67153E+06, 0.70102E+06, 0.73153E+06, 0.76306E+06, 0.79566E+06, - 0.82934E+06, 0.86413E+06, 0.90006E+06, 0.93716E+06, 0.97545E+06, - 0.10150E+07, 0.10557E+07, 0.10977E+07, 0.11411E+07, 0.11858E+07, - 0.12318E+07, 0.12792E+07, 0.13281E+07, 0.13784E+07, 0.14302E+07, - 0.14835E+07, 0.15384E+07, 0.15948E+07, 0.16529E+07, 0.17126E+07, - 0.17740E+07, 0.18371E+07, 0.19020E+07, 0.19686E+07, 0.20371E+07, - 0.21074E+07, 0.21797E+07, 0.22538E+07, 0.23300E+07, 0.24081E+07, - 0.24883E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.30333E+03, 0.51126E+03, 0.75274E+03, 0.10241E+04, 0.13236E+04, 0.16508E+04, 0.20068E+04, + 0.23935E+04, 0.28136E+04, 0.32703E+04, 0.37672E+04, 0.43082E+04, 0.48975E+04, 0.55395E+04, + 0.62386E+04, 0.69996E+04, 0.78272E+04, 0.87264E+04, 0.97026E+04, 0.10761E+05, 0.11907E+05, + 0.13146E+05, 0.14485E+05, 0.15929E+05, 0.17484E+05, 0.19158E+05, 0.20957E+05, 0.22887E+05, + 0.24956E+05, 0.27172E+05, 0.29541E+05, 0.32072E+05, 0.34773E+05, 0.37652E+05, 0.40718E+05, + 0.43979E+05, 0.47444E+05, 0.51123E+05, 0.55026E+05, 0.59161E+05, 0.63540E+05, 0.68172E+05, + 0.73069E+05, 0.78240E+05, 0.83698E+05, 0.89453E+05, 0.95517E+05, 0.10190E+06, 0.10862E+06, + 0.11569E+06, 0.12311E+06, 0.13091E+06, 0.13909E+06, 0.14767E+06, 0.15666E+06, 0.16608E+06, + 0.17594E+06, 0.18626E+06, 0.19706E+06, 0.20834E+06, 0.22012E+06, 0.23242E+06, 0.24526E+06, + 0.25866E+06, 0.27262E+06, 0.28717E+06, 0.30233E+06, 0.31811E+06, 0.33453E+06, 0.35161E+06, + 0.36937E+06, 0.38784E+06, 0.40702E+06, 0.42694E+06, 0.44762E+06, 0.46909E+06, 0.49135E+06, + 0.51444E+06, 0.53838E+06, 0.56318E+06, 0.58887E+06, 0.61548E+06, 0.64303E+06, 0.67153E+06, + 0.70102E+06, 0.73153E+06, 0.76306E+06, 0.79566E+06, 0.82934E+06, 0.86413E+06, 0.90006E+06, + 0.93716E+06, 0.97545E+06, 0.10150E+07, 0.10557E+07, 0.10977E+07, 0.11411E+07, 0.11858E+07, + 0.12318E+07, 0.12792E+07, 0.13281E+07, 0.13784E+07, 0.14302E+07, 0.14835E+07, 0.15384E+07, + 0.15948E+07, 0.16529E+07, 0.17126E+07, 0.17740E+07, 0.18371E+07, 0.19020E+07, 0.19686E+07, + 0.20371E+07, 0.21074E+07, 0.21797E+07, 0.22538E+07, 0.23300E+07, 0.24081E+07, 0.24883E+07]) # --------------- O3 668: M = 3, I = 2 --------------------- M = 3 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.64763E+03, 0.10916E+04, 0.16073E+04, - 0.21870E+04, 0.28271E+04, 0.35272E+04, 0.42900E+04, 0.51197E+04, - 0.60225E+04, 0.70057E+04, 0.80771E+04, 0.92455E+04, 0.10520E+05, - 0.11911E+05, 0.13427E+05, 0.15079E+05, 0.16878E+05, 0.18834E+05, - 0.20960E+05, 0.23267E+05, 0.25767E+05, 0.28472E+05, 0.31397E+05, - 0.34553E+05, 0.37957E+05, 0.41620E+05, 0.45559E+05, 0.49790E+05, - 0.54327E+05, 0.59187E+05, 0.64387E+05, 0.69944E+05, 0.75877E+05, - 0.82203E+05, 0.88943E+05, 0.96114E+05, 0.10374E+06, 0.11184E+06, - 0.12043E+06, 0.12954E+06, 0.13918E+06, 0.14939E+06, 0.16018E+06, - 0.17159E+06, 0.18362E+06, 0.19632E+06, 0.20970E+06, 0.22380E+06, - 0.23863E+06, 0.25423E+06, 0.27063E+06, 0.28786E+06, 0.30594E+06, - 0.32490E+06, 0.34478E+06, 0.36561E+06, 0.38743E+06, 0.41026E+06, - 0.43413E+06, 0.45909E+06, 0.48517E+06, 0.51241E+06, 0.54084E+06, - 0.57049E+06, 0.60141E+06, 0.63365E+06, 0.66722E+06, 0.70219E+06, - 0.73858E+06, 0.77644E+06, 0.81581E+06, 0.85674E+06, 0.89927E+06, - 0.94345E+06, 0.98932E+06, 0.10369E+07, 0.10863E+07, 0.11375E+07, - 0.11906E+07, 0.12457E+07, 0.13027E+07, 0.13618E+07, 0.14229E+07, - 0.14862E+07, 0.15517E+07, 0.16194E+07, 0.16894E+07, 0.17618E+07, - 0.18366E+07, 0.19139E+07, 0.19937E+07, 0.20761E+07, 0.21612E+07, - 0.22490E+07, 0.23395E+07, 0.24330E+07, 0.25293E+07, 0.26286E+07, - 0.27309E+07, 0.28363E+07, 0.29449E+07, 0.30568E+07, 0.31720E+07, - 0.32905E+07, 0.34125E+07, 0.35381E+07, 0.36672E+07, 0.38000E+07, - 0.39366E+07, 0.40770E+07, 0.42213E+07, 0.43696E+07, 0.45220E+07, - 0.46785E+07, 0.48392E+07, 0.50043E+07, 0.51737E+07, 0.53476E+07, - 0.55261E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.64763E+03, 0.10916E+04, 0.16073E+04, 0.21870E+04, 0.28271E+04, 0.35272E+04, 0.42900E+04, + 0.51197E+04, 0.60225E+04, 0.70057E+04, 0.80771E+04, 0.92455E+04, 0.10520E+05, 0.11911E+05, + 0.13427E+05, 0.15079E+05, 0.16878E+05, 0.18834E+05, 0.20960E+05, 0.23267E+05, 0.25767E+05, + 0.28472E+05, 0.31397E+05, 0.34553E+05, 0.37957E+05, 0.41620E+05, 0.45559E+05, 0.49790E+05, + 0.54327E+05, 0.59187E+05, 0.64387E+05, 0.69944E+05, 0.75877E+05, 0.82203E+05, 0.88943E+05, + 0.96114E+05, 0.10374E+06, 0.11184E+06, 0.12043E+06, 0.12954E+06, 0.13918E+06, 0.14939E+06, + 0.16018E+06, 0.17159E+06, 0.18362E+06, 0.19632E+06, 0.20970E+06, 0.22380E+06, 0.23863E+06, + 0.25423E+06, 0.27063E+06, 0.28786E+06, 0.30594E+06, 0.32490E+06, 0.34478E+06, 0.36561E+06, + 0.38743E+06, 0.41026E+06, 0.43413E+06, 0.45909E+06, 0.48517E+06, 0.51241E+06, 0.54084E+06, + 0.57049E+06, 0.60141E+06, 0.63365E+06, 0.66722E+06, 0.70219E+06, 0.73858E+06, 0.77644E+06, + 0.81581E+06, 0.85674E+06, 0.89927E+06, 0.94345E+06, 0.98932E+06, 0.10369E+07, 0.10863E+07, + 0.11375E+07, 0.11906E+07, 0.12457E+07, 0.13027E+07, 0.13618E+07, 0.14229E+07, 0.14862E+07, + 0.15517E+07, 0.16194E+07, 0.16894E+07, 0.17618E+07, 0.18366E+07, 0.19139E+07, 0.19937E+07, + 0.20761E+07, 0.21612E+07, 0.22490E+07, 0.23395E+07, 0.24330E+07, 0.25293E+07, 0.26286E+07, + 0.27309E+07, 0.28363E+07, 0.29449E+07, 0.30568E+07, 0.31720E+07, 0.32905E+07, 0.34125E+07, + 0.35381E+07, 0.36672E+07, 0.38000E+07, 0.39366E+07, 0.40770E+07, 0.42213E+07, 0.43696E+07, + 0.45220E+07, 0.46785E+07, 0.48392E+07, 0.50043E+07, 0.51737E+07, 0.53476E+07, 0.55261E+07]) # --------------- O3 686: M = 3, I = 3 --------------------- M = 3 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.31656E+03, 0.53355E+03, 0.78557E+03, - 0.10688E+04, 0.13815E+04, 0.17235E+04, 0.20960E+04, 0.25011E+04, - 0.29420E+04, 0.34223E+04, 0.39459E+04, 0.45172E+04, 0.51408E+04, - 0.58213E+04, 0.65639E+04, 0.73735E+04, 0.82555E+04, 0.92152E+04, - 0.10259E+05, 0.11391E+05, 0.12619E+05, 0.13949E+05, 0.15387E+05, - 0.16940E+05, 0.18614E+05, 0.20417E+05, 0.22357E+05, 0.24440E+05, - 0.26675E+05, 0.29070E+05, 0.31633E+05, 0.34374E+05, 0.37299E+05, - 0.40420E+05, 0.43746E+05, 0.47285E+05, 0.51049E+05, 0.55047E+05, - 0.59289E+05, 0.63788E+05, 0.68554E+05, 0.73598E+05, 0.78932E+05, - 0.84568E+05, 0.90519E+05, 0.96796E+05, 0.10341E+06, 0.11039E+06, - 0.11772E+06, 0.12544E+06, 0.13356E+06, 0.14208E+06, 0.15103E+06, - 0.16041E+06, 0.17026E+06, 0.18057E+06, 0.19137E+06, 0.20268E+06, - 0.21450E+06, 0.22687E+06, 0.23979E+06, 0.25328E+06, 0.26736E+06, - 0.28206E+06, 0.29738E+06, 0.31336E+06, 0.33000E+06, 0.34733E+06, - 0.36537E+06, 0.38414E+06, 0.40366E+06, 0.42396E+06, 0.44505E+06, - 0.46696E+06, 0.48971E+06, 0.51332E+06, 0.53782E+06, 0.56323E+06, - 0.58958E+06, 0.61689E+06, 0.64518E+06, 0.67448E+06, 0.70482E+06, - 0.73623E+06, 0.76872E+06, 0.80234E+06, 0.83710E+06, 0.87303E+06, - 0.91017E+06, 0.94853E+06, 0.98816E+06, 0.10291E+07, 0.10713E+07, - 0.11149E+07, 0.11599E+07, 0.12063E+07, 0.12541E+07, 0.13034E+07, - 0.13542E+07, 0.14066E+07, 0.14606E+07, 0.15161E+07, 0.15733E+07, - 0.16322E+07, 0.16928E+07, 0.17552E+07, 0.18194E+07, 0.18854E+07, - 0.19532E+07, 0.20230E+07, 0.20947E+07, 0.21684E+07, 0.22441E+07, - 0.23219E+07, 0.24018E+07, 0.24838E+07, 0.25680E+07, 0.26545E+07, - 0.27432E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.31656E+03, 0.53355E+03, 0.78557E+03, 0.10688E+04, 0.13815E+04, 0.17235E+04, 0.20960E+04, + 0.25011E+04, 0.29420E+04, 0.34223E+04, 0.39459E+04, 0.45172E+04, 0.51408E+04, 0.58213E+04, + 0.65639E+04, 0.73735E+04, 0.82555E+04, 0.92152E+04, 0.10259E+05, 0.11391E+05, 0.12619E+05, + 0.13949E+05, 0.15387E+05, 0.16940E+05, 0.18614E+05, 0.20417E+05, 0.22357E+05, 0.24440E+05, + 0.26675E+05, 0.29070E+05, 0.31633E+05, 0.34374E+05, 0.37299E+05, 0.40420E+05, 0.43746E+05, + 0.47285E+05, 0.51049E+05, 0.55047E+05, 0.59289E+05, 0.63788E+05, 0.68554E+05, 0.73598E+05, + 0.78932E+05, 0.84568E+05, 0.90519E+05, 0.96796E+05, 0.10341E+06, 0.11039E+06, 0.11772E+06, + 0.12544E+06, 0.13356E+06, 0.14208E+06, 0.15103E+06, 0.16041E+06, 0.17026E+06, 0.18057E+06, + 0.19137E+06, 0.20268E+06, 0.21450E+06, 0.22687E+06, 0.23979E+06, 0.25328E+06, 0.26736E+06, + 0.28206E+06, 0.29738E+06, 0.31336E+06, 0.33000E+06, 0.34733E+06, 0.36537E+06, 0.38414E+06, + 0.40366E+06, 0.42396E+06, 0.44505E+06, 0.46696E+06, 0.48971E+06, 0.51332E+06, 0.53782E+06, + 0.56323E+06, 0.58958E+06, 0.61689E+06, 0.64518E+06, 0.67448E+06, 0.70482E+06, 0.73623E+06, + 0.76872E+06, 0.80234E+06, 0.83710E+06, 0.87303E+06, 0.91017E+06, 0.94853E+06, 0.98816E+06, + 0.10291E+07, 0.10713E+07, 0.11149E+07, 0.11599E+07, 0.12063E+07, 0.12541E+07, 0.13034E+07, + 0.13542E+07, 0.14066E+07, 0.14606E+07, 0.15161E+07, 0.15733E+07, 0.16322E+07, 0.16928E+07, + 0.17552E+07, 0.18194E+07, 0.18854E+07, 0.19532E+07, 0.20230E+07, 0.20947E+07, 0.21684E+07, + 0.22441E+07, 0.23219E+07, 0.24018E+07, 0.24838E+07, 0.25680E+07, 0.26545E+07, 0.27432E+07]) # --------------- O3 667: M = 3, I = 4 --------------------- M = 3 I = 4 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.37657E+04, 0.63472E+04, 0.93454E+04, - 0.12715E+05, 0.16435E+05, 0.20502E+05, 0.24929E+05, 0.29742E+05, - 0.34975E+05, 0.40668E+05, 0.46868E+05, 0.53624E+05, 0.60990E+05, - 0.69018E+05, 0.77768E+05, 0.87296E+05, 0.97666E+05, 0.10894E+06, - 0.12118E+06, 0.13446E+06, 0.14885E+06, 0.16441E+06, 0.18123E+06, - 0.19938E+06, 0.21894E+06, 0.23998E+06, 0.26261E+06, 0.28690E+06, - 0.31295E+06, 0.34084E+06, 0.37068E+06, 0.40256E+06, 0.43659E+06, - 0.47287E+06, 0.51151E+06, 0.55262E+06, 0.59632E+06, 0.64272E+06, - 0.69194E+06, 0.74412E+06, 0.79937E+06, 0.85783E+06, 0.91963E+06, - 0.98492E+06, 0.10538E+07, 0.11265E+07, 0.12031E+07, 0.12837E+07, - 0.13686E+07, 0.14579E+07, 0.15517E+07, 0.16502E+07, 0.17536E+07, - 0.18621E+07, 0.19758E+07, 0.20949E+07, 0.22196E+07, 0.23501E+07, - 0.24866E+07, 0.26292E+07, 0.27783E+07, 0.29339E+07, 0.30963E+07, - 0.32658E+07, 0.34425E+07, 0.36266E+07, 0.38184E+07, 0.40181E+07, - 0.42260E+07, 0.44422E+07, 0.46671E+07, 0.49008E+07, 0.51437E+07, - 0.53959E+07, 0.56578E+07, 0.59296E+07, 0.62116E+07, 0.65040E+07, - 0.68071E+07, 0.71213E+07, 0.74468E+07, 0.77838E+07, 0.81328E+07, - 0.84939E+07, 0.88676E+07, 0.92541E+07, 0.96536E+07, 0.10067E+08, - 0.10493E+08, 0.10934E+08, 0.11390E+08, 0.11860E+08, 0.12345E+08, - 0.12846E+08, 0.13363E+08, 0.13895E+08, 0.14445E+08, 0.15011E+08, - 0.15595E+08, 0.16196E+08, 0.16815E+08, 0.17453E+08, 0.18110E+08, - 0.18786E+08, 0.19482E+08, 0.20198E+08, 0.20934E+08, 0.21691E+08, - 0.22470E+08, 0.23270E+08, 0.24093E+08, 0.24939E+08, 0.25807E+08, - 0.26699E+08, 0.27616E+08, 0.28556E+08, 0.29522E+08, 0.30514E+08, - 0.31531E+08]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.37657E+04, 0.63472E+04, 0.93454E+04, 0.12715E+05, 0.16435E+05, 0.20502E+05, 0.24929E+05, + 0.29742E+05, 0.34975E+05, 0.40668E+05, 0.46868E+05, 0.53624E+05, 0.60990E+05, 0.69018E+05, + 0.77768E+05, 0.87296E+05, 0.97666E+05, 0.10894E+06, 0.12118E+06, 0.13446E+06, 0.14885E+06, + 0.16441E+06, 0.18123E+06, 0.19938E+06, 0.21894E+06, 0.23998E+06, 0.26261E+06, 0.28690E+06, + 0.31295E+06, 0.34084E+06, 0.37068E+06, 0.40256E+06, 0.43659E+06, 0.47287E+06, 0.51151E+06, + 0.55262E+06, 0.59632E+06, 0.64272E+06, 0.69194E+06, 0.74412E+06, 0.79937E+06, 0.85783E+06, + 0.91963E+06, 0.98492E+06, 0.10538E+07, 0.11265E+07, 0.12031E+07, 0.12837E+07, 0.13686E+07, + 0.14579E+07, 0.15517E+07, 0.16502E+07, 0.17536E+07, 0.18621E+07, 0.19758E+07, 0.20949E+07, + 0.22196E+07, 0.23501E+07, 0.24866E+07, 0.26292E+07, 0.27783E+07, 0.29339E+07, 0.30963E+07, + 0.32658E+07, 0.34425E+07, 0.36266E+07, 0.38184E+07, 0.40181E+07, 0.42260E+07, 0.44422E+07, + 0.46671E+07, 0.49008E+07, 0.51437E+07, 0.53959E+07, 0.56578E+07, 0.59296E+07, 0.62116E+07, + 0.65040E+07, 0.68071E+07, 0.71213E+07, 0.74468E+07, 0.77838E+07, 0.81328E+07, 0.84939E+07, + 0.88676E+07, 0.92541E+07, 0.96536E+07, 0.10067E+08, 0.10493E+08, 0.10934E+08, 0.11390E+08, + 0.11860E+08, 0.12345E+08, 0.12846E+08, 0.13363E+08, 0.13895E+08, 0.14445E+08, 0.15011E+08, + 0.15595E+08, 0.16196E+08, 0.16815E+08, 0.17453E+08, 0.18110E+08, 0.18786E+08, 0.19482E+08, + 0.20198E+08, 0.20934E+08, 0.21691E+08, 0.22470E+08, 0.23270E+08, 0.24093E+08, 0.24939E+08, + 0.25807E+08, 0.26699E+08, 0.27616E+08, 0.28556E+08, 0.29522E+08, 0.30514E+08, 0.31531E+08]) # --------------- O3 676: M = 3, I = 5 --------------------- M = 3 I = 5 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.18608E+04, 0.31363E+04, 0.46177E+04, - 0.62826E+04, 0.81202E+04, 0.10129E+05, 0.12316E+05, 0.14693E+05, - 0.17277E+05, 0.20089E+05, 0.23153E+05, 0.26492E+05, 0.30133E+05, - 0.34103E+05, 0.38430E+05, 0.43145E+05, 0.48277E+05, 0.53858E+05, - 0.59920E+05, 0.66497E+05, 0.73624E+05, 0.81336E+05, 0.89671E+05, - 0.98668E+05, 0.10836E+06, 0.11880E+06, 0.13002E+06, 0.14207E+06, - 0.15500E+06, 0.16884E+06, 0.18365E+06, 0.19947E+06, 0.21636E+06, - 0.23438E+06, 0.25356E+06, 0.27398E+06, 0.29568E+06, 0.31873E+06, - 0.34318E+06, 0.36911E+06, 0.39656E+06, 0.42561E+06, 0.45632E+06, - 0.48877E+06, 0.52302E+06, 0.55914E+06, 0.59722E+06, 0.63732E+06, - 0.67952E+06, 0.72390E+06, 0.77055E+06, 0.81954E+06, 0.87097E+06, - 0.92491E+06, 0.98146E+06, 0.10407E+07, 0.11027E+07, 0.11677E+07, - 0.12356E+07, 0.13066E+07, 0.13807E+07, 0.14582E+07, 0.15390E+07, - 0.16233E+07, 0.17113E+07, 0.18029E+07, 0.18984E+07, 0.19978E+07, - 0.21012E+07, 0.22089E+07, 0.23208E+07, 0.24372E+07, 0.25581E+07, - 0.26837E+07, 0.28141E+07, 0.29494E+07, 0.30898E+07, 0.32354E+07, - 0.33864E+07, 0.35428E+07, 0.37049E+07, 0.38728E+07, 0.40466E+07, - 0.42264E+07, 0.44125E+07, 0.46050E+07, 0.48040E+07, 0.50098E+07, - 0.52224E+07, 0.54420E+07, 0.56689E+07, 0.59031E+07, 0.61449E+07, - 0.63943E+07, 0.66517E+07, 0.69172E+07, 0.71909E+07, 0.74731E+07, - 0.77639E+07, 0.80635E+07, 0.83721E+07, 0.86900E+07, 0.90172E+07, - 0.93541E+07, 0.97008E+07, 0.10058E+08, 0.10424E+08, 0.10802E+08, - 0.11190E+08, 0.11589E+08, 0.11999E+08, 0.12420E+08, 0.12853E+08, - 0.13298E+08, 0.13755E+08, 0.14223E+08, 0.14705E+08, 0.15199E+08, - 0.15706E+08]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.18608E+04, 0.31363E+04, 0.46177E+04, 0.62826E+04, 0.81202E+04, 0.10129E+05, 0.12316E+05, + 0.14693E+05, 0.17277E+05, 0.20089E+05, 0.23153E+05, 0.26492E+05, 0.30133E+05, 0.34103E+05, + 0.38430E+05, 0.43145E+05, 0.48277E+05, 0.53858E+05, 0.59920E+05, 0.66497E+05, 0.73624E+05, + 0.81336E+05, 0.89671E+05, 0.98668E+05, 0.10836E+06, 0.11880E+06, 0.13002E+06, 0.14207E+06, + 0.15500E+06, 0.16884E+06, 0.18365E+06, 0.19947E+06, 0.21636E+06, 0.23438E+06, 0.25356E+06, + 0.27398E+06, 0.29568E+06, 0.31873E+06, 0.34318E+06, 0.36911E+06, 0.39656E+06, 0.42561E+06, + 0.45632E+06, 0.48877E+06, 0.52302E+06, 0.55914E+06, 0.59722E+06, 0.63732E+06, 0.67952E+06, + 0.72390E+06, 0.77055E+06, 0.81954E+06, 0.87097E+06, 0.92491E+06, 0.98146E+06, 0.10407E+07, + 0.11027E+07, 0.11677E+07, 0.12356E+07, 0.13066E+07, 0.13807E+07, 0.14582E+07, 0.15390E+07, + 0.16233E+07, 0.17113E+07, 0.18029E+07, 0.18984E+07, 0.19978E+07, 0.21012E+07, 0.22089E+07, + 0.23208E+07, 0.24372E+07, 0.25581E+07, 0.26837E+07, 0.28141E+07, 0.29494E+07, 0.30898E+07, + 0.32354E+07, 0.33864E+07, 0.35428E+07, 0.37049E+07, 0.38728E+07, 0.40466E+07, 0.42264E+07, + 0.44125E+07, 0.46050E+07, 0.48040E+07, 0.50098E+07, 0.52224E+07, 0.54420E+07, 0.56689E+07, + 0.59031E+07, 0.61449E+07, 0.63943E+07, 0.66517E+07, 0.69172E+07, 0.71909E+07, 0.74731E+07, + 0.77639E+07, 0.80635E+07, 0.83721E+07, 0.86900E+07, 0.90172E+07, 0.93541E+07, 0.97008E+07, + 0.10058E+08, 0.10424E+08, 0.10802E+08, 0.11190E+08, 0.11589E+08, 0.11999E+08, 0.12420E+08, + 0.12853E+08, 0.13298E+08, 0.13755E+08, 0.14223E+08, 0.14705E+08, 0.15199E+08, 0.15706E+08]) # --------------- O3 886: M = 3, I = 6 --------------------- M = 3 I = 6 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.67639E+03, 0.11401E+04, 0.16787E+04, - 0.22843E+04, 0.29532E+04, 0.36856E+04, 0.44842E+04, 0.53545E+04, - 0.63030E+04, 0.73381E+04, 0.84686E+04, 0.97040E+04, 0.11054E+05, - 0.12530E+05, 0.14143E+05, 0.15903E+05, 0.17823E+05, 0.19915E+05, - 0.22190E+05, 0.24663E+05, 0.27346E+05, 0.30254E+05, 0.33400E+05, - 0.36800E+05, 0.40469E+05, 0.44423E+05, 0.48678E+05, 0.53251E+05, - 0.58160E+05, 0.63423E+05, 0.69058E+05, 0.75085E+05, 0.81524E+05, - 0.88395E+05, 0.95719E+05, 0.10352E+06, 0.11181E+06, 0.12063E+06, - 0.12999E+06, 0.13991E+06, 0.15043E+06, 0.16157E+06, 0.17335E+06, - 0.18580E+06, 0.19895E+06, 0.21283E+06, 0.22746E+06, 0.24288E+06, - 0.25911E+06, 0.27619E+06, 0.29415E+06, 0.31301E+06, 0.33283E+06, - 0.35362E+06, 0.37542E+06, 0.39827E+06, 0.42221E+06, 0.44726E+06, - 0.47348E+06, 0.50089E+06, 0.52954E+06, 0.55947E+06, 0.59072E+06, - 0.62332E+06, 0.65733E+06, 0.69279E+06, 0.72973E+06, 0.76821E+06, - 0.80827E+06, 0.84996E+06, 0.89332E+06, 0.93840E+06, 0.98526E+06, - 0.10339E+07, 0.10845E+07, 0.11370E+07, 0.11914E+07, 0.12479E+07, - 0.13065E+07, 0.13672E+07, 0.14302E+07, 0.14953E+07, 0.15628E+07, - 0.16327E+07, 0.17050E+07, 0.17798E+07, 0.18571E+07, 0.19371E+07, - 0.20197E+07, 0.21051E+07, 0.21933E+07, 0.22844E+07, 0.23785E+07, - 0.24755E+07, 0.25757E+07, 0.26790E+07, 0.27855E+07, 0.28954E+07, - 0.30086E+07, 0.31253E+07, 0.32455E+07, 0.33693E+07, 0.34967E+07, - 0.36280E+07, 0.37631E+07, 0.39021E+07, 0.40451E+07, 0.41922E+07, - 0.43435E+07, 0.44990E+07, 0.46589E+07, 0.48232E+07, 0.49920E+07, - 0.51654E+07, 0.53436E+07, 0.55265E+07, 0.57143E+07, 0.59071E+07, - 0.61050E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.67639E+03, 0.11401E+04, 0.16787E+04, 0.22843E+04, 0.29532E+04, 0.36856E+04, 0.44842E+04, + 0.53545E+04, 0.63030E+04, 0.73381E+04, 0.84686E+04, 0.97040E+04, 0.11054E+05, 0.12530E+05, + 0.14143E+05, 0.15903E+05, 0.17823E+05, 0.19915E+05, 0.22190E+05, 0.24663E+05, 0.27346E+05, + 0.30254E+05, 0.33400E+05, 0.36800E+05, 0.40469E+05, 0.44423E+05, 0.48678E+05, 0.53251E+05, + 0.58160E+05, 0.63423E+05, 0.69058E+05, 0.75085E+05, 0.81524E+05, 0.88395E+05, 0.95719E+05, + 0.10352E+06, 0.11181E+06, 0.12063E+06, 0.12999E+06, 0.13991E+06, 0.15043E+06, 0.16157E+06, + 0.17335E+06, 0.18580E+06, 0.19895E+06, 0.21283E+06, 0.22746E+06, 0.24288E+06, 0.25911E+06, + 0.27619E+06, 0.29415E+06, 0.31301E+06, 0.33283E+06, 0.35362E+06, 0.37542E+06, 0.39827E+06, + 0.42221E+06, 0.44726E+06, 0.47348E+06, 0.50089E+06, 0.52954E+06, 0.55947E+06, 0.59072E+06, + 0.62332E+06, 0.65733E+06, 0.69279E+06, 0.72973E+06, 0.76821E+06, 0.80827E+06, 0.84996E+06, + 0.89332E+06, 0.93840E+06, 0.98526E+06, 0.10339E+07, 0.10845E+07, 0.11370E+07, 0.11914E+07, + 0.12479E+07, 0.13065E+07, 0.13672E+07, 0.14302E+07, 0.14953E+07, 0.15628E+07, 0.16327E+07, + 0.17050E+07, 0.17798E+07, 0.18571E+07, 0.19371E+07, 0.20197E+07, 0.21051E+07, 0.21933E+07, + 0.22844E+07, 0.23785E+07, 0.24755E+07, 0.25757E+07, 0.26790E+07, 0.27855E+07, 0.28954E+07, + 0.30086E+07, 0.31253E+07, 0.32455E+07, 0.33693E+07, 0.34967E+07, 0.36280E+07, 0.37631E+07, + 0.39021E+07, 0.40451E+07, 0.41922E+07, 0.43435E+07, 0.44990E+07, 0.46589E+07, 0.48232E+07, + 0.49920E+07, 0.51654E+07, 0.53436E+07, 0.55265E+07, 0.57143E+07, 0.59071E+07, 0.61050E+07]) # --------------- O3 868: M = 3, I = 7 --------------------- M = 3 I = 7 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.34615E+03, 0.58348E+03, 0.85915E+03, - 0.11692E+04, 0.15117E+04, 0.18868E+04, 0.22960E+04, 0.27419E+04, - 0.32278E+04, 0.37579E+04, 0.43366E+04, 0.49686E+04, 0.56591E+04, - 0.64134E+04, 0.72369E+04, 0.81354E+04, 0.91148E+04, 0.10181E+05, - 0.11341E+05, 0.12600E+05, 0.13966E+05, 0.15446E+05, 0.17046E+05, - 0.18775E+05, 0.20640E+05, 0.22649E+05, 0.24810E+05, 0.27132E+05, - 0.29624E+05, 0.32295E+05, 0.35154E+05, 0.38211E+05, 0.41475E+05, - 0.44958E+05, 0.48670E+05, 0.52621E+05, 0.56823E+05, 0.61288E+05, - 0.66026E+05, 0.71052E+05, 0.76376E+05, 0.82011E+05, 0.87972E+05, - 0.94271E+05, 0.10092E+06, 0.10794E+06, 0.11534E+06, 0.12313E+06, - 0.13134E+06, 0.13997E+06, 0.14905E+06, 0.15858E+06, 0.16859E+06, - 0.17909E+06, 0.19010E+06, 0.20164E+06, 0.21373E+06, 0.22638E+06, - 0.23962E+06, 0.25346E+06, 0.26792E+06, 0.28302E+06, 0.29879E+06, - 0.31524E+06, 0.33240E+06, 0.35029E+06, 0.36892E+06, 0.38833E+06, - 0.40853E+06, 0.42956E+06, 0.45142E+06, 0.47416E+06, 0.49778E+06, - 0.52233E+06, 0.54781E+06, 0.57427E+06, 0.60172E+06, 0.63019E+06, - 0.65971E+06, 0.69031E+06, 0.72201E+06, 0.75485E+06, 0.78886E+06, - 0.82405E+06, 0.86048E+06, 0.89815E+06, 0.93711E+06, 0.97739E+06, - 0.10190E+07, 0.10620E+07, 0.11065E+07, 0.11523E+07, 0.11997E+07, - 0.12485E+07, 0.12990E+07, 0.13510E+07, 0.14046E+07, 0.14599E+07, - 0.15169E+07, 0.15756E+07, 0.16361E+07, 0.16984E+07, 0.17626E+07, - 0.18287E+07, 0.18966E+07, 0.19666E+07, 0.20386E+07, 0.21126E+07, - 0.21887E+07, 0.22669E+07, 0.23474E+07, 0.24300E+07, 0.25150E+07, - 0.26022E+07, 0.26919E+07, 0.27839E+07, 0.28784E+07, 0.29753E+07, - 0.30749E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.34615E+03, 0.58348E+03, 0.85915E+03, 0.11692E+04, 0.15117E+04, 0.18868E+04, 0.22960E+04, + 0.27419E+04, 0.32278E+04, 0.37579E+04, 0.43366E+04, 0.49686E+04, 0.56591E+04, 0.64134E+04, + 0.72369E+04, 0.81354E+04, 0.91148E+04, 0.10181E+05, 0.11341E+05, 0.12600E+05, 0.13966E+05, + 0.15446E+05, 0.17046E+05, 0.18775E+05, 0.20640E+05, 0.22649E+05, 0.24810E+05, 0.27132E+05, + 0.29624E+05, 0.32295E+05, 0.35154E+05, 0.38211E+05, 0.41475E+05, 0.44958E+05, 0.48670E+05, + 0.52621E+05, 0.56823E+05, 0.61288E+05, 0.66026E+05, 0.71052E+05, 0.76376E+05, 0.82011E+05, + 0.87972E+05, 0.94271E+05, 0.10092E+06, 0.10794E+06, 0.11534E+06, 0.12313E+06, 0.13134E+06, + 0.13997E+06, 0.14905E+06, 0.15858E+06, 0.16859E+06, 0.17909E+06, 0.19010E+06, 0.20164E+06, + 0.21373E+06, 0.22638E+06, 0.23962E+06, 0.25346E+06, 0.26792E+06, 0.28302E+06, 0.29879E+06, + 0.31524E+06, 0.33240E+06, 0.35029E+06, 0.36892E+06, 0.38833E+06, 0.40853E+06, 0.42956E+06, + 0.45142E+06, 0.47416E+06, 0.49778E+06, 0.52233E+06, 0.54781E+06, 0.57427E+06, 0.60172E+06, + 0.63019E+06, 0.65971E+06, 0.69031E+06, 0.72201E+06, 0.75485E+06, 0.78886E+06, 0.82405E+06, + 0.86048E+06, 0.89815E+06, 0.93711E+06, 0.97739E+06, 0.10190E+07, 0.10620E+07, 0.11065E+07, + 0.11523E+07, 0.11997E+07, 0.12485E+07, 0.12990E+07, 0.13510E+07, 0.14046E+07, 0.14599E+07, + 0.15169E+07, 0.15756E+07, 0.16361E+07, 0.16984E+07, 0.17626E+07, 0.18287E+07, 0.18966E+07, + 0.19666E+07, 0.20386E+07, 0.21126E+07, 0.21887E+07, 0.22669E+07, 0.23474E+07, 0.24300E+07, + 0.25150E+07, 0.26022E+07, 0.26919E+07, 0.27839E+07, 0.28784E+07, 0.29753E+07, 0.30749E+07]) # --------------- O3 678: M = 3, I = 8 --------------------- M = 3 I = 8 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.39745E+04, 0.66993E+04, 0.98642E+04, - 0.13422E+05, 0.17352E+05, 0.21652E+05, 0.26339E+05, 0.31442E+05, - 0.37000E+05, 0.43058E+05, 0.49669E+05, 0.56885E+05, 0.64766E+05, - 0.73372E+05, 0.82765E+05, 0.93011E+05, 0.10418E+06, 0.11633E+06, - 0.12955E+06, 0.14390E+06, 0.15946E+06, 0.17632E+06, 0.19455E+06, - 0.21424E+06, 0.23547E+06, 0.25835E+06, 0.28296E+06, 0.30939E+06, - 0.33776E+06, 0.36816E+06, 0.40070E+06, 0.43549E+06, 0.47264E+06, - 0.51228E+06, 0.55451E+06, 0.59947E+06, 0.64728E+06, 0.69807E+06, - 0.75198E+06, 0.80915E+06, 0.86971E+06, 0.93381E+06, 0.10016E+07, - 0.10733E+07, 0.11489E+07, 0.12287E+07, 0.13128E+07, 0.14015E+07, - 0.14948E+07, 0.15930E+07, 0.16961E+07, 0.18045E+07, 0.19183E+07, - 0.20378E+07, 0.21629E+07, 0.22942E+07, 0.24316E+07, 0.25754E+07, - 0.27258E+07, 0.28831E+07, 0.30475E+07, 0.32192E+07, 0.33984E+07, - 0.35855E+07, 0.37805E+07, 0.39838E+07, 0.41956E+07, 0.44162E+07, - 0.46458E+07, 0.48847E+07, 0.51332E+07, 0.53916E+07, 0.56601E+07, - 0.59390E+07, 0.62286E+07, 0.65292E+07, 0.68412E+07, 0.71647E+07, - 0.75002E+07, 0.78479E+07, 0.82081E+07, 0.85813E+07, 0.89676E+07, - 0.93676E+07, 0.97814E+07, 0.10209E+08, 0.10652E+08, 0.11110E+08, - 0.11583E+08, 0.12071E+08, 0.12576E+08, 0.13097E+08, 0.13635E+08, - 0.14190E+08, 0.14763E+08, 0.15354E+08, 0.15963E+08, 0.16592E+08, - 0.17239E+08, 0.17906E+08, 0.18593E+08, 0.19301E+08, 0.20030E+08, - 0.20780E+08, 0.21553E+08, 0.22347E+08, 0.23165E+08, 0.24006E+08, - 0.24870E+08, 0.25759E+08, 0.26673E+08, 0.27612E+08, 0.28577E+08, - 0.29568E+08, 0.30585E+08, 0.31631E+08, 0.32704E+08, 0.33805E+08, - 0.34936E+08]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.39745E+04, 0.66993E+04, 0.98642E+04, 0.13422E+05, 0.17352E+05, 0.21652E+05, 0.26339E+05, + 0.31442E+05, 0.37000E+05, 0.43058E+05, 0.49669E+05, 0.56885E+05, 0.64766E+05, 0.73372E+05, + 0.82765E+05, 0.93011E+05, 0.10418E+06, 0.11633E+06, 0.12955E+06, 0.14390E+06, 0.15946E+06, + 0.17632E+06, 0.19455E+06, 0.21424E+06, 0.23547E+06, 0.25835E+06, 0.28296E+06, 0.30939E+06, + 0.33776E+06, 0.36816E+06, 0.40070E+06, 0.43549E+06, 0.47264E+06, 0.51228E+06, 0.55451E+06, + 0.59947E+06, 0.64728E+06, 0.69807E+06, 0.75198E+06, 0.80915E+06, 0.86971E+06, 0.93381E+06, + 0.10016E+07, 0.10733E+07, 0.11489E+07, 0.12287E+07, 0.13128E+07, 0.14015E+07, 0.14948E+07, + 0.15930E+07, 0.16961E+07, 0.18045E+07, 0.19183E+07, 0.20378E+07, 0.21629E+07, 0.22942E+07, + 0.24316E+07, 0.25754E+07, 0.27258E+07, 0.28831E+07, 0.30475E+07, 0.32192E+07, 0.33984E+07, + 0.35855E+07, 0.37805E+07, 0.39838E+07, 0.41956E+07, 0.44162E+07, 0.46458E+07, 0.48847E+07, + 0.51332E+07, 0.53916E+07, 0.56601E+07, 0.59390E+07, 0.62286E+07, 0.65292E+07, 0.68412E+07, + 0.71647E+07, 0.75002E+07, 0.78479E+07, 0.82081E+07, 0.85813E+07, 0.89676E+07, 0.93676E+07, + 0.97814E+07, 0.10209E+08, 0.10652E+08, 0.11110E+08, 0.11583E+08, 0.12071E+08, 0.12576E+08, + 0.13097E+08, 0.13635E+08, 0.14190E+08, 0.14763E+08, 0.15354E+08, 0.15963E+08, 0.16592E+08, + 0.17239E+08, 0.17906E+08, 0.18593E+08, 0.19301E+08, 0.20030E+08, 0.20780E+08, 0.21553E+08, + 0.22347E+08, 0.23165E+08, 0.24006E+08, 0.24870E+08, 0.25759E+08, 0.26673E+08, 0.27612E+08, + 0.28577E+08, 0.29568E+08, 0.30585E+08, 0.31631E+08, 0.32704E+08, 0.33805E+08, 0.34936E+08]) # --------------- O3 768: M = 3, I = 9 --------------------- M = 3 I = 9 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.40228E+04, 0.67808E+04, 0.99842E+04, - 0.13586E+05, 0.17564E+05, 0.21919E+05, 0.26665E+05, 0.31833E+05, - 0.37461E+05, 0.43596E+05, 0.50286E+05, 0.57589E+05, 0.65562E+05, - 0.74264E+05, 0.83761E+05, 0.94115E+05, 0.10540E+06, 0.11767E+06, - 0.13102E+06, 0.14550E+06, 0.16121E+06, 0.17822E+06, 0.19661E+06, - 0.21646E+06, 0.23788E+06, 0.26094E+06, 0.28574E+06, 0.31239E+06, - 0.34097E+06, 0.37160E+06, 0.40437E+06, 0.43941E+06, 0.47683E+06, - 0.51673E+06, 0.55925E+06, 0.60451E+06, 0.65262E+06, 0.70374E+06, - 0.75799E+06, 0.81550E+06, 0.87643E+06, 0.94092E+06, 0.10091E+07, - 0.10812E+07, 0.11572E+07, 0.12375E+07, 0.13221E+07, 0.14112E+07, - 0.15050E+07, 0.16037E+07, 0.17074E+07, 0.18164E+07, 0.19307E+07, - 0.20507E+07, 0.21765E+07, 0.23084E+07, 0.24464E+07, 0.25909E+07, - 0.27421E+07, 0.29001E+07, 0.30652E+07, 0.32377E+07, 0.34177E+07, - 0.36055E+07, 0.38014E+07, 0.40055E+07, 0.42182E+07, 0.44397E+07, - 0.46703E+07, 0.49102E+07, 0.51597E+07, 0.54191E+07, 0.56886E+07, - 0.59686E+07, 0.62593E+07, 0.65611E+07, 0.68742E+07, 0.71989E+07, - 0.75356E+07, 0.78846E+07, 0.82461E+07, 0.86206E+07, 0.90083E+07, - 0.94097E+07, 0.98249E+07, 0.10254E+08, 0.10699E+08, 0.11158E+08, - 0.11632E+08, 0.12123E+08, 0.12629E+08, 0.13152E+08, 0.13691E+08, - 0.14248E+08, 0.14823E+08, 0.15416E+08, 0.16027E+08, 0.16657E+08, - 0.17307E+08, 0.17976E+08, 0.18665E+08, 0.19375E+08, 0.20106E+08, - 0.20858E+08, 0.21633E+08, 0.22430E+08, 0.23250E+08, 0.24093E+08, - 0.24960E+08, 0.25851E+08, 0.26767E+08, 0.27709E+08, 0.28676E+08, - 0.29670E+08, 0.30691E+08, 0.31739E+08, 0.32815E+08, 0.33919E+08, - 0.35053E+08]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.40228E+04, 0.67808E+04, 0.99842E+04, 0.13586E+05, 0.17564E+05, 0.21919E+05, 0.26665E+05, + 0.31833E+05, 0.37461E+05, 0.43596E+05, 0.50286E+05, 0.57589E+05, 0.65562E+05, 0.74264E+05, + 0.83761E+05, 0.94115E+05, 0.10540E+06, 0.11767E+06, 0.13102E+06, 0.14550E+06, 0.16121E+06, + 0.17822E+06, 0.19661E+06, 0.21646E+06, 0.23788E+06, 0.26094E+06, 0.28574E+06, 0.31239E+06, + 0.34097E+06, 0.37160E+06, 0.40437E+06, 0.43941E+06, 0.47683E+06, 0.51673E+06, 0.55925E+06, + 0.60451E+06, 0.65262E+06, 0.70374E+06, 0.75799E+06, 0.81550E+06, 0.87643E+06, 0.94092E+06, + 0.10091E+07, 0.10812E+07, 0.11572E+07, 0.12375E+07, 0.13221E+07, 0.14112E+07, 0.15050E+07, + 0.16037E+07, 0.17074E+07, 0.18164E+07, 0.19307E+07, 0.20507E+07, 0.21765E+07, 0.23084E+07, + 0.24464E+07, 0.25909E+07, 0.27421E+07, 0.29001E+07, 0.30652E+07, 0.32377E+07, 0.34177E+07, + 0.36055E+07, 0.38014E+07, 0.40055E+07, 0.42182E+07, 0.44397E+07, 0.46703E+07, 0.49102E+07, + 0.51597E+07, 0.54191E+07, 0.56886E+07, 0.59686E+07, 0.62593E+07, 0.65611E+07, 0.68742E+07, + 0.71989E+07, 0.75356E+07, 0.78846E+07, 0.82461E+07, 0.86206E+07, 0.90083E+07, 0.94097E+07, + 0.98249E+07, 0.10254E+08, 0.10699E+08, 0.11158E+08, 0.11632E+08, 0.12123E+08, 0.12629E+08, + 0.13152E+08, 0.13691E+08, 0.14248E+08, 0.14823E+08, 0.15416E+08, 0.16027E+08, 0.16657E+08, + 0.17307E+08, 0.17976E+08, 0.18665E+08, 0.19375E+08, 0.20106E+08, 0.20858E+08, 0.21633E+08, + 0.22430E+08, 0.23250E+08, 0.24093E+08, 0.24960E+08, 0.25851E+08, 0.26767E+08, 0.27709E+08, + 0.28676E+08, 0.29670E+08, 0.30691E+08, 0.31739E+08, 0.32815E+08, 0.33919E+08, 0.35053E+08]) # --------------- O3 786: M = 3, I = 10 --------------------- M = 3 I = 10 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.39315E+04, 0.66267E+04, 0.97569E+04, - 0.13276E+05, 0.17162E+05, 0.21414E+05, 0.26048E+05, 0.31094E+05, - 0.36590E+05, 0.42581E+05, 0.49120E+05, 0.56260E+05, 0.64061E+05, - 0.72580E+05, 0.81882E+05, 0.92031E+05, 0.10309E+06, 0.11514E+06, - 0.12824E+06, 0.14247E+06, 0.15791E+06, 0.17463E+06, 0.19272E+06, - 0.21226E+06, 0.23333E+06, 0.25604E+06, 0.28047E+06, 0.30673E+06, - 0.33490E+06, 0.36510E+06, 0.39743E+06, 0.43200E+06, 0.46892E+06, - 0.50831E+06, 0.55029E+06, 0.59498E+06, 0.64251E+06, 0.69301E+06, - 0.74662E+06, 0.80347E+06, 0.86370E+06, 0.92747E+06, 0.99491E+06, - 0.10662E+07, 0.11414E+07, 0.12208E+07, 0.13046E+07, 0.13928E+07, - 0.14856E+07, 0.15833E+07, 0.16860E+07, 0.17939E+07, 0.19072E+07, - 0.20261E+07, 0.21508E+07, 0.22814E+07, 0.24182E+07, 0.25614E+07, - 0.27112E+07, 0.28679E+07, 0.30316E+07, 0.32026E+07, 0.33811E+07, - 0.35674E+07, 0.37617E+07, 0.39642E+07, 0.41752E+07, 0.43950E+07, - 0.46237E+07, 0.48618E+07, 0.51094E+07, 0.53668E+07, 0.56343E+07, - 0.59123E+07, 0.62009E+07, 0.65005E+07, 0.68113E+07, 0.71338E+07, - 0.74681E+07, 0.78147E+07, 0.81737E+07, 0.85457E+07, 0.89308E+07, - 0.93295E+07, 0.97420E+07, 0.10169E+08, 0.10610E+08, 0.11066E+08, - 0.11538E+08, 0.12025E+08, 0.12528E+08, 0.13048E+08, 0.13584E+08, - 0.14138E+08, 0.14709E+08, 0.15298E+08, 0.15906E+08, 0.16532E+08, - 0.17178E+08, 0.17843E+08, 0.18528E+08, 0.19234E+08, 0.19961E+08, - 0.20710E+08, 0.21480E+08, 0.22272E+08, 0.23088E+08, 0.23926E+08, - 0.24789E+08, 0.25675E+08, 0.26587E+08, 0.27523E+08, 0.28485E+08, - 0.29474E+08, 0.30489E+08, 0.31532E+08, 0.32603E+08, 0.33701E+08, - 0.34829E+08]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.39315E+04, 0.66267E+04, 0.97569E+04, 0.13276E+05, 0.17162E+05, 0.21414E+05, 0.26048E+05, + 0.31094E+05, 0.36590E+05, 0.42581E+05, 0.49120E+05, 0.56260E+05, 0.64061E+05, 0.72580E+05, + 0.81882E+05, 0.92031E+05, 0.10309E+06, 0.11514E+06, 0.12824E+06, 0.14247E+06, 0.15791E+06, + 0.17463E+06, 0.19272E+06, 0.21226E+06, 0.23333E+06, 0.25604E+06, 0.28047E+06, 0.30673E+06, + 0.33490E+06, 0.36510E+06, 0.39743E+06, 0.43200E+06, 0.46892E+06, 0.50831E+06, 0.55029E+06, + 0.59498E+06, 0.64251E+06, 0.69301E+06, 0.74662E+06, 0.80347E+06, 0.86370E+06, 0.92747E+06, + 0.99491E+06, 0.10662E+07, 0.11414E+07, 0.12208E+07, 0.13046E+07, 0.13928E+07, 0.14856E+07, + 0.15833E+07, 0.16860E+07, 0.17939E+07, 0.19072E+07, 0.20261E+07, 0.21508E+07, 0.22814E+07, + 0.24182E+07, 0.25614E+07, 0.27112E+07, 0.28679E+07, 0.30316E+07, 0.32026E+07, 0.33811E+07, + 0.35674E+07, 0.37617E+07, 0.39642E+07, 0.41752E+07, 0.43950E+07, 0.46237E+07, 0.48618E+07, + 0.51094E+07, 0.53668E+07, 0.56343E+07, 0.59123E+07, 0.62009E+07, 0.65005E+07, 0.68113E+07, + 0.71338E+07, 0.74681E+07, 0.78147E+07, 0.81737E+07, 0.85457E+07, 0.89308E+07, 0.93295E+07, + 0.97420E+07, 0.10169E+08, 0.10610E+08, 0.11066E+08, 0.11538E+08, 0.12025E+08, 0.12528E+08, + 0.13048E+08, 0.13584E+08, 0.14138E+08, 0.14709E+08, 0.15298E+08, 0.15906E+08, 0.16532E+08, + 0.17178E+08, 0.17843E+08, 0.18528E+08, 0.19234E+08, 0.19961E+08, 0.20710E+08, 0.21480E+08, + 0.22272E+08, 0.23088E+08, 0.23926E+08, 0.24789E+08, 0.25675E+08, 0.26587E+08, 0.27523E+08, + 0.28485E+08, 0.29474E+08, 0.30489E+08, 0.31532E+08, 0.32603E+08, 0.33701E+08, 0.34829E+08]) # --------------- O3 776: M = 3, I = 11 --------------------- M = 3 I = 11 TIPS_GSI_HASH[(M, I)] = __FloatType__(36.) -TIPS_ISO_HASH[(M, I)] = float32([0.23106E+05, 0.38945E+05, 0.57342E+05, - 0.78021E+05, 0.10085E+06, 0.12582E+06, 0.15302E+06, 0.18262E+06, - 0.21482E+06, 0.24989E+06, 0.28812E+06, 0.32983E+06, 0.37535E+06, - 0.42501E+06, 0.47919E+06, 0.53825E+06, 0.60258E+06, 0.67256E+06, - 0.74862E+06, 0.83118E+06, 0.92069E+06, 0.10176E+07, 0.11223E+07, - 0.12354E+07, 0.13574E+07, 0.14887E+07, 0.16299E+07, 0.17816E+07, - 0.19443E+07, 0.21187E+07, 0.23052E+07, 0.25047E+07, 0.27176E+07, - 0.29447E+07, 0.31866E+07, 0.34441E+07, 0.37179E+07, 0.40087E+07, - 0.43173E+07, 0.46444E+07, 0.49910E+07, 0.53578E+07, 0.57456E+07, - 0.61554E+07, 0.65880E+07, 0.70444E+07, 0.75255E+07, 0.80322E+07, - 0.85656E+07, 0.91266E+07, 0.97163E+07, 0.10336E+08, 0.10986E+08, - 0.11668E+08, 0.12383E+08, 0.13133E+08, 0.13918E+08, 0.14739E+08, - 0.15598E+08, 0.16496E+08, 0.17435E+08, 0.18415E+08, 0.19438E+08, - 0.20505E+08, 0.21619E+08, 0.22779E+08, 0.23987E+08, 0.25246E+08, - 0.26556E+08, 0.27920E+08, 0.29337E+08, 0.30811E+08, 0.32343E+08, - 0.33934E+08, 0.35585E+08, 0.37300E+08, 0.39079E+08, 0.40924E+08, - 0.42837E+08, 0.44819E+08, 0.46873E+08, 0.49001E+08, 0.51203E+08, - 0.53483E+08, 0.55842E+08, 0.58282E+08, 0.60805E+08, 0.63414E+08, - 0.66109E+08, 0.68894E+08, 0.71770E+08, 0.74740E+08, 0.77806E+08, - 0.80970E+08, 0.84234E+08, 0.87600E+08, 0.91072E+08, 0.94651E+08, - 0.98339E+08, 0.10214E+09, 0.10605E+09, 0.11009E+09, 0.11424E+09, - 0.11851E+09, 0.12291E+09, 0.12744E+09, 0.13209E+09, 0.13688E+09, - 0.14180E+09, 0.14687E+09, 0.15207E+09, 0.15742E+09, 0.16291E+09, - 0.16855E+09, 0.17435E+09, 0.18030E+09, 0.18641E+09, 0.19268E+09, - 0.19912E+09]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.23106E+05, 0.38945E+05, 0.57342E+05, 0.78021E+05, 0.10085E+06, 0.12582E+06, 0.15302E+06, + 0.18262E+06, 0.21482E+06, 0.24989E+06, 0.28812E+06, 0.32983E+06, 0.37535E+06, 0.42501E+06, + 0.47919E+06, 0.53825E+06, 0.60258E+06, 0.67256E+06, 0.74862E+06, 0.83118E+06, 0.92069E+06, + 0.10176E+07, 0.11223E+07, 0.12354E+07, 0.13574E+07, 0.14887E+07, 0.16299E+07, 0.17816E+07, + 0.19443E+07, 0.21187E+07, 0.23052E+07, 0.25047E+07, 0.27176E+07, 0.29447E+07, 0.31866E+07, + 0.34441E+07, 0.37179E+07, 0.40087E+07, 0.43173E+07, 0.46444E+07, 0.49910E+07, 0.53578E+07, + 0.57456E+07, 0.61554E+07, 0.65880E+07, 0.70444E+07, 0.75255E+07, 0.80322E+07, 0.85656E+07, + 0.91266E+07, 0.97163E+07, 0.10336E+08, 0.10986E+08, 0.11668E+08, 0.12383E+08, 0.13133E+08, + 0.13918E+08, 0.14739E+08, 0.15598E+08, 0.16496E+08, 0.17435E+08, 0.18415E+08, 0.19438E+08, + 0.20505E+08, 0.21619E+08, 0.22779E+08, 0.23987E+08, 0.25246E+08, 0.26556E+08, 0.27920E+08, + 0.29337E+08, 0.30811E+08, 0.32343E+08, 0.33934E+08, 0.35585E+08, 0.37300E+08, 0.39079E+08, + 0.40924E+08, 0.42837E+08, 0.44819E+08, 0.46873E+08, 0.49001E+08, 0.51203E+08, 0.53483E+08, + 0.55842E+08, 0.58282E+08, 0.60805E+08, 0.63414E+08, 0.66109E+08, 0.68894E+08, 0.71770E+08, + 0.74740E+08, 0.77806E+08, 0.80970E+08, 0.84234E+08, 0.87600E+08, 0.91072E+08, 0.94651E+08, + 0.98339E+08, 0.10214E+09, 0.10605E+09, 0.11009E+09, 0.11424E+09, 0.11851E+09, 0.12291E+09, + 0.12744E+09, 0.13209E+09, 0.13688E+09, 0.14180E+09, 0.14687E+09, 0.15207E+09, 0.15742E+09, + 0.16291E+09, 0.16855E+09, 0.17435E+09, 0.18030E+09, 0.18641E+09, 0.19268E+09, 0.19912E+09]) # --------------- O3 767: M = 3, I = 12 --------------------- M = 3 I = 12 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.11692E+05, 0.19707E+05, 0.29017E+05, - 0.39482E+05, 0.51038E+05, 0.63680E+05, 0.77450E+05, 0.92432E+05, - 0.10873E+06, 0.12649E+06, 0.14584E+06, 0.16694E+06, 0.18996E+06, - 0.21507E+06, 0.24245E+06, 0.27229E+06, 0.30478E+06, 0.34013E+06, - 0.37853E+06, 0.42020E+06, 0.46536E+06, 0.51424E+06, 0.56708E+06, - 0.62411E+06, 0.68559E+06, 0.75178E+06, 0.82296E+06, 0.89939E+06, - 0.98137E+06, 0.10692E+07, 0.11631E+07, 0.12636E+07, 0.13708E+07, - 0.14851E+07, 0.16069E+07, 0.17365E+07, 0.18742E+07, 0.20206E+07, - 0.21758E+07, 0.23404E+07, 0.25148E+07, 0.26992E+07, 0.28943E+07, - 0.31004E+07, 0.33179E+07, 0.35474E+07, 0.37892E+07, 0.40440E+07, - 0.43121E+07, 0.45940E+07, 0.48904E+07, 0.52017E+07, 0.55285E+07, - 0.58713E+07, 0.62306E+07, 0.66071E+07, 0.70014E+07, 0.74140E+07, - 0.78456E+07, 0.82967E+07, 0.87681E+07, 0.92604E+07, 0.97742E+07, - 0.10310E+08, 0.10869E+08, 0.11452E+08, 0.12059E+08, 0.12691E+08, - 0.13348E+08, 0.14033E+08, 0.14745E+08, 0.15484E+08, 0.16253E+08, - 0.17052E+08, 0.17881E+08, 0.18741E+08, 0.19634E+08, 0.20560E+08, - 0.21520E+08, 0.22515E+08, 0.23546E+08, 0.24613E+08, 0.25718E+08, - 0.26862E+08, 0.28046E+08, 0.29270E+08, 0.30536E+08, 0.31845E+08, - 0.33197E+08, 0.34594E+08, 0.36037E+08, 0.37527E+08, 0.39065E+08, - 0.40652E+08, 0.42289E+08, 0.43977E+08, 0.45719E+08, 0.47514E+08, - 0.49363E+08, 0.51270E+08, 0.53233E+08, 0.55255E+08, 0.57337E+08, - 0.59480E+08, 0.61686E+08, 0.63956E+08, 0.66290E+08, 0.68691E+08, - 0.71160E+08, 0.73699E+08, 0.76307E+08, 0.78988E+08, 0.81743E+08, - 0.84572E+08, 0.87478E+08, 0.90462E+08, 0.93525E+08, 0.96669E+08, - 0.99896E+08]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.11692E+05, 0.19707E+05, 0.29017E+05, 0.39482E+05, 0.51038E+05, 0.63680E+05, 0.77450E+05, + 0.92432E+05, 0.10873E+06, 0.12649E+06, 0.14584E+06, 0.16694E+06, 0.18996E+06, 0.21507E+06, + 0.24245E+06, 0.27229E+06, 0.30478E+06, 0.34013E+06, 0.37853E+06, 0.42020E+06, 0.46536E+06, + 0.51424E+06, 0.56708E+06, 0.62411E+06, 0.68559E+06, 0.75178E+06, 0.82296E+06, 0.89939E+06, + 0.98137E+06, 0.10692E+07, 0.11631E+07, 0.12636E+07, 0.13708E+07, 0.14851E+07, 0.16069E+07, + 0.17365E+07, 0.18742E+07, 0.20206E+07, 0.21758E+07, 0.23404E+07, 0.25148E+07, 0.26992E+07, + 0.28943E+07, 0.31004E+07, 0.33179E+07, 0.35474E+07, 0.37892E+07, 0.40440E+07, 0.43121E+07, + 0.45940E+07, 0.48904E+07, 0.52017E+07, 0.55285E+07, 0.58713E+07, 0.62306E+07, 0.66071E+07, + 0.70014E+07, 0.74140E+07, 0.78456E+07, 0.82967E+07, 0.87681E+07, 0.92604E+07, 0.97742E+07, + 0.10310E+08, 0.10869E+08, 0.11452E+08, 0.12059E+08, 0.12691E+08, 0.13348E+08, 0.14033E+08, + 0.14745E+08, 0.15484E+08, 0.16253E+08, 0.17052E+08, 0.17881E+08, 0.18741E+08, 0.19634E+08, + 0.20560E+08, 0.21520E+08, 0.22515E+08, 0.23546E+08, 0.24613E+08, 0.25718E+08, 0.26862E+08, + 0.28046E+08, 0.29270E+08, 0.30536E+08, 0.31845E+08, 0.33197E+08, 0.34594E+08, 0.36037E+08, + 0.37527E+08, 0.39065E+08, 0.40652E+08, 0.42289E+08, 0.43977E+08, 0.45719E+08, 0.47514E+08, + 0.49363E+08, 0.51270E+08, 0.53233E+08, 0.55255E+08, 0.57337E+08, 0.59480E+08, 0.61686E+08, + 0.63956E+08, 0.66290E+08, 0.68691E+08, 0.71160E+08, 0.73699E+08, 0.76307E+08, 0.78988E+08, + 0.81743E+08, 0.84572E+08, 0.87478E+08, 0.90462E+08, 0.93525E+08, 0.96669E+08, 0.99896E+08]) # --------------- O3 888: M = 3, I = 13 --------------------- M = 3 I = 13 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.36175E+03, 0.60978E+03, 0.89790E+03, - 0.12219E+04, 0.15802E+04, 0.19728E+04, 0.24016E+04, 0.28696E+04, - 0.33807E+04, 0.39394E+04, 0.45506E+04, 0.52196E+04, 0.59521E+04, - 0.67538E+04, 0.76308E+04, 0.85894E+04, 0.96361E+04, 0.10777E+05, - 0.12021E+05, 0.13373E+05, 0.14841E+05, 0.16434E+05, 0.18158E+05, - 0.20023E+05, 0.22037E+05, 0.24208E+05, 0.26547E+05, 0.29061E+05, - 0.31762E+05, 0.34659E+05, 0.37762E+05, 0.41083E+05, 0.44632E+05, - 0.48421E+05, 0.52462E+05, 0.56766E+05, 0.61346E+05, 0.66215E+05, - 0.71386E+05, 0.76873E+05, 0.82688E+05, 0.88848E+05, 0.95365E+05, - 0.10226E+06, 0.10954E+06, 0.11722E+06, 0.12532E+06, 0.13387E+06, - 0.14286E+06, 0.15233E+06, 0.16229E+06, 0.17275E+06, 0.18374E+06, - 0.19528E+06, 0.20737E+06, 0.22006E+06, 0.23335E+06, 0.24726E+06, - 0.26182E+06, 0.27705E+06, 0.29297E+06, 0.30960E+06, 0.32696E+06, - 0.34509E+06, 0.36399E+06, 0.38371E+06, 0.40425E+06, 0.42566E+06, - 0.44794E+06, 0.47114E+06, 0.49527E+06, 0.52036E+06, 0.54644E+06, - 0.57354E+06, 0.60169E+06, 0.63091E+06, 0.66124E+06, 0.69270E+06, - 0.72533E+06, 0.75916E+06, 0.79421E+06, 0.83053E+06, 0.86814E+06, - 0.90708E+06, 0.94737E+06, 0.98907E+06, 0.10322E+07, 0.10768E+07, - 0.11229E+07, 0.11705E+07, 0.12197E+07, 0.12705E+07, 0.13230E+07, - 0.13771E+07, 0.14330E+07, 0.14906E+07, 0.15501E+07, 0.16114E+07, - 0.16745E+07, 0.17397E+07, 0.18067E+07, 0.18759E+07, 0.19470E+07, - 0.20203E+07, 0.20957E+07, 0.21733E+07, 0.22532E+07, 0.23353E+07, - 0.24198E+07, 0.25067E+07, 0.25960E+07, 0.26878E+07, 0.27821E+07, - 0.28790E+07, 0.29785E+07, 0.30807E+07, 0.31857E+07, 0.32934E+07, - 0.34040E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.36175E+03, 0.60978E+03, 0.89790E+03, 0.12219E+04, 0.15802E+04, 0.19728E+04, 0.24016E+04, + 0.28696E+04, 0.33807E+04, 0.39394E+04, 0.45506E+04, 0.52196E+04, 0.59521E+04, 0.67538E+04, + 0.76308E+04, 0.85894E+04, 0.96361E+04, 0.10777E+05, 0.12021E+05, 0.13373E+05, 0.14841E+05, + 0.16434E+05, 0.18158E+05, 0.20023E+05, 0.22037E+05, 0.24208E+05, 0.26547E+05, 0.29061E+05, + 0.31762E+05, 0.34659E+05, 0.37762E+05, 0.41083E+05, 0.44632E+05, 0.48421E+05, 0.52462E+05, + 0.56766E+05, 0.61346E+05, 0.66215E+05, 0.71386E+05, 0.76873E+05, 0.82688E+05, 0.88848E+05, + 0.95365E+05, 0.10226E+06, 0.10954E+06, 0.11722E+06, 0.12532E+06, 0.13387E+06, 0.14286E+06, + 0.15233E+06, 0.16229E+06, 0.17275E+06, 0.18374E+06, 0.19528E+06, 0.20737E+06, 0.22006E+06, + 0.23335E+06, 0.24726E+06, 0.26182E+06, 0.27705E+06, 0.29297E+06, 0.30960E+06, 0.32696E+06, + 0.34509E+06, 0.36399E+06, 0.38371E+06, 0.40425E+06, 0.42566E+06, 0.44794E+06, 0.47114E+06, + 0.49527E+06, 0.52036E+06, 0.54644E+06, 0.57354E+06, 0.60169E+06, 0.63091E+06, 0.66124E+06, + 0.69270E+06, 0.72533E+06, 0.75916E+06, 0.79421E+06, 0.83053E+06, 0.86814E+06, 0.90708E+06, + 0.94737E+06, 0.98907E+06, 0.10322E+07, 0.10768E+07, 0.11229E+07, 0.11705E+07, 0.12197E+07, + 0.12705E+07, 0.13230E+07, 0.13771E+07, 0.14330E+07, 0.14906E+07, 0.15501E+07, 0.16114E+07, + 0.16745E+07, 0.17397E+07, 0.18067E+07, 0.18759E+07, 0.19470E+07, 0.20203E+07, 0.20957E+07, + 0.21733E+07, 0.22532E+07, 0.23353E+07, 0.24198E+07, 0.25067E+07, 0.25960E+07, 0.26878E+07, + 0.27821E+07, 0.28790E+07, 0.29785E+07, 0.30807E+07, 0.31857E+07, 0.32934E+07, 0.34040E+07]) # --------------- O3 887: M = 3, I = 14 --------------------- M = 3 I = 14 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.42000E+04, 0.70796E+04, 0.10424E+05, - 0.14186E+05, 0.18342E+05, 0.22896E+05, 0.27866E+05, 0.33285E+05, - 0.39199E+05, 0.45659E+05, 0.52720E+05, 0.60444E+05, 0.68895E+05, - 0.78139E+05, 0.88246E+05, 0.99288E+05, 0.11134E+06, 0.12447E+06, - 0.13877E+06, 0.15431E+06, 0.17119E+06, 0.18949E+06, 0.20930E+06, - 0.23071E+06, 0.25383E+06, 0.27875E+06, 0.30558E+06, 0.33442E+06, - 0.36539E+06, 0.39861E+06, 0.43418E+06, 0.47224E+06, 0.51291E+06, - 0.55632E+06, 0.60260E+06, 0.65189E+06, 0.70434E+06, 0.76008E+06, - 0.81927E+06, 0.88206E+06, 0.94862E+06, 0.10191E+07, 0.10937E+07, - 0.11725E+07, 0.12558E+07, 0.13436E+07, 0.14363E+07, 0.15340E+07, - 0.16368E+07, 0.17450E+07, 0.18588E+07, 0.19784E+07, 0.21040E+07, - 0.22358E+07, 0.23741E+07, 0.25190E+07, 0.26708E+07, 0.28297E+07, - 0.29961E+07, 0.31700E+07, 0.33518E+07, 0.35417E+07, 0.37400E+07, - 0.39469E+07, 0.41628E+07, 0.43878E+07, 0.46224E+07, 0.48667E+07, - 0.51210E+07, 0.53858E+07, 0.56611E+07, 0.59475E+07, 0.62451E+07, - 0.65544E+07, 0.68755E+07, 0.72089E+07, 0.75550E+07, 0.79139E+07, - 0.82861E+07, 0.86720E+07, 0.90719E+07, 0.94861E+07, 0.99151E+07, - 0.10359E+08, 0.10819E+08, 0.11294E+08, 0.11786E+08, 0.12294E+08, - 0.12820E+08, 0.13363E+08, 0.13924E+08, 0.14503E+08, 0.15101E+08, - 0.15719E+08, 0.16356E+08, 0.17013E+08, 0.17690E+08, 0.18389E+08, - 0.19109E+08, 0.19851E+08, 0.20616E+08, 0.21404E+08, 0.22215E+08, - 0.23050E+08, 0.23910E+08, 0.24794E+08, 0.25704E+08, 0.26640E+08, - 0.27603E+08, 0.28593E+08, 0.29610E+08, 0.30656E+08, 0.31731E+08, - 0.32835E+08, 0.33969E+08, 0.35133E+08, 0.36329E+08, 0.37556E+08, - 0.38816E+08]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.42000E+04, 0.70796E+04, 0.10424E+05, 0.14186E+05, 0.18342E+05, 0.22896E+05, 0.27866E+05, + 0.33285E+05, 0.39199E+05, 0.45659E+05, 0.52720E+05, 0.60444E+05, 0.68895E+05, 0.78139E+05, + 0.88246E+05, 0.99288E+05, 0.11134E+06, 0.12447E+06, 0.13877E+06, 0.15431E+06, 0.17119E+06, + 0.18949E+06, 0.20930E+06, 0.23071E+06, 0.25383E+06, 0.27875E+06, 0.30558E+06, 0.33442E+06, + 0.36539E+06, 0.39861E+06, 0.43418E+06, 0.47224E+06, 0.51291E+06, 0.55632E+06, 0.60260E+06, + 0.65189E+06, 0.70434E+06, 0.76008E+06, 0.81927E+06, 0.88206E+06, 0.94862E+06, 0.10191E+07, + 0.10937E+07, 0.11725E+07, 0.12558E+07, 0.13436E+07, 0.14363E+07, 0.15340E+07, 0.16368E+07, + 0.17450E+07, 0.18588E+07, 0.19784E+07, 0.21040E+07, 0.22358E+07, 0.23741E+07, 0.25190E+07, + 0.26708E+07, 0.28297E+07, 0.29961E+07, 0.31700E+07, 0.33518E+07, 0.35417E+07, 0.37400E+07, + 0.39469E+07, 0.41628E+07, 0.43878E+07, 0.46224E+07, 0.48667E+07, 0.51210E+07, 0.53858E+07, + 0.56611E+07, 0.59475E+07, 0.62451E+07, 0.65544E+07, 0.68755E+07, 0.72089E+07, 0.75550E+07, + 0.79139E+07, 0.82861E+07, 0.86720E+07, 0.90719E+07, 0.94861E+07, 0.99151E+07, 0.10359E+08, + 0.10819E+08, 0.11294E+08, 0.11786E+08, 0.12294E+08, 0.12820E+08, 0.13363E+08, 0.13924E+08, + 0.14503E+08, 0.15101E+08, 0.15719E+08, 0.16356E+08, 0.17013E+08, 0.17690E+08, 0.18389E+08, + 0.19109E+08, 0.19851E+08, 0.20616E+08, 0.21404E+08, 0.22215E+08, 0.23050E+08, 0.23910E+08, + 0.24794E+08, 0.25704E+08, 0.26640E+08, 0.27603E+08, 0.28593E+08, 0.29610E+08, 0.30656E+08, + 0.31731E+08, 0.32835E+08, 0.33969E+08, 0.35133E+08, 0.36329E+08, 0.37556E+08, 0.38816E+08]) # --------------- O3 878: M = 3, I = 15 --------------------- M = 3 I = 15 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.21250E+04, 0.35820E+04, 0.52744E+04, - 0.71778E+04, 0.92814E+04, 0.11586E+05, 0.14102E+05, 0.16845E+05, - 0.19839E+05, 0.23108E+05, 0.26680E+05, 0.30588E+05, 0.34861E+05, - 0.39534E+05, 0.44642E+05, 0.50219E+05, 0.56305E+05, 0.62937E+05, - 0.70155E+05, 0.78001E+05, 0.86516E+05, 0.95747E+05, 0.10574E+06, - 0.11653E+06, 0.12819E+06, 0.14075E+06, 0.15427E+06, 0.16881E+06, - 0.18441E+06, 0.20114E+06, 0.21906E+06, 0.23823E+06, 0.25871E+06, - 0.28056E+06, 0.30386E+06, 0.32867E+06, 0.35507E+06, 0.38312E+06, - 0.41291E+06, 0.44450E+06, 0.47799E+06, 0.51344E+06, 0.55095E+06, - 0.59060E+06, 0.63248E+06, 0.67667E+06, 0.72327E+06, 0.77238E+06, - 0.82409E+06, 0.87850E+06, 0.93571E+06, 0.99583E+06, 0.10590E+07, - 0.11252E+07, 0.11947E+07, 0.12675E+07, 0.13438E+07, 0.14237E+07, - 0.15072E+07, 0.15946E+07, 0.16859E+07, 0.17814E+07, 0.18810E+07, - 0.19849E+07, 0.20934E+07, 0.22064E+07, 0.23242E+07, 0.24469E+07, - 0.25747E+07, 0.27076E+07, 0.28459E+07, 0.29897E+07, 0.31391E+07, - 0.32944E+07, 0.34557E+07, 0.36231E+07, 0.37968E+07, 0.39770E+07, - 0.41639E+07, 0.43576E+07, 0.45583E+07, 0.47663E+07, 0.49816E+07, - 0.52045E+07, 0.54352E+07, 0.56739E+07, 0.59207E+07, 0.61759E+07, - 0.64396E+07, 0.67121E+07, 0.69936E+07, 0.72844E+07, 0.75845E+07, - 0.78943E+07, 0.82139E+07, 0.85436E+07, 0.88837E+07, 0.92342E+07, - 0.95956E+07, 0.99680E+07, 0.10352E+08, 0.10747E+08, 0.11154E+08, - 0.11573E+08, 0.12004E+08, 0.12448E+08, 0.12904E+08, 0.13374E+08, - 0.13857E+08, 0.14353E+08, 0.14864E+08, 0.15388E+08, 0.15927E+08, - 0.16481E+08, 0.17050E+08, 0.17634E+08, 0.18234E+08, 0.18849E+08, - 0.19481E+08]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.21250E+04, 0.35820E+04, 0.52744E+04, 0.71778E+04, 0.92814E+04, 0.11586E+05, 0.14102E+05, + 0.16845E+05, 0.19839E+05, 0.23108E+05, 0.26680E+05, 0.30588E+05, 0.34861E+05, 0.39534E+05, + 0.44642E+05, 0.50219E+05, 0.56305E+05, 0.62937E+05, 0.70155E+05, 0.78001E+05, 0.86516E+05, + 0.95747E+05, 0.10574E+06, 0.11653E+06, 0.12819E+06, 0.14075E+06, 0.15427E+06, 0.16881E+06, + 0.18441E+06, 0.20114E+06, 0.21906E+06, 0.23823E+06, 0.25871E+06, 0.28056E+06, 0.30386E+06, + 0.32867E+06, 0.35507E+06, 0.38312E+06, 0.41291E+06, 0.44450E+06, 0.47799E+06, 0.51344E+06, + 0.55095E+06, 0.59060E+06, 0.63248E+06, 0.67667E+06, 0.72327E+06, 0.77238E+06, 0.82409E+06, + 0.87850E+06, 0.93571E+06, 0.99583E+06, 0.10590E+07, 0.11252E+07, 0.11947E+07, 0.12675E+07, + 0.13438E+07, 0.14237E+07, 0.15072E+07, 0.15946E+07, 0.16859E+07, 0.17814E+07, 0.18810E+07, + 0.19849E+07, 0.20934E+07, 0.22064E+07, 0.23242E+07, 0.24469E+07, 0.25747E+07, 0.27076E+07, + 0.28459E+07, 0.29897E+07, 0.31391E+07, 0.32944E+07, 0.34557E+07, 0.36231E+07, 0.37968E+07, + 0.39770E+07, 0.41639E+07, 0.43576E+07, 0.45583E+07, 0.47663E+07, 0.49816E+07, 0.52045E+07, + 0.54352E+07, 0.56739E+07, 0.59207E+07, 0.61759E+07, 0.64396E+07, 0.67121E+07, 0.69936E+07, + 0.72844E+07, 0.75845E+07, 0.78943E+07, 0.82139E+07, 0.85436E+07, 0.88837E+07, 0.92342E+07, + 0.95956E+07, 0.99680E+07, 0.10352E+08, 0.10747E+08, 0.11154E+08, 0.11573E+08, 0.12004E+08, + 0.12448E+08, 0.12904E+08, 0.13374E+08, 0.13857E+08, 0.14353E+08, 0.14864E+08, 0.15388E+08, + 0.15927E+08, 0.16481E+08, 0.17050E+08, 0.17634E+08, 0.18234E+08, 0.18849E+08, 0.19481E+08]) # --------------- O3 778: M = 3, I = 16 --------------------- M = 3 I = 16 TIPS_GSI_HASH[(M, I)] = __FloatType__(36.) -TIPS_ISO_HASH[(M, I)] = float32([0.24692E+05, 0.41621E+05, 0.61284E+05, - 0.83394E+05, 0.10782E+06, 0.13457E+06, 0.16375E+06, 0.19554E+06, - 0.23020E+06, 0.26801E+06, 0.30930E+06, 0.35443E+06, 0.40375E+06, - 0.45763E+06, 0.51650E+06, 0.58075E+06, 0.65080E+06, 0.72711E+06, - 0.81012E+06, 0.90030E+06, 0.99815E+06, 0.11042E+07, 0.12189E+07, - 0.13428E+07, 0.14765E+07, 0.16206E+07, 0.17757E+07, 0.19423E+07, - 0.21212E+07, 0.23129E+07, 0.25181E+07, 0.27377E+07, 0.29721E+07, - 0.32223E+07, 0.34890E+07, 0.37729E+07, 0.40750E+07, 0.43959E+07, - 0.47365E+07, 0.50978E+07, 0.54807E+07, 0.58860E+07, 0.63147E+07, - 0.67678E+07, 0.72463E+07, 0.77512E+07, 0.82836E+07, 0.88445E+07, - 0.94351E+07, 0.10056E+08, 0.10710E+08, 0.11396E+08, 0.12117E+08, - 0.12873E+08, 0.13666E+08, 0.14497E+08, 0.15367E+08, 0.16279E+08, - 0.17232E+08, 0.18229E+08, 0.19271E+08, 0.20359E+08, 0.21495E+08, - 0.22681E+08, 0.23917E+08, 0.25206E+08, 0.26549E+08, 0.27948E+08, - 0.29404E+08, 0.30920E+08, 0.32496E+08, 0.34135E+08, 0.35838E+08, - 0.37608E+08, 0.39445E+08, 0.41353E+08, 0.43332E+08, 0.45385E+08, - 0.47514E+08, 0.49721E+08, 0.52007E+08, 0.54376E+08, 0.56829E+08, - 0.59367E+08, 0.61995E+08, 0.64712E+08, 0.67523E+08, 0.70429E+08, - 0.73432E+08, 0.76535E+08, 0.79740E+08, 0.83050E+08, 0.86467E+08, - 0.89993E+08, 0.93632E+08, 0.97385E+08, 0.10126E+09, 0.10525E+09, - 0.10936E+09, 0.11360E+09, 0.11796E+09, 0.12246E+09, 0.12709E+09, - 0.13186E+09, 0.13677E+09, 0.14182E+09, 0.14701E+09, 0.15236E+09, - 0.15785E+09, 0.16350E+09, 0.16931E+09, 0.17528E+09, 0.18141E+09, - 0.18771E+09, 0.19418E+09, 0.20082E+09, 0.20764E+09, 0.21465E+09, - 0.22183E+09]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.24692E+05, 0.41621E+05, 0.61284E+05, 0.83394E+05, 0.10782E+06, 0.13457E+06, 0.16375E+06, + 0.19554E+06, 0.23020E+06, 0.26801E+06, 0.30930E+06, 0.35443E+06, 0.40375E+06, 0.45763E+06, + 0.51650E+06, 0.58075E+06, 0.65080E+06, 0.72711E+06, 0.81012E+06, 0.90030E+06, 0.99815E+06, + 0.11042E+07, 0.12189E+07, 0.13428E+07, 0.14765E+07, 0.16206E+07, 0.17757E+07, 0.19423E+07, + 0.21212E+07, 0.23129E+07, 0.25181E+07, 0.27377E+07, 0.29721E+07, 0.32223E+07, 0.34890E+07, + 0.37729E+07, 0.40750E+07, 0.43959E+07, 0.47365E+07, 0.50978E+07, 0.54807E+07, 0.58860E+07, + 0.63147E+07, 0.67678E+07, 0.72463E+07, 0.77512E+07, 0.82836E+07, 0.88445E+07, 0.94351E+07, + 0.10056E+08, 0.10710E+08, 0.11396E+08, 0.12117E+08, 0.12873E+08, 0.13666E+08, 0.14497E+08, + 0.15367E+08, 0.16279E+08, 0.17232E+08, 0.18229E+08, 0.19271E+08, 0.20359E+08, 0.21495E+08, + 0.22681E+08, 0.23917E+08, 0.25206E+08, 0.26549E+08, 0.27948E+08, 0.29404E+08, 0.30920E+08, + 0.32496E+08, 0.34135E+08, 0.35838E+08, 0.37608E+08, 0.39445E+08, 0.41353E+08, 0.43332E+08, + 0.45385E+08, 0.47514E+08, 0.49721E+08, 0.52007E+08, 0.54376E+08, 0.56829E+08, 0.59367E+08, + 0.61995E+08, 0.64712E+08, 0.67523E+08, 0.70429E+08, 0.73432E+08, 0.76535E+08, 0.79740E+08, + 0.83050E+08, 0.86467E+08, 0.89993E+08, 0.93632E+08, 0.97385E+08, 0.10126E+09, 0.10525E+09, + 0.10936E+09, 0.11360E+09, 0.11796E+09, 0.12246E+09, 0.12709E+09, 0.13186E+09, 0.13677E+09, + 0.14182E+09, 0.14701E+09, 0.15236E+09, 0.15785E+09, 0.16350E+09, 0.16931E+09, 0.17528E+09, + 0.18141E+09, 0.18771E+09, 0.19418E+09, 0.20082E+09, 0.20764E+09, 0.21465E+09, 0.22183E+09]) # --------------- O3 787: M = 3, I = 17 --------------------- M = 3 I = 17 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.12211E+05, 0.20582E+05, 0.30305E+05, - 0.41237E+05, 0.53314E+05, 0.66536E+05, 0.80957E+05, 0.96672E+05, - 0.11380E+06, 0.13250E+06, 0.15292E+06, 0.17524E+06, 0.19965E+06, - 0.22632E+06, 0.25546E+06, 0.28728E+06, 0.32199E+06, 0.35980E+06, - 0.40094E+06, 0.44565E+06, 0.49417E+06, 0.54676E+06, 0.60366E+06, - 0.66516E+06, 0.73152E+06, 0.80305E+06, 0.88002E+06, 0.96276E+06, - 0.10516E+07, 0.11468E+07, 0.12488E+07, 0.13578E+07, 0.14743E+07, - 0.15987E+07, 0.17312E+07, 0.18723E+07, 0.20225E+07, 0.21820E+07, - 0.23514E+07, 0.25310E+07, 0.27214E+07, 0.29230E+07, 0.31362E+07, - 0.33616E+07, 0.35997E+07, 0.38509E+07, 0.41158E+07, 0.43949E+07, - 0.46887E+07, 0.49980E+07, 0.53231E+07, 0.56647E+07, 0.60234E+07, - 0.63998E+07, 0.67946E+07, 0.72084E+07, 0.76418E+07, 0.80955E+07, - 0.85702E+07, 0.90666E+07, 0.95854E+07, 0.10127E+08, 0.10693E+08, - 0.11284E+08, 0.11900E+08, 0.12542E+08, 0.13211E+08, 0.13907E+08, - 0.14633E+08, 0.15388E+08, 0.16173E+08, 0.16990E+08, 0.17838E+08, - 0.18720E+08, 0.19636E+08, 0.20586E+08, 0.21573E+08, 0.22596E+08, - 0.23657E+08, 0.24757E+08, 0.25896E+08, 0.27077E+08, 0.28299E+08, - 0.29565E+08, 0.30874E+08, 0.32229E+08, 0.33630E+08, 0.35079E+08, - 0.36576E+08, 0.38123E+08, 0.39721E+08, 0.41371E+08, 0.43075E+08, - 0.44833E+08, 0.46647E+08, 0.48518E+08, 0.50448E+08, 0.52438E+08, - 0.54489E+08, 0.56603E+08, 0.58780E+08, 0.61023E+08, 0.63332E+08, - 0.65710E+08, 0.68157E+08, 0.70676E+08, 0.73266E+08, 0.75931E+08, - 0.78672E+08, 0.81490E+08, 0.84386E+08, 0.87363E+08, 0.90422E+08, - 0.93564E+08, 0.96791E+08, 0.10011E+09, 0.10351E+09, 0.10700E+09, - 0.11059E+09]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.12211E+05, 0.20582E+05, 0.30305E+05, 0.41237E+05, 0.53314E+05, 0.66536E+05, 0.80957E+05, + 0.96672E+05, 0.11380E+06, 0.13250E+06, 0.15292E+06, 0.17524E+06, 0.19965E+06, 0.22632E+06, + 0.25546E+06, 0.28728E+06, 0.32199E+06, 0.35980E+06, 0.40094E+06, 0.44565E+06, 0.49417E+06, + 0.54676E+06, 0.60366E+06, 0.66516E+06, 0.73152E+06, 0.80305E+06, 0.88002E+06, 0.96276E+06, + 0.10516E+07, 0.11468E+07, 0.12488E+07, 0.13578E+07, 0.14743E+07, 0.15987E+07, 0.17312E+07, + 0.18723E+07, 0.20225E+07, 0.21820E+07, 0.23514E+07, 0.25310E+07, 0.27214E+07, 0.29230E+07, + 0.31362E+07, 0.33616E+07, 0.35997E+07, 0.38509E+07, 0.41158E+07, 0.43949E+07, 0.46887E+07, + 0.49980E+07, 0.53231E+07, 0.56647E+07, 0.60234E+07, 0.63998E+07, 0.67946E+07, 0.72084E+07, + 0.76418E+07, 0.80955E+07, 0.85702E+07, 0.90666E+07, 0.95854E+07, 0.10127E+08, 0.10693E+08, + 0.11284E+08, 0.11900E+08, 0.12542E+08, 0.13211E+08, 0.13907E+08, 0.14633E+08, 0.15388E+08, + 0.16173E+08, 0.16990E+08, 0.17838E+08, 0.18720E+08, 0.19636E+08, 0.20586E+08, 0.21573E+08, + 0.22596E+08, 0.23657E+08, 0.24757E+08, 0.25896E+08, 0.27077E+08, 0.28299E+08, 0.29565E+08, + 0.30874E+08, 0.32229E+08, 0.33630E+08, 0.35079E+08, 0.36576E+08, 0.38123E+08, 0.39721E+08, + 0.41371E+08, 0.43075E+08, 0.44833E+08, 0.46647E+08, 0.48518E+08, 0.50448E+08, 0.52438E+08, + 0.54489E+08, 0.56603E+08, 0.58780E+08, 0.61023E+08, 0.63332E+08, 0.65710E+08, 0.68157E+08, + 0.70676E+08, 0.73266E+08, 0.75931E+08, 0.78672E+08, 0.81490E+08, 0.84386E+08, 0.87363E+08, + 0.90422E+08, 0.93564E+08, 0.96791E+08, 0.10011E+09, 0.10351E+09, 0.10700E+09, 0.11059E+09]) # --------------- O3 777: M = 3, I = 18 --------------------- M = 3 I = 18 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.71750E+05, 0.12094E+06, 0.17807E+06, - 0.24230E+06, 0.31324E+06, 0.39088E+06, 0.47550E+06, 0.56764E+06, - 0.66800E+06, 0.77740E+06, 0.89677E+06, 0.10271E+07, 0.11694E+07, - 0.13249E+07, 0.14945E+07, 0.16796E+07, 0.18813E+07, 0.21009E+07, - 0.23396E+07, 0.25989E+07, 0.28801E+07, 0.31847E+07, 0.35140E+07, - 0.38698E+07, 0.42535E+07, 0.46669E+07, 0.51115E+07, 0.55893E+07, - 0.61019E+07, 0.66513E+07, 0.72393E+07, 0.78680E+07, 0.85395E+07, - 0.92558E+07, 0.10019E+08, 0.10832E+08, 0.11696E+08, 0.12614E+08, - 0.13588E+08, 0.14621E+08, 0.15716E+08, 0.16875E+08, 0.18100E+08, - 0.19395E+08, 0.20762E+08, 0.22205E+08, 0.23726E+08, 0.25328E+08, - 0.27015E+08, 0.28789E+08, 0.30654E+08, 0.32614E+08, 0.34671E+08, - 0.36830E+08, 0.39093E+08, 0.41465E+08, 0.43949E+08, 0.46549E+08, - 0.49269E+08, 0.52112E+08, 0.55084E+08, 0.58188E+08, 0.61428E+08, - 0.64809E+08, 0.68335E+08, 0.72010E+08, 0.75840E+08, 0.79828E+08, - 0.83979E+08, 0.88299E+08, 0.92792E+08, 0.97463E+08, 0.10232E+09, - 0.10736E+09, 0.11260E+09, 0.11803E+09, 0.12367E+09, 0.12952E+09, - 0.13559E+09, 0.14187E+09, 0.14839E+09, 0.15513E+09, 0.16212E+09, - 0.16935E+09, 0.17683E+09, 0.18457E+09, 0.19257E+09, 0.20085E+09, - 0.20940E+09, 0.21824E+09, 0.22736E+09, 0.23678E+09, 0.24651E+09, - 0.25655E+09, 0.26691E+09, 0.27759E+09, 0.28861E+09, 0.29997E+09, - 0.31167E+09, 0.32374E+09, 0.33616E+09, 0.34896E+09, 0.36214E+09, - 0.37571E+09, 0.38967E+09, 0.40404E+09, 0.41882E+09, 0.43403E+09, - 0.44966E+09, 0.46573E+09, 0.48226E+09, 0.49923E+09, 0.51668E+09, - 0.53460E+09, 0.55301E+09, 0.57191E+09, 0.59131E+09, 0.61123E+09, - 0.63167E+09]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.71750E+05, 0.12094E+06, 0.17807E+06, 0.24230E+06, 0.31324E+06, 0.39088E+06, 0.47550E+06, + 0.56764E+06, 0.66800E+06, 0.77740E+06, 0.89677E+06, 0.10271E+07, 0.11694E+07, 0.13249E+07, + 0.14945E+07, 0.16796E+07, 0.18813E+07, 0.21009E+07, 0.23396E+07, 0.25989E+07, 0.28801E+07, + 0.31847E+07, 0.35140E+07, 0.38698E+07, 0.42535E+07, 0.46669E+07, 0.51115E+07, 0.55893E+07, + 0.61019E+07, 0.66513E+07, 0.72393E+07, 0.78680E+07, 0.85395E+07, 0.92558E+07, 0.10019E+08, + 0.10832E+08, 0.11696E+08, 0.12614E+08, 0.13588E+08, 0.14621E+08, 0.15716E+08, 0.16875E+08, + 0.18100E+08, 0.19395E+08, 0.20762E+08, 0.22205E+08, 0.23726E+08, 0.25328E+08, 0.27015E+08, + 0.28789E+08, 0.30654E+08, 0.32614E+08, 0.34671E+08, 0.36830E+08, 0.39093E+08, 0.41465E+08, + 0.43949E+08, 0.46549E+08, 0.49269E+08, 0.52112E+08, 0.55084E+08, 0.58188E+08, 0.61428E+08, + 0.64809E+08, 0.68335E+08, 0.72010E+08, 0.75840E+08, 0.79828E+08, 0.83979E+08, 0.88299E+08, + 0.92792E+08, 0.97463E+08, 0.10232E+09, 0.10736E+09, 0.11260E+09, 0.11803E+09, 0.12367E+09, + 0.12952E+09, 0.13559E+09, 0.14187E+09, 0.14839E+09, 0.15513E+09, 0.16212E+09, 0.16935E+09, + 0.17683E+09, 0.18457E+09, 0.19257E+09, 0.20085E+09, 0.20940E+09, 0.21824E+09, 0.22736E+09, + 0.23678E+09, 0.24651E+09, 0.25655E+09, 0.26691E+09, 0.27759E+09, 0.28861E+09, 0.29997E+09, + 0.31167E+09, 0.32374E+09, 0.33616E+09, 0.34896E+09, 0.36214E+09, 0.37571E+09, 0.38967E+09, + 0.40404E+09, 0.41882E+09, 0.43403E+09, 0.44966E+09, 0.46573E+09, 0.48226E+09, 0.49923E+09, + 0.51668E+09, 0.53460E+09, 0.55301E+09, 0.57191E+09, 0.59131E+09, 0.61123E+09, 0.63167E+09]) # --------------- N2O 446: M = 4, I = 1 --------------------- M = 4 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(9.) -TIPS_ISO_HASH[(M, I)] = float32([0.89943E+03, 0.12734E+04, 0.16489E+04, - 0.20293E+04, 0.24205E+04, 0.28289E+04, 0.32609E+04, 0.37222E+04, - 0.42180E+04, 0.47529E+04, 0.53312E+04, 0.59572E+04, 0.66348E+04, - 0.73683E+04, 0.81616E+04, 0.90190E+04, 0.99450E+04, 0.10944E+05, - 0.12021E+05, 0.13180E+05, 0.14426E+05, 0.15766E+05, 0.17203E+05, - 0.18745E+05, 0.20396E+05, 0.22162E+05, 0.24051E+05, 0.26069E+05, - 0.28222E+05, 0.30517E+05, 0.32962E+05, 0.35564E+05, 0.38331E+05, - 0.41271E+05, 0.44393E+05, 0.47704E+05, 0.51214E+05, 0.54932E+05, - 0.58868E+05, 0.63030E+05, 0.67429E+05, 0.72075E+05, 0.76979E+05, - 0.82151E+05, 0.87604E+05, 0.93348E+05, 0.99395E+05, 0.10576E+06, - 0.11245E+06, 0.11948E+06, 0.12686E+06, 0.13461E+06, 0.14275E+06, - 0.15128E+06, 0.16021E+06, 0.16958E+06, 0.17938E+06, 0.18964E+06, - 0.20037E+06, 0.21159E+06, 0.22331E+06, 0.23556E+06, 0.24834E+06, - 0.26169E+06, 0.27561E+06, 0.29012E+06, 0.30525E+06, 0.32101E+06, - 0.33743E+06, 0.35452E+06, 0.37230E+06, 0.39080E+06, 0.41004E+06, - 0.43004E+06, 0.45082E+06, 0.47241E+06, 0.49483E+06, 0.51810E+06, - 0.54225E+06, 0.56730E+06, 0.59329E+06, 0.62022E+06, 0.64814E+06, - 0.67707E+06, 0.70703E+06, 0.73806E+06, 0.77018E+06, 0.80342E+06, - 0.83781E+06, 0.87338E+06, 0.91016E+06, 0.94818E+06, 0.98748E+06, - 0.10281E+07, 0.10700E+07, 0.11133E+07, 0.11581E+07, 0.12042E+07, - 0.12519E+07, 0.13010E+07, 0.13517E+07, 0.14040E+07, 0.14579E+07, - 0.15134E+07, 0.15707E+07, 0.16297E+07, 0.16905E+07, 0.17530E+07, - 0.18175E+07, 0.18838E+07, 0.19521E+07, 0.20224E+07, 0.20947E+07, - 0.21690E+07, 0.22455E+07, 0.23242E+07, 0.24050E+07, 0.24881E+07, - 0.25735E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.89943E+03, 0.12734E+04, 0.16489E+04, 0.20293E+04, 0.24205E+04, 0.28289E+04, 0.32609E+04, + 0.37222E+04, 0.42180E+04, 0.47529E+04, 0.53312E+04, 0.59572E+04, 0.66348E+04, 0.73683E+04, + 0.81616E+04, 0.90190E+04, 0.99450E+04, 0.10944E+05, 0.12021E+05, 0.13180E+05, 0.14426E+05, + 0.15766E+05, 0.17203E+05, 0.18745E+05, 0.20396E+05, 0.22162E+05, 0.24051E+05, 0.26069E+05, + 0.28222E+05, 0.30517E+05, 0.32962E+05, 0.35564E+05, 0.38331E+05, 0.41271E+05, 0.44393E+05, + 0.47704E+05, 0.51214E+05, 0.54932E+05, 0.58868E+05, 0.63030E+05, 0.67429E+05, 0.72075E+05, + 0.76979E+05, 0.82151E+05, 0.87604E+05, 0.93348E+05, 0.99395E+05, 0.10576E+06, 0.11245E+06, + 0.11948E+06, 0.12686E+06, 0.13461E+06, 0.14275E+06, 0.15128E+06, 0.16021E+06, 0.16958E+06, + 0.17938E+06, 0.18964E+06, 0.20037E+06, 0.21159E+06, 0.22331E+06, 0.23556E+06, 0.24834E+06, + 0.26169E+06, 0.27561E+06, 0.29012E+06, 0.30525E+06, 0.32101E+06, 0.33743E+06, 0.35452E+06, + 0.37230E+06, 0.39080E+06, 0.41004E+06, 0.43004E+06, 0.45082E+06, 0.47241E+06, 0.49483E+06, + 0.51810E+06, 0.54225E+06, 0.56730E+06, 0.59329E+06, 0.62022E+06, 0.64814E+06, 0.67707E+06, + 0.70703E+06, 0.73806E+06, 0.77018E+06, 0.80342E+06, 0.83781E+06, 0.87338E+06, 0.91016E+06, + 0.94818E+06, 0.98748E+06, 0.10281E+07, 0.10700E+07, 0.11133E+07, 0.11581E+07, 0.12042E+07, + 0.12519E+07, 0.13010E+07, 0.13517E+07, 0.14040E+07, 0.14579E+07, 0.15134E+07, 0.15707E+07, + 0.16297E+07, 0.16905E+07, 0.17530E+07, 0.18175E+07, 0.18838E+07, 0.19521E+07, 0.20224E+07, + 0.20947E+07, 0.21690E+07, 0.22455E+07, 0.23242E+07, 0.24050E+07, 0.24881E+07, 0.25735E+07]) # --------------- N2O 456: M = 4, I = 2 --------------------- M = 4 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.59966E+03, 0.84903E+03, 0.10995E+04, - 0.13538E+04, 0.16158E+04, 0.18903E+04, 0.21815E+04, 0.24934E+04, - 0.28295E+04, 0.31927E+04, 0.35862E+04, 0.40128E+04, 0.44752E+04, - 0.49763E+04, 0.55189E+04, 0.61059E+04, 0.67404E+04, 0.74256E+04, - 0.81646E+04, 0.89609E+04, 0.98180E+04, 0.10740E+05, 0.11729E+05, - 0.12791E+05, 0.13930E+05, 0.15149E+05, 0.16453E+05, 0.17847E+05, - 0.19335E+05, 0.20922E+05, 0.22614E+05, 0.24416E+05, 0.26333E+05, - 0.28371E+05, 0.30535E+05, 0.32833E+05, 0.35269E+05, 0.37851E+05, - 0.40585E+05, 0.43478E+05, 0.46537E+05, 0.49769E+05, 0.53182E+05, - 0.56783E+05, 0.60580E+05, 0.64582E+05, 0.68796E+05, 0.73232E+05, - 0.77898E+05, 0.82803E+05, 0.87957E+05, 0.93369E+05, 0.99048E+05, - 0.10501E+06, 0.11125E+06, 0.11780E+06, 0.12465E+06, 0.13182E+06, - 0.13933E+06, 0.14718E+06, 0.15539E+06, 0.16396E+06, 0.17291E+06, - 0.18226E+06, 0.19201E+06, 0.20218E+06, 0.21278E+06, 0.22383E+06, - 0.23534E+06, 0.24733E+06, 0.25980E+06, 0.27278E+06, 0.28628E+06, - 0.30032E+06, 0.31491E+06, 0.33007E+06, 0.34581E+06, 0.36216E+06, - 0.37912E+06, 0.39673E+06, 0.41499E+06, 0.43392E+06, 0.45355E+06, - 0.47389E+06, 0.49496E+06, 0.51678E+06, 0.53937E+06, 0.56276E+06, - 0.58695E+06, 0.61199E+06, 0.63788E+06, 0.66464E+06, 0.69231E+06, - 0.72090E+06, 0.75044E+06, 0.78094E+06, 0.81244E+06, 0.84496E+06, - 0.87853E+06, 0.91316E+06, 0.94889E+06, 0.98573E+06, 0.10237E+07, - 0.10629E+07, 0.11033E+07, 0.11449E+07, 0.11877E+07, 0.12319E+07, - 0.12773E+07, 0.13241E+07, 0.13723E+07, 0.14219E+07, 0.14729E+07, - 0.15254E+07, 0.15793E+07, 0.16349E+07, 0.16919E+07, 0.17506E+07, - 0.18109E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.59966E+03, 0.84903E+03, 0.10995E+04, 0.13538E+04, 0.16158E+04, 0.18903E+04, 0.21815E+04, + 0.24934E+04, 0.28295E+04, 0.31927E+04, 0.35862E+04, 0.40128E+04, 0.44752E+04, 0.49763E+04, + 0.55189E+04, 0.61059E+04, 0.67404E+04, 0.74256E+04, 0.81646E+04, 0.89609E+04, 0.98180E+04, + 0.10740E+05, 0.11729E+05, 0.12791E+05, 0.13930E+05, 0.15149E+05, 0.16453E+05, 0.17847E+05, + 0.19335E+05, 0.20922E+05, 0.22614E+05, 0.24416E+05, 0.26333E+05, 0.28371E+05, 0.30535E+05, + 0.32833E+05, 0.35269E+05, 0.37851E+05, 0.40585E+05, 0.43478E+05, 0.46537E+05, 0.49769E+05, + 0.53182E+05, 0.56783E+05, 0.60580E+05, 0.64582E+05, 0.68796E+05, 0.73232E+05, 0.77898E+05, + 0.82803E+05, 0.87957E+05, 0.93369E+05, 0.99048E+05, 0.10501E+06, 0.11125E+06, 0.11780E+06, + 0.12465E+06, 0.13182E+06, 0.13933E+06, 0.14718E+06, 0.15539E+06, 0.16396E+06, 0.17291E+06, + 0.18226E+06, 0.19201E+06, 0.20218E+06, 0.21278E+06, 0.22383E+06, 0.23534E+06, 0.24733E+06, + 0.25980E+06, 0.27278E+06, 0.28628E+06, 0.30032E+06, 0.31491E+06, 0.33007E+06, 0.34581E+06, + 0.36216E+06, 0.37912E+06, 0.39673E+06, 0.41499E+06, 0.43392E+06, 0.45355E+06, 0.47389E+06, + 0.49496E+06, 0.51678E+06, 0.53937E+06, 0.56276E+06, 0.58695E+06, 0.61199E+06, 0.63788E+06, + 0.66464E+06, 0.69231E+06, 0.72090E+06, 0.75044E+06, 0.78094E+06, 0.81244E+06, 0.84496E+06, + 0.87853E+06, 0.91316E+06, 0.94889E+06, 0.98573E+06, 0.10237E+07, 0.10629E+07, 0.11033E+07, + 0.11449E+07, 0.11877E+07, 0.12319E+07, 0.12773E+07, 0.13241E+07, 0.13723E+07, 0.14219E+07, + 0.14729E+07, 0.15254E+07, 0.15793E+07, 0.16349E+07, 0.16919E+07, 0.17506E+07, 0.18109E+07]) # --------------- N2O 546: M = 4, I = 3 --------------------- M = 4 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.62051E+03, 0.87856E+03, 0.11377E+04, - 0.14003E+04, 0.16705E+04, 0.19529E+04, 0.22518E+04, 0.25713E+04, - 0.29149E+04, 0.32859E+04, 0.36873E+04, 0.41220E+04, 0.45929E+04, - 0.51028E+04, 0.56547E+04, 0.62515E+04, 0.68963E+04, 0.75923E+04, - 0.83428E+04, 0.91511E+04, 0.10021E+05, 0.10956E+05, 0.11960E+05, - 0.13036E+05, 0.14190E+05, 0.15425E+05, 0.16746E+05, 0.18158E+05, - 0.19664E+05, 0.21271E+05, 0.22984E+05, 0.24806E+05, 0.26745E+05, - 0.28806E+05, 0.30995E+05, 0.33317E+05, 0.35780E+05, 0.38389E+05, - 0.41151E+05, 0.44073E+05, 0.47162E+05, 0.50425E+05, 0.53871E+05, - 0.57505E+05, 0.61338E+05, 0.65375E+05, 0.69628E+05, 0.74102E+05, - 0.78808E+05, 0.83755E+05, 0.88951E+05, 0.94407E+05, 0.10013E+06, - 0.10614E+06, 0.11243E+06, 0.11902E+06, 0.12593E+06, 0.13316E+06, - 0.14072E+06, 0.14862E+06, 0.15689E+06, 0.16552E+06, 0.17453E+06, - 0.18394E+06, 0.19376E+06, 0.20399E+06, 0.21466E+06, 0.22578E+06, - 0.23737E+06, 0.24942E+06, 0.26198E+06, 0.27503E+06, 0.28861E+06, - 0.30273E+06, 0.31741E+06, 0.33265E+06, 0.34848E+06, 0.36492E+06, - 0.38197E+06, 0.39967E+06, 0.41803E+06, 0.43706E+06, 0.45679E+06, - 0.47723E+06, 0.49840E+06, 0.52033E+06, 0.54303E+06, 0.56653E+06, - 0.59084E+06, 0.61599E+06, 0.64200E+06, 0.66888E+06, 0.69667E+06, - 0.72539E+06, 0.75506E+06, 0.78569E+06, 0.81733E+06, 0.84998E+06, - 0.88369E+06, 0.91846E+06, 0.95433E+06, 0.99132E+06, 0.10295E+07, - 0.10688E+07, 0.11093E+07, 0.11511E+07, 0.11941E+07, 0.12384E+07, - 0.12840E+07, 0.13310E+07, 0.13793E+07, 0.14291E+07, 0.14803E+07, - 0.15329E+07, 0.15871E+07, 0.16428E+07, 0.17000E+07, 0.17589E+07, - 0.18194E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.62051E+03, 0.87856E+03, 0.11377E+04, 0.14003E+04, 0.16705E+04, 0.19529E+04, 0.22518E+04, + 0.25713E+04, 0.29149E+04, 0.32859E+04, 0.36873E+04, 0.41220E+04, 0.45929E+04, 0.51028E+04, + 0.56547E+04, 0.62515E+04, 0.68963E+04, 0.75923E+04, 0.83428E+04, 0.91511E+04, 0.10021E+05, + 0.10956E+05, 0.11960E+05, 0.13036E+05, 0.14190E+05, 0.15425E+05, 0.16746E+05, 0.18158E+05, + 0.19664E+05, 0.21271E+05, 0.22984E+05, 0.24806E+05, 0.26745E+05, 0.28806E+05, 0.30995E+05, + 0.33317E+05, 0.35780E+05, 0.38389E+05, 0.41151E+05, 0.44073E+05, 0.47162E+05, 0.50425E+05, + 0.53871E+05, 0.57505E+05, 0.61338E+05, 0.65375E+05, 0.69628E+05, 0.74102E+05, 0.78808E+05, + 0.83755E+05, 0.88951E+05, 0.94407E+05, 0.10013E+06, 0.10614E+06, 0.11243E+06, 0.11902E+06, + 0.12593E+06, 0.13316E+06, 0.14072E+06, 0.14862E+06, 0.15689E+06, 0.16552E+06, 0.17453E+06, + 0.18394E+06, 0.19376E+06, 0.20399E+06, 0.21466E+06, 0.22578E+06, 0.23737E+06, 0.24942E+06, + 0.26198E+06, 0.27503E+06, 0.28861E+06, 0.30273E+06, 0.31741E+06, 0.33265E+06, 0.34848E+06, + 0.36492E+06, 0.38197E+06, 0.39967E+06, 0.41803E+06, 0.43706E+06, 0.45679E+06, 0.47723E+06, + 0.49840E+06, 0.52033E+06, 0.54303E+06, 0.56653E+06, 0.59084E+06, 0.61599E+06, 0.64200E+06, + 0.66888E+06, 0.69667E+06, 0.72539E+06, 0.75506E+06, 0.78569E+06, 0.81733E+06, 0.84998E+06, + 0.88369E+06, 0.91846E+06, 0.95433E+06, 0.99132E+06, 0.10295E+07, 0.10688E+07, 0.11093E+07, + 0.11511E+07, 0.11941E+07, 0.12384E+07, 0.12840E+07, 0.13310E+07, 0.13793E+07, 0.14291E+07, + 0.14803E+07, 0.15329E+07, 0.15871E+07, 0.16428E+07, 0.17000E+07, 0.17589E+07, 0.18194E+07]) # --------------- N2O 448: M = 4, I = 4 --------------------- M = 4 I = 4 TIPS_GSI_HASH[(M, I)] = __FloatType__(9.) -TIPS_ISO_HASH[(M, I)] = float32([0.95253E+03, 0.13487E+04, 0.17465E+04, - 0.21498E+04, 0.25648E+04, 0.29986E+04, 0.34580E+04, 0.39493E+04, - 0.44779E+04, 0.50488E+04, 0.56669E+04, 0.63366E+04, 0.70625E+04, - 0.78488E+04, 0.87003E+04, 0.96216E+04, 0.10617E+05, 0.11692E+05, - 0.12852E+05, 0.14102E+05, 0.15447E+05, 0.16893E+05, 0.18446E+05, - 0.20112E+05, 0.21898E+05, 0.23811E+05, 0.25856E+05, 0.28042E+05, - 0.30377E+05, 0.32866E+05, 0.35520E+05, 0.38345E+05, 0.41351E+05, - 0.44545E+05, 0.47939E+05, 0.51540E+05, 0.55359E+05, 0.59405E+05, - 0.63689E+05, 0.68222E+05, 0.73015E+05, 0.78078E+05, 0.83424E+05, - 0.89064E+05, 0.95012E+05, 0.10128E+06, 0.10788E+06, 0.11482E+06, - 0.12213E+06, 0.12981E+06, 0.13788E+06, 0.14635E+06, 0.15524E+06, - 0.16456E+06, 0.17433E+06, 0.18457E+06, 0.19530E+06, 0.20652E+06, - 0.21827E+06, 0.23055E+06, 0.24338E+06, 0.25679E+06, 0.27079E+06, - 0.28541E+06, 0.30066E+06, 0.31656E+06, 0.33314E+06, 0.35042E+06, - 0.36841E+06, 0.38715E+06, 0.40666E+06, 0.42695E+06, 0.44805E+06, - 0.46999E+06, 0.49279E+06, 0.51649E+06, 0.54109E+06, 0.56664E+06, - 0.59315E+06, 0.62066E+06, 0.64919E+06, 0.67877E+06, 0.70943E+06, - 0.74121E+06, 0.77413E+06, 0.80822E+06, 0.84351E+06, 0.88004E+06, - 0.91783E+06, 0.95693E+06, 0.99737E+06, 0.10392E+07, 0.10824E+07, - 0.11270E+07, 0.11732E+07, 0.12208E+07, 0.12700E+07, 0.13208E+07, - 0.13732E+07, 0.14272E+07, 0.14830E+07, 0.15405E+07, 0.15999E+07, - 0.16610E+07, 0.17240E+07, 0.17890E+07, 0.18559E+07, 0.19248E+07, - 0.19957E+07, 0.20687E+07, 0.21439E+07, 0.22213E+07, 0.23009E+07, - 0.23828E+07, 0.24671E+07, 0.25537E+07, 0.26428E+07, 0.27343E+07, - 0.28284E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.95253E+03, 0.13487E+04, 0.17465E+04, 0.21498E+04, 0.25648E+04, 0.29986E+04, 0.34580E+04, + 0.39493E+04, 0.44779E+04, 0.50488E+04, 0.56669E+04, 0.63366E+04, 0.70625E+04, 0.78488E+04, + 0.87003E+04, 0.96216E+04, 0.10617E+05, 0.11692E+05, 0.12852E+05, 0.14102E+05, 0.15447E+05, + 0.16893E+05, 0.18446E+05, 0.20112E+05, 0.21898E+05, 0.23811E+05, 0.25856E+05, 0.28042E+05, + 0.30377E+05, 0.32866E+05, 0.35520E+05, 0.38345E+05, 0.41351E+05, 0.44545E+05, 0.47939E+05, + 0.51540E+05, 0.55359E+05, 0.59405E+05, 0.63689E+05, 0.68222E+05, 0.73015E+05, 0.78078E+05, + 0.83424E+05, 0.89064E+05, 0.95012E+05, 0.10128E+06, 0.10788E+06, 0.11482E+06, 0.12213E+06, + 0.12981E+06, 0.13788E+06, 0.14635E+06, 0.15524E+06, 0.16456E+06, 0.17433E+06, 0.18457E+06, + 0.19530E+06, 0.20652E+06, 0.21827E+06, 0.23055E+06, 0.24338E+06, 0.25679E+06, 0.27079E+06, + 0.28541E+06, 0.30066E+06, 0.31656E+06, 0.33314E+06, 0.35042E+06, 0.36841E+06, 0.38715E+06, + 0.40666E+06, 0.42695E+06, 0.44805E+06, 0.46999E+06, 0.49279E+06, 0.51649E+06, 0.54109E+06, + 0.56664E+06, 0.59315E+06, 0.62066E+06, 0.64919E+06, 0.67877E+06, 0.70943E+06, 0.74121E+06, + 0.77413E+06, 0.80822E+06, 0.84351E+06, 0.88004E+06, 0.91783E+06, 0.95693E+06, 0.99737E+06, + 0.10392E+07, 0.10824E+07, 0.11270E+07, 0.11732E+07, 0.12208E+07, 0.12700E+07, 0.13208E+07, + 0.13732E+07, 0.14272E+07, 0.14830E+07, 0.15405E+07, 0.15999E+07, 0.16610E+07, 0.17240E+07, + 0.17890E+07, 0.18559E+07, 0.19248E+07, 0.19957E+07, 0.20687E+07, 0.21439E+07, 0.22213E+07, + 0.23009E+07, 0.23828E+07, 0.24671E+07, 0.25537E+07, 0.26428E+07, 0.27343E+07, 0.28284E+07]) # --------------- N2O 447: M = 4, I = 5 --------------------- M = 4 I = 5 TIPS_GSI_HASH[(M, I)] = __FloatType__(54.) -TIPS_ISO_HASH[(M, I)] = float32([0.55598E+04, 0.78718E+04, 0.10193E+05, - 0.12546E+05, 0.14966E+05, 0.17495E+05, 0.20171E+05, 0.23031E+05, - 0.26106E+05, 0.29426E+05, 0.33018E+05, 0.36908E+05, 0.41121E+05, - 0.45684E+05, 0.50622E+05, 0.55962E+05, 0.61731E+05, 0.67958E+05, - 0.74671E+05, 0.81902E+05, 0.89681E+05, 0.98043E+05, 0.10702E+06, - 0.11665E+06, 0.12697E+06, 0.13801E+06, 0.14983E+06, 0.16244E+06, - 0.17591E+06, 0.19028E+06, 0.20558E+06, 0.22188E+06, 0.23920E+06, - 0.25762E+06, 0.27718E+06, 0.29793E+06, 0.31993E+06, 0.34323E+06, - 0.36791E+06, 0.39401E+06, 0.42160E+06, 0.45074E+06, 0.48151E+06, - 0.51397E+06, 0.54819E+06, 0.58424E+06, 0.62221E+06, 0.66215E+06, - 0.70416E+06, 0.74832E+06, 0.79470E+06, 0.84340E+06, 0.89450E+06, - 0.94808E+06, 0.10042E+07, 0.10631E+07, 0.11247E+07, 0.11892E+07, - 0.12567E+07, 0.13272E+07, 0.14009E+07, 0.14779E+07, 0.15583E+07, - 0.16422E+07, 0.17298E+07, 0.18211E+07, 0.19163E+07, 0.20154E+07, - 0.21187E+07, 0.22263E+07, 0.23382E+07, 0.24546E+07, 0.25757E+07, - 0.27016E+07, 0.28324E+07, 0.29683E+07, 0.31095E+07, 0.32560E+07, - 0.34081E+07, 0.35659E+07, 0.37295E+07, 0.38991E+07, 0.40750E+07, - 0.42572E+07, 0.44459E+07, 0.46414E+07, 0.48437E+07, 0.50531E+07, - 0.52698E+07, 0.54939E+07, 0.57257E+07, 0.59653E+07, 0.62129E+07, - 0.64688E+07, 0.67331E+07, 0.70061E+07, 0.72880E+07, 0.75790E+07, - 0.78792E+07, 0.81891E+07, 0.85086E+07, 0.88382E+07, 0.91780E+07, - 0.95283E+07, 0.98893E+07, 0.10261E+08, 0.10644E+08, 0.11039E+08, - 0.11445E+08, 0.11864E+08, 0.12294E+08, 0.12738E+08, 0.13194E+08, - 0.13663E+08, 0.14145E+08, 0.14641E+08, 0.15151E+08, 0.15675E+08, - 0.16214E+08]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.55598E+04, 0.78718E+04, 0.10193E+05, 0.12546E+05, 0.14966E+05, 0.17495E+05, 0.20171E+05, + 0.23031E+05, 0.26106E+05, 0.29426E+05, 0.33018E+05, 0.36908E+05, 0.41121E+05, 0.45684E+05, + 0.50622E+05, 0.55962E+05, 0.61731E+05, 0.67958E+05, 0.74671E+05, 0.81902E+05, 0.89681E+05, + 0.98043E+05, 0.10702E+06, 0.11665E+06, 0.12697E+06, 0.13801E+06, 0.14983E+06, 0.16244E+06, + 0.17591E+06, 0.19028E+06, 0.20558E+06, 0.22188E+06, 0.23920E+06, 0.25762E+06, 0.27718E+06, + 0.29793E+06, 0.31993E+06, 0.34323E+06, 0.36791E+06, 0.39401E+06, 0.42160E+06, 0.45074E+06, + 0.48151E+06, 0.51397E+06, 0.54819E+06, 0.58424E+06, 0.62221E+06, 0.66215E+06, 0.70416E+06, + 0.74832E+06, 0.79470E+06, 0.84340E+06, 0.89450E+06, 0.94808E+06, 0.10042E+07, 0.10631E+07, + 0.11247E+07, 0.11892E+07, 0.12567E+07, 0.13272E+07, 0.14009E+07, 0.14779E+07, 0.15583E+07, + 0.16422E+07, 0.17298E+07, 0.18211E+07, 0.19163E+07, 0.20154E+07, 0.21187E+07, 0.22263E+07, + 0.23382E+07, 0.24546E+07, 0.25757E+07, 0.27016E+07, 0.28324E+07, 0.29683E+07, 0.31095E+07, + 0.32560E+07, 0.34081E+07, 0.35659E+07, 0.37295E+07, 0.38991E+07, 0.40750E+07, 0.42572E+07, + 0.44459E+07, 0.46414E+07, 0.48437E+07, 0.50531E+07, 0.52698E+07, 0.54939E+07, 0.57257E+07, + 0.59653E+07, 0.62129E+07, 0.64688E+07, 0.67331E+07, 0.70061E+07, 0.72880E+07, 0.75790E+07, + 0.78792E+07, 0.81891E+07, 0.85086E+07, 0.88382E+07, 0.91780E+07, 0.95283E+07, 0.98893E+07, + 0.10261E+08, 0.10644E+08, 0.11039E+08, 0.11445E+08, 0.11864E+08, 0.12294E+08, 0.12738E+08, + 0.13194E+08, 0.13663E+08, 0.14145E+08, 0.14641E+08, 0.15151E+08, 0.15675E+08, 0.16214E+08]) # --------------- CO 26: M = 5, I = 1 --------------------- M = 5 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.21948E+02, 0.30961E+02, 0.39980E+02, - 0.49004E+02, 0.58035E+02, 0.67071E+02, 0.76112E+02, 0.85160E+02, - 0.94213E+02, 0.10327E+03, 0.11234E+03, 0.12142E+03, 0.13050E+03, - 0.13960E+03, 0.14872E+03, 0.15787E+03, 0.16704E+03, 0.17624E+03, - 0.18548E+03, 0.19477E+03, 0.20411E+03, 0.21350E+03, 0.22295E+03, - 0.23248E+03, 0.24207E+03, 0.25175E+03, 0.26151E+03, 0.27136E+03, - 0.28130E+03, 0.29134E+03, 0.30148E+03, 0.31172E+03, 0.32207E+03, - 0.33253E+03, 0.34312E+03, 0.35381E+03, 0.36463E+03, 0.37557E+03, - 0.38663E+03, 0.39782E+03, 0.40914E+03, 0.42060E+03, 0.43218E+03, - 0.44389E+03, 0.45575E+03, 0.46774E+03, 0.47987E+03, 0.49213E+03, - 0.50454E+03, 0.51708E+03, 0.52978E+03, 0.54261E+03, 0.55559E+03, - 0.56871E+03, 0.58198E+03, 0.59540E+03, 0.60896E+03, 0.62267E+03, - 0.63653E+03, 0.65055E+03, 0.66470E+03, 0.67901E+03, 0.69347E+03, - 0.70808E+03, 0.72284E+03, 0.73776E+03, 0.75283E+03, 0.76805E+03, - 0.78342E+03, 0.79895E+03, 0.81463E+03, 0.83047E+03, 0.84646E+03, - 0.86260E+03, 0.87891E+03, 0.89536E+03, 0.91197E+03, 0.92874E+03, - 0.94566E+03, 0.96275E+03, 0.97998E+03, 0.99738E+03, 0.10149E+04, - 0.10326E+04, 0.10505E+04, 0.10685E+04, 0.10867E+04, 0.11051E+04, - 0.11236E+04, 0.11422E+04, 0.11611E+04, 0.11800E+04, 0.11992E+04, - 0.12185E+04, 0.12380E+04, 0.12576E+04, 0.12774E+04, 0.12973E+04, - 0.13174E+04, 0.13377E+04, 0.13581E+04, 0.13787E+04, 0.13994E+04, - 0.14203E+04, 0.14414E+04, 0.14627E+04, 0.14841E+04, 0.15056E+04, - 0.15273E+04, 0.15492E+04, 0.15713E+04, 0.15935E+04, 0.16159E+04, - 0.16384E+04, 0.16611E+04, 0.16840E+04, 0.17070E+04, 0.17302E+04, - 0.17536E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.21948E+02, 0.30961E+02, 0.39980E+02, 0.49004E+02, 0.58035E+02, 0.67071E+02, 0.76112E+02, + 0.85160E+02, 0.94213E+02, 0.10327E+03, 0.11234E+03, 0.12142E+03, 0.13050E+03, 0.13960E+03, + 0.14872E+03, 0.15787E+03, 0.16704E+03, 0.17624E+03, 0.18548E+03, 0.19477E+03, 0.20411E+03, + 0.21350E+03, 0.22295E+03, 0.23248E+03, 0.24207E+03, 0.25175E+03, 0.26151E+03, 0.27136E+03, + 0.28130E+03, 0.29134E+03, 0.30148E+03, 0.31172E+03, 0.32207E+03, 0.33253E+03, 0.34312E+03, + 0.35381E+03, 0.36463E+03, 0.37557E+03, 0.38663E+03, 0.39782E+03, 0.40914E+03, 0.42060E+03, + 0.43218E+03, 0.44389E+03, 0.45575E+03, 0.46774E+03, 0.47987E+03, 0.49213E+03, 0.50454E+03, + 0.51708E+03, 0.52978E+03, 0.54261E+03, 0.55559E+03, 0.56871E+03, 0.58198E+03, 0.59540E+03, + 0.60896E+03, 0.62267E+03, 0.63653E+03, 0.65055E+03, 0.66470E+03, 0.67901E+03, 0.69347E+03, + 0.70808E+03, 0.72284E+03, 0.73776E+03, 0.75283E+03, 0.76805E+03, 0.78342E+03, 0.79895E+03, + 0.81463E+03, 0.83047E+03, 0.84646E+03, 0.86260E+03, 0.87891E+03, 0.89536E+03, 0.91197E+03, + 0.92874E+03, 0.94566E+03, 0.96275E+03, 0.97998E+03, 0.99738E+03, 0.10149E+04, 0.10326E+04, + 0.10505E+04, 0.10685E+04, 0.10867E+04, 0.11051E+04, 0.11236E+04, 0.11422E+04, 0.11611E+04, + 0.11800E+04, 0.11992E+04, 0.12185E+04, 0.12380E+04, 0.12576E+04, 0.12774E+04, 0.12973E+04, + 0.13174E+04, 0.13377E+04, 0.13581E+04, 0.13787E+04, 0.13994E+04, 0.14203E+04, 0.14414E+04, + 0.14627E+04, 0.14841E+04, 0.15056E+04, 0.15273E+04, 0.15492E+04, 0.15713E+04, 0.15935E+04, + 0.16159E+04, 0.16384E+04, 0.16611E+04, 0.16840E+04, 0.17070E+04, 0.17302E+04, 0.17536E+04]) # --------------- CO 36: M = 5, I = 2 --------------------- M = 5 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.45888E+02, 0.64745E+02, 0.83615E+02, - 0.10250E+03, 0.12139E+03, 0.14030E+03, 0.15921E+03, 0.17814E+03, - 0.19708E+03, 0.21604E+03, 0.23501E+03, 0.25400E+03, 0.27302E+03, - 0.29207E+03, 0.31117E+03, 0.33031E+03, 0.34952E+03, 0.36880E+03, - 0.38817E+03, 0.40764E+03, 0.42723E+03, 0.44694E+03, 0.46679E+03, - 0.48679E+03, 0.50696E+03, 0.52730E+03, 0.54783E+03, 0.56855E+03, - 0.58948E+03, 0.61061E+03, 0.63198E+03, 0.65357E+03, 0.67539E+03, - 0.69747E+03, 0.71979E+03, 0.74237E+03, 0.76521E+03, 0.78832E+03, - 0.81169E+03, 0.83534E+03, 0.85927E+03, 0.88348E+03, 0.90798E+03, - 0.93277E+03, 0.95784E+03, 0.98322E+03, 0.10089E+04, 0.10349E+04, - 0.10611E+04, 0.10877E+04, 0.11146E+04, 0.11418E+04, 0.11693E+04, - 0.11971E+04, 0.12253E+04, 0.12537E+04, 0.12825E+04, 0.13115E+04, - 0.13409E+04, 0.13707E+04, 0.14007E+04, 0.14311E+04, 0.14617E+04, - 0.14928E+04, 0.15241E+04, 0.15558E+04, 0.15877E+04, 0.16200E+04, - 0.16527E+04, 0.16857E+04, 0.17190E+04, 0.17526E+04, 0.17866E+04, - 0.18209E+04, 0.18555E+04, 0.18905E+04, 0.19258E+04, 0.19614E+04, - 0.19974E+04, 0.20337E+04, 0.20703E+04, 0.21073E+04, 0.21446E+04, - 0.21823E+04, 0.22203E+04, 0.22586E+04, 0.22973E+04, 0.23363E+04, - 0.23756E+04, 0.24153E+04, 0.24553E+04, 0.24957E+04, 0.25364E+04, - 0.25775E+04, 0.26189E+04, 0.26606E+04, 0.27027E+04, 0.27451E+04, - 0.27879E+04, 0.28310E+04, 0.28745E+04, 0.29183E+04, 0.29625E+04, - 0.30070E+04, 0.30518E+04, 0.30970E+04, 0.31425E+04, 0.31885E+04, - 0.32347E+04, 0.32813E+04, 0.33282E+04, 0.33755E+04, 0.34231E+04, - 0.34711E+04, 0.35194E+04, 0.35681E+04, 0.36172E+04, 0.36666E+04, - 0.37163E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.45888E+02, 0.64745E+02, 0.83615E+02, 0.10250E+03, 0.12139E+03, 0.14030E+03, 0.15921E+03, + 0.17814E+03, 0.19708E+03, 0.21604E+03, 0.23501E+03, 0.25400E+03, 0.27302E+03, 0.29207E+03, + 0.31117E+03, 0.33031E+03, 0.34952E+03, 0.36880E+03, 0.38817E+03, 0.40764E+03, 0.42723E+03, + 0.44694E+03, 0.46679E+03, 0.48679E+03, 0.50696E+03, 0.52730E+03, 0.54783E+03, 0.56855E+03, + 0.58948E+03, 0.61061E+03, 0.63198E+03, 0.65357E+03, 0.67539E+03, 0.69747E+03, 0.71979E+03, + 0.74237E+03, 0.76521E+03, 0.78832E+03, 0.81169E+03, 0.83534E+03, 0.85927E+03, 0.88348E+03, + 0.90798E+03, 0.93277E+03, 0.95784E+03, 0.98322E+03, 0.10089E+04, 0.10349E+04, 0.10611E+04, + 0.10877E+04, 0.11146E+04, 0.11418E+04, 0.11693E+04, 0.11971E+04, 0.12253E+04, 0.12537E+04, + 0.12825E+04, 0.13115E+04, 0.13409E+04, 0.13707E+04, 0.14007E+04, 0.14311E+04, 0.14617E+04, + 0.14928E+04, 0.15241E+04, 0.15558E+04, 0.15877E+04, 0.16200E+04, 0.16527E+04, 0.16857E+04, + 0.17190E+04, 0.17526E+04, 0.17866E+04, 0.18209E+04, 0.18555E+04, 0.18905E+04, 0.19258E+04, + 0.19614E+04, 0.19974E+04, 0.20337E+04, 0.20703E+04, 0.21073E+04, 0.21446E+04, 0.21823E+04, + 0.22203E+04, 0.22586E+04, 0.22973E+04, 0.23363E+04, 0.23756E+04, 0.24153E+04, 0.24553E+04, + 0.24957E+04, 0.25364E+04, 0.25775E+04, 0.26189E+04, 0.26606E+04, 0.27027E+04, 0.27451E+04, + 0.27879E+04, 0.28310E+04, 0.28745E+04, 0.29183E+04, 0.29625E+04, 0.30070E+04, 0.30518E+04, + 0.30970E+04, 0.31425E+04, 0.31885E+04, 0.32347E+04, 0.32813E+04, 0.33282E+04, 0.33755E+04, + 0.34231E+04, 0.34711E+04, 0.35194E+04, 0.35681E+04, 0.36172E+04, 0.36666E+04, 0.37163E+04]) # --------------- CO 28: M = 5, I = 3 --------------------- M = 5 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.23030E+02, 0.32495E+02, 0.41966E+02, - 0.51443E+02, 0.60926E+02, 0.70415E+02, 0.79910E+02, 0.89410E+02, - 0.98918E+02, 0.10843E+03, 0.11795E+03, 0.12749E+03, 0.13703E+03, - 0.14659E+03, 0.15618E+03, 0.16579E+03, 0.17543E+03, 0.18511E+03, - 0.19483E+03, 0.20461E+03, 0.21444E+03, 0.22434E+03, 0.23430E+03, - 0.24435E+03, 0.25447E+03, 0.26468E+03, 0.27499E+03, 0.28540E+03, - 0.29591E+03, 0.30652E+03, 0.31725E+03, 0.32810E+03, 0.33906E+03, - 0.35014E+03, 0.36136E+03, 0.37270E+03, 0.38417E+03, 0.39577E+03, - 0.40752E+03, 0.41940E+03, 0.43142E+03, 0.44358E+03, 0.45589E+03, - 0.46834E+03, 0.48094E+03, 0.49369E+03, 0.50659E+03, 0.51964E+03, - 0.53284E+03, 0.54619E+03, 0.55971E+03, 0.57337E+03, 0.58719E+03, - 0.60117E+03, 0.61530E+03, 0.62959E+03, 0.64405E+03, 0.65866E+03, - 0.67343E+03, 0.68837E+03, 0.70346E+03, 0.71872E+03, 0.73414E+03, - 0.74972E+03, 0.76547E+03, 0.78138E+03, 0.79745E+03, 0.81369E+03, - 0.83010E+03, 0.84667E+03, 0.86341E+03, 0.88031E+03, 0.89738E+03, - 0.91462E+03, 0.93202E+03, 0.94960E+03, 0.96734E+03, 0.98524E+03, - 0.10033E+04, 0.10216E+04, 0.10400E+04, 0.10586E+04, 0.10773E+04, - 0.10962E+04, 0.11153E+04, 0.11346E+04, 0.11540E+04, 0.11737E+04, - 0.11934E+04, 0.12134E+04, 0.12335E+04, 0.12538E+04, 0.12743E+04, - 0.12949E+04, 0.13157E+04, 0.13367E+04, 0.13578E+04, 0.13792E+04, - 0.14007E+04, 0.14223E+04, 0.14442E+04, 0.14662E+04, 0.14884E+04, - 0.15108E+04, 0.15333E+04, 0.15560E+04, 0.15789E+04, 0.16020E+04, - 0.16252E+04, 0.16486E+04, 0.16722E+04, 0.16960E+04, 0.17199E+04, - 0.17441E+04, 0.17684E+04, 0.17928E+04, 0.18175E+04, 0.18423E+04, - 0.18673E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.23030E+02, 0.32495E+02, 0.41966E+02, 0.51443E+02, 0.60926E+02, 0.70415E+02, 0.79910E+02, + 0.89410E+02, 0.98918E+02, 0.10843E+03, 0.11795E+03, 0.12749E+03, 0.13703E+03, 0.14659E+03, + 0.15618E+03, 0.16579E+03, 0.17543E+03, 0.18511E+03, 0.19483E+03, 0.20461E+03, 0.21444E+03, + 0.22434E+03, 0.23430E+03, 0.24435E+03, 0.25447E+03, 0.26468E+03, 0.27499E+03, 0.28540E+03, + 0.29591E+03, 0.30652E+03, 0.31725E+03, 0.32810E+03, 0.33906E+03, 0.35014E+03, 0.36136E+03, + 0.37270E+03, 0.38417E+03, 0.39577E+03, 0.40752E+03, 0.41940E+03, 0.43142E+03, 0.44358E+03, + 0.45589E+03, 0.46834E+03, 0.48094E+03, 0.49369E+03, 0.50659E+03, 0.51964E+03, 0.53284E+03, + 0.54619E+03, 0.55971E+03, 0.57337E+03, 0.58719E+03, 0.60117E+03, 0.61530E+03, 0.62959E+03, + 0.64405E+03, 0.65866E+03, 0.67343E+03, 0.68837E+03, 0.70346E+03, 0.71872E+03, 0.73414E+03, + 0.74972E+03, 0.76547E+03, 0.78138E+03, 0.79745E+03, 0.81369E+03, 0.83010E+03, 0.84667E+03, + 0.86341E+03, 0.88031E+03, 0.89738E+03, 0.91462E+03, 0.93202E+03, 0.94960E+03, 0.96734E+03, + 0.98524E+03, 0.10033E+04, 0.10216E+04, 0.10400E+04, 0.10586E+04, 0.10773E+04, 0.10962E+04, + 0.11153E+04, 0.11346E+04, 0.11540E+04, 0.11737E+04, 0.11934E+04, 0.12134E+04, 0.12335E+04, + 0.12538E+04, 0.12743E+04, 0.12949E+04, 0.13157E+04, 0.13367E+04, 0.13578E+04, 0.13792E+04, + 0.14007E+04, 0.14223E+04, 0.14442E+04, 0.14662E+04, 0.14884E+04, 0.15108E+04, 0.15333E+04, + 0.15560E+04, 0.15789E+04, 0.16020E+04, 0.16252E+04, 0.16486E+04, 0.16722E+04, 0.16960E+04, + 0.17199E+04, 0.17441E+04, 0.17684E+04, 0.17928E+04, 0.18175E+04, 0.18423E+04, 0.18673E+04]) # --------------- CO 27: M = 5, I = 4 --------------------- M = 5 I = 4 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.13505E+03, 0.19054E+03, 0.24606E+03, - 0.30161E+03, 0.35720E+03, 0.41283E+03, 0.46848E+03, 0.52418E+03, - 0.57991E+03, 0.63568E+03, 0.69149E+03, 0.74737E+03, 0.80332E+03, - 0.85937E+03, 0.91553E+03, 0.97183E+03, 0.10283E+04, 0.10850E+04, - 0.11420E+04, 0.11992E+04, 0.12568E+04, 0.13147E+04, 0.13730E+04, - 0.14318E+04, 0.14910E+04, 0.15507E+04, 0.16110E+04, 0.16718E+04, - 0.17332E+04, 0.17952E+04, 0.18579E+04, 0.19212E+04, 0.19852E+04, - 0.20499E+04, 0.21153E+04, 0.21815E+04, 0.22484E+04, 0.23161E+04, - 0.23846E+04, 0.24539E+04, 0.25240E+04, 0.25949E+04, 0.26666E+04, - 0.27392E+04, 0.28127E+04, 0.28869E+04, 0.29621E+04, 0.30381E+04, - 0.31150E+04, 0.31928E+04, 0.32715E+04, 0.33511E+04, 0.34316E+04, - 0.35129E+04, 0.35952E+04, 0.36785E+04, 0.37626E+04, 0.38477E+04, - 0.39336E+04, 0.40206E+04, 0.41084E+04, 0.41972E+04, 0.42869E+04, - 0.43776E+04, 0.44692E+04, 0.45618E+04, 0.46553E+04, 0.47498E+04, - 0.48452E+04, 0.49416E+04, 0.50390E+04, 0.51373E+04, 0.52366E+04, - 0.53368E+04, 0.54381E+04, 0.55403E+04, 0.56435E+04, 0.57476E+04, - 0.58527E+04, 0.59588E+04, 0.60659E+04, 0.61739E+04, 0.62829E+04, - 0.63930E+04, 0.65040E+04, 0.66160E+04, 0.67290E+04, 0.68429E+04, - 0.69579E+04, 0.70739E+04, 0.71908E+04, 0.73088E+04, 0.74277E+04, - 0.75477E+04, 0.76686E+04, 0.77905E+04, 0.79135E+04, 0.80374E+04, - 0.81624E+04, 0.82883E+04, 0.84153E+04, 0.85432E+04, 0.86722E+04, - 0.88022E+04, 0.89331E+04, 0.90651E+04, 0.91982E+04, 0.93322E+04, - 0.94672E+04, 0.96033E+04, 0.97404E+04, 0.98785E+04, 0.10018E+05, - 0.10158E+05, 0.10299E+05, 0.10441E+05, 0.10584E+05, 0.10728E+05, - 0.10874E+05]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.13505E+03, 0.19054E+03, 0.24606E+03, 0.30161E+03, 0.35720E+03, 0.41283E+03, 0.46848E+03, + 0.52418E+03, 0.57991E+03, 0.63568E+03, 0.69149E+03, 0.74737E+03, 0.80332E+03, 0.85937E+03, + 0.91553E+03, 0.97183E+03, 0.10283E+04, 0.10850E+04, 0.11420E+04, 0.11992E+04, 0.12568E+04, + 0.13147E+04, 0.13730E+04, 0.14318E+04, 0.14910E+04, 0.15507E+04, 0.16110E+04, 0.16718E+04, + 0.17332E+04, 0.17952E+04, 0.18579E+04, 0.19212E+04, 0.19852E+04, 0.20499E+04, 0.21153E+04, + 0.21815E+04, 0.22484E+04, 0.23161E+04, 0.23846E+04, 0.24539E+04, 0.25240E+04, 0.25949E+04, + 0.26666E+04, 0.27392E+04, 0.28127E+04, 0.28869E+04, 0.29621E+04, 0.30381E+04, 0.31150E+04, + 0.31928E+04, 0.32715E+04, 0.33511E+04, 0.34316E+04, 0.35129E+04, 0.35952E+04, 0.36785E+04, + 0.37626E+04, 0.38477E+04, 0.39336E+04, 0.40206E+04, 0.41084E+04, 0.41972E+04, 0.42869E+04, + 0.43776E+04, 0.44692E+04, 0.45618E+04, 0.46553E+04, 0.47498E+04, 0.48452E+04, 0.49416E+04, + 0.50390E+04, 0.51373E+04, 0.52366E+04, 0.53368E+04, 0.54381E+04, 0.55403E+04, 0.56435E+04, + 0.57476E+04, 0.58527E+04, 0.59588E+04, 0.60659E+04, 0.61739E+04, 0.62829E+04, 0.63930E+04, + 0.65040E+04, 0.66160E+04, 0.67290E+04, 0.68429E+04, 0.69579E+04, 0.70739E+04, 0.71908E+04, + 0.73088E+04, 0.74277E+04, 0.75477E+04, 0.76686E+04, 0.77905E+04, 0.79135E+04, 0.80374E+04, + 0.81624E+04, 0.82883E+04, 0.84153E+04, 0.85432E+04, 0.86722E+04, 0.88022E+04, 0.89331E+04, + 0.90651E+04, 0.91982E+04, 0.93322E+04, 0.94672E+04, 0.96033E+04, 0.97404E+04, 0.98785E+04, + 0.10018E+05, 0.10158E+05, 0.10299E+05, 0.10441E+05, 0.10584E+05, 0.10728E+05, 0.10874E+05]) # --------------- CO 38: M = 5, I = 5 --------------------- M = 5 I = 5 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.48264E+02, 0.68112E+02, 0.87974E+02, - 0.10785E+03, 0.12773E+03, 0.14763E+03, 0.16754E+03, 0.18747E+03, - 0.20741E+03, 0.22736E+03, 0.24733E+03, 0.26732E+03, 0.28735E+03, - 0.30741E+03, 0.32752E+03, 0.34770E+03, 0.36794E+03, 0.38828E+03, - 0.40871E+03, 0.42926E+03, 0.44994E+03, 0.47077E+03, 0.49175E+03, - 0.51290E+03, 0.53424E+03, 0.55578E+03, 0.57752E+03, 0.59948E+03, - 0.62166E+03, 0.64409E+03, 0.66676E+03, 0.68969E+03, 0.71287E+03, - 0.73633E+03, 0.76006E+03, 0.78407E+03, 0.80836E+03, 0.83295E+03, - 0.85784E+03, 0.88302E+03, 0.90851E+03, 0.93431E+03, 0.96042E+03, - 0.98686E+03, 0.10136E+04, 0.10407E+04, 0.10681E+04, 0.10958E+04, - 0.11238E+04, 0.11522E+04, 0.11809E+04, 0.12100E+04, 0.12393E+04, - 0.12691E+04, 0.12991E+04, 0.13295E+04, 0.13603E+04, 0.13914E+04, - 0.14228E+04, 0.14546E+04, 0.14867E+04, 0.15192E+04, 0.15520E+04, - 0.15852E+04, 0.16187E+04, 0.16526E+04, 0.16869E+04, 0.17215E+04, - 0.17564E+04, 0.17917E+04, 0.18274E+04, 0.18634E+04, 0.18998E+04, - 0.19365E+04, 0.19736E+04, 0.20111E+04, 0.20489E+04, 0.20871E+04, - 0.21256E+04, 0.21645E+04, 0.22038E+04, 0.22434E+04, 0.22834E+04, - 0.23238E+04, 0.23645E+04, 0.24056E+04, 0.24471E+04, 0.24889E+04, - 0.25311E+04, 0.25736E+04, 0.26166E+04, 0.26599E+04, 0.27035E+04, - 0.27476E+04, 0.27920E+04, 0.28368E+04, 0.28819E+04, 0.29275E+04, - 0.29733E+04, 0.30196E+04, 0.30662E+04, 0.31133E+04, 0.31606E+04, - 0.32084E+04, 0.32565E+04, 0.33050E+04, 0.33539E+04, 0.34032E+04, - 0.34528E+04, 0.35028E+04, 0.35532E+04, 0.36040E+04, 0.36551E+04, - 0.37067E+04, 0.37586E+04, 0.38108E+04, 0.38635E+04, 0.39165E+04, - 0.39699E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.48264E+02, 0.68112E+02, 0.87974E+02, 0.10785E+03, 0.12773E+03, 0.14763E+03, 0.16754E+03, + 0.18747E+03, 0.20741E+03, 0.22736E+03, 0.24733E+03, 0.26732E+03, 0.28735E+03, 0.30741E+03, + 0.32752E+03, 0.34770E+03, 0.36794E+03, 0.38828E+03, 0.40871E+03, 0.42926E+03, 0.44994E+03, + 0.47077E+03, 0.49175E+03, 0.51290E+03, 0.53424E+03, 0.55578E+03, 0.57752E+03, 0.59948E+03, + 0.62166E+03, 0.64409E+03, 0.66676E+03, 0.68969E+03, 0.71287E+03, 0.73633E+03, 0.76006E+03, + 0.78407E+03, 0.80836E+03, 0.83295E+03, 0.85784E+03, 0.88302E+03, 0.90851E+03, 0.93431E+03, + 0.96042E+03, 0.98686E+03, 0.10136E+04, 0.10407E+04, 0.10681E+04, 0.10958E+04, 0.11238E+04, + 0.11522E+04, 0.11809E+04, 0.12100E+04, 0.12393E+04, 0.12691E+04, 0.12991E+04, 0.13295E+04, + 0.13603E+04, 0.13914E+04, 0.14228E+04, 0.14546E+04, 0.14867E+04, 0.15192E+04, 0.15520E+04, + 0.15852E+04, 0.16187E+04, 0.16526E+04, 0.16869E+04, 0.17215E+04, 0.17564E+04, 0.17917E+04, + 0.18274E+04, 0.18634E+04, 0.18998E+04, 0.19365E+04, 0.19736E+04, 0.20111E+04, 0.20489E+04, + 0.20871E+04, 0.21256E+04, 0.21645E+04, 0.22038E+04, 0.22434E+04, 0.22834E+04, 0.23238E+04, + 0.23645E+04, 0.24056E+04, 0.24471E+04, 0.24889E+04, 0.25311E+04, 0.25736E+04, 0.26166E+04, + 0.26599E+04, 0.27035E+04, 0.27476E+04, 0.27920E+04, 0.28368E+04, 0.28819E+04, 0.29275E+04, + 0.29733E+04, 0.30196E+04, 0.30662E+04, 0.31133E+04, 0.31606E+04, 0.32084E+04, 0.32565E+04, + 0.33050E+04, 0.33539E+04, 0.34032E+04, 0.34528E+04, 0.35028E+04, 0.35532E+04, 0.36040E+04, + 0.36551E+04, 0.37067E+04, 0.37586E+04, 0.38108E+04, 0.38635E+04, 0.39165E+04, 0.39699E+04]) # --------------- CO 37: M = 5, I = 6 --------------------- M = 5 I = 6 TIPS_GSI_HASH[(M, I)] = __FloatType__(12.) -TIPS_ISO_HASH[(M, I)] = float32([0.28271E+03, 0.39894E+03, 0.51524E+03, - 0.63162E+03, 0.74807E+03, 0.86459E+03, 0.98119E+03, 0.10979E+04, - 0.12146E+04, 0.13314E+04, 0.14484E+04, 0.15654E+04, 0.16826E+04, - 0.18000E+04, 0.19176E+04, 0.20355E+04, 0.21538E+04, 0.22725E+04, - 0.23916E+04, 0.25114E+04, 0.26318E+04, 0.27529E+04, 0.28749E+04, - 0.29977E+04, 0.31215E+04, 0.32463E+04, 0.33721E+04, 0.34991E+04, - 0.36274E+04, 0.37568E+04, 0.38876E+04, 0.40197E+04, 0.41533E+04, - 0.42882E+04, 0.44247E+04, 0.45626E+04, 0.47022E+04, 0.48433E+04, - 0.49860E+04, 0.51304E+04, 0.52763E+04, 0.54240E+04, 0.55735E+04, - 0.57246E+04, 0.58775E+04, 0.60321E+04, 0.61886E+04, 0.63468E+04, - 0.65068E+04, 0.66687E+04, 0.68324E+04, 0.69980E+04, 0.71654E+04, - 0.73347E+04, 0.75058E+04, 0.76789E+04, 0.78539E+04, 0.80307E+04, - 0.82096E+04, 0.83903E+04, 0.85729E+04, 0.87576E+04, 0.89441E+04, - 0.91326E+04, 0.93230E+04, 0.95154E+04, 0.97098E+04, 0.99061E+04, - 0.10104E+05, 0.10305E+05, 0.10507E+05, 0.10711E+05, 0.10918E+05, - 0.11126E+05, 0.11336E+05, 0.11549E+05, 0.11763E+05, 0.11979E+05, - 0.12198E+05, 0.12418E+05, 0.12640E+05, 0.12865E+05, 0.13091E+05, - 0.13320E+05, 0.13550E+05, 0.13783E+05, 0.14018E+05, 0.14254E+05, - 0.14493E+05, 0.14734E+05, 0.14977E+05, 0.15221E+05, 0.15468E+05, - 0.15718E+05, 0.15969E+05, 0.16222E+05, 0.16477E+05, 0.16734E+05, - 0.16994E+05, 0.17255E+05, 0.17519E+05, 0.17784E+05, 0.18052E+05, - 0.18322E+05, 0.18594E+05, 0.18868E+05, 0.19144E+05, 0.19422E+05, - 0.19703E+05, 0.19985E+05, 0.20270E+05, 0.20556E+05, 0.20845E+05, - 0.21136E+05, 0.21429E+05, 0.21724E+05, 0.22021E+05, 0.22320E+05, - 0.22622E+05]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.28271E+03, 0.39894E+03, 0.51524E+03, 0.63162E+03, 0.74807E+03, 0.86459E+03, 0.98119E+03, + 0.10979E+04, 0.12146E+04, 0.13314E+04, 0.14484E+04, 0.15654E+04, 0.16826E+04, 0.18000E+04, + 0.19176E+04, 0.20355E+04, 0.21538E+04, 0.22725E+04, 0.23916E+04, 0.25114E+04, 0.26318E+04, + 0.27529E+04, 0.28749E+04, 0.29977E+04, 0.31215E+04, 0.32463E+04, 0.33721E+04, 0.34991E+04, + 0.36274E+04, 0.37568E+04, 0.38876E+04, 0.40197E+04, 0.41533E+04, 0.42882E+04, 0.44247E+04, + 0.45626E+04, 0.47022E+04, 0.48433E+04, 0.49860E+04, 0.51304E+04, 0.52763E+04, 0.54240E+04, + 0.55735E+04, 0.57246E+04, 0.58775E+04, 0.60321E+04, 0.61886E+04, 0.63468E+04, 0.65068E+04, + 0.66687E+04, 0.68324E+04, 0.69980E+04, 0.71654E+04, 0.73347E+04, 0.75058E+04, 0.76789E+04, + 0.78539E+04, 0.80307E+04, 0.82096E+04, 0.83903E+04, 0.85729E+04, 0.87576E+04, 0.89441E+04, + 0.91326E+04, 0.93230E+04, 0.95154E+04, 0.97098E+04, 0.99061E+04, 0.10104E+05, 0.10305E+05, + 0.10507E+05, 0.10711E+05, 0.10918E+05, 0.11126E+05, 0.11336E+05, 0.11549E+05, 0.11763E+05, + 0.11979E+05, 0.12198E+05, 0.12418E+05, 0.12640E+05, 0.12865E+05, 0.13091E+05, 0.13320E+05, + 0.13550E+05, 0.13783E+05, 0.14018E+05, 0.14254E+05, 0.14493E+05, 0.14734E+05, 0.14977E+05, + 0.15221E+05, 0.15468E+05, 0.15718E+05, 0.15969E+05, 0.16222E+05, 0.16477E+05, 0.16734E+05, + 0.16994E+05, 0.17255E+05, 0.17519E+05, 0.17784E+05, 0.18052E+05, 0.18322E+05, 0.18594E+05, + 0.18868E+05, 0.19144E+05, 0.19422E+05, 0.19703E+05, 0.19985E+05, 0.20270E+05, 0.20556E+05, + 0.20845E+05, 0.21136E+05, 0.21429E+05, 0.21724E+05, 0.22021E+05, 0.22320E+05, 0.22622E+05]) # --------------- CH4 211: M = 6, I = 1 --------------------- M = 6 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.54800E+02, 0.91500E+02, 0.13410E+03, - 0.18180E+03, 0.23410E+03, 0.29070E+03, 0.35140E+03, 0.41600E+03, - 0.48450E+03, 0.55720E+03, 0.63420E+03, 0.71600E+03, 0.80310E+03, - 0.89590E+03, 0.99520E+03, 0.11017E+04, 0.12161E+04, 0.13393E+04, - 0.14721E+04, 0.16155E+04, 0.17706E+04, 0.19384E+04, 0.21202E+04, - 0.23172E+04, 0.25307E+04, 0.27624E+04, 0.30137E+04, 0.32864E+04, - 0.35823E+04, 0.39034E+04, 0.42519E+04, 0.46300E+04, 0.50402E+04, - 0.54853E+04, 0.59679E+04, 0.64913E+04, 0.70588E+04, 0.76739E+04, - 0.83404E+04, 0.90625E+04, 0.98446E+04, 0.10691E+05, 0.11608E+05, - 0.12600E+05, 0.13674E+05, 0.14835E+05, 0.16090E+05, 0.17447E+05, - 0.18914E+05, 0.20500E+05, 0.22212E+05, 0.24063E+05, 0.26061E+05, - 0.28218E+05, 0.30548E+05, 0.33063E+05, 0.35778E+05, 0.38708E+05, - 0.41871E+05, 0.45284E+05, 0.48970E+05, 0.52940E+05, 0.57230E+05, - 0.61860E+05, 0.66860E+05, 0.72250E+05, 0.78070E+05, 0.84350E+05, - 0.91130E+05, 0.98450E+05, 0.10635E+06, 0.11488E+06, 0.12408E+06, - 0.13403E+06, 0.14480E+06, 0.15640E+06, 0.16890E+06, 0.18240E+06, - 0.19700E+06, 0.21280E+06, 0.22980E+06, 0.24830E+06, 0.26820E+06, - 0.28970E+06, 0.31290E+06, 0.33800E+06, 0.36520E+06, 0.39450E+06, - 0.42600E+06, 0.46000E+06, 0.49700E+06, 0.53700E+06, 0.58100E+06, - 0.62700E+06, 0.67800E+06, 0.73300E+06, 0.79200E+06, 0.85600E+06, - 0.92500E+06, 0.10000E+07, 0.10800E+07, 0.11670E+07, 0.12610E+07, - 0.13620E+07, 0.14720E+07, 0.15910E+07, 0.17190E+07, 0.18600E+07, - 0.20100E+07, 0.21700E+07, 0.23400E+07, 0.25300E+07, 0.27300E+07, - 0.29500E+07, 0.31800E+07, 0.34300E+07, 0.37000E+07, 0.39900E+07, - 0.42856E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.54800E+02, 0.91500E+02, 0.13410E+03, 0.18180E+03, 0.23410E+03, 0.29070E+03, 0.35140E+03, + 0.41600E+03, 0.48450E+03, 0.55720E+03, 0.63420E+03, 0.71600E+03, 0.80310E+03, 0.89590E+03, + 0.99520E+03, 0.11017E+04, 0.12161E+04, 0.13393E+04, 0.14721E+04, 0.16155E+04, 0.17706E+04, + 0.19384E+04, 0.21202E+04, 0.23172E+04, 0.25307E+04, 0.27624E+04, 0.30137E+04, 0.32864E+04, + 0.35823E+04, 0.39034E+04, 0.42519E+04, 0.46300E+04, 0.50402E+04, 0.54853E+04, 0.59679E+04, + 0.64913E+04, 0.70588E+04, 0.76739E+04, 0.83404E+04, 0.90625E+04, 0.98446E+04, 0.10691E+05, + 0.11608E+05, 0.12600E+05, 0.13674E+05, 0.14835E+05, 0.16090E+05, 0.17447E+05, 0.18914E+05, + 0.20500E+05, 0.22212E+05, 0.24063E+05, 0.26061E+05, 0.28218E+05, 0.30548E+05, 0.33063E+05, + 0.35778E+05, 0.38708E+05, 0.41871E+05, 0.45284E+05, 0.48970E+05, 0.52940E+05, 0.57230E+05, + 0.61860E+05, 0.66860E+05, 0.72250E+05, 0.78070E+05, 0.84350E+05, 0.91130E+05, 0.98450E+05, + 0.10635E+06, 0.11488E+06, 0.12408E+06, 0.13403E+06, 0.14480E+06, 0.15640E+06, 0.16890E+06, + 0.18240E+06, 0.19700E+06, 0.21280E+06, 0.22980E+06, 0.24830E+06, 0.26820E+06, 0.28970E+06, + 0.31290E+06, 0.33800E+06, 0.36520E+06, 0.39450E+06, 0.42600E+06, 0.46000E+06, 0.49700E+06, + 0.53700E+06, 0.58100E+06, 0.62700E+06, 0.67800E+06, 0.73300E+06, 0.79200E+06, 0.85600E+06, + 0.92500E+06, 0.10000E+07, 0.10800E+07, 0.11670E+07, 0.12610E+07, 0.13620E+07, 0.14720E+07, + 0.15910E+07, 0.17190E+07, 0.18600E+07, 0.20100E+07, 0.21700E+07, 0.23400E+07, 0.25300E+07, + 0.27300E+07, 0.29500E+07, 0.31800E+07, 0.34300E+07, 0.37000E+07, 0.39900E+07, 0.42856E+07]) # --------------- CH4 311: M = 6, I = 2 --------------------- M = 6 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.10958E+03, 0.18304E+03, 0.26818E+03, - 0.36356E+03, 0.46820E+03, 0.58141E+03, 0.70270E+03, 0.83186E+03, - 0.96893E+03, 0.11142E+04, 0.12682E+04, 0.14316E+04, 0.16055E+04, - 0.17909E+04, 0.19891E+04, 0.22016E+04, 0.24297E+04, 0.26752E+04, - 0.29399E+04, 0.32255E+04, 0.35342E+04, 0.38680E+04, 0.42294E+04, - 0.46208E+04, 0.50449E+04, 0.55046E+04, 0.60030E+04, 0.65434E+04, - 0.71293E+04, 0.77646E+04, 0.84535E+04, 0.92004E+04, 0.10010E+05, - 0.10888E+05, 0.11838E+05, 0.12869E+05, 0.13984E+05, 0.15193E+05, - 0.16501E+05, 0.17916E+05, 0.19448E+05, 0.21104E+05, 0.22895E+05, - 0.24830E+05, 0.26921E+05, 0.29180E+05, 0.31618E+05, 0.34250E+05, - 0.37090E+05, 0.40152E+05, 0.43454E+05, 0.47012E+05, 0.50845E+05, - 0.54973E+05, 0.59416E+05, 0.64197E+05, 0.69340E+05, 0.74870E+05, - 0.80813E+05, 0.87198E+05, 0.94055E+05, 0.10142E+06, 0.10932E+06, - 0.11779E+06, 0.12688E+06, 0.13662E+06, 0.14706E+06, 0.15824E+06, - 0.17021E+06, 0.18302E+06, 0.19673E+06, 0.21139E+06, 0.22706E+06, - 0.24381E+06, 0.26171E+06, 0.28082E+06, 0.30122E+06, 0.32299E+06, - 0.34621E+06, 0.37097E+06, 0.39737E+06, 0.42551E+06, 0.45548E+06, - 0.48739E+06, 0.52136E+06, 0.55752E+06, 0.59598E+06, 0.63688E+06, - 0.68036E+06, 0.72657E+06, 0.77566E+06, 0.82780E+06, 0.88316E+06, - 0.94191E+06, 0.10043E+07, 0.10704E+07, 0.11405E+07, 0.12148E+07, - 0.12936E+07, 0.13770E+07, 0.14654E+07, 0.15589E+07, 0.16579E+07, - 0.17627E+07, 0.18736E+07, 0.19908E+07, 0.21147E+07, 0.22456E+07, - 0.23840E+07, 0.25301E+07, 0.26844E+07, 0.28474E+07, 0.30193E+07, - 0.32007E+07, 0.33921E+07, 0.35939E+07, 0.38067E+07, 0.40310E+07, - 0.42673E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.10958E+03, 0.18304E+03, 0.26818E+03, 0.36356E+03, 0.46820E+03, 0.58141E+03, 0.70270E+03, + 0.83186E+03, 0.96893E+03, 0.11142E+04, 0.12682E+04, 0.14316E+04, 0.16055E+04, 0.17909E+04, + 0.19891E+04, 0.22016E+04, 0.24297E+04, 0.26752E+04, 0.29399E+04, 0.32255E+04, 0.35342E+04, + 0.38680E+04, 0.42294E+04, 0.46208E+04, 0.50449E+04, 0.55046E+04, 0.60030E+04, 0.65434E+04, + 0.71293E+04, 0.77646E+04, 0.84535E+04, 0.92004E+04, 0.10010E+05, 0.10888E+05, 0.11838E+05, + 0.12869E+05, 0.13984E+05, 0.15193E+05, 0.16501E+05, 0.17916E+05, 0.19448E+05, 0.21104E+05, + 0.22895E+05, 0.24830E+05, 0.26921E+05, 0.29180E+05, 0.31618E+05, 0.34250E+05, 0.37090E+05, + 0.40152E+05, 0.43454E+05, 0.47012E+05, 0.50845E+05, 0.54973E+05, 0.59416E+05, 0.64197E+05, + 0.69340E+05, 0.74870E+05, 0.80813E+05, 0.87198E+05, 0.94055E+05, 0.10142E+06, 0.10932E+06, + 0.11779E+06, 0.12688E+06, 0.13662E+06, 0.14706E+06, 0.15824E+06, 0.17021E+06, 0.18302E+06, + 0.19673E+06, 0.21139E+06, 0.22706E+06, 0.24381E+06, 0.26171E+06, 0.28082E+06, 0.30122E+06, + 0.32299E+06, 0.34621E+06, 0.37097E+06, 0.39737E+06, 0.42551E+06, 0.45548E+06, 0.48739E+06, + 0.52136E+06, 0.55752E+06, 0.59598E+06, 0.63688E+06, 0.68036E+06, 0.72657E+06, 0.77566E+06, + 0.82780E+06, 0.88316E+06, 0.94191E+06, 0.10043E+07, 0.10704E+07, 0.11405E+07, 0.12148E+07, + 0.12936E+07, 0.13770E+07, 0.14654E+07, 0.15589E+07, 0.16579E+07, 0.17627E+07, 0.18736E+07, + 0.19908E+07, 0.21147E+07, 0.22456E+07, 0.23840E+07, 0.25301E+07, 0.26844E+07, 0.28474E+07, + 0.30193E+07, 0.32007E+07, 0.33921E+07, 0.35939E+07, 0.38067E+07, 0.40310E+07, 0.42673E+07]) # --------------- CH4 212: M = 6, I = 3 --------------------- M = 6 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(3.) -TIPS_ISO_HASH[(M, I)] = float32([0.44079E+03, 0.73786E+03, 0.10822E+04, - 0.14679E+04, 0.18913E+04, 0.23497E+04, 0.28415E+04, 0.33665E+04, - 0.39257E+04, 0.45211E+04, 0.51562E+04, 0.58349E+04, 0.65624E+04, - 0.73445E+04, 0.81872E+04, 0.90978E+04, 0.10084E+05, 0.11153E+05, - 0.12315E+05, 0.13579E+05, 0.14955E+05, 0.16455E+05, 0.18089E+05, - 0.19871E+05, 0.21816E+05, 0.23937E+05, 0.26251E+05, 0.28776E+05, - 0.31531E+05, 0.34535E+05, 0.37811E+05, 0.41384E+05, 0.45278E+05, - 0.49521E+05, 0.54144E+05, 0.59178E+05, 0.64657E+05, 0.70621E+05, - 0.77108E+05, 0.84161E+05, 0.91828E+05, 0.10016E+06, 0.10921E+06, - 0.11903E+06, 0.12968E+06, 0.14124E+06, 0.15378E+06, 0.16736E+06, - 0.18207E+06, 0.19800E+06, 0.21524E+06, 0.23389E+06, 0.25405E+06, - 0.27585E+06, 0.29939E+06, 0.32482E+06, 0.35226E+06, 0.38186E+06, - 0.41379E+06, 0.44821E+06, 0.48529E+06, 0.52522E+06, 0.56821E+06, - 0.61447E+06, 0.66422E+06, 0.71771E+06, 0.77519E+06, 0.83693E+06, - 0.90323E+06, 0.97438E+06, 0.10507E+07, 0.11326E+07, 0.12203E+07, - 0.13143E+07, 0.14150E+07, 0.15228E+07, 0.16382E+07, 0.17616E+07, - 0.18935E+07, 0.20346E+07, 0.21853E+07, 0.23463E+07, 0.25181E+07, - 0.27016E+07, 0.28973E+07, 0.31060E+07, 0.33284E+07, 0.35655E+07, - 0.38181E+07, 0.40870E+07, 0.43733E+07, 0.46780E+07, 0.50020E+07, - 0.53467E+07, 0.57130E+07, 0.61023E+07, 0.65158E+07, 0.69549E+07, - 0.74211E+07, 0.79158E+07, 0.84407E+07, 0.89973E+07, 0.95874E+07, - 0.10213E+08, 0.10875E+08, 0.11577E+08, 0.12320E+08, 0.13107E+08, - 0.13940E+08, 0.14820E+08, 0.15752E+08, 0.16736E+08, 0.17777E+08, - 0.18877E+08, 0.20038E+08, 0.21265E+08, 0.22560E+08, 0.23927E+08, - 0.25369E+08]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.44079E+03, 0.73786E+03, 0.10822E+04, 0.14679E+04, 0.18913E+04, 0.23497E+04, 0.28415E+04, + 0.33665E+04, 0.39257E+04, 0.45211E+04, 0.51562E+04, 0.58349E+04, 0.65624E+04, 0.73445E+04, + 0.81872E+04, 0.90978E+04, 0.10084E+05, 0.11153E+05, 0.12315E+05, 0.13579E+05, 0.14955E+05, + 0.16455E+05, 0.18089E+05, 0.19871E+05, 0.21816E+05, 0.23937E+05, 0.26251E+05, 0.28776E+05, + 0.31531E+05, 0.34535E+05, 0.37811E+05, 0.41384E+05, 0.45278E+05, 0.49521E+05, 0.54144E+05, + 0.59178E+05, 0.64657E+05, 0.70621E+05, 0.77108E+05, 0.84161E+05, 0.91828E+05, 0.10016E+06, + 0.10921E+06, 0.11903E+06, 0.12968E+06, 0.14124E+06, 0.15378E+06, 0.16736E+06, 0.18207E+06, + 0.19800E+06, 0.21524E+06, 0.23389E+06, 0.25405E+06, 0.27585E+06, 0.29939E+06, 0.32482E+06, + 0.35226E+06, 0.38186E+06, 0.41379E+06, 0.44821E+06, 0.48529E+06, 0.52522E+06, 0.56821E+06, + 0.61447E+06, 0.66422E+06, 0.71771E+06, 0.77519E+06, 0.83693E+06, 0.90323E+06, 0.97438E+06, + 0.10507E+07, 0.11326E+07, 0.12203E+07, 0.13143E+07, 0.14150E+07, 0.15228E+07, 0.16382E+07, + 0.17616E+07, 0.18935E+07, 0.20346E+07, 0.21853E+07, 0.23463E+07, 0.25181E+07, 0.27016E+07, + 0.28973E+07, 0.31060E+07, 0.33284E+07, 0.35655E+07, 0.38181E+07, 0.40870E+07, 0.43733E+07, + 0.46780E+07, 0.50020E+07, 0.53467E+07, 0.57130E+07, 0.61023E+07, 0.65158E+07, 0.69549E+07, + 0.74211E+07, 0.79158E+07, 0.84407E+07, 0.89973E+07, 0.95874E+07, 0.10213E+08, 0.10875E+08, + 0.11577E+08, 0.12320E+08, 0.13107E+08, 0.13940E+08, 0.14820E+08, 0.15752E+08, 0.16736E+08, + 0.17777E+08, 0.18877E+08, 0.20038E+08, 0.21265E+08, 0.22560E+08, 0.23927E+08, 0.25369E+08]) # --------------- CH4 312: M = 6, I = 4 --------------------- M = 6 I = 4 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.88231E+03, 0.14770E+04, 0.21661E+04, - 0.29384E+04, 0.37859E+04, 0.47034E+04, 0.56879E+04, 0.67388E+04, - 0.78581E+04, 0.90501E+04, 0.10321E+05, 0.11680E+05, 0.13136E+05, - 0.14702E+05, 0.16389E+05, 0.18212E+05, 0.20186E+05, 0.22328E+05, - 0.24654E+05, 0.27185E+05, 0.29941E+05, 0.32943E+05, 0.36216E+05, - 0.39786E+05, 0.43681E+05, 0.47930E+05, 0.52567E+05, 0.57625E+05, - 0.63144E+05, 0.69164E+05, 0.75730E+05, 0.82890E+05, 0.90693E+05, - 0.99198E+05, 0.10846E+06, 0.11855E+06, 0.12954E+06, 0.14149E+06, - 0.15450E+06, 0.16864E+06, 0.18402E+06, 0.20072E+06, 0.21886E+06, - 0.23856E+06, 0.25993E+06, 0.28312E+06, 0.30825E+06, 0.33550E+06, - 0.36501E+06, 0.39696E+06, 0.43155E+06, 0.46896E+06, 0.50942E+06, - 0.55315E+06, 0.60039E+06, 0.65141E+06, 0.70648E+06, 0.76589E+06, - 0.82997E+06, 0.89904E+06, 0.97346E+06, 0.10536E+07, 0.11399E+07, - 0.12327E+07, 0.13326E+07, 0.14400E+07, 0.15554E+07, 0.16793E+07, - 0.18124E+07, 0.19553E+07, 0.21085E+07, 0.22729E+07, 0.24490E+07, - 0.26378E+07, 0.28400E+07, 0.30565E+07, 0.32881E+07, 0.35360E+07, - 0.38010E+07, 0.40843E+07, 0.43870E+07, 0.47103E+07, 0.50555E+07, - 0.54239E+07, 0.58169E+07, 0.62361E+07, 0.66830E+07, 0.71592E+07, - 0.76666E+07, 0.82069E+07, 0.87820E+07, 0.93940E+07, 0.10045E+08, - 0.10737E+08, 0.11473E+08, 0.12256E+08, 0.13086E+08, 0.13969E+08, - 0.14905E+08, 0.15899E+08, 0.16954E+08, 0.18072E+08, 0.19258E+08, - 0.20515E+08, 0.21847E+08, 0.23257E+08, 0.24750E+08, 0.26331E+08, - 0.28004E+08, 0.29774E+08, 0.31646E+08, 0.33625E+08, 0.35716E+08, - 0.37926E+08, 0.40261E+08, 0.42726E+08, 0.45329E+08, 0.48077E+08, - 0.50975E+08]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.88231E+03, 0.14770E+04, 0.21661E+04, 0.29384E+04, 0.37859E+04, 0.47034E+04, 0.56879E+04, + 0.67388E+04, 0.78581E+04, 0.90501E+04, 0.10321E+05, 0.11680E+05, 0.13136E+05, 0.14702E+05, + 0.16389E+05, 0.18212E+05, 0.20186E+05, 0.22328E+05, 0.24654E+05, 0.27185E+05, 0.29941E+05, + 0.32943E+05, 0.36216E+05, 0.39786E+05, 0.43681E+05, 0.47930E+05, 0.52567E+05, 0.57625E+05, + 0.63144E+05, 0.69164E+05, 0.75730E+05, 0.82890E+05, 0.90693E+05, 0.99198E+05, 0.10846E+06, + 0.11855E+06, 0.12954E+06, 0.14149E+06, 0.15450E+06, 0.16864E+06, 0.18402E+06, 0.20072E+06, + 0.21886E+06, 0.23856E+06, 0.25993E+06, 0.28312E+06, 0.30825E+06, 0.33550E+06, 0.36501E+06, + 0.39696E+06, 0.43155E+06, 0.46896E+06, 0.50942E+06, 0.55315E+06, 0.60039E+06, 0.65141E+06, + 0.70648E+06, 0.76589E+06, 0.82997E+06, 0.89904E+06, 0.97346E+06, 0.10536E+07, 0.11399E+07, + 0.12327E+07, 0.13326E+07, 0.14400E+07, 0.15554E+07, 0.16793E+07, 0.18124E+07, 0.19553E+07, + 0.21085E+07, 0.22729E+07, 0.24490E+07, 0.26378E+07, 0.28400E+07, 0.30565E+07, 0.32881E+07, + 0.35360E+07, 0.38010E+07, 0.40843E+07, 0.43870E+07, 0.47103E+07, 0.50555E+07, 0.54239E+07, + 0.58169E+07, 0.62361E+07, 0.66830E+07, 0.71592E+07, 0.76666E+07, 0.82069E+07, 0.87820E+07, + 0.93940E+07, 0.10045E+08, 0.10737E+08, 0.11473E+08, 0.12256E+08, 0.13086E+08, 0.13969E+08, + 0.14905E+08, 0.15899E+08, 0.16954E+08, 0.18072E+08, 0.19258E+08, 0.20515E+08, 0.21847E+08, + 0.23257E+08, 0.24750E+08, 0.26331E+08, 0.28004E+08, 0.29774E+08, 0.31646E+08, 0.33625E+08, + 0.35716E+08, 0.37926E+08, 0.40261E+08, 0.42726E+08, 0.45329E+08, 0.48077E+08, 0.50975E+08]) # --------------- O2 66: M = 7, I = 1 --------------------- M = 7 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.44334E+02, 0.62460E+02, 0.80596E+02, - 0.98738E+02, 0.11688E+03, 0.13503E+03, 0.15319E+03, 0.17136E+03, - 0.18954E+03, 0.20775E+03, 0.22600E+03, 0.24431E+03, 0.26270E+03, - 0.28119E+03, 0.29981E+03, 0.31857E+03, 0.33750E+03, 0.35662E+03, - 0.37594E+03, 0.39550E+03, 0.41529E+03, 0.43535E+03, 0.45568E+03, - 0.47630E+03, 0.49722E+03, 0.51844E+03, 0.53998E+03, 0.56185E+03, - 0.58406E+03, 0.60660E+03, 0.62949E+03, 0.65274E+03, 0.67635E+03, - 0.70031E+03, 0.72465E+03, 0.74936E+03, 0.77444E+03, 0.79990E+03, - 0.82574E+03, 0.85197E+03, 0.87858E+03, 0.90558E+03, 0.93297E+03, - 0.96076E+03, 0.98895E+03, 0.10175E+04, 0.10465E+04, 0.10759E+04, - 0.11057E+04, 0.11359E+04, 0.11665E+04, 0.11976E+04, 0.12290E+04, - 0.12609E+04, 0.12931E+04, 0.13258E+04, 0.13590E+04, 0.13925E+04, - 0.14265E+04, 0.14609E+04, 0.14958E+04, 0.15311E+04, 0.15669E+04, - 0.16031E+04, 0.16397E+04, 0.16768E+04, 0.17144E+04, 0.17524E+04, - 0.17909E+04, 0.18298E+04, 0.18692E+04, 0.19091E+04, 0.19495E+04, - 0.19904E+04, 0.20318E+04, 0.20736E+04, 0.21160E+04, 0.21588E+04, - 0.22022E+04, 0.22461E+04, 0.22905E+04, 0.23354E+04, 0.23809E+04, - 0.24268E+04, 0.24734E+04, 0.25204E+04, 0.25680E+04, 0.26162E+04, - 0.26649E+04, 0.27142E+04, 0.27641E+04, 0.28145E+04, 0.28655E+04, - 0.29171E+04, 0.29693E+04, 0.30221E+04, 0.30755E+04, 0.31295E+04, - 0.31841E+04, 0.32393E+04, 0.32951E+04, 0.33516E+04, 0.34087E+04, - 0.34665E+04, 0.35249E+04, 0.35839E+04, 0.36436E+04, 0.37040E+04, - 0.37650E+04, 0.38267E+04, 0.38891E+04, 0.39522E+04, 0.40159E+04, - 0.40804E+04, 0.41455E+04, 0.42114E+04, 0.42780E+04, 0.43452E+04, - 0.44132E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.44334E+02, 0.62460E+02, 0.80596E+02, 0.98738E+02, 0.11688E+03, 0.13503E+03, 0.15319E+03, + 0.17136E+03, 0.18954E+03, 0.20775E+03, 0.22600E+03, 0.24431E+03, 0.26270E+03, 0.28119E+03, + 0.29981E+03, 0.31857E+03, 0.33750E+03, 0.35662E+03, 0.37594E+03, 0.39550E+03, 0.41529E+03, + 0.43535E+03, 0.45568E+03, 0.47630E+03, 0.49722E+03, 0.51844E+03, 0.53998E+03, 0.56185E+03, + 0.58406E+03, 0.60660E+03, 0.62949E+03, 0.65274E+03, 0.67635E+03, 0.70031E+03, 0.72465E+03, + 0.74936E+03, 0.77444E+03, 0.79990E+03, 0.82574E+03, 0.85197E+03, 0.87858E+03, 0.90558E+03, + 0.93297E+03, 0.96076E+03, 0.98895E+03, 0.10175E+04, 0.10465E+04, 0.10759E+04, 0.11057E+04, + 0.11359E+04, 0.11665E+04, 0.11976E+04, 0.12290E+04, 0.12609E+04, 0.12931E+04, 0.13258E+04, + 0.13590E+04, 0.13925E+04, 0.14265E+04, 0.14609E+04, 0.14958E+04, 0.15311E+04, 0.15669E+04, + 0.16031E+04, 0.16397E+04, 0.16768E+04, 0.17144E+04, 0.17524E+04, 0.17909E+04, 0.18298E+04, + 0.18692E+04, 0.19091E+04, 0.19495E+04, 0.19904E+04, 0.20318E+04, 0.20736E+04, 0.21160E+04, + 0.21588E+04, 0.22022E+04, 0.22461E+04, 0.22905E+04, 0.23354E+04, 0.23809E+04, 0.24268E+04, + 0.24734E+04, 0.25204E+04, 0.25680E+04, 0.26162E+04, 0.26649E+04, 0.27142E+04, 0.27641E+04, + 0.28145E+04, 0.28655E+04, 0.29171E+04, 0.29693E+04, 0.30221E+04, 0.30755E+04, 0.31295E+04, + 0.31841E+04, 0.32393E+04, 0.32951E+04, 0.33516E+04, 0.34087E+04, 0.34665E+04, 0.35249E+04, + 0.35839E+04, 0.36436E+04, 0.37040E+04, 0.37650E+04, 0.38267E+04, 0.38891E+04, 0.39522E+04, + 0.40159E+04, 0.40804E+04, 0.41455E+04, 0.42114E+04, 0.42780E+04, 0.43452E+04, 0.44132E+04]) # --------------- O2 68: M = 7, I = 2 --------------------- M = 7 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.89206E+02, 0.12759E+03, 0.16600E+03, - 0.20442E+03, 0.24285E+03, 0.28128E+03, 0.31973E+03, 0.35821E+03, - 0.39672E+03, 0.43530E+03, 0.47398E+03, 0.51281E+03, 0.55183E+03, - 0.59108E+03, 0.63062E+03, 0.67051E+03, 0.71078E+03, 0.75148E+03, - 0.79265E+03, 0.83435E+03, 0.87659E+03, 0.91941E+03, 0.96285E+03, - 0.10069E+04, 0.10517E+04, 0.10971E+04, 0.11432E+04, 0.11901E+04, - 0.12377E+04, 0.12861E+04, 0.13352E+04, 0.13851E+04, 0.14358E+04, - 0.14872E+04, 0.15395E+04, 0.15926E+04, 0.16466E+04, 0.17013E+04, - 0.17569E+04, 0.18134E+04, 0.18706E+04, 0.19288E+04, 0.19877E+04, - 0.20476E+04, 0.21083E+04, 0.21698E+04, 0.22323E+04, 0.22956E+04, - 0.23598E+04, 0.24248E+04, 0.24908E+04, 0.25576E+04, 0.26253E+04, - 0.26940E+04, 0.27635E+04, 0.28339E+04, 0.29052E+04, 0.29775E+04, - 0.30506E+04, 0.31247E+04, 0.31997E+04, 0.32756E+04, 0.33524E+04, - 0.34302E+04, 0.35089E+04, 0.35885E+04, 0.36691E+04, 0.37506E+04, - 0.38331E+04, 0.39166E+04, 0.40010E+04, 0.40864E+04, 0.41727E+04, - 0.42601E+04, 0.43484E+04, 0.44377E+04, 0.45280E+04, 0.46193E+04, - 0.47116E+04, 0.48049E+04, 0.48992E+04, 0.49946E+04, 0.50909E+04, - 0.51883E+04, 0.52868E+04, 0.53863E+04, 0.54868E+04, 0.55884E+04, - 0.56911E+04, 0.57949E+04, 0.58997E+04, 0.60056E+04, 0.61126E+04, - 0.62207E+04, 0.63298E+04, 0.64401E+04, 0.65516E+04, 0.66641E+04, - 0.67778E+04, 0.68926E+04, 0.70085E+04, 0.71256E+04, 0.72439E+04, - 0.73633E+04, 0.74839E+04, 0.76056E+04, 0.77286E+04, 0.78527E+04, - 0.79781E+04, 0.81046E+04, 0.82324E+04, 0.83613E+04, 0.84915E+04, - 0.86229E+04, 0.87556E+04, 0.88895E+04, 0.90247E+04, 0.91611E+04, - 0.92988E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.89206E+02, 0.12759E+03, 0.16600E+03, 0.20442E+03, 0.24285E+03, 0.28128E+03, 0.31973E+03, + 0.35821E+03, 0.39672E+03, 0.43530E+03, 0.47398E+03, 0.51281E+03, 0.55183E+03, 0.59108E+03, + 0.63062E+03, 0.67051E+03, 0.71078E+03, 0.75148E+03, 0.79265E+03, 0.83435E+03, 0.87659E+03, + 0.91941E+03, 0.96285E+03, 0.10069E+04, 0.10517E+04, 0.10971E+04, 0.11432E+04, 0.11901E+04, + 0.12377E+04, 0.12861E+04, 0.13352E+04, 0.13851E+04, 0.14358E+04, 0.14872E+04, 0.15395E+04, + 0.15926E+04, 0.16466E+04, 0.17013E+04, 0.17569E+04, 0.18134E+04, 0.18706E+04, 0.19288E+04, + 0.19877E+04, 0.20476E+04, 0.21083E+04, 0.21698E+04, 0.22323E+04, 0.22956E+04, 0.23598E+04, + 0.24248E+04, 0.24908E+04, 0.25576E+04, 0.26253E+04, 0.26940E+04, 0.27635E+04, 0.28339E+04, + 0.29052E+04, 0.29775E+04, 0.30506E+04, 0.31247E+04, 0.31997E+04, 0.32756E+04, 0.33524E+04, + 0.34302E+04, 0.35089E+04, 0.35885E+04, 0.36691E+04, 0.37506E+04, 0.38331E+04, 0.39166E+04, + 0.40010E+04, 0.40864E+04, 0.41727E+04, 0.42601E+04, 0.43484E+04, 0.44377E+04, 0.45280E+04, + 0.46193E+04, 0.47116E+04, 0.48049E+04, 0.48992E+04, 0.49946E+04, 0.50909E+04, 0.51883E+04, + 0.52868E+04, 0.53863E+04, 0.54868E+04, 0.55884E+04, 0.56911E+04, 0.57949E+04, 0.58997E+04, + 0.60056E+04, 0.61126E+04, 0.62207E+04, 0.63298E+04, 0.64401E+04, 0.65516E+04, 0.66641E+04, + 0.67778E+04, 0.68926E+04, 0.70085E+04, 0.71256E+04, 0.72439E+04, 0.73633E+04, 0.74839E+04, + 0.76056E+04, 0.77286E+04, 0.78527E+04, 0.79781E+04, 0.81046E+04, 0.82324E+04, 0.83613E+04, + 0.84915E+04, 0.86229E+04, 0.87556E+04, 0.88895E+04, 0.90247E+04, 0.91611E+04, 0.92988E+04]) # --------------- O2 67: M = 7, I = 3 --------------------- M = 7 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.52071E+03, 0.74484E+03, 0.96908E+03, - 0.11934E+04, 0.14177E+04, 0.16422E+04, 0.18667E+04, 0.20913E+04, - 0.23161E+04, 0.25413E+04, 0.27671E+04, 0.29936E+04, 0.32212E+04, - 0.34501E+04, 0.36806E+04, 0.39130E+04, 0.41476E+04, 0.43846E+04, - 0.46242E+04, 0.48668E+04, 0.51125E+04, 0.53615E+04, 0.56140E+04, - 0.58701E+04, 0.61300E+04, 0.63938E+04, 0.66617E+04, 0.69337E+04, - 0.72099E+04, 0.74904E+04, 0.77754E+04, 0.80647E+04, 0.83586E+04, - 0.86571E+04, 0.89602E+04, 0.92680E+04, 0.95805E+04, 0.98977E+04, - 0.10220E+05, 0.10547E+05, 0.10878E+05, 0.11215E+05, 0.11556E+05, - 0.11903E+05, 0.12254E+05, 0.12611E+05, 0.12972E+05, 0.13338E+05, - 0.13710E+05, 0.14086E+05, 0.14468E+05, 0.14855E+05, 0.15247E+05, - 0.15644E+05, 0.16046E+05, 0.16453E+05, 0.16866E+05, 0.17283E+05, - 0.17706E+05, 0.18135E+05, 0.18568E+05, 0.19007E+05, 0.19452E+05, - 0.19901E+05, 0.20356E+05, 0.20817E+05, 0.21283E+05, 0.21754E+05, - 0.22231E+05, 0.22713E+05, 0.23201E+05, 0.23695E+05, 0.24194E+05, - 0.24699E+05, 0.25209E+05, 0.25725E+05, 0.26247E+05, 0.26775E+05, - 0.27308E+05, 0.27847E+05, 0.28393E+05, 0.28944E+05, 0.29500E+05, - 0.30063E+05, 0.30632E+05, 0.31207E+05, 0.31788E+05, 0.32375E+05, - 0.32968E+05, 0.33568E+05, 0.34173E+05, 0.34785E+05, 0.35403E+05, - 0.36028E+05, 0.36659E+05, 0.37296E+05, 0.37939E+05, 0.38590E+05, - 0.39246E+05, 0.39909E+05, 0.40579E+05, 0.41256E+05, 0.41939E+05, - 0.42629E+05, 0.43325E+05, 0.44029E+05, 0.44739E+05, 0.45456E+05, - 0.46180E+05, 0.46911E+05, 0.47649E+05, 0.48394E+05, 0.49146E+05, - 0.49905E+05, 0.50671E+05, 0.51445E+05, 0.52226E+05, 0.53014E+05, - 0.53809E+05]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.52071E+03, 0.74484E+03, 0.96908E+03, 0.11934E+04, 0.14177E+04, 0.16422E+04, 0.18667E+04, + 0.20913E+04, 0.23161E+04, 0.25413E+04, 0.27671E+04, 0.29936E+04, 0.32212E+04, 0.34501E+04, + 0.36806E+04, 0.39130E+04, 0.41476E+04, 0.43846E+04, 0.46242E+04, 0.48668E+04, 0.51125E+04, + 0.53615E+04, 0.56140E+04, 0.58701E+04, 0.61300E+04, 0.63938E+04, 0.66617E+04, 0.69337E+04, + 0.72099E+04, 0.74904E+04, 0.77754E+04, 0.80647E+04, 0.83586E+04, 0.86571E+04, 0.89602E+04, + 0.92680E+04, 0.95805E+04, 0.98977E+04, 0.10220E+05, 0.10547E+05, 0.10878E+05, 0.11215E+05, + 0.11556E+05, 0.11903E+05, 0.12254E+05, 0.12611E+05, 0.12972E+05, 0.13338E+05, 0.13710E+05, + 0.14086E+05, 0.14468E+05, 0.14855E+05, 0.15247E+05, 0.15644E+05, 0.16046E+05, 0.16453E+05, + 0.16866E+05, 0.17283E+05, 0.17706E+05, 0.18135E+05, 0.18568E+05, 0.19007E+05, 0.19452E+05, + 0.19901E+05, 0.20356E+05, 0.20817E+05, 0.21283E+05, 0.21754E+05, 0.22231E+05, 0.22713E+05, + 0.23201E+05, 0.23695E+05, 0.24194E+05, 0.24699E+05, 0.25209E+05, 0.25725E+05, 0.26247E+05, + 0.26775E+05, 0.27308E+05, 0.27847E+05, 0.28393E+05, 0.28944E+05, 0.29500E+05, 0.30063E+05, + 0.30632E+05, 0.31207E+05, 0.31788E+05, 0.32375E+05, 0.32968E+05, 0.33568E+05, 0.34173E+05, + 0.34785E+05, 0.35403E+05, 0.36028E+05, 0.36659E+05, 0.37296E+05, 0.37939E+05, 0.38590E+05, + 0.39246E+05, 0.39909E+05, 0.40579E+05, 0.41256E+05, 0.41939E+05, 0.42629E+05, 0.43325E+05, + 0.44029E+05, 0.44739E+05, 0.45456E+05, 0.46180E+05, 0.46911E+05, 0.47649E+05, 0.48394E+05, + 0.49146E+05, 0.49905E+05, 0.50671E+05, 0.51445E+05, 0.52226E+05, 0.53014E+05, 0.53809E+05]) # --------------- NO 46: M = 8, I = 1 --------------------- M = 8 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(3.) -TIPS_ISO_HASH[(M, I)] = float32([0.15840E+03, 0.23971E+03, 0.33080E+03, - 0.42907E+03, 0.53251E+03, 0.63972E+03, 0.74975E+03, 0.86195E+03, - 0.97582E+03, 0.10911E+04, 0.12074E+04, 0.13248E+04, 0.14430E+04, - 0.15621E+04, 0.16820E+04, 0.18027E+04, 0.19243E+04, 0.20468E+04, - 0.21703E+04, 0.22948E+04, 0.24204E+04, 0.25472E+04, 0.26753E+04, - 0.28046E+04, 0.29354E+04, 0.30676E+04, 0.32013E+04, 0.33365E+04, - 0.34734E+04, 0.36120E+04, 0.37522E+04, 0.38942E+04, 0.40379E+04, - 0.41835E+04, 0.43310E+04, 0.44803E+04, 0.46316E+04, 0.47849E+04, - 0.49400E+04, 0.50972E+04, 0.52564E+04, 0.54176E+04, 0.55809E+04, - 0.57462E+04, 0.59137E+04, 0.60832E+04, 0.62548E+04, 0.64286E+04, - 0.66045E+04, 0.67825E+04, 0.69628E+04, 0.71451E+04, 0.73297E+04, - 0.75164E+04, 0.77053E+04, 0.78964E+04, 0.80897E+04, 0.82853E+04, - 0.84830E+04, 0.86830E+04, 0.88852E+04, 0.90896E+04, 0.92963E+04, - 0.95052E+04, 0.97164E+04, 0.99297E+04, 0.10145E+05, 0.10363E+05, - 0.10583E+05, 0.10806E+05, 0.11031E+05, 0.11258E+05, 0.11487E+05, - 0.11718E+05, 0.11952E+05, 0.12188E+05, 0.12426E+05, 0.12667E+05, - 0.12910E+05, 0.13155E+05, 0.13403E+05, 0.13652E+05, 0.13905E+05, - 0.14159E+05, 0.14416E+05, 0.14675E+05, 0.14936E+05, 0.15199E+05, - 0.15465E+05, 0.15733E+05, 0.16004E+05, 0.16277E+05, 0.16552E+05, - 0.16829E+05, 0.17109E+05, 0.17391E+05, 0.17675E+05, 0.17962E+05, - 0.18251E+05, 0.18542E+05, 0.18836E+05, 0.19131E+05, 0.19430E+05, - 0.19730E+05, 0.20033E+05, 0.20338E+05, 0.20646E+05, 0.20955E+05, - 0.21268E+05, 0.21582E+05, 0.21899E+05, 0.22218E+05, 0.22539E+05, - 0.22863E+05, 0.23189E+05, 0.23518E+05, 0.23848E+05, 0.24181E+05, - 0.24517E+05]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.15840E+03, 0.23971E+03, 0.33080E+03, 0.42907E+03, 0.53251E+03, 0.63972E+03, 0.74975E+03, + 0.86195E+03, 0.97582E+03, 0.10911E+04, 0.12074E+04, 0.13248E+04, 0.14430E+04, 0.15621E+04, + 0.16820E+04, 0.18027E+04, 0.19243E+04, 0.20468E+04, 0.21703E+04, 0.22948E+04, 0.24204E+04, + 0.25472E+04, 0.26753E+04, 0.28046E+04, 0.29354E+04, 0.30676E+04, 0.32013E+04, 0.33365E+04, + 0.34734E+04, 0.36120E+04, 0.37522E+04, 0.38942E+04, 0.40379E+04, 0.41835E+04, 0.43310E+04, + 0.44803E+04, 0.46316E+04, 0.47849E+04, 0.49400E+04, 0.50972E+04, 0.52564E+04, 0.54176E+04, + 0.55809E+04, 0.57462E+04, 0.59137E+04, 0.60832E+04, 0.62548E+04, 0.64286E+04, 0.66045E+04, + 0.67825E+04, 0.69628E+04, 0.71451E+04, 0.73297E+04, 0.75164E+04, 0.77053E+04, 0.78964E+04, + 0.80897E+04, 0.82853E+04, 0.84830E+04, 0.86830E+04, 0.88852E+04, 0.90896E+04, 0.92963E+04, + 0.95052E+04, 0.97164E+04, 0.99297E+04, 0.10145E+05, 0.10363E+05, 0.10583E+05, 0.10806E+05, + 0.11031E+05, 0.11258E+05, 0.11487E+05, 0.11718E+05, 0.11952E+05, 0.12188E+05, 0.12426E+05, + 0.12667E+05, 0.12910E+05, 0.13155E+05, 0.13403E+05, 0.13652E+05, 0.13905E+05, 0.14159E+05, + 0.14416E+05, 0.14675E+05, 0.14936E+05, 0.15199E+05, 0.15465E+05, 0.15733E+05, 0.16004E+05, + 0.16277E+05, 0.16552E+05, 0.16829E+05, 0.17109E+05, 0.17391E+05, 0.17675E+05, 0.17962E+05, + 0.18251E+05, 0.18542E+05, 0.18836E+05, 0.19131E+05, 0.19430E+05, 0.19730E+05, 0.20033E+05, + 0.20338E+05, 0.20646E+05, 0.20955E+05, 0.21268E+05, 0.21582E+05, 0.21899E+05, 0.22218E+05, + 0.22539E+05, 0.22863E+05, 0.23189E+05, 0.23518E+05, 0.23848E+05, 0.24181E+05, 0.24517E+05]) # --------------- NO 56: M = 8, I = 2 --------------------- M = 8 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.10942E+03, 0.16560E+03, 0.22856E+03, - 0.29647E+03, 0.36795E+03, 0.44204E+03, 0.51808E+03, 0.59561E+03, - 0.67432E+03, 0.75396E+03, 0.83439E+03, 0.91551E+03, 0.99725E+03, - 0.10796E+04, 0.11625E+04, 0.12460E+04, 0.13302E+04, 0.14150E+04, - 0.15005E+04, 0.15868E+04, 0.16739E+04, 0.17618E+04, 0.18506E+04, - 0.19404E+04, 0.20311E+04, 0.21229E+04, 0.22158E+04, 0.23098E+04, - 0.24050E+04, 0.25013E+04, 0.25989E+04, 0.26976E+04, 0.27977E+04, - 0.28991E+04, 0.30018E+04, 0.31058E+04, 0.32112E+04, 0.33180E+04, - 0.34262E+04, 0.35358E+04, 0.36468E+04, 0.37593E+04, 0.38732E+04, - 0.39885E+04, 0.41054E+04, 0.42237E+04, 0.43436E+04, 0.44649E+04, - 0.45877E+04, 0.47121E+04, 0.48379E+04, 0.49654E+04, 0.50943E+04, - 0.52248E+04, 0.53568E+04, 0.54904E+04, 0.56255E+04, 0.57622E+04, - 0.59004E+04, 0.60403E+04, 0.61816E+04, 0.63246E+04, 0.64692E+04, - 0.66152E+04, 0.67630E+04, 0.69123E+04, 0.70631E+04, 0.72156E+04, - 0.73696E+04, 0.75253E+04, 0.76825E+04, 0.78414E+04, 0.80018E+04, - 0.81638E+04, 0.83275E+04, 0.84927E+04, 0.86596E+04, 0.88280E+04, - 0.89981E+04, 0.91698E+04, 0.93430E+04, 0.95180E+04, 0.96945E+04, - 0.98726E+04, 0.10052E+05, 0.10234E+05, 0.10417E+05, 0.10601E+05, - 0.10788E+05, 0.10975E+05, 0.11165E+05, 0.11356E+05, 0.11549E+05, - 0.11743E+05, 0.11939E+05, 0.12137E+05, 0.12336E+05, 0.12537E+05, - 0.12739E+05, 0.12943E+05, 0.13149E+05, 0.13356E+05, 0.13565E+05, - 0.13776E+05, 0.13988E+05, 0.14202E+05, 0.14418E+05, 0.14635E+05, - 0.14853E+05, 0.15074E+05, 0.15296E+05, 0.15520E+05, 0.15745E+05, - 0.15972E+05, 0.16200E+05, 0.16431E+05, 0.16663E+05, 0.16896E+05, - 0.17131E+05]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.10942E+03, 0.16560E+03, 0.22856E+03, 0.29647E+03, 0.36795E+03, 0.44204E+03, 0.51808E+03, + 0.59561E+03, 0.67432E+03, 0.75396E+03, 0.83439E+03, 0.91551E+03, 0.99725E+03, 0.10796E+04, + 0.11625E+04, 0.12460E+04, 0.13302E+04, 0.14150E+04, 0.15005E+04, 0.15868E+04, 0.16739E+04, + 0.17618E+04, 0.18506E+04, 0.19404E+04, 0.20311E+04, 0.21229E+04, 0.22158E+04, 0.23098E+04, + 0.24050E+04, 0.25013E+04, 0.25989E+04, 0.26976E+04, 0.27977E+04, 0.28991E+04, 0.30018E+04, + 0.31058E+04, 0.32112E+04, 0.33180E+04, 0.34262E+04, 0.35358E+04, 0.36468E+04, 0.37593E+04, + 0.38732E+04, 0.39885E+04, 0.41054E+04, 0.42237E+04, 0.43436E+04, 0.44649E+04, 0.45877E+04, + 0.47121E+04, 0.48379E+04, 0.49654E+04, 0.50943E+04, 0.52248E+04, 0.53568E+04, 0.54904E+04, + 0.56255E+04, 0.57622E+04, 0.59004E+04, 0.60403E+04, 0.61816E+04, 0.63246E+04, 0.64692E+04, + 0.66152E+04, 0.67630E+04, 0.69123E+04, 0.70631E+04, 0.72156E+04, 0.73696E+04, 0.75253E+04, + 0.76825E+04, 0.78414E+04, 0.80018E+04, 0.81638E+04, 0.83275E+04, 0.84927E+04, 0.86596E+04, + 0.88280E+04, 0.89981E+04, 0.91698E+04, 0.93430E+04, 0.95180E+04, 0.96945E+04, 0.98726E+04, + 0.10052E+05, 0.10234E+05, 0.10417E+05, 0.10601E+05, 0.10788E+05, 0.10975E+05, 0.11165E+05, + 0.11356E+05, 0.11549E+05, 0.11743E+05, 0.11939E+05, 0.12137E+05, 0.12336E+05, 0.12537E+05, + 0.12739E+05, 0.12943E+05, 0.13149E+05, 0.13356E+05, 0.13565E+05, 0.13776E+05, 0.13988E+05, + 0.14202E+05, 0.14418E+05, 0.14635E+05, 0.14853E+05, 0.15074E+05, 0.15296E+05, 0.15520E+05, + 0.15745E+05, 0.15972E+05, 0.16200E+05, 0.16431E+05, 0.16663E+05, 0.16896E+05, 0.17131E+05]) # --------------- NO 48: M = 8, I = 3 --------------------- M = 8 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(3.) -TIPS_ISO_HASH[(M, I)] = float32([0.16695E+03, 0.25269E+03, 0.34876E+03, - 0.45239E+03, 0.56148E+03, 0.67455E+03, 0.79059E+03, 0.90891E+03, - 0.10290E+04, 0.11506E+04, 0.12733E+04, 0.13971E+04, 0.15219E+04, - 0.16476E+04, 0.17742E+04, 0.19017E+04, 0.20302E+04, 0.21598E+04, - 0.22904E+04, 0.24223E+04, 0.25553E+04, 0.26897E+04, 0.28255E+04, - 0.29628E+04, 0.31016E+04, 0.32420E+04, 0.33842E+04, 0.35280E+04, - 0.36736E+04, 0.38211E+04, 0.39704E+04, 0.41217E+04, 0.42750E+04, - 0.44302E+04, 0.45876E+04, 0.47469E+04, 0.49084E+04, 0.50720E+04, - 0.52378E+04, 0.54058E+04, 0.55759E+04, 0.57483E+04, 0.59230E+04, - 0.60999E+04, 0.62791E+04, 0.64605E+04, 0.66443E+04, 0.68304E+04, - 0.70187E+04, 0.72095E+04, 0.74026E+04, 0.75980E+04, 0.77958E+04, - 0.79960E+04, 0.81986E+04, 0.84036E+04, 0.86109E+04, 0.88207E+04, - 0.90328E+04, 0.92474E+04, 0.94644E+04, 0.96839E+04, 0.99057E+04, - 0.10130E+05, 0.10357E+05, 0.10586E+05, 0.10817E+05, 0.11052E+05, - 0.11288E+05, 0.11527E+05, 0.11768E+05, 0.12012E+05, 0.12259E+05, - 0.12507E+05, 0.12759E+05, 0.13012E+05, 0.13269E+05, 0.13527E+05, - 0.13788E+05, 0.14052E+05, 0.14318E+05, 0.14587E+05, 0.14858E+05, - 0.15131E+05, 0.15408E+05, 0.15686E+05, 0.15967E+05, 0.16251E+05, - 0.16537E+05, 0.16825E+05, 0.17116E+05, 0.17410E+05, 0.17706E+05, - 0.18004E+05, 0.18305E+05, 0.18609E+05, 0.18915E+05, 0.19224E+05, - 0.19535E+05, 0.19848E+05, 0.20164E+05, 0.20483E+05, 0.20804E+05, - 0.21127E+05, 0.21453E+05, 0.21782E+05, 0.22113E+05, 0.22447E+05, - 0.22783E+05, 0.23122E+05, 0.23463E+05, 0.23807E+05, 0.24153E+05, - 0.24502E+05, 0.24853E+05, 0.25207E+05, 0.25563E+05, 0.25922E+05, - 0.26283E+05]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.16695E+03, 0.25269E+03, 0.34876E+03, 0.45239E+03, 0.56148E+03, 0.67455E+03, 0.79059E+03, + 0.90891E+03, 0.10290E+04, 0.11506E+04, 0.12733E+04, 0.13971E+04, 0.15219E+04, 0.16476E+04, + 0.17742E+04, 0.19017E+04, 0.20302E+04, 0.21598E+04, 0.22904E+04, 0.24223E+04, 0.25553E+04, + 0.26897E+04, 0.28255E+04, 0.29628E+04, 0.31016E+04, 0.32420E+04, 0.33842E+04, 0.35280E+04, + 0.36736E+04, 0.38211E+04, 0.39704E+04, 0.41217E+04, 0.42750E+04, 0.44302E+04, 0.45876E+04, + 0.47469E+04, 0.49084E+04, 0.50720E+04, 0.52378E+04, 0.54058E+04, 0.55759E+04, 0.57483E+04, + 0.59230E+04, 0.60999E+04, 0.62791E+04, 0.64605E+04, 0.66443E+04, 0.68304E+04, 0.70187E+04, + 0.72095E+04, 0.74026E+04, 0.75980E+04, 0.77958E+04, 0.79960E+04, 0.81986E+04, 0.84036E+04, + 0.86109E+04, 0.88207E+04, 0.90328E+04, 0.92474E+04, 0.94644E+04, 0.96839E+04, 0.99057E+04, + 0.10130E+05, 0.10357E+05, 0.10586E+05, 0.10817E+05, 0.11052E+05, 0.11288E+05, 0.11527E+05, + 0.11768E+05, 0.12012E+05, 0.12259E+05, 0.12507E+05, 0.12759E+05, 0.13012E+05, 0.13269E+05, + 0.13527E+05, 0.13788E+05, 0.14052E+05, 0.14318E+05, 0.14587E+05, 0.14858E+05, 0.15131E+05, + 0.15408E+05, 0.15686E+05, 0.15967E+05, 0.16251E+05, 0.16537E+05, 0.16825E+05, 0.17116E+05, + 0.17410E+05, 0.17706E+05, 0.18004E+05, 0.18305E+05, 0.18609E+05, 0.18915E+05, 0.19224E+05, + 0.19535E+05, 0.19848E+05, 0.20164E+05, 0.20483E+05, 0.20804E+05, 0.21127E+05, 0.21453E+05, + 0.21782E+05, 0.22113E+05, 0.22447E+05, 0.22783E+05, 0.23122E+05, 0.23463E+05, 0.23807E+05, + 0.24153E+05, 0.24502E+05, 0.24853E+05, 0.25207E+05, 0.25563E+05, 0.25922E+05, 0.26283E+05]) # --------------- SO2 626: M = 9, I = 1 --------------------- M = 9 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.52899E+03, 0.89171E+03, 0.13139E+04, - 0.17915E+04, 0.23246E+04, 0.29155E+04, 0.35675E+04, 0.42848E+04, - 0.50723E+04, 0.59352E+04, 0.68794E+04, 0.79109E+04, 0.90366E+04, - 0.10264E+05, 0.11599E+05, 0.13052E+05, 0.14629E+05, 0.16340E+05, - 0.18193E+05, 0.20199E+05, 0.22366E+05, 0.24704E+05, 0.27225E+05, - 0.29938E+05, 0.32855E+05, 0.35987E+05, 0.39346E+05, 0.42944E+05, - 0.46794E+05, 0.50909E+05, 0.55302E+05, 0.59986E+05, 0.64977E+05, - 0.70288E+05, 0.75934E+05, 0.81931E+05, 0.88294E+05, 0.95040E+05, - 0.10219E+06, 0.10975E+06, 0.11774E+06, 0.12619E+06, 0.13511E+06, - 0.14452E+06, 0.15443E+06, 0.16487E+06, 0.17586E+06, 0.18742E+06, - 0.19957E+06, 0.21234E+06, 0.22573E+06, 0.23978E+06, 0.25451E+06, - 0.26995E+06, 0.28611E+06, 0.30302E+06, 0.32071E+06, 0.33920E+06, - 0.35852E+06, 0.37869E+06, 0.39974E+06, 0.42171E+06, 0.44461E+06, - 0.46848E+06, 0.49334E+06, 0.51922E+06, 0.54617E+06, 0.57419E+06, - 0.60334E+06, 0.63363E+06, 0.66511E+06, 0.69780E+06, 0.73174E+06, - 0.76696E+06, 0.80349E+06, 0.84138E+06, 0.88066E+06, 0.92136E+06, - 0.96352E+06, 0.10072E+07, 0.10524E+07, 0.10992E+07, 0.11475E+07, - 0.11976E+07, 0.12493E+07, 0.13028E+07, 0.13580E+07, 0.14151E+07, - 0.14741E+07, 0.15349E+07, 0.15977E+07, 0.16625E+07, 0.17293E+07, - 0.17982E+07, 0.18693E+07, 0.19425E+07, 0.20180E+07, 0.20958E+07, - 0.21758E+07, 0.22583E+07, 0.23432E+07, 0.24305E+07, 0.25204E+07, - 0.26129E+07, 0.27080E+07, 0.28058E+07, 0.29064E+07, 0.30097E+07, - 0.31159E+07, 0.32250E+07, 0.33371E+07, 0.34522E+07, 0.35705E+07, - 0.36918E+07, 0.38164E+07, 0.39442E+07, 0.40754E+07, 0.42099E+07, - 0.43479E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.52899E+03, 0.89171E+03, 0.13139E+04, 0.17915E+04, 0.23246E+04, 0.29155E+04, 0.35675E+04, + 0.42848E+04, 0.50723E+04, 0.59352E+04, 0.68794E+04, 0.79109E+04, 0.90366E+04, 0.10264E+05, + 0.11599E+05, 0.13052E+05, 0.14629E+05, 0.16340E+05, 0.18193E+05, 0.20199E+05, 0.22366E+05, + 0.24704E+05, 0.27225E+05, 0.29938E+05, 0.32855E+05, 0.35987E+05, 0.39346E+05, 0.42944E+05, + 0.46794E+05, 0.50909E+05, 0.55302E+05, 0.59986E+05, 0.64977E+05, 0.70288E+05, 0.75934E+05, + 0.81931E+05, 0.88294E+05, 0.95040E+05, 0.10219E+06, 0.10975E+06, 0.11774E+06, 0.12619E+06, + 0.13511E+06, 0.14452E+06, 0.15443E+06, 0.16487E+06, 0.17586E+06, 0.18742E+06, 0.19957E+06, + 0.21234E+06, 0.22573E+06, 0.23978E+06, 0.25451E+06, 0.26995E+06, 0.28611E+06, 0.30302E+06, + 0.32071E+06, 0.33920E+06, 0.35852E+06, 0.37869E+06, 0.39974E+06, 0.42171E+06, 0.44461E+06, + 0.46848E+06, 0.49334E+06, 0.51922E+06, 0.54617E+06, 0.57419E+06, 0.60334E+06, 0.63363E+06, + 0.66511E+06, 0.69780E+06, 0.73174E+06, 0.76696E+06, 0.80349E+06, 0.84138E+06, 0.88066E+06, + 0.92136E+06, 0.96352E+06, 0.10072E+07, 0.10524E+07, 0.10992E+07, 0.11475E+07, 0.11976E+07, + 0.12493E+07, 0.13028E+07, 0.13580E+07, 0.14151E+07, 0.14741E+07, 0.15349E+07, 0.15977E+07, + 0.16625E+07, 0.17293E+07, 0.17982E+07, 0.18693E+07, 0.19425E+07, 0.20180E+07, 0.20958E+07, + 0.21758E+07, 0.22583E+07, 0.23432E+07, 0.24305E+07, 0.25204E+07, 0.26129E+07, 0.27080E+07, + 0.28058E+07, 0.29064E+07, 0.30097E+07, 0.31159E+07, 0.32250E+07, 0.33371E+07, 0.34522E+07, + 0.35705E+07, 0.36918E+07, 0.38164E+07, 0.39442E+07, 0.40754E+07, 0.42099E+07, 0.43479E+07]) # --------------- SO2 646: M = 9, I = 2 --------------------- M = 9 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.53140E+03, 0.89578E+03, 0.13199E+04, - 0.17997E+04, 0.23353E+04, 0.29288E+04, 0.35837E+04, 0.43043E+04, - 0.50953E+04, 0.59621E+04, 0.69104E+04, 0.79465E+04, 0.90772E+04, - 0.10310E+05, 0.11651E+05, 0.13110E+05, 0.14694E+05, 0.16413E+05, - 0.18274E+05, 0.20289E+05, 0.22465E+05, 0.24814E+05, 0.27345E+05, - 0.30070E+05, 0.33000E+05, 0.36145E+05, 0.39519E+05, 0.43133E+05, - 0.46999E+05, 0.51132E+05, 0.55544E+05, 0.60248E+05, 0.65260E+05, - 0.70594E+05, 0.76264E+05, 0.82287E+05, 0.88678E+05, 0.95453E+05, - 0.10263E+06, 0.11022E+06, 0.11825E+06, 0.12674E+06, 0.13569E+06, - 0.14514E+06, 0.15510E+06, 0.16558E+06, 0.17662E+06, 0.18823E+06, - 0.20043E+06, 0.21325E+06, 0.22670E+06, 0.24081E+06, 0.25561E+06, - 0.27111E+06, 0.28733E+06, 0.30432E+06, 0.32208E+06, 0.34065E+06, - 0.36005E+06, 0.38031E+06, 0.40145E+06, 0.42351E+06, 0.44651E+06, - 0.47047E+06, 0.49544E+06, 0.52144E+06, 0.54849E+06, 0.57664E+06, - 0.60591E+06, 0.63633E+06, 0.66794E+06, 0.70077E+06, 0.73485E+06, - 0.77022E+06, 0.80691E+06, 0.84496E+06, 0.88440E+06, 0.92527E+06, - 0.96761E+06, 0.10115E+07, 0.10568E+07, 0.11038E+07, 0.11524E+07, - 0.12027E+07, 0.12546E+07, 0.13083E+07, 0.13638E+07, 0.14211E+07, - 0.14803E+07, 0.15414E+07, 0.16045E+07, 0.16695E+07, 0.17366E+07, - 0.18059E+07, 0.18772E+07, 0.19507E+07, 0.20265E+07, 0.21046E+07, - 0.21850E+07, 0.22678E+07, 0.23531E+07, 0.24408E+07, 0.25310E+07, - 0.26239E+07, 0.27194E+07, 0.28176E+07, 0.29186E+07, 0.30224E+07, - 0.31290E+07, 0.32386E+07, 0.33512E+07, 0.34668E+07, 0.35855E+07, - 0.37074E+07, 0.38324E+07, 0.39608E+07, 0.40925E+07, 0.42276E+07, - 0.43662E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.53140E+03, 0.89578E+03, 0.13199E+04, 0.17997E+04, 0.23353E+04, 0.29288E+04, 0.35837E+04, + 0.43043E+04, 0.50953E+04, 0.59621E+04, 0.69104E+04, 0.79465E+04, 0.90772E+04, 0.10310E+05, + 0.11651E+05, 0.13110E+05, 0.14694E+05, 0.16413E+05, 0.18274E+05, 0.20289E+05, 0.22465E+05, + 0.24814E+05, 0.27345E+05, 0.30070E+05, 0.33000E+05, 0.36145E+05, 0.39519E+05, 0.43133E+05, + 0.46999E+05, 0.51132E+05, 0.55544E+05, 0.60248E+05, 0.65260E+05, 0.70594E+05, 0.76264E+05, + 0.82287E+05, 0.88678E+05, 0.95453E+05, 0.10263E+06, 0.11022E+06, 0.11825E+06, 0.12674E+06, + 0.13569E+06, 0.14514E+06, 0.15510E+06, 0.16558E+06, 0.17662E+06, 0.18823E+06, 0.20043E+06, + 0.21325E+06, 0.22670E+06, 0.24081E+06, 0.25561E+06, 0.27111E+06, 0.28733E+06, 0.30432E+06, + 0.32208E+06, 0.34065E+06, 0.36005E+06, 0.38031E+06, 0.40145E+06, 0.42351E+06, 0.44651E+06, + 0.47047E+06, 0.49544E+06, 0.52144E+06, 0.54849E+06, 0.57664E+06, 0.60591E+06, 0.63633E+06, + 0.66794E+06, 0.70077E+06, 0.73485E+06, 0.77022E+06, 0.80691E+06, 0.84496E+06, 0.88440E+06, + 0.92527E+06, 0.96761E+06, 0.10115E+07, 0.10568E+07, 0.11038E+07, 0.11524E+07, 0.12027E+07, + 0.12546E+07, 0.13083E+07, 0.13638E+07, 0.14211E+07, 0.14803E+07, 0.15414E+07, 0.16045E+07, + 0.16695E+07, 0.17366E+07, 0.18059E+07, 0.18772E+07, 0.19507E+07, 0.20265E+07, 0.21046E+07, + 0.21850E+07, 0.22678E+07, 0.23531E+07, 0.24408E+07, 0.25310E+07, 0.26239E+07, 0.27194E+07, + 0.28176E+07, 0.29186E+07, 0.30224E+07, 0.31290E+07, 0.32386E+07, 0.33512E+07, 0.34668E+07, + 0.35855E+07, 0.37074E+07, 0.38324E+07, 0.39608E+07, 0.40925E+07, 0.42276E+07, 0.43662E+07]) # --------------- NO2 646: M = 10, I = 1 --------------------- M = 10 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(3.) -TIPS_ISO_HASH[(M, I)] = float32([0.12046E+04, 0.20297E+04, 0.29875E+04, - 0.40626E+04, 0.52463E+04, 0.65350E+04, 0.79286E+04, 0.94298E+04, - 0.11043E+05, 0.12776E+05, 0.14634E+05, 0.16627E+05, 0.18765E+05, - 0.21056E+05, 0.23511E+05, 0.26143E+05, 0.28961E+05, 0.31979E+05, - 0.35209E+05, 0.38663E+05, 0.42355E+05, 0.46300E+05, 0.50510E+05, - 0.55001E+05, 0.59787E+05, 0.64884E+05, 0.70308E+05, 0.76075E+05, - 0.82201E+05, 0.88704E+05, 0.95602E+05, 0.10291E+06, 0.11065E+06, - 0.11884E+06, 0.12750E+06, 0.13665E+06, 0.14631E+06, 0.15650E+06, - 0.16724E+06, 0.17856E+06, 0.19047E+06, 0.20301E+06, 0.21618E+06, - 0.23002E+06, 0.24456E+06, 0.25981E+06, 0.27580E+06, 0.29256E+06, - 0.31012E+06, 0.32850E+06, 0.34773E+06, 0.36784E+06, 0.38886E+06, - 0.41082E+06, 0.43374E+06, 0.45766E+06, 0.48262E+06, 0.50863E+06, - 0.53574E+06, 0.56398E+06, 0.59339E+06, 0.62398E+06, 0.65581E+06, - 0.68891E+06, 0.72331E+06, 0.75905E+06, 0.79617E+06, 0.83470E+06, - 0.87469E+06, 0.91617E+06, 0.95919E+06, 0.10038E+07, 0.10500E+07, - 0.10979E+07, 0.11474E+07, 0.11988E+07, 0.12519E+07, 0.13068E+07, - 0.13636E+07, 0.14224E+07, 0.14831E+07, 0.15459E+07, 0.16107E+07, - 0.16776E+07, 0.17467E+07, 0.18180E+07, 0.18916E+07, 0.19675E+07, - 0.20458E+07, 0.21265E+07, 0.22097E+07, 0.22954E+07, 0.23837E+07, - 0.24747E+07, 0.25684E+07, 0.26648E+07, 0.27641E+07, 0.28662E+07, - 0.29713E+07, 0.30794E+07, 0.31905E+07, 0.33048E+07, 0.34223E+07, - 0.35430E+07, 0.36670E+07, 0.37944E+07, 0.39253E+07, 0.40597E+07, - 0.41976E+07, 0.43393E+07, 0.44846E+07, 0.46337E+07, 0.47867E+07, - 0.49437E+07, 0.51046E+07, 0.52696E+07, 0.54388E+07, 0.56122E+07, - 0.57900E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.12046E+04, 0.20297E+04, 0.29875E+04, 0.40626E+04, 0.52463E+04, 0.65350E+04, 0.79286E+04, + 0.94298E+04, 0.11043E+05, 0.12776E+05, 0.14634E+05, 0.16627E+05, 0.18765E+05, 0.21056E+05, + 0.23511E+05, 0.26143E+05, 0.28961E+05, 0.31979E+05, 0.35209E+05, 0.38663E+05, 0.42355E+05, + 0.46300E+05, 0.50510E+05, 0.55001E+05, 0.59787E+05, 0.64884E+05, 0.70308E+05, 0.76075E+05, + 0.82201E+05, 0.88704E+05, 0.95602E+05, 0.10291E+06, 0.11065E+06, 0.11884E+06, 0.12750E+06, + 0.13665E+06, 0.14631E+06, 0.15650E+06, 0.16724E+06, 0.17856E+06, 0.19047E+06, 0.20301E+06, + 0.21618E+06, 0.23002E+06, 0.24456E+06, 0.25981E+06, 0.27580E+06, 0.29256E+06, 0.31012E+06, + 0.32850E+06, 0.34773E+06, 0.36784E+06, 0.38886E+06, 0.41082E+06, 0.43374E+06, 0.45766E+06, + 0.48262E+06, 0.50863E+06, 0.53574E+06, 0.56398E+06, 0.59339E+06, 0.62398E+06, 0.65581E+06, + 0.68891E+06, 0.72331E+06, 0.75905E+06, 0.79617E+06, 0.83470E+06, 0.87469E+06, 0.91617E+06, + 0.95919E+06, 0.10038E+07, 0.10500E+07, 0.10979E+07, 0.11474E+07, 0.11988E+07, 0.12519E+07, + 0.13068E+07, 0.13636E+07, 0.14224E+07, 0.14831E+07, 0.15459E+07, 0.16107E+07, 0.16776E+07, + 0.17467E+07, 0.18180E+07, 0.18916E+07, 0.19675E+07, 0.20458E+07, 0.21265E+07, 0.22097E+07, + 0.22954E+07, 0.23837E+07, 0.24747E+07, 0.25684E+07, 0.26648E+07, 0.27641E+07, 0.28662E+07, + 0.29713E+07, 0.30794E+07, 0.31905E+07, 0.33048E+07, 0.34223E+07, 0.35430E+07, 0.36670E+07, + 0.37944E+07, 0.39253E+07, 0.40597E+07, 0.41976E+07, 0.43393E+07, 0.44846E+07, 0.46337E+07, + 0.47867E+07, 0.49437E+07, 0.51046E+07, 0.52696E+07, 0.54388E+07, 0.56122E+07, 0.57900E+07]) # --------------- NH3 4111: M = 11, I = 1 --------------------- M = 11 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(3.) -TIPS_ISO_HASH[(M, I)] = float32([0.16013E+03, 0.26692E+03, 0.39067E+03, - 0.52933E+03, 0.68153E+03, 0.84641E+03, 0.10234E+04, 0.12125E+04, - 0.14136E+04, 0.16272E+04, 0.18537E+04, 0.20937E+04, 0.23481E+04, - 0.26177E+04, 0.29035E+04, 0.32065E+04, 0.35279E+04, 0.38688E+04, - 0.42304E+04, 0.46141E+04, 0.50212E+04, 0.54531E+04, 0.59114E+04, - 0.63976E+04, 0.69133E+04, 0.74602E+04, 0.80401E+04, 0.86549E+04, - 0.93066E+04, 0.99971E+04, 0.10729E+05, 0.11504E+05, 0.12324E+05, - 0.13193E+05, 0.14112E+05, 0.15085E+05, 0.16114E+05, 0.17201E+05, - 0.18352E+05, 0.19567E+05, 0.20851E+05, 0.22208E+05, 0.23640E+05, - 0.25152E+05, 0.26747E+05, 0.28430E+05, 0.30205E+05, 0.32077E+05, - 0.34050E+05, 0.36128E+05, 0.38317E+05, 0.40623E+05, 0.43050E+05, - 0.45605E+05, 0.48292E+05, 0.51119E+05, 0.54091E+05, 0.57215E+05, - 0.60498E+05, 0.63947E+05, 0.67569E+05, 0.71372E+05, 0.75364E+05, - 0.79552E+05, 0.83946E+05, 0.88553E+05, 0.93384E+05, 0.98447E+05, - 0.10375E+06, 0.10931E+06, 0.11513E+06, 0.12122E+06, 0.12760E+06, - 0.13427E+06, 0.14125E+06, 0.14855E+06, 0.15619E+06, 0.16417E+06, - 0.17250E+06, 0.18121E+06, 0.19031E+06, 0.19981E+06, 0.20973E+06, - 0.22008E+06, 0.23088E+06, 0.24215E+06, 0.25390E+06, 0.26615E+06, - 0.27892E+06, 0.29223E+06, 0.30610E+06, 0.32055E+06, 0.33559E+06, - 0.35125E+06, 0.36756E+06, 0.38453E+06, 0.40219E+06, 0.42056E+06, - 0.43967E+06, 0.45953E+06, 0.48019E+06, 0.50165E+06, 0.52396E+06, - 0.54714E+06, 0.57122E+06, 0.59622E+06, 0.62218E+06, 0.64913E+06, - 0.67710E+06, 0.70613E+06, 0.73624E+06, 0.76748E+06, 0.79988E+06, - 0.83347E+06, 0.86829E+06, 0.90439E+06, 0.94180E+06, 0.98056E+06, - 0.10207E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.16013E+03, 0.26692E+03, 0.39067E+03, 0.52933E+03, 0.68153E+03, 0.84641E+03, 0.10234E+04, + 0.12125E+04, 0.14136E+04, 0.16272E+04, 0.18537E+04, 0.20937E+04, 0.23481E+04, 0.26177E+04, + 0.29035E+04, 0.32065E+04, 0.35279E+04, 0.38688E+04, 0.42304E+04, 0.46141E+04, 0.50212E+04, + 0.54531E+04, 0.59114E+04, 0.63976E+04, 0.69133E+04, 0.74602E+04, 0.80401E+04, 0.86549E+04, + 0.93066E+04, 0.99971E+04, 0.10729E+05, 0.11504E+05, 0.12324E+05, 0.13193E+05, 0.14112E+05, + 0.15085E+05, 0.16114E+05, 0.17201E+05, 0.18352E+05, 0.19567E+05, 0.20851E+05, 0.22208E+05, + 0.23640E+05, 0.25152E+05, 0.26747E+05, 0.28430E+05, 0.30205E+05, 0.32077E+05, 0.34050E+05, + 0.36128E+05, 0.38317E+05, 0.40623E+05, 0.43050E+05, 0.45605E+05, 0.48292E+05, 0.51119E+05, + 0.54091E+05, 0.57215E+05, 0.60498E+05, 0.63947E+05, 0.67569E+05, 0.71372E+05, 0.75364E+05, + 0.79552E+05, 0.83946E+05, 0.88553E+05, 0.93384E+05, 0.98447E+05, 0.10375E+06, 0.10931E+06, + 0.11513E+06, 0.12122E+06, 0.12760E+06, 0.13427E+06, 0.14125E+06, 0.14855E+06, 0.15619E+06, + 0.16417E+06, 0.17250E+06, 0.18121E+06, 0.19031E+06, 0.19981E+06, 0.20973E+06, 0.22008E+06, + 0.23088E+06, 0.24215E+06, 0.25390E+06, 0.26615E+06, 0.27892E+06, 0.29223E+06, 0.30610E+06, + 0.32055E+06, 0.33559E+06, 0.35125E+06, 0.36756E+06, 0.38453E+06, 0.40219E+06, 0.42056E+06, + 0.43967E+06, 0.45953E+06, 0.48019E+06, 0.50165E+06, 0.52396E+06, 0.54714E+06, 0.57122E+06, + 0.59622E+06, 0.62218E+06, 0.64913E+06, 0.67710E+06, 0.70613E+06, 0.73624E+06, 0.76748E+06, + 0.79988E+06, 0.83347E+06, 0.86829E+06, 0.90439E+06, 0.94180E+06, 0.98056E+06, 0.10207E+07]) # --------------- NH3 5111: M = 11, I = 2 --------------------- M = 11 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.10697E+03, 0.17832E+03, 0.26100E+03, - 0.35364E+03, 0.45533E+03, 0.56549E+03, 0.68377E+03, 0.81007E+03, - 0.94447E+03, 0.10872E+04, 0.12385E+04, 0.13988E+04, 0.15688E+04, - 0.17490E+04, 0.19399E+04, 0.21424E+04, 0.23571E+04, 0.25848E+04, - 0.28264E+04, 0.30828E+04, 0.33548E+04, 0.36434E+04, 0.39496E+04, - 0.42745E+04, 0.46190E+04, 0.49845E+04, 0.53720E+04, 0.57828E+04, - 0.62182E+04, 0.66796E+04, 0.71684E+04, 0.76862E+04, 0.82344E+04, - 0.88149E+04, 0.94292E+04, 0.10079E+05, 0.10767E+05, 0.11494E+05, - 0.12262E+05, 0.13074E+05, 0.13932E+05, 0.14839E+05, 0.15796E+05, - 0.16806E+05, 0.17872E+05, 0.18997E+05, 0.20183E+05, 0.21434E+05, - 0.22752E+05, 0.24141E+05, 0.25604E+05, 0.27145E+05, 0.28767E+05, - 0.30475E+05, 0.32271E+05, 0.34160E+05, 0.36146E+05, 0.38234E+05, - 0.40428E+05, 0.42733E+05, 0.45154E+05, 0.47696E+05, 0.50364E+05, - 0.53163E+05, 0.56100E+05, 0.59180E+05, 0.62408E+05, 0.65792E+05, - 0.69339E+05, 0.73053E+05, 0.76943E+05, 0.81016E+05, 0.85279E+05, - 0.89740E+05, 0.94406E+05, 0.99287E+05, 0.10439E+06, 0.10972E+06, - 0.11530E+06, 0.12112E+06, 0.12720E+06, 0.13355E+06, 0.14018E+06, - 0.14711E+06, 0.15433E+06, 0.16186E+06, 0.16971E+06, 0.17791E+06, - 0.18645E+06, 0.19534E+06, 0.20462E+06, 0.21428E+06, 0.22434E+06, - 0.23481E+06, 0.24572E+06, 0.25706E+06, 0.26887E+06, 0.28116E+06, - 0.29393E+06, 0.30722E+06, 0.32103E+06, 0.33539E+06, 0.35031E+06, - 0.36581E+06, 0.38191E+06, 0.39864E+06, 0.41600E+06, 0.43403E+06, - 0.45274E+06, 0.47215E+06, 0.49230E+06, 0.51319E+06, 0.53487E+06, - 0.55734E+06, 0.58064E+06, 0.60478E+06, 0.62981E+06, 0.65574E+06, - 0.68260E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.10697E+03, 0.17832E+03, 0.26100E+03, 0.35364E+03, 0.45533E+03, 0.56549E+03, 0.68377E+03, + 0.81007E+03, 0.94447E+03, 0.10872E+04, 0.12385E+04, 0.13988E+04, 0.15688E+04, 0.17490E+04, + 0.19399E+04, 0.21424E+04, 0.23571E+04, 0.25848E+04, 0.28264E+04, 0.30828E+04, 0.33548E+04, + 0.36434E+04, 0.39496E+04, 0.42745E+04, 0.46190E+04, 0.49845E+04, 0.53720E+04, 0.57828E+04, + 0.62182E+04, 0.66796E+04, 0.71684E+04, 0.76862E+04, 0.82344E+04, 0.88149E+04, 0.94292E+04, + 0.10079E+05, 0.10767E+05, 0.11494E+05, 0.12262E+05, 0.13074E+05, 0.13932E+05, 0.14839E+05, + 0.15796E+05, 0.16806E+05, 0.17872E+05, 0.18997E+05, 0.20183E+05, 0.21434E+05, 0.22752E+05, + 0.24141E+05, 0.25604E+05, 0.27145E+05, 0.28767E+05, 0.30475E+05, 0.32271E+05, 0.34160E+05, + 0.36146E+05, 0.38234E+05, 0.40428E+05, 0.42733E+05, 0.45154E+05, 0.47696E+05, 0.50364E+05, + 0.53163E+05, 0.56100E+05, 0.59180E+05, 0.62408E+05, 0.65792E+05, 0.69339E+05, 0.73053E+05, + 0.76943E+05, 0.81016E+05, 0.85279E+05, 0.89740E+05, 0.94406E+05, 0.99287E+05, 0.10439E+06, + 0.10972E+06, 0.11530E+06, 0.12112E+06, 0.12720E+06, 0.13355E+06, 0.14018E+06, 0.14711E+06, + 0.15433E+06, 0.16186E+06, 0.16971E+06, 0.17791E+06, 0.18645E+06, 0.19534E+06, 0.20462E+06, + 0.21428E+06, 0.22434E+06, 0.23481E+06, 0.24572E+06, 0.25706E+06, 0.26887E+06, 0.28116E+06, + 0.29393E+06, 0.30722E+06, 0.32103E+06, 0.33539E+06, 0.35031E+06, 0.36581E+06, 0.38191E+06, + 0.39864E+06, 0.41600E+06, 0.43403E+06, 0.45274E+06, 0.47215E+06, 0.49230E+06, 0.51319E+06, + 0.53487E+06, 0.55734E+06, 0.58064E+06, 0.60478E+06, 0.62981E+06, 0.65574E+06, 0.68260E+06]) # --------------- HNO3 146: M = 12, I = 1 --------------------- M = 12 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.15010E+05, 0.25316E+05, 0.37374E+05, - 0.51216E+05, 0.67105E+05, 0.85473E+05, 0.10688E+06, 0.13201E+06, - 0.16165E+06, 0.19671E+06, 0.23825E+06, 0.28749E+06, 0.34583E+06, - 0.41490E+06, 0.49657E+06, 0.59302E+06, 0.70673E+06, 0.84054E+06, - 0.99775E+06, 0.11821E+07, 0.13978E+07, 0.16498E+07, 0.19436E+07, - 0.22855E+07, 0.26825E+07, 0.31428E+07, 0.36753E+07, 0.42903E+07, - 0.49993E+07, 0.58151E+07, 0.67523E+07, 0.78269E+07, 0.90572E+07, - 0.10463E+08, 0.12067E+08, 0.13895E+08, 0.15973E+08, 0.18333E+08, - 0.21009E+08, 0.24039E+08, 0.27464E+08, 0.31331E+08, 0.35690E+08, - 0.40597E+08, 0.46115E+08, 0.52310E+08, 0.59257E+08, 0.67037E+08, - 0.75739E+08, 0.85461E+08, 0.96310E+08, 0.10840E+09, 0.12186E+09, - 0.13683E+09, 0.15346E+09, 0.17191E+09, 0.19236E+09, 0.21501E+09, - 0.24006E+09, 0.26774E+09, 0.29830E+09, 0.33200E+09, 0.36914E+09, - 0.41002E+09, 0.45498E+09, 0.50438E+09, 0.55862E+09, 0.61812E+09, - 0.68332E+09, 0.75473E+09, 0.83286E+09, 0.91828E+09, 0.10116E+10, - 0.11134E+10, 0.12245E+10, 0.13456E+10, 0.14775E+10, 0.16210E+10, - 0.17771E+10, 0.19467E+10, 0.21309E+10, 0.23309E+10, 0.25477E+10, - 0.27827E+10, 0.30372E+10, 0.33127E+10, 0.36107E+10, 0.39329E+10, - 0.42809E+10, 0.46567E+10, 0.50623E+10, 0.54997E+10, 0.59711E+10, - 0.64789E+10, 0.70257E+10, 0.76140E+10, 0.82468E+10, 0.89269E+10, - 0.96575E+10, 0.10442E+11, 0.11284E+11, 0.12187E+11, 0.13155E+11, - 0.14193E+11, 0.15304E+11, 0.16494E+11, 0.17767E+11, 0.19129E+11, - 0.20585E+11, 0.22140E+11, 0.23802E+11, 0.25576E+11, 0.27469E+11, - 0.29489E+11, 0.31642E+11, 0.33937E+11, 0.36382E+11, 0.38985E+11, - 0.41757E+11]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.15010E+05, 0.25316E+05, 0.37374E+05, 0.51216E+05, 0.67105E+05, 0.85473E+05, 0.10688E+06, + 0.13201E+06, 0.16165E+06, 0.19671E+06, 0.23825E+06, 0.28749E+06, 0.34583E+06, 0.41490E+06, + 0.49657E+06, 0.59302E+06, 0.70673E+06, 0.84054E+06, 0.99775E+06, 0.11821E+07, 0.13978E+07, + 0.16498E+07, 0.19436E+07, 0.22855E+07, 0.26825E+07, 0.31428E+07, 0.36753E+07, 0.42903E+07, + 0.49993E+07, 0.58151E+07, 0.67523E+07, 0.78269E+07, 0.90572E+07, 0.10463E+08, 0.12067E+08, + 0.13895E+08, 0.15973E+08, 0.18333E+08, 0.21009E+08, 0.24039E+08, 0.27464E+08, 0.31331E+08, + 0.35690E+08, 0.40597E+08, 0.46115E+08, 0.52310E+08, 0.59257E+08, 0.67037E+08, 0.75739E+08, + 0.85461E+08, 0.96310E+08, 0.10840E+09, 0.12186E+09, 0.13683E+09, 0.15346E+09, 0.17191E+09, + 0.19236E+09, 0.21501E+09, 0.24006E+09, 0.26774E+09, 0.29830E+09, 0.33200E+09, 0.36914E+09, + 0.41002E+09, 0.45498E+09, 0.50438E+09, 0.55862E+09, 0.61812E+09, 0.68332E+09, 0.75473E+09, + 0.83286E+09, 0.91828E+09, 0.10116E+10, 0.11134E+10, 0.12245E+10, 0.13456E+10, 0.14775E+10, + 0.16210E+10, 0.17771E+10, 0.19467E+10, 0.21309E+10, 0.23309E+10, 0.25477E+10, 0.27827E+10, + 0.30372E+10, 0.33127E+10, 0.36107E+10, 0.39329E+10, 0.42809E+10, 0.46567E+10, 0.50623E+10, + 0.54997E+10, 0.59711E+10, 0.64789E+10, 0.70257E+10, 0.76140E+10, 0.82468E+10, 0.89269E+10, + 0.96575E+10, 0.10442E+11, 0.11284E+11, 0.12187E+11, 0.13155E+11, 0.14193E+11, 0.15304E+11, + 0.16494E+11, 0.17767E+11, 0.19129E+11, 0.20585E+11, 0.22140E+11, 0.23802E+11, 0.25576E+11, + 0.27469E+11, 0.29489E+11, 0.31642E+11, 0.33937E+11, 0.36382E+11, 0.38985E+11, 0.41757E+11]) # --------------- HNO3 156: M = 12, I = 2 --------------------- NOT IN TIPS-2011 M = 12 @@ -7600,121 +6681,93 @@ def AtoB(aa, A, B, npt): M = 13 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.20066E+02, 0.24774E+02, 0.30309E+02, - 0.36357E+02, 0.42745E+02, 0.49371E+02, 0.56168E+02, 0.63093E+02, - 0.70116E+02, 0.77217E+02, 0.84380E+02, 0.91594E+02, 0.98850E+02, - 0.10614E+03, 0.11346E+03, 0.12081E+03, 0.12818E+03, 0.13557E+03, - 0.14298E+03, 0.15041E+03, 0.15785E+03, 0.16531E+03, 0.17278E+03, - 0.18027E+03, 0.18778E+03, 0.19530E+03, 0.20284E+03, 0.21040E+03, - 0.21797E+03, 0.22556E+03, 0.23318E+03, 0.24082E+03, 0.24848E+03, - 0.25617E+03, 0.26389E+03, 0.27163E+03, 0.27941E+03, 0.28721E+03, - 0.29505E+03, 0.30292E+03, 0.31084E+03, 0.31878E+03, 0.32677E+03, - 0.33480E+03, 0.34287E+03, 0.35099E+03, 0.35915E+03, 0.36736E+03, - 0.37561E+03, 0.38391E+03, 0.39227E+03, 0.40067E+03, 0.40913E+03, - 0.41764E+03, 0.42620E+03, 0.43482E+03, 0.44350E+03, 0.45223E+03, - 0.46102E+03, 0.46987E+03, 0.47878E+03, 0.48775E+03, 0.49679E+03, - 0.50588E+03, 0.51503E+03, 0.52425E+03, 0.53354E+03, 0.54288E+03, - 0.55229E+03, 0.56177E+03, 0.57132E+03, 0.58092E+03, 0.59060E+03, - 0.60035E+03, 0.61016E+03, 0.62004E+03, 0.62999E+03, 0.64001E+03, - 0.65010E+03, 0.66025E+03, 0.67049E+03, 0.68078E+03, 0.69115E+03, - 0.70160E+03, 0.71211E+03, 0.72269E+03, 0.73335E+03, 0.74408E+03, - 0.75488E+03, 0.76576E+03, 0.77671E+03, 0.78773E+03, 0.79883E+03, - 0.81000E+03, 0.82124E+03, 0.83256E+03, 0.84396E+03, 0.85542E+03, - 0.86696E+03, 0.87858E+03, 0.89027E+03, 0.90204E+03, 0.91389E+03, - 0.92580E+03, 0.93781E+03, 0.94988E+03, 0.96203E+03, 0.97425E+03, - 0.98656E+03, 0.99893E+03, 0.10114E+04, 0.10239E+04, 0.10365E+04, - 0.10492E+04, 0.10620E+04, 0.10748E+04, 0.10878E+04, 0.11007E+04, - 0.11138E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.20066E+02, 0.24774E+02, 0.30309E+02, 0.36357E+02, 0.42745E+02, 0.49371E+02, 0.56168E+02, + 0.63093E+02, 0.70116E+02, 0.77217E+02, 0.84380E+02, 0.91594E+02, 0.98850E+02, 0.10614E+03, + 0.11346E+03, 0.12081E+03, 0.12818E+03, 0.13557E+03, 0.14298E+03, 0.15041E+03, 0.15785E+03, + 0.16531E+03, 0.17278E+03, 0.18027E+03, 0.18778E+03, 0.19530E+03, 0.20284E+03, 0.21040E+03, + 0.21797E+03, 0.22556E+03, 0.23318E+03, 0.24082E+03, 0.24848E+03, 0.25617E+03, 0.26389E+03, + 0.27163E+03, 0.27941E+03, 0.28721E+03, 0.29505E+03, 0.30292E+03, 0.31084E+03, 0.31878E+03, + 0.32677E+03, 0.33480E+03, 0.34287E+03, 0.35099E+03, 0.35915E+03, 0.36736E+03, 0.37561E+03, + 0.38391E+03, 0.39227E+03, 0.40067E+03, 0.40913E+03, 0.41764E+03, 0.42620E+03, 0.43482E+03, + 0.44350E+03, 0.45223E+03, 0.46102E+03, 0.46987E+03, 0.47878E+03, 0.48775E+03, 0.49679E+03, + 0.50588E+03, 0.51503E+03, 0.52425E+03, 0.53354E+03, 0.54288E+03, 0.55229E+03, 0.56177E+03, + 0.57132E+03, 0.58092E+03, 0.59060E+03, 0.60035E+03, 0.61016E+03, 0.62004E+03, 0.62999E+03, + 0.64001E+03, 0.65010E+03, 0.66025E+03, 0.67049E+03, 0.68078E+03, 0.69115E+03, 0.70160E+03, + 0.71211E+03, 0.72269E+03, 0.73335E+03, 0.74408E+03, 0.75488E+03, 0.76576E+03, 0.77671E+03, + 0.78773E+03, 0.79883E+03, 0.81000E+03, 0.82124E+03, 0.83256E+03, 0.84396E+03, 0.85542E+03, + 0.86696E+03, 0.87858E+03, 0.89027E+03, 0.90204E+03, 0.91389E+03, 0.92580E+03, 0.93781E+03, + 0.94988E+03, 0.96203E+03, 0.97425E+03, 0.98656E+03, 0.99893E+03, 0.10114E+04, 0.10239E+04, + 0.10365E+04, 0.10492E+04, 0.10620E+04, 0.10748E+04, 0.10878E+04, 0.11007E+04, 0.11138E+04]) # --------------- OH 81: M = 13, I = 2 --------------------- M = 13 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.20124E+02, 0.24876E+02, 0.30457E+02, - 0.36553E+02, 0.42991E+02, 0.49666E+02, 0.56513E+02, 0.63489E+02, - 0.70563E+02, 0.77715E+02, 0.84929E+02, 0.92195E+02, 0.99504E+02, - 0.10685E+03, 0.11423E+03, 0.12164E+03, 0.12907E+03, 0.13654E+03, - 0.14403E+03, 0.15154E+03, 0.15909E+03, 0.16666E+03, 0.17427E+03, - 0.18191E+03, 0.18959E+03, 0.19731E+03, 0.20507E+03, 0.21287E+03, - 0.22073E+03, 0.22863E+03, 0.23658E+03, 0.24459E+03, 0.25266E+03, - 0.26078E+03, 0.26897E+03, 0.27722E+03, 0.28554E+03, 0.29393E+03, - 0.30238E+03, 0.31091E+03, 0.31952E+03, 0.32820E+03, 0.33696E+03, - 0.34579E+03, 0.35471E+03, 0.36371E+03, 0.37279E+03, 0.38196E+03, - 0.39121E+03, 0.40055E+03, 0.40998E+03, 0.41949E+03, 0.42910E+03, - 0.43879E+03, 0.44858E+03, 0.45845E+03, 0.46843E+03, 0.47849E+03, - 0.48865E+03, 0.49890E+03, 0.50924E+03, 0.51969E+03, 0.53022E+03, - 0.54086E+03, 0.55159E+03, 0.56242E+03, 0.57335E+03, 0.58437E+03, - 0.59550E+03, 0.60673E+03, 0.61805E+03, 0.62947E+03, 0.64100E+03, - 0.65263E+03, 0.66435E+03, 0.67618E+03, 0.68811E+03, 0.70014E+03, - 0.71228E+03, 0.72451E+03, 0.73685E+03, 0.74929E+03, 0.76184E+03, - 0.77449E+03, 0.78724E+03, 0.80009E+03, 0.81306E+03, 0.82612E+03, - 0.83929E+03, 0.85256E+03, 0.86594E+03, 0.87942E+03, 0.89301E+03, - 0.90670E+03, 0.92050E+03, 0.93440E+03, 0.94841E+03, 0.96253E+03, - 0.97675E+03, 0.99108E+03, 0.10055E+04, 0.10201E+04, 0.10347E+04, - 0.10495E+04, 0.10643E+04, 0.10793E+04, 0.10944E+04, 0.11096E+04, - 0.11248E+04, 0.11402E+04, 0.11558E+04, 0.11714E+04, 0.11871E+04, - 0.12029E+04, 0.12189E+04, 0.12349E+04, 0.12511E+04, 0.12673E+04, - 0.12837E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.20124E+02, 0.24876E+02, 0.30457E+02, 0.36553E+02, 0.42991E+02, 0.49666E+02, 0.56513E+02, + 0.63489E+02, 0.70563E+02, 0.77715E+02, 0.84929E+02, 0.92195E+02, 0.99504E+02, 0.10685E+03, + 0.11423E+03, 0.12164E+03, 0.12907E+03, 0.13654E+03, 0.14403E+03, 0.15154E+03, 0.15909E+03, + 0.16666E+03, 0.17427E+03, 0.18191E+03, 0.18959E+03, 0.19731E+03, 0.20507E+03, 0.21287E+03, + 0.22073E+03, 0.22863E+03, 0.23658E+03, 0.24459E+03, 0.25266E+03, 0.26078E+03, 0.26897E+03, + 0.27722E+03, 0.28554E+03, 0.29393E+03, 0.30238E+03, 0.31091E+03, 0.31952E+03, 0.32820E+03, + 0.33696E+03, 0.34579E+03, 0.35471E+03, 0.36371E+03, 0.37279E+03, 0.38196E+03, 0.39121E+03, + 0.40055E+03, 0.40998E+03, 0.41949E+03, 0.42910E+03, 0.43879E+03, 0.44858E+03, 0.45845E+03, + 0.46843E+03, 0.47849E+03, 0.48865E+03, 0.49890E+03, 0.50924E+03, 0.51969E+03, 0.53022E+03, + 0.54086E+03, 0.55159E+03, 0.56242E+03, 0.57335E+03, 0.58437E+03, 0.59550E+03, 0.60673E+03, + 0.61805E+03, 0.62947E+03, 0.64100E+03, 0.65263E+03, 0.66435E+03, 0.67618E+03, 0.68811E+03, + 0.70014E+03, 0.71228E+03, 0.72451E+03, 0.73685E+03, 0.74929E+03, 0.76184E+03, 0.77449E+03, + 0.78724E+03, 0.80009E+03, 0.81306E+03, 0.82612E+03, 0.83929E+03, 0.85256E+03, 0.86594E+03, + 0.87942E+03, 0.89301E+03, 0.90670E+03, 0.92050E+03, 0.93440E+03, 0.94841E+03, 0.96253E+03, + 0.97675E+03, 0.99108E+03, 0.10055E+04, 0.10201E+04, 0.10347E+04, 0.10495E+04, 0.10643E+04, + 0.10793E+04, 0.10944E+04, 0.11096E+04, 0.11248E+04, 0.11402E+04, 0.11558E+04, 0.11714E+04, + 0.11871E+04, 0.12029E+04, 0.12189E+04, 0.12349E+04, 0.12511E+04, 0.12673E+04, 0.12837E+04]) # --------------- OH 62: M = 13, I = 3 --------------------- M = 13 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(3.) -TIPS_ISO_HASH[(M, I)] = float32([0.41032E+02, 0.54704E+02, 0.70201E+02, - 0.86985E+02, 0.10469E+03, 0.12306E+03, 0.14194E+03, 0.16119E+03, - 0.18075E+03, 0.20054E+03, 0.22053E+03, 0.24068E+03, 0.26096E+03, - 0.28135E+03, 0.30183E+03, 0.32241E+03, 0.34305E+03, 0.36376E+03, - 0.38453E+03, 0.40535E+03, 0.42622E+03, 0.44714E+03, 0.46811E+03, - 0.48913E+03, 0.51019E+03, 0.53131E+03, 0.55246E+03, 0.57368E+03, - 0.59495E+03, 0.61627E+03, 0.63766E+03, 0.65912E+03, 0.68064E+03, - 0.70223E+03, 0.72390E+03, 0.74565E+03, 0.76749E+03, 0.78941E+03, - 0.81143E+03, 0.83355E+03, 0.85578E+03, 0.87810E+03, 0.90054E+03, - 0.92310E+03, 0.94577E+03, 0.96857E+03, 0.99149E+03, 0.10145E+04, - 0.10377E+04, 0.10611E+04, 0.10845E+04, 0.11081E+04, 0.11319E+04, - 0.11558E+04, 0.11798E+04, 0.12040E+04, 0.12284E+04, 0.12529E+04, - 0.12776E+04, 0.13025E+04, 0.13275E+04, 0.13527E+04, 0.13781E+04, - 0.14036E+04, 0.14293E+04, 0.14552E+04, 0.14813E+04, 0.15076E+04, - 0.15340E+04, 0.15606E+04, 0.15874E+04, 0.16144E+04, 0.16416E+04, - 0.16690E+04, 0.16965E+04, 0.17243E+04, 0.17522E+04, 0.17804E+04, - 0.18087E+04, 0.18373E+04, 0.18660E+04, 0.18949E+04, 0.19241E+04, - 0.19534E+04, 0.19829E+04, 0.20127E+04, 0.20426E+04, 0.20727E+04, - 0.21031E+04, 0.21336E+04, 0.21644E+04, 0.21954E+04, 0.22266E+04, - 0.22579E+04, 0.22895E+04, 0.23213E+04, 0.23534E+04, 0.23856E+04, - 0.24180E+04, 0.24506E+04, 0.24835E+04, 0.25166E+04, 0.25499E+04, - 0.25834E+04, 0.26171E+04, 0.26510E+04, 0.26852E+04, 0.27195E+04, - 0.27541E+04, 0.27889E+04, 0.28239E+04, 0.28592E+04, 0.28946E+04, - 0.29303E+04, 0.29661E+04, 0.30023E+04, 0.30386E+04, 0.30751E+04, - 0.31119E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.41032E+02, 0.54704E+02, 0.70201E+02, 0.86985E+02, 0.10469E+03, 0.12306E+03, 0.14194E+03, + 0.16119E+03, 0.18075E+03, 0.20054E+03, 0.22053E+03, 0.24068E+03, 0.26096E+03, 0.28135E+03, + 0.30183E+03, 0.32241E+03, 0.34305E+03, 0.36376E+03, 0.38453E+03, 0.40535E+03, 0.42622E+03, + 0.44714E+03, 0.46811E+03, 0.48913E+03, 0.51019E+03, 0.53131E+03, 0.55246E+03, 0.57368E+03, + 0.59495E+03, 0.61627E+03, 0.63766E+03, 0.65912E+03, 0.68064E+03, 0.70223E+03, 0.72390E+03, + 0.74565E+03, 0.76749E+03, 0.78941E+03, 0.81143E+03, 0.83355E+03, 0.85578E+03, 0.87810E+03, + 0.90054E+03, 0.92310E+03, 0.94577E+03, 0.96857E+03, 0.99149E+03, 0.10145E+04, 0.10377E+04, + 0.10611E+04, 0.10845E+04, 0.11081E+04, 0.11319E+04, 0.11558E+04, 0.11798E+04, 0.12040E+04, + 0.12284E+04, 0.12529E+04, 0.12776E+04, 0.13025E+04, 0.13275E+04, 0.13527E+04, 0.13781E+04, + 0.14036E+04, 0.14293E+04, 0.14552E+04, 0.14813E+04, 0.15076E+04, 0.15340E+04, 0.15606E+04, + 0.15874E+04, 0.16144E+04, 0.16416E+04, 0.16690E+04, 0.16965E+04, 0.17243E+04, 0.17522E+04, + 0.17804E+04, 0.18087E+04, 0.18373E+04, 0.18660E+04, 0.18949E+04, 0.19241E+04, 0.19534E+04, + 0.19829E+04, 0.20127E+04, 0.20426E+04, 0.20727E+04, 0.21031E+04, 0.21336E+04, 0.21644E+04, + 0.21954E+04, 0.22266E+04, 0.22579E+04, 0.22895E+04, 0.23213E+04, 0.23534E+04, 0.23856E+04, + 0.24180E+04, 0.24506E+04, 0.24835E+04, 0.25166E+04, 0.25499E+04, 0.25834E+04, 0.26171E+04, + 0.26510E+04, 0.26852E+04, 0.27195E+04, 0.27541E+04, 0.27889E+04, 0.28239E+04, 0.28592E+04, + 0.28946E+04, 0.29303E+04, 0.29661E+04, 0.30023E+04, 0.30386E+04, 0.30751E+04, 0.31119E+04]) # --------------- HF 19: M = 14, I = 1 --------------------- M = 14 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(4.) -TIPS_ISO_HASH[(M, I)] = float32([0.95958E+01, 0.12933E+02, 0.16295E+02, - 0.19666E+02, 0.23043E+02, 0.26425E+02, 0.29809E+02, 0.33195E+02, - 0.36584E+02, 0.39974E+02, 0.43366E+02, 0.46759E+02, 0.50154E+02, - 0.53550E+02, 0.56947E+02, 0.60346E+02, 0.63746E+02, 0.67148E+02, - 0.70550E+02, 0.73955E+02, 0.77361E+02, 0.80769E+02, 0.84179E+02, - 0.87591E+02, 0.91006E+02, 0.94424E+02, 0.97846E+02, 0.10127E+03, - 0.10470E+03, 0.10813E+03, 0.11157E+03, 0.11502E+03, 0.11847E+03, - 0.12193E+03, 0.12540E+03, 0.12888E+03, 0.13236E+03, 0.13586E+03, - 0.13936E+03, 0.14288E+03, 0.14641E+03, 0.14995E+03, 0.15351E+03, - 0.15708E+03, 0.16066E+03, 0.16426E+03, 0.16788E+03, 0.17151E+03, - 0.17516E+03, 0.17882E+03, 0.18251E+03, 0.18621E+03, 0.18994E+03, - 0.19368E+03, 0.19745E+03, 0.20123E+03, 0.20504E+03, 0.20887E+03, - 0.21272E+03, 0.21659E+03, 0.22049E+03, 0.22441E+03, 0.22836E+03, - 0.23233E+03, 0.23632E+03, 0.24034E+03, 0.24439E+03, 0.24846E+03, - 0.25255E+03, 0.25668E+03, 0.26083E+03, 0.26501E+03, 0.26921E+03, - 0.27344E+03, 0.27770E+03, 0.28199E+03, 0.28631E+03, 0.29066E+03, - 0.29503E+03, 0.29944E+03, 0.30387E+03, 0.30833E+03, 0.31282E+03, - 0.31735E+03, 0.32190E+03, 0.32648E+03, 0.33110E+03, 0.33574E+03, - 0.34042E+03, 0.34512E+03, 0.34986E+03, 0.35463E+03, 0.35943E+03, - 0.36426E+03, 0.36913E+03, 0.37402E+03, 0.37895E+03, 0.38391E+03, - 0.38891E+03, 0.39393E+03, 0.39899E+03, 0.40408E+03, 0.40921E+03, - 0.41436E+03, 0.41955E+03, 0.42478E+03, 0.43004E+03, 0.43533E+03, - 0.44065E+03, 0.44601E+03, 0.45140E+03, 0.45683E+03, 0.46229E+03, - 0.46779E+03, 0.47332E+03, 0.47888E+03, 0.48448E+03, 0.49011E+03, - 0.49578E+03]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.95958E+01, 0.12933E+02, 0.16295E+02, 0.19666E+02, 0.23043E+02, 0.26425E+02, 0.29809E+02, + 0.33195E+02, 0.36584E+02, 0.39974E+02, 0.43366E+02, 0.46759E+02, 0.50154E+02, 0.53550E+02, + 0.56947E+02, 0.60346E+02, 0.63746E+02, 0.67148E+02, 0.70550E+02, 0.73955E+02, 0.77361E+02, + 0.80769E+02, 0.84179E+02, 0.87591E+02, 0.91006E+02, 0.94424E+02, 0.97846E+02, 0.10127E+03, + 0.10470E+03, 0.10813E+03, 0.11157E+03, 0.11502E+03, 0.11847E+03, 0.12193E+03, 0.12540E+03, + 0.12888E+03, 0.13236E+03, 0.13586E+03, 0.13936E+03, 0.14288E+03, 0.14641E+03, 0.14995E+03, + 0.15351E+03, 0.15708E+03, 0.16066E+03, 0.16426E+03, 0.16788E+03, 0.17151E+03, 0.17516E+03, + 0.17882E+03, 0.18251E+03, 0.18621E+03, 0.18994E+03, 0.19368E+03, 0.19745E+03, 0.20123E+03, + 0.20504E+03, 0.20887E+03, 0.21272E+03, 0.21659E+03, 0.22049E+03, 0.22441E+03, 0.22836E+03, + 0.23233E+03, 0.23632E+03, 0.24034E+03, 0.24439E+03, 0.24846E+03, 0.25255E+03, 0.25668E+03, + 0.26083E+03, 0.26501E+03, 0.26921E+03, 0.27344E+03, 0.27770E+03, 0.28199E+03, 0.28631E+03, + 0.29066E+03, 0.29503E+03, 0.29944E+03, 0.30387E+03, 0.30833E+03, 0.31282E+03, 0.31735E+03, + 0.32190E+03, 0.32648E+03, 0.33110E+03, 0.33574E+03, 0.34042E+03, 0.34512E+03, 0.34986E+03, + 0.35463E+03, 0.35943E+03, 0.36426E+03, 0.36913E+03, 0.37402E+03, 0.37895E+03, 0.38391E+03, + 0.38891E+03, 0.39393E+03, 0.39899E+03, 0.40408E+03, 0.40921E+03, 0.41436E+03, 0.41955E+03, + 0.42478E+03, 0.43004E+03, 0.43533E+03, 0.44065E+03, 0.44601E+03, 0.45140E+03, 0.45683E+03, + 0.46229E+03, 0.46779E+03, 0.47332E+03, 0.47888E+03, 0.48448E+03, 0.49011E+03, 0.49578E+03]) # --------------- HF 29: M = 14, I = 2 --------------------- not in TIPS-2011 M = 14 @@ -7726,61 +6779,47 @@ def AtoB(aa, A, B, npt): M = 15 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(8.) -TIPS_ISO_HASH[(M, I)] = float32([0.34775E+02, 0.48060E+02, 0.61370E+02, - 0.74692E+02, 0.88024E+02, 0.10136E+03, 0.11471E+03, 0.12806E+03, - 0.14141E+03, 0.15478E+03, 0.16814E+03, 0.18151E+03, 0.19489E+03, - 0.20827E+03, 0.22166E+03, 0.23506E+03, 0.24847E+03, 0.26189E+03, - 0.27533E+03, 0.28878E+03, 0.30225E+03, 0.31575E+03, 0.32928E+03, - 0.34284E+03, 0.35645E+03, 0.37009E+03, 0.38378E+03, 0.39753E+03, - 0.41134E+03, 0.42521E+03, 0.43914E+03, 0.45316E+03, 0.46725E+03, - 0.48142E+03, 0.49568E+03, 0.51003E+03, 0.52448E+03, 0.53902E+03, - 0.55368E+03, 0.56843E+03, 0.58330E+03, 0.59829E+03, 0.61339E+03, - 0.62862E+03, 0.64396E+03, 0.65944E+03, 0.67504E+03, 0.69078E+03, - 0.70665E+03, 0.72265E+03, 0.73880E+03, 0.75508E+03, 0.77151E+03, - 0.78809E+03, 0.80481E+03, 0.82168E+03, 0.83870E+03, 0.85587E+03, - 0.87320E+03, 0.89068E+03, 0.90832E+03, 0.92611E+03, 0.94407E+03, - 0.96218E+03, 0.98046E+03, 0.99889E+03, 0.10175E+04, 0.10363E+04, - 0.10552E+04, 0.10743E+04, 0.10936E+04, 0.11130E+04, 0.11326E+04, - 0.11524E+04, 0.11723E+04, 0.11924E+04, 0.12127E+04, 0.12332E+04, - 0.12538E+04, 0.12746E+04, 0.12956E+04, 0.13168E+04, 0.13381E+04, - 0.13597E+04, 0.13814E+04, 0.14032E+04, 0.14253E+04, 0.14475E+04, - 0.14700E+04, 0.14926E+04, 0.15153E+04, 0.15383E+04, 0.15615E+04, - 0.15848E+04, 0.16083E+04, 0.16320E+04, 0.16559E+04, 0.16800E+04, - 0.17043E+04, 0.17287E+04, 0.17533E+04, 0.17782E+04, 0.18032E+04, - 0.18284E+04, 0.18538E+04, 0.18794E+04, 0.19051E+04, 0.19311E+04, - 0.19573E+04, 0.19836E+04, 0.20102E+04, 0.20369E+04, 0.20638E+04, - 0.20910E+04, 0.21183E+04, 0.21458E+04, 0.21735E+04, 0.22014E+04, - 0.22295E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.34775E+02, 0.48060E+02, 0.61370E+02, 0.74692E+02, 0.88024E+02, 0.10136E+03, 0.11471E+03, + 0.12806E+03, 0.14141E+03, 0.15478E+03, 0.16814E+03, 0.18151E+03, 0.19489E+03, 0.20827E+03, + 0.22166E+03, 0.23506E+03, 0.24847E+03, 0.26189E+03, 0.27533E+03, 0.28878E+03, 0.30225E+03, + 0.31575E+03, 0.32928E+03, 0.34284E+03, 0.35645E+03, 0.37009E+03, 0.38378E+03, 0.39753E+03, + 0.41134E+03, 0.42521E+03, 0.43914E+03, 0.45316E+03, 0.46725E+03, 0.48142E+03, 0.49568E+03, + 0.51003E+03, 0.52448E+03, 0.53902E+03, 0.55368E+03, 0.56843E+03, 0.58330E+03, 0.59829E+03, + 0.61339E+03, 0.62862E+03, 0.64396E+03, 0.65944E+03, 0.67504E+03, 0.69078E+03, 0.70665E+03, + 0.72265E+03, 0.73880E+03, 0.75508E+03, 0.77151E+03, 0.78809E+03, 0.80481E+03, 0.82168E+03, + 0.83870E+03, 0.85587E+03, 0.87320E+03, 0.89068E+03, 0.90832E+03, 0.92611E+03, 0.94407E+03, + 0.96218E+03, 0.98046E+03, 0.99889E+03, 0.10175E+04, 0.10363E+04, 0.10552E+04, 0.10743E+04, + 0.10936E+04, 0.11130E+04, 0.11326E+04, 0.11524E+04, 0.11723E+04, 0.11924E+04, 0.12127E+04, + 0.12332E+04, 0.12538E+04, 0.12746E+04, 0.12956E+04, 0.13168E+04, 0.13381E+04, 0.13597E+04, + 0.13814E+04, 0.14032E+04, 0.14253E+04, 0.14475E+04, 0.14700E+04, 0.14926E+04, 0.15153E+04, + 0.15383E+04, 0.15615E+04, 0.15848E+04, 0.16083E+04, 0.16320E+04, 0.16559E+04, 0.16800E+04, + 0.17043E+04, 0.17287E+04, 0.17533E+04, 0.17782E+04, 0.18032E+04, 0.18284E+04, 0.18538E+04, + 0.18794E+04, 0.19051E+04, 0.19311E+04, 0.19573E+04, 0.19836E+04, 0.20102E+04, 0.20369E+04, + 0.20638E+04, 0.20910E+04, 0.21183E+04, 0.21458E+04, 0.21735E+04, 0.22014E+04, 0.22295E+04]) # --------------- HСl 17: M = 15, I = 2 --------------------- M = 15 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(8.) -TIPS_ISO_HASH[(M, I)] = float32([0.34823E+02, 0.48128E+02, 0.61458E+02, - 0.74801E+02, 0.88152E+02, 0.10151E+03, 0.11488E+03, 0.12825E+03, - 0.14162E+03, 0.15500E+03, 0.16839E+03, 0.18178E+03, 0.19518E+03, - 0.20858E+03, 0.22199E+03, 0.23541E+03, 0.24884E+03, 0.26228E+03, - 0.27574E+03, 0.28921E+03, 0.30270E+03, 0.31622E+03, 0.32977E+03, - 0.34336E+03, 0.35698E+03, 0.37065E+03, 0.38436E+03, 0.39813E+03, - 0.41196E+03, 0.42585E+03, 0.43981E+03, 0.45384E+03, 0.46796E+03, - 0.48215E+03, 0.49644E+03, 0.51081E+03, 0.52528E+03, 0.53986E+03, - 0.55453E+03, 0.56932E+03, 0.58421E+03, 0.59922E+03, 0.61435E+03, - 0.62960E+03, 0.64498E+03, 0.66048E+03, 0.67611E+03, 0.69187E+03, - 0.70777E+03, 0.72381E+03, 0.73998E+03, 0.75630E+03, 0.77276E+03, - 0.78936E+03, 0.80612E+03, 0.82302E+03, 0.84007E+03, 0.85727E+03, - 0.87463E+03, 0.89215E+03, 0.90982E+03, 0.92765E+03, 0.94563E+03, - 0.96378E+03, 0.98209E+03, 0.10006E+04, 0.10192E+04, 0.10380E+04, - 0.10570E+04, 0.10761E+04, 0.10954E+04, 0.11149E+04, 0.11345E+04, - 0.11543E+04, 0.11743E+04, 0.11945E+04, 0.12148E+04, 0.12353E+04, - 0.12560E+04, 0.12768E+04, 0.12979E+04, 0.13191E+04, 0.13405E+04, - 0.13620E+04, 0.13838E+04, 0.14057E+04, 0.14278E+04, 0.14501E+04, - 0.14726E+04, 0.14952E+04, 0.15180E+04, 0.15410E+04, 0.15642E+04, - 0.15876E+04, 0.16112E+04, 0.16349E+04, 0.16589E+04, 0.16830E+04, - 0.17073E+04, 0.17318E+04, 0.17565E+04, 0.17814E+04, 0.18064E+04, - 0.18317E+04, 0.18572E+04, 0.18828E+04, 0.19086E+04, 0.19346E+04, - 0.19609E+04, 0.19873E+04, 0.20139E+04, 0.20406E+04, 0.20676E+04, - 0.20948E+04, 0.21222E+04, 0.21498E+04, 0.21775E+04, 0.22055E+04, - 0.22337E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.34823E+02, 0.48128E+02, 0.61458E+02, 0.74801E+02, 0.88152E+02, 0.10151E+03, 0.11488E+03, + 0.12825E+03, 0.14162E+03, 0.15500E+03, 0.16839E+03, 0.18178E+03, 0.19518E+03, 0.20858E+03, + 0.22199E+03, 0.23541E+03, 0.24884E+03, 0.26228E+03, 0.27574E+03, 0.28921E+03, 0.30270E+03, + 0.31622E+03, 0.32977E+03, 0.34336E+03, 0.35698E+03, 0.37065E+03, 0.38436E+03, 0.39813E+03, + 0.41196E+03, 0.42585E+03, 0.43981E+03, 0.45384E+03, 0.46796E+03, 0.48215E+03, 0.49644E+03, + 0.51081E+03, 0.52528E+03, 0.53986E+03, 0.55453E+03, 0.56932E+03, 0.58421E+03, 0.59922E+03, + 0.61435E+03, 0.62960E+03, 0.64498E+03, 0.66048E+03, 0.67611E+03, 0.69187E+03, 0.70777E+03, + 0.72381E+03, 0.73998E+03, 0.75630E+03, 0.77276E+03, 0.78936E+03, 0.80612E+03, 0.82302E+03, + 0.84007E+03, 0.85727E+03, 0.87463E+03, 0.89215E+03, 0.90982E+03, 0.92765E+03, 0.94563E+03, + 0.96378E+03, 0.98209E+03, 0.10006E+04, 0.10192E+04, 0.10380E+04, 0.10570E+04, 0.10761E+04, + 0.10954E+04, 0.11149E+04, 0.11345E+04, 0.11543E+04, 0.11743E+04, 0.11945E+04, 0.12148E+04, + 0.12353E+04, 0.12560E+04, 0.12768E+04, 0.12979E+04, 0.13191E+04, 0.13405E+04, 0.13620E+04, + 0.13838E+04, 0.14057E+04, 0.14278E+04, 0.14501E+04, 0.14726E+04, 0.14952E+04, 0.15180E+04, + 0.15410E+04, 0.15642E+04, 0.15876E+04, 0.16112E+04, 0.16349E+04, 0.16589E+04, 0.16830E+04, + 0.17073E+04, 0.17318E+04, 0.17565E+04, 0.17814E+04, 0.18064E+04, 0.18317E+04, 0.18572E+04, + 0.18828E+04, 0.19086E+04, 0.19346E+04, 0.19609E+04, 0.19873E+04, 0.20139E+04, 0.20406E+04, + 0.20676E+04, 0.20948E+04, 0.21222E+04, 0.21498E+04, 0.21775E+04, 0.22055E+04, 0.22337E+04]) # --------------- HСl 25: M = 15, I = 3 --------------------- not in TIPS-2011 M = 15 @@ -7798,61 +6837,47 @@ def AtoB(aa, A, B, npt): M = 16 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(8.) -TIPS_ISO_HASH[(M, I)] = float32([0.42744E+02, 0.59373E+02, 0.76023E+02, - 0.92685E+02, 0.10936E+03, 0.12604E+03, 0.14272E+03, 0.15942E+03, - 0.17612E+03, 0.19282E+03, 0.20954E+03, 0.22626E+03, 0.24299E+03, - 0.25973E+03, 0.27648E+03, 0.29325E+03, 0.31004E+03, 0.32686E+03, - 0.34371E+03, 0.36060E+03, 0.37753E+03, 0.39451E+03, 0.41156E+03, - 0.42868E+03, 0.44587E+03, 0.46314E+03, 0.48051E+03, 0.49798E+03, - 0.51556E+03, 0.53325E+03, 0.55106E+03, 0.56900E+03, 0.58708E+03, - 0.60530E+03, 0.62367E+03, 0.64219E+03, 0.66088E+03, 0.67972E+03, - 0.69874E+03, 0.71793E+03, 0.73730E+03, 0.75685E+03, 0.77659E+03, - 0.79652E+03, 0.81664E+03, 0.83696E+03, 0.85748E+03, 0.87820E+03, - 0.89914E+03, 0.92028E+03, 0.94163E+03, 0.96319E+03, 0.98498E+03, - 0.10070E+04, 0.10292E+04, 0.10516E+04, 0.10743E+04, 0.10972E+04, - 0.11203E+04, 0.11437E+04, 0.11673E+04, 0.11911E+04, 0.12151E+04, - 0.12394E+04, 0.12640E+04, 0.12887E+04, 0.13137E+04, 0.13390E+04, - 0.13645E+04, 0.13902E+04, 0.14162E+04, 0.14424E+04, 0.14689E+04, - 0.14956E+04, 0.15226E+04, 0.15498E+04, 0.15773E+04, 0.16050E+04, - 0.16330E+04, 0.16612E+04, 0.16897E+04, 0.17185E+04, 0.17475E+04, - 0.17767E+04, 0.18062E+04, 0.18360E+04, 0.18660E+04, 0.18963E+04, - 0.19269E+04, 0.19577E+04, 0.19888E+04, 0.20202E+04, 0.20518E+04, - 0.20837E+04, 0.21158E+04, 0.21482E+04, 0.21809E+04, 0.22139E+04, - 0.22471E+04, 0.22806E+04, 0.23143E+04, 0.23484E+04, 0.23827E+04, - 0.24173E+04, 0.24521E+04, 0.24873E+04, 0.25227E+04, 0.25584E+04, - 0.25943E+04, 0.26306E+04, 0.26671E+04, 0.27039E+04, 0.27409E+04, - 0.27783E+04, 0.28159E+04, 0.28538E+04, 0.28920E+04, 0.29305E+04, - 0.29693E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.42744E+02, 0.59373E+02, 0.76023E+02, 0.92685E+02, 0.10936E+03, 0.12604E+03, 0.14272E+03, + 0.15942E+03, 0.17612E+03, 0.19282E+03, 0.20954E+03, 0.22626E+03, 0.24299E+03, 0.25973E+03, + 0.27648E+03, 0.29325E+03, 0.31004E+03, 0.32686E+03, 0.34371E+03, 0.36060E+03, 0.37753E+03, + 0.39451E+03, 0.41156E+03, 0.42868E+03, 0.44587E+03, 0.46314E+03, 0.48051E+03, 0.49798E+03, + 0.51556E+03, 0.53325E+03, 0.55106E+03, 0.56900E+03, 0.58708E+03, 0.60530E+03, 0.62367E+03, + 0.64219E+03, 0.66088E+03, 0.67972E+03, 0.69874E+03, 0.71793E+03, 0.73730E+03, 0.75685E+03, + 0.77659E+03, 0.79652E+03, 0.81664E+03, 0.83696E+03, 0.85748E+03, 0.87820E+03, 0.89914E+03, + 0.92028E+03, 0.94163E+03, 0.96319E+03, 0.98498E+03, 0.10070E+04, 0.10292E+04, 0.10516E+04, + 0.10743E+04, 0.10972E+04, 0.11203E+04, 0.11437E+04, 0.11673E+04, 0.11911E+04, 0.12151E+04, + 0.12394E+04, 0.12640E+04, 0.12887E+04, 0.13137E+04, 0.13390E+04, 0.13645E+04, 0.13902E+04, + 0.14162E+04, 0.14424E+04, 0.14689E+04, 0.14956E+04, 0.15226E+04, 0.15498E+04, 0.15773E+04, + 0.16050E+04, 0.16330E+04, 0.16612E+04, 0.16897E+04, 0.17185E+04, 0.17475E+04, 0.17767E+04, + 0.18062E+04, 0.18360E+04, 0.18660E+04, 0.18963E+04, 0.19269E+04, 0.19577E+04, 0.19888E+04, + 0.20202E+04, 0.20518E+04, 0.20837E+04, 0.21158E+04, 0.21482E+04, 0.21809E+04, 0.22139E+04, + 0.22471E+04, 0.22806E+04, 0.23143E+04, 0.23484E+04, 0.23827E+04, 0.24173E+04, 0.24521E+04, + 0.24873E+04, 0.25227E+04, 0.25584E+04, 0.25943E+04, 0.26306E+04, 0.26671E+04, 0.27039E+04, + 0.27409E+04, 0.27783E+04, 0.28159E+04, 0.28538E+04, 0.28920E+04, 0.29305E+04, 0.29693E+04]) # --------------- HBr 11: M = 16, I = 2 --------------------- M = 16 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(8.) -TIPS_ISO_HASH[(M, I)] = float32([0.42756E+02, 0.59390E+02, 0.76045E+02, - 0.92713E+02, 0.10939E+03, 0.12607E+03, 0.14277E+03, 0.15947E+03, - 0.17617E+03, 0.19288E+03, 0.20960E+03, 0.22633E+03, 0.24306E+03, - 0.25981E+03, 0.27656E+03, 0.29334E+03, 0.31014E+03, 0.32696E+03, - 0.34381E+03, 0.36071E+03, 0.37764E+03, 0.39464E+03, 0.41169E+03, - 0.42881E+03, 0.44601E+03, 0.46329E+03, 0.48066E+03, 0.49813E+03, - 0.51572E+03, 0.53341E+03, 0.55123E+03, 0.56918E+03, 0.58727E+03, - 0.60549E+03, 0.62387E+03, 0.64240E+03, 0.66109E+03, 0.67994E+03, - 0.69896E+03, 0.71816E+03, 0.73754E+03, 0.75710E+03, 0.77684E+03, - 0.79678E+03, 0.81691E+03, 0.83724E+03, 0.85776E+03, 0.87850E+03, - 0.89943E+03, 0.92058E+03, 0.94194E+03, 0.96352E+03, 0.98531E+03, - 0.10073E+04, 0.10295E+04, 0.10520E+04, 0.10747E+04, 0.10976E+04, - 0.11207E+04, 0.11441E+04, 0.11677E+04, 0.11915E+04, 0.12156E+04, - 0.12399E+04, 0.12644E+04, 0.12892E+04, 0.13142E+04, 0.13395E+04, - 0.13650E+04, 0.13907E+04, 0.14167E+04, 0.14429E+04, 0.14694E+04, - 0.14961E+04, 0.15231E+04, 0.15504E+04, 0.15778E+04, 0.16056E+04, - 0.16336E+04, 0.16618E+04, 0.16903E+04, 0.17191E+04, 0.17481E+04, - 0.17773E+04, 0.18069E+04, 0.18367E+04, 0.18667E+04, 0.18970E+04, - 0.19276E+04, 0.19584E+04, 0.19895E+04, 0.20209E+04, 0.20525E+04, - 0.20844E+04, 0.21166E+04, 0.21490E+04, 0.21817E+04, 0.22147E+04, - 0.22479E+04, 0.22814E+04, 0.23152E+04, 0.23492E+04, 0.23835E+04, - 0.24181E+04, 0.24530E+04, 0.24882E+04, 0.25236E+04, 0.25593E+04, - 0.25952E+04, 0.26315E+04, 0.26680E+04, 0.27048E+04, 0.27419E+04, - 0.27793E+04, 0.28169E+04, 0.28549E+04, 0.28931E+04, 0.29316E+04, - 0.29703E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.42756E+02, 0.59390E+02, 0.76045E+02, 0.92713E+02, 0.10939E+03, 0.12607E+03, 0.14277E+03, + 0.15947E+03, 0.17617E+03, 0.19288E+03, 0.20960E+03, 0.22633E+03, 0.24306E+03, 0.25981E+03, + 0.27656E+03, 0.29334E+03, 0.31014E+03, 0.32696E+03, 0.34381E+03, 0.36071E+03, 0.37764E+03, + 0.39464E+03, 0.41169E+03, 0.42881E+03, 0.44601E+03, 0.46329E+03, 0.48066E+03, 0.49813E+03, + 0.51572E+03, 0.53341E+03, 0.55123E+03, 0.56918E+03, 0.58727E+03, 0.60549E+03, 0.62387E+03, + 0.64240E+03, 0.66109E+03, 0.67994E+03, 0.69896E+03, 0.71816E+03, 0.73754E+03, 0.75710E+03, + 0.77684E+03, 0.79678E+03, 0.81691E+03, 0.83724E+03, 0.85776E+03, 0.87850E+03, 0.89943E+03, + 0.92058E+03, 0.94194E+03, 0.96352E+03, 0.98531E+03, 0.10073E+04, 0.10295E+04, 0.10520E+04, + 0.10747E+04, 0.10976E+04, 0.11207E+04, 0.11441E+04, 0.11677E+04, 0.11915E+04, 0.12156E+04, + 0.12399E+04, 0.12644E+04, 0.12892E+04, 0.13142E+04, 0.13395E+04, 0.13650E+04, 0.13907E+04, + 0.14167E+04, 0.14429E+04, 0.14694E+04, 0.14961E+04, 0.15231E+04, 0.15504E+04, 0.15778E+04, + 0.16056E+04, 0.16336E+04, 0.16618E+04, 0.16903E+04, 0.17191E+04, 0.17481E+04, 0.17773E+04, + 0.18069E+04, 0.18367E+04, 0.18667E+04, 0.18970E+04, 0.19276E+04, 0.19584E+04, 0.19895E+04, + 0.20209E+04, 0.20525E+04, 0.20844E+04, 0.21166E+04, 0.21490E+04, 0.21817E+04, 0.22147E+04, + 0.22479E+04, 0.22814E+04, 0.23152E+04, 0.23492E+04, 0.23835E+04, 0.24181E+04, 0.24530E+04, + 0.24882E+04, 0.25236E+04, 0.25593E+04, 0.25952E+04, 0.26315E+04, 0.26680E+04, 0.27048E+04, + 0.27419E+04, 0.27793E+04, 0.28169E+04, 0.28549E+04, 0.28931E+04, 0.29316E+04, 0.29703E+04]) # --------------- HBr 29: M = 16, I = 3 --------------------- not in TIPS-2011 M = 16 @@ -7870,31 +6895,24 @@ def AtoB(aa, A, B, npt): M = 17 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(12.) -TIPS_ISO_HASH[(M, I)] = float32([0.82031E+02, 0.11447E+03, 0.14694E+03, - 0.17943E+03, 0.21194E+03, 0.24445E+03, 0.27699E+03, 0.30953E+03, - 0.34209E+03, 0.37466E+03, 0.40725E+03, 0.43986E+03, 0.47249E+03, - 0.50517E+03, 0.53789E+03, 0.57068E+03, 0.60354E+03, 0.63650E+03, - 0.66957E+03, 0.70278E+03, 0.73614E+03, 0.76967E+03, 0.80340E+03, - 0.83735E+03, 0.87153E+03, 0.90596E+03, 0.94067E+03, 0.97566E+03, - 0.10110E+04, 0.10466E+04, 0.10826E+04, 0.11189E+04, 0.11555E+04, - 0.11926E+04, 0.12300E+04, 0.12679E+04, 0.13061E+04, 0.13448E+04, - 0.13839E+04, 0.14235E+04, 0.14635E+04, 0.15039E+04, 0.15448E+04, - 0.15862E+04, 0.16280E+04, 0.16704E+04, 0.17132E+04, 0.17565E+04, - 0.18003E+04, 0.18446E+04, 0.18894E+04, 0.19347E+04, 0.19806E+04, - 0.20269E+04, 0.20738E+04, 0.21212E+04, 0.21691E+04, 0.22176E+04, - 0.22666E+04, 0.23162E+04, 0.23662E+04, 0.24169E+04, 0.24680E+04, - 0.25198E+04, 0.25720E+04, 0.26249E+04, 0.26783E+04, 0.27322E+04, - 0.27867E+04, 0.28418E+04, 0.28975E+04, 0.29537E+04, 0.30105E+04, - 0.30678E+04, 0.31258E+04, 0.31843E+04, 0.32434E+04, 0.33031E+04, - 0.33633E+04, 0.34242E+04, 0.34856E+04, 0.35477E+04, 0.36103E+04, - 0.36735E+04, 0.37373E+04, 0.38018E+04, 0.38668E+04, 0.39324E+04, - 0.39986E+04, 0.40654E+04, 0.41329E+04, 0.42009E+04, 0.42696E+04, - 0.43388E+04, 0.44087E+04, 0.44792E+04, 0.45503E+04, 0.46221E+04, - 0.46944E+04, 0.47674E+04, 0.48410E+04, 0.49152E+04, 0.49901E+04, - 0.50656E+04, 0.51417E+04, 0.52185E+04, 0.52959E+04, 0.53739E+04, - 0.54526E+04, 0.55319E+04, 0.56118E+04, 0.56924E+04, 0.57736E+04, - 0.58555E+04, 0.59380E+04, 0.60212E+04, 0.61050E+04, 0.61895E+04, - 0.62746E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.82031E+02, 0.11447E+03, 0.14694E+03, 0.17943E+03, 0.21194E+03, 0.24445E+03, 0.27699E+03, + 0.30953E+03, 0.34209E+03, 0.37466E+03, 0.40725E+03, 0.43986E+03, 0.47249E+03, 0.50517E+03, + 0.53789E+03, 0.57068E+03, 0.60354E+03, 0.63650E+03, 0.66957E+03, 0.70278E+03, 0.73614E+03, + 0.76967E+03, 0.80340E+03, 0.83735E+03, 0.87153E+03, 0.90596E+03, 0.94067E+03, 0.97566E+03, + 0.10110E+04, 0.10466E+04, 0.10826E+04, 0.11189E+04, 0.11555E+04, 0.11926E+04, 0.12300E+04, + 0.12679E+04, 0.13061E+04, 0.13448E+04, 0.13839E+04, 0.14235E+04, 0.14635E+04, 0.15039E+04, + 0.15448E+04, 0.15862E+04, 0.16280E+04, 0.16704E+04, 0.17132E+04, 0.17565E+04, 0.18003E+04, + 0.18446E+04, 0.18894E+04, 0.19347E+04, 0.19806E+04, 0.20269E+04, 0.20738E+04, 0.21212E+04, + 0.21691E+04, 0.22176E+04, 0.22666E+04, 0.23162E+04, 0.23662E+04, 0.24169E+04, 0.24680E+04, + 0.25198E+04, 0.25720E+04, 0.26249E+04, 0.26783E+04, 0.27322E+04, 0.27867E+04, 0.28418E+04, + 0.28975E+04, 0.29537E+04, 0.30105E+04, 0.30678E+04, 0.31258E+04, 0.31843E+04, 0.32434E+04, + 0.33031E+04, 0.33633E+04, 0.34242E+04, 0.34856E+04, 0.35477E+04, 0.36103E+04, 0.36735E+04, + 0.37373E+04, 0.38018E+04, 0.38668E+04, 0.39324E+04, 0.39986E+04, 0.40654E+04, 0.41329E+04, + 0.42009E+04, 0.42696E+04, 0.43388E+04, 0.44087E+04, 0.44792E+04, 0.45503E+04, 0.46221E+04, + 0.46944E+04, 0.47674E+04, 0.48410E+04, 0.49152E+04, 0.49901E+04, 0.50656E+04, 0.51417E+04, + 0.52185E+04, 0.52959E+04, 0.53739E+04, 0.54526E+04, 0.55319E+04, 0.56118E+04, 0.56924E+04, + 0.57736E+04, 0.58555E+04, 0.59380E+04, 0.60212E+04, 0.61050E+04, 0.61895E+04, 0.62746E+04]) # --------------- HI 27: M = 17, I = 2 --------------------- not in TIPS-2011 M = 17 @@ -7906,391 +6924,300 @@ def AtoB(aa, A, B, npt): M = 18 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(4.) -TIPS_ISO_HASH[(M, I)] = float32([0.53847E+03, 0.76580E+03, 0.10017E+04, - 0.12511E+04, 0.15168E+04, 0.18001E+04, 0.21014E+04, 0.24206E+04, - 0.27577E+04, 0.31127E+04, 0.34857E+04, 0.38765E+04, 0.42854E+04, - 0.47124E+04, 0.51575E+04, 0.56208E+04, 0.61025E+04, 0.66026E+04, - 0.71211E+04, 0.76582E+04, 0.82138E+04, 0.87882E+04, 0.93813E+04, - 0.99932E+04, 0.10624E+05, 0.11273E+05, 0.11942E+05, 0.12629E+05, - 0.13336E+05, 0.14061E+05, 0.14806E+05, 0.15570E+05, 0.16353E+05, - 0.17155E+05, 0.17976E+05, 0.18816E+05, 0.19676E+05, 0.20555E+05, - 0.21453E+05, 0.22371E+05, 0.23308E+05, 0.24264E+05, 0.25240E+05, - 0.26236E+05, 0.27250E+05, 0.28284E+05, 0.29338E+05, 0.30412E+05, - 0.31505E+05, 0.32617E+05, 0.33749E+05, 0.34901E+05, 0.36072E+05, - 0.37263E+05, 0.38474E+05, 0.39705E+05, 0.40955E+05, 0.42225E+05, - 0.43515E+05, 0.44825E+05, 0.46154E+05, 0.47504E+05, 0.48873E+05, - 0.50262E+05, 0.51672E+05, 0.53101E+05, 0.54549E+05, 0.56019E+05, - 0.57508E+05, 0.59017E+05, 0.60546E+05, 0.62095E+05, 0.63665E+05, - 0.65254E+05, 0.66864E+05, 0.68494E+05, 0.70144E+05, 0.71814E+05, - 0.73504E+05, 0.75215E+05, 0.76946E+05, 0.78698E+05, 0.80470E+05, - 0.82261E+05, 0.84074E+05, 0.85907E+05, 0.87760E+05, 0.89633E+05, - 0.91527E+05, 0.93442E+05, 0.95377E+05, 0.97333E+05, 0.99309E+05, - 0.10131E+06, 0.10332E+06, 0.10536E+06, 0.10742E+06, 0.10950E+06, - 0.11160E+06, 0.11372E+06, 0.11586E+06, 0.11802E+06, 0.12020E+06, - 0.12241E+06, 0.12463E+06, 0.12688E+06, 0.12914E+06, 0.13143E+06, - 0.13374E+06, 0.13607E+06, 0.13842E+06, 0.14079E+06, 0.14318E+06, - 0.14559E+06, 0.14802E+06, 0.15048E+06, 0.15295E+06, 0.15545E+06, - 0.15797E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.53847E+03, 0.76580E+03, 0.10017E+04, 0.12511E+04, 0.15168E+04, 0.18001E+04, 0.21014E+04, + 0.24206E+04, 0.27577E+04, 0.31127E+04, 0.34857E+04, 0.38765E+04, 0.42854E+04, 0.47124E+04, + 0.51575E+04, 0.56208E+04, 0.61025E+04, 0.66026E+04, 0.71211E+04, 0.76582E+04, 0.82138E+04, + 0.87882E+04, 0.93813E+04, 0.99932E+04, 0.10624E+05, 0.11273E+05, 0.11942E+05, 0.12629E+05, + 0.13336E+05, 0.14061E+05, 0.14806E+05, 0.15570E+05, 0.16353E+05, 0.17155E+05, 0.17976E+05, + 0.18816E+05, 0.19676E+05, 0.20555E+05, 0.21453E+05, 0.22371E+05, 0.23308E+05, 0.24264E+05, + 0.25240E+05, 0.26236E+05, 0.27250E+05, 0.28284E+05, 0.29338E+05, 0.30412E+05, 0.31505E+05, + 0.32617E+05, 0.33749E+05, 0.34901E+05, 0.36072E+05, 0.37263E+05, 0.38474E+05, 0.39705E+05, + 0.40955E+05, 0.42225E+05, 0.43515E+05, 0.44825E+05, 0.46154E+05, 0.47504E+05, 0.48873E+05, + 0.50262E+05, 0.51672E+05, 0.53101E+05, 0.54549E+05, 0.56019E+05, 0.57508E+05, 0.59017E+05, + 0.60546E+05, 0.62095E+05, 0.63665E+05, 0.65254E+05, 0.66864E+05, 0.68494E+05, 0.70144E+05, + 0.71814E+05, 0.73504E+05, 0.75215E+05, 0.76946E+05, 0.78698E+05, 0.80470E+05, 0.82261E+05, + 0.84074E+05, 0.85907E+05, 0.87760E+05, 0.89633E+05, 0.91527E+05, 0.93442E+05, 0.95377E+05, + 0.97333E+05, 0.99309E+05, 0.10131E+06, 0.10332E+06, 0.10536E+06, 0.10742E+06, 0.10950E+06, + 0.11160E+06, 0.11372E+06, 0.11586E+06, 0.11802E+06, 0.12020E+06, 0.12241E+06, 0.12463E+06, + 0.12688E+06, 0.12914E+06, 0.13143E+06, 0.13374E+06, 0.13607E+06, 0.13842E+06, 0.14079E+06, + 0.14318E+06, 0.14559E+06, 0.14802E+06, 0.15048E+06, 0.15295E+06, 0.15545E+06, 0.15797E+06]) # --------------- ClO 76: M = 18, I = 2 --------------------- M = 18 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(4.) -TIPS_ISO_HASH[(M, I)] = float32([0.54775E+03, 0.77899E+03, 0.10189E+04, - 0.12726E+04, 0.15430E+04, 0.18313E+04, 0.21378E+04, 0.24627E+04, - 0.28059E+04, 0.31674E+04, 0.35472E+04, 0.39454E+04, 0.43621E+04, - 0.47972E+04, 0.52508E+04, 0.57232E+04, 0.62143E+04, 0.67242E+04, - 0.72531E+04, 0.78010E+04, 0.83678E+04, 0.89537E+04, 0.95589E+04, - 0.10183E+05, 0.10827E+05, 0.11490E+05, 0.12172E+05, 0.12874E+05, - 0.13595E+05, 0.14335E+05, 0.15095E+05, 0.15875E+05, 0.16674E+05, - 0.17493E+05, 0.18332E+05, 0.19190E+05, 0.20068E+05, 0.20965E+05, - 0.21882E+05, 0.22820E+05, 0.23776E+05, 0.24753E+05, 0.25750E+05, - 0.26766E+05, 0.27803E+05, 0.28859E+05, 0.29935E+05, 0.31032E+05, - 0.32148E+05, 0.33284E+05, 0.34441E+05, 0.35617E+05, 0.36814E+05, - 0.38031E+05, 0.39267E+05, 0.40524E+05, 0.41802E+05, 0.43099E+05, - 0.44417E+05, 0.45755E+05, 0.47113E+05, 0.48492E+05, 0.49891E+05, - 0.51310E+05, 0.52750E+05, 0.54210E+05, 0.55690E+05, 0.57191E+05, - 0.58713E+05, 0.60255E+05, 0.61817E+05, 0.63400E+05, 0.65004E+05, - 0.66628E+05, 0.68272E+05, 0.69938E+05, 0.71624E+05, 0.73331E+05, - 0.75058E+05, 0.76806E+05, 0.78575E+05, 0.80364E+05, 0.82175E+05, - 0.84006E+05, 0.85858E+05, 0.87731E+05, 0.89625E+05, 0.91539E+05, - 0.93475E+05, 0.95431E+05, 0.97409E+05, 0.99407E+05, 0.10143E+06, - 0.10347E+06, 0.10553E+06, 0.10761E+06, 0.10972E+06, 0.11184E+06, - 0.11399E+06, 0.11615E+06, 0.11834E+06, 0.12055E+06, 0.12278E+06, - 0.12503E+06, 0.12731E+06, 0.12960E+06, 0.13192E+06, 0.13425E+06, - 0.13661E+06, 0.13899E+06, 0.14139E+06, 0.14382E+06, 0.14626E+06, - 0.14873E+06, 0.15121E+06, 0.15372E+06, 0.15625E+06, 0.15880E+06, - 0.16138E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.54775E+03, 0.77899E+03, 0.10189E+04, 0.12726E+04, 0.15430E+04, 0.18313E+04, 0.21378E+04, + 0.24627E+04, 0.28059E+04, 0.31674E+04, 0.35472E+04, 0.39454E+04, 0.43621E+04, 0.47972E+04, + 0.52508E+04, 0.57232E+04, 0.62143E+04, 0.67242E+04, 0.72531E+04, 0.78010E+04, 0.83678E+04, + 0.89537E+04, 0.95589E+04, 0.10183E+05, 0.10827E+05, 0.11490E+05, 0.12172E+05, 0.12874E+05, + 0.13595E+05, 0.14335E+05, 0.15095E+05, 0.15875E+05, 0.16674E+05, 0.17493E+05, 0.18332E+05, + 0.19190E+05, 0.20068E+05, 0.20965E+05, 0.21882E+05, 0.22820E+05, 0.23776E+05, 0.24753E+05, + 0.25750E+05, 0.26766E+05, 0.27803E+05, 0.28859E+05, 0.29935E+05, 0.31032E+05, 0.32148E+05, + 0.33284E+05, 0.34441E+05, 0.35617E+05, 0.36814E+05, 0.38031E+05, 0.39267E+05, 0.40524E+05, + 0.41802E+05, 0.43099E+05, 0.44417E+05, 0.45755E+05, 0.47113E+05, 0.48492E+05, 0.49891E+05, + 0.51310E+05, 0.52750E+05, 0.54210E+05, 0.55690E+05, 0.57191E+05, 0.58713E+05, 0.60255E+05, + 0.61817E+05, 0.63400E+05, 0.65004E+05, 0.66628E+05, 0.68272E+05, 0.69938E+05, 0.71624E+05, + 0.73331E+05, 0.75058E+05, 0.76806E+05, 0.78575E+05, 0.80364E+05, 0.82175E+05, 0.84006E+05, + 0.85858E+05, 0.87731E+05, 0.89625E+05, 0.91539E+05, 0.93475E+05, 0.95431E+05, 0.97409E+05, + 0.99407E+05, 0.10143E+06, 0.10347E+06, 0.10553E+06, 0.10761E+06, 0.10972E+06, 0.11184E+06, + 0.11399E+06, 0.11615E+06, 0.11834E+06, 0.12055E+06, 0.12278E+06, 0.12503E+06, 0.12731E+06, + 0.12960E+06, 0.13192E+06, 0.13425E+06, 0.13661E+06, 0.13899E+06, 0.14139E+06, 0.14382E+06, + 0.14626E+06, 0.14873E+06, 0.15121E+06, 0.15372E+06, 0.15625E+06, 0.15880E+06, 0.16138E+06]) # --------------- OCS 622: M = 19, I = 1 --------------------- M = 19 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.20609E+03, 0.29199E+03, 0.37861E+03, - 0.46737E+03, 0.56024E+03, 0.65929E+03, 0.76649E+03, 0.88361E+03, - 0.10123E+04, 0.11541E+04, 0.13105E+04, 0.14829E+04, 0.16728E+04, - 0.18818E+04, 0.21113E+04, 0.23629E+04, 0.26383E+04, 0.29391E+04, - 0.32672E+04, 0.36245E+04, 0.40128E+04, 0.44343E+04, 0.48911E+04, - 0.53853E+04, 0.59193E+04, 0.64956E+04, 0.71166E+04, 0.77849E+04, - 0.85033E+04, 0.92746E+04, 0.10102E+05, 0.10988E+05, 0.11936E+05, - 0.12949E+05, 0.14032E+05, 0.15186E+05, 0.16416E+05, 0.17726E+05, - 0.19120E+05, 0.20601E+05, 0.22173E+05, 0.23842E+05, 0.25611E+05, - 0.27484E+05, 0.29468E+05, 0.31566E+05, 0.33783E+05, 0.36124E+05, - 0.38595E+05, 0.41202E+05, 0.43949E+05, 0.46842E+05, 0.49888E+05, - 0.53092E+05, 0.56460E+05, 0.59999E+05, 0.63716E+05, 0.67616E+05, - 0.71708E+05, 0.75997E+05, 0.80491E+05, 0.85197E+05, 0.90124E+05, - 0.95278E+05, 0.10067E+06, 0.10630E+06, 0.11219E+06, 0.11833E+06, - 0.12475E+06, 0.13144E+06, 0.13842E+06, 0.14570E+06, 0.15328E+06, - 0.16117E+06, 0.16940E+06, 0.17795E+06, 0.18686E+06, 0.19611E+06, - 0.20574E+06, 0.21574E+06, 0.22613E+06, 0.23692E+06, 0.24813E+06, - 0.25975E+06, 0.27182E+06, 0.28433E+06, 0.29730E+06, 0.31074E+06, - 0.32467E+06, 0.33909E+06, 0.35403E+06, 0.36950E+06, 0.38551E+06, - 0.40207E+06, 0.41920E+06, 0.43691E+06, 0.45522E+06, 0.47415E+06, - 0.49370E+06, 0.51390E+06, 0.53476E+06, 0.55629E+06, 0.57852E+06, - 0.60146E+06, 0.62513E+06, 0.64954E+06, 0.67471E+06, 0.70067E+06, - 0.72742E+06, 0.75499E+06, 0.78339E+06, 0.81265E+06, 0.84279E+06, - 0.87381E+06, 0.90576E+06, 0.93863E+06, 0.97246E+06, 0.10073E+07, - 0.10431E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.20609E+03, 0.29199E+03, 0.37861E+03, 0.46737E+03, 0.56024E+03, 0.65929E+03, 0.76649E+03, + 0.88361E+03, 0.10123E+04, 0.11541E+04, 0.13105E+04, 0.14829E+04, 0.16728E+04, 0.18818E+04, + 0.21113E+04, 0.23629E+04, 0.26383E+04, 0.29391E+04, 0.32672E+04, 0.36245E+04, 0.40128E+04, + 0.44343E+04, 0.48911E+04, 0.53853E+04, 0.59193E+04, 0.64956E+04, 0.71166E+04, 0.77849E+04, + 0.85033E+04, 0.92746E+04, 0.10102E+05, 0.10988E+05, 0.11936E+05, 0.12949E+05, 0.14032E+05, + 0.15186E+05, 0.16416E+05, 0.17726E+05, 0.19120E+05, 0.20601E+05, 0.22173E+05, 0.23842E+05, + 0.25611E+05, 0.27484E+05, 0.29468E+05, 0.31566E+05, 0.33783E+05, 0.36124E+05, 0.38595E+05, + 0.41202E+05, 0.43949E+05, 0.46842E+05, 0.49888E+05, 0.53092E+05, 0.56460E+05, 0.59999E+05, + 0.63716E+05, 0.67616E+05, 0.71708E+05, 0.75997E+05, 0.80491E+05, 0.85197E+05, 0.90124E+05, + 0.95278E+05, 0.10067E+06, 0.10630E+06, 0.11219E+06, 0.11833E+06, 0.12475E+06, 0.13144E+06, + 0.13842E+06, 0.14570E+06, 0.15328E+06, 0.16117E+06, 0.16940E+06, 0.17795E+06, 0.18686E+06, + 0.19611E+06, 0.20574E+06, 0.21574E+06, 0.22613E+06, 0.23692E+06, 0.24813E+06, 0.25975E+06, + 0.27182E+06, 0.28433E+06, 0.29730E+06, 0.31074E+06, 0.32467E+06, 0.33909E+06, 0.35403E+06, + 0.36950E+06, 0.38551E+06, 0.40207E+06, 0.41920E+06, 0.43691E+06, 0.45522E+06, 0.47415E+06, + 0.49370E+06, 0.51390E+06, 0.53476E+06, 0.55629E+06, 0.57852E+06, 0.60146E+06, 0.62513E+06, + 0.64954E+06, 0.67471E+06, 0.70067E+06, 0.72742E+06, 0.75499E+06, 0.78339E+06, 0.81265E+06, + 0.84279E+06, 0.87381E+06, 0.90576E+06, 0.93863E+06, 0.97246E+06, 0.10073E+07, 0.10431E+07]) # --------------- OCS 624: M = 19, I = 2 --------------------- M = 19 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.21125E+03, 0.29930E+03, 0.38809E+03, - 0.47911E+03, 0.57437E+03, 0.67603E+03, 0.78610E+03, 0.90643E+03, - 0.10387E+04, 0.11846E+04, 0.13456E+04, 0.15231E+04, 0.17188E+04, - 0.19342E+04, 0.21709E+04, 0.24304E+04, 0.27145E+04, 0.30250E+04, - 0.33638E+04, 0.37328E+04, 0.41339E+04, 0.45694E+04, 0.50415E+04, - 0.55524E+04, 0.61045E+04, 0.67004E+04, 0.73427E+04, 0.80340E+04, - 0.87773E+04, 0.95755E+04, 0.10432E+05, 0.11349E+05, 0.12330E+05, - 0.13380E+05, 0.14500E+05, 0.15696E+05, 0.16970E+05, 0.18327E+05, - 0.19770E+05, 0.21305E+05, 0.22934E+05, 0.24663E+05, 0.26497E+05, - 0.28439E+05, 0.30495E+05, 0.32669E+05, 0.34968E+05, 0.37396E+05, - 0.39958E+05, 0.42661E+05, 0.45510E+05, 0.48511E+05, 0.51669E+05, - 0.54993E+05, 0.58487E+05, 0.62159E+05, 0.66014E+05, 0.70061E+05, - 0.74306E+05, 0.78757E+05, 0.83421E+05, 0.88305E+05, 0.93418E+05, - 0.98767E+05, 0.10436E+06, 0.11021E+06, 0.11632E+06, 0.12270E+06, - 0.12936E+06, 0.13631E+06, 0.14355E+06, 0.15111E+06, 0.15898E+06, - 0.16718E+06, 0.17572E+06, 0.18460E+06, 0.19385E+06, 0.20346E+06, - 0.21346E+06, 0.22385E+06, 0.23464E+06, 0.24585E+06, 0.25748E+06, - 0.26956E+06, 0.28209E+06, 0.29509E+06, 0.30856E+06, 0.32252E+06, - 0.33699E+06, 0.35198E+06, 0.36750E+06, 0.38357E+06, 0.40020E+06, - 0.41741E+06, 0.43521E+06, 0.45362E+06, 0.47264E+06, 0.49231E+06, - 0.51263E+06, 0.53362E+06, 0.55529E+06, 0.57768E+06, 0.60078E+06, - 0.62462E+06, 0.64922E+06, 0.67459E+06, 0.70075E+06, 0.72773E+06, - 0.75554E+06, 0.78419E+06, 0.81372E+06, 0.84413E+06, 0.87546E+06, - 0.90771E+06, 0.94092E+06, 0.97509E+06, 0.10103E+07, 0.10464E+07, - 0.10837E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.21125E+03, 0.29930E+03, 0.38809E+03, 0.47911E+03, 0.57437E+03, 0.67603E+03, 0.78610E+03, + 0.90643E+03, 0.10387E+04, 0.11846E+04, 0.13456E+04, 0.15231E+04, 0.17188E+04, 0.19342E+04, + 0.21709E+04, 0.24304E+04, 0.27145E+04, 0.30250E+04, 0.33638E+04, 0.37328E+04, 0.41339E+04, + 0.45694E+04, 0.50415E+04, 0.55524E+04, 0.61045E+04, 0.67004E+04, 0.73427E+04, 0.80340E+04, + 0.87773E+04, 0.95755E+04, 0.10432E+05, 0.11349E+05, 0.12330E+05, 0.13380E+05, 0.14500E+05, + 0.15696E+05, 0.16970E+05, 0.18327E+05, 0.19770E+05, 0.21305E+05, 0.22934E+05, 0.24663E+05, + 0.26497E+05, 0.28439E+05, 0.30495E+05, 0.32669E+05, 0.34968E+05, 0.37396E+05, 0.39958E+05, + 0.42661E+05, 0.45510E+05, 0.48511E+05, 0.51669E+05, 0.54993E+05, 0.58487E+05, 0.62159E+05, + 0.66014E+05, 0.70061E+05, 0.74306E+05, 0.78757E+05, 0.83421E+05, 0.88305E+05, 0.93418E+05, + 0.98767E+05, 0.10436E+06, 0.11021E+06, 0.11632E+06, 0.12270E+06, 0.12936E+06, 0.13631E+06, + 0.14355E+06, 0.15111E+06, 0.15898E+06, 0.16718E+06, 0.17572E+06, 0.18460E+06, 0.19385E+06, + 0.20346E+06, 0.21346E+06, 0.22385E+06, 0.23464E+06, 0.24585E+06, 0.25748E+06, 0.26956E+06, + 0.28209E+06, 0.29509E+06, 0.30856E+06, 0.32252E+06, 0.33699E+06, 0.35198E+06, 0.36750E+06, + 0.38357E+06, 0.40020E+06, 0.41741E+06, 0.43521E+06, 0.45362E+06, 0.47264E+06, 0.49231E+06, + 0.51263E+06, 0.53362E+06, 0.55529E+06, 0.57768E+06, 0.60078E+06, 0.62462E+06, 0.64922E+06, + 0.67459E+06, 0.70075E+06, 0.72773E+06, 0.75554E+06, 0.78419E+06, 0.81372E+06, 0.84413E+06, + 0.87546E+06, 0.90771E+06, 0.94092E+06, 0.97509E+06, 0.10103E+07, 0.10464E+07, 0.10837E+07]) # --------------- OCS 632: M = 19, I = 3 --------------------- M = 19 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.41351E+03, 0.58591E+03, 0.76004E+03, - 0.93907E+03, 0.11273E+04, 0.13289E+04, 0.15481E+04, 0.17884E+04, - 0.20533E+04, 0.23459E+04, 0.26692E+04, 0.30264E+04, 0.34205E+04, - 0.38547E+04, 0.43323E+04, 0.48565E+04, 0.54309E+04, 0.60592E+04, - 0.67451E+04, 0.74928E+04, 0.83064E+04, 0.91903E+04, 0.10149E+05, - 0.11187E+05, 0.12310E+05, 0.13523E+05, 0.14831E+05, 0.16240E+05, - 0.17756E+05, 0.19384E+05, 0.21132E+05, 0.23005E+05, 0.25011E+05, - 0.27157E+05, 0.29449E+05, 0.31896E+05, 0.34506E+05, 0.37286E+05, - 0.40245E+05, 0.43392E+05, 0.46735E+05, 0.50284E+05, 0.54048E+05, - 0.58038E+05, 0.62263E+05, 0.66733E+05, 0.71460E+05, 0.76455E+05, - 0.81728E+05, 0.87292E+05, 0.93159E+05, 0.99341E+05, 0.10585E+06, - 0.11270E+06, 0.11991E+06, 0.12748E+06, 0.13543E+06, 0.14378E+06, - 0.15255E+06, 0.16174E+06, 0.17137E+06, 0.18146E+06, 0.19202E+06, - 0.20308E+06, 0.21465E+06, 0.22674E+06, 0.23937E+06, 0.25257E+06, - 0.26635E+06, 0.28073E+06, 0.29573E+06, 0.31137E+06, 0.32767E+06, - 0.34466E+06, 0.36235E+06, 0.38076E+06, 0.39992E+06, 0.41985E+06, - 0.44057E+06, 0.46211E+06, 0.48450E+06, 0.50775E+06, 0.53189E+06, - 0.55695E+06, 0.58295E+06, 0.60992E+06, 0.63789E+06, 0.66688E+06, - 0.69693E+06, 0.72806E+06, 0.76030E+06, 0.79368E+06, 0.82823E+06, - 0.86399E+06, 0.90097E+06, 0.93923E+06, 0.97878E+06, 0.10197E+07, - 0.10619E+07, 0.11056E+07, 0.11506E+07, 0.11972E+07, 0.12453E+07, - 0.12949E+07, 0.13460E+07, 0.13988E+07, 0.14533E+07, 0.15094E+07, - 0.15673E+07, 0.16270E+07, 0.16884E+07, 0.17518E+07, 0.18170E+07, - 0.18842E+07, 0.19533E+07, 0.20245E+07, 0.20978E+07, 0.21732E+07, - 0.22507E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.41351E+03, 0.58591E+03, 0.76004E+03, 0.93907E+03, 0.11273E+04, 0.13289E+04, 0.15481E+04, + 0.17884E+04, 0.20533E+04, 0.23459E+04, 0.26692E+04, 0.30264E+04, 0.34205E+04, 0.38547E+04, + 0.43323E+04, 0.48565E+04, 0.54309E+04, 0.60592E+04, 0.67451E+04, 0.74928E+04, 0.83064E+04, + 0.91903E+04, 0.10149E+05, 0.11187E+05, 0.12310E+05, 0.13523E+05, 0.14831E+05, 0.16240E+05, + 0.17756E+05, 0.19384E+05, 0.21132E+05, 0.23005E+05, 0.25011E+05, 0.27157E+05, 0.29449E+05, + 0.31896E+05, 0.34506E+05, 0.37286E+05, 0.40245E+05, 0.43392E+05, 0.46735E+05, 0.50284E+05, + 0.54048E+05, 0.58038E+05, 0.62263E+05, 0.66733E+05, 0.71460E+05, 0.76455E+05, 0.81728E+05, + 0.87292E+05, 0.93159E+05, 0.99341E+05, 0.10585E+06, 0.11270E+06, 0.11991E+06, 0.12748E+06, + 0.13543E+06, 0.14378E+06, 0.15255E+06, 0.16174E+06, 0.17137E+06, 0.18146E+06, 0.19202E+06, + 0.20308E+06, 0.21465E+06, 0.22674E+06, 0.23937E+06, 0.25257E+06, 0.26635E+06, 0.28073E+06, + 0.29573E+06, 0.31137E+06, 0.32767E+06, 0.34466E+06, 0.36235E+06, 0.38076E+06, 0.39992E+06, + 0.41985E+06, 0.44057E+06, 0.46211E+06, 0.48450E+06, 0.50775E+06, 0.53189E+06, 0.55695E+06, + 0.58295E+06, 0.60992E+06, 0.63789E+06, 0.66688E+06, 0.69693E+06, 0.72806E+06, 0.76030E+06, + 0.79368E+06, 0.82823E+06, 0.86399E+06, 0.90097E+06, 0.93923E+06, 0.97878E+06, 0.10197E+07, + 0.10619E+07, 0.11056E+07, 0.11506E+07, 0.11972E+07, 0.12453E+07, 0.12949E+07, 0.13460E+07, + 0.13988E+07, 0.14533E+07, 0.15094E+07, 0.15673E+07, 0.16270E+07, 0.16884E+07, 0.17518E+07, + 0.18170E+07, 0.18842E+07, 0.19533E+07, 0.20245E+07, 0.20978E+07, 0.21732E+07, 0.22507E+07]) # --------------- OCS 623: M = 19, I = 4 --------------------- M = 19 I = 4 TIPS_GSI_HASH[(M, I)] = __FloatType__(4.) -TIPS_ISO_HASH[(M, I)] = float32([0.83485E+03, 0.11828E+04, 0.15337E+04, - 0.18934E+04, 0.22697E+04, 0.26712E+04, 0.31059E+04, 0.35809E+04, - 0.41030E+04, 0.46785E+04, 0.53133E+04, 0.60135E+04, 0.67850E+04, - 0.76338E+04, 0.85663E+04, 0.95888E+04, 0.10708E+05, 0.11931E+05, - 0.13265E+05, 0.14718E+05, 0.16298E+05, 0.18012E+05, 0.19870E+05, - 0.21881E+05, 0.24054E+05, 0.26399E+05, 0.28926E+05, 0.31646E+05, - 0.34570E+05, 0.37710E+05, 0.41077E+05, 0.44685E+05, 0.48545E+05, - 0.52672E+05, 0.57078E+05, 0.61780E+05, 0.66790E+05, 0.72125E+05, - 0.77801E+05, 0.83833E+05, 0.90239E+05, 0.97036E+05, 0.10424E+06, - 0.11188E+06, 0.11996E+06, 0.12850E+06, 0.13754E+06, 0.14708E+06, - 0.15715E+06, 0.16777E+06, 0.17896E+06, 0.19076E+06, 0.20317E+06, - 0.21623E+06, 0.22996E+06, 0.24438E+06, 0.25953E+06, 0.27543E+06, - 0.29211E+06, 0.30959E+06, 0.32791E+06, 0.34710E+06, 0.36718E+06, - 0.38820E+06, 0.41017E+06, 0.43314E+06, 0.45713E+06, 0.48219E+06, - 0.50835E+06, 0.53564E+06, 0.56409E+06, 0.59376E+06, 0.62468E+06, - 0.65688E+06, 0.69041E+06, 0.72530E+06, 0.76161E+06, 0.79937E+06, - 0.83862E+06, 0.87941E+06, 0.92179E+06, 0.96581E+06, 0.10115E+07, - 0.10589E+07, 0.11081E+07, 0.11591E+07, 0.12120E+07, 0.12669E+07, - 0.13237E+07, 0.13825E+07, 0.14435E+07, 0.15066E+07, 0.15718E+07, - 0.16394E+07, 0.17093E+07, 0.17815E+07, 0.18562E+07, 0.19334E+07, - 0.20132E+07, 0.20956E+07, 0.21807E+07, 0.22685E+07, 0.23592E+07, - 0.24528E+07, 0.25494E+07, 0.26490E+07, 0.27517E+07, 0.28576E+07, - 0.29667E+07, 0.30792E+07, 0.31951E+07, 0.33145E+07, 0.34374E+07, - 0.35640E+07, 0.36943E+07, 0.38285E+07, 0.39665E+07, 0.41085E+07, - 0.42546E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.83485E+03, 0.11828E+04, 0.15337E+04, 0.18934E+04, 0.22697E+04, 0.26712E+04, 0.31059E+04, + 0.35809E+04, 0.41030E+04, 0.46785E+04, 0.53133E+04, 0.60135E+04, 0.67850E+04, 0.76338E+04, + 0.85663E+04, 0.95888E+04, 0.10708E+05, 0.11931E+05, 0.13265E+05, 0.14718E+05, 0.16298E+05, + 0.18012E+05, 0.19870E+05, 0.21881E+05, 0.24054E+05, 0.26399E+05, 0.28926E+05, 0.31646E+05, + 0.34570E+05, 0.37710E+05, 0.41077E+05, 0.44685E+05, 0.48545E+05, 0.52672E+05, 0.57078E+05, + 0.61780E+05, 0.66790E+05, 0.72125E+05, 0.77801E+05, 0.83833E+05, 0.90239E+05, 0.97036E+05, + 0.10424E+06, 0.11188E+06, 0.11996E+06, 0.12850E+06, 0.13754E+06, 0.14708E+06, 0.15715E+06, + 0.16777E+06, 0.17896E+06, 0.19076E+06, 0.20317E+06, 0.21623E+06, 0.22996E+06, 0.24438E+06, + 0.25953E+06, 0.27543E+06, 0.29211E+06, 0.30959E+06, 0.32791E+06, 0.34710E+06, 0.36718E+06, + 0.38820E+06, 0.41017E+06, 0.43314E+06, 0.45713E+06, 0.48219E+06, 0.50835E+06, 0.53564E+06, + 0.56409E+06, 0.59376E+06, 0.62468E+06, 0.65688E+06, 0.69041E+06, 0.72530E+06, 0.76161E+06, + 0.79937E+06, 0.83862E+06, 0.87941E+06, 0.92179E+06, 0.96581E+06, 0.10115E+07, 0.10589E+07, + 0.11081E+07, 0.11591E+07, 0.12120E+07, 0.12669E+07, 0.13237E+07, 0.13825E+07, 0.14435E+07, + 0.15066E+07, 0.15718E+07, 0.16394E+07, 0.17093E+07, 0.17815E+07, 0.18562E+07, 0.19334E+07, + 0.20132E+07, 0.20956E+07, 0.21807E+07, 0.22685E+07, 0.23592E+07, 0.24528E+07, 0.25494E+07, + 0.26490E+07, 0.27517E+07, 0.28576E+07, 0.29667E+07, 0.30792E+07, 0.31951E+07, 0.33145E+07, + 0.34374E+07, 0.35640E+07, 0.36943E+07, 0.38285E+07, 0.39665E+07, 0.41085E+07, 0.42546E+07]) # --------------- OCS 822: M = 19, I = 5 --------------------- M = 19 I = 5 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.21967E+03, 0.31126E+03, 0.40370E+03, - 0.49862E+03, 0.59823E+03, 0.70481E+03, 0.82050E+03, 0.94724E+03, - 0.10868E+04, 0.12409E+04, 0.14112E+04, 0.15993E+04, 0.18067E+04, - 0.20353E+04, 0.22866E+04, 0.25624E+04, 0.28645E+04, 0.31950E+04, - 0.35558E+04, 0.39490E+04, 0.43767E+04, 0.48413E+04, 0.53452E+04, - 0.58909E+04, 0.64810E+04, 0.71182E+04, 0.78053E+04, 0.85454E+04, - 0.93413E+04, 0.10196E+05, 0.11114E+05, 0.12098E+05, 0.13151E+05, - 0.14277E+05, 0.15480E+05, 0.16764E+05, 0.18133E+05, 0.19592E+05, - 0.21144E+05, 0.22794E+05, 0.24548E+05, 0.26409E+05, 0.28383E+05, - 0.30475E+05, 0.32689E+05, 0.35033E+05, 0.37511E+05, 0.40128E+05, - 0.42892E+05, 0.45808E+05, 0.48882E+05, 0.52121E+05, 0.55532E+05, - 0.59121E+05, 0.62895E+05, 0.66861E+05, 0.71028E+05, 0.75402E+05, - 0.79991E+05, 0.84803E+05, 0.89847E+05, 0.95130E+05, 0.10066E+06, - 0.10645E+06, 0.11251E+06, 0.11883E+06, 0.12545E+06, 0.13236E+06, - 0.13957E+06, 0.14710E+06, 0.15495E+06, 0.16313E+06, 0.17166E+06, - 0.18055E+06, 0.18980E+06, 0.19944E+06, 0.20946E+06, 0.21989E+06, - 0.23073E+06, 0.24200E+06, 0.25371E+06, 0.26587E+06, 0.27850E+06, - 0.29161E+06, 0.30521E+06, 0.31931E+06, 0.33394E+06, 0.34910E+06, - 0.36482E+06, 0.38109E+06, 0.39795E+06, 0.41541E+06, 0.43348E+06, - 0.45217E+06, 0.47151E+06, 0.49151E+06, 0.51219E+06, 0.53356E+06, - 0.55565E+06, 0.57847E+06, 0.60204E+06, 0.62637E+06, 0.65149E+06, - 0.67742E+06, 0.70417E+06, 0.73176E+06, 0.76023E+06, 0.78957E+06, - 0.81982E+06, 0.85100E+06, 0.88313E+06, 0.91622E+06, 0.95031E+06, - 0.98541E+06, 0.10216E+07, 0.10587E+07, 0.10970E+07, 0.11364E+07, - 0.11769E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.21967E+03, 0.31126E+03, 0.40370E+03, 0.49862E+03, 0.59823E+03, 0.70481E+03, 0.82050E+03, + 0.94724E+03, 0.10868E+04, 0.12409E+04, 0.14112E+04, 0.15993E+04, 0.18067E+04, 0.20353E+04, + 0.22866E+04, 0.25624E+04, 0.28645E+04, 0.31950E+04, 0.35558E+04, 0.39490E+04, 0.43767E+04, + 0.48413E+04, 0.53452E+04, 0.58909E+04, 0.64810E+04, 0.71182E+04, 0.78053E+04, 0.85454E+04, + 0.93413E+04, 0.10196E+05, 0.11114E+05, 0.12098E+05, 0.13151E+05, 0.14277E+05, 0.15480E+05, + 0.16764E+05, 0.18133E+05, 0.19592E+05, 0.21144E+05, 0.22794E+05, 0.24548E+05, 0.26409E+05, + 0.28383E+05, 0.30475E+05, 0.32689E+05, 0.35033E+05, 0.37511E+05, 0.40128E+05, 0.42892E+05, + 0.45808E+05, 0.48882E+05, 0.52121E+05, 0.55532E+05, 0.59121E+05, 0.62895E+05, 0.66861E+05, + 0.71028E+05, 0.75402E+05, 0.79991E+05, 0.84803E+05, 0.89847E+05, 0.95130E+05, 0.10066E+06, + 0.10645E+06, 0.11251E+06, 0.11883E+06, 0.12545E+06, 0.13236E+06, 0.13957E+06, 0.14710E+06, + 0.15495E+06, 0.16313E+06, 0.17166E+06, 0.18055E+06, 0.18980E+06, 0.19944E+06, 0.20946E+06, + 0.21989E+06, 0.23073E+06, 0.24200E+06, 0.25371E+06, 0.26587E+06, 0.27850E+06, 0.29161E+06, + 0.30521E+06, 0.31931E+06, 0.33394E+06, 0.34910E+06, 0.36482E+06, 0.38109E+06, 0.39795E+06, + 0.41541E+06, 0.43348E+06, 0.45217E+06, 0.47151E+06, 0.49151E+06, 0.51219E+06, 0.53356E+06, + 0.55565E+06, 0.57847E+06, 0.60204E+06, 0.62637E+06, 0.65149E+06, 0.67742E+06, 0.70417E+06, + 0.73176E+06, 0.76023E+06, 0.78957E+06, 0.81982E+06, 0.85100E+06, 0.88313E+06, 0.91622E+06, + 0.95031E+06, 0.98541E+06, 0.10216E+07, 0.10587E+07, 0.10970E+07, 0.11364E+07, 0.11769E+07]) # --------------- H2CO 126: M = 20, I = 2 --------------------- M = 20 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.25934E+03, 0.43623E+03, 0.64143E+03, - 0.87152E+03, 0.11241E+04, 0.13975E+04, 0.16906E+04, 0.20029E+04, - 0.23344E+04, 0.26857E+04, 0.30577E+04, 0.34518E+04, 0.38698E+04, - 0.43138E+04, 0.47860E+04, 0.52890E+04, 0.58256E+04, 0.63985E+04, - 0.70109E+04, 0.76660E+04, 0.83673E+04, 0.91184E+04, 0.99230E+04, - 0.10785E+05, 0.11710E+05, 0.12700E+05, 0.13762E+05, 0.14900E+05, - 0.16119E+05, 0.17425E+05, 0.18823E+05, 0.20320E+05, 0.21923E+05, - 0.23637E+05, 0.25471E+05, 0.27432E+05, 0.29527E+05, 0.31765E+05, - 0.34155E+05, 0.36706E+05, 0.39428E+05, 0.42330E+05, 0.45424E+05, - 0.48720E+05, 0.52231E+05, 0.55968E+05, 0.59945E+05, 0.64175E+05, - 0.68672E+05, 0.73450E+05, 0.78526E+05, 0.83915E+05, 0.89634E+05, - 0.95701E+05, 0.10213E+06, 0.10895E+06, 0.11618E+06, 0.12383E+06, - 0.13193E+06, 0.14049E+06, 0.14956E+06, 0.15914E+06, 0.16927E+06, - 0.17997E+06, 0.19127E+06, 0.20320E+06, 0.21578E+06, 0.22906E+06, - 0.24306E+06, 0.25782E+06, 0.27336E+06, 0.28974E+06, 0.30698E+06, - 0.32513E+06, 0.34422E+06, 0.36430E+06, 0.38542E+06, 0.40761E+06, - 0.43093E+06, 0.45542E+06, 0.48114E+06, 0.50813E+06, 0.53646E+06, - 0.56617E+06, 0.59733E+06, 0.63000E+06, 0.66423E+06, 0.70010E+06, - 0.73767E+06, 0.77701E+06, 0.81818E+06, 0.86127E+06, 0.90635E+06, - 0.95349E+06, 0.10028E+07, 0.10543E+07, 0.11082E+07, 0.11644E+07, - 0.12232E+07, 0.12845E+07, 0.13485E+07, 0.14154E+07, 0.14851E+07, - 0.15578E+07, 0.16337E+07, 0.17127E+07, 0.17952E+07, 0.18810E+07, - 0.19705E+07, 0.20637E+07, 0.21607E+07, 0.22617E+07, 0.23669E+07, - 0.24763E+07, 0.25901E+07, 0.27085E+07, 0.28316E+07, 0.29596E+07, - 0.30926E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.25934E+03, 0.43623E+03, 0.64143E+03, 0.87152E+03, 0.11241E+04, 0.13975E+04, 0.16906E+04, + 0.20029E+04, 0.23344E+04, 0.26857E+04, 0.30577E+04, 0.34518E+04, 0.38698E+04, 0.43138E+04, + 0.47860E+04, 0.52890E+04, 0.58256E+04, 0.63985E+04, 0.70109E+04, 0.76660E+04, 0.83673E+04, + 0.91184E+04, 0.99230E+04, 0.10785E+05, 0.11710E+05, 0.12700E+05, 0.13762E+05, 0.14900E+05, + 0.16119E+05, 0.17425E+05, 0.18823E+05, 0.20320E+05, 0.21923E+05, 0.23637E+05, 0.25471E+05, + 0.27432E+05, 0.29527E+05, 0.31765E+05, 0.34155E+05, 0.36706E+05, 0.39428E+05, 0.42330E+05, + 0.45424E+05, 0.48720E+05, 0.52231E+05, 0.55968E+05, 0.59945E+05, 0.64175E+05, 0.68672E+05, + 0.73450E+05, 0.78526E+05, 0.83915E+05, 0.89634E+05, 0.95701E+05, 0.10213E+06, 0.10895E+06, + 0.11618E+06, 0.12383E+06, 0.13193E+06, 0.14049E+06, 0.14956E+06, 0.15914E+06, 0.16927E+06, + 0.17997E+06, 0.19127E+06, 0.20320E+06, 0.21578E+06, 0.22906E+06, 0.24306E+06, 0.25782E+06, + 0.27336E+06, 0.28974E+06, 0.30698E+06, 0.32513E+06, 0.34422E+06, 0.36430E+06, 0.38542E+06, + 0.40761E+06, 0.43093E+06, 0.45542E+06, 0.48114E+06, 0.50813E+06, 0.53646E+06, 0.56617E+06, + 0.59733E+06, 0.63000E+06, 0.66423E+06, 0.70010E+06, 0.73767E+06, 0.77701E+06, 0.81818E+06, + 0.86127E+06, 0.90635E+06, 0.95349E+06, 0.10028E+07, 0.10543E+07, 0.11082E+07, 0.11644E+07, + 0.12232E+07, 0.12845E+07, 0.13485E+07, 0.14154E+07, 0.14851E+07, 0.15578E+07, 0.16337E+07, + 0.17127E+07, 0.17952E+07, 0.18810E+07, 0.19705E+07, 0.20637E+07, 0.21607E+07, 0.22617E+07, + 0.23669E+07, 0.24763E+07, 0.25901E+07, 0.27085E+07, 0.28316E+07, 0.29596E+07, 0.30926E+07]) # --------------- H2CO 136: M = 20, I = 2 --------------------- M = 20 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.53173E+03, 0.89447E+03, 0.13153E+04, - 0.17871E+04, 0.23051E+04, 0.28658E+04, 0.34669E+04, 0.41073E+04, - 0.47872E+04, 0.55074E+04, 0.62702E+04, 0.70785E+04, 0.79357E+04, - 0.88462E+04, 0.98147E+04, 0.10846E+05, 0.11946E+05, 0.13121E+05, - 0.14377E+05, 0.15721E+05, 0.17159E+05, 0.18699E+05, 0.20349E+05, - 0.22118E+05, 0.24013E+05, 0.26045E+05, 0.28222E+05, 0.30555E+05, - 0.33055E+05, 0.35733E+05, 0.38601E+05, 0.41671E+05, 0.44958E+05, - 0.48474E+05, 0.52235E+05, 0.56255E+05, 0.60552E+05, 0.65142E+05, - 0.70043E+05, 0.75275E+05, 0.80856E+05, 0.86808E+05, 0.93152E+05, - 0.99913E+05, 0.10711E+06, 0.11478E+06, 0.12293E+06, 0.13161E+06, - 0.14083E+06, 0.15063E+06, 0.16104E+06, 0.17209E+06, 0.18382E+06, - 0.19626E+06, 0.20945E+06, 0.22343E+06, 0.23825E+06, 0.25394E+06, - 0.27054E+06, 0.28812E+06, 0.30671E+06, 0.32636E+06, 0.34713E+06, - 0.36907E+06, 0.39224E+06, 0.41671E+06, 0.44252E+06, 0.46975E+06, - 0.49845E+06, 0.52872E+06, 0.56060E+06, 0.59418E+06, 0.62954E+06, - 0.66676E+06, 0.70591E+06, 0.74710E+06, 0.79040E+06, 0.83591E+06, - 0.88373E+06, 0.93395E+06, 0.98669E+06, 0.10421E+07, 0.11001E+07, - 0.11611E+07, 0.12250E+07, 0.12920E+07, 0.13622E+07, 0.14357E+07, - 0.15128E+07, 0.15934E+07, 0.16779E+07, 0.17662E+07, 0.18587E+07, - 0.19554E+07, 0.20565E+07, 0.21621E+07, 0.22725E+07, 0.23879E+07, - 0.25084E+07, 0.26342E+07, 0.27655E+07, 0.29026E+07, 0.30456E+07, - 0.31947E+07, 0.33502E+07, 0.35124E+07, 0.36814E+07, 0.38575E+07, - 0.40410E+07, 0.42321E+07, 0.44311E+07, 0.46382E+07, 0.48538E+07, - 0.50782E+07, 0.53116E+07, 0.55544E+07, 0.58068E+07, 0.60693E+07, - 0.63421E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.53173E+03, 0.89447E+03, 0.13153E+04, 0.17871E+04, 0.23051E+04, 0.28658E+04, 0.34669E+04, + 0.41073E+04, 0.47872E+04, 0.55074E+04, 0.62702E+04, 0.70785E+04, 0.79357E+04, 0.88462E+04, + 0.98147E+04, 0.10846E+05, 0.11946E+05, 0.13121E+05, 0.14377E+05, 0.15721E+05, 0.17159E+05, + 0.18699E+05, 0.20349E+05, 0.22118E+05, 0.24013E+05, 0.26045E+05, 0.28222E+05, 0.30555E+05, + 0.33055E+05, 0.35733E+05, 0.38601E+05, 0.41671E+05, 0.44958E+05, 0.48474E+05, 0.52235E+05, + 0.56255E+05, 0.60552E+05, 0.65142E+05, 0.70043E+05, 0.75275E+05, 0.80856E+05, 0.86808E+05, + 0.93152E+05, 0.99913E+05, 0.10711E+06, 0.11478E+06, 0.12293E+06, 0.13161E+06, 0.14083E+06, + 0.15063E+06, 0.16104E+06, 0.17209E+06, 0.18382E+06, 0.19626E+06, 0.20945E+06, 0.22343E+06, + 0.23825E+06, 0.25394E+06, 0.27054E+06, 0.28812E+06, 0.30671E+06, 0.32636E+06, 0.34713E+06, + 0.36907E+06, 0.39224E+06, 0.41671E+06, 0.44252E+06, 0.46975E+06, 0.49845E+06, 0.52872E+06, + 0.56060E+06, 0.59418E+06, 0.62954E+06, 0.66676E+06, 0.70591E+06, 0.74710E+06, 0.79040E+06, + 0.83591E+06, 0.88373E+06, 0.93395E+06, 0.98669E+06, 0.10421E+07, 0.11001E+07, 0.11611E+07, + 0.12250E+07, 0.12920E+07, 0.13622E+07, 0.14357E+07, 0.15128E+07, 0.15934E+07, 0.16779E+07, + 0.17662E+07, 0.18587E+07, 0.19554E+07, 0.20565E+07, 0.21621E+07, 0.22725E+07, 0.23879E+07, + 0.25084E+07, 0.26342E+07, 0.27655E+07, 0.29026E+07, 0.30456E+07, 0.31947E+07, 0.33502E+07, + 0.35124E+07, 0.36814E+07, 0.38575E+07, 0.40410E+07, 0.42321E+07, 0.44311E+07, 0.46382E+07, + 0.48538E+07, 0.50782E+07, 0.53116E+07, 0.55544E+07, 0.58068E+07, 0.60693E+07, 0.63421E+07]) # --------------- H2CO 128: M = 20, I = 3 --------------------- M = 20 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.27198E+03, 0.45755E+03, 0.67282E+03, - 0.91421E+03, 0.11792E+04, 0.14660E+04, 0.17735E+04, 0.21012E+04, - 0.24490E+04, 0.28175E+04, 0.32077E+04, 0.36212E+04, 0.40598E+04, - 0.45256E+04, 0.50211E+04, 0.55488E+04, 0.61116E+04, 0.67127E+04, - 0.73552E+04, 0.80426E+04, 0.87783E+04, 0.95663E+04, 0.10410E+05, - 0.11315E+05, 0.12285E+05, 0.13324E+05, 0.14438E+05, 0.15632E+05, - 0.16911E+05, 0.18281E+05, 0.19748E+05, 0.21319E+05, 0.23000E+05, - 0.24799E+05, 0.26723E+05, 0.28780E+05, 0.30978E+05, 0.33326E+05, - 0.35834E+05, 0.38510E+05, 0.41365E+05, 0.44410E+05, 0.47656E+05, - 0.51115E+05, 0.54798E+05, 0.58719E+05, 0.62891E+05, 0.67329E+05, - 0.72047E+05, 0.77060E+05, 0.82385E+05, 0.88039E+05, 0.94039E+05, - 0.10040E+06, 0.10715E+06, 0.11431E+06, 0.12189E+06, 0.12991E+06, - 0.13841E+06, 0.14740E+06, 0.15691E+06, 0.16696E+06, 0.17759E+06, - 0.18882E+06, 0.20067E+06, 0.21318E+06, 0.22639E+06, 0.24032E+06, - 0.25501E+06, 0.27049E+06, 0.28680E+06, 0.30398E+06, 0.32207E+06, - 0.34111E+06, 0.36114E+06, 0.38221E+06, 0.40436E+06, 0.42765E+06, - 0.45211E+06, 0.47781E+06, 0.50479E+06, 0.53311E+06, 0.56283E+06, - 0.59400E+06, 0.62669E+06, 0.66097E+06, 0.69688E+06, 0.73451E+06, - 0.77393E+06, 0.81520E+06, 0.85840E+06, 0.90360E+06, 0.95090E+06, - 0.10004E+07, 0.10521E+07, 0.11061E+07, 0.11626E+07, 0.12216E+07, - 0.12833E+07, 0.13476E+07, 0.14148E+07, 0.14849E+07, 0.15581E+07, - 0.16344E+07, 0.17140E+07, 0.17969E+07, 0.18834E+07, 0.19735E+07, - 0.20674E+07, 0.21651E+07, 0.22669E+07, 0.23729E+07, 0.24832E+07, - 0.25980E+07, 0.27174E+07, 0.28416E+07, 0.29708E+07, 0.31050E+07, - 0.32446E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.27198E+03, 0.45755E+03, 0.67282E+03, 0.91421E+03, 0.11792E+04, 0.14660E+04, 0.17735E+04, + 0.21012E+04, 0.24490E+04, 0.28175E+04, 0.32077E+04, 0.36212E+04, 0.40598E+04, 0.45256E+04, + 0.50211E+04, 0.55488E+04, 0.61116E+04, 0.67127E+04, 0.73552E+04, 0.80426E+04, 0.87783E+04, + 0.95663E+04, 0.10410E+05, 0.11315E+05, 0.12285E+05, 0.13324E+05, 0.14438E+05, 0.15632E+05, + 0.16911E+05, 0.18281E+05, 0.19748E+05, 0.21319E+05, 0.23000E+05, 0.24799E+05, 0.26723E+05, + 0.28780E+05, 0.30978E+05, 0.33326E+05, 0.35834E+05, 0.38510E+05, 0.41365E+05, 0.44410E+05, + 0.47656E+05, 0.51115E+05, 0.54798E+05, 0.58719E+05, 0.62891E+05, 0.67329E+05, 0.72047E+05, + 0.77060E+05, 0.82385E+05, 0.88039E+05, 0.94039E+05, 0.10040E+06, 0.10715E+06, 0.11431E+06, + 0.12189E+06, 0.12991E+06, 0.13841E+06, 0.14740E+06, 0.15691E+06, 0.16696E+06, 0.17759E+06, + 0.18882E+06, 0.20067E+06, 0.21318E+06, 0.22639E+06, 0.24032E+06, 0.25501E+06, 0.27049E+06, + 0.28680E+06, 0.30398E+06, 0.32207E+06, 0.34111E+06, 0.36114E+06, 0.38221E+06, 0.40436E+06, + 0.42765E+06, 0.45211E+06, 0.47781E+06, 0.50479E+06, 0.53311E+06, 0.56283E+06, 0.59400E+06, + 0.62669E+06, 0.66097E+06, 0.69688E+06, 0.73451E+06, 0.77393E+06, 0.81520E+06, 0.85840E+06, + 0.90360E+06, 0.95090E+06, 0.10004E+07, 0.10521E+07, 0.11061E+07, 0.11626E+07, 0.12216E+07, + 0.12833E+07, 0.13476E+07, 0.14148E+07, 0.14849E+07, 0.15581E+07, 0.16344E+07, 0.17140E+07, + 0.17969E+07, 0.18834E+07, 0.19735E+07, 0.20674E+07, 0.21651E+07, 0.22669E+07, 0.23729E+07, + 0.24832E+07, 0.25980E+07, 0.27174E+07, 0.28416E+07, 0.29708E+07, 0.31050E+07, 0.32446E+07]) # --------------- HOCl 165: M = 21, I = 1 --------------------- M = 21 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(8.) -TIPS_ISO_HASH[(M, I)] = float32([0.17041E+04, 0.28708E+04, 0.42250E+04, - 0.57456E+04, 0.74211E+04, 0.92470E+04, 0.11225E+05, 0.13359E+05, - 0.15657E+05, 0.18129E+05, 0.20785E+05, 0.23637E+05, 0.26696E+05, - 0.29974E+05, 0.33484E+05, 0.37239E+05, 0.41252E+05, 0.45536E+05, - 0.50105E+05, 0.54973E+05, 0.60152E+05, 0.65659E+05, 0.71507E+05, - 0.77711E+05, 0.84286E+05, 0.91249E+05, 0.98614E+05, 0.10640E+06, - 0.11462E+06, 0.12330E+06, 0.13244E+06, 0.14208E+06, 0.15222E+06, - 0.16289E+06, 0.17411E+06, 0.18589E+06, 0.19825E+06, 0.21123E+06, - 0.22483E+06, 0.23908E+06, 0.25400E+06, 0.26962E+06, 0.28596E+06, - 0.30303E+06, 0.32087E+06, 0.33950E+06, 0.35895E+06, 0.37923E+06, - 0.40038E+06, 0.42243E+06, 0.44539E+06, 0.46930E+06, 0.49419E+06, - 0.52008E+06, 0.54700E+06, 0.57498E+06, 0.60406E+06, 0.63426E+06, - 0.66562E+06, 0.69816E+06, 0.73192E+06, 0.76692E+06, 0.80322E+06, - 0.84083E+06, 0.87979E+06, 0.92014E+06, 0.96192E+06, 0.10052E+07, - 0.10499E+07, 0.10961E+07, 0.11440E+07, 0.11934E+07, 0.12445E+07, - 0.12973E+07, 0.13518E+07, 0.14081E+07, 0.14661E+07, 0.15261E+07, - 0.15879E+07, 0.16516E+07, 0.17174E+07, 0.17851E+07, 0.18550E+07, - 0.19269E+07, 0.20010E+07, 0.20773E+07, 0.21559E+07, 0.22367E+07, - 0.23200E+07, 0.24056E+07, 0.24936E+07, 0.25842E+07, 0.26773E+07, - 0.27730E+07, 0.28714E+07, 0.29724E+07, 0.30763E+07, 0.31829E+07, - 0.32924E+07, 0.34049E+07, 0.35203E+07, 0.36387E+07, 0.37603E+07, - 0.38850E+07, 0.40129E+07, 0.41441E+07, 0.42786E+07, 0.44165E+07, - 0.45579E+07, 0.47028E+07, 0.48512E+07, 0.50033E+07, 0.51592E+07, - 0.53187E+07, 0.54822E+07, 0.56495E+07, 0.58208E+07, 0.59961E+07, - 0.61755E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.17041E+04, 0.28708E+04, 0.42250E+04, 0.57456E+04, 0.74211E+04, 0.92470E+04, 0.11225E+05, + 0.13359E+05, 0.15657E+05, 0.18129E+05, 0.20785E+05, 0.23637E+05, 0.26696E+05, 0.29974E+05, + 0.33484E+05, 0.37239E+05, 0.41252E+05, 0.45536E+05, 0.50105E+05, 0.54973E+05, 0.60152E+05, + 0.65659E+05, 0.71507E+05, 0.77711E+05, 0.84286E+05, 0.91249E+05, 0.98614E+05, 0.10640E+06, + 0.11462E+06, 0.12330E+06, 0.13244E+06, 0.14208E+06, 0.15222E+06, 0.16289E+06, 0.17411E+06, + 0.18589E+06, 0.19825E+06, 0.21123E+06, 0.22483E+06, 0.23908E+06, 0.25400E+06, 0.26962E+06, + 0.28596E+06, 0.30303E+06, 0.32087E+06, 0.33950E+06, 0.35895E+06, 0.37923E+06, 0.40038E+06, + 0.42243E+06, 0.44539E+06, 0.46930E+06, 0.49419E+06, 0.52008E+06, 0.54700E+06, 0.57498E+06, + 0.60406E+06, 0.63426E+06, 0.66562E+06, 0.69816E+06, 0.73192E+06, 0.76692E+06, 0.80322E+06, + 0.84083E+06, 0.87979E+06, 0.92014E+06, 0.96192E+06, 0.10052E+07, 0.10499E+07, 0.10961E+07, + 0.11440E+07, 0.11934E+07, 0.12445E+07, 0.12973E+07, 0.13518E+07, 0.14081E+07, 0.14661E+07, + 0.15261E+07, 0.15879E+07, 0.16516E+07, 0.17174E+07, 0.17851E+07, 0.18550E+07, 0.19269E+07, + 0.20010E+07, 0.20773E+07, 0.21559E+07, 0.22367E+07, 0.23200E+07, 0.24056E+07, 0.24936E+07, + 0.25842E+07, 0.26773E+07, 0.27730E+07, 0.28714E+07, 0.29724E+07, 0.30763E+07, 0.31829E+07, + 0.32924E+07, 0.34049E+07, 0.35203E+07, 0.36387E+07, 0.37603E+07, 0.38850E+07, 0.40129E+07, + 0.41441E+07, 0.42786E+07, 0.44165E+07, 0.45579E+07, 0.47028E+07, 0.48512E+07, 0.50033E+07, + 0.51592E+07, 0.53187E+07, 0.54822E+07, 0.56495E+07, 0.58208E+07, 0.59961E+07, 0.61755E+07]) # --------------- HOCl 167: M = 21, I = 2 --------------------- M = 21 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(8.) -TIPS_ISO_HASH[(M, I)] = float32([0.17342E+04, 0.29215E+04, 0.42998E+04, - 0.58473E+04, 0.75524E+04, 0.94107E+04, 0.11423E+05, 0.13595E+05, - 0.15935E+05, 0.18450E+05, 0.21154E+05, 0.24056E+05, 0.27168E+05, - 0.30505E+05, 0.34077E+05, 0.37899E+05, 0.41983E+05, 0.46343E+05, - 0.50993E+05, 0.55947E+05, 0.61218E+05, 0.66822E+05, 0.72774E+05, - 0.79088E+05, 0.85780E+05, 0.92866E+05, 0.10036E+06, 0.10829E+06, - 0.11665E+06, 0.12548E+06, 0.13479E+06, 0.14460E+06, 0.15492E+06, - 0.16578E+06, 0.17719E+06, 0.18918E+06, 0.20177E+06, 0.21497E+06, - 0.22881E+06, 0.24332E+06, 0.25851E+06, 0.27440E+06, 0.29102E+06, - 0.30840E+06, 0.32656E+06, 0.34552E+06, 0.36531E+06, 0.38595E+06, - 0.40748E+06, 0.42991E+06, 0.45328E+06, 0.47762E+06, 0.50295E+06, - 0.52929E+06, 0.55669E+06, 0.58517E+06, 0.61477E+06, 0.64550E+06, - 0.67741E+06, 0.71053E+06, 0.74489E+06, 0.78052E+06, 0.81745E+06, - 0.85573E+06, 0.89539E+06, 0.93645E+06, 0.97897E+06, 0.10230E+07, - 0.10685E+07, 0.11156E+07, 0.11643E+07, 0.12146E+07, 0.12666E+07, - 0.13203E+07, 0.13757E+07, 0.14330E+07, 0.14921E+07, 0.15531E+07, - 0.16160E+07, 0.16809E+07, 0.17478E+07, 0.18168E+07, 0.18878E+07, - 0.19611E+07, 0.20365E+07, 0.21141E+07, 0.21941E+07, 0.22764E+07, - 0.23611E+07, 0.24482E+07, 0.25378E+07, 0.26300E+07, 0.27248E+07, - 0.28222E+07, 0.29223E+07, 0.30251E+07, 0.31308E+07, 0.32393E+07, - 0.33508E+07, 0.34652E+07, 0.35827E+07, 0.37032E+07, 0.38269E+07, - 0.39539E+07, 0.40840E+07, 0.42176E+07, 0.43545E+07, 0.44948E+07, - 0.46387E+07, 0.47861E+07, 0.49372E+07, 0.50920E+07, 0.52506E+07, - 0.54130E+07, 0.55793E+07, 0.57496E+07, 0.59239E+07, 0.61024E+07, - 0.62850E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.17342E+04, 0.29215E+04, 0.42998E+04, 0.58473E+04, 0.75524E+04, 0.94107E+04, 0.11423E+05, + 0.13595E+05, 0.15935E+05, 0.18450E+05, 0.21154E+05, 0.24056E+05, 0.27168E+05, 0.30505E+05, + 0.34077E+05, 0.37899E+05, 0.41983E+05, 0.46343E+05, 0.50993E+05, 0.55947E+05, 0.61218E+05, + 0.66822E+05, 0.72774E+05, 0.79088E+05, 0.85780E+05, 0.92866E+05, 0.10036E+06, 0.10829E+06, + 0.11665E+06, 0.12548E+06, 0.13479E+06, 0.14460E+06, 0.15492E+06, 0.16578E+06, 0.17719E+06, + 0.18918E+06, 0.20177E+06, 0.21497E+06, 0.22881E+06, 0.24332E+06, 0.25851E+06, 0.27440E+06, + 0.29102E+06, 0.30840E+06, 0.32656E+06, 0.34552E+06, 0.36531E+06, 0.38595E+06, 0.40748E+06, + 0.42991E+06, 0.45328E+06, 0.47762E+06, 0.50295E+06, 0.52929E+06, 0.55669E+06, 0.58517E+06, + 0.61477E+06, 0.64550E+06, 0.67741E+06, 0.71053E+06, 0.74489E+06, 0.78052E+06, 0.81745E+06, + 0.85573E+06, 0.89539E+06, 0.93645E+06, 0.97897E+06, 0.10230E+07, 0.10685E+07, 0.11156E+07, + 0.11643E+07, 0.12146E+07, 0.12666E+07, 0.13203E+07, 0.13757E+07, 0.14330E+07, 0.14921E+07, + 0.15531E+07, 0.16160E+07, 0.16809E+07, 0.17478E+07, 0.18168E+07, 0.18878E+07, 0.19611E+07, + 0.20365E+07, 0.21141E+07, 0.21941E+07, 0.22764E+07, 0.23611E+07, 0.24482E+07, 0.25378E+07, + 0.26300E+07, 0.27248E+07, 0.28222E+07, 0.29223E+07, 0.30251E+07, 0.31308E+07, 0.32393E+07, + 0.33508E+07, 0.34652E+07, 0.35827E+07, 0.37032E+07, 0.38269E+07, 0.39539E+07, 0.40840E+07, + 0.42176E+07, 0.43545E+07, 0.44948E+07, 0.46387E+07, 0.47861E+07, 0.49372E+07, 0.50920E+07, + 0.52506E+07, 0.54130E+07, 0.55793E+07, 0.57496E+07, 0.59239E+07, 0.61024E+07, 0.62850E+07]) # --------------- N2 44: M = 22, I = 1 --------------------- M = 22 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.95487E+02, 0.13466E+03, 0.17386E+03, - 0.21307E+03, 0.25230E+03, 0.29154E+03, 0.33080E+03, 0.37008E+03, - 0.40937E+03, 0.44868E+03, 0.48800E+03, 0.52736E+03, 0.56674E+03, - 0.60616E+03, 0.64562E+03, 0.68515E+03, 0.72475E+03, 0.76445E+03, - 0.80426E+03, 0.84420E+03, 0.88430E+03, 0.92457E+03, 0.96505E+03, - 0.10057E+04, 0.10467E+04, 0.10879E+04, 0.11293E+04, 0.11711E+04, - 0.12132E+04, 0.12556E+04, 0.12984E+04, 0.13416E+04, 0.13851E+04, - 0.14291E+04, 0.14734E+04, 0.15182E+04, 0.15635E+04, 0.16091E+04, - 0.16553E+04, 0.17019E+04, 0.17490E+04, 0.17965E+04, 0.18446E+04, - 0.18932E+04, 0.19422E+04, 0.19918E+04, 0.20419E+04, 0.20926E+04, - 0.21437E+04, 0.21954E+04, 0.22477E+04, 0.23004E+04, 0.23538E+04, - 0.24077E+04, 0.24621E+04, 0.25171E+04, 0.25727E+04, 0.26288E+04, - 0.26856E+04, 0.27428E+04, 0.28007E+04, 0.28591E+04, 0.29181E+04, - 0.29777E+04, 0.30379E+04, 0.30986E+04, 0.31600E+04, 0.32219E+04, - 0.32844E+04, 0.33475E+04, 0.34112E+04, 0.34755E+04, 0.35404E+04, - 0.36059E+04, 0.36720E+04, 0.37387E+04, 0.38060E+04, 0.38739E+04, - 0.39424E+04, 0.40115E+04, 0.40812E+04, 0.41515E+04, 0.42224E+04, - 0.42939E+04, 0.43661E+04, 0.44388E+04, 0.45122E+04, 0.45861E+04, - 0.46607E+04, 0.47359E+04, 0.48117E+04, 0.48882E+04, 0.49652E+04, - 0.50428E+04, 0.51211E+04, 0.52000E+04, 0.52795E+04, 0.53596E+04, - 0.54404E+04, 0.55217E+04, 0.56037E+04, 0.56863E+04, 0.57695E+04, - 0.58533E+04, 0.59378E+04, 0.60229E+04, 0.61086E+04, 0.61950E+04, - 0.62819E+04, 0.63695E+04, 0.64577E+04, 0.65465E+04, 0.66360E+04, - 0.67261E+04, 0.68168E+04, 0.69081E+04, 0.70001E+04, 0.70927E+04, - 0.71859E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.95487E+02, 0.13466E+03, 0.17386E+03, 0.21307E+03, 0.25230E+03, 0.29154E+03, 0.33080E+03, + 0.37008E+03, 0.40937E+03, 0.44868E+03, 0.48800E+03, 0.52736E+03, 0.56674E+03, 0.60616E+03, + 0.64562E+03, 0.68515E+03, 0.72475E+03, 0.76445E+03, 0.80426E+03, 0.84420E+03, 0.88430E+03, + 0.92457E+03, 0.96505E+03, 0.10057E+04, 0.10467E+04, 0.10879E+04, 0.11293E+04, 0.11711E+04, + 0.12132E+04, 0.12556E+04, 0.12984E+04, 0.13416E+04, 0.13851E+04, 0.14291E+04, 0.14734E+04, + 0.15182E+04, 0.15635E+04, 0.16091E+04, 0.16553E+04, 0.17019E+04, 0.17490E+04, 0.17965E+04, + 0.18446E+04, 0.18932E+04, 0.19422E+04, 0.19918E+04, 0.20419E+04, 0.20926E+04, 0.21437E+04, + 0.21954E+04, 0.22477E+04, 0.23004E+04, 0.23538E+04, 0.24077E+04, 0.24621E+04, 0.25171E+04, + 0.25727E+04, 0.26288E+04, 0.26856E+04, 0.27428E+04, 0.28007E+04, 0.28591E+04, 0.29181E+04, + 0.29777E+04, 0.30379E+04, 0.30986E+04, 0.31600E+04, 0.32219E+04, 0.32844E+04, 0.33475E+04, + 0.34112E+04, 0.34755E+04, 0.35404E+04, 0.36059E+04, 0.36720E+04, 0.37387E+04, 0.38060E+04, + 0.38739E+04, 0.39424E+04, 0.40115E+04, 0.40812E+04, 0.41515E+04, 0.42224E+04, 0.42939E+04, + 0.43661E+04, 0.44388E+04, 0.45122E+04, 0.45861E+04, 0.46607E+04, 0.47359E+04, 0.48117E+04, + 0.48882E+04, 0.49652E+04, 0.50428E+04, 0.51211E+04, 0.52000E+04, 0.52795E+04, 0.53596E+04, + 0.54404E+04, 0.55217E+04, 0.56037E+04, 0.56863E+04, 0.57695E+04, 0.58533E+04, 0.59378E+04, + 0.60229E+04, 0.61086E+04, 0.61950E+04, 0.62819E+04, 0.63695E+04, 0.64577E+04, 0.65465E+04, + 0.66360E+04, 0.67261E+04, 0.68168E+04, 0.69081E+04, 0.70001E+04, 0.70927E+04, 0.71859E+04]) # --------------- N2 45: M = 22, I = 2 --------------------- not in TIPS-2011 M = 22 @@ -8302,391 +7229,300 @@ def AtoB(aa, A, B, npt): M = 23 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.17143E+03, 0.24209E+03, 0.31285E+03, - 0.38392E+03, 0.45582E+03, 0.52929E+03, 0.60515E+03, 0.68424E+03, - 0.76731E+03, 0.85505E+03, 0.94805E+03, 0.10468E+04, 0.11519E+04, - 0.12637E+04, 0.13826E+04, 0.15090E+04, 0.16435E+04, 0.17863E+04, - 0.19378E+04, 0.20985E+04, 0.22689E+04, 0.24492E+04, 0.26401E+04, - 0.28418E+04, 0.30550E+04, 0.32801E+04, 0.35176E+04, 0.37680E+04, - 0.40318E+04, 0.43097E+04, 0.46021E+04, 0.49097E+04, 0.52330E+04, - 0.55727E+04, 0.59294E+04, 0.63038E+04, 0.66964E+04, 0.71081E+04, - 0.75396E+04, 0.79915E+04, 0.84646E+04, 0.89596E+04, 0.94774E+04, - 0.10019E+05, 0.10585E+05, 0.11176E+05, 0.11793E+05, 0.12437E+05, - 0.13108E+05, 0.13809E+05, 0.14540E+05, 0.15301E+05, 0.16094E+05, - 0.16919E+05, 0.17779E+05, 0.18673E+05, 0.19603E+05, 0.20570E+05, - 0.21575E+05, 0.22619E+05, 0.23704E+05, 0.24831E+05, 0.26000E+05, - 0.27213E+05, 0.28472E+05, 0.29778E+05, 0.31131E+05, 0.32534E+05, - 0.33987E+05, 0.35493E+05, 0.37052E+05, 0.38666E+05, 0.40336E+05, - 0.42064E+05, 0.43852E+05, 0.45701E+05, 0.47612E+05, 0.49587E+05, - 0.51629E+05, 0.53738E+05, 0.55916E+05, 0.58165E+05, 0.60486E+05, - 0.62883E+05, 0.65355E+05, 0.67905E+05, 0.70536E+05, 0.73249E+05, - 0.76045E+05, 0.78927E+05, 0.81897E+05, 0.84957E+05, 0.88108E+05, - 0.91354E+05, 0.94696E+05, 0.98136E+05, 0.10168E+06, 0.10532E+06, - 0.10907E+06, 0.11292E+06, 0.11689E+06, 0.12096E+06, 0.12516E+06, - 0.12946E+06, 0.13389E+06, 0.13844E+06, 0.14311E+06, 0.14791E+06, - 0.15284E+06, 0.15790E+06, 0.16310E+06, 0.16843E+06, 0.17391E+06, - 0.17953E+06, 0.18529E+06, 0.19120E+06, 0.19726E+06, 0.20348E+06, - 0.20986E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.17143E+03, 0.24209E+03, 0.31285E+03, 0.38392E+03, 0.45582E+03, 0.52929E+03, 0.60515E+03, + 0.68424E+03, 0.76731E+03, 0.85505E+03, 0.94805E+03, 0.10468E+04, 0.11519E+04, 0.12637E+04, + 0.13826E+04, 0.15090E+04, 0.16435E+04, 0.17863E+04, 0.19378E+04, 0.20985E+04, 0.22689E+04, + 0.24492E+04, 0.26401E+04, 0.28418E+04, 0.30550E+04, 0.32801E+04, 0.35176E+04, 0.37680E+04, + 0.40318E+04, 0.43097E+04, 0.46021E+04, 0.49097E+04, 0.52330E+04, 0.55727E+04, 0.59294E+04, + 0.63038E+04, 0.66964E+04, 0.71081E+04, 0.75396E+04, 0.79915E+04, 0.84646E+04, 0.89596E+04, + 0.94774E+04, 0.10019E+05, 0.10585E+05, 0.11176E+05, 0.11793E+05, 0.12437E+05, 0.13108E+05, + 0.13809E+05, 0.14540E+05, 0.15301E+05, 0.16094E+05, 0.16919E+05, 0.17779E+05, 0.18673E+05, + 0.19603E+05, 0.20570E+05, 0.21575E+05, 0.22619E+05, 0.23704E+05, 0.24831E+05, 0.26000E+05, + 0.27213E+05, 0.28472E+05, 0.29778E+05, 0.31131E+05, 0.32534E+05, 0.33987E+05, 0.35493E+05, + 0.37052E+05, 0.38666E+05, 0.40336E+05, 0.42064E+05, 0.43852E+05, 0.45701E+05, 0.47612E+05, + 0.49587E+05, 0.51629E+05, 0.53738E+05, 0.55916E+05, 0.58165E+05, 0.60486E+05, 0.62883E+05, + 0.65355E+05, 0.67905E+05, 0.70536E+05, 0.73249E+05, 0.76045E+05, 0.78927E+05, 0.81897E+05, + 0.84957E+05, 0.88108E+05, 0.91354E+05, 0.94696E+05, 0.98136E+05, 0.10168E+06, 0.10532E+06, + 0.10907E+06, 0.11292E+06, 0.11689E+06, 0.12096E+06, 0.12516E+06, 0.12946E+06, 0.13389E+06, + 0.13844E+06, 0.14311E+06, 0.14791E+06, 0.15284E+06, 0.15790E+06, 0.16310E+06, 0.16843E+06, + 0.17391E+06, 0.17953E+06, 0.18529E+06, 0.19120E+06, 0.19726E+06, 0.20348E+06, 0.20986E+06]) # --------------- HCN 134: M = 23, I = 2 --------------------- M = 23 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(12.) -TIPS_ISO_HASH[(M, I)] = float32([0.35186E+03, 0.49693E+03, 0.64221E+03, - 0.78815E+03, 0.93585E+03, 0.10868E+04, 0.12428E+04, 0.14056E+04, - 0.15766E+04, 0.17574E+04, 0.19491E+04, 0.21528E+04, 0.23695E+04, - 0.26002E+04, 0.28457E+04, 0.31068E+04, 0.33845E+04, 0.36795E+04, - 0.39926E+04, 0.43249E+04, 0.46770E+04, 0.50500E+04, 0.54447E+04, - 0.58621E+04, 0.63032E+04, 0.67690E+04, 0.72606E+04, 0.77789E+04, - 0.83252E+04, 0.89005E+04, 0.95062E+04, 0.10143E+05, 0.10813E+05, - 0.11517E+05, 0.12256E+05, 0.13032E+05, 0.13846E+05, 0.14699E+05, - 0.15593E+05, 0.16530E+05, 0.17511E+05, 0.18538E+05, 0.19612E+05, - 0.20734E+05, 0.21908E+05, 0.23134E+05, 0.24414E+05, 0.25750E+05, - 0.27145E+05, 0.28599E+05, 0.30115E+05, 0.31694E+05, 0.33340E+05, - 0.35054E+05, 0.36838E+05, 0.38694E+05, 0.40625E+05, 0.42633E+05, - 0.44720E+05, 0.46889E+05, 0.49142E+05, 0.51481E+05, 0.53910E+05, - 0.56430E+05, 0.59045E+05, 0.61757E+05, 0.64568E+05, 0.67482E+05, - 0.70502E+05, 0.73630E+05, 0.76869E+05, 0.80223E+05, 0.83694E+05, - 0.87285E+05, 0.91000E+05, 0.94843E+05, 0.98815E+05, 0.10292E+06, - 0.10716E+06, 0.11155E+06, 0.11608E+06, 0.12075E+06, 0.12558E+06, - 0.13056E+06, 0.13570E+06, 0.14100E+06, 0.14647E+06, 0.15211E+06, - 0.15793E+06, 0.16392E+06, 0.17009E+06, 0.17646E+06, 0.18301E+06, - 0.18976E+06, 0.19671E+06, 0.20387E+06, 0.21123E+06, 0.21881E+06, - 0.22660E+06, 0.23462E+06, 0.24287E+06, 0.25135E+06, 0.26007E+06, - 0.26903E+06, 0.27824E+06, 0.28771E+06, 0.29743E+06, 0.30742E+06, - 0.31767E+06, 0.32820E+06, 0.33901E+06, 0.35011E+06, 0.36150E+06, - 0.37319E+06, 0.38518E+06, 0.39749E+06, 0.41010E+06, 0.42304E+06, - 0.43631E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.35186E+03, 0.49693E+03, 0.64221E+03, 0.78815E+03, 0.93585E+03, 0.10868E+04, 0.12428E+04, + 0.14056E+04, 0.15766E+04, 0.17574E+04, 0.19491E+04, 0.21528E+04, 0.23695E+04, 0.26002E+04, + 0.28457E+04, 0.31068E+04, 0.33845E+04, 0.36795E+04, 0.39926E+04, 0.43249E+04, 0.46770E+04, + 0.50500E+04, 0.54447E+04, 0.58621E+04, 0.63032E+04, 0.67690E+04, 0.72606E+04, 0.77789E+04, + 0.83252E+04, 0.89005E+04, 0.95062E+04, 0.10143E+05, 0.10813E+05, 0.11517E+05, 0.12256E+05, + 0.13032E+05, 0.13846E+05, 0.14699E+05, 0.15593E+05, 0.16530E+05, 0.17511E+05, 0.18538E+05, + 0.19612E+05, 0.20734E+05, 0.21908E+05, 0.23134E+05, 0.24414E+05, 0.25750E+05, 0.27145E+05, + 0.28599E+05, 0.30115E+05, 0.31694E+05, 0.33340E+05, 0.35054E+05, 0.36838E+05, 0.38694E+05, + 0.40625E+05, 0.42633E+05, 0.44720E+05, 0.46889E+05, 0.49142E+05, 0.51481E+05, 0.53910E+05, + 0.56430E+05, 0.59045E+05, 0.61757E+05, 0.64568E+05, 0.67482E+05, 0.70502E+05, 0.73630E+05, + 0.76869E+05, 0.80223E+05, 0.83694E+05, 0.87285E+05, 0.91000E+05, 0.94843E+05, 0.98815E+05, + 0.10292E+06, 0.10716E+06, 0.11155E+06, 0.11608E+06, 0.12075E+06, 0.12558E+06, 0.13056E+06, + 0.13570E+06, 0.14100E+06, 0.14647E+06, 0.15211E+06, 0.15793E+06, 0.16392E+06, 0.17009E+06, + 0.17646E+06, 0.18301E+06, 0.18976E+06, 0.19671E+06, 0.20387E+06, 0.21123E+06, 0.21881E+06, + 0.22660E+06, 0.23462E+06, 0.24287E+06, 0.25135E+06, 0.26007E+06, 0.26903E+06, 0.27824E+06, + 0.28771E+06, 0.29743E+06, 0.30742E+06, 0.31767E+06, 0.32820E+06, 0.33901E+06, 0.35011E+06, + 0.36150E+06, 0.37319E+06, 0.38518E+06, 0.39749E+06, 0.41010E+06, 0.42304E+06, 0.43631E+06]) # --------------- HCN 135: M = 23, I = 3 --------------------- M = 23 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(4.) -TIPS_ISO_HASH[(M, I)] = float32([0.11863E+03, 0.16755E+03, 0.21653E+03, - 0.26576E+03, 0.31559E+03, 0.36656E+03, 0.41926E+03, 0.47428E+03, - 0.53214E+03, 0.59333E+03, 0.65824E+03, 0.72727E+03, 0.80074E+03, - 0.87898E+03, 0.96227E+03, 0.10509E+04, 0.11452E+04, 0.12454E+04, - 0.13518E+04, 0.14647E+04, 0.15844E+04, 0.17112E+04, 0.18455E+04, - 0.19875E+04, 0.21377E+04, 0.22962E+04, 0.24636E+04, 0.26402E+04, - 0.28263E+04, 0.30224E+04, 0.32289E+04, 0.34461E+04, 0.36745E+04, - 0.39145E+04, 0.41667E+04, 0.44314E+04, 0.47092E+04, 0.50005E+04, - 0.53059E+04, 0.56259E+04, 0.59609E+04, 0.63116E+04, 0.66785E+04, - 0.70622E+04, 0.74633E+04, 0.78823E+04, 0.83200E+04, 0.87769E+04, - 0.92536E+04, 0.97509E+04, 0.10269E+05, 0.10810E+05, 0.11373E+05, - 0.11959E+05, 0.12570E+05, 0.13205E+05, 0.13866E+05, 0.14554E+05, - 0.15268E+05, 0.16011E+05, 0.16782E+05, 0.17583E+05, 0.18415E+05, - 0.19279E+05, 0.20174E+05, 0.21103E+05, 0.22067E+05, 0.23065E+05, - 0.24100E+05, 0.25172E+05, 0.26282E+05, 0.27432E+05, 0.28622E+05, - 0.29853E+05, 0.31127E+05, 0.32445E+05, 0.33807E+05, 0.35215E+05, - 0.36670E+05, 0.38174E+05, 0.39727E+05, 0.41330E+05, 0.42986E+05, - 0.44695E+05, 0.46459E+05, 0.48278E+05, 0.50155E+05, 0.52091E+05, - 0.54086E+05, 0.56143E+05, 0.58263E+05, 0.60447E+05, 0.62696E+05, - 0.65013E+05, 0.67399E+05, 0.69856E+05, 0.72384E+05, 0.74986E+05, - 0.77663E+05, 0.80416E+05, 0.83249E+05, 0.86161E+05, 0.89156E+05, - 0.92233E+05, 0.95397E+05, 0.98648E+05, 0.10199E+06, 0.10542E+06, - 0.10894E+06, 0.11256E+06, 0.11627E+06, 0.12009E+06, 0.12400E+06, - 0.12802E+06, 0.13214E+06, 0.13636E+06, 0.14070E+06, 0.14515E+06, - 0.14971E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.11863E+03, 0.16755E+03, 0.21653E+03, 0.26576E+03, 0.31559E+03, 0.36656E+03, 0.41926E+03, + 0.47428E+03, 0.53214E+03, 0.59333E+03, 0.65824E+03, 0.72727E+03, 0.80074E+03, 0.87898E+03, + 0.96227E+03, 0.10509E+04, 0.11452E+04, 0.12454E+04, 0.13518E+04, 0.14647E+04, 0.15844E+04, + 0.17112E+04, 0.18455E+04, 0.19875E+04, 0.21377E+04, 0.22962E+04, 0.24636E+04, 0.26402E+04, + 0.28263E+04, 0.30224E+04, 0.32289E+04, 0.34461E+04, 0.36745E+04, 0.39145E+04, 0.41667E+04, + 0.44314E+04, 0.47092E+04, 0.50005E+04, 0.53059E+04, 0.56259E+04, 0.59609E+04, 0.63116E+04, + 0.66785E+04, 0.70622E+04, 0.74633E+04, 0.78823E+04, 0.83200E+04, 0.87769E+04, 0.92536E+04, + 0.97509E+04, 0.10269E+05, 0.10810E+05, 0.11373E+05, 0.11959E+05, 0.12570E+05, 0.13205E+05, + 0.13866E+05, 0.14554E+05, 0.15268E+05, 0.16011E+05, 0.16782E+05, 0.17583E+05, 0.18415E+05, + 0.19279E+05, 0.20174E+05, 0.21103E+05, 0.22067E+05, 0.23065E+05, 0.24100E+05, 0.25172E+05, + 0.26282E+05, 0.27432E+05, 0.28622E+05, 0.29853E+05, 0.31127E+05, 0.32445E+05, 0.33807E+05, + 0.35215E+05, 0.36670E+05, 0.38174E+05, 0.39727E+05, 0.41330E+05, 0.42986E+05, 0.44695E+05, + 0.46459E+05, 0.48278E+05, 0.50155E+05, 0.52091E+05, 0.54086E+05, 0.56143E+05, 0.58263E+05, + 0.60447E+05, 0.62696E+05, 0.65013E+05, 0.67399E+05, 0.69856E+05, 0.72384E+05, 0.74986E+05, + 0.77663E+05, 0.80416E+05, 0.83249E+05, 0.86161E+05, 0.89156E+05, 0.92233E+05, 0.95397E+05, + 0.98648E+05, 0.10199E+06, 0.10542E+06, 0.10894E+06, 0.11256E+06, 0.11627E+06, 0.12009E+06, + 0.12400E+06, 0.12802E+06, 0.13214E+06, 0.13636E+06, 0.14070E+06, 0.14515E+06, 0.14971E+06]) # --------------- CH3Cl 215: M = 24, I = 1 --------------------- M = 24 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(4.) -TIPS_ISO_HASH[(M, I)] = float32([0.50529E+04, 0.85123E+04, 0.12528E+05, - 0.17036E+05, 0.22005E+05, 0.27429E+05, 0.33325E+05, 0.39734E+05, - 0.46713E+05, 0.54336E+05, 0.62690E+05, 0.71876E+05, 0.82006E+05, - 0.93204E+05, 0.10560E+06, 0.11936E+06, 0.13463E+06, 0.15158E+06, - 0.17043E+06, 0.19137E+06, 0.21464E+06, 0.24049E+06, 0.26920E+06, - 0.30107E+06, 0.33642E+06, 0.37563E+06, 0.41907E+06, 0.46719E+06, - 0.52045E+06, 0.57936E+06, 0.64448E+06, 0.71641E+06, 0.79582E+06, - 0.88341E+06, 0.97997E+06, 0.10863E+07, 0.12034E+07, 0.13323E+07, - 0.14739E+07, 0.16295E+07, 0.18003E+07, 0.19877E+07, 0.21932E+07, - 0.24183E+07, 0.26649E+07, 0.29346E+07, 0.32296E+07, 0.35519E+07, - 0.39039E+07, 0.42881E+07, 0.47072E+07, 0.51639E+07, 0.56615E+07, - 0.62032E+07, 0.67926E+07, 0.74335E+07, 0.81299E+07, 0.88862E+07, - 0.97071E+07, 0.10598E+08, 0.11563E+08, 0.12609E+08, 0.13742E+08, - 0.14968E+08, 0.16294E+08, 0.17728E+08, 0.19277E+08, 0.20950E+08, - 0.22756E+08, 0.24704E+08, 0.26805E+08, 0.29069E+08, 0.31507E+08, - 0.34132E+08, 0.36957E+08, 0.39995E+08, 0.43260E+08, 0.46769E+08, - 0.50538E+08, 0.54583E+08, 0.58923E+08, 0.63578E+08, 0.68568E+08, - 0.73914E+08, 0.79640E+08, 0.85770E+08, 0.92329E+08, 0.99345E+08, - 0.10685E+09, 0.11486E+09, 0.12342E+09, 0.13257E+09, 0.14233E+09, - 0.15274E+09, 0.16384E+09, 0.17568E+09, 0.18829E+09, 0.20173E+09, - 0.21604E+09, 0.23127E+09, 0.24748E+09, 0.26471E+09, 0.28304E+09, - 0.30252E+09, 0.32322E+09, 0.34520E+09, 0.36853E+09, 0.39330E+09, - 0.41958E+09, 0.44745E+09, 0.47701E+09, 0.50833E+09, 0.54151E+09, - 0.57667E+09, 0.61389E+09, 0.65329E+09, 0.69498E+09, 0.73909E+09, - 0.78573E+09]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.50529E+04, 0.85123E+04, 0.12528E+05, 0.17036E+05, 0.22005E+05, 0.27429E+05, 0.33325E+05, + 0.39734E+05, 0.46713E+05, 0.54336E+05, 0.62690E+05, 0.71876E+05, 0.82006E+05, 0.93204E+05, + 0.10560E+06, 0.11936E+06, 0.13463E+06, 0.15158E+06, 0.17043E+06, 0.19137E+06, 0.21464E+06, + 0.24049E+06, 0.26920E+06, 0.30107E+06, 0.33642E+06, 0.37563E+06, 0.41907E+06, 0.46719E+06, + 0.52045E+06, 0.57936E+06, 0.64448E+06, 0.71641E+06, 0.79582E+06, 0.88341E+06, 0.97997E+06, + 0.10863E+07, 0.12034E+07, 0.13323E+07, 0.14739E+07, 0.16295E+07, 0.18003E+07, 0.19877E+07, + 0.21932E+07, 0.24183E+07, 0.26649E+07, 0.29346E+07, 0.32296E+07, 0.35519E+07, 0.39039E+07, + 0.42881E+07, 0.47072E+07, 0.51639E+07, 0.56615E+07, 0.62032E+07, 0.67926E+07, 0.74335E+07, + 0.81299E+07, 0.88862E+07, 0.97071E+07, 0.10598E+08, 0.11563E+08, 0.12609E+08, 0.13742E+08, + 0.14968E+08, 0.16294E+08, 0.17728E+08, 0.19277E+08, 0.20950E+08, 0.22756E+08, 0.24704E+08, + 0.26805E+08, 0.29069E+08, 0.31507E+08, 0.34132E+08, 0.36957E+08, 0.39995E+08, 0.43260E+08, + 0.46769E+08, 0.50538E+08, 0.54583E+08, 0.58923E+08, 0.63578E+08, 0.68568E+08, 0.73914E+08, + 0.79640E+08, 0.85770E+08, 0.92329E+08, 0.99345E+08, 0.10685E+09, 0.11486E+09, 0.12342E+09, + 0.13257E+09, 0.14233E+09, 0.15274E+09, 0.16384E+09, 0.17568E+09, 0.18829E+09, 0.20173E+09, + 0.21604E+09, 0.23127E+09, 0.24748E+09, 0.26471E+09, 0.28304E+09, 0.30252E+09, 0.32322E+09, + 0.34520E+09, 0.36853E+09, 0.39330E+09, 0.41958E+09, 0.44745E+09, 0.47701E+09, 0.50833E+09, + 0.54151E+09, 0.57667E+09, 0.61389E+09, 0.65329E+09, 0.69498E+09, 0.73909E+09, 0.78573E+09]) # --------------- CH3Cl 217: M = 24, I = 2 --------------------- M = 24 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(4.) -TIPS_ISO_HASH[(M, I)] = float32([0.51327E+04, 0.86469E+04, 0.12726E+05, - 0.17306E+05, 0.22354E+05, 0.27863E+05, 0.33853E+05, 0.40364E+05, - 0.47453E+05, 0.55197E+05, 0.63684E+05, 0.73016E+05, 0.83306E+05, - 0.94681E+05, 0.10728E+06, 0.12125E+06, 0.13676E+06, 0.15399E+06, - 0.17313E+06, 0.19441E+06, 0.21804E+06, 0.24430E+06, 0.27347E+06, - 0.30584E+06, 0.34176E+06, 0.38158E+06, 0.42572E+06, 0.47460E+06, - 0.52871E+06, 0.58855E+06, 0.65471E+06, 0.72778E+06, 0.80844E+06, - 0.89743E+06, 0.99552E+06, 0.11036E+07, 0.12225E+07, 0.13534E+07, - 0.14973E+07, 0.16553E+07, 0.18289E+07, 0.20193E+07, 0.22280E+07, - 0.24567E+07, 0.27072E+07, 0.29812E+07, 0.32808E+07, 0.36083E+07, - 0.39659E+07, 0.43562E+07, 0.47819E+07, 0.52459E+07, 0.57514E+07, - 0.63017E+07, 0.69005E+07, 0.75515E+07, 0.82590E+07, 0.90273E+07, - 0.98613E+07, 0.10766E+08, 0.11747E+08, 0.12809E+08, 0.13960E+08, - 0.15206E+08, 0.16553E+08, 0.18010E+08, 0.19584E+08, 0.21283E+08, - 0.23118E+08, 0.25097E+08, 0.27231E+08, 0.29531E+08, 0.32008E+08, - 0.34674E+08, 0.37544E+08, 0.40630E+08, 0.43948E+08, 0.47513E+08, - 0.51341E+08, 0.55451E+08, 0.59860E+08, 0.64589E+08, 0.69658E+08, - 0.75089E+08, 0.80906E+08, 0.87134E+08, 0.93797E+08, 0.10092E+09, - 0.10854E+09, 0.11669E+09, 0.12539E+09, 0.13467E+09, 0.14459E+09, - 0.15517E+09, 0.16645E+09, 0.17847E+09, 0.19129E+09, 0.20494E+09, - 0.21948E+09, 0.23495E+09, 0.25141E+09, 0.26893E+09, 0.28754E+09, - 0.30733E+09, 0.32836E+09, 0.35069E+09, 0.37440E+09, 0.39956E+09, - 0.42626E+09, 0.45457E+09, 0.48460E+09, 0.51642E+09, 0.55013E+09, - 0.58585E+09, 0.62366E+09, 0.66369E+09, 0.70605E+09, 0.75085E+09, - 0.79824E+09]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.51327E+04, 0.86469E+04, 0.12726E+05, 0.17306E+05, 0.22354E+05, 0.27863E+05, 0.33853E+05, + 0.40364E+05, 0.47453E+05, 0.55197E+05, 0.63684E+05, 0.73016E+05, 0.83306E+05, 0.94681E+05, + 0.10728E+06, 0.12125E+06, 0.13676E+06, 0.15399E+06, 0.17313E+06, 0.19441E+06, 0.21804E+06, + 0.24430E+06, 0.27347E+06, 0.30584E+06, 0.34176E+06, 0.38158E+06, 0.42572E+06, 0.47460E+06, + 0.52871E+06, 0.58855E+06, 0.65471E+06, 0.72778E+06, 0.80844E+06, 0.89743E+06, 0.99552E+06, + 0.11036E+07, 0.12225E+07, 0.13534E+07, 0.14973E+07, 0.16553E+07, 0.18289E+07, 0.20193E+07, + 0.22280E+07, 0.24567E+07, 0.27072E+07, 0.29812E+07, 0.32808E+07, 0.36083E+07, 0.39659E+07, + 0.43562E+07, 0.47819E+07, 0.52459E+07, 0.57514E+07, 0.63017E+07, 0.69005E+07, 0.75515E+07, + 0.82590E+07, 0.90273E+07, 0.98613E+07, 0.10766E+08, 0.11747E+08, 0.12809E+08, 0.13960E+08, + 0.15206E+08, 0.16553E+08, 0.18010E+08, 0.19584E+08, 0.21283E+08, 0.23118E+08, 0.25097E+08, + 0.27231E+08, 0.29531E+08, 0.32008E+08, 0.34674E+08, 0.37544E+08, 0.40630E+08, 0.43948E+08, + 0.47513E+08, 0.51341E+08, 0.55451E+08, 0.59860E+08, 0.64589E+08, 0.69658E+08, 0.75089E+08, + 0.80906E+08, 0.87134E+08, 0.93797E+08, 0.10092E+09, 0.10854E+09, 0.11669E+09, 0.12539E+09, + 0.13467E+09, 0.14459E+09, 0.15517E+09, 0.16645E+09, 0.17847E+09, 0.19129E+09, 0.20494E+09, + 0.21948E+09, 0.23495E+09, 0.25141E+09, 0.26893E+09, 0.28754E+09, 0.30733E+09, 0.32836E+09, + 0.35069E+09, 0.37440E+09, 0.39956E+09, 0.42626E+09, 0.45457E+09, 0.48460E+09, 0.51642E+09, + 0.55013E+09, 0.58585E+09, 0.62366E+09, 0.66369E+09, 0.70605E+09, 0.75085E+09, 0.79824E+09]) # --------------- H2O2 1661: M = 25, I = 1 --------------------- M = 25 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.62392E+03, 0.10958E+04, 0.16692E+04, - 0.23492E+04, 0.31427E+04, 0.40574E+04, 0.51014E+04, 0.62840E+04, - 0.76157E+04, 0.91085E+04, 0.10776E+05, 0.12633E+05, 0.14696E+05, - 0.16983E+05, 0.19515E+05, 0.22312E+05, 0.25396E+05, 0.28792E+05, - 0.32526E+05, 0.36625E+05, 0.41118E+05, 0.46036E+05, 0.51410E+05, - 0.57275E+05, 0.63667E+05, 0.70623E+05, 0.78185E+05, 0.86394E+05, - 0.95295E+05, 0.10493E+06, 0.11536E+06, 0.12662E+06, 0.13878E+06, - 0.15188E+06, 0.16600E+06, 0.18118E+06, 0.19750E+06, 0.21503E+06, - 0.23383E+06, 0.25398E+06, 0.27556E+06, 0.29864E+06, 0.32333E+06, - 0.34970E+06, 0.37784E+06, 0.40786E+06, 0.43985E+06, 0.47392E+06, - 0.51018E+06, 0.54874E+06, 0.58972E+06, 0.63324E+06, 0.67943E+06, - 0.72843E+06, 0.78037E+06, 0.83540E+06, 0.89366E+06, 0.95530E+06, - 0.10205E+07, 0.10894E+07, 0.11622E+07, 0.12391E+07, 0.13202E+07, - 0.14057E+07, 0.14959E+07, 0.15909E+07, 0.16910E+07, 0.17963E+07, - 0.19072E+07, 0.20237E+07, 0.21463E+07, 0.22750E+07, 0.24102E+07, - 0.25522E+07, 0.27012E+07, 0.28575E+07, 0.30213E+07, 0.31931E+07, - 0.33730E+07, 0.35615E+07, 0.37588E+07, 0.39653E+07, 0.41813E+07, - 0.44072E+07, 0.46433E+07, 0.48901E+07, 0.51479E+07, 0.54171E+07, - 0.56982E+07, 0.59915E+07, 0.62976E+07, 0.66167E+07, 0.69495E+07, - 0.72963E+07, 0.76577E+07, 0.80342E+07, 0.84262E+07, 0.88343E+07, - 0.92591E+07, 0.97011E+07, 0.10161E+08, 0.10639E+08, 0.11136E+08, - 0.11652E+08, 0.12189E+08, 0.12746E+08, 0.13325E+08, 0.13926E+08, - 0.14550E+08, 0.15198E+08, 0.15870E+08, 0.16566E+08, 0.17289E+08, - 0.18038E+08, 0.18814E+08, 0.19619E+08, 0.20452E+08, 0.21315E+08, - 0.22209E+08]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.62392E+03, 0.10958E+04, 0.16692E+04, 0.23492E+04, 0.31427E+04, 0.40574E+04, 0.51014E+04, + 0.62840E+04, 0.76157E+04, 0.91085E+04, 0.10776E+05, 0.12633E+05, 0.14696E+05, 0.16983E+05, + 0.19515E+05, 0.22312E+05, 0.25396E+05, 0.28792E+05, 0.32526E+05, 0.36625E+05, 0.41118E+05, + 0.46036E+05, 0.51410E+05, 0.57275E+05, 0.63667E+05, 0.70623E+05, 0.78185E+05, 0.86394E+05, + 0.95295E+05, 0.10493E+06, 0.11536E+06, 0.12662E+06, 0.13878E+06, 0.15188E+06, 0.16600E+06, + 0.18118E+06, 0.19750E+06, 0.21503E+06, 0.23383E+06, 0.25398E+06, 0.27556E+06, 0.29864E+06, + 0.32333E+06, 0.34970E+06, 0.37784E+06, 0.40786E+06, 0.43985E+06, 0.47392E+06, 0.51018E+06, + 0.54874E+06, 0.58972E+06, 0.63324E+06, 0.67943E+06, 0.72843E+06, 0.78037E+06, 0.83540E+06, + 0.89366E+06, 0.95530E+06, 0.10205E+07, 0.10894E+07, 0.11622E+07, 0.12391E+07, 0.13202E+07, + 0.14057E+07, 0.14959E+07, 0.15909E+07, 0.16910E+07, 0.17963E+07, 0.19072E+07, 0.20237E+07, + 0.21463E+07, 0.22750E+07, 0.24102E+07, 0.25522E+07, 0.27012E+07, 0.28575E+07, 0.30213E+07, + 0.31931E+07, 0.33730E+07, 0.35615E+07, 0.37588E+07, 0.39653E+07, 0.41813E+07, 0.44072E+07, + 0.46433E+07, 0.48901E+07, 0.51479E+07, 0.54171E+07, 0.56982E+07, 0.59915E+07, 0.62976E+07, + 0.66167E+07, 0.69495E+07, 0.72963E+07, 0.76577E+07, 0.80342E+07, 0.84262E+07, 0.88343E+07, + 0.92591E+07, 0.97011E+07, 0.10161E+08, 0.10639E+08, 0.11136E+08, 0.11652E+08, 0.12189E+08, + 0.12746E+08, 0.13325E+08, 0.13926E+08, 0.14550E+08, 0.15198E+08, 0.15870E+08, 0.16566E+08, + 0.17289E+08, 0.18038E+08, 0.18814E+08, 0.19619E+08, 0.20452E+08, 0.21315E+08, 0.22209E+08]) # --------------- C2H2 1221: M = 26, I = 1 --------------------- M = 26 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.71617E+02, 0.10121E+03, 0.13092E+03, - 0.16104E+03, 0.19218E+03, 0.22509E+03, 0.26062E+03, 0.29959E+03, - 0.34281E+03, 0.39103E+03, 0.44503E+03, 0.50558E+03, 0.57346E+03, - 0.64950E+03, 0.73457E+03, 0.82960E+03, 0.93557E+03, 0.10535E+04, - 0.11846E+04, 0.13301E+04, 0.14911E+04, 0.16692E+04, 0.18658E+04, - 0.20825E+04, 0.23211E+04, 0.25833E+04, 0.28711E+04, 0.31867E+04, - 0.35323E+04, 0.39102E+04, 0.43230E+04, 0.47735E+04, 0.52645E+04, - 0.57991E+04, 0.63807E+04, 0.70127E+04, 0.76988E+04, 0.84430E+04, - 0.92495E+04, 0.10123E+05, 0.11067E+05, 0.12088E+05, 0.13191E+05, - 0.14381E+05, 0.15664E+05, 0.17047E+05, 0.18536E+05, 0.20137E+05, - 0.21859E+05, 0.23710E+05, 0.25696E+05, 0.27827E+05, 0.30112E+05, - 0.32561E+05, 0.35183E+05, 0.37990E+05, 0.40991E+05, 0.44199E+05, - 0.47626E+05, 0.51285E+05, 0.55189E+05, 0.59353E+05, 0.63791E+05, - 0.68518E+05, 0.73551E+05, 0.78908E+05, 0.84604E+05, 0.90661E+05, - 0.97095E+05, 0.10393E+06, 0.11118E+06, 0.11888E+06, 0.12704E+06, - 0.13569E+06, 0.14486E+06, 0.15457E+06, 0.16485E+06, 0.17572E+06, - 0.18722E+06, 0.19938E+06, 0.21223E+06, 0.22581E+06, 0.24014E+06, - 0.25527E+06, 0.27123E+06, 0.28807E+06, 0.30582E+06, 0.32452E+06, - 0.34423E+06, 0.36498E+06, 0.38683E+06, 0.40982E+06, 0.43401E+06, - 0.45944E+06, 0.48618E+06, 0.51428E+06, 0.54380E+06, 0.57480E+06, - 0.60735E+06, 0.64151E+06, 0.67735E+06, 0.71494E+06, 0.75436E+06, - 0.79568E+06, 0.83898E+06, 0.88434E+06, 0.93184E+06, 0.98158E+06, - 0.10336E+07, 0.10881E+07, 0.11451E+07, 0.12047E+07, 0.12670E+07, - 0.13321E+07, 0.14002E+07, 0.14713E+07, 0.15455E+07, 0.16231E+07, - 0.17040E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.71617E+02, 0.10121E+03, 0.13092E+03, 0.16104E+03, 0.19218E+03, 0.22509E+03, 0.26062E+03, + 0.29959E+03, 0.34281E+03, 0.39103E+03, 0.44503E+03, 0.50558E+03, 0.57346E+03, 0.64950E+03, + 0.73457E+03, 0.82960E+03, 0.93557E+03, 0.10535E+04, 0.11846E+04, 0.13301E+04, 0.14911E+04, + 0.16692E+04, 0.18658E+04, 0.20825E+04, 0.23211E+04, 0.25833E+04, 0.28711E+04, 0.31867E+04, + 0.35323E+04, 0.39102E+04, 0.43230E+04, 0.47735E+04, 0.52645E+04, 0.57991E+04, 0.63807E+04, + 0.70127E+04, 0.76988E+04, 0.84430E+04, 0.92495E+04, 0.10123E+05, 0.11067E+05, 0.12088E+05, + 0.13191E+05, 0.14381E+05, 0.15664E+05, 0.17047E+05, 0.18536E+05, 0.20137E+05, 0.21859E+05, + 0.23710E+05, 0.25696E+05, 0.27827E+05, 0.30112E+05, 0.32561E+05, 0.35183E+05, 0.37990E+05, + 0.40991E+05, 0.44199E+05, 0.47626E+05, 0.51285E+05, 0.55189E+05, 0.59353E+05, 0.63791E+05, + 0.68518E+05, 0.73551E+05, 0.78908E+05, 0.84604E+05, 0.90661E+05, 0.97095E+05, 0.10393E+06, + 0.11118E+06, 0.11888E+06, 0.12704E+06, 0.13569E+06, 0.14486E+06, 0.15457E+06, 0.16485E+06, + 0.17572E+06, 0.18722E+06, 0.19938E+06, 0.21223E+06, 0.22581E+06, 0.24014E+06, 0.25527E+06, + 0.27123E+06, 0.28807E+06, 0.30582E+06, 0.32452E+06, 0.34423E+06, 0.36498E+06, 0.38683E+06, + 0.40982E+06, 0.43401E+06, 0.45944E+06, 0.48618E+06, 0.51428E+06, 0.54380E+06, 0.57480E+06, + 0.60735E+06, 0.64151E+06, 0.67735E+06, 0.71494E+06, 0.75436E+06, 0.79568E+06, 0.83898E+06, + 0.88434E+06, 0.93184E+06, 0.98158E+06, 0.10336E+07, 0.10881E+07, 0.11451E+07, 0.12047E+07, + 0.12670E+07, 0.13321E+07, 0.14002E+07, 0.14713E+07, 0.15455E+07, 0.16231E+07, 0.17040E+07]) # --------------- C2H2 1231: M = 26, I = 2 --------------------- M = 26 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(8.) -TIPS_ISO_HASH[(M, I)] = float32([0.28647E+03, 0.40486E+03, 0.52369E+03, - 0.64419E+03, 0.76874E+03, 0.90040E+03, 0.10425E+04, 0.11984E+04, - 0.13713E+04, 0.15642E+04, 0.17802E+04, 0.20223E+04, 0.22939E+04, - 0.25981E+04, 0.29384E+04, 0.33185E+04, 0.37424E+04, 0.42142E+04, - 0.47386E+04, 0.53203E+04, 0.59646E+04, 0.66769E+04, 0.74633E+04, - 0.83302E+04, 0.92845E+04, 0.10333E+05, 0.11485E+05, 0.12747E+05, - 0.14129E+05, 0.15641E+05, 0.17292E+05, 0.19094E+05, 0.21058E+05, - 0.23197E+05, 0.25523E+05, 0.28051E+05, 0.30796E+05, 0.33773E+05, - 0.36999E+05, 0.40492E+05, 0.44270E+05, 0.48354E+05, 0.52765E+05, - 0.57525E+05, 0.62658E+05, 0.68189E+05, 0.74144E+05, 0.80551E+05, - 0.87439E+05, 0.94840E+05, 0.10279E+06, 0.11131E+06, 0.12045E+06, - 0.13025E+06, 0.14074E+06, 0.15196E+06, 0.16397E+06, 0.17680E+06, - 0.19051E+06, 0.20514E+06, 0.22076E+06, 0.23742E+06, 0.25517E+06, - 0.27408E+06, 0.29421E+06, 0.31564E+06, 0.33842E+06, 0.36265E+06, - 0.38839E+06, 0.41572E+06, 0.44474E+06, 0.47553E+06, 0.50818E+06, - 0.54278E+06, 0.57945E+06, 0.61829E+06, 0.65940E+06, 0.70289E+06, - 0.74890E+06, 0.79754E+06, 0.84894E+06, 0.90324E+06, 0.96057E+06, - 0.10211E+07, 0.10849E+07, 0.11523E+07, 0.12233E+07, 0.12981E+07, - 0.13769E+07, 0.14599E+07, 0.15473E+07, 0.16393E+07, 0.17361E+07, - 0.18378E+07, 0.19447E+07, 0.20571E+07, 0.21752E+07, 0.22992E+07, - 0.24294E+07, 0.25661E+07, 0.27094E+07, 0.28598E+07, 0.30175E+07, - 0.31828E+07, 0.33560E+07, 0.35374E+07, 0.37274E+07, 0.39264E+07, - 0.41346E+07, 0.43525E+07, 0.45805E+07, 0.48188E+07, 0.50681E+07, - 0.53286E+07, 0.56008E+07, 0.58852E+07, 0.61823E+07, 0.64924E+07, - 0.68162E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.28647E+03, 0.40486E+03, 0.52369E+03, 0.64419E+03, 0.76874E+03, 0.90040E+03, 0.10425E+04, + 0.11984E+04, 0.13713E+04, 0.15642E+04, 0.17802E+04, 0.20223E+04, 0.22939E+04, 0.25981E+04, + 0.29384E+04, 0.33185E+04, 0.37424E+04, 0.42142E+04, 0.47386E+04, 0.53203E+04, 0.59646E+04, + 0.66769E+04, 0.74633E+04, 0.83302E+04, 0.92845E+04, 0.10333E+05, 0.11485E+05, 0.12747E+05, + 0.14129E+05, 0.15641E+05, 0.17292E+05, 0.19094E+05, 0.21058E+05, 0.23197E+05, 0.25523E+05, + 0.28051E+05, 0.30796E+05, 0.33773E+05, 0.36999E+05, 0.40492E+05, 0.44270E+05, 0.48354E+05, + 0.52765E+05, 0.57525E+05, 0.62658E+05, 0.68189E+05, 0.74144E+05, 0.80551E+05, 0.87439E+05, + 0.94840E+05, 0.10279E+06, 0.11131E+06, 0.12045E+06, 0.13025E+06, 0.14074E+06, 0.15196E+06, + 0.16397E+06, 0.17680E+06, 0.19051E+06, 0.20514E+06, 0.22076E+06, 0.23742E+06, 0.25517E+06, + 0.27408E+06, 0.29421E+06, 0.31564E+06, 0.33842E+06, 0.36265E+06, 0.38839E+06, 0.41572E+06, + 0.44474E+06, 0.47553E+06, 0.50818E+06, 0.54278E+06, 0.57945E+06, 0.61829E+06, 0.65940E+06, + 0.70289E+06, 0.74890E+06, 0.79754E+06, 0.84894E+06, 0.90324E+06, 0.96057E+06, 0.10211E+07, + 0.10849E+07, 0.11523E+07, 0.12233E+07, 0.12981E+07, 0.13769E+07, 0.14599E+07, 0.15473E+07, + 0.16393E+07, 0.17361E+07, 0.18378E+07, 0.19447E+07, 0.20571E+07, 0.21752E+07, 0.22992E+07, + 0.24294E+07, 0.25661E+07, 0.27094E+07, 0.28598E+07, 0.30175E+07, 0.31828E+07, 0.33560E+07, + 0.35374E+07, 0.37274E+07, 0.39264E+07, 0.41346E+07, 0.43525E+07, 0.45805E+07, 0.48188E+07, + 0.50681E+07, 0.53286E+07, 0.56008E+07, 0.58852E+07, 0.61823E+07, 0.64924E+07, 0.68162E+07]) # --------------- C2H2 1222: M = 26, I = 3 --------------------- M = 26 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.24843E+03, 0.35373E+03, 0.45997E+03, - 0.56930E+03, 0.68497E+03, 0.81065E+03, 0.94999E+03, 0.11065E+04, - 0.12837E+04, 0.14848E+04, 0.17135E+04, 0.19731E+04, 0.22675E+04, - 0.26205E+04, 0.29999E+04, 0.34276E+04, 0.39086E+04, 0.44486E+04, - 0.50533E+04, 0.57294E+04, 0.64837E+04, 0.73237E+04, 0.82576E+04, - 0.92941E+04, 0.10443E+05, 0.11714E+05, 0.13117E+05, 0.14666E+05, - 0.16373E+05, 0.18250E+05, 0.20313E+05, 0.22578E+05, 0.25060E+05, - 0.27777E+05, 0.30750E+05, 0.33997E+05, 0.37541E+05, 0.41405E+05, - 0.45614E+05, 0.50192E+05, 0.55170E+05, 0.60576E+05, 0.66441E+05, - 0.72799E+05, 0.79686E+05, 0.87140E+05, 0.95199E+05, 0.10391E+06, - 0.11331E+06, 0.12345E+06, 0.13438E+06, 0.14615E+06, 0.15882E+06, - 0.17245E+06, 0.18710E+06, 0.20283E+06, 0.21972E+06, 0.23783E+06, - 0.25724E+06, 0.27804E+06, 0.30030E+06, 0.32411E+06, 0.34958E+06, - 0.37679E+06, 0.40585E+06, 0.43686E+06, 0.46994E+06, 0.50521E+06, - 0.54280E+06, 0.58282E+06, 0.62542E+06, 0.67074E+06, 0.71892E+06, - 0.77013E+06, 0.82453E+06, 0.88228E+06, 0.94356E+06, 0.10086E+07, - 0.10775E+07, 0.11505E+07, 0.12279E+07, 0.13098E+07, 0.13964E+07, - 0.14881E+07, 0.15850E+07, 0.16875E+07, 0.17957E+07, 0.19100E+07, - 0.20307E+07, 0.21580E+07, 0.22923E+07, 0.24339E+07, 0.25831E+07, - 0.27404E+07, 0.29060E+07, 0.30803E+07, 0.32638E+07, 0.34568E+07, - 0.36598E+07, 0.38733E+07, 0.40976E+07, 0.43332E+07, 0.45807E+07, - 0.48406E+07, 0.51133E+07, 0.53995E+07, 0.56997E+07, 0.60144E+07, - 0.63444E+07, 0.66901E+07, 0.70524E+07, 0.74317E+07, 0.78289E+07, - 0.82447E+07, 0.86797E+07, 0.91348E+07, 0.96108E+07, 0.10108E+08, - 0.10629E+08]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.24843E+03, 0.35373E+03, 0.45997E+03, 0.56930E+03, 0.68497E+03, 0.81065E+03, 0.94999E+03, + 0.11065E+04, 0.12837E+04, 0.14848E+04, 0.17135E+04, 0.19731E+04, 0.22675E+04, 0.26205E+04, + 0.29999E+04, 0.34276E+04, 0.39086E+04, 0.44486E+04, 0.50533E+04, 0.57294E+04, 0.64837E+04, + 0.73237E+04, 0.82576E+04, 0.92941E+04, 0.10443E+05, 0.11714E+05, 0.13117E+05, 0.14666E+05, + 0.16373E+05, 0.18250E+05, 0.20313E+05, 0.22578E+05, 0.25060E+05, 0.27777E+05, 0.30750E+05, + 0.33997E+05, 0.37541E+05, 0.41405E+05, 0.45614E+05, 0.50192E+05, 0.55170E+05, 0.60576E+05, + 0.66441E+05, 0.72799E+05, 0.79686E+05, 0.87140E+05, 0.95199E+05, 0.10391E+06, 0.11331E+06, + 0.12345E+06, 0.13438E+06, 0.14615E+06, 0.15882E+06, 0.17245E+06, 0.18710E+06, 0.20283E+06, + 0.21972E+06, 0.23783E+06, 0.25724E+06, 0.27804E+06, 0.30030E+06, 0.32411E+06, 0.34958E+06, + 0.37679E+06, 0.40585E+06, 0.43686E+06, 0.46994E+06, 0.50521E+06, 0.54280E+06, 0.58282E+06, + 0.62542E+06, 0.67074E+06, 0.71892E+06, 0.77013E+06, 0.82453E+06, 0.88228E+06, 0.94356E+06, + 0.10086E+07, 0.10775E+07, 0.11505E+07, 0.12279E+07, 0.13098E+07, 0.13964E+07, 0.14881E+07, + 0.15850E+07, 0.16875E+07, 0.17957E+07, 0.19100E+07, 0.20307E+07, 0.21580E+07, 0.22923E+07, + 0.24339E+07, 0.25831E+07, 0.27404E+07, 0.29060E+07, 0.30803E+07, 0.32638E+07, 0.34568E+07, + 0.36598E+07, 0.38733E+07, 0.40976E+07, 0.43332E+07, 0.45807E+07, 0.48406E+07, 0.51133E+07, + 0.53995E+07, 0.56997E+07, 0.60144E+07, 0.63444E+07, 0.66901E+07, 0.70524E+07, 0.74317E+07, + 0.78289E+07, 0.82447E+07, 0.86797E+07, 0.91348E+07, 0.96108E+07, 0.10108E+08, 0.10629E+08]) # --------------- C2H6 1221: M = 27, I = 1 --------------------- M = 27 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.47267E+04, 0.80011E+04, 0.11928E+05, - 0.16564E+05, 0.21985E+05, 0.28287E+05, 0.35590E+05, 0.44049E+05, - 0.53862E+05, 0.65277E+05, 0.78597E+05, 0.94191E+05, 0.11250E+06, - 0.13407E+06, 0.15952E+06, 0.18962E+06, 0.22526E+06, 0.26751E+06, - 0.31763E+06, 0.37714E+06, 0.44780E+06, 0.53174E+06, 0.63145E+06, - 0.74989E+06, 0.89056E+06, 0.10576E+07, 0.12559E+07, 0.14912E+07, - 0.17704E+07, 0.21013E+07, 0.24936E+07, 0.29582E+07, 0.35083E+07, - 0.41591E+07, 0.49286E+07, 0.58379E+07, 0.69116E+07, 0.81787E+07, - 0.96728E+07, 0.11433E+08, 0.13506E+08, 0.15945E+08, 0.18812E+08, - 0.22180E+08, 0.26134E+08, 0.30770E+08, 0.36204E+08, 0.42565E+08, - 0.50008E+08, 0.58708E+08, 0.68868E+08, 0.80725E+08, 0.94548E+08, - 0.11065E+09, 0.12940E+09, 0.15119E+09, 0.17652E+09, 0.20593E+09, - 0.24003E+09, 0.27956E+09, 0.32533E+09, 0.37829E+09, 0.43951E+09, - 0.51021E+09, 0.59180E+09, 0.68588E+09, 0.79427E+09, 0.91904E+09, - 0.10625E+10, 0.12275E+10, 0.14168E+10, 0.16341E+10, 0.18831E+10, - 0.21684E+10, 0.24949E+10, 0.28684E+10, 0.32951E+10, 0.37823E+10, - 0.43382E+10, 0.49719E+10, 0.56938E+10, 0.65156E+10, 0.74502E+10, - 0.85125E+10, 0.97190E+10, 0.11088E+11, 0.12641E+11, 0.14401E+11, - 0.16393E+11, 0.18648E+11, 0.21198E+11, 0.24079E+11, 0.27332E+11, - 0.31003E+11, 0.35142E+11, 0.39807E+11, 0.45060E+11, 0.50972E+11, - 0.57620E+11, 0.65091E+11, 0.73483E+11, 0.82902E+11, 0.93467E+11, - 0.10531E+12, 0.11858E+12, 0.13343E+12, 0.15005E+12, 0.16864E+12, - 0.18941E+12, 0.21260E+12, 0.23849E+12, 0.26737E+12, 0.29957E+12, - 0.33545E+12, 0.37541E+12, 0.41987E+12, 0.46934E+12, 0.52432E+12, - 0.58542E+12]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.47267E+04, 0.80011E+04, 0.11928E+05, 0.16564E+05, 0.21985E+05, 0.28287E+05, 0.35590E+05, + 0.44049E+05, 0.53862E+05, 0.65277E+05, 0.78597E+05, 0.94191E+05, 0.11250E+06, 0.13407E+06, + 0.15952E+06, 0.18962E+06, 0.22526E+06, 0.26751E+06, 0.31763E+06, 0.37714E+06, 0.44780E+06, + 0.53174E+06, 0.63145E+06, 0.74989E+06, 0.89056E+06, 0.10576E+07, 0.12559E+07, 0.14912E+07, + 0.17704E+07, 0.21013E+07, 0.24936E+07, 0.29582E+07, 0.35083E+07, 0.41591E+07, 0.49286E+07, + 0.58379E+07, 0.69116E+07, 0.81787E+07, 0.96728E+07, 0.11433E+08, 0.13506E+08, 0.15945E+08, + 0.18812E+08, 0.22180E+08, 0.26134E+08, 0.30770E+08, 0.36204E+08, 0.42565E+08, 0.50008E+08, + 0.58708E+08, 0.68868E+08, 0.80725E+08, 0.94548E+08, 0.11065E+09, 0.12940E+09, 0.15119E+09, + 0.17652E+09, 0.20593E+09, 0.24003E+09, 0.27956E+09, 0.32533E+09, 0.37829E+09, 0.43951E+09, + 0.51021E+09, 0.59180E+09, 0.68588E+09, 0.79427E+09, 0.91904E+09, 0.10625E+10, 0.12275E+10, + 0.14168E+10, 0.16341E+10, 0.18831E+10, 0.21684E+10, 0.24949E+10, 0.28684E+10, 0.32951E+10, + 0.37823E+10, 0.43382E+10, 0.49719E+10, 0.56938E+10, 0.65156E+10, 0.74502E+10, 0.85125E+10, + 0.97190E+10, 0.11088E+11, 0.12641E+11, 0.14401E+11, 0.16393E+11, 0.18648E+11, 0.21198E+11, + 0.24079E+11, 0.27332E+11, 0.31003E+11, 0.35142E+11, 0.39807E+11, 0.45060E+11, 0.50972E+11, + 0.57620E+11, 0.65091E+11, 0.73483E+11, 0.82902E+11, 0.93467E+11, 0.10531E+12, 0.11858E+12, + 0.13343E+12, 0.15005E+12, 0.16864E+12, 0.18941E+12, 0.21260E+12, 0.23849E+12, 0.26737E+12, + 0.29957E+12, 0.33545E+12, 0.37541E+12, 0.41987E+12, 0.46934E+12, 0.52432E+12, 0.58542E+12]) # --------------- C2H6 1231: M = 27, I = 2 --------------------- M = 27 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.24128E+04, 0.40845E+04, 0.60896E+04, - 0.84564E+04, 0.11224E+05, 0.14442E+05, 0.18170E+05, 0.22490E+05, - 0.27501E+05, 0.33329E+05, 0.40131E+05, 0.48094E+05, 0.57446E+05, - 0.68459E+05, 0.81458E+05, 0.96828E+05, 0.11503E+06, 0.13661E+06, - 0.16221E+06, 0.19260E+06, 0.22869E+06, 0.27156E+06, 0.32249E+06, - 0.38298E+06, 0.45483E+06, 0.54015E+06, 0.64144E+06, 0.76164E+06, - 0.90423E+06, 0.10733E+07, 0.12737E+07, 0.15110E+07, 0.17920E+07, - 0.21245E+07, 0.25176E+07, 0.29821E+07, 0.35307E+07, 0.41780E+07, - 0.49414E+07, 0.58408E+07, 0.68999E+07, 0.81461E+07, 0.96110E+07, - 0.11332E+08, 0.13352E+08, 0.15721E+08, 0.18497E+08, 0.21748E+08, - 0.25551E+08, 0.29997E+08, 0.35189E+08, 0.41248E+08, 0.48313E+08, - 0.56542E+08, 0.66122E+08, 0.77262E+08, 0.90206E+08, 0.10523E+09, - 0.12267E+09, 0.14287E+09, 0.16626E+09, 0.19333E+09, 0.22462E+09, - 0.26076E+09, 0.30247E+09, 0.35056E+09, 0.40596E+09, 0.46974E+09, - 0.54310E+09, 0.62740E+09, 0.72420E+09, 0.83527E+09, 0.96260E+09, - 0.11084E+10, 0.12754E+10, 0.14663E+10, 0.16845E+10, 0.19336E+10, - 0.22178E+10, 0.25418E+10, 0.29109E+10, 0.33311E+10, 0.38090E+10, - 0.43522E+10, 0.49691E+10, 0.56693E+10, 0.64633E+10, 0.73631E+10, - 0.83821E+10, 0.95352E+10, 0.10839E+11, 0.12312E+11, 0.13976E+11, - 0.15854E+11, 0.17971E+11, 0.20357E+11, 0.23043E+11, 0.26067E+11, - 0.29467E+11, 0.33289E+11, 0.37581E+11, 0.42399E+11, 0.47804E+11, - 0.53862E+11, 0.60649E+11, 0.68247E+11, 0.76750E+11, 0.86257E+11, - 0.96882E+11, 0.10875E+12, 0.12199E+12, 0.13677E+12, 0.15325E+12, - 0.17160E+12, 0.19204E+12, 0.21480E+12, 0.24010E+12, 0.26824E+12, - 0.29950E+12]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.24128E+04, 0.40845E+04, 0.60896E+04, 0.84564E+04, 0.11224E+05, 0.14442E+05, 0.18170E+05, + 0.22490E+05, 0.27501E+05, 0.33329E+05, 0.40131E+05, 0.48094E+05, 0.57446E+05, 0.68459E+05, + 0.81458E+05, 0.96828E+05, 0.11503E+06, 0.13661E+06, 0.16221E+06, 0.19260E+06, 0.22869E+06, + 0.27156E+06, 0.32249E+06, 0.38298E+06, 0.45483E+06, 0.54015E+06, 0.64144E+06, 0.76164E+06, + 0.90423E+06, 0.10733E+07, 0.12737E+07, 0.15110E+07, 0.17920E+07, 0.21245E+07, 0.25176E+07, + 0.29821E+07, 0.35307E+07, 0.41780E+07, 0.49414E+07, 0.58408E+07, 0.68999E+07, 0.81461E+07, + 0.96110E+07, 0.11332E+08, 0.13352E+08, 0.15721E+08, 0.18497E+08, 0.21748E+08, 0.25551E+08, + 0.29997E+08, 0.35189E+08, 0.41248E+08, 0.48313E+08, 0.56542E+08, 0.66122E+08, 0.77262E+08, + 0.90206E+08, 0.10523E+09, 0.12267E+09, 0.14287E+09, 0.16626E+09, 0.19333E+09, 0.22462E+09, + 0.26076E+09, 0.30247E+09, 0.35056E+09, 0.40596E+09, 0.46974E+09, 0.54310E+09, 0.62740E+09, + 0.72420E+09, 0.83527E+09, 0.96260E+09, 0.11084E+10, 0.12754E+10, 0.14663E+10, 0.16845E+10, + 0.19336E+10, 0.22178E+10, 0.25418E+10, 0.29109E+10, 0.33311E+10, 0.38090E+10, 0.43522E+10, + 0.49691E+10, 0.56693E+10, 0.64633E+10, 0.73631E+10, 0.83821E+10, 0.95352E+10, 0.10839E+11, + 0.12312E+11, 0.13976E+11, 0.15854E+11, 0.17971E+11, 0.20357E+11, 0.23043E+11, 0.26067E+11, + 0.29467E+11, 0.33289E+11, 0.37581E+11, 0.42399E+11, 0.47804E+11, 0.53862E+11, 0.60649E+11, + 0.68247E+11, 0.76750E+11, 0.86257E+11, 0.96882E+11, 0.10875E+12, 0.12199E+12, 0.13677E+12, + 0.15325E+12, 0.17160E+12, 0.19204E+12, 0.21480E+12, 0.24010E+12, 0.26824E+12, 0.29950E+12]) # --------------- PH3 1111: M = 28, I = 1 --------------------- M = 28 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.29652E+03, 0.49643E+03, 0.72810E+03, - 0.98777E+03, 0.12729E+04, 0.15820E+04, 0.19145E+04, 0.22708E+04, - 0.26520E+04, 0.30600E+04, 0.34971E+04, 0.39662E+04, 0.44702E+04, - 0.50126E+04, 0.55970E+04, 0.62273E+04, 0.69075E+04, 0.76421E+04, - 0.84357E+04, 0.92933E+04, 0.10220E+05, 0.11222E+05, 0.12304E+05, - 0.13473E+05, 0.14736E+05, 0.16099E+05, 0.17571E+05, 0.19160E+05, - 0.20873E+05, 0.22720E+05, 0.24710E+05, 0.26854E+05, 0.29162E+05, - 0.31646E+05, 0.34317E+05, 0.37188E+05, 0.40273E+05, 0.43585E+05, - 0.47140E+05, 0.50953E+05, 0.55040E+05, 0.59419E+05, 0.64108E+05, - 0.69127E+05, 0.74496E+05, 0.80236E+05, 0.86369E+05, 0.92918E+05, - 0.99909E+05, 0.10737E+06, 0.11532E+06, 0.12380E+06, 0.13282E+06, - 0.14244E+06, 0.15266E+06, 0.16354E+06, 0.17511E+06, 0.18739E+06, - 0.20044E+06, 0.21430E+06, 0.22900E+06, 0.24459E+06, 0.26111E+06, - 0.27862E+06, 0.29716E+06, 0.31680E+06, 0.33757E+06, 0.35954E+06, - 0.38277E+06, 0.40733E+06, 0.43326E+06, 0.46065E+06, 0.48955E+06, - 0.52005E+06, 0.55222E+06, 0.58614E+06, 0.62188E+06, 0.65953E+06, - 0.69917E+06, 0.74091E+06, 0.78483E+06, 0.83103E+06, 0.87960E+06, - 0.93067E+06, 0.98432E+06, 0.10407E+07, 0.10999E+07, 0.11620E+07, - 0.12272E+07, 0.12956E+07, 0.13673E+07, 0.14425E+07, 0.15212E+07, - 0.16038E+07, 0.16902E+07, 0.17808E+07, 0.18755E+07, 0.19746E+07, - 0.20784E+07, 0.21868E+07, 0.23002E+07, 0.24187E+07, 0.25425E+07, - 0.26719E+07, 0.28070E+07, 0.29480E+07, 0.30952E+07, 0.32488E+07, - 0.34091E+07, 0.35762E+07, 0.37504E+07, 0.39320E+07, 0.41213E+07, - 0.43185E+07, 0.45239E+07, 0.47378E+07, 0.49605E+07, 0.51923E+07, - 0.54335E+07]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.29652E+03, 0.49643E+03, 0.72810E+03, 0.98777E+03, 0.12729E+04, 0.15820E+04, 0.19145E+04, + 0.22708E+04, 0.26520E+04, 0.30600E+04, 0.34971E+04, 0.39662E+04, 0.44702E+04, 0.50126E+04, + 0.55970E+04, 0.62273E+04, 0.69075E+04, 0.76421E+04, 0.84357E+04, 0.92933E+04, 0.10220E+05, + 0.11222E+05, 0.12304E+05, 0.13473E+05, 0.14736E+05, 0.16099E+05, 0.17571E+05, 0.19160E+05, + 0.20873E+05, 0.22720E+05, 0.24710E+05, 0.26854E+05, 0.29162E+05, 0.31646E+05, 0.34317E+05, + 0.37188E+05, 0.40273E+05, 0.43585E+05, 0.47140E+05, 0.50953E+05, 0.55040E+05, 0.59419E+05, + 0.64108E+05, 0.69127E+05, 0.74496E+05, 0.80236E+05, 0.86369E+05, 0.92918E+05, 0.99909E+05, + 0.10737E+06, 0.11532E+06, 0.12380E+06, 0.13282E+06, 0.14244E+06, 0.15266E+06, 0.16354E+06, + 0.17511E+06, 0.18739E+06, 0.20044E+06, 0.21430E+06, 0.22900E+06, 0.24459E+06, 0.26111E+06, + 0.27862E+06, 0.29716E+06, 0.31680E+06, 0.33757E+06, 0.35954E+06, 0.38277E+06, 0.40733E+06, + 0.43326E+06, 0.46065E+06, 0.48955E+06, 0.52005E+06, 0.55222E+06, 0.58614E+06, 0.62188E+06, + 0.65953E+06, 0.69917E+06, 0.74091E+06, 0.78483E+06, 0.83103E+06, 0.87960E+06, 0.93067E+06, + 0.98432E+06, 0.10407E+07, 0.10999E+07, 0.11620E+07, 0.12272E+07, 0.12956E+07, 0.13673E+07, + 0.14425E+07, 0.15212E+07, 0.16038E+07, 0.16902E+07, 0.17808E+07, 0.18755E+07, 0.19746E+07, + 0.20784E+07, 0.21868E+07, 0.23002E+07, 0.24187E+07, 0.25425E+07, 0.26719E+07, 0.28070E+07, + 0.29480E+07, 0.30952E+07, 0.32488E+07, 0.34091E+07, 0.35762E+07, 0.37504E+07, 0.39320E+07, + 0.41213E+07, 0.43185E+07, 0.45239E+07, 0.47378E+07, 0.49605E+07, 0.51923E+07, 0.54335E+07]) # --------------- COF2 269: M = 29, I = 1 --------------------- M = 29 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.54999E+04, 0.92749E+04, 0.13668E+05, - 0.18643E+05, 0.24224E+05, 0.30487E+05, 0.37547E+05, 0.45543E+05, - 0.54639E+05, 0.65019E+05, 0.76886E+05, 0.90462E+05, 0.10600E+06, - 0.12377E+06, 0.14407E+06, 0.16723E+06, 0.19363E+06, 0.22367E+06, - 0.25780E+06, 0.29650E+06, 0.34031E+06, 0.38982E+06, 0.44568E+06, - 0.50859E+06, 0.57932E+06, 0.65872E+06, 0.74770E+06, 0.84724E+06, - 0.95844E+06, 0.10825E+07, 0.12205E+07, 0.13741E+07, 0.15446E+07, - 0.17336E+07, 0.19428E+07, 0.21742E+07, 0.24296E+07, 0.27113E+07, - 0.30214E+07, 0.33626E+07, 0.37373E+07, 0.41484E+07, 0.45989E+07, - 0.50921E+07, 0.56313E+07, 0.62202E+07, 0.68626E+07, 0.75628E+07, - 0.83251E+07, 0.91542E+07, 0.10055E+08, 0.11033E+08, 0.12093E+08, - 0.13242E+08, 0.14486E+08, 0.15831E+08, 0.17284E+08, 0.18853E+08, - 0.20546E+08, 0.22371E+08, 0.24335E+08, 0.26450E+08, 0.28724E+08, - 0.31167E+08, 0.33790E+08, 0.36605E+08, 0.39623E+08, 0.42856E+08, - 0.46318E+08, 0.50022E+08, 0.53983E+08, 0.58215E+08, 0.62735E+08, - 0.67558E+08, 0.72702E+08, 0.78186E+08, 0.84028E+08, 0.90247E+08, - 0.96865E+08, 0.10390E+09, 0.11138E+09, 0.11933E+09, 0.12777E+09, - 0.13672E+09, 0.14622E+09, 0.15629E+09, 0.16695E+09, 0.17825E+09, - 0.19021E+09, 0.20287E+09, 0.21625E+09, 0.23039E+09, 0.24534E+09, - 0.26113E+09, 0.27779E+09, 0.29538E+09, 0.31392E+09, 0.33348E+09, - 0.35409E+09, 0.37580E+09, 0.39867E+09, 0.42274E+09, 0.44806E+09, - 0.47470E+09, 0.50271E+09, 0.53215E+09, 0.56308E+09, 0.59557E+09, - 0.62968E+09, 0.66548E+09, 0.70304E+09, 0.74243E+09, 0.78374E+09, - 0.82703E+09, 0.87240E+09, 0.91992E+09, 0.96967E+09, 0.10218E+10, - 0.10763E+10]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.54999E+04, 0.92749E+04, 0.13668E+05, 0.18643E+05, 0.24224E+05, 0.30487E+05, 0.37547E+05, + 0.45543E+05, 0.54639E+05, 0.65019E+05, 0.76886E+05, 0.90462E+05, 0.10600E+06, 0.12377E+06, + 0.14407E+06, 0.16723E+06, 0.19363E+06, 0.22367E+06, 0.25780E+06, 0.29650E+06, 0.34031E+06, + 0.38982E+06, 0.44568E+06, 0.50859E+06, 0.57932E+06, 0.65872E+06, 0.74770E+06, 0.84724E+06, + 0.95844E+06, 0.10825E+07, 0.12205E+07, 0.13741E+07, 0.15446E+07, 0.17336E+07, 0.19428E+07, + 0.21742E+07, 0.24296E+07, 0.27113E+07, 0.30214E+07, 0.33626E+07, 0.37373E+07, 0.41484E+07, + 0.45989E+07, 0.50921E+07, 0.56313E+07, 0.62202E+07, 0.68626E+07, 0.75628E+07, 0.83251E+07, + 0.91542E+07, 0.10055E+08, 0.11033E+08, 0.12093E+08, 0.13242E+08, 0.14486E+08, 0.15831E+08, + 0.17284E+08, 0.18853E+08, 0.20546E+08, 0.22371E+08, 0.24335E+08, 0.26450E+08, 0.28724E+08, + 0.31167E+08, 0.33790E+08, 0.36605E+08, 0.39623E+08, 0.42856E+08, 0.46318E+08, 0.50022E+08, + 0.53983E+08, 0.58215E+08, 0.62735E+08, 0.67558E+08, 0.72702E+08, 0.78186E+08, 0.84028E+08, + 0.90247E+08, 0.96865E+08, 0.10390E+09, 0.11138E+09, 0.11933E+09, 0.12777E+09, 0.13672E+09, + 0.14622E+09, 0.15629E+09, 0.16695E+09, 0.17825E+09, 0.19021E+09, 0.20287E+09, 0.21625E+09, + 0.23039E+09, 0.24534E+09, 0.26113E+09, 0.27779E+09, 0.29538E+09, 0.31392E+09, 0.33348E+09, + 0.35409E+09, 0.37580E+09, 0.39867E+09, 0.42274E+09, 0.44806E+09, 0.47470E+09, 0.50271E+09, + 0.53215E+09, 0.56308E+09, 0.59557E+09, 0.62968E+09, 0.66548E+09, 0.70304E+09, 0.74243E+09, + 0.78374E+09, 0.82703E+09, 0.87240E+09, 0.91992E+09, 0.96967E+09, 0.10218E+10, 0.10763E+10]) # --------------- COF2 369: M = 29, I = 2 --------------------- not in TIPS-2011 M = 29 @@ -8698,181 +7534,139 @@ def AtoB(aa, A, B, npt): M = 30 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.46373E+05, 0.78844E+05, 0.11939E+06, - 0.17183E+06, 0.24247E+06, 0.34059E+06, 0.47963E+06, 0.67906E+06, - 0.96713E+06, 0.13848E+07, 0.19911E+07, 0.28714E+07, 0.41481E+07, - 0.59956E+07, 0.86617E+07, 0.12496E+08, 0.17991E+08, 0.25832E+08, - 0.36971E+08, 0.52724E+08, 0.74895E+08, 0.10595E+09, 0.14923E+09, - 0.20925E+09, 0.29208E+09, 0.40582E+09, 0.56124E+09, 0.77259E+09, - 0.10586E+10, 0.14439E+10, 0.19605E+10, 0.26500E+10, 0.35662E+10, - 0.47781E+10, 0.63747E+10, 0.84689E+10, 0.11205E+11, 0.14765E+11, - 0.19378E+11, 0.25336E+11, 0.32998E+11, 0.42819E+11, 0.55361E+11, - 0.71323E+11, 0.91569E+11, 0.11716E+12, 0.14941E+12, 0.18992E+12, - 0.24065E+12, 0.30398E+12, 0.38283E+12, 0.48069E+12, 0.60182E+12, - 0.75136E+12, 0.93546E+12, 0.11615E+13, 0.14384E+13, 0.17767E+13, - 0.21890E+13, 0.26903E+13, 0.32984E+13, 0.40344E+13, 0.49232E+13, - 0.59942E+13, 0.72819E+13, 0.88272E+13, 0.10678E+14, 0.12889E+14, - 0.15527E+14, 0.18666E+14, 0.22397E+14, 0.26823E+14, 0.32062E+14, - 0.38253E+14, 0.45558E+14, 0.54161E+14, 0.64277E+14, 0.76153E+14, - 0.90072E+14, 0.10636E+15, 0.12539E+15, 0.14759E+15, 0.17345E+15, - 0.20354E+15, 0.23848E+15, 0.27902E+15, 0.32597E+15, 0.38028E+15, - 0.44303E+15, 0.51542E+15, 0.59883E+15, 0.69482E+15, 0.80516E+15, - 0.93182E+15, 0.10770E+16, 0.12434E+16, 0.14336E+16, 0.16511E+16, - 0.18992E+16, 0.21821E+16, 0.25043E+16, 0.28709E+16, 0.32875E+16, - 0.37604E+16, 0.42968E+16, 0.49046E+16, 0.55925E+16, 0.63704E+16, - 0.72492E+16, 0.82411E+16, 0.93596E+16, 0.10620E+17, 0.12038E+17, - 0.13633E+17, 0.15425E+17, 0.17438E+17, 0.19694E+17, 0.22224E+17, - 0.25057E+17]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.46373E+05, 0.78844E+05, 0.11939E+06, 0.17183E+06, 0.24247E+06, 0.34059E+06, 0.47963E+06, + 0.67906E+06, 0.96713E+06, 0.13848E+07, 0.19911E+07, 0.28714E+07, 0.41481E+07, 0.59956E+07, + 0.86617E+07, 0.12496E+08, 0.17991E+08, 0.25832E+08, 0.36971E+08, 0.52724E+08, 0.74895E+08, + 0.10595E+09, 0.14923E+09, 0.20925E+09, 0.29208E+09, 0.40582E+09, 0.56124E+09, 0.77259E+09, + 0.10586E+10, 0.14439E+10, 0.19605E+10, 0.26500E+10, 0.35662E+10, 0.47781E+10, 0.63747E+10, + 0.84689E+10, 0.11205E+11, 0.14765E+11, 0.19378E+11, 0.25336E+11, 0.32998E+11, 0.42819E+11, + 0.55361E+11, 0.71323E+11, 0.91569E+11, 0.11716E+12, 0.14941E+12, 0.18992E+12, 0.24065E+12, + 0.30398E+12, 0.38283E+12, 0.48069E+12, 0.60182E+12, 0.75136E+12, 0.93546E+12, 0.11615E+13, + 0.14384E+13, 0.17767E+13, 0.21890E+13, 0.26903E+13, 0.32984E+13, 0.40344E+13, 0.49232E+13, + 0.59942E+13, 0.72819E+13, 0.88272E+13, 0.10678E+14, 0.12889E+14, 0.15527E+14, 0.18666E+14, + 0.22397E+14, 0.26823E+14, 0.32062E+14, 0.38253E+14, 0.45558E+14, 0.54161E+14, 0.64277E+14, + 0.76153E+14, 0.90072E+14, 0.10636E+15, 0.12539E+15, 0.14759E+15, 0.17345E+15, 0.20354E+15, + 0.23848E+15, 0.27902E+15, 0.32597E+15, 0.38028E+15, 0.44303E+15, 0.51542E+15, 0.59883E+15, + 0.69482E+15, 0.80516E+15, 0.93182E+15, 0.10770E+16, 0.12434E+16, 0.14336E+16, 0.16511E+16, + 0.18992E+16, 0.21821E+16, 0.25043E+16, 0.28709E+16, 0.32875E+16, 0.37604E+16, 0.42968E+16, + 0.49046E+16, 0.55925E+16, 0.63704E+16, 0.72492E+16, 0.82411E+16, 0.93596E+16, 0.10620E+17, + 0.12038E+17, 0.13633E+17, 0.15425E+17, 0.17438E+17, 0.19694E+17, 0.22224E+17, 0.25057E+17]) # --------------- H2S 121: M = 31, I = 1 --------------------- M = 31 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.47192E+02, 0.78671E+02, 0.11510E+03, - 0.15589E+03, 0.20061E+03, 0.24896E+03, 0.30070E+03, 0.35571E+03, - 0.41386E+03, 0.47513E+03, 0.53951E+03, 0.60703E+03, 0.67772E+03, - 0.75167E+03, 0.82896E+03, 0.90969E+03, 0.99396E+03, 0.10819E+04, - 0.11736E+04, 0.12692E+04, 0.13689E+04, 0.14727E+04, 0.15809E+04, - 0.16937E+04, 0.18111E+04, 0.19333E+04, 0.20606E+04, 0.21931E+04, - 0.23309E+04, 0.24744E+04, 0.26236E+04, 0.27788E+04, 0.29403E+04, - 0.31081E+04, 0.32825E+04, 0.34638E+04, 0.36522E+04, 0.38478E+04, - 0.40510E+04, 0.42619E+04, 0.44808E+04, 0.47080E+04, 0.49437E+04, - 0.51881E+04, 0.54415E+04, 0.57042E+04, 0.59764E+04, 0.62584E+04, - 0.65505E+04, 0.68529E+04, 0.71660E+04, 0.74899E+04, 0.78251E+04, - 0.81718E+04, 0.85303E+04, 0.89008E+04, 0.92838E+04, 0.96795E+04, - 0.10088E+05, 0.10510E+05, 0.10946E+05, 0.11396E+05, 0.11860E+05, - 0.12339E+05, 0.12833E+05, 0.13342E+05, 0.13867E+05, 0.14408E+05, - 0.14966E+05, 0.15540E+05, 0.16132E+05, 0.16741E+05, 0.17368E+05, - 0.18013E+05, 0.18677E+05, 0.19361E+05, 0.20064E+05, 0.20786E+05, - 0.21529E+05, 0.22293E+05, 0.23078E+05, 0.23885E+05, 0.24714E+05, - 0.25565E+05, 0.26439E+05, 0.27337E+05, 0.28258E+05, 0.29204E+05, - 0.30174E+05, 0.31170E+05, 0.32191E+05, 0.33239E+05, 0.34313E+05, - 0.35414E+05, 0.36543E+05, 0.37700E+05, 0.38886E+05, 0.40101E+05, - 0.41346E+05, 0.42621E+05, 0.43926E+05, 0.45263E+05, 0.46631E+05, - 0.48033E+05, 0.49466E+05, 0.50934E+05, 0.52435E+05, 0.53971E+05, - 0.55542E+05, 0.57149E+05, 0.58792E+05, 0.60472E+05, 0.62190E+05, - 0.63946E+05, 0.65740E+05, 0.67574E+05, 0.69448E+05, 0.71362E+05, - 0.73318E+05]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.47192E+02, 0.78671E+02, 0.11510E+03, 0.15589E+03, 0.20061E+03, 0.24896E+03, 0.30070E+03, + 0.35571E+03, 0.41386E+03, 0.47513E+03, 0.53951E+03, 0.60703E+03, 0.67772E+03, 0.75167E+03, + 0.82896E+03, 0.90969E+03, 0.99396E+03, 0.10819E+04, 0.11736E+04, 0.12692E+04, 0.13689E+04, + 0.14727E+04, 0.15809E+04, 0.16937E+04, 0.18111E+04, 0.19333E+04, 0.20606E+04, 0.21931E+04, + 0.23309E+04, 0.24744E+04, 0.26236E+04, 0.27788E+04, 0.29403E+04, 0.31081E+04, 0.32825E+04, + 0.34638E+04, 0.36522E+04, 0.38478E+04, 0.40510E+04, 0.42619E+04, 0.44808E+04, 0.47080E+04, + 0.49437E+04, 0.51881E+04, 0.54415E+04, 0.57042E+04, 0.59764E+04, 0.62584E+04, 0.65505E+04, + 0.68529E+04, 0.71660E+04, 0.74899E+04, 0.78251E+04, 0.81718E+04, 0.85303E+04, 0.89008E+04, + 0.92838E+04, 0.96795E+04, 0.10088E+05, 0.10510E+05, 0.10946E+05, 0.11396E+05, 0.11860E+05, + 0.12339E+05, 0.12833E+05, 0.13342E+05, 0.13867E+05, 0.14408E+05, 0.14966E+05, 0.15540E+05, + 0.16132E+05, 0.16741E+05, 0.17368E+05, 0.18013E+05, 0.18677E+05, 0.19361E+05, 0.20064E+05, + 0.20786E+05, 0.21529E+05, 0.22293E+05, 0.23078E+05, 0.23885E+05, 0.24714E+05, 0.25565E+05, + 0.26439E+05, 0.27337E+05, 0.28258E+05, 0.29204E+05, 0.30174E+05, 0.31170E+05, 0.32191E+05, + 0.33239E+05, 0.34313E+05, 0.35414E+05, 0.36543E+05, 0.37700E+05, 0.38886E+05, 0.40101E+05, + 0.41346E+05, 0.42621E+05, 0.43926E+05, 0.45263E+05, 0.46631E+05, 0.48033E+05, 0.49466E+05, + 0.50934E+05, 0.52435E+05, 0.53971E+05, 0.55542E+05, 0.57149E+05, 0.58792E+05, 0.60472E+05, + 0.62190E+05, 0.63946E+05, 0.65740E+05, 0.67574E+05, 0.69448E+05, 0.71362E+05, 0.73318E+05]) # --------------- H2S 141: M = 31, I = 2 --------------------- M = 31 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.47310E+02, 0.78869E+02, 0.11539E+03, - 0.15628E+03, 0.20112E+03, 0.24959E+03, 0.30147E+03, 0.35661E+03, - 0.41491E+03, 0.47634E+03, 0.54088E+03, 0.60857E+03, 0.67945E+03, - 0.75359E+03, 0.83107E+03, 0.91201E+03, 0.99649E+03, 0.10846E+04, - 0.11766E+04, 0.12724E+04, 0.13724E+04, 0.14765E+04, 0.15850E+04, - 0.16980E+04, 0.18157E+04, 0.19382E+04, 0.20658E+04, 0.21987E+04, - 0.23369E+04, 0.24807E+04, 0.26303E+04, 0.27859E+04, 0.29478E+04, - 0.31160E+04, 0.32909E+04, 0.34727E+04, 0.36615E+04, 0.38576E+04, - 0.40613E+04, 0.42728E+04, 0.44923E+04, 0.47200E+04, 0.49563E+04, - 0.52013E+04, 0.54554E+04, 0.57188E+04, 0.59917E+04, 0.62744E+04, - 0.65672E+04, 0.68704E+04, 0.71843E+04, 0.75090E+04, 0.78451E+04, - 0.81926E+04, 0.85520E+04, 0.89236E+04, 0.93075E+04, 0.97042E+04, - 0.10114E+05, 0.10537E+05, 0.10974E+05, 0.11425E+05, 0.11890E+05, - 0.12370E+05, 0.12866E+05, 0.13376E+05, 0.13903E+05, 0.14445E+05, - 0.15004E+05, 0.15580E+05, 0.16173E+05, 0.16784E+05, 0.17412E+05, - 0.18059E+05, 0.18725E+05, 0.19410E+05, 0.20115E+05, 0.20839E+05, - 0.21584E+05, 0.22350E+05, 0.23137E+05, 0.23946E+05, 0.24777E+05, - 0.25630E+05, 0.26507E+05, 0.27407E+05, 0.28330E+05, 0.29278E+05, - 0.30251E+05, 0.31249E+05, 0.32273E+05, 0.33324E+05, 0.34401E+05, - 0.35505E+05, 0.36637E+05, 0.37797E+05, 0.38985E+05, 0.40204E+05, - 0.41451E+05, 0.42729E+05, 0.44038E+05, 0.45379E+05, 0.46751E+05, - 0.48155E+05, 0.49593E+05, 0.51064E+05, 0.52569E+05, 0.54109E+05, - 0.55684E+05, 0.57295E+05, 0.58943E+05, 0.60627E+05, 0.62349E+05, - 0.64109E+05, 0.65908E+05, 0.67747E+05, 0.69625E+05, 0.71544E+05, - 0.73505E+05]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.47310E+02, 0.78869E+02, 0.11539E+03, 0.15628E+03, 0.20112E+03, 0.24959E+03, 0.30147E+03, + 0.35661E+03, 0.41491E+03, 0.47634E+03, 0.54088E+03, 0.60857E+03, 0.67945E+03, 0.75359E+03, + 0.83107E+03, 0.91201E+03, 0.99649E+03, 0.10846E+04, 0.11766E+04, 0.12724E+04, 0.13724E+04, + 0.14765E+04, 0.15850E+04, 0.16980E+04, 0.18157E+04, 0.19382E+04, 0.20658E+04, 0.21987E+04, + 0.23369E+04, 0.24807E+04, 0.26303E+04, 0.27859E+04, 0.29478E+04, 0.31160E+04, 0.32909E+04, + 0.34727E+04, 0.36615E+04, 0.38576E+04, 0.40613E+04, 0.42728E+04, 0.44923E+04, 0.47200E+04, + 0.49563E+04, 0.52013E+04, 0.54554E+04, 0.57188E+04, 0.59917E+04, 0.62744E+04, 0.65672E+04, + 0.68704E+04, 0.71843E+04, 0.75090E+04, 0.78451E+04, 0.81926E+04, 0.85520E+04, 0.89236E+04, + 0.93075E+04, 0.97042E+04, 0.10114E+05, 0.10537E+05, 0.10974E+05, 0.11425E+05, 0.11890E+05, + 0.12370E+05, 0.12866E+05, 0.13376E+05, 0.13903E+05, 0.14445E+05, 0.15004E+05, 0.15580E+05, + 0.16173E+05, 0.16784E+05, 0.17412E+05, 0.18059E+05, 0.18725E+05, 0.19410E+05, 0.20115E+05, + 0.20839E+05, 0.21584E+05, 0.22350E+05, 0.23137E+05, 0.23946E+05, 0.24777E+05, 0.25630E+05, + 0.26507E+05, 0.27407E+05, 0.28330E+05, 0.29278E+05, 0.30251E+05, 0.31249E+05, 0.32273E+05, + 0.33324E+05, 0.34401E+05, 0.35505E+05, 0.36637E+05, 0.37797E+05, 0.38985E+05, 0.40204E+05, + 0.41451E+05, 0.42729E+05, 0.44038E+05, 0.45379E+05, 0.46751E+05, 0.48155E+05, 0.49593E+05, + 0.51064E+05, 0.52569E+05, 0.54109E+05, 0.55684E+05, 0.57295E+05, 0.58943E+05, 0.60627E+05, + 0.62349E+05, 0.64109E+05, 0.65908E+05, 0.67747E+05, 0.69625E+05, 0.71544E+05, 0.73505E+05]) # --------------- H2S 131: M = 30, I = 3 --------------------- M = 31 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(4.) -TIPS_ISO_HASH[(M, I)] = float32([0.18901E+03, 0.31509E+03, 0.46102E+03, - 0.62437E+03, 0.80349E+03, 0.99713E+03, 0.12044E+04, 0.14247E+04, - 0.16576E+04, 0.19030E+04, 0.21609E+04, 0.24313E+04, 0.27145E+04, - 0.30106E+04, 0.33202E+04, 0.36436E+04, 0.39811E+04, 0.43332E+04, - 0.47005E+04, 0.50835E+04, 0.54827E+04, 0.58987E+04, 0.63321E+04, - 0.67836E+04, 0.72538E+04, 0.77434E+04, 0.82532E+04, 0.87838E+04, - 0.93360E+04, 0.99106E+04, 0.10508E+05, 0.11130E+05, 0.11777E+05, - 0.12449E+05, 0.13147E+05, 0.13874E+05, 0.14628E+05, 0.15412E+05, - 0.16225E+05, 0.17070E+05, 0.17947E+05, 0.18857E+05, 0.19801E+05, - 0.20780E+05, 0.21795E+05, 0.22847E+05, 0.23937E+05, 0.25067E+05, - 0.26236E+05, 0.27448E+05, 0.28702E+05, 0.29999E+05, 0.31342E+05, - 0.32730E+05, 0.34166E+05, 0.35650E+05, 0.37184E+05, 0.38769E+05, - 0.40406E+05, 0.42097E+05, 0.43842E+05, 0.45644E+05, 0.47503E+05, - 0.49421E+05, 0.51399E+05, 0.53439E+05, 0.55542E+05, 0.57709E+05, - 0.59942E+05, 0.62242E+05, 0.64611E+05, 0.67051E+05, 0.69563E+05, - 0.72148E+05, 0.74808E+05, 0.77545E+05, 0.80360E+05, 0.83255E+05, - 0.86232E+05, 0.89291E+05, 0.92435E+05, 0.95667E+05, 0.98986E+05, - 0.10240E+06, 0.10590E+06, 0.10949E+06, 0.11318E+06, 0.11697E+06, - 0.12086E+06, 0.12484E+06, 0.12893E+06, 0.13313E+06, 0.13743E+06, - 0.14184E+06, 0.14637E+06, 0.15100E+06, 0.15575E+06, 0.16062E+06, - 0.16560E+06, 0.17071E+06, 0.17594E+06, 0.18129E+06, 0.18677E+06, - 0.19238E+06, 0.19813E+06, 0.20400E+06, 0.21002E+06, 0.21617E+06, - 0.22246E+06, 0.22890E+06, 0.23548E+06, 0.24221E+06, 0.24909E+06, - 0.25612E+06, 0.26331E+06, 0.27065E+06, 0.27816E+06, 0.28583E+06, - 0.29366E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.18901E+03, 0.31509E+03, 0.46102E+03, 0.62437E+03, 0.80349E+03, 0.99713E+03, 0.12044E+04, + 0.14247E+04, 0.16576E+04, 0.19030E+04, 0.21609E+04, 0.24313E+04, 0.27145E+04, 0.30106E+04, + 0.33202E+04, 0.36436E+04, 0.39811E+04, 0.43332E+04, 0.47005E+04, 0.50835E+04, 0.54827E+04, + 0.58987E+04, 0.63321E+04, 0.67836E+04, 0.72538E+04, 0.77434E+04, 0.82532E+04, 0.87838E+04, + 0.93360E+04, 0.99106E+04, 0.10508E+05, 0.11130E+05, 0.11777E+05, 0.12449E+05, 0.13147E+05, + 0.13874E+05, 0.14628E+05, 0.15412E+05, 0.16225E+05, 0.17070E+05, 0.17947E+05, 0.18857E+05, + 0.19801E+05, 0.20780E+05, 0.21795E+05, 0.22847E+05, 0.23937E+05, 0.25067E+05, 0.26236E+05, + 0.27448E+05, 0.28702E+05, 0.29999E+05, 0.31342E+05, 0.32730E+05, 0.34166E+05, 0.35650E+05, + 0.37184E+05, 0.38769E+05, 0.40406E+05, 0.42097E+05, 0.43842E+05, 0.45644E+05, 0.47503E+05, + 0.49421E+05, 0.51399E+05, 0.53439E+05, 0.55542E+05, 0.57709E+05, 0.59942E+05, 0.62242E+05, + 0.64611E+05, 0.67051E+05, 0.69563E+05, 0.72148E+05, 0.74808E+05, 0.77545E+05, 0.80360E+05, + 0.83255E+05, 0.86232E+05, 0.89291E+05, 0.92435E+05, 0.95667E+05, 0.98986E+05, 0.10240E+06, + 0.10590E+06, 0.10949E+06, 0.11318E+06, 0.11697E+06, 0.12086E+06, 0.12484E+06, 0.12893E+06, + 0.13313E+06, 0.13743E+06, 0.14184E+06, 0.14637E+06, 0.15100E+06, 0.15575E+06, 0.16062E+06, + 0.16560E+06, 0.17071E+06, 0.17594E+06, 0.18129E+06, 0.18677E+06, 0.19238E+06, 0.19813E+06, + 0.20400E+06, 0.21002E+06, 0.21617E+06, 0.22246E+06, 0.22890E+06, 0.23548E+06, 0.24221E+06, + 0.24909E+06, 0.25612E+06, 0.26331E+06, 0.27065E+06, 0.27816E+06, 0.28583E+06, 0.29366E+06]) # --------------- HCOOH 126: M = 32, I = 1 --------------------- M = 32 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(4.) -TIPS_ISO_HASH[(M, I)] = float32([0.31899E+04, 0.53773E+04, 0.79205E+04, - 0.10792E+05, 0.13993E+05, 0.17550E+05, 0.21509E+05, 0.25930E+05, - 0.30885E+05, 0.36460E+05, 0.42750E+05, 0.49864E+05, 0.57926E+05, - 0.67071E+05, 0.77453E+05, 0.89243E+05, 0.10263E+06, 0.11783E+06, - 0.13507E+06, 0.15462E+06, 0.17676E+06, 0.20183E+06, 0.23018E+06, - 0.26221E+06, 0.29836E+06, 0.33911E+06, 0.38501E+06, 0.43664E+06, - 0.49467E+06, 0.55981E+06, 0.63286E+06, 0.71470E+06, 0.80628E+06, - 0.90865E+06, 0.10230E+07, 0.11505E+07, 0.12927E+07, 0.14509E+07, - 0.16269E+07, 0.18225E+07, 0.20396E+07, 0.22804E+07, 0.25472E+07, - 0.28425E+07, 0.31692E+07, 0.35301E+07, 0.39285E+07, 0.43681E+07, - 0.48525E+07, 0.53858E+07, 0.59727E+07, 0.66178E+07, 0.73265E+07, - 0.81042E+07, 0.89571E+07, 0.98918E+07, 0.10915E+08, 0.12035E+08, - 0.13259E+08, 0.14597E+08, 0.16057E+08, 0.17650E+08, 0.19387E+08, - 0.21279E+08, 0.23339E+08, 0.25579E+08, 0.28016E+08, 0.30663E+08, - 0.33536E+08, 0.36655E+08, 0.40037E+08, 0.43701E+08, 0.47671E+08, - 0.51967E+08, 0.56614E+08, 0.61639E+08, 0.67068E+08, 0.72930E+08, - 0.79257E+08, 0.86082E+08, 0.93439E+08, 0.10137E+09, 0.10990E+09, - 0.11909E+09, 0.12898E+09, 0.13960E+09, 0.15102E+09, 0.16329E+09, - 0.17646E+09, 0.19059E+09, 0.20575E+09, 0.22200E+09, 0.23941E+09, - 0.25806E+09, 0.27802E+09, 0.29938E+09, 0.32223E+09, 0.34666E+09, - 0.37276E+09, 0.40064E+09, 0.43041E+09, 0.46218E+09, 0.49607E+09, - 0.53221E+09, 0.57074E+09, 0.61179E+09, 0.65551E+09, 0.70206E+09, - 0.75159E+09, 0.80430E+09, 0.86034E+09, 0.91992E+09, 0.98324E+09, - 0.10505E+10, 0.11219E+10, 0.11977E+10, 0.12782E+10, 0.13635E+10, - 0.14540E+10]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.31899E+04, 0.53773E+04, 0.79205E+04, 0.10792E+05, 0.13993E+05, 0.17550E+05, 0.21509E+05, + 0.25930E+05, 0.30885E+05, 0.36460E+05, 0.42750E+05, 0.49864E+05, 0.57926E+05, 0.67071E+05, + 0.77453E+05, 0.89243E+05, 0.10263E+06, 0.11783E+06, 0.13507E+06, 0.15462E+06, 0.17676E+06, + 0.20183E+06, 0.23018E+06, 0.26221E+06, 0.29836E+06, 0.33911E+06, 0.38501E+06, 0.43664E+06, + 0.49467E+06, 0.55981E+06, 0.63286E+06, 0.71470E+06, 0.80628E+06, 0.90865E+06, 0.10230E+07, + 0.11505E+07, 0.12927E+07, 0.14509E+07, 0.16269E+07, 0.18225E+07, 0.20396E+07, 0.22804E+07, + 0.25472E+07, 0.28425E+07, 0.31692E+07, 0.35301E+07, 0.39285E+07, 0.43681E+07, 0.48525E+07, + 0.53858E+07, 0.59727E+07, 0.66178E+07, 0.73265E+07, 0.81042E+07, 0.89571E+07, 0.98918E+07, + 0.10915E+08, 0.12035E+08, 0.13259E+08, 0.14597E+08, 0.16057E+08, 0.17650E+08, 0.19387E+08, + 0.21279E+08, 0.23339E+08, 0.25579E+08, 0.28016E+08, 0.30663E+08, 0.33536E+08, 0.36655E+08, + 0.40037E+08, 0.43701E+08, 0.47671E+08, 0.51967E+08, 0.56614E+08, 0.61639E+08, 0.67068E+08, + 0.72930E+08, 0.79257E+08, 0.86082E+08, 0.93439E+08, 0.10137E+09, 0.10990E+09, 0.11909E+09, + 0.12898E+09, 0.13960E+09, 0.15102E+09, 0.16329E+09, 0.17646E+09, 0.19059E+09, 0.20575E+09, + 0.22200E+09, 0.23941E+09, 0.25806E+09, 0.27802E+09, 0.29938E+09, 0.32223E+09, 0.34666E+09, + 0.37276E+09, 0.40064E+09, 0.43041E+09, 0.46218E+09, 0.49607E+09, 0.53221E+09, 0.57074E+09, + 0.61179E+09, 0.65551E+09, 0.70206E+09, 0.75159E+09, 0.80430E+09, 0.86034E+09, 0.91992E+09, + 0.98324E+09, 0.10505E+10, 0.11219E+10, 0.11977E+10, 0.12782E+10, 0.13635E+10, 0.14540E+10]) # --------------- HO2 166: M = 33, I = 1 --------------------- M = 33 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.39277E+03, 0.66062E+03, 0.97123E+03, - 0.13194E+04, 0.17014E+04, 0.21148E+04, 0.25578E+04, 0.30296E+04, - 0.35297E+04, 0.40585E+04, 0.46167E+04, 0.52055E+04, 0.58264E+04, - 0.64809E+04, 0.71707E+04, 0.78978E+04, 0.86641E+04, 0.94715E+04, - 0.10322E+05, 0.11218E+05, 0.12161E+05, 0.13154E+05, 0.14198E+05, - 0.15296E+05, 0.16449E+05, 0.17661E+05, 0.18933E+05, 0.20267E+05, - 0.21666E+05, 0.23133E+05, 0.24669E+05, 0.26277E+05, 0.27960E+05, - 0.29720E+05, 0.31560E+05, 0.33482E+05, 0.35489E+05, 0.37584E+05, - 0.39769E+05, 0.42048E+05, 0.44423E+05, 0.46898E+05, 0.49475E+05, - 0.52157E+05, 0.54948E+05, 0.57850E+05, 0.60868E+05, 0.64003E+05, - 0.67261E+05, 0.70643E+05, 0.74154E+05, 0.77797E+05, 0.81575E+05, - 0.85492E+05, 0.89553E+05, 0.93760E+05, 0.98118E+05, 0.10263E+06, - 0.10730E+06, 0.11213E+06, 0.11713E+06, 0.12230E+06, 0.12765E+06, - 0.13317E+06, 0.13888E+06, 0.14478E+06, 0.15086E+06, 0.15715E+06, - 0.16363E+06, 0.17032E+06, 0.17723E+06, 0.18434E+06, 0.19168E+06, - 0.19924E+06, 0.20704E+06, 0.21506E+06, 0.22333E+06, 0.23185E+06, - 0.24061E+06, 0.24963E+06, 0.25891E+06, 0.26846E+06, 0.27828E+06, - 0.28838E+06, 0.29876E+06, 0.30943E+06, 0.32039E+06, 0.33166E+06, - 0.34323E+06, 0.35512E+06, 0.36732E+06, 0.37985E+06, 0.39271E+06, - 0.40590E+06, 0.41944E+06, 0.43333E+06, 0.44758E+06, 0.46219E+06, - 0.47717E+06, 0.49252E+06, 0.50826E+06, 0.52439E+06, 0.54091E+06, - 0.55784E+06, 0.57518E+06, 0.59293E+06, 0.61112E+06, 0.62973E+06, - 0.64878E+06, 0.66828E+06, 0.68824E+06, 0.70866E+06, 0.72955E+06, - 0.75091E+06, 0.77276E+06, 0.79511E+06, 0.81795E+06, 0.84131E+06, - 0.86518E+06]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.39277E+03, 0.66062E+03, 0.97123E+03, 0.13194E+04, 0.17014E+04, 0.21148E+04, 0.25578E+04, + 0.30296E+04, 0.35297E+04, 0.40585E+04, 0.46167E+04, 0.52055E+04, 0.58264E+04, 0.64809E+04, + 0.71707E+04, 0.78978E+04, 0.86641E+04, 0.94715E+04, 0.10322E+05, 0.11218E+05, 0.12161E+05, + 0.13154E+05, 0.14198E+05, 0.15296E+05, 0.16449E+05, 0.17661E+05, 0.18933E+05, 0.20267E+05, + 0.21666E+05, 0.23133E+05, 0.24669E+05, 0.26277E+05, 0.27960E+05, 0.29720E+05, 0.31560E+05, + 0.33482E+05, 0.35489E+05, 0.37584E+05, 0.39769E+05, 0.42048E+05, 0.44423E+05, 0.46898E+05, + 0.49475E+05, 0.52157E+05, 0.54948E+05, 0.57850E+05, 0.60868E+05, 0.64003E+05, 0.67261E+05, + 0.70643E+05, 0.74154E+05, 0.77797E+05, 0.81575E+05, 0.85492E+05, 0.89553E+05, 0.93760E+05, + 0.98118E+05, 0.10263E+06, 0.10730E+06, 0.11213E+06, 0.11713E+06, 0.12230E+06, 0.12765E+06, + 0.13317E+06, 0.13888E+06, 0.14478E+06, 0.15086E+06, 0.15715E+06, 0.16363E+06, 0.17032E+06, + 0.17723E+06, 0.18434E+06, 0.19168E+06, 0.19924E+06, 0.20704E+06, 0.21506E+06, 0.22333E+06, + 0.23185E+06, 0.24061E+06, 0.24963E+06, 0.25891E+06, 0.26846E+06, 0.27828E+06, 0.28838E+06, + 0.29876E+06, 0.30943E+06, 0.32039E+06, 0.33166E+06, 0.34323E+06, 0.35512E+06, 0.36732E+06, + 0.37985E+06, 0.39271E+06, 0.40590E+06, 0.41944E+06, 0.43333E+06, 0.44758E+06, 0.46219E+06, + 0.47717E+06, 0.49252E+06, 0.50826E+06, 0.52439E+06, 0.54091E+06, 0.55784E+06, 0.57518E+06, + 0.59293E+06, 0.61112E+06, 0.62973E+06, 0.64878E+06, 0.66828E+06, 0.68824E+06, 0.70866E+06, + 0.72955E+06, 0.75091E+06, 0.77276E+06, 0.79511E+06, 0.81795E+06, 0.84131E+06, 0.86518E+06]) # --------------- O 6: M = 34, I = 1 --------------------- not in TIPS-2011 M = 34 @@ -8884,211 +7678,162 @@ def AtoB(aa, A, B, npt): M = 35 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(12.) -TIPS_ISO_HASH[(M, I)] = float32([0.11444E+06, 0.21121E+06, 0.34858E+06, - 0.53934E+06, 0.80041E+06, 0.11539E+07, 0.16286E+07, 0.22614E+07, - 0.30992E+07, 0.42015E+07, 0.56426E+07, 0.75152E+07, 0.99344E+07, - 0.13042E+08, 0.17012E+08, 0.22058E+08, 0.28437E+08, 0.36463E+08, - 0.46514E+08, 0.59042E+08, 0.74589E+08, 0.93801E+08, 0.11744E+09, - 0.14643E+09, 0.18181E+09, 0.22486E+09, 0.27705E+09, 0.34009E+09, - 0.41598E+09, 0.50705E+09, 0.61599E+09, 0.74590E+09, 0.90037E+09, - 0.10835E+10, 0.13001E+10, 0.15554E+10, 0.18556E+10, 0.22079E+10, - 0.26200E+10, 0.31012E+10, 0.36615E+10, 0.43126E+10, 0.50675E+10, - 0.59409E+10, 0.69492E+10, 0.81110E+10, 0.94469E+10, 0.10980E+11, - 0.12736E+11, 0.14745E+11, 0.17037E+11, 0.19649E+11, 0.22620E+11, - 0.25994E+11, 0.29819E+11, 0.34150E+11, 0.39044E+11, 0.44568E+11, - 0.50794E+11, 0.57799E+11, 0.65672E+11, 0.74506E+11, 0.84408E+11, - 0.95490E+11, 0.10788E+12, 0.12171E+12, 0.13713E+12, 0.15431E+12, - 0.17342E+12, 0.19465E+12, 0.21822E+12, 0.24435E+12, 0.27329E+12, - 0.30530E+12, 0.34069E+12, 0.37976E+12, 0.42286E+12, 0.47034E+12, - 0.52262E+12, 0.58012E+12, 0.64330E+12, 0.71267E+12, 0.78875E+12, - 0.87214E+12, 0.96344E+12, 0.10633E+13, 0.11725E+13, 0.12918E+13, - 0.14220E+13, 0.15640E+13, 0.17188E+13, 0.18873E+13, 0.20706E+13, - 0.22700E+13, 0.24866E+13, 0.27218E+13, 0.29771E+13, 0.32538E+13, - 0.35537E+13, 0.38784E+13, 0.42299E+13, 0.46100E+13, 0.50208E+13, - 0.54645E+13, 0.59435E+13, 0.64603E+13, 0.70175E+13, 0.76180E+13, - 0.82647E+13, 0.89608E+13, 0.97097E+13, 0.10515E+14, 0.11380E+14, - 0.12310E+14, 0.13307E+14, 0.14378E+14, 0.15526E+14, 0.16756E+14, - 0.18075E+14]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.11444E+06, 0.21121E+06, 0.34858E+06, 0.53934E+06, 0.80041E+06, 0.11539E+07, 0.16286E+07, + 0.22614E+07, 0.30992E+07, 0.42015E+07, 0.56426E+07, 0.75152E+07, 0.99344E+07, 0.13042E+08, + 0.17012E+08, 0.22058E+08, 0.28437E+08, 0.36463E+08, 0.46514E+08, 0.59042E+08, 0.74589E+08, + 0.93801E+08, 0.11744E+09, 0.14643E+09, 0.18181E+09, 0.22486E+09, 0.27705E+09, 0.34009E+09, + 0.41598E+09, 0.50705E+09, 0.61599E+09, 0.74590E+09, 0.90037E+09, 0.10835E+10, 0.13001E+10, + 0.15554E+10, 0.18556E+10, 0.22079E+10, 0.26200E+10, 0.31012E+10, 0.36615E+10, 0.43126E+10, + 0.50675E+10, 0.59409E+10, 0.69492E+10, 0.81110E+10, 0.94469E+10, 0.10980E+11, 0.12736E+11, + 0.14745E+11, 0.17037E+11, 0.19649E+11, 0.22620E+11, 0.25994E+11, 0.29819E+11, 0.34150E+11, + 0.39044E+11, 0.44568E+11, 0.50794E+11, 0.57799E+11, 0.65672E+11, 0.74506E+11, 0.84408E+11, + 0.95490E+11, 0.10788E+12, 0.12171E+12, 0.13713E+12, 0.15431E+12, 0.17342E+12, 0.19465E+12, + 0.21822E+12, 0.24435E+12, 0.27329E+12, 0.30530E+12, 0.34069E+12, 0.37976E+12, 0.42286E+12, + 0.47034E+12, 0.52262E+12, 0.58012E+12, 0.64330E+12, 0.71267E+12, 0.78875E+12, 0.87214E+12, + 0.96344E+12, 0.10633E+13, 0.11725E+13, 0.12918E+13, 0.14220E+13, 0.15640E+13, 0.17188E+13, + 0.18873E+13, 0.20706E+13, 0.22700E+13, 0.24866E+13, 0.27218E+13, 0.29771E+13, 0.32538E+13, + 0.35537E+13, 0.38784E+13, 0.42299E+13, 0.46100E+13, 0.50208E+13, 0.54645E+13, 0.59435E+13, + 0.64603E+13, 0.70175E+13, 0.76180E+13, 0.82647E+13, 0.89608E+13, 0.97097E+13, 0.10515E+14, + 0.11380E+14, 0.12310E+14, 0.13307E+14, 0.14378E+14, 0.15526E+14, 0.16756E+14, 0.18075E+14]) # --------------- ClONO2 7646: M = 35, I = 2 --------------------- M = 35 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(12.) -TIPS_ISO_HASH[(M, I)] = float32([0.11735E+06, 0.21659E+06, 0.35745E+06, - 0.55307E+06, 0.82078E+06, 0.11833E+07, 0.16700E+07, 0.23189E+07, - 0.31781E+07, 0.43084E+07, 0.57862E+07, 0.77065E+07, 0.10187E+08, - 0.13374E+08, 0.17445E+08, 0.22619E+08, 0.29161E+08, 0.37391E+08, - 0.47698E+08, 0.60545E+08, 0.76487E+08, 0.96188E+08, 0.12043E+09, - 0.15015E+09, 0.18644E+09, 0.23059E+09, 0.28410E+09, 0.34874E+09, - 0.42657E+09, 0.51995E+09, 0.63167E+09, 0.76489E+09, 0.92329E+09, - 0.11111E+10, 0.13331E+10, 0.15950E+10, 0.19029E+10, 0.22641E+10, - 0.26867E+10, 0.31801E+10, 0.37547E+10, 0.44224E+10, 0.51965E+10, - 0.60921E+10, 0.71261E+10, 0.83174E+10, 0.96873E+10, 0.11260E+11, - 0.13061E+11, 0.15120E+11, 0.17471E+11, 0.20149E+11, 0.23196E+11, - 0.26656E+11, 0.30578E+11, 0.35019E+11, 0.40038E+11, 0.45703E+11, - 0.52087E+11, 0.59270E+11, 0.67343E+11, 0.76403E+11, 0.86556E+11, - 0.97921E+11, 0.11062E+12, 0.12481E+12, 0.14062E+12, 0.15824E+12, - 0.17783E+12, 0.19961E+12, 0.22377E+12, 0.25057E+12, 0.28024E+12, - 0.31308E+12, 0.34936E+12, 0.38943E+12, 0.43362E+12, 0.48232E+12, - 0.53593E+12, 0.59489E+12, 0.65968E+12, 0.73081E+12, 0.80883E+12, - 0.89434E+12, 0.98797E+12, 0.10904E+13, 0.12024E+13, 0.13247E+13, - 0.14582E+13, 0.16038E+13, 0.17625E+13, 0.19353E+13, 0.21233E+13, - 0.23278E+13, 0.25499E+13, 0.27911E+13, 0.30528E+13, 0.33366E+13, - 0.36442E+13, 0.39772E+13, 0.43376E+13, 0.47273E+13, 0.51486E+13, - 0.56036E+13, 0.60948E+13, 0.66248E+13, 0.71962E+13, 0.78119E+13, - 0.84751E+13, 0.91889E+13, 0.99569E+13, 0.10783E+14, 0.11670E+14, - 0.12623E+14, 0.13646E+14, 0.14744E+14, 0.15921E+14, 0.17183E+14, - 0.18535E+14]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.11735E+06, 0.21659E+06, 0.35745E+06, 0.55307E+06, 0.82078E+06, 0.11833E+07, 0.16700E+07, + 0.23189E+07, 0.31781E+07, 0.43084E+07, 0.57862E+07, 0.77065E+07, 0.10187E+08, 0.13374E+08, + 0.17445E+08, 0.22619E+08, 0.29161E+08, 0.37391E+08, 0.47698E+08, 0.60545E+08, 0.76487E+08, + 0.96188E+08, 0.12043E+09, 0.15015E+09, 0.18644E+09, 0.23059E+09, 0.28410E+09, 0.34874E+09, + 0.42657E+09, 0.51995E+09, 0.63167E+09, 0.76489E+09, 0.92329E+09, 0.11111E+10, 0.13331E+10, + 0.15950E+10, 0.19029E+10, 0.22641E+10, 0.26867E+10, 0.31801E+10, 0.37547E+10, 0.44224E+10, + 0.51965E+10, 0.60921E+10, 0.71261E+10, 0.83174E+10, 0.96873E+10, 0.11260E+11, 0.13061E+11, + 0.15120E+11, 0.17471E+11, 0.20149E+11, 0.23196E+11, 0.26656E+11, 0.30578E+11, 0.35019E+11, + 0.40038E+11, 0.45703E+11, 0.52087E+11, 0.59270E+11, 0.67343E+11, 0.76403E+11, 0.86556E+11, + 0.97921E+11, 0.11062E+12, 0.12481E+12, 0.14062E+12, 0.15824E+12, 0.17783E+12, 0.19961E+12, + 0.22377E+12, 0.25057E+12, 0.28024E+12, 0.31308E+12, 0.34936E+12, 0.38943E+12, 0.43362E+12, + 0.48232E+12, 0.53593E+12, 0.59489E+12, 0.65968E+12, 0.73081E+12, 0.80883E+12, 0.89434E+12, + 0.98797E+12, 0.10904E+13, 0.12024E+13, 0.13247E+13, 0.14582E+13, 0.16038E+13, 0.17625E+13, + 0.19353E+13, 0.21233E+13, 0.23278E+13, 0.25499E+13, 0.27911E+13, 0.30528E+13, 0.33366E+13, + 0.36442E+13, 0.39772E+13, 0.43376E+13, 0.47273E+13, 0.51486E+13, 0.56036E+13, 0.60948E+13, + 0.66248E+13, 0.71962E+13, 0.78119E+13, 0.84751E+13, 0.91889E+13, 0.99569E+13, 0.10783E+14, + 0.11670E+14, 0.12623E+14, 0.13646E+14, 0.14744E+14, 0.15921E+14, 0.17183E+14, 0.18535E+14]) # --------------- NOp 46: M = 36, I = 1 --------------------- M = 36 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(3.) -TIPS_ISO_HASH[(M, I)] = float32([0.63956E+02, 0.90185E+02, 0.11642E+03, - 0.14265E+03, 0.16889E+03, 0.19513E+03, 0.22138E+03, 0.24763E+03, - 0.27388E+03, 0.30013E+03, 0.32639E+03, 0.35266E+03, 0.37894E+03, - 0.40523E+03, 0.43155E+03, 0.45790E+03, 0.48429E+03, 0.51074E+03, - 0.53725E+03, 0.56383E+03, 0.59052E+03, 0.61731E+03, 0.64422E+03, - 0.67127E+03, 0.69846E+03, 0.72582E+03, 0.75335E+03, 0.78108E+03, - 0.80901E+03, 0.83715E+03, 0.86552E+03, 0.89413E+03, 0.92298E+03, - 0.95208E+03, 0.98144E+03, 0.10111E+04, 0.10410E+04, 0.10712E+04, - 0.11017E+04, 0.11325E+04, 0.11636E+04, 0.11950E+04, 0.12268E+04, - 0.12588E+04, 0.12912E+04, 0.13239E+04, 0.13570E+04, 0.13903E+04, - 0.14241E+04, 0.14581E+04, 0.14926E+04, 0.15273E+04, 0.15624E+04, - 0.15979E+04, 0.16337E+04, 0.16699E+04, 0.17065E+04, 0.17434E+04, - 0.17806E+04, 0.18183E+04, 0.18563E+04, 0.18947E+04, 0.19334E+04, - 0.19725E+04, 0.20120E+04, 0.20519E+04, 0.20921E+04, 0.21327E+04, - 0.21737E+04, 0.22151E+04, 0.22568E+04, 0.22990E+04, 0.23415E+04, - 0.23844E+04, 0.24276E+04, 0.24713E+04, 0.25153E+04, 0.25598E+04, - 0.26046E+04, 0.26497E+04, 0.26953E+04, 0.27413E+04, 0.27876E+04, - 0.28343E+04, 0.28815E+04, 0.29290E+04, 0.29769E+04, 0.30251E+04, - 0.30738E+04, 0.31229E+04, 0.31723E+04, 0.32222E+04, 0.32724E+04, - 0.33230E+04, 0.33740E+04, 0.34254E+04, 0.34772E+04, 0.35294E+04, - 0.35819E+04, 0.36349E+04, 0.36883E+04, 0.37420E+04, 0.37961E+04, - 0.38507E+04, 0.39056E+04, 0.39609E+04, 0.40166E+04, 0.40727E+04, - 0.41292E+04, 0.41861E+04, 0.42434E+04, 0.43010E+04, 0.43591E+04, - 0.44176E+04, 0.44764E+04, 0.45357E+04, 0.45953E+04, 0.46554E+04, - 0.47158E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.63956E+02, 0.90185E+02, 0.11642E+03, 0.14265E+03, 0.16889E+03, 0.19513E+03, 0.22138E+03, + 0.24763E+03, 0.27388E+03, 0.30013E+03, 0.32639E+03, 0.35266E+03, 0.37894E+03, 0.40523E+03, + 0.43155E+03, 0.45790E+03, 0.48429E+03, 0.51074E+03, 0.53725E+03, 0.56383E+03, 0.59052E+03, + 0.61731E+03, 0.64422E+03, 0.67127E+03, 0.69846E+03, 0.72582E+03, 0.75335E+03, 0.78108E+03, + 0.80901E+03, 0.83715E+03, 0.86552E+03, 0.89413E+03, 0.92298E+03, 0.95208E+03, 0.98144E+03, + 0.10111E+04, 0.10410E+04, 0.10712E+04, 0.11017E+04, 0.11325E+04, 0.11636E+04, 0.11950E+04, + 0.12268E+04, 0.12588E+04, 0.12912E+04, 0.13239E+04, 0.13570E+04, 0.13903E+04, 0.14241E+04, + 0.14581E+04, 0.14926E+04, 0.15273E+04, 0.15624E+04, 0.15979E+04, 0.16337E+04, 0.16699E+04, + 0.17065E+04, 0.17434E+04, 0.17806E+04, 0.18183E+04, 0.18563E+04, 0.18947E+04, 0.19334E+04, + 0.19725E+04, 0.20120E+04, 0.20519E+04, 0.20921E+04, 0.21327E+04, 0.21737E+04, 0.22151E+04, + 0.22568E+04, 0.22990E+04, 0.23415E+04, 0.23844E+04, 0.24276E+04, 0.24713E+04, 0.25153E+04, + 0.25598E+04, 0.26046E+04, 0.26497E+04, 0.26953E+04, 0.27413E+04, 0.27876E+04, 0.28343E+04, + 0.28815E+04, 0.29290E+04, 0.29769E+04, 0.30251E+04, 0.30738E+04, 0.31229E+04, 0.31723E+04, + 0.32222E+04, 0.32724E+04, 0.33230E+04, 0.33740E+04, 0.34254E+04, 0.34772E+04, 0.35294E+04, + 0.35819E+04, 0.36349E+04, 0.36883E+04, 0.37420E+04, 0.37961E+04, 0.38507E+04, 0.39056E+04, + 0.39609E+04, 0.40166E+04, 0.40727E+04, 0.41292E+04, 0.41861E+04, 0.42434E+04, 0.43010E+04, + 0.43591E+04, 0.44176E+04, 0.44764E+04, 0.45357E+04, 0.45953E+04, 0.46554E+04, 0.47158E+04]) # --------------- HOBr 169: M = 37, I = 1 --------------------- M = 37 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(8.) -TIPS_ISO_HASH[(M, I)] = float32([0.24445E+04, 0.41206E+04, 0.60683E+04, - 0.82610E+04, 0.10689E+05, 0.13352E+05, 0.16261E+05, 0.19427E+05, - 0.22867E+05, 0.26600E+05, 0.30643E+05, 0.35018E+05, 0.39745E+05, - 0.44844E+05, 0.50338E+05, 0.56249E+05, 0.62599E+05, 0.69410E+05, - 0.76706E+05, 0.84509E+05, 0.92845E+05, 0.10174E+06, 0.11121E+06, - 0.12128E+06, 0.13199E+06, 0.14335E+06, 0.15540E+06, 0.16815E+06, - 0.18165E+06, 0.19591E+06, 0.21096E+06, 0.22684E+06, 0.24358E+06, - 0.26120E+06, 0.27974E+06, 0.29922E+06, 0.31969E+06, 0.34118E+06, - 0.36372E+06, 0.38735E+06, 0.41210E+06, 0.43800E+06, 0.46511E+06, - 0.49345E+06, 0.52307E+06, 0.55400E+06, 0.58628E+06, 0.61997E+06, - 0.65509E+06, 0.69170E+06, 0.72984E+06, 0.76954E+06, 0.81087E+06, - 0.85386E+06, 0.89856E+06, 0.94502E+06, 0.99329E+06, 0.10434E+07, - 0.10955E+07, 0.11495E+07, 0.12055E+07, 0.12636E+07, 0.13238E+07, - 0.13862E+07, 0.14508E+07, 0.15177E+07, 0.15870E+07, 0.16587E+07, - 0.17328E+07, 0.18095E+07, 0.18888E+07, 0.19707E+07, 0.20554E+07, - 0.21428E+07, 0.22331E+07, 0.23263E+07, 0.24225E+07, 0.25217E+07, - 0.26241E+07, 0.27296E+07, 0.28385E+07, 0.29506E+07, 0.30662E+07, - 0.31853E+07, 0.33079E+07, 0.34341E+07, 0.35641E+07, 0.36979E+07, - 0.38355E+07, 0.39771E+07, 0.41228E+07, 0.42725E+07, 0.44265E+07, - 0.45848E+07, 0.47474E+07, 0.49145E+07, 0.50862E+07, 0.52624E+07, - 0.54435E+07, 0.56293E+07, 0.58201E+07, 0.60159E+07, 0.62168E+07, - 0.64229E+07, 0.66343E+07, 0.68511E+07, 0.70734E+07, 0.73013E+07, - 0.75349E+07, 0.77742E+07, 0.80196E+07, 0.82709E+07, 0.85283E+07, - 0.87920E+07, 0.90620E+07, 0.93385E+07, 0.96215E+07, 0.99112E+07, - 0.10208E+08]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.24445E+04, 0.41206E+04, 0.60683E+04, 0.82610E+04, 0.10689E+05, 0.13352E+05, 0.16261E+05, + 0.19427E+05, 0.22867E+05, 0.26600E+05, 0.30643E+05, 0.35018E+05, 0.39745E+05, 0.44844E+05, + 0.50338E+05, 0.56249E+05, 0.62599E+05, 0.69410E+05, 0.76706E+05, 0.84509E+05, 0.92845E+05, + 0.10174E+06, 0.11121E+06, 0.12128E+06, 0.13199E+06, 0.14335E+06, 0.15540E+06, 0.16815E+06, + 0.18165E+06, 0.19591E+06, 0.21096E+06, 0.22684E+06, 0.24358E+06, 0.26120E+06, 0.27974E+06, + 0.29922E+06, 0.31969E+06, 0.34118E+06, 0.36372E+06, 0.38735E+06, 0.41210E+06, 0.43800E+06, + 0.46511E+06, 0.49345E+06, 0.52307E+06, 0.55400E+06, 0.58628E+06, 0.61997E+06, 0.65509E+06, + 0.69170E+06, 0.72984E+06, 0.76954E+06, 0.81087E+06, 0.85386E+06, 0.89856E+06, 0.94502E+06, + 0.99329E+06, 0.10434E+07, 0.10955E+07, 0.11495E+07, 0.12055E+07, 0.12636E+07, 0.13238E+07, + 0.13862E+07, 0.14508E+07, 0.15177E+07, 0.15870E+07, 0.16587E+07, 0.17328E+07, 0.18095E+07, + 0.18888E+07, 0.19707E+07, 0.20554E+07, 0.21428E+07, 0.22331E+07, 0.23263E+07, 0.24225E+07, + 0.25217E+07, 0.26241E+07, 0.27296E+07, 0.28385E+07, 0.29506E+07, 0.30662E+07, 0.31853E+07, + 0.33079E+07, 0.34341E+07, 0.35641E+07, 0.36979E+07, 0.38355E+07, 0.39771E+07, 0.41228E+07, + 0.42725E+07, 0.44265E+07, 0.45848E+07, 0.47474E+07, 0.49145E+07, 0.50862E+07, 0.52624E+07, + 0.54435E+07, 0.56293E+07, 0.58201E+07, 0.60159E+07, 0.62168E+07, 0.64229E+07, 0.66343E+07, + 0.68511E+07, 0.70734E+07, 0.73013E+07, 0.75349E+07, 0.77742E+07, 0.80196E+07, 0.82709E+07, + 0.85283E+07, 0.87920E+07, 0.90620E+07, 0.93385E+07, 0.96215E+07, 0.99112E+07, 0.10208E+08]) # --------------- HOBr 161: M = 37, I = 2 --------------------- M = 37 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(8.) -TIPS_ISO_HASH[(M, I)] = float32([0.24350E+04, 0.41047E+04, 0.60448E+04, - 0.82291E+04, 0.10648E+05, 0.13301E+05, 0.16200E+05, 0.19355E+05, - 0.22784E+05, 0.26504E+05, 0.30534E+05, 0.34895E+05, 0.39607E+05, - 0.44691E+05, 0.50169E+05, 0.56063E+05, 0.62394E+05, 0.69186E+05, - 0.76461E+05, 0.84243E+05, 0.92555E+05, 0.10142E+06, 0.11087E+06, - 0.12091E+06, 0.13159E+06, 0.14292E+06, 0.15494E+06, 0.16766E+06, - 0.18112E+06, 0.19534E+06, 0.21036E+06, 0.22620E+06, 0.24289E+06, - 0.26047E+06, 0.27896E+06, 0.29840E+06, 0.31882E+06, 0.34025E+06, - 0.36274E+06, 0.38630E+06, 0.41099E+06, 0.43683E+06, 0.46387E+06, - 0.49215E+06, 0.52169E+06, 0.55255E+06, 0.58475E+06, 0.61836E+06, - 0.65340E+06, 0.68992E+06, 0.72796E+06, 0.76757E+06, 0.80880E+06, - 0.85169E+06, 0.89628E+06, 0.94263E+06, 0.99079E+06, 0.10408E+07, - 0.10927E+07, 0.11466E+07, 0.12025E+07, 0.12605E+07, 0.13205E+07, - 0.13828E+07, 0.14472E+07, 0.15140E+07, 0.15831E+07, 0.16546E+07, - 0.17286E+07, 0.18051E+07, 0.18842E+07, 0.19660E+07, 0.20504E+07, - 0.21377E+07, 0.22277E+07, 0.23207E+07, 0.24167E+07, 0.25157E+07, - 0.26178E+07, 0.27231E+07, 0.28317E+07, 0.29436E+07, 0.30589E+07, - 0.31777E+07, 0.33001E+07, 0.34260E+07, 0.35557E+07, 0.36892E+07, - 0.38265E+07, 0.39678E+07, 0.41131E+07, 0.42626E+07, 0.44162E+07, - 0.45741E+07, 0.47364E+07, 0.49031E+07, 0.50744E+07, 0.52503E+07, - 0.54309E+07, 0.56164E+07, 0.58067E+07, 0.60021E+07, 0.62025E+07, - 0.64081E+07, 0.66191E+07, 0.68354E+07, 0.70572E+07, 0.72846E+07, - 0.75177E+07, 0.77565E+07, 0.80013E+07, 0.82521E+07, 0.85090E+07, - 0.87721E+07, 0.90415E+07, 0.93173E+07, 0.95997E+07, 0.98888E+07, - 0.10185E+08]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.24350E+04, 0.41047E+04, 0.60448E+04, 0.82291E+04, 0.10648E+05, 0.13301E+05, 0.16200E+05, + 0.19355E+05, 0.22784E+05, 0.26504E+05, 0.30534E+05, 0.34895E+05, 0.39607E+05, 0.44691E+05, + 0.50169E+05, 0.56063E+05, 0.62394E+05, 0.69186E+05, 0.76461E+05, 0.84243E+05, 0.92555E+05, + 0.10142E+06, 0.11087E+06, 0.12091E+06, 0.13159E+06, 0.14292E+06, 0.15494E+06, 0.16766E+06, + 0.18112E+06, 0.19534E+06, 0.21036E+06, 0.22620E+06, 0.24289E+06, 0.26047E+06, 0.27896E+06, + 0.29840E+06, 0.31882E+06, 0.34025E+06, 0.36274E+06, 0.38630E+06, 0.41099E+06, 0.43683E+06, + 0.46387E+06, 0.49215E+06, 0.52169E+06, 0.55255E+06, 0.58475E+06, 0.61836E+06, 0.65340E+06, + 0.68992E+06, 0.72796E+06, 0.76757E+06, 0.80880E+06, 0.85169E+06, 0.89628E+06, 0.94263E+06, + 0.99079E+06, 0.10408E+07, 0.10927E+07, 0.11466E+07, 0.12025E+07, 0.12605E+07, 0.13205E+07, + 0.13828E+07, 0.14472E+07, 0.15140E+07, 0.15831E+07, 0.16546E+07, 0.17286E+07, 0.18051E+07, + 0.18842E+07, 0.19660E+07, 0.20504E+07, 0.21377E+07, 0.22277E+07, 0.23207E+07, 0.24167E+07, + 0.25157E+07, 0.26178E+07, 0.27231E+07, 0.28317E+07, 0.29436E+07, 0.30589E+07, 0.31777E+07, + 0.33001E+07, 0.34260E+07, 0.35557E+07, 0.36892E+07, 0.38265E+07, 0.39678E+07, 0.41131E+07, + 0.42626E+07, 0.44162E+07, 0.45741E+07, 0.47364E+07, 0.49031E+07, 0.50744E+07, 0.52503E+07, + 0.54309E+07, 0.56164E+07, 0.58067E+07, 0.60021E+07, 0.62025E+07, 0.64081E+07, 0.66191E+07, + 0.68354E+07, 0.70572E+07, 0.72846E+07, 0.75177E+07, 0.77565E+07, 0.80013E+07, 0.82521E+07, + 0.85090E+07, 0.87721E+07, 0.90415E+07, 0.93173E+07, 0.95997E+07, 0.98888E+07, 0.10185E+08]) # --------------- C2H4 221: M = 38, I = 1 --------------------- M = 38 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.95843E+03, 0.16137E+04, 0.23744E+04, - 0.32285E+04, 0.41694E+04, 0.51963E+04, 0.63143E+04, 0.75337E+04, - 0.88702E+04, 0.10344E+05, 0.11978E+05, 0.13802E+05, 0.15846E+05, - 0.18145E+05, 0.20740E+05, 0.23675E+05, 0.27000E+05, 0.30770E+05, - 0.35048E+05, 0.39905E+05, 0.45420E+05, 0.51680E+05, 0.58786E+05, - 0.66850E+05, 0.75997E+05, 0.86369E+05, 0.98123E+05, 0.11144E+06, - 0.12651E+06, 0.14356E+06, 0.16284E+06, 0.18463E+06, 0.20923E+06, - 0.23699E+06, 0.26831E+06, 0.30360E+06, 0.34334E+06, 0.38808E+06, - 0.43840E+06, 0.49495E+06, 0.55847E+06, 0.62976E+06, 0.70973E+06, - 0.79935E+06, 0.89973E+06, 0.10121E+07, 0.11378E+07, 0.12782E+07, - 0.14351E+07, 0.16102E+07, 0.18055E+07, 0.20231E+07, 0.22656E+07, - 0.25354E+07, 0.28356E+07, 0.31692E+07, 0.35398E+07, 0.39511E+07, - 0.44074E+07, 0.49132E+07, 0.54736E+07, 0.60940E+07, 0.67803E+07, - 0.75392E+07, 0.83776E+07, 0.93035E+07, 0.10325E+08, 0.11452E+08, - 0.12694E+08, 0.14062E+08, 0.15567E+08, 0.17224E+08, 0.19045E+08, - 0.21046E+08, 0.23243E+08, 0.25655E+08, 0.28300E+08, 0.31200E+08, - 0.34377E+08, 0.37856E+08, 0.41662E+08, 0.45826E+08, 0.50378E+08, - 0.55351E+08, 0.60781E+08, 0.66707E+08, 0.73172E+08, 0.80219E+08, - 0.87899E+08, 0.96262E+08, 0.10537E+09, 0.11527E+09, 0.12604E+09, - 0.13775E+09, 0.15047E+09, 0.16428E+09, 0.17927E+09, 0.19553E+09, - 0.21316E+09, 0.23226E+09, 0.25296E+09, 0.27537E+09, 0.29963E+09, - 0.32587E+09, 0.35425E+09, 0.38492E+09, 0.41805E+09, 0.45383E+09, - 0.49246E+09, 0.53413E+09, 0.57908E+09, 0.62754E+09, 0.67977E+09, - 0.73602E+09, 0.79660E+09, 0.86179E+09, 0.93194E+09, 0.10074E+10, - 0.10885E+10]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.95843E+03, 0.16137E+04, 0.23744E+04, 0.32285E+04, 0.41694E+04, 0.51963E+04, 0.63143E+04, + 0.75337E+04, 0.88702E+04, 0.10344E+05, 0.11978E+05, 0.13802E+05, 0.15846E+05, 0.18145E+05, + 0.20740E+05, 0.23675E+05, 0.27000E+05, 0.30770E+05, 0.35048E+05, 0.39905E+05, 0.45420E+05, + 0.51680E+05, 0.58786E+05, 0.66850E+05, 0.75997E+05, 0.86369E+05, 0.98123E+05, 0.11144E+06, + 0.12651E+06, 0.14356E+06, 0.16284E+06, 0.18463E+06, 0.20923E+06, 0.23699E+06, 0.26831E+06, + 0.30360E+06, 0.34334E+06, 0.38808E+06, 0.43840E+06, 0.49495E+06, 0.55847E+06, 0.62976E+06, + 0.70973E+06, 0.79935E+06, 0.89973E+06, 0.10121E+07, 0.11378E+07, 0.12782E+07, 0.14351E+07, + 0.16102E+07, 0.18055E+07, 0.20231E+07, 0.22656E+07, 0.25354E+07, 0.28356E+07, 0.31692E+07, + 0.35398E+07, 0.39511E+07, 0.44074E+07, 0.49132E+07, 0.54736E+07, 0.60940E+07, 0.67803E+07, + 0.75392E+07, 0.83776E+07, 0.93035E+07, 0.10325E+08, 0.11452E+08, 0.12694E+08, 0.14062E+08, + 0.15567E+08, 0.17224E+08, 0.19045E+08, 0.21046E+08, 0.23243E+08, 0.25655E+08, 0.28300E+08, + 0.31200E+08, 0.34377E+08, 0.37856E+08, 0.41662E+08, 0.45826E+08, 0.50378E+08, 0.55351E+08, + 0.60781E+08, 0.66707E+08, 0.73172E+08, 0.80219E+08, 0.87899E+08, 0.96262E+08, 0.10537E+09, + 0.11527E+09, 0.12604E+09, 0.13775E+09, 0.15047E+09, 0.16428E+09, 0.17927E+09, 0.19553E+09, + 0.21316E+09, 0.23226E+09, 0.25296E+09, 0.27537E+09, 0.29963E+09, 0.32587E+09, 0.35425E+09, + 0.38492E+09, 0.41805E+09, 0.45383E+09, 0.49246E+09, 0.53413E+09, 0.57908E+09, 0.62754E+09, + 0.67977E+09, 0.73602E+09, 0.79660E+09, 0.86179E+09, 0.93194E+09, 0.10074E+10, 0.10885E+10]) # --------------- C2H4 231: M = 38, I = 2 --------------------- M = 38 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.39228E+04, 0.66051E+04, 0.97190E+04, - 0.13215E+05, 0.17066E+05, 0.21270E+05, 0.25846E+05, 0.30838E+05, - 0.36309E+05, 0.42341E+05, 0.49032E+05, 0.56496E+05, 0.64862E+05, - 0.74275E+05, 0.84897E+05, 0.96912E+05, 0.11052E+06, 0.12595E+06, - 0.14347E+06, 0.16335E+06, 0.18592E+06, 0.21155E+06, 0.24064E+06, - 0.27365E+06, 0.31109E+06, 0.35354E+06, 0.40166E+06, 0.45615E+06, - 0.51785E+06, 0.58765E+06, 0.66657E+06, 0.75575E+06, 0.85646E+06, - 0.97011E+06, 0.10983E+07, 0.12428E+07, 0.14055E+07, 0.15886E+07, - 0.17945E+07, 0.20260E+07, 0.22861E+07, 0.25779E+07, 0.29052E+07, - 0.32721E+07, 0.36830E+07, 0.41429E+07, 0.46573E+07, 0.52323E+07, - 0.58744E+07, 0.65912E+07, 0.73906E+07, 0.82816E+07, 0.92740E+07, - 0.10379E+08, 0.11607E+08, 0.12973E+08, 0.14490E+08, 0.16174E+08, - 0.18042E+08, 0.20112E+08, 0.22406E+08, 0.24945E+08, 0.27755E+08, - 0.30861E+08, 0.34293E+08, 0.38083E+08, 0.42266E+08, 0.46878E+08, - 0.51961E+08, 0.57560E+08, 0.63724E+08, 0.70504E+08, 0.77959E+08, - 0.86150E+08, 0.95145E+08, 0.10502E+09, 0.11585E+09, 0.12772E+09, - 0.14072E+09, 0.15496E+09, 0.17054E+09, 0.18759E+09, 0.20622E+09, - 0.22658E+09, 0.24880E+09, 0.27306E+09, 0.29952E+09, 0.32837E+09, - 0.35981E+09, 0.39404E+09, 0.43131E+09, 0.47186E+09, 0.51595E+09, - 0.56387E+09, 0.61594E+09, 0.67247E+09, 0.73382E+09, 0.80038E+09, - 0.87255E+09, 0.95076E+09, 0.10355E+10, 0.11272E+10, 0.12265E+10, - 0.13339E+10, 0.14501E+10, 0.15756E+10, 0.17113E+10, 0.18577E+10, - 0.20159E+10, 0.21865E+10, 0.23705E+10, 0.25688E+10, 0.27826E+10, - 0.30129E+10, 0.32608E+10, 0.35277E+10, 0.38149E+10, 0.41237E+10, - 0.44557E+10]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.39228E+04, 0.66051E+04, 0.97190E+04, 0.13215E+05, 0.17066E+05, 0.21270E+05, 0.25846E+05, + 0.30838E+05, 0.36309E+05, 0.42341E+05, 0.49032E+05, 0.56496E+05, 0.64862E+05, 0.74275E+05, + 0.84897E+05, 0.96912E+05, 0.11052E+06, 0.12595E+06, 0.14347E+06, 0.16335E+06, 0.18592E+06, + 0.21155E+06, 0.24064E+06, 0.27365E+06, 0.31109E+06, 0.35354E+06, 0.40166E+06, 0.45615E+06, + 0.51785E+06, 0.58765E+06, 0.66657E+06, 0.75575E+06, 0.85646E+06, 0.97011E+06, 0.10983E+07, + 0.12428E+07, 0.14055E+07, 0.15886E+07, 0.17945E+07, 0.20260E+07, 0.22861E+07, 0.25779E+07, + 0.29052E+07, 0.32721E+07, 0.36830E+07, 0.41429E+07, 0.46573E+07, 0.52323E+07, 0.58744E+07, + 0.65912E+07, 0.73906E+07, 0.82816E+07, 0.92740E+07, 0.10379E+08, 0.11607E+08, 0.12973E+08, + 0.14490E+08, 0.16174E+08, 0.18042E+08, 0.20112E+08, 0.22406E+08, 0.24945E+08, 0.27755E+08, + 0.30861E+08, 0.34293E+08, 0.38083E+08, 0.42266E+08, 0.46878E+08, 0.51961E+08, 0.57560E+08, + 0.63724E+08, 0.70504E+08, 0.77959E+08, 0.86150E+08, 0.95145E+08, 0.10502E+09, 0.11585E+09, + 0.12772E+09, 0.14072E+09, 0.15496E+09, 0.17054E+09, 0.18759E+09, 0.20622E+09, 0.22658E+09, + 0.24880E+09, 0.27306E+09, 0.29952E+09, 0.32837E+09, 0.35981E+09, 0.39404E+09, 0.43131E+09, + 0.47186E+09, 0.51595E+09, 0.56387E+09, 0.61594E+09, 0.67247E+09, 0.73382E+09, 0.80038E+09, + 0.87255E+09, 0.95076E+09, 0.10355E+10, 0.11272E+10, 0.12265E+10, 0.13339E+10, 0.14501E+10, + 0.15756E+10, 0.17113E+10, 0.18577E+10, 0.20159E+10, 0.21865E+10, 0.23705E+10, 0.25688E+10, + 0.27826E+10, 0.30129E+10, 0.32608E+10, 0.35277E+10, 0.38149E+10, 0.41237E+10, 0.44557E+10]) # --------------- CH3OH 2161: M = 39, I = 1 --------------------- not in TIPS-2011 M = 39 @@ -9100,601 +7845,461 @@ def AtoB(aa, A, B, npt): M = 40 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(4.) -TIPS_ISO_HASH[(M, I)] = float32([0.70299E+04, 0.11847E+05, 0.17442E+05, - 0.23741E+05, 0.30723E+05, 0.38408E+05, 0.46851E+05, 0.56138E+05, - 0.66375E+05, 0.77692E+05, 0.90239E+05, 0.10418E+06, 0.11972E+06, - 0.13704E+06, 0.15639E+06, 0.17801E+06, 0.20218E+06, 0.22920E+06, - 0.25940E+06, 0.29316E+06, 0.33087E+06, 0.37296E+06, 0.41992E+06, - 0.47229E+06, 0.53062E+06, 0.59557E+06, 0.66781E+06, 0.74812E+06, - 0.83731E+06, 0.93629E+06, 0.10461E+07, 0.11677E+07, 0.13023E+07, - 0.14513E+07, 0.16159E+07, 0.17978E+07, 0.19985E+07, 0.22199E+07, - 0.24638E+07, 0.27324E+07, 0.30280E+07, 0.33529E+07, 0.37099E+07, - 0.41019E+07, 0.45319E+07, 0.50034E+07, 0.55199E+07, 0.60853E+07, - 0.67039E+07, 0.73801E+07, 0.81189E+07, 0.89255E+07, 0.98056E+07, - 0.10765E+08, 0.11811E+08, 0.12949E+08, 0.14188E+08, 0.15535E+08, - 0.17000E+08, 0.18590E+08, 0.20317E+08, 0.22190E+08, 0.24220E+08, - 0.26421E+08, 0.28804E+08, 0.31383E+08, 0.34173E+08, 0.37189E+08, - 0.40448E+08, 0.43967E+08, 0.47765E+08, 0.51862E+08, 0.56280E+08, - 0.61040E+08, 0.66167E+08, 0.71686E+08, 0.77624E+08, 0.84009E+08, - 0.90873E+08, 0.98247E+08, 0.10616E+09, 0.11466E+09, 0.12378E+09, - 0.13356E+09, 0.14403E+09, 0.15526E+09, 0.16728E+09, 0.18014E+09, - 0.19391E+09, 0.20863E+09, 0.22436E+09, 0.24117E+09, 0.25913E+09, - 0.27830E+09, 0.29875E+09, 0.32057E+09, 0.34384E+09, 0.36864E+09, - 0.39506E+09, 0.42320E+09, 0.45316E+09, 0.48504E+09, 0.51896E+09, - 0.55502E+09, 0.59336E+09, 0.63410E+09, 0.67738E+09, 0.72334E+09, - 0.77212E+09, 0.82388E+09, 0.87879E+09, 0.93701E+09, 0.99873E+09, - 0.10641E+10, 0.11334E+10, 0.12068E+10, 0.12845E+10, 0.13667E+10, - 0.14536E+10]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.70299E+04, 0.11847E+05, 0.17442E+05, 0.23741E+05, 0.30723E+05, 0.38408E+05, 0.46851E+05, + 0.56138E+05, 0.66375E+05, 0.77692E+05, 0.90239E+05, 0.10418E+06, 0.11972E+06, 0.13704E+06, + 0.15639E+06, 0.17801E+06, 0.20218E+06, 0.22920E+06, 0.25940E+06, 0.29316E+06, 0.33087E+06, + 0.37296E+06, 0.41992E+06, 0.47229E+06, 0.53062E+06, 0.59557E+06, 0.66781E+06, 0.74812E+06, + 0.83731E+06, 0.93629E+06, 0.10461E+07, 0.11677E+07, 0.13023E+07, 0.14513E+07, 0.16159E+07, + 0.17978E+07, 0.19985E+07, 0.22199E+07, 0.24638E+07, 0.27324E+07, 0.30280E+07, 0.33529E+07, + 0.37099E+07, 0.41019E+07, 0.45319E+07, 0.50034E+07, 0.55199E+07, 0.60853E+07, 0.67039E+07, + 0.73801E+07, 0.81189E+07, 0.89255E+07, 0.98056E+07, 0.10765E+08, 0.11811E+08, 0.12949E+08, + 0.14188E+08, 0.15535E+08, 0.17000E+08, 0.18590E+08, 0.20317E+08, 0.22190E+08, 0.24220E+08, + 0.26421E+08, 0.28804E+08, 0.31383E+08, 0.34173E+08, 0.37189E+08, 0.40448E+08, 0.43967E+08, + 0.47765E+08, 0.51862E+08, 0.56280E+08, 0.61040E+08, 0.66167E+08, 0.71686E+08, 0.77624E+08, + 0.84009E+08, 0.90873E+08, 0.98247E+08, 0.10616E+09, 0.11466E+09, 0.12378E+09, 0.13356E+09, + 0.14403E+09, 0.15526E+09, 0.16728E+09, 0.18014E+09, 0.19391E+09, 0.20863E+09, 0.22436E+09, + 0.24117E+09, 0.25913E+09, 0.27830E+09, 0.29875E+09, 0.32057E+09, 0.34384E+09, 0.36864E+09, + 0.39506E+09, 0.42320E+09, 0.45316E+09, 0.48504E+09, 0.51896E+09, 0.55502E+09, 0.59336E+09, + 0.63410E+09, 0.67738E+09, 0.72334E+09, 0.77212E+09, 0.82388E+09, 0.87879E+09, 0.93701E+09, + 0.99873E+09, 0.10641E+10, 0.11334E+10, 0.12068E+10, 0.12845E+10, 0.13667E+10, 0.14536E+10]) # --------------- CH3Br 211: M = 40, I = 2 --------------------- M = 40 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(4.) -TIPS_ISO_HASH[(M, I)] = float32([0.70566E+04, 0.11892E+05, 0.17508E+05, - 0.23832E+05, 0.30841E+05, 0.38557E+05, 0.47036E+05, 0.56362E+05, - 0.66644E+05, 0.78011E+05, 0.90615E+05, 0.10462E+06, 0.12023E+06, - 0.13763E+06, 0.15707E+06, 0.17880E+06, 0.20308E+06, 0.23023E+06, - 0.26059E+06, 0.29451E+06, 0.33240E+06, 0.37471E+06, 0.42191E+06, - 0.47453E+06, 0.53316E+06, 0.59843E+06, 0.67104E+06, 0.75176E+06, - 0.84141E+06, 0.94090E+06, 0.10512E+07, 0.11735E+07, 0.13088E+07, - 0.14585E+07, 0.16241E+07, 0.18069E+07, 0.20086E+07, 0.22312E+07, - 0.24764E+07, 0.27464E+07, 0.30435E+07, 0.33702E+07, 0.37291E+07, - 0.41231E+07, 0.45554E+07, 0.50294E+07, 0.55486E+07, 0.61171E+07, - 0.67389E+07, 0.74188E+07, 0.81616E+07, 0.89725E+07, 0.98573E+07, - 0.10822E+08, 0.11873E+08, 0.13018E+08, 0.14263E+08, 0.15618E+08, - 0.17090E+08, 0.18689E+08, 0.20425E+08, 0.22308E+08, 0.24350E+08, - 0.26563E+08, 0.28959E+08, 0.31552E+08, 0.34357E+08, 0.37389E+08, - 0.40666E+08, 0.44204E+08, 0.48023E+08, 0.52143E+08, 0.56585E+08, - 0.61371E+08, 0.66526E+08, 0.72076E+08, 0.78046E+08, 0.84467E+08, - 0.91369E+08, 0.98783E+08, 0.10674E+09, 0.11529E+09, 0.12446E+09, - 0.13429E+09, 0.14482E+09, 0.15611E+09, 0.16820E+09, 0.18113E+09, - 0.19497E+09, 0.20978E+09, 0.22560E+09, 0.24250E+09, 0.26056E+09, - 0.27983E+09, 0.30040E+09, 0.32234E+09, 0.34574E+09, 0.37068E+09, - 0.39725E+09, 0.42555E+09, 0.45567E+09, 0.48773E+09, 0.52184E+09, - 0.55811E+09, 0.59666E+09, 0.63763E+09, 0.68115E+09, 0.72736E+09, - 0.77642E+09, 0.82847E+09, 0.88368E+09, 0.94223E+09, 0.10043E+10, - 0.10701E+10, 0.11397E+10, 0.12135E+10, 0.12916E+10, 0.13743E+10, - 0.14618E+10]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.70566E+04, 0.11892E+05, 0.17508E+05, 0.23832E+05, 0.30841E+05, 0.38557E+05, 0.47036E+05, + 0.56362E+05, 0.66644E+05, 0.78011E+05, 0.90615E+05, 0.10462E+06, 0.12023E+06, 0.13763E+06, + 0.15707E+06, 0.17880E+06, 0.20308E+06, 0.23023E+06, 0.26059E+06, 0.29451E+06, 0.33240E+06, + 0.37471E+06, 0.42191E+06, 0.47453E+06, 0.53316E+06, 0.59843E+06, 0.67104E+06, 0.75176E+06, + 0.84141E+06, 0.94090E+06, 0.10512E+07, 0.11735E+07, 0.13088E+07, 0.14585E+07, 0.16241E+07, + 0.18069E+07, 0.20086E+07, 0.22312E+07, 0.24764E+07, 0.27464E+07, 0.30435E+07, 0.33702E+07, + 0.37291E+07, 0.41231E+07, 0.45554E+07, 0.50294E+07, 0.55486E+07, 0.61171E+07, 0.67389E+07, + 0.74188E+07, 0.81616E+07, 0.89725E+07, 0.98573E+07, 0.10822E+08, 0.11873E+08, 0.13018E+08, + 0.14263E+08, 0.15618E+08, 0.17090E+08, 0.18689E+08, 0.20425E+08, 0.22308E+08, 0.24350E+08, + 0.26563E+08, 0.28959E+08, 0.31552E+08, 0.34357E+08, 0.37389E+08, 0.40666E+08, 0.44204E+08, + 0.48023E+08, 0.52143E+08, 0.56585E+08, 0.61371E+08, 0.66526E+08, 0.72076E+08, 0.78046E+08, + 0.84467E+08, 0.91369E+08, 0.98783E+08, 0.10674E+09, 0.11529E+09, 0.12446E+09, 0.13429E+09, + 0.14482E+09, 0.15611E+09, 0.16820E+09, 0.18113E+09, 0.19497E+09, 0.20978E+09, 0.22560E+09, + 0.24250E+09, 0.26056E+09, 0.27983E+09, 0.30040E+09, 0.32234E+09, 0.34574E+09, 0.37068E+09, + 0.39725E+09, 0.42555E+09, 0.45567E+09, 0.48773E+09, 0.52184E+09, 0.55811E+09, 0.59666E+09, + 0.63763E+09, 0.68115E+09, 0.72736E+09, 0.77642E+09, 0.82847E+09, 0.88368E+09, 0.94223E+09, + 0.10043E+10, 0.10701E+10, 0.11397E+10, 0.12135E+10, 0.12916E+10, 0.13743E+10, 0.14618E+10]) # --------------- CH3CN 2124: M = 41, I = 1 --------------------- M = 41 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(3.) -TIPS_ISO_HASH[(M, I)] = float32([0.54361E+04, 0.91953E+04, 0.13708E+05, - 0.19097E+05, 0.25531E+05, 0.33206E+05, 0.42337E+05, 0.53173E+05, - 0.66002E+05, 0.81163E+05, 0.99053E+05, 0.12014E+06, 0.14496E+06, - 0.17414E+06, 0.20843E+06, 0.24866E+06, 0.29580E+06, 0.35099E+06, - 0.41551E+06, 0.49085E+06, 0.57871E+06, 0.68104E+06, 0.80008E+06, - 0.93836E+06, 0.10988E+07, 0.12848E+07, 0.14999E+07, 0.17487E+07, - 0.20359E+07, 0.23670E+07, 0.27484E+07, 0.31871E+07, 0.36912E+07, - 0.42697E+07, 0.49328E+07, 0.56921E+07, 0.65605E+07, 0.75526E+07, - 0.86847E+07, 0.99753E+07, 0.11445E+08, 0.13116E+08, 0.15016E+08, - 0.17172E+08, 0.19617E+08, 0.22386E+08, 0.25520E+08, 0.29063E+08, - 0.33064E+08, 0.37578E+08, 0.42667E+08, 0.48397E+08, 0.54844E+08, - 0.62090E+08, 0.70228E+08, 0.79358E+08, 0.89592E+08, 0.10105E+09, - 0.11388E+09, 0.12822E+09, 0.14424E+09, 0.16212E+09, 0.18205E+09, - 0.20427E+09, 0.22900E+09, 0.25652E+09, 0.28710E+09, 0.32107E+09, - 0.35877E+09, 0.40059E+09, 0.44692E+09, 0.49822E+09, 0.55500E+09, - 0.61777E+09, 0.68712E+09, 0.76370E+09, 0.84819E+09, 0.94135E+09, - 0.10440E+10, 0.11570E+10, 0.12814E+10, 0.14181E+10, 0.15684E+10, - 0.17334E+10, 0.19145E+10, 0.21131E+10, 0.23308E+10, 0.25693E+10, - 0.28304E+10, 0.31161E+10, 0.34285E+10, 0.37698E+10, 0.41426E+10, - 0.45496E+10, 0.49935E+10, 0.54776E+10, 0.60051E+10, 0.65796E+10, - 0.72049E+10, 0.78853E+10, 0.86251E+10, 0.94291E+10, 0.10303E+11, - 0.11251E+11, 0.12280E+11, 0.13396E+11, 0.14606E+11, 0.15916E+11, - 0.17336E+11, 0.18873E+11, 0.20536E+11, 0.22334E+11, 0.24278E+11, - 0.26379E+11, 0.28647E+11, 0.31096E+11, 0.33739E+11, 0.36589E+11, - 0.39661E+11]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.54361E+04, 0.91953E+04, 0.13708E+05, 0.19097E+05, 0.25531E+05, 0.33206E+05, 0.42337E+05, + 0.53173E+05, 0.66002E+05, 0.81163E+05, 0.99053E+05, 0.12014E+06, 0.14496E+06, 0.17414E+06, + 0.20843E+06, 0.24866E+06, 0.29580E+06, 0.35099E+06, 0.41551E+06, 0.49085E+06, 0.57871E+06, + 0.68104E+06, 0.80008E+06, 0.93836E+06, 0.10988E+07, 0.12848E+07, 0.14999E+07, 0.17487E+07, + 0.20359E+07, 0.23670E+07, 0.27484E+07, 0.31871E+07, 0.36912E+07, 0.42697E+07, 0.49328E+07, + 0.56921E+07, 0.65605E+07, 0.75526E+07, 0.86847E+07, 0.99753E+07, 0.11445E+08, 0.13116E+08, + 0.15016E+08, 0.17172E+08, 0.19617E+08, 0.22386E+08, 0.25520E+08, 0.29063E+08, 0.33064E+08, + 0.37578E+08, 0.42667E+08, 0.48397E+08, 0.54844E+08, 0.62090E+08, 0.70228E+08, 0.79358E+08, + 0.89592E+08, 0.10105E+09, 0.11388E+09, 0.12822E+09, 0.14424E+09, 0.16212E+09, 0.18205E+09, + 0.20427E+09, 0.22900E+09, 0.25652E+09, 0.28710E+09, 0.32107E+09, 0.35877E+09, 0.40059E+09, + 0.44692E+09, 0.49822E+09, 0.55500E+09, 0.61777E+09, 0.68712E+09, 0.76370E+09, 0.84819E+09, + 0.94135E+09, 0.10440E+10, 0.11570E+10, 0.12814E+10, 0.14181E+10, 0.15684E+10, 0.17334E+10, + 0.19145E+10, 0.21131E+10, 0.23308E+10, 0.25693E+10, 0.28304E+10, 0.31161E+10, 0.34285E+10, + 0.37698E+10, 0.41426E+10, 0.45496E+10, 0.49935E+10, 0.54776E+10, 0.60051E+10, 0.65796E+10, + 0.72049E+10, 0.78853E+10, 0.86251E+10, 0.94291E+10, 0.10303E+11, 0.11251E+11, 0.12280E+11, + 0.13396E+11, 0.14606E+11, 0.15916E+11, 0.17336E+11, 0.18873E+11, 0.20536E+11, 0.22334E+11, + 0.24278E+11, 0.26379E+11, 0.28647E+11, 0.31096E+11, 0.33739E+11, 0.36589E+11, 0.39661E+11]) # --------------- CH3CN 2134: M = 41, I = 2 --------------------- not in HITRAN-2012 M = 41 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.10906E+05, 0.18458E+05, 0.27552E+05, - 0.38455E+05, 0.51523E+05, 0.67161E+05, 0.85818E+05, 0.10801E+06, - 0.13434E+06, 0.16550E+06, 0.20234E+06, 0.24581E+06, 0.29705E+06, - 0.35737E+06, 0.42831E+06, 0.51162E+06, 0.60936E+06, 0.72387E+06, - 0.85786E+06, 0.10145E+07, 0.11972E+07, 0.14102E+07, 0.16582E+07, - 0.19465E+07, 0.22813E+07, 0.26695E+07, 0.31190E+07, 0.36390E+07, - 0.42397E+07, 0.49328E+07, 0.57314E+07, 0.66507E+07, 0.77076E+07, - 0.89211E+07, 0.10313E+08, 0.11907E+08, 0.13732E+08, 0.15817E+08, - 0.18198E+08, 0.20914E+08, 0.24007E+08, 0.27527E+08, 0.31529E+08, - 0.36073E+08, 0.41228E+08, 0.47070E+08, 0.53683E+08, 0.61162E+08, - 0.69612E+08, 0.79149E+08, 0.89903E+08, 0.10202E+09, 0.11565E+09, - 0.13098E+09, 0.14820E+09, 0.16753E+09, 0.18921E+09, 0.21349E+09, - 0.24066E+09, 0.27106E+09, 0.30502E+09, 0.34293E+09, 0.38523E+09, - 0.43237E+09, 0.48486E+09, 0.54328E+09, 0.60823E+09, 0.68039E+09, - 0.76049E+09, 0.84935E+09, 0.94784E+09, 0.10569E+10, 0.11777E+10, - 0.13112E+10, 0.14588E+10, 0.16217E+10, 0.18016E+10, 0.19999E+10, - 0.22185E+10, 0.24592E+10, 0.27241E+10, 0.30155E+10, 0.33357E+10, - 0.36875E+10, 0.40736E+10, 0.44971E+10, 0.49615E+10, 0.54702E+10, - 0.60273E+10, 0.66369E+10, 0.73035E+10, 0.80322E+10, 0.88282E+10, - 0.96972E+10, 0.10645E+11, 0.11679E+11, 0.12806E+11, 0.14034E+11, - 0.15370E+11, 0.16824E+11, 0.18406E+11, 0.20125E+11, 0.21992E+11, - 0.24020E+11, 0.26221E+11, 0.28608E+11, 0.31197E+11, 0.34002E+11, - 0.37040E+11, 0.40330E+11, 0.43889E+11, 0.47739E+11, 0.51902E+11, - 0.56400E+11, 0.61259E+11, 0.66504E+11, 0.72165E+11, 0.78272E+11, - 0.84856E+11]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.10906E+05, 0.18458E+05, 0.27552E+05, 0.38455E+05, 0.51523E+05, 0.67161E+05, 0.85818E+05, + 0.10801E+06, 0.13434E+06, 0.16550E+06, 0.20234E+06, 0.24581E+06, 0.29705E+06, 0.35737E+06, + 0.42831E+06, 0.51162E+06, 0.60936E+06, 0.72387E+06, 0.85786E+06, 0.10145E+07, 0.11972E+07, + 0.14102E+07, 0.16582E+07, 0.19465E+07, 0.22813E+07, 0.26695E+07, 0.31190E+07, 0.36390E+07, + 0.42397E+07, 0.49328E+07, 0.57314E+07, 0.66507E+07, 0.77076E+07, 0.89211E+07, 0.10313E+08, + 0.11907E+08, 0.13732E+08, 0.15817E+08, 0.18198E+08, 0.20914E+08, 0.24007E+08, 0.27527E+08, + 0.31529E+08, 0.36073E+08, 0.41228E+08, 0.47070E+08, 0.53683E+08, 0.61162E+08, 0.69612E+08, + 0.79149E+08, 0.89903E+08, 0.10202E+09, 0.11565E+09, 0.13098E+09, 0.14820E+09, 0.16753E+09, + 0.18921E+09, 0.21349E+09, 0.24066E+09, 0.27106E+09, 0.30502E+09, 0.34293E+09, 0.38523E+09, + 0.43237E+09, 0.48486E+09, 0.54328E+09, 0.60823E+09, 0.68039E+09, 0.76049E+09, 0.84935E+09, + 0.94784E+09, 0.10569E+10, 0.11777E+10, 0.13112E+10, 0.14588E+10, 0.16217E+10, 0.18016E+10, + 0.19999E+10, 0.22185E+10, 0.24592E+10, 0.27241E+10, 0.30155E+10, 0.33357E+10, 0.36875E+10, + 0.40736E+10, 0.44971E+10, 0.49615E+10, 0.54702E+10, 0.60273E+10, 0.66369E+10, 0.73035E+10, + 0.80322E+10, 0.88282E+10, 0.96972E+10, 0.10645E+11, 0.11679E+11, 0.12806E+11, 0.14034E+11, + 0.15370E+11, 0.16824E+11, 0.18406E+11, 0.20125E+11, 0.21992E+11, 0.24020E+11, 0.26221E+11, + 0.28608E+11, 0.31197E+11, 0.34002E+11, 0.37040E+11, 0.40330E+11, 0.43889E+11, 0.47739E+11, + 0.51902E+11, 0.56400E+11, 0.61259E+11, 0.66504E+11, 0.72165E+11, 0.78272E+11, 0.84856E+11]) # --------------- CH3CN 3124: M = 41, I = 3 --------------------- not in HITRAN-2012 M = 41 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.11223E+05, 0.18985E+05, 0.28307E+05, - 0.39441E+05, 0.52744E+05, 0.68620E+05, 0.87523E+05, 0.10997E+06, - 0.13658E+06, 0.16806E+06, 0.20524E+06, 0.24910E+06, 0.30080E+06, - 0.36165E+06, 0.43319E+06, 0.51722E+06, 0.61579E+06, 0.73127E+06, - 0.86640E+06, 0.10243E+07, 0.12086E+07, 0.14234E+07, 0.16735E+07, - 0.19642E+07, 0.23017E+07, 0.26931E+07, 0.31464E+07, 0.36706E+07, - 0.42762E+07, 0.49749E+07, 0.57801E+07, 0.67069E+07, 0.77722E+07, - 0.89955E+07, 0.10398E+08, 0.12006E+08, 0.13845E+08, 0.15947E+08, - 0.18346E+08, 0.21083E+08, 0.24201E+08, 0.27748E+08, 0.31781E+08, - 0.36361E+08, 0.41556E+08, 0.47442E+08, 0.54106E+08, 0.61643E+08, - 0.70157E+08, 0.79767E+08, 0.90604E+08, 0.10281E+09, 0.11655E+09, - 0.13199E+09, 0.14935E+09, 0.16882E+09, 0.19065E+09, 0.21512E+09, - 0.24250E+09, 0.27312E+09, 0.30733E+09, 0.34553E+09, 0.38814E+09, - 0.43562E+09, 0.48851E+09, 0.54736E+09, 0.61279E+09, 0.68548E+09, - 0.76617E+09, 0.85568E+09, 0.95489E+09, 0.10648E+10, 0.11864E+10, - 0.13209E+10, 0.14695E+10, 0.16337E+10, 0.18148E+10, 0.20146E+10, - 0.22348E+10, 0.24772E+10, 0.27441E+10, 0.30375E+10, 0.33601E+10, - 0.37143E+10, 0.41032E+10, 0.45298E+10, 0.49975E+10, 0.55099E+10, - 0.60709E+10, 0.66849E+10, 0.73563E+10, 0.80902E+10, 0.88918E+10, - 0.97670E+10, 0.10722E+11, 0.11763E+11, 0.12898E+11, 0.14134E+11, - 0.15480E+11, 0.16945E+11, 0.18537E+11, 0.20269E+11, 0.22149E+11, - 0.24191E+11, 0.26408E+11, 0.28812E+11, 0.31419E+11, 0.34244E+11, - 0.37303E+11, 0.40616E+11, 0.44201E+11, 0.48078E+11, 0.52269E+11, - 0.56799E+11, 0.61692E+11, 0.66974E+11, 0.72675E+11, 0.78824E+11, - 0.85454E+11]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.11223E+05, 0.18985E+05, 0.28307E+05, 0.39441E+05, 0.52744E+05, 0.68620E+05, 0.87523E+05, + 0.10997E+06, 0.13658E+06, 0.16806E+06, 0.20524E+06, 0.24910E+06, 0.30080E+06, 0.36165E+06, + 0.43319E+06, 0.51722E+06, 0.61579E+06, 0.73127E+06, 0.86640E+06, 0.10243E+07, 0.12086E+07, + 0.14234E+07, 0.16735E+07, 0.19642E+07, 0.23017E+07, 0.26931E+07, 0.31464E+07, 0.36706E+07, + 0.42762E+07, 0.49749E+07, 0.57801E+07, 0.67069E+07, 0.77722E+07, 0.89955E+07, 0.10398E+08, + 0.12006E+08, 0.13845E+08, 0.15947E+08, 0.18346E+08, 0.21083E+08, 0.24201E+08, 0.27748E+08, + 0.31781E+08, 0.36361E+08, 0.41556E+08, 0.47442E+08, 0.54106E+08, 0.61643E+08, 0.70157E+08, + 0.79767E+08, 0.90604E+08, 0.10281E+09, 0.11655E+09, 0.13199E+09, 0.14935E+09, 0.16882E+09, + 0.19065E+09, 0.21512E+09, 0.24250E+09, 0.27312E+09, 0.30733E+09, 0.34553E+09, 0.38814E+09, + 0.43562E+09, 0.48851E+09, 0.54736E+09, 0.61279E+09, 0.68548E+09, 0.76617E+09, 0.85568E+09, + 0.95489E+09, 0.10648E+10, 0.11864E+10, 0.13209E+10, 0.14695E+10, 0.16337E+10, 0.18148E+10, + 0.20146E+10, 0.22348E+10, 0.24772E+10, 0.27441E+10, 0.30375E+10, 0.33601E+10, 0.37143E+10, + 0.41032E+10, 0.45298E+10, 0.49975E+10, 0.55099E+10, 0.60709E+10, 0.66849E+10, 0.73563E+10, + 0.80902E+10, 0.88918E+10, 0.97670E+10, 0.10722E+11, 0.11763E+11, 0.12898E+11, 0.14134E+11, + 0.15480E+11, 0.16945E+11, 0.18537E+11, 0.20269E+11, 0.22149E+11, 0.24191E+11, 0.26408E+11, + 0.28812E+11, 0.31419E+11, 0.34244E+11, 0.37303E+11, 0.40616E+11, 0.44201E+11, 0.48078E+11, + 0.52269E+11, 0.56799E+11, 0.61692E+11, 0.66974E+11, 0.72675E+11, 0.78824E+11, 0.85454E+11]) # --------------- CH3CN 3134: M = 41, I = 4 --------------------- not in HITRAN-2012 M = 41 I = 4 TIPS_GSI_HASH[(M, I)] = __FloatType__(12.) -TIPS_ISO_HASH[(M, I)] = float32([0.22522E+05, 0.38117E+05, 0.56899E+05, - 0.79412E+05, 0.10640E+06, 0.13870E+06, 0.17726E+06, 0.22314E+06, - 0.27761E+06, 0.34214E+06, 0.41847E+06, 0.50862E+06, 0.61497E+06, - 0.74028E+06, 0.88774E+06, 0.10611E+07, 0.12646E+07, 0.15031E+07, - 0.17825E+07, 0.21092E+07, 0.24908E+07, 0.29358E+07, 0.34541E+07, - 0.40571E+07, 0.47576E+07, 0.55703E+07, 0.65120E+07, 0.76018E+07, - 0.88614E+07, 0.10315E+08, 0.11992E+08, 0.13922E+08, 0.16142E+08, - 0.18693E+08, 0.21619E+08, 0.24973E+08, 0.28812E+08, 0.33202E+08, - 0.38216E+08, 0.43936E+08, 0.50455E+08, 0.57876E+08, 0.66315E+08, - 0.75901E+08, 0.86779E+08, 0.99110E+08, 0.11307E+09, 0.12887E+09, - 0.14672E+09, 0.16688E+09, 0.18961E+09, 0.21523E+09, 0.24407E+09, - 0.27651E+09, 0.31295E+09, 0.35387E+09, 0.39975E+09, 0.45118E+09, - 0.50875E+09, 0.57315E+09, 0.64512E+09, 0.72549E+09, 0.81517E+09, - 0.91514E+09, 0.10265E+10, 0.11504E+10, 0.12883E+10, 0.14414E+10, - 0.16115E+10, 0.18001E+10, 0.20093E+10, 0.22410E+10, 0.24975E+10, - 0.27812E+10, 0.30948E+10, 0.34412E+10, 0.38235E+10, 0.42452E+10, - 0.47101E+10, 0.52220E+10, 0.57856E+10, 0.64055E+10, 0.70869E+10, - 0.78355E+10, 0.86574E+10, 0.95591E+10, 0.10548E+11, 0.11631E+11, - 0.12817E+11, 0.14116E+11, 0.15536E+11, 0.17088E+11, 0.18785E+11, - 0.20636E+11, 0.22657E+11, 0.24861E+11, 0.27264E+11, 0.29881E+11, - 0.32730E+11, 0.35832E+11, 0.39205E+11, 0.42871E+11, 0.46855E+11, - 0.51182E+11, 0.55878E+11, 0.60973E+11, 0.66497E+11, 0.72484E+11, - 0.78970E+11, 0.85992E+11, 0.93592E+11, 0.10181E+12, 0.11070E+12, - 0.12031E+12, 0.13069E+12, 0.14189E+12, 0.15398E+12, 0.16703E+12, - 0.18110E+12]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.22522E+05, 0.38117E+05, 0.56899E+05, 0.79412E+05, 0.10640E+06, 0.13870E+06, 0.17726E+06, + 0.22314E+06, 0.27761E+06, 0.34214E+06, 0.41847E+06, 0.50862E+06, 0.61497E+06, 0.74028E+06, + 0.88774E+06, 0.10611E+07, 0.12646E+07, 0.15031E+07, 0.17825E+07, 0.21092E+07, 0.24908E+07, + 0.29358E+07, 0.34541E+07, 0.40571E+07, 0.47576E+07, 0.55703E+07, 0.65120E+07, 0.76018E+07, + 0.88614E+07, 0.10315E+08, 0.11992E+08, 0.13922E+08, 0.16142E+08, 0.18693E+08, 0.21619E+08, + 0.24973E+08, 0.28812E+08, 0.33202E+08, 0.38216E+08, 0.43936E+08, 0.50455E+08, 0.57876E+08, + 0.66315E+08, 0.75901E+08, 0.86779E+08, 0.99110E+08, 0.11307E+09, 0.12887E+09, 0.14672E+09, + 0.16688E+09, 0.18961E+09, 0.21523E+09, 0.24407E+09, 0.27651E+09, 0.31295E+09, 0.35387E+09, + 0.39975E+09, 0.45118E+09, 0.50875E+09, 0.57315E+09, 0.64512E+09, 0.72549E+09, 0.81517E+09, + 0.91514E+09, 0.10265E+10, 0.11504E+10, 0.12883E+10, 0.14414E+10, 0.16115E+10, 0.18001E+10, + 0.20093E+10, 0.22410E+10, 0.24975E+10, 0.27812E+10, 0.30948E+10, 0.34412E+10, 0.38235E+10, + 0.42452E+10, 0.47101E+10, 0.52220E+10, 0.57856E+10, 0.64055E+10, 0.70869E+10, 0.78355E+10, + 0.86574E+10, 0.95591E+10, 0.10548E+11, 0.11631E+11, 0.12817E+11, 0.14116E+11, 0.15536E+11, + 0.17088E+11, 0.18785E+11, 0.20636E+11, 0.22657E+11, 0.24861E+11, 0.27264E+11, 0.29881E+11, + 0.32730E+11, 0.35832E+11, 0.39205E+11, 0.42871E+11, 0.46855E+11, 0.51182E+11, 0.55878E+11, + 0.60973E+11, 0.66497E+11, 0.72484E+11, 0.78970E+11, 0.85992E+11, 0.93592E+11, 0.10181E+12, + 0.11070E+12, 0.12031E+12, 0.13069E+12, 0.14189E+12, 0.15398E+12, 0.16703E+12, 0.18110E+12]) # --------------- CF4 29: M = 42, I = 1 --------------------- M = 42 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.76233E+04, 0.12867E+05, 0.19059E+05, - 0.26316E+05, 0.34895E+05, 0.45145E+05, 0.57461E+05, 0.72259E+05, - 0.89950E+05, 0.11092E+06, 0.13550E+06, 0.16399E+06, 0.19658E+06, - 0.23341E+06, 0.27457E+06, 0.32004E+06, 0.36978E+06, 0.42369E+06, - 0.48161E+06, 0.54338E+06, 0.60880E+06, 0.67764E+06, 0.55684E+07, - 0.71250E+07, 0.90615E+07, 0.11458E+08, 0.14407E+08, 0.18021E+08, - 0.22428E+08, 0.27778E+08, 0.34247E+08, 0.42038E+08, 0.51386E+08, - 0.62559E+08, 0.75869E+08, 0.91670E+08, 0.11037E+09, 0.13242E+09, - 0.15836E+09, 0.18878E+09, 0.22436E+09, 0.26584E+09, 0.31410E+09, - 0.37008E+09, 0.43488E+09, 0.50970E+09, 0.59589E+09, 0.69496E+09, - 0.80858E+09, 0.93863E+09, 0.10872E+10, 0.12565E+10, 0.14491E+10, - 0.16679E+10, 0.19159E+10, 0.21966E+10, 0.25136E+10, 0.28711E+10, - 0.32740E+10, 0.37260E+10, 0.42340E+10, 0.48030E+10, 0.54400E+10, - 0.61520E+10, 0.69470E+10, 0.78320E+10, 0.88170E+10, 0.99120E+10, - 0.11130E+11, 0.12470E+11, 0.13970E+11, 0.15620E+11, 0.17440E+11, - 0.19450E+11, 0.21670E+11, 0.24100E+11, 0.26790E+11, 0.29730E+11, - 0.33000E+11, 0.36500E+11, 0.40400E+11, 0.44600E+11, 0.49300E+11, - 0.54300E+11, 0.59800E+11, 0.65800E+11, 0.72400E+11, 0.79500E+11, - 0.87200E+11, 0.95500E+11, 0.10500E+12, 0.11400E+12, 0.12500E+12, - 0.13600E+12, 0.14900E+12, 0.16200E+12, 0.17700E+12, 0.19200E+12, - 0.21000E+12, 0.23000E+12, 0.25000E+12, 0.27000E+12, 0.29000E+12, - 0.31000E+12, 0.34000E+12, 0.36000E+12, 0.39000E+12, 0.42000E+12, - 0.46000E+12, 0.49000E+12, 0.53000E+12, 0.57000E+12, 0.61000E+12, - 0.66000E+12, 0.70000E+12, 0.75000E+12, 0.81000E+12, 0.86000E+12, - 0.93000E+12]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.76233E+04, 0.12867E+05, 0.19059E+05, 0.26316E+05, 0.34895E+05, 0.45145E+05, 0.57461E+05, + 0.72259E+05, 0.89950E+05, 0.11092E+06, 0.13550E+06, 0.16399E+06, 0.19658E+06, 0.23341E+06, + 0.27457E+06, 0.32004E+06, 0.36978E+06, 0.42369E+06, 0.48161E+06, 0.54338E+06, 0.60880E+06, + 0.67764E+06, 0.55684E+07, 0.71250E+07, 0.90615E+07, 0.11458E+08, 0.14407E+08, 0.18021E+08, + 0.22428E+08, 0.27778E+08, 0.34247E+08, 0.42038E+08, 0.51386E+08, 0.62559E+08, 0.75869E+08, + 0.91670E+08, 0.11037E+09, 0.13242E+09, 0.15836E+09, 0.18878E+09, 0.22436E+09, 0.26584E+09, + 0.31410E+09, 0.37008E+09, 0.43488E+09, 0.50970E+09, 0.59589E+09, 0.69496E+09, 0.80858E+09, + 0.93863E+09, 0.10872E+10, 0.12565E+10, 0.14491E+10, 0.16679E+10, 0.19159E+10, 0.21966E+10, + 0.25136E+10, 0.28711E+10, 0.32740E+10, 0.37260E+10, 0.42340E+10, 0.48030E+10, 0.54400E+10, + 0.61520E+10, 0.69470E+10, 0.78320E+10, 0.88170E+10, 0.99120E+10, 0.11130E+11, 0.12470E+11, + 0.13970E+11, 0.15620E+11, 0.17440E+11, 0.19450E+11, 0.21670E+11, 0.24100E+11, 0.26790E+11, + 0.29730E+11, 0.33000E+11, 0.36500E+11, 0.40400E+11, 0.44600E+11, 0.49300E+11, 0.54300E+11, + 0.59800E+11, 0.65800E+11, 0.72400E+11, 0.79500E+11, 0.87200E+11, 0.95500E+11, 0.10500E+12, + 0.11400E+12, 0.12500E+12, 0.13600E+12, 0.14900E+12, 0.16200E+12, 0.17700E+12, 0.19200E+12, + 0.21000E+12, 0.23000E+12, 0.25000E+12, 0.27000E+12, 0.29000E+12, 0.31000E+12, 0.34000E+12, + 0.36000E+12, 0.39000E+12, 0.42000E+12, 0.46000E+12, 0.49000E+12, 0.53000E+12, 0.57000E+12, + 0.61000E+12, 0.66000E+12, 0.70000E+12, 0.75000E+12, 0.81000E+12, 0.86000E+12, 0.93000E+12]) # --------------- C4H2 1221: M = 43, I = 1 --------------------- M = 43 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.57628E+03, 0.84874E+03, 0.11789E+04, - 0.15952E+04, 0.21317E+04, 0.28324E+04, 0.37543E+04, 0.49705E+04, - 0.65754E+04, 0.86894E+04, 0.11466E+05, 0.15099E+05, 0.19834E+05, - 0.25980E+05, 0.33920E+05, 0.44132E+05, 0.57210E+05, 0.73884E+05, - 0.95049E+05, 0.12180E+06, 0.15548E+06, 0.19771E+06, 0.25045E+06, - 0.31606E+06, 0.39739E+06, 0.49786E+06, 0.62152E+06, 0.77324E+06, - 0.95878E+06, 0.11850E+07, 0.14599E+07, 0.17930E+07, 0.21956E+07, - 0.26807E+07, 0.32637E+07, 0.39626E+07, 0.47983E+07, 0.57951E+07, - 0.69813E+07, 0.83896E+07, 0.10058E+08, 0.12030E+08, 0.14356E+08, - 0.17093E+08, 0.20309E+08, 0.24079E+08, 0.28491E+08, 0.33644E+08, - 0.39651E+08, 0.46642E+08, 0.54764E+08, 0.64184E+08, 0.75091E+08, - 0.87699E+08, 0.10225E+09, 0.11902E+09, 0.13832E+09, 0.16049E+09, - 0.18593E+09, 0.21507E+09, 0.24841E+09, 0.28650E+09, 0.32996E+09, - 0.37949E+09, 0.43586E+09, 0.49993E+09, 0.57266E+09, 0.65513E+09, - 0.74852E+09, 0.85418E+09, 0.97356E+09, 0.11083E+10, 0.12602E+10, - 0.14313E+10, 0.16238E+10, 0.18401E+10, 0.20829E+10, 0.23553E+10, - 0.26605E+10, 0.30021E+10, 0.33841E+10, 0.38109E+10, 0.42874E+10, - 0.48187E+10, 0.54107E+10, 0.60698E+10, 0.68029E+10, 0.76176E+10, - 0.85223E+10, 0.95260E+10, 0.10639E+11, 0.11871E+11, 0.13236E+11, - 0.14744E+11, 0.16412E+11, 0.18253E+11, 0.20285E+11, 0.22526E+11, - 0.24995E+11, 0.27714E+11, 0.30705E+11, 0.33995E+11, 0.37609E+11, - 0.41579E+11, 0.45934E+11, 0.50711E+11, 0.55947E+11, 0.61681E+11, - 0.67957E+11, 0.74824E+11, 0.82330E+11, 0.90532E+11, 0.99487E+11, - 0.10926E+12, 0.11992E+12, 0.13154E+12, 0.14420E+12, 0.15799E+12, - 0.17299E+12]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.57628E+03, 0.84874E+03, 0.11789E+04, 0.15952E+04, 0.21317E+04, 0.28324E+04, 0.37543E+04, + 0.49705E+04, 0.65754E+04, 0.86894E+04, 0.11466E+05, 0.15099E+05, 0.19834E+05, 0.25980E+05, + 0.33920E+05, 0.44132E+05, 0.57210E+05, 0.73884E+05, 0.95049E+05, 0.12180E+06, 0.15548E+06, + 0.19771E+06, 0.25045E+06, 0.31606E+06, 0.39739E+06, 0.49786E+06, 0.62152E+06, 0.77324E+06, + 0.95878E+06, 0.11850E+07, 0.14599E+07, 0.17930E+07, 0.21956E+07, 0.26807E+07, 0.32637E+07, + 0.39626E+07, 0.47983E+07, 0.57951E+07, 0.69813E+07, 0.83896E+07, 0.10058E+08, 0.12030E+08, + 0.14356E+08, 0.17093E+08, 0.20309E+08, 0.24079E+08, 0.28491E+08, 0.33644E+08, 0.39651E+08, + 0.46642E+08, 0.54764E+08, 0.64184E+08, 0.75091E+08, 0.87699E+08, 0.10225E+09, 0.11902E+09, + 0.13832E+09, 0.16049E+09, 0.18593E+09, 0.21507E+09, 0.24841E+09, 0.28650E+09, 0.32996E+09, + 0.37949E+09, 0.43586E+09, 0.49993E+09, 0.57266E+09, 0.65513E+09, 0.74852E+09, 0.85418E+09, + 0.97356E+09, 0.11083E+10, 0.12602E+10, 0.14313E+10, 0.16238E+10, 0.18401E+10, 0.20829E+10, + 0.23553E+10, 0.26605E+10, 0.30021E+10, 0.33841E+10, 0.38109E+10, 0.42874E+10, 0.48187E+10, + 0.54107E+10, 0.60698E+10, 0.68029E+10, 0.76176E+10, 0.85223E+10, 0.95260E+10, 0.10639E+11, + 0.11871E+11, 0.13236E+11, 0.14744E+11, 0.16412E+11, 0.18253E+11, 0.20285E+11, 0.22526E+11, + 0.24995E+11, 0.27714E+11, 0.30705E+11, 0.33995E+11, 0.37609E+11, 0.41579E+11, 0.45934E+11, + 0.50711E+11, 0.55947E+11, 0.61681E+11, 0.67957E+11, 0.74824E+11, 0.82330E+11, 0.90532E+11, + 0.99487E+11, 0.10926E+12, 0.11992E+12, 0.13154E+12, 0.14420E+12, 0.15799E+12, 0.17299E+12]) # --------------- HC3N 12224: M = 44, I = 1 --------------------- 1224 in HITRAN, 12224 in TIPS M = 44 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.16683E+04, 0.24538E+04, 0.33995E+04, - 0.45769E+04, 0.60637E+04, 0.79533E+04, 0.10360E+05, 0.13422E+05, - 0.17311E+05, 0.22232E+05, 0.28434E+05, 0.36215E+05, 0.45932E+05, - 0.58011E+05, 0.72958E+05, 0.91370E+05, 0.11395E+06, 0.14153E+06, - 0.17507E+06, 0.21570E+06, 0.26475E+06, 0.32372E+06, 0.39440E+06, - 0.47881E+06, 0.57930E+06, 0.69856E+06, 0.83968E+06, 0.10062E+07, - 0.12021E+07, 0.14320E+07, 0.17011E+07, 0.20153E+07, 0.23812E+07, - 0.28065E+07, 0.32996E+07, 0.38701E+07, 0.45287E+07, 0.52876E+07, - 0.61602E+07, 0.71616E+07, 0.83088E+07, 0.96206E+07, 0.11118E+08, - 0.12824E+08, 0.14765E+08, 0.16969E+08, 0.19469E+08, 0.22299E+08, - 0.25498E+08, 0.29110E+08, 0.33181E+08, 0.37763E+08, 0.42914E+08, - 0.48697E+08, 0.55180E+08, 0.62440E+08, 0.70558E+08, 0.79627E+08, - 0.89743E+08, 0.10102E+09, 0.11356E+09, 0.12752E+09, 0.14301E+09, - 0.16020E+09, 0.17925E+09, 0.20035E+09, 0.22367E+09, 0.24945E+09, - 0.27790E+09, 0.30928E+09, 0.34385E+09, 0.38191E+09, 0.42376E+09, - 0.46975E+09, 0.52023E+09, 0.57562E+09, 0.63632E+09, 0.70279E+09, - 0.77553E+09, 0.85506E+09, 0.94195E+09, 0.10368E+10, 0.11403E+10, - 0.12531E+10, 0.13759E+10, 0.15097E+10, 0.16552E+10, 0.18133E+10, - 0.19851E+10, 0.21715E+10, 0.23738E+10, 0.25931E+10, 0.28307E+10, - 0.30879E+10, 0.33662E+10, 0.36672E+10, 0.39926E+10, 0.43439E+10, - 0.47233E+10, 0.51325E+10, 0.55738E+10, 0.60493E+10, 0.65615E+10, - 0.71129E+10, 0.77061E+10, 0.83441E+10, 0.90298E+10, 0.97664E+10, - 0.10557E+11, 0.11406E+11, 0.12317E+11, 0.13293E+11, 0.14339E+11, - 0.15459E+11, 0.16659E+11, 0.17942E+11, 0.19316E+11, 0.20784E+11, - 0.22353E+11]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.16683E+04, 0.24538E+04, 0.33995E+04, 0.45769E+04, 0.60637E+04, 0.79533E+04, 0.10360E+05, + 0.13422E+05, 0.17311E+05, 0.22232E+05, 0.28434E+05, 0.36215E+05, 0.45932E+05, 0.58011E+05, + 0.72958E+05, 0.91370E+05, 0.11395E+06, 0.14153E+06, 0.17507E+06, 0.21570E+06, 0.26475E+06, + 0.32372E+06, 0.39440E+06, 0.47881E+06, 0.57930E+06, 0.69856E+06, 0.83968E+06, 0.10062E+07, + 0.12021E+07, 0.14320E+07, 0.17011E+07, 0.20153E+07, 0.23812E+07, 0.28065E+07, 0.32996E+07, + 0.38701E+07, 0.45287E+07, 0.52876E+07, 0.61602E+07, 0.71616E+07, 0.83088E+07, 0.96206E+07, + 0.11118E+08, 0.12824E+08, 0.14765E+08, 0.16969E+08, 0.19469E+08, 0.22299E+08, 0.25498E+08, + 0.29110E+08, 0.33181E+08, 0.37763E+08, 0.42914E+08, 0.48697E+08, 0.55180E+08, 0.62440E+08, + 0.70558E+08, 0.79627E+08, 0.89743E+08, 0.10102E+09, 0.11356E+09, 0.12752E+09, 0.14301E+09, + 0.16020E+09, 0.17925E+09, 0.20035E+09, 0.22367E+09, 0.24945E+09, 0.27790E+09, 0.30928E+09, + 0.34385E+09, 0.38191E+09, 0.42376E+09, 0.46975E+09, 0.52023E+09, 0.57562E+09, 0.63632E+09, + 0.70279E+09, 0.77553E+09, 0.85506E+09, 0.94195E+09, 0.10368E+10, 0.11403E+10, 0.12531E+10, + 0.13759E+10, 0.15097E+10, 0.16552E+10, 0.18133E+10, 0.19851E+10, 0.21715E+10, 0.23738E+10, + 0.25931E+10, 0.28307E+10, 0.30879E+10, 0.33662E+10, 0.36672E+10, 0.39926E+10, 0.43439E+10, + 0.47233E+10, 0.51325E+10, 0.55738E+10, 0.60493E+10, 0.65615E+10, 0.71129E+10, 0.77061E+10, + 0.83441E+10, 0.90298E+10, 0.97664E+10, 0.10557E+11, 0.11406E+11, 0.12317E+11, 0.13293E+11, + 0.14339E+11, 0.15459E+11, 0.16659E+11, 0.17942E+11, 0.19316E+11, 0.20784E+11, 0.22353E+11]) # --------------- HC3N 12234: M = 44, I = 2 --------------------- see above M = 44 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(12.) -TIPS_ISO_HASH[(M, I)] = float32([0.33507E+04, 0.49290E+04, 0.68293E+04, - 0.91959E+04, 0.12185E+05, 0.15986E+05, 0.20828E+05, 0.26993E+05, - 0.34824E+05, 0.44739E+05, 0.57239E+05, 0.72931E+05, 0.92539E+05, - 0.11693E+06, 0.14713E+06, 0.18435E+06, 0.23004E+06, 0.28588E+06, - 0.35384E+06, 0.43625E+06, 0.53580E+06, 0.65562E+06, 0.79933E+06, - 0.97115E+06, 0.11759E+07, 0.14191E+07, 0.17073E+07, 0.20476E+07, - 0.24486E+07, 0.29196E+07, 0.34716E+07, 0.41169E+07, 0.48696E+07, - 0.57453E+07, 0.67621E+07, 0.79402E+07, 0.93022E+07, 0.10874E+08, - 0.12684E+08, 0.14764E+08, 0.17150E+08, 0.19884E+08, 0.23009E+08, - 0.26576E+08, 0.30641E+08, 0.35265E+08, 0.40518E+08, 0.46477E+08, - 0.53225E+08, 0.60856E+08, 0.69475E+08, 0.79195E+08, 0.90143E+08, - 0.10246E+09, 0.11629E+09, 0.13182E+09, 0.14921E+09, 0.16868E+09, - 0.19045E+09, 0.21477E+09, 0.24189E+09, 0.27211E+09, 0.30575E+09, - 0.34316E+09, 0.38471E+09, 0.43083E+09, 0.48196E+09, 0.53858E+09, - 0.60125E+09, 0.67052E+09, 0.74704E+09, 0.83148E+09, 0.92459E+09, - 0.10272E+10, 0.11401E+10, 0.12643E+10, 0.14007E+10, 0.15506E+10, - 0.17150E+10, 0.18953E+10, 0.20928E+10, 0.23090E+10, 0.25456E+10, - 0.28042E+10, 0.30867E+10, 0.33951E+10, 0.37316E+10, 0.40984E+10, - 0.44981E+10, 0.49332E+10, 0.54067E+10, 0.59216E+10, 0.64812E+10, - 0.70890E+10, 0.77488E+10, 0.84645E+10, 0.92405E+10, 0.10081E+11, - 0.10992E+11, 0.11978E+11, 0.13044E+11, 0.14197E+11, 0.15443E+11, - 0.16789E+11, 0.18243E+11, 0.19810E+11, 0.21501E+11, 0.23324E+11, - 0.25288E+11, 0.27403E+11, 0.29680E+11, 0.32130E+11, 0.34764E+11, - 0.37596E+11, 0.40639E+11, 0.43907E+11, 0.47416E+11, 0.51181E+11, - 0.55220E+11]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.33507E+04, 0.49290E+04, 0.68293E+04, 0.91959E+04, 0.12185E+05, 0.15986E+05, 0.20828E+05, + 0.26993E+05, 0.34824E+05, 0.44739E+05, 0.57239E+05, 0.72931E+05, 0.92539E+05, 0.11693E+06, + 0.14713E+06, 0.18435E+06, 0.23004E+06, 0.28588E+06, 0.35384E+06, 0.43625E+06, 0.53580E+06, + 0.65562E+06, 0.79933E+06, 0.97115E+06, 0.11759E+07, 0.14191E+07, 0.17073E+07, 0.20476E+07, + 0.24486E+07, 0.29196E+07, 0.34716E+07, 0.41169E+07, 0.48696E+07, 0.57453E+07, 0.67621E+07, + 0.79402E+07, 0.93022E+07, 0.10874E+08, 0.12684E+08, 0.14764E+08, 0.17150E+08, 0.19884E+08, + 0.23009E+08, 0.26576E+08, 0.30641E+08, 0.35265E+08, 0.40518E+08, 0.46477E+08, 0.53225E+08, + 0.60856E+08, 0.69475E+08, 0.79195E+08, 0.90143E+08, 0.10246E+09, 0.11629E+09, 0.13182E+09, + 0.14921E+09, 0.16868E+09, 0.19045E+09, 0.21477E+09, 0.24189E+09, 0.27211E+09, 0.30575E+09, + 0.34316E+09, 0.38471E+09, 0.43083E+09, 0.48196E+09, 0.53858E+09, 0.60125E+09, 0.67052E+09, + 0.74704E+09, 0.83148E+09, 0.92459E+09, 0.10272E+10, 0.11401E+10, 0.12643E+10, 0.14007E+10, + 0.15506E+10, 0.17150E+10, 0.18953E+10, 0.20928E+10, 0.23090E+10, 0.25456E+10, 0.28042E+10, + 0.30867E+10, 0.33951E+10, 0.37316E+10, 0.40984E+10, 0.44981E+10, 0.49332E+10, 0.54067E+10, + 0.59216E+10, 0.64812E+10, 0.70890E+10, 0.77488E+10, 0.84645E+10, 0.92405E+10, 0.10081E+11, + 0.10992E+11, 0.11978E+11, 0.13044E+11, 0.14197E+11, 0.15443E+11, 0.16789E+11, 0.18243E+11, + 0.19810E+11, 0.21501E+11, 0.23324E+11, 0.25288E+11, 0.27403E+11, 0.29680E+11, 0.32130E+11, + 0.34764E+11, 0.37596E+11, 0.40639E+11, 0.43907E+11, 0.47416E+11, 0.51181E+11, 0.55220E+11]) # --------------- HC3N 12324: M = 44, I = 3 --------------------- see above M = 44 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(12.) -TIPS_ISO_HASH[(M, I)] = float32([0.33506E+04, 0.49280E+04, 0.68267E+04, - 0.91901E+04, 0.12174E+05, 0.15966E+05, 0.20793E+05, 0.26936E+05, - 0.34734E+05, 0.44598E+05, 0.57026E+05, 0.72612E+05, 0.92071E+05, - 0.11625E+06, 0.14616E+06, 0.18298E+06, 0.22813E+06, 0.28323E+06, - 0.35022E+06, 0.43133E+06, 0.52918E+06, 0.64677E+06, 0.78761E+06, - 0.95571E+06, 0.11557E+07, 0.13929E+07, 0.16734E+07, 0.20041E+07, - 0.23929E+07, 0.28488E+07, 0.33820E+07, 0.40040E+07, 0.47280E+07, - 0.55686E+07, 0.65423E+07, 0.76678E+07, 0.89661E+07, 0.10460E+08, - 0.12177E+08, 0.14145E+08, 0.16397E+08, 0.18970E+08, 0.21903E+08, - 0.25242E+08, 0.29036E+08, 0.33339E+08, 0.38214E+08, 0.43726E+08, - 0.49949E+08, 0.56965E+08, 0.64864E+08, 0.73743E+08, 0.83711E+08, - 0.94886E+08, 0.10740E+09, 0.12139E+09, 0.13701E+09, 0.15443E+09, - 0.17384E+09, 0.19543E+09, 0.21943E+09, 0.24607E+09, 0.27561E+09, - 0.30832E+09, 0.34452E+09, 0.38453E+09, 0.42870E+09, 0.47742E+09, - 0.53110E+09, 0.59020E+09, 0.65518E+09, 0.72659E+09, 0.80496E+09, - 0.89092E+09, 0.98510E+09, 0.10882E+10, 0.12010E+10, 0.13242E+10, - 0.14588E+10, 0.16056E+10, 0.17657E+10, 0.19401E+10, 0.21299E+10, - 0.23363E+10, 0.25606E+10, 0.28043E+10, 0.30687E+10, 0.33553E+10, - 0.36660E+10, 0.40024E+10, 0.43665E+10, 0.47601E+10, 0.51856E+10, - 0.56450E+10, 0.61408E+10, 0.66756E+10, 0.72520E+10, 0.78729E+10, - 0.85413E+10, 0.92604E+10, 0.10034E+11, 0.10864E+11, 0.11757E+11, - 0.12714E+11, 0.13742E+11, 0.14843E+11, 0.16023E+11, 0.17287E+11, - 0.18640E+11, 0.20087E+11, 0.21634E+11, 0.23288E+11, 0.25054E+11, - 0.26939E+11, 0.28950E+11, 0.31096E+11, 0.33382E+11, 0.35819E+11, - 0.38413E+11]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.33506E+04, 0.49280E+04, 0.68267E+04, 0.91901E+04, 0.12174E+05, 0.15966E+05, 0.20793E+05, + 0.26936E+05, 0.34734E+05, 0.44598E+05, 0.57026E+05, 0.72612E+05, 0.92071E+05, 0.11625E+06, + 0.14616E+06, 0.18298E+06, 0.22813E+06, 0.28323E+06, 0.35022E+06, 0.43133E+06, 0.52918E+06, + 0.64677E+06, 0.78761E+06, 0.95571E+06, 0.11557E+07, 0.13929E+07, 0.16734E+07, 0.20041E+07, + 0.23929E+07, 0.28488E+07, 0.33820E+07, 0.40040E+07, 0.47280E+07, 0.55686E+07, 0.65423E+07, + 0.76678E+07, 0.89661E+07, 0.10460E+08, 0.12177E+08, 0.14145E+08, 0.16397E+08, 0.18970E+08, + 0.21903E+08, 0.25242E+08, 0.29036E+08, 0.33339E+08, 0.38214E+08, 0.43726E+08, 0.49949E+08, + 0.56965E+08, 0.64864E+08, 0.73743E+08, 0.83711E+08, 0.94886E+08, 0.10740E+09, 0.12139E+09, + 0.13701E+09, 0.15443E+09, 0.17384E+09, 0.19543E+09, 0.21943E+09, 0.24607E+09, 0.27561E+09, + 0.30832E+09, 0.34452E+09, 0.38453E+09, 0.42870E+09, 0.47742E+09, 0.53110E+09, 0.59020E+09, + 0.65518E+09, 0.72659E+09, 0.80496E+09, 0.89092E+09, 0.98510E+09, 0.10882E+10, 0.12010E+10, + 0.13242E+10, 0.14588E+10, 0.16056E+10, 0.17657E+10, 0.19401E+10, 0.21299E+10, 0.23363E+10, + 0.25606E+10, 0.28043E+10, 0.30687E+10, 0.33553E+10, 0.36660E+10, 0.40024E+10, 0.43665E+10, + 0.47601E+10, 0.51856E+10, 0.56450E+10, 0.61408E+10, 0.66756E+10, 0.72520E+10, 0.78729E+10, + 0.85413E+10, 0.92604E+10, 0.10034E+11, 0.10864E+11, 0.11757E+11, 0.12714E+11, 0.13742E+11, + 0.14843E+11, 0.16023E+11, 0.17287E+11, 0.18640E+11, 0.20087E+11, 0.21634E+11, 0.23288E+11, + 0.25054E+11, 0.26939E+11, 0.28950E+11, 0.31096E+11, 0.33382E+11, 0.35819E+11, 0.38413E+11]) # --------------- HC3N 13224: M = 44, I = 4 --------------------- see above M = 44 I = 4 TIPS_GSI_HASH[(M, I)] = __FloatType__(12.) -TIPS_ISO_HASH[(M, I)] = float32([0.34439E+04, 0.50672E+04, 0.70230E+04, - 0.94603E+04, 0.12542E+05, 0.16462E+05, 0.21461E+05, 0.27833E+05, - 0.35935E+05, 0.46204E+05, 0.59168E+05, 0.75463E+05, 0.95854E+05, - 0.12126E+06, 0.15276E+06, 0.19165E+06, 0.23947E+06, 0.29802E+06, - 0.36943E+06, 0.45619E+06, 0.56121E+06, 0.68789E+06, 0.84018E+06, - 0.10227E+07, 0.12407E+07, 0.15003E+07, 0.18086E+07, 0.21738E+07, - 0.26052E+07, 0.31134E+07, 0.37106E+07, 0.44109E+07, 0.52300E+07, - 0.61861E+07, 0.72996E+07, 0.85939E+07, 0.10095E+08, 0.11833E+08, - 0.13841E+08, 0.16158E+08, 0.18825E+08, 0.21890E+08, 0.25407E+08, - 0.29436E+08, 0.34045E+08, 0.39308E+08, 0.45309E+08, 0.52143E+08, - 0.59912E+08, 0.68734E+08, 0.78737E+08, 0.90065E+08, 0.10288E+09, - 0.11735E+09, 0.13367E+09, 0.15206E+09, 0.17277E+09, 0.19604E+09, - 0.22217E+09, 0.25148E+09, 0.28432E+09, 0.32108E+09, 0.36218E+09, - 0.40809E+09, 0.45932E+09, 0.51644E+09, 0.58004E+09, 0.65082E+09, - 0.72950E+09, 0.81690E+09, 0.91388E+09, 0.10214E+10, 0.11405E+10, - 0.12724E+10, 0.14182E+10, 0.15794E+10, 0.17573E+10, 0.19536E+10, - 0.21701E+10, 0.24086E+10, 0.26711E+10, 0.29599E+10, 0.32774E+10, - 0.36262E+10, 0.40090E+10, 0.44290E+10, 0.48895E+10, 0.53939E+10, - 0.59462E+10, 0.65504E+10, 0.72111E+10, 0.79332E+10, 0.87217E+10, - 0.95823E+10, 0.10521E+11, 0.11544E+11, 0.12659E+11, 0.13874E+11, - 0.15195E+11, 0.16632E+11, 0.18194E+11, 0.19892E+11, 0.21735E+11, - 0.23736E+11, 0.25907E+11, 0.28260E+11, 0.30810E+11, 0.33572E+11, - 0.36563E+11, 0.39799E+11, 0.43299E+11, 0.47083E+11, 0.51172E+11, - 0.55588E+11, 0.60355E+11, 0.65500E+11, 0.71049E+11, 0.77031E+11, - 0.83478E+11]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.34439E+04, 0.50672E+04, 0.70230E+04, 0.94603E+04, 0.12542E+05, 0.16462E+05, 0.21461E+05, + 0.27833E+05, 0.35935E+05, 0.46204E+05, 0.59168E+05, 0.75463E+05, 0.95854E+05, 0.12126E+06, + 0.15276E+06, 0.19165E+06, 0.23947E+06, 0.29802E+06, 0.36943E+06, 0.45619E+06, 0.56121E+06, + 0.68789E+06, 0.84018E+06, 0.10227E+07, 0.12407E+07, 0.15003E+07, 0.18086E+07, 0.21738E+07, + 0.26052E+07, 0.31134E+07, 0.37106E+07, 0.44109E+07, 0.52300E+07, 0.61861E+07, 0.72996E+07, + 0.85939E+07, 0.10095E+08, 0.11833E+08, 0.13841E+08, 0.16158E+08, 0.18825E+08, 0.21890E+08, + 0.25407E+08, 0.29436E+08, 0.34045E+08, 0.39308E+08, 0.45309E+08, 0.52143E+08, 0.59912E+08, + 0.68734E+08, 0.78737E+08, 0.90065E+08, 0.10288E+09, 0.11735E+09, 0.13367E+09, 0.15206E+09, + 0.17277E+09, 0.19604E+09, 0.22217E+09, 0.25148E+09, 0.28432E+09, 0.32108E+09, 0.36218E+09, + 0.40809E+09, 0.45932E+09, 0.51644E+09, 0.58004E+09, 0.65082E+09, 0.72950E+09, 0.81690E+09, + 0.91388E+09, 0.10214E+10, 0.11405E+10, 0.12724E+10, 0.14182E+10, 0.15794E+10, 0.17573E+10, + 0.19536E+10, 0.21701E+10, 0.24086E+10, 0.26711E+10, 0.29599E+10, 0.32774E+10, 0.36262E+10, + 0.40090E+10, 0.44290E+10, 0.48895E+10, 0.53939E+10, 0.59462E+10, 0.65504E+10, 0.72111E+10, + 0.79332E+10, 0.87217E+10, 0.95823E+10, 0.10521E+11, 0.11544E+11, 0.12659E+11, 0.13874E+11, + 0.15195E+11, 0.16632E+11, 0.18194E+11, 0.19892E+11, 0.21735E+11, 0.23736E+11, 0.25907E+11, + 0.28260E+11, 0.30810E+11, 0.33572E+11, 0.36563E+11, 0.39799E+11, 0.43299E+11, 0.47083E+11, + 0.51172E+11, 0.55588E+11, 0.60355E+11, 0.65500E+11, 0.71049E+11, 0.77031E+11, 0.83478E+11]) # --------------- HC3N 12225: M = 44, I = 5 --------------------- see above M = 44 I = 5 TIPS_GSI_HASH[(M, I)] = __FloatType__(4.) -TIPS_ISO_HASH[(M, I)] = float32([0.11455E+04, 0.16850E+04, 0.23345E+04, - 0.31432E+04, 0.41647E+04, 0.54630E+04, 0.71168E+04, 0.92219E+04, - 0.11895E+05, 0.15279E+05, 0.19545E+05, 0.24897E+05, 0.31584E+05, - 0.39899E+05, 0.50190E+05, 0.62871E+05, 0.78428E+05, 0.97434E+05, - 0.12056E+06, 0.14859E+06, 0.18243E+06, 0.22314E+06, 0.27194E+06, - 0.33026E+06, 0.39972E+06, 0.48219E+06, 0.57983E+06, 0.69509E+06, - 0.83077E+06, 0.99009E+06, 0.11767E+07, 0.13946E+07, 0.16487E+07, - 0.19441E+07, 0.22868E+07, 0.26836E+07, 0.31420E+07, 0.36704E+07, - 0.42786E+07, 0.49770E+07, 0.57776E+07, 0.66938E+07, 0.77404E+07, - 0.89339E+07, 0.10293E+08, 0.11837E+08, 0.13590E+08, 0.15576E+08, - 0.17823E+08, 0.20362E+08, 0.23227E+08, 0.26454E+08, 0.30085E+08, - 0.34166E+08, 0.38745E+08, 0.43877E+08, 0.49622E+08, 0.56046E+08, - 0.63219E+08, 0.71222E+08, 0.80138E+08, 0.90062E+08, 0.10110E+09, - 0.11335E+09, 0.12695E+09, 0.14202E+09, 0.15870E+09, 0.17716E+09, - 0.19756E+09, 0.22009E+09, 0.24493E+09, 0.27232E+09, 0.30247E+09, - 0.33565E+09, 0.37211E+09, 0.41217E+09, 0.45613E+09, 0.50433E+09, - 0.55714E+09, 0.61497E+09, 0.67823E+09, 0.74739E+09, 0.82293E+09, - 0.90540E+09, 0.99536E+09, 0.10934E+10, 0.12002E+10, 0.13165E+10, - 0.14430E+10, 0.15805E+10, 0.17299E+10, 0.18922E+10, 0.20682E+10, - 0.22591E+10, 0.24660E+10, 0.26901E+10, 0.29326E+10, 0.31951E+10, - 0.34788E+10, 0.37854E+10, 0.41166E+10, 0.44741E+10, 0.48598E+10, - 0.52758E+10, 0.57240E+10, 0.62069E+10, 0.67269E+10, 0.72864E+10, - 0.78882E+10, 0.85352E+10, 0.92305E+10, 0.99773E+10, 0.10779E+11, - 0.11639E+11, 0.12562E+11, 0.13552E+11, 0.14612E+11, 0.15748E+11, - 0.16964E+11]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.11455E+04, 0.16850E+04, 0.23345E+04, 0.31432E+04, 0.41647E+04, 0.54630E+04, 0.71168E+04, + 0.92219E+04, 0.11895E+05, 0.15279E+05, 0.19545E+05, 0.24897E+05, 0.31584E+05, 0.39899E+05, + 0.50190E+05, 0.62871E+05, 0.78428E+05, 0.97434E+05, 0.12056E+06, 0.14859E+06, 0.18243E+06, + 0.22314E+06, 0.27194E+06, 0.33026E+06, 0.39972E+06, 0.48219E+06, 0.57983E+06, 0.69509E+06, + 0.83077E+06, 0.99009E+06, 0.11767E+07, 0.13946E+07, 0.16487E+07, 0.19441E+07, 0.22868E+07, + 0.26836E+07, 0.31420E+07, 0.36704E+07, 0.42786E+07, 0.49770E+07, 0.57776E+07, 0.66938E+07, + 0.77404E+07, 0.89339E+07, 0.10293E+08, 0.11837E+08, 0.13590E+08, 0.15576E+08, 0.17823E+08, + 0.20362E+08, 0.23227E+08, 0.26454E+08, 0.30085E+08, 0.34166E+08, 0.38745E+08, 0.43877E+08, + 0.49622E+08, 0.56046E+08, 0.63219E+08, 0.71222E+08, 0.80138E+08, 0.90062E+08, 0.10110E+09, + 0.11335E+09, 0.12695E+09, 0.14202E+09, 0.15870E+09, 0.17716E+09, 0.19756E+09, 0.22009E+09, + 0.24493E+09, 0.27232E+09, 0.30247E+09, 0.33565E+09, 0.37211E+09, 0.41217E+09, 0.45613E+09, + 0.50433E+09, 0.55714E+09, 0.61497E+09, 0.67823E+09, 0.74739E+09, 0.82293E+09, 0.90540E+09, + 0.99536E+09, 0.10934E+10, 0.12002E+10, 0.13165E+10, 0.14430E+10, 0.15805E+10, 0.17299E+10, + 0.18922E+10, 0.20682E+10, 0.22591E+10, 0.24660E+10, 0.26901E+10, 0.29326E+10, 0.31951E+10, + 0.34788E+10, 0.37854E+10, 0.41166E+10, 0.44741E+10, 0.48598E+10, 0.52758E+10, 0.57240E+10, + 0.62069E+10, 0.67269E+10, 0.72864E+10, 0.78882E+10, 0.85352E+10, 0.92305E+10, 0.99773E+10, + 0.10779E+11, 0.11639E+11, 0.12562E+11, 0.13552E+11, 0.14612E+11, 0.15748E+11, 0.16964E+11]) # --------------- HC3N 22224: M = 44, I = 6 --------------------- see above M = 44 I = 6 TIPS_GSI_HASH[(M, I)] = __FloatType__(9.) -TIPS_ISO_HASH[(M, I)] = float32([0.27029E+04, 0.39999E+04, 0.55894E+04, - 0.76092E+04, 0.10219E+05, 0.13616E+05, 0.18042E+05, 0.23798E+05, - 0.31255E+05, 0.40867E+05, 0.53189E+05, 0.68897E+05, 0.88807E+05, - 0.11390E+06, 0.14537E+06, 0.18461E+06, 0.23330E+06, 0.29342E+06, - 0.36733E+06, 0.45779E+06, 0.56802E+06, 0.70182E+06, 0.86361E+06, - 0.10585E+07, 0.12925E+07, 0.15725E+07, 0.19064E+07, 0.23034E+07, - 0.27739E+07, 0.33302E+07, 0.39858E+07, 0.47566E+07, 0.56604E+07, - 0.67176E+07, 0.79511E+07, 0.93872E+07, 0.11055E+08, 0.12989E+08, - 0.15225E+08, 0.17806E+08, 0.20779E+08, 0.24197E+08, 0.28119E+08, - 0.32612E+08, 0.37749E+08, 0.43612E+08, 0.50294E+08, 0.57895E+08, - 0.66528E+08, 0.76318E+08, 0.87403E+08, 0.99937E+08, 0.11409E+09, - 0.13004E+09, 0.14800E+09, 0.16819E+09, 0.19086E+09, 0.21629E+09, - 0.24476E+09, 0.27661E+09, 0.31219E+09, 0.35189E+09, 0.39615E+09, - 0.44542E+09, 0.50021E+09, 0.56108E+09, 0.62862E+09, 0.70350E+09, - 0.78641E+09, 0.87814E+09, 0.97952E+09, 0.10915E+10, 0.12149E+10, - 0.13510E+10, 0.15008E+10, 0.16656E+10, 0.18468E+10, 0.20457E+10, - 0.22640E+10, 0.25032E+10, 0.27653E+10, 0.30522E+10, 0.33659E+10, - 0.37088E+10, 0.40832E+10, 0.44917E+10, 0.49371E+10, 0.54224E+10, - 0.59508E+10, 0.65256E+10, 0.71507E+10, 0.78298E+10, 0.85671E+10, - 0.93672E+10, 0.10235E+11, 0.11175E+11, 0.12193E+11, 0.13295E+11, - 0.14487E+11, 0.15776E+11, 0.17168E+11, 0.18671E+11, 0.20293E+11, - 0.22043E+11, 0.23929E+11, 0.25960E+11, 0.28148E+11, 0.30502E+11, - 0.33034E+11, 0.35756E+11, 0.38681E+11, 0.41823E+11, 0.45195E+11, - 0.48812E+11, 0.52692E+11, 0.56850E+11, 0.61306E+11, 0.66076E+11, - 0.71183E+11]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.27029E+04, 0.39999E+04, 0.55894E+04, 0.76092E+04, 0.10219E+05, 0.13616E+05, 0.18042E+05, + 0.23798E+05, 0.31255E+05, 0.40867E+05, 0.53189E+05, 0.68897E+05, 0.88807E+05, 0.11390E+06, + 0.14537E+06, 0.18461E+06, 0.23330E+06, 0.29342E+06, 0.36733E+06, 0.45779E+06, 0.56802E+06, + 0.70182E+06, 0.86361E+06, 0.10585E+07, 0.12925E+07, 0.15725E+07, 0.19064E+07, 0.23034E+07, + 0.27739E+07, 0.33302E+07, 0.39858E+07, 0.47566E+07, 0.56604E+07, 0.67176E+07, 0.79511E+07, + 0.93872E+07, 0.11055E+08, 0.12989E+08, 0.15225E+08, 0.17806E+08, 0.20779E+08, 0.24197E+08, + 0.28119E+08, 0.32612E+08, 0.37749E+08, 0.43612E+08, 0.50294E+08, 0.57895E+08, 0.66528E+08, + 0.76318E+08, 0.87403E+08, 0.99937E+08, 0.11409E+09, 0.13004E+09, 0.14800E+09, 0.16819E+09, + 0.19086E+09, 0.21629E+09, 0.24476E+09, 0.27661E+09, 0.31219E+09, 0.35189E+09, 0.39615E+09, + 0.44542E+09, 0.50021E+09, 0.56108E+09, 0.62862E+09, 0.70350E+09, 0.78641E+09, 0.87814E+09, + 0.97952E+09, 0.10915E+10, 0.12149E+10, 0.13510E+10, 0.15008E+10, 0.16656E+10, 0.18468E+10, + 0.20457E+10, 0.22640E+10, 0.25032E+10, 0.27653E+10, 0.30522E+10, 0.33659E+10, 0.37088E+10, + 0.40832E+10, 0.44917E+10, 0.49371E+10, 0.54224E+10, 0.59508E+10, 0.65256E+10, 0.71507E+10, + 0.78298E+10, 0.85671E+10, 0.93672E+10, 0.10235E+11, 0.11175E+11, 0.12193E+11, 0.13295E+11, + 0.14487E+11, 0.15776E+11, 0.17168E+11, 0.18671E+11, 0.20293E+11, 0.22043E+11, 0.23929E+11, + 0.25960E+11, 0.28148E+11, 0.30502E+11, 0.33034E+11, 0.35756E+11, 0.38681E+11, 0.41823E+11, + 0.45195E+11, 0.48812E+11, 0.52692E+11, 0.56850E+11, 0.61306E+11, 0.66076E+11, 0.71183E+11]) # --------------- H2 11: M = 45, I = 1 --------------------- M = 45 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.15265E+01, 0.22243E+01, 0.29619E+01, - 0.36724E+01, 0.43456E+01, 0.49880E+01, 0.56090E+01, 0.62165E+01, - 0.68161E+01, 0.74113E+01, 0.80044E+01, 0.85966E+01, 0.91887E+01, - 0.97810E+01, 0.10374E+02, 0.10967E+02, 0.11561E+02, 0.12156E+02, - 0.12751E+02, 0.13347E+02, 0.13944E+02, 0.14541E+02, 0.15139E+02, - 0.15738E+02, 0.16337E+02, 0.16937E+02, 0.17538E+02, 0.18140E+02, - 0.18743E+02, 0.19346E+02, 0.19951E+02, 0.20556E+02, 0.21163E+02, - 0.21771E+02, 0.22379E+02, 0.22990E+02, 0.23601E+02, 0.24214E+02, - 0.24829E+02, 0.25445E+02, 0.26063E+02, 0.26683E+02, 0.27304E+02, - 0.27928E+02, 0.28553E+02, 0.29181E+02, 0.29811E+02, 0.30443E+02, - 0.31078E+02, 0.31715E+02, 0.32355E+02, 0.32997E+02, 0.33643E+02, - 0.34291E+02, 0.34942E+02, 0.35596E+02, 0.36253E+02, 0.36914E+02, - 0.37578E+02, 0.38245E+02, 0.38916E+02, 0.39590E+02, 0.40268E+02, - 0.40949E+02, 0.41635E+02, 0.42324E+02, 0.43017E+02, 0.43715E+02, - 0.44416E+02, 0.45122E+02, 0.45831E+02, 0.46546E+02, 0.47264E+02, - 0.47987E+02, 0.48714E+02, 0.49446E+02, 0.50183E+02, 0.50925E+02, - 0.51671E+02, 0.52422E+02, 0.53178E+02, 0.53939E+02, 0.54705E+02, - 0.55476E+02, 0.56252E+02, 0.57033E+02, 0.57820E+02, 0.58612E+02, - 0.59409E+02, 0.60212E+02, 0.61020E+02, 0.61833E+02, 0.62652E+02, - 0.63477E+02, 0.64308E+02, 0.65144E+02, 0.65986E+02, 0.66833E+02, - 0.67687E+02, 0.68546E+02, 0.69411E+02, 0.70283E+02, 0.71160E+02, - 0.72043E+02, 0.72933E+02, 0.73829E+02, 0.74730E+02, 0.75638E+02, - 0.76553E+02, 0.77473E+02, 0.78400E+02, 0.79333E+02, 0.80273E+02, - 0.81219E+02, 0.82172E+02, 0.83131E+02, 0.84097E+02, 0.85069E+02, - 0.86048E+02]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.15265E+01, 0.22243E+01, 0.29619E+01, 0.36724E+01, 0.43456E+01, 0.49880E+01, 0.56090E+01, + 0.62165E+01, 0.68161E+01, 0.74113E+01, 0.80044E+01, 0.85966E+01, 0.91887E+01, 0.97810E+01, + 0.10374E+02, 0.10967E+02, 0.11561E+02, 0.12156E+02, 0.12751E+02, 0.13347E+02, 0.13944E+02, + 0.14541E+02, 0.15139E+02, 0.15738E+02, 0.16337E+02, 0.16937E+02, 0.17538E+02, 0.18140E+02, + 0.18743E+02, 0.19346E+02, 0.19951E+02, 0.20556E+02, 0.21163E+02, 0.21771E+02, 0.22379E+02, + 0.22990E+02, 0.23601E+02, 0.24214E+02, 0.24829E+02, 0.25445E+02, 0.26063E+02, 0.26683E+02, + 0.27304E+02, 0.27928E+02, 0.28553E+02, 0.29181E+02, 0.29811E+02, 0.30443E+02, 0.31078E+02, + 0.31715E+02, 0.32355E+02, 0.32997E+02, 0.33643E+02, 0.34291E+02, 0.34942E+02, 0.35596E+02, + 0.36253E+02, 0.36914E+02, 0.37578E+02, 0.38245E+02, 0.38916E+02, 0.39590E+02, 0.40268E+02, + 0.40949E+02, 0.41635E+02, 0.42324E+02, 0.43017E+02, 0.43715E+02, 0.44416E+02, 0.45122E+02, + 0.45831E+02, 0.46546E+02, 0.47264E+02, 0.47987E+02, 0.48714E+02, 0.49446E+02, 0.50183E+02, + 0.50925E+02, 0.51671E+02, 0.52422E+02, 0.53178E+02, 0.53939E+02, 0.54705E+02, 0.55476E+02, + 0.56252E+02, 0.57033E+02, 0.57820E+02, 0.58612E+02, 0.59409E+02, 0.60212E+02, 0.61020E+02, + 0.61833E+02, 0.62652E+02, 0.63477E+02, 0.64308E+02, 0.65144E+02, 0.65986E+02, 0.66833E+02, + 0.67687E+02, 0.68546E+02, 0.69411E+02, 0.70283E+02, 0.71160E+02, 0.72043E+02, 0.72933E+02, + 0.73829E+02, 0.74730E+02, 0.75638E+02, 0.76553E+02, 0.77473E+02, 0.78400E+02, 0.79333E+02, + 0.80273E+02, 0.81219E+02, 0.82172E+02, 0.83131E+02, 0.84097E+02, 0.85069E+02, 0.86048E+02]) # --------------- H2 12: M = 45, I = 2 --------------------- M = 45 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(6.) -TIPS_ISO_HASH[(M, I)] = float32([0.81692E+01, 0.10308E+02, 0.12557E+02, - 0.14848E+02, 0.17159E+02, 0.19482E+02, 0.21815E+02, 0.24153E+02, - 0.26497E+02, 0.28845E+02, 0.31197E+02, 0.33552E+02, 0.35910E+02, - 0.38272E+02, 0.40636E+02, 0.43002E+02, 0.45372E+02, 0.47744E+02, - 0.50119E+02, 0.52496E+02, 0.54877E+02, 0.57261E+02, 0.59649E+02, - 0.62040E+02, 0.64435E+02, 0.66835E+02, 0.69240E+02, 0.71650E+02, - 0.74066E+02, 0.76489E+02, 0.78918E+02, 0.81354E+02, 0.83799E+02, - 0.86252E+02, 0.88715E+02, 0.91187E+02, 0.93669E+02, 0.96163E+02, - 0.98668E+02, 0.10118E+03, 0.10371E+03, 0.10626E+03, 0.10881E+03, - 0.11138E+03, 0.11397E+03, 0.11657E+03, 0.11919E+03, 0.12182E+03, - 0.12447E+03, 0.12714E+03, 0.12982E+03, 0.13252E+03, 0.13524E+03, - 0.13798E+03, 0.14074E+03, 0.14352E+03, 0.14632E+03, 0.14914E+03, - 0.15198E+03, 0.15484E+03, 0.15772E+03, 0.16062E+03, 0.16355E+03, - 0.16649E+03, 0.16946E+03, 0.17246E+03, 0.17547E+03, 0.17851E+03, - 0.18157E+03, 0.18466E+03, 0.18777E+03, 0.19090E+03, 0.19406E+03, - 0.19725E+03, 0.20045E+03, 0.20369E+03, 0.20695E+03, 0.21023E+03, - 0.21354E+03, 0.21687E+03, 0.22024E+03, 0.22362E+03, 0.22704E+03, - 0.23048E+03, 0.23394E+03, 0.23744E+03, 0.24096E+03, 0.24451E+03, - 0.24808E+03, 0.25169E+03, 0.25532E+03, 0.25897E+03, 0.26266E+03, - 0.26638E+03, 0.27012E+03, 0.27389E+03, 0.27769E+03, 0.28152E+03, - 0.28537E+03, 0.28926E+03, 0.29317E+03, 0.29712E+03, 0.30109E+03, - 0.30509E+03, 0.30913E+03, 0.31319E+03, 0.31728E+03, 0.32140E+03, - 0.32555E+03, 0.32974E+03, 0.33395E+03, 0.33819E+03, 0.34246E+03, - 0.34677E+03, 0.35110E+03, 0.35547E+03, 0.35987E+03, 0.36429E+03, - 0.36875E+03]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.81692E+01, 0.10308E+02, 0.12557E+02, 0.14848E+02, 0.17159E+02, 0.19482E+02, 0.21815E+02, + 0.24153E+02, 0.26497E+02, 0.28845E+02, 0.31197E+02, 0.33552E+02, 0.35910E+02, 0.38272E+02, + 0.40636E+02, 0.43002E+02, 0.45372E+02, 0.47744E+02, 0.50119E+02, 0.52496E+02, 0.54877E+02, + 0.57261E+02, 0.59649E+02, 0.62040E+02, 0.64435E+02, 0.66835E+02, 0.69240E+02, 0.71650E+02, + 0.74066E+02, 0.76489E+02, 0.78918E+02, 0.81354E+02, 0.83799E+02, 0.86252E+02, 0.88715E+02, + 0.91187E+02, 0.93669E+02, 0.96163E+02, 0.98668E+02, 0.10118E+03, 0.10371E+03, 0.10626E+03, + 0.10881E+03, 0.11138E+03, 0.11397E+03, 0.11657E+03, 0.11919E+03, 0.12182E+03, 0.12447E+03, + 0.12714E+03, 0.12982E+03, 0.13252E+03, 0.13524E+03, 0.13798E+03, 0.14074E+03, 0.14352E+03, + 0.14632E+03, 0.14914E+03, 0.15198E+03, 0.15484E+03, 0.15772E+03, 0.16062E+03, 0.16355E+03, + 0.16649E+03, 0.16946E+03, 0.17246E+03, 0.17547E+03, 0.17851E+03, 0.18157E+03, 0.18466E+03, + 0.18777E+03, 0.19090E+03, 0.19406E+03, 0.19725E+03, 0.20045E+03, 0.20369E+03, 0.20695E+03, + 0.21023E+03, 0.21354E+03, 0.21687E+03, 0.22024E+03, 0.22362E+03, 0.22704E+03, 0.23048E+03, + 0.23394E+03, 0.23744E+03, 0.24096E+03, 0.24451E+03, 0.24808E+03, 0.25169E+03, 0.25532E+03, + 0.25897E+03, 0.26266E+03, 0.26638E+03, 0.27012E+03, 0.27389E+03, 0.27769E+03, 0.28152E+03, + 0.28537E+03, 0.28926E+03, 0.29317E+03, 0.29712E+03, 0.30109E+03, 0.30509E+03, 0.30913E+03, + 0.31319E+03, 0.31728E+03, 0.32140E+03, 0.32555E+03, 0.32974E+03, 0.33395E+03, 0.33819E+03, + 0.34246E+03, 0.34677E+03, 0.35110E+03, 0.35547E+03, 0.35987E+03, 0.36429E+03, 0.36875E+03]) # --------------- CS 22: M = 46, I = 1 --------------------- M = 46 I = 1 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.51416E+02, 0.72723E+02, 0.94044E+02, - 0.11538E+03, 0.13673E+03, 0.15810E+03, 0.17949E+03, 0.20093E+03, - 0.22245E+03, 0.24407E+03, 0.26582E+03, 0.28776E+03, 0.30992E+03, - 0.33233E+03, 0.35504E+03, 0.37807E+03, 0.40147E+03, 0.42525E+03, - 0.44944E+03, 0.47406E+03, 0.49914E+03, 0.52468E+03, 0.55071E+03, - 0.57723E+03, 0.60427E+03, 0.63183E+03, 0.65991E+03, 0.68854E+03, - 0.71771E+03, 0.74743E+03, 0.77771E+03, 0.80855E+03, 0.83996E+03, - 0.87193E+03, 0.90449E+03, 0.93762E+03, 0.97134E+03, 0.10056E+04, - 0.10405E+04, 0.10760E+04, 0.11121E+04, 0.11487E+04, 0.11860E+04, - 0.12239E+04, 0.12623E+04, 0.13014E+04, 0.13410E+04, 0.13813E+04, - 0.14222E+04, 0.14637E+04, 0.15057E+04, 0.15484E+04, 0.15917E+04, - 0.16357E+04, 0.16802E+04, 0.17253E+04, 0.17711E+04, 0.18175E+04, - 0.18645E+04, 0.19121E+04, 0.19603E+04, 0.20091E+04, 0.20586E+04, - 0.21087E+04, 0.21594E+04, 0.22107E+04, 0.22626E+04, 0.23152E+04, - 0.23684E+04, 0.24222E+04, 0.24767E+04, 0.25317E+04, 0.25874E+04, - 0.26438E+04, 0.27007E+04, 0.27583E+04, 0.28165E+04, 0.28754E+04, - 0.29348E+04, 0.29949E+04, 0.30557E+04, 0.31170E+04, 0.31790E+04, - 0.32417E+04, 0.33049E+04, 0.33688E+04, 0.34334E+04, 0.34986E+04, - 0.35644E+04, 0.36308E+04, 0.36979E+04, 0.37656E+04, 0.38340E+04, - 0.39030E+04, 0.39727E+04, 0.40430E+04, 0.41139E+04, 0.41855E+04, - 0.42577E+04, 0.43306E+04, 0.44041E+04, 0.44782E+04, 0.45530E+04, - 0.46284E+04, 0.47045E+04, 0.47813E+04, 0.48587E+04, 0.49367E+04, - 0.50154E+04, 0.50947E+04, 0.51747E+04, 0.52553E+04, 0.53366E+04, - 0.54185E+04, 0.55011E+04, 0.55844E+04, 0.56683E+04, 0.57528E+04, - 0.58380E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.51416E+02, 0.72723E+02, 0.94044E+02, 0.11538E+03, 0.13673E+03, 0.15810E+03, 0.17949E+03, + 0.20093E+03, 0.22245E+03, 0.24407E+03, 0.26582E+03, 0.28776E+03, 0.30992E+03, 0.33233E+03, + 0.35504E+03, 0.37807E+03, 0.40147E+03, 0.42525E+03, 0.44944E+03, 0.47406E+03, 0.49914E+03, + 0.52468E+03, 0.55071E+03, 0.57723E+03, 0.60427E+03, 0.63183E+03, 0.65991E+03, 0.68854E+03, + 0.71771E+03, 0.74743E+03, 0.77771E+03, 0.80855E+03, 0.83996E+03, 0.87193E+03, 0.90449E+03, + 0.93762E+03, 0.97134E+03, 0.10056E+04, 0.10405E+04, 0.10760E+04, 0.11121E+04, 0.11487E+04, + 0.11860E+04, 0.12239E+04, 0.12623E+04, 0.13014E+04, 0.13410E+04, 0.13813E+04, 0.14222E+04, + 0.14637E+04, 0.15057E+04, 0.15484E+04, 0.15917E+04, 0.16357E+04, 0.16802E+04, 0.17253E+04, + 0.17711E+04, 0.18175E+04, 0.18645E+04, 0.19121E+04, 0.19603E+04, 0.20091E+04, 0.20586E+04, + 0.21087E+04, 0.21594E+04, 0.22107E+04, 0.22626E+04, 0.23152E+04, 0.23684E+04, 0.24222E+04, + 0.24767E+04, 0.25317E+04, 0.25874E+04, 0.26438E+04, 0.27007E+04, 0.27583E+04, 0.28165E+04, + 0.28754E+04, 0.29348E+04, 0.29949E+04, 0.30557E+04, 0.31170E+04, 0.31790E+04, 0.32417E+04, + 0.33049E+04, 0.33688E+04, 0.34334E+04, 0.34986E+04, 0.35644E+04, 0.36308E+04, 0.36979E+04, + 0.37656E+04, 0.38340E+04, 0.39030E+04, 0.39727E+04, 0.40430E+04, 0.41139E+04, 0.41855E+04, + 0.42577E+04, 0.43306E+04, 0.44041E+04, 0.44782E+04, 0.45530E+04, 0.46284E+04, 0.47045E+04, + 0.47813E+04, 0.48587E+04, 0.49367E+04, 0.50154E+04, 0.50947E+04, 0.51747E+04, 0.52553E+04, + 0.53366E+04, 0.54185E+04, 0.55011E+04, 0.55844E+04, 0.56683E+04, 0.57528E+04, 0.58380E+04]) # --------------- CS 24: M = 46, I = 2 --------------------- M = 46 I = 2 TIPS_GSI_HASH[(M, I)] = __FloatType__(1.) -TIPS_ISO_HASH[(M, I)] = float32([0.52247E+02, 0.73900E+02, 0.95568E+02, - 0.11725E+03, 0.13895E+03, 0.16066E+03, 0.18241E+03, 0.20420E+03, - 0.22607E+03, 0.24805E+03, 0.27018E+03, 0.29249E+03, 0.31503E+03, - 0.33784E+03, 0.36096E+03, 0.38442E+03, 0.40824E+03, 0.43247E+03, - 0.45712E+03, 0.48221E+03, 0.50778E+03, 0.53382E+03, 0.56037E+03, - 0.58743E+03, 0.61501E+03, 0.64312E+03, 0.67179E+03, 0.70100E+03, - 0.73077E+03, 0.76111E+03, 0.79202E+03, 0.82351E+03, 0.85559E+03, - 0.88824E+03, 0.92149E+03, 0.95533E+03, 0.98977E+03, 0.10248E+04, - 0.10605E+04, 0.10967E+04, 0.11336E+04, 0.11710E+04, 0.12091E+04, - 0.12478E+04, 0.12871E+04, 0.13270E+04, 0.13675E+04, 0.14087E+04, - 0.14505E+04, 0.14929E+04, 0.15359E+04, 0.15795E+04, 0.16238E+04, - 0.16687E+04, 0.17142E+04, 0.17604E+04, 0.18071E+04, 0.18546E+04, - 0.19026E+04, 0.19513E+04, 0.20006E+04, 0.20505E+04, 0.21011E+04, - 0.21523E+04, 0.22042E+04, 0.22566E+04, 0.23098E+04, 0.23635E+04, - 0.24179E+04, 0.24730E+04, 0.25286E+04, 0.25850E+04, 0.26419E+04, - 0.26995E+04, 0.27578E+04, 0.28167E+04, 0.28762E+04, 0.29364E+04, - 0.29972E+04, 0.30587E+04, 0.31208E+04, 0.31836E+04, 0.32470E+04, - 0.33111E+04, 0.33758E+04, 0.34412E+04, 0.35072E+04, 0.35739E+04, - 0.36412E+04, 0.37092E+04, 0.37778E+04, 0.38471E+04, 0.39171E+04, - 0.39877E+04, 0.40589E+04, 0.41309E+04, 0.42034E+04, 0.42767E+04, - 0.43505E+04, 0.44251E+04, 0.45003E+04, 0.45762E+04, 0.46527E+04, - 0.47299E+04, 0.48077E+04, 0.48863E+04, 0.49654E+04, 0.50453E+04, - 0.51258E+04, 0.52070E+04, 0.52888E+04, 0.53713E+04, 0.54545E+04, - 0.55383E+04, 0.56229E+04, 0.57080E+04, 0.57939E+04, 0.58804E+04, - 0.59676E+04]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.52247E+02, 0.73900E+02, 0.95568E+02, 0.11725E+03, 0.13895E+03, 0.16066E+03, 0.18241E+03, + 0.20420E+03, 0.22607E+03, 0.24805E+03, 0.27018E+03, 0.29249E+03, 0.31503E+03, 0.33784E+03, + 0.36096E+03, 0.38442E+03, 0.40824E+03, 0.43247E+03, 0.45712E+03, 0.48221E+03, 0.50778E+03, + 0.53382E+03, 0.56037E+03, 0.58743E+03, 0.61501E+03, 0.64312E+03, 0.67179E+03, 0.70100E+03, + 0.73077E+03, 0.76111E+03, 0.79202E+03, 0.82351E+03, 0.85559E+03, 0.88824E+03, 0.92149E+03, + 0.95533E+03, 0.98977E+03, 0.10248E+04, 0.10605E+04, 0.10967E+04, 0.11336E+04, 0.11710E+04, + 0.12091E+04, 0.12478E+04, 0.12871E+04, 0.13270E+04, 0.13675E+04, 0.14087E+04, 0.14505E+04, + 0.14929E+04, 0.15359E+04, 0.15795E+04, 0.16238E+04, 0.16687E+04, 0.17142E+04, 0.17604E+04, + 0.18071E+04, 0.18546E+04, 0.19026E+04, 0.19513E+04, 0.20006E+04, 0.20505E+04, 0.21011E+04, + 0.21523E+04, 0.22042E+04, 0.22566E+04, 0.23098E+04, 0.23635E+04, 0.24179E+04, 0.24730E+04, + 0.25286E+04, 0.25850E+04, 0.26419E+04, 0.26995E+04, 0.27578E+04, 0.28167E+04, 0.28762E+04, + 0.29364E+04, 0.29972E+04, 0.30587E+04, 0.31208E+04, 0.31836E+04, 0.32470E+04, 0.33111E+04, + 0.33758E+04, 0.34412E+04, 0.35072E+04, 0.35739E+04, 0.36412E+04, 0.37092E+04, 0.37778E+04, + 0.38471E+04, 0.39171E+04, 0.39877E+04, 0.40589E+04, 0.41309E+04, 0.42034E+04, 0.42767E+04, + 0.43505E+04, 0.44251E+04, 0.45003E+04, 0.45762E+04, 0.46527E+04, 0.47299E+04, 0.48077E+04, + 0.48863E+04, 0.49654E+04, 0.50453E+04, 0.51258E+04, 0.52070E+04, 0.52888E+04, 0.53713E+04, + 0.54545E+04, 0.55383E+04, 0.56229E+04, 0.57080E+04, 0.57939E+04, 0.58804E+04, 0.59676E+04]) # --------------- CS 32: M = 46, I = 3 --------------------- M = 46 I = 3 TIPS_GSI_HASH[(M, I)] = __FloatType__(2.) -TIPS_ISO_HASH[(M, I)] = float32([0.10889E+03, 0.15403E+03, 0.19920E+03, - 0.24440E+03, 0.28964E+03, 0.33491E+03, 0.38026E+03, 0.42571E+03, - 0.47134E+03, 0.51722E+03, 0.56342E+03, 0.61005E+03, 0.65719E+03, - 0.70493E+03, 0.75334E+03, 0.80249E+03, 0.85245E+03, 0.90329E+03, - 0.95504E+03, 0.10078E+04, 0.10615E+04, 0.11163E+04, 0.11721E+04, - 0.12291E+04, 0.12872E+04, 0.13464E+04, 0.14068E+04, 0.14684E+04, - 0.15311E+04, 0.15951E+04, 0.16604E+04, 0.17268E+04, 0.17945E+04, - 0.18635E+04, 0.19337E+04, 0.20051E+04, 0.20779E+04, 0.21519E+04, - 0.22272E+04, 0.23038E+04, 0.23817E+04, 0.24609E+04, 0.25414E+04, - 0.26232E+04, 0.27064E+04, 0.27908E+04, 0.28765E+04, 0.29636E+04, - 0.30520E+04, 0.31417E+04, 0.32327E+04, 0.33251E+04, 0.34188E+04, - 0.35138E+04, 0.36102E+04, 0.37079E+04, 0.38070E+04, 0.39074E+04, - 0.40091E+04, 0.41122E+04, 0.42166E+04, 0.43224E+04, 0.44295E+04, - 0.45380E+04, 0.46478E+04, 0.47590E+04, 0.48715E+04, 0.49854E+04, - 0.51007E+04, 0.52173E+04, 0.53353E+04, 0.54547E+04, 0.55754E+04, - 0.56975E+04, 0.58210E+04, 0.59458E+04, 0.60720E+04, 0.61996E+04, - 0.63285E+04, 0.64589E+04, 0.65906E+04, 0.67236E+04, 0.68581E+04, - 0.69940E+04, 0.71312E+04, 0.72698E+04, 0.74098E+04, 0.75512E+04, - 0.76940E+04, 0.78381E+04, 0.79837E+04, 0.81307E+04, 0.82790E+04, - 0.84287E+04, 0.85799E+04, 0.87324E+04, 0.88864E+04, 0.90417E+04, - 0.91984E+04, 0.93566E+04, 0.95161E+04, 0.96771E+04, 0.98394E+04, - 0.10003E+05, 0.10168E+05, 0.10335E+05, 0.10503E+05, 0.10672E+05, - 0.10843E+05, 0.11015E+05, 0.11189E+05, 0.11364E+05, 0.11541E+05, - 0.11719E+05, 0.11898E+05, 0.12079E+05, 0.12261E+05, 0.12444E+05, - 0.12630E+05]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.10889E+03, 0.15403E+03, 0.19920E+03, 0.24440E+03, 0.28964E+03, 0.33491E+03, 0.38026E+03, + 0.42571E+03, 0.47134E+03, 0.51722E+03, 0.56342E+03, 0.61005E+03, 0.65719E+03, 0.70493E+03, + 0.75334E+03, 0.80249E+03, 0.85245E+03, 0.90329E+03, 0.95504E+03, 0.10078E+04, 0.10615E+04, + 0.11163E+04, 0.11721E+04, 0.12291E+04, 0.12872E+04, 0.13464E+04, 0.14068E+04, 0.14684E+04, + 0.15311E+04, 0.15951E+04, 0.16604E+04, 0.17268E+04, 0.17945E+04, 0.18635E+04, 0.19337E+04, + 0.20051E+04, 0.20779E+04, 0.21519E+04, 0.22272E+04, 0.23038E+04, 0.23817E+04, 0.24609E+04, + 0.25414E+04, 0.26232E+04, 0.27064E+04, 0.27908E+04, 0.28765E+04, 0.29636E+04, 0.30520E+04, + 0.31417E+04, 0.32327E+04, 0.33251E+04, 0.34188E+04, 0.35138E+04, 0.36102E+04, 0.37079E+04, + 0.38070E+04, 0.39074E+04, 0.40091E+04, 0.41122E+04, 0.42166E+04, 0.43224E+04, 0.44295E+04, + 0.45380E+04, 0.46478E+04, 0.47590E+04, 0.48715E+04, 0.49854E+04, 0.51007E+04, 0.52173E+04, + 0.53353E+04, 0.54547E+04, 0.55754E+04, 0.56975E+04, 0.58210E+04, 0.59458E+04, 0.60720E+04, + 0.61996E+04, 0.63285E+04, 0.64589E+04, 0.65906E+04, 0.67236E+04, 0.68581E+04, 0.69940E+04, + 0.71312E+04, 0.72698E+04, 0.74098E+04, 0.75512E+04, 0.76940E+04, 0.78381E+04, 0.79837E+04, + 0.81307E+04, 0.82790E+04, 0.84287E+04, 0.85799E+04, 0.87324E+04, 0.88864E+04, 0.90417E+04, + 0.91984E+04, 0.93566E+04, 0.95161E+04, 0.96771E+04, 0.98394E+04, 0.10003E+05, 0.10168E+05, + 0.10335E+05, 0.10503E+05, 0.10672E+05, 0.10843E+05, 0.11015E+05, 0.11189E+05, 0.11364E+05, + 0.11541E+05, 0.11719E+05, 0.11898E+05, 0.12079E+05, 0.12261E+05, 0.12444E+05, 0.12630E+05]) # --------------- CS 23: M = 46, I = 4 --------------------- M = 46 I = 4 TIPS_GSI_HASH[(M, I)] = __FloatType__(4.) -TIPS_ISO_HASH[(M, I)] = float32([0.20737E+03, 0.29330E+03, 0.37930E+03, - 0.46535E+03, 0.55145E+03, 0.63764E+03, 0.72394E+03, 0.81043E+03, - 0.89722E+03, 0.98443E+03, 0.10722E+04, 0.11607E+04, 0.12501E+04, - 0.13406E+04, 0.14323E+04, 0.15253E+04, 0.16197E+04, 0.17158E+04, - 0.18135E+04, 0.19129E+04, 0.20142E+04, 0.21174E+04, 0.22226E+04, - 0.23298E+04, 0.24391E+04, 0.25504E+04, 0.26639E+04, 0.27796E+04, - 0.28976E+04, 0.30177E+04, 0.31401E+04, 0.32648E+04, 0.33918E+04, - 0.35211E+04, 0.36527E+04, 0.37867E+04, 0.39231E+04, 0.40618E+04, - 0.42029E+04, 0.43463E+04, 0.44922E+04, 0.46405E+04, 0.47912E+04, - 0.49443E+04, 0.50999E+04, 0.52579E+04, 0.54183E+04, 0.55812E+04, - 0.57465E+04, 0.59143E+04, 0.60846E+04, 0.62573E+04, 0.64325E+04, - 0.66102E+04, 0.67903E+04, 0.69729E+04, 0.71581E+04, 0.73457E+04, - 0.75358E+04, 0.77284E+04, 0.79235E+04, 0.81211E+04, 0.83212E+04, - 0.85239E+04, 0.87290E+04, 0.89367E+04, 0.91469E+04, 0.93596E+04, - 0.95748E+04, 0.97926E+04, 0.10013E+05, 0.10236E+05, 0.10461E+05, - 0.10689E+05, 0.10920E+05, 0.11153E+05, 0.11388E+05, 0.11626E+05, - 0.11867E+05, 0.12110E+05, 0.12356E+05, 0.12604E+05, 0.12855E+05, - 0.13109E+05, 0.13365E+05, 0.13623E+05, 0.13884E+05, 0.14148E+05, - 0.14415E+05, 0.14683E+05, 0.14955E+05, 0.15229E+05, 0.15506E+05, - 0.15785E+05, 0.16067E+05, 0.16351E+05, 0.16638E+05, 0.16928E+05, - 0.17220E+05, 0.17515E+05, 0.17813E+05, 0.18113E+05, 0.18416E+05, - 0.18721E+05, 0.19029E+05, 0.19340E+05, 0.19653E+05, 0.19969E+05, - 0.20287E+05, 0.20608E+05, 0.20932E+05, 0.21258E+05, 0.21587E+05, - 0.21919E+05, 0.22253E+05, 0.22590E+05, 0.22930E+05, 0.23272E+05, - 0.23617E+05]) +TIPS_ISO_HASH[(M, I)] = float32( + [0.20737E+03, 0.29330E+03, 0.37930E+03, 0.46535E+03, 0.55145E+03, 0.63764E+03, 0.72394E+03, + 0.81043E+03, 0.89722E+03, 0.98443E+03, 0.10722E+04, 0.11607E+04, 0.12501E+04, 0.13406E+04, + 0.14323E+04, 0.15253E+04, 0.16197E+04, 0.17158E+04, 0.18135E+04, 0.19129E+04, 0.20142E+04, + 0.21174E+04, 0.22226E+04, 0.23298E+04, 0.24391E+04, 0.25504E+04, 0.26639E+04, 0.27796E+04, + 0.28976E+04, 0.30177E+04, 0.31401E+04, 0.32648E+04, 0.33918E+04, 0.35211E+04, 0.36527E+04, + 0.37867E+04, 0.39231E+04, 0.40618E+04, 0.42029E+04, 0.43463E+04, 0.44922E+04, 0.46405E+04, + 0.47912E+04, 0.49443E+04, 0.50999E+04, 0.52579E+04, 0.54183E+04, 0.55812E+04, 0.57465E+04, + 0.59143E+04, 0.60846E+04, 0.62573E+04, 0.64325E+04, 0.66102E+04, 0.67903E+04, 0.69729E+04, + 0.71581E+04, 0.73457E+04, 0.75358E+04, 0.77284E+04, 0.79235E+04, 0.81211E+04, 0.83212E+04, + 0.85239E+04, 0.87290E+04, 0.89367E+04, 0.91469E+04, 0.93596E+04, 0.95748E+04, 0.97926E+04, + 0.10013E+05, 0.10236E+05, 0.10461E+05, 0.10689E+05, 0.10920E+05, 0.11153E+05, 0.11388E+05, + 0.11626E+05, 0.11867E+05, 0.12110E+05, 0.12356E+05, 0.12604E+05, 0.12855E+05, 0.13109E+05, + 0.13365E+05, 0.13623E+05, 0.13884E+05, 0.14148E+05, 0.14415E+05, 0.14683E+05, 0.14955E+05, + 0.15229E+05, 0.15506E+05, 0.15785E+05, 0.16067E+05, 0.16351E+05, 0.16638E+05, 0.16928E+05, + 0.17220E+05, 0.17515E+05, 0.17813E+05, 0.18113E+05, 0.18416E+05, 0.18721E+05, 0.19029E+05, + 0.19340E+05, 0.19653E+05, 0.19969E+05, 0.20287E+05, 0.20608E+05, 0.20932E+05, 0.21258E+05, + 0.21587E+05, 0.21919E+05, 0.22253E+05, 0.22590E+05, 0.22930E+05, 0.23272E+05, 0.23617E+05]) # --------------- SO3 26: M = 46, I = 1 --------------------- not in TIPS-2011 M = 47 @@ -9822,8 +8427,8 @@ def partitionSum(M, I, T, step=None): zone = __ComplexType__(1.0e0 + 0.0e0j) zi = __ComplexType__(0.0e0 + 1.0e0j) tt = __FloatType__( - [0.5e0, 1.5e0, 2.5e0, 3.5e0, 4.5e0, 5.5e0, 6.5e0, 7.5e0, 8.5e0, 9.5e0, 10.5e0, 11.5e0, - 12.5e0, 13.5e0, 14.5e0]) + [0.5e0, 1.5e0, 2.5e0, 3.5e0, 4.5e0, 5.5e0, 6.5e0, 7.5e0, 8.5e0, 9.5e0, 10.5e0, 11.5e0, 12.5e0, + 13.5e0, 14.5e0]) pipwoeronehalf = __FloatType__(0.564189583547756e0) @@ -9856,11 +8461,11 @@ def cpf3(X, Y): T = __FloatType__( - [0.314240376e0, 0.947788391e0, 1.59768264e0, 2.27950708e0, 3.02063703e0, 3.8897249e0]) + [0.314240376e0, 0.947788391e0, 1.59768264e0, 2.27950708e0, 3.02063703e0, 3.8897249e0]) U = __FloatType__( - [1.01172805e0, -0.75197147e0, 1.2557727e-2, 1.00220082e-2, -2.42068135e-4, 5.00848061e-7]) + [1.01172805e0, -0.75197147e0, 1.2557727e-2, 1.00220082e-2, -2.42068135e-4, 5.00848061e-7]) S = __FloatType__( - [1.393237e0, 0.231152406e0, -0.155351466e0, 6.21836624e-3, 9.19082986e-5, -6.27525958e-7]) + [1.393237e0, 0.231152406e0, -0.155351466e0, 6.21836624e-3, 9.19082986e-5, -6.27525958e-7]) # Complex probability function implementation (Humlicek) @@ -9902,8 +8507,8 @@ def cpf(X, Y): Y2_REGION12 = Y1_REGION12 ** 2 # REGION2 - subindex_REGION2 = where((Y_REGION12 <= 0.85e0) & - (abs(X_REGION12) >= (18.1e0 * Y_REGION12 + 1.65e0))) + subindex_REGION2 = where( + (Y_REGION12 <= 0.85e0) & (abs(X_REGION12) >= (18.1e0 * Y_REGION12 + 1.65e0))) index_REGION2 = index_REGION12[subindex_REGION2] @@ -9928,18 +8533,18 @@ def cpf(X, Y): D1_REGION2 = Y1_REGION2 * D_REGION2 D2_REGION2 = R_REGION2 * D_REGION2 WR_REGION2 = WR_REGION2 + Y_REGION2 * ( - U[I] * (R_REGION2 * D2_REGION2 - 1.5e0 * D1_REGION2) + - S[I] * Y3_REGION2 * D2_REGION2) / (R2_REGION2 + 2.25e0) + U[I] * (R_REGION2 * D2_REGION2 - 1.5e0 * D1_REGION2) + S[ + I] * Y3_REGION2 * D2_REGION2) / (R2_REGION2 + 2.25e0) R_REGION2 = X_REGION2 + T[I] R2_REGION2 = R_REGION2 ** 2 D_REGION2 = __FloatType__(1.0e0) / (R2_REGION2 + Y2_REGION2) D3_REGION2 = Y1_REGION2 * D_REGION2 D4_REGION2 = R_REGION2 * D_REGION2 WR_REGION2 = WR_REGION2 + Y_REGION2 * ( - U[I] * (R_REGION2 * D4_REGION2 - 1.5e0 * D3_REGION2) - - S[I] * Y3_REGION2 * D4_REGION2) / (R2_REGION2 + 2.25e0) + U[I] * (R_REGION2 * D4_REGION2 - 1.5e0 * D3_REGION2) - S[ + I] * Y3_REGION2 * D4_REGION2) / (R2_REGION2 + 2.25e0) WI_REGION2 = WI_REGION2 + U[I] * (D2_REGION2 + D4_REGION2) + S[I] * ( - D1_REGION2 - D3_REGION2) + D1_REGION2 - D3_REGION2) # REGION3 index_REGION1 = setdiff1d(array(index_REGION12), array(index_REGION2)) @@ -9964,9 +8569,9 @@ def cpf(X, Y): D4_REGION1 = R_REGION1 * D_REGION1 WR_REGION1 = WR_REGION1 + U[I] * (D1_REGION1 + D3_REGION1) - S[I] * ( - D2_REGION1 - D4_REGION1) + D2_REGION1 - D4_REGION1) WI_REGION1 = WI_REGION1 + U[I] * (D2_REGION1 + D4_REGION1) + S[I] * ( - D1_REGION1 - D3_REGION1) + D1_REGION1 - D3_REGION1) # total result WR_TOTAL = zeros(len(X)) @@ -10099,8 +8704,8 @@ def pcqsdhc(sg0, GamD, Gam0, Gam2, Shift0, Shift2, anuVC, eta, sg): sg = array([sg]) number_of_points = len(sg) - Aterm_GLOBAL = zeros(number_of_points, dtype = __ComplexType__) - Bterm_GLOBAL = zeros(number_of_points, dtype = __ComplexType__) + Aterm_GLOBAL = zeros(number_of_points, dtype=__ComplexType__) + Bterm_GLOBAL = zeros(number_of_points, dtype=__ComplexType__) cte = sqrt(log(2.0e0)) / GamD rpi = sqrt(pi) @@ -10122,10 +8727,10 @@ def pcqsdhc(sg0, GamD, Gam0, Gam2, Shift0, Shift2, anuVC, eta, sg): index_NOT_Z1 = ~index_Z1 if any(index_Z1): Bterm_GLOBAL = rpi * cte * ( - (1.0e0 - Z1 ** 2) * __ComplexType__(WR1 + 1.0e0j * WI1) + Z1 / rpi) + (1.0e0 - Z1 ** 2) * __ComplexType__(WR1 + 1.0e0j * WI1) + Z1 / rpi) if any(index_NOT_Z1): Bterm_GLOBAL = cte * ( - rpi * __ComplexType__(WR1 + 1.0e0j * WI1) + 0.5e0 / Z1 - 0.75e0 / (Z1 ** 3)) + rpi * __ComplexType__(WR1 + 1.0e0j * WI1) + 0.5e0 / Z1 - 0.75e0 / (Z1 ** 3)) else: # PART2, PART3 AND PART4 (PART4 IS A MAIN PART) @@ -10176,11 +8781,10 @@ def pcqsdhc(sg0, GamD, Gam0, Gam2, Shift0, Shift2, anuVC, eta, sg): Aterm = rpi * cte * (__ComplexType__(WR1_PART4 + 1.0e0j * WI1_PART4) - __ComplexType__( WR2_PART4 + 1.0e0j * WI2_PART4)) - Bterm = (-1.0e0 + - rpi / (2.0e0 * csqrtY) * (1.0e0 - Z1 ** 2) * __ComplexType__( - WR1_PART4 + 1.0e0j * WI1_PART4) - - rpi / (2.0e0 * csqrtY) * (1.0e0 - Z2 ** 2) * __ComplexType__( - WR2_PART4 + 1.0e0j * WI2_PART4)) / c2t + Bterm = (-1.0e0 + rpi / (2.0e0 * csqrtY) * (1.0e0 - Z1 ** 2) * __ComplexType__( + WR1_PART4 + 1.0e0j * WI1_PART4) - rpi / (2.0e0 * csqrtY) * ( + 1.0e0 - Z2 ** 2) * __ComplexType__( + WR2_PART4 + 1.0e0j * WI2_PART4)) / c2t Aterm_GLOBAL[index_PART4] = Aterm Bterm_GLOBAL[index_PART4] = Bterm @@ -10197,11 +8801,10 @@ def pcqsdhc(sg0, GamD, Gam0, Gam2, Shift0, Shift2, anuVC, eta, sg): WR2_PART2, WI2_PART2 = VARIABLES['CPF'](xZ2, yZ2) Aterm = rpi * cte * (__ComplexType__(WR1_PART2 + 1.0e0j * WI1_PART2) - __ComplexType__( WR2_PART2 + 1.0e0j * WI2_PART2)) - Bterm = (-1.0e0 + - rpi / (2.0e0 * csqrtY) * (1.0e0 - Z1 ** 2) * __ComplexType__( - WR1_PART2 + 1.0e0j * WI1_PART2) - - rpi / (2.0e0 * csqrtY) * (1.0e0 - Z2 ** 2) * __ComplexType__( - WR2_PART2 + 1.0e0j * WI2_PART2)) / c2t + Bterm = (-1.0e0 + rpi / (2.0e0 * csqrtY) * (1.0e0 - Z1 ** 2) * __ComplexType__( + WR1_PART2 + 1.0e0j * WI1_PART2) - rpi / (2.0e0 * csqrtY) * ( + 1.0e0 - Z2 ** 2) * __ComplexType__( + WR2_PART2 + 1.0e0j * WI2_PART2)) / c2t Aterm_GLOBAL[index_PART2] = Aterm Bterm_GLOBAL[index_PART2] = Bterm @@ -10213,35 +8816,33 @@ def pcqsdhc(sg0, GamD, Gam0, Gam2, Shift0, Shift2, anuVC, eta, sg): WR1_PART3, WI1_PART3 = VARIABLES['CPF'](xZ1, yZ1) index_ABS = abs(sqrt(X_TMP)) <= 4.0e3 index_NOT_ABS = ~index_ABS - Aterm = zeros(len(index_PART3), dtype = __ComplexType__) - Bterm = zeros(len(index_PART3), dtype = __ComplexType__) + Aterm = zeros(len(index_PART3), dtype=__ComplexType__) + Bterm = zeros(len(index_PART3), dtype=__ComplexType__) if any(index_ABS): xXb = -sqrt(X).imag yXb = sqrt(X).real WRb, WIb = VARIABLES['CPF'](xXb, yXb) Aterm[index_ABS] = (2.0e0 * rpi / c2t) * ( - 1.0e0 / rpi - sqrt(X_TMP[index_ABS]) * __ComplexType__( - WRb + 1.0e0j * WIb)) - Bterm[index_ABS] = (1.0e0 / c2t) * (-1.0e0 + - 2.0e0 * rpi * (1.0e0 - X_TMP[ - index_ABS] - 2.0e0 * Y) * (1.0e0 / rpi - sqrt( - X_TMP[index_ABS]) * __ComplexType__(WRb + 1.0e0j * WIb)) + - 2.0e0 * rpi * sqrt( - X_TMP[index_ABS] + Y) * __ComplexType__(WR1_PART3 + 1.0e0j * WI1_PART3)) + 1.0e0 / rpi - sqrt(X_TMP[index_ABS]) * __ComplexType__(WRb + 1.0e0j * WIb)) + Bterm[index_ABS] = (1.0e0 / c2t) * ( + -1.0e0 + 2.0e0 * rpi * (1.0e0 - X_TMP[index_ABS] - 2.0e0 * Y) * ( + 1.0e0 / rpi - sqrt(X_TMP[index_ABS]) * __ComplexType__( + WRb + 1.0e0j * WIb)) + 2.0e0 * rpi * sqrt( + X_TMP[index_ABS] + Y) * __ComplexType__(WR1_PART3 + 1.0e0j * WI1_PART3)) if any(index_NOT_ABS): Aterm[index_NOT_ABS] = (1.0e0 / c2t) * ( - 1.0e0 / X_TMP[index_NOT_ABS] - 1.5e0 / (X_TMP[index_NOT_ABS] ** 2)) + 1.0e0 / X_TMP[index_NOT_ABS] - 1.5e0 / (X_TMP[index_NOT_ABS] ** 2)) Bterm[index_NOT_ABS] = (1.0e0 / c2t) * ( - -1.0e0 + (1.0e0 - X_TMP[index_NOT_ABS] - 2.0e0 * Y) * - (1.0e0 / X_TMP[index_NOT_ABS] - 1.5e0 / (X_TMP[index_NOT_ABS] ** 2)) + - 2.0e0 * rpi * sqrt(X_TMP[index_NOT_ABS] + Y) * __ComplexType__( - WR1 + 1.0e0j * WI1)) + -1.0e0 + (1.0e0 - X_TMP[index_NOT_ABS] - 2.0e0 * Y) * ( + 1.0e0 / X_TMP[index_NOT_ABS] - 1.5e0 / ( + X_TMP[index_NOT_ABS] ** 2)) + 2.0e0 * rpi * sqrt( + X_TMP[index_NOT_ABS] + Y) * __ComplexType__(WR1 + 1.0e0j * WI1)) Aterm_GLOBAL[index_PART3] = Aterm Bterm_GLOBAL[index_PART3] = Bterm # common part LS_pCqSDHC = (1.0e0 / pi) * (Aterm_GLOBAL / ( - 1.0e0 - (anuVC - eta * (c0 - 1.5e0 * c2)) * Aterm_GLOBAL + eta * c2 * Bterm_GLOBAL)) + 1.0e0 - (anuVC - eta * (c0 - 1.5e0 * c2)) * Aterm_GLOBAL + eta * c2 * Bterm_GLOBAL)) return LS_pCqSDHC.real, LS_pCqSDHC.imag @@ -10397,8 +8998,8 @@ def volumeConcentration(p, T): # ------------------------------- PARAMETER DEPENDENCIES -------------------------------- # temperature dependence for intencities (HITRAN) -def EnvironmentDependency_Intensity(LineIntensityRef, T, Tref, SigmaT, SigmaTref, - LowerStateEnergy, LineCenter): +def EnvironmentDependency_Intensity(LineIntensityRef, T, Tref, SigmaT, SigmaTref, LowerStateEnergy, + LineCenter): const = __FloatType__(1.4388028496642257) ch = exp(-const * LowerStateEnergy / T) * (1 - exp(-const * LineCenter / T)) zn = exp(-const * LowerStateEnergy / Tref) * (1 - exp(-const * LineCenter / Tref)) @@ -10442,10 +9043,10 @@ def EnvironmentDependency_anuVC(anuVC_ref, T, Tref, p, pref): # ------------------------------- BINGINGS -------------------------------- # default parameter bindings -DefaultParameterBindings = { } +DefaultParameterBindings = {} # default temperature dependencies -DefaultEnvironmentDependencyBindings = { } +DefaultEnvironmentDependencyBindings = {} # ------------------------------- /BINGINGS -------------------------------- @@ -10466,14 +9067,14 @@ def listOfTuples(a): # determine default parameters from those which are passed to absorptionCoefficient_... -def getDefaultValuesForXsect(Components, SourceTables, Environment, OmegaRange, - OmegaStep, OmegaWing, IntensityThreshold, Format): +def getDefaultValuesForXsect(Components, SourceTables, Environment, OmegaRange, OmegaStep, + OmegaWing, IntensityThreshold, Format): if SourceTables[0] == None: SourceTables = ['__BUFFER__', ] if Environment == None: - Environment = { 'T': 296., 'p': 1. } + Environment = {'T': 296., 'p': 1.} if Components == [None]: - CompDict = { } + CompDict = {} for TableName in SourceTables: # check table existance if TableName not in LOCAL_TABLE_CACHE.keys(): @@ -10515,8 +9116,8 @@ def getDefaultValuesForXsect(Components, SourceTables, Environment, OmegaRange, Format = '%%.%df %%e' % actual_number_of_digits """ Format = '%.12f %e' - return Components, SourceTables, Environment, OmegaRange, \ - OmegaStep, OmegaWing, IntensityThreshold, Format + return Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, \ + IntensityThreshold, Format # save numpy arrays to file @@ -10539,12 +9140,11 @@ def save_to_file(fname, fformat, *arg): def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFunction=PYTIPS, Environment=None, OmegaRange=None, OmegaStep=None, OmegaWing=None, IntensityThreshold=DefaultIntensityThreshold, - OmegaWingHW=DefaultOmegaWingHW, - GammaL='gamma_air', HITRAN_units=True, LineShift=True, - File=None, Format=None, OmegaGrid=None, + OmegaWingHW=DefaultOmegaWingHW, GammaL='gamma_air', HITRAN_units=True, + LineShift=True, File=None, Format=None, OmegaGrid=None, WavenumberRange=None, WavenumberStep=None, WavenumberWing=None, - WavenumberWingHW=None, WavenumberGrid=None, - Diluent={ }, EnvDependences=None): + WavenumberWingHW=None, WavenumberGrid=None, Diluent={}, + EnvDependences=None): """ INPUT PARAMETERS: Components: list of tuples [(M,I,D)], where @@ -10605,10 +9205,10 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti SourceTables = listOfTuples(SourceTables) # determine final input values - Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, \ - IntensityThreshold, Format = \ - getDefaultValuesForXsect(Components, SourceTables, Environment, OmegaRange, - OmegaStep, OmegaWing, IntensityThreshold, Format) + Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, IntensityThreshold, \ + Format = getDefaultValuesForXsect( + Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, IntensityThreshold, + Format) # warn user about too large omega step if OmegaStep > 0.1: @@ -10643,8 +9243,8 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti print('absorptionCoefficient_HT: TrefHT=%f' % TrefHT) # create dictionary from Components - ABUNDANCES = { } - NATURAL_ABUNDANCES = { } + ABUNDANCES = {} + NATURAL_ABUNDANCES = {} for Component in Components: M = Component[0] I = Component[1] @@ -10668,7 +9268,7 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti # setup the default empty environment dependence function if not EnvDependences: - EnvDependences = lambda ENV, LINE: { } + EnvDependences = lambda ENV, LINE: {} Env = Environment.copy() Env['Tref'] = Tref Env['pref'] = pref @@ -10677,9 +9277,9 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti GammaL = GammaL.lower() if not Diluent: if GammaL == 'gamma_air': - Diluent = { 'air': 1. } + Diluent = {'air': 1.} elif GammaL == 'gamma_self': - Diluent = { 'self': 1. } + Diluent = {'self': 1.} else: raise Exception('Unknown GammaL value: %s' % GammaL) if VARIABLES['DEBUG']: @@ -10704,7 +9304,7 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti for RowID in range(nline): # Get the custom environment dependences - Line = { } + Line = {} for parname in parnames: Line[parname] = LOCAL_TABLE_CACHE[TableName]['data'][parname][RowID] CustomEnvDependences = EnvDependences(Env, Line) @@ -10731,8 +9331,8 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti LineIntensity = CustomEnvDependences['sw'] else: LineIntensity = EnvironmentDependency_Intensity(LineIntensityDB, T, Tref, SigmaT, - SigmaTref, - LowerStateEnergyDB, LineCenterDB) + SigmaTref, LowerStateEnergyDB, + LineCenterDB) # FILTER by LineIntensity: compare it with IntencityThreshold if LineIntensity < IntensityThreshold: @@ -10764,7 +9364,7 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti raise KeyError if VARIABLES['DEBUG']: print('absorptionCoefficient_HT: Gamma0DB=%f (found as %s)' % ( - Gamma0DB, 'gamma_HT_0_%s_%d' % (species_lower, TrefHT))) + Gamma0DB, 'gamma_HT_0_%s_%d' % (species_lower, TrefHT))) except KeyError: try: # search for Voigt-style name @@ -10772,48 +9372,51 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti RowID] if VARIABLES['DEBUG']: print('absorptionCoefficient_HT: Gamma0DB=%f (found as %s)' % ( - Gamma0DB, 'gamma_%s' % species_lower)) + Gamma0DB, 'gamma_%s' % species_lower)) except KeyError: Gamma0DB = 0.0 if VARIABLES['DEBUG']: print( - 'absorptionCoefficient_HT: Gamma0DB=%f (not found in database)' % Gamma0DB) + 'absorptionCoefficient_HT: Gamma0DB=%f (not found in database)' % + Gamma0DB) # Search for temperature exponent for broadening HWHM. try: # search for HT-style name - TempRatioPowerDB = \ - LOCAL_TABLE_CACHE[TableName]['data']['n_HT_%s_%d' % (species_lower, TrefHT)][ - RowID] + TempRatioPowerDB = LOCAL_TABLE_CACHE[TableName]['data'][ + 'n_HT_%s_%d' % (species_lower, TrefHT)][RowID] if TempRatioPowerDB == 0.: raise KeyError Tref = TrefHT if VARIABLES['DEBUG']: print('absorptionCoefficient_HT: TempRatioPowerDB=%f (found as %s)' % ( - TempRatioPowerDB, 'n_HT_%s_%d' % (species_lower, TrefHT))) + TempRatioPowerDB, 'n_HT_%s_%d' % (species_lower, TrefHT))) except KeyError: Tref = 296. try: # search for Voigt-style name TempRatioPowerDB = \ - LOCAL_TABLE_CACHE[TableName]['data']['n_%s' % species_lower][RowID] + LOCAL_TABLE_CACHE[TableName]['data']['n_%s' % species_lower][RowID] if VARIABLES['DEBUG']: print( - 'absorptionCoefficient_HT: TempRatioPowerDB=%f (found as %s). Tref is set to 296K.' % ( - TempRatioPowerDB, 'n_%s' % species_lower)) + 'absorptionCoefficient_HT: TempRatioPowerDB=%f (found as %s). ' + 'Tref is set to 296K.' % ( + TempRatioPowerDB, 'n_%s' % species_lower)) if species_lower == 'self' and TempRatioPowerDB == 0.: TempRatioPowerDB = LOCAL_TABLE_CACHE[TableName]['data']['n_air'][ RowID] # same for self as for air if VARIABLES['DEBUG']: print( - 'absorptionCoefficient_HT: using n_air for self species because n_self=0.0') + 'absorptionCoefficient_HT: using n_air for self species ' + 'because n_self=0.0') except KeyError: # print('TempRatioPowerDB is set to zero') # TempRatioPowerDB = 0 TempRatioPowerDB = LOCAL_TABLE_CACHE[TableName]['data']['n_air'][RowID] if VARIABLES['DEBUG']: print( - 'absorptionCoefficient_HT: TempRatioPowerDB=%f (found as n_air). Tref is set to 296K.' % TempRatioPowerDB) + 'absorptionCoefficient_HT: TempRatioPowerDB=%f (found as n_air). ' + 'Tref is set to 296K.' % TempRatioPowerDB) # Add to the final Gamma0 Gamma0T = CustomEnvDependences.get('gamma_HT_0_%s_%d' % (species_lower, TrefHT), @@ -10833,7 +9436,7 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti raise KeyError if VARIABLES['DEBUG']: print('absorptionCoefficient_HT: Shift0DB=%f (found as %s)' % ( - Shift0DB, 'delta_HT_0_%s_%d' % (species_lower, TrefHT))) + Shift0DB, 'delta_HT_0_%s_%d' % (species_lower, TrefHT))) except KeyError: try: # search for Voigt-style name @@ -10841,12 +9444,13 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti RowID] if VARIABLES['DEBUG']: print('absorptionCoefficient_HT: Shift0DB=%f (found as %s)' % ( - Shift0DB, 'delta_%s' % species_lower)) + Shift0DB, 'delta_%s' % species_lower)) except KeyError: Shift0DB = 0.0 if VARIABLES['DEBUG']: print( - 'absorptionCoefficient_HT: Shift0DB=%f (not found in database)' % Shift0DB) + 'absorptionCoefficient_HT: Shift0DB=%f (not found in database)' % + Shift0DB) # Search for temperature dependence for shift. try: @@ -10858,7 +9462,7 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti Tref = TrefHT if VARIABLES['DEBUG']: print('absorptionCoefficient_HT: deltap=%f (found as %s)' % ( - deltap, 'deltap_HT_%s_%d' % (species_lower, TrefHT))) + deltap, 'deltap_HT_%s_%d' % (species_lower, TrefHT))) except KeyError: Tref = 296. try: @@ -10867,19 +9471,21 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti RowID] if VARIABLES['DEBUG']: print( - 'absorptionCoefficient_HT: deltap=%f (found as %s). Tref is set to 296K.' % ( - deltap, 'deltap_%s' % species_lower)) + 'absorptionCoefficient_HT: deltap=%f (found as %s). Tref is set ' + 'to 296K.' % ( + deltap, 'deltap_%s' % species_lower)) except KeyError: deltap = 0.0 if VARIABLES['DEBUG']: print( - 'absorptionCoefficient_HT: deltap=%f (not found in database)' % deltap) + 'absorptionCoefficient_HT: deltap=%f (not found in database)' % + deltap) Shift0T = CustomEnvDependences.get('deltap_HT_%s_%d' % (species_lower, TrefHT), CustomEnvDependences.get( - 'deltap_%s' % species_lower, - ((Shift0DB + deltap * ( - T - Tref)) * p / pref))) + 'deltap_%s' % species_lower, (( + Shift0DB + deltap * ( + T - Tref)) * p / pref))) Shift0 += abun * Shift0T # Search for speed dependence for HWHM. @@ -10890,21 +9496,22 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti raise KeyError if VARIABLES['DEBUG']: print('absorptionCoefficient_HT: Gamma2DB=%f (found as %s)' % ( - Gamma2DB, 'gamma_HT_2_%s_%d' % (species_lower, TrefHT))) + Gamma2DB, 'gamma_HT_2_%s_%d' % (species_lower, TrefHT))) except KeyError: try: SDDB = LOCAL_TABLE_CACHE[TableName]['data']['SD_%s' % species_lower][RowID] Gamma2DB = SDDB * Gamma0DB if VARIABLES['DEBUG']: print('absorptionCoefficient_HT: SDDB=%f (found as %s)' % ( - SDDB, 'SD_%s' % species_lower)) + SDDB, 'SD_%s' % species_lower)) if VARIABLES['DEBUG']: print('absorptionCoefficient_HT: Gamma2DB = SDDB*Gamma0DB') except KeyError: Gamma2DB = 0.0 if VARIABLES['DEBUG']: print( - 'absorptionCoefficient_HT: Gamma2DB=%f (not found in database)' % Gamma2DB) + 'absorptionCoefficient_HT: Gamma2DB=%f (not found in database)' % + Gamma2DB) Gamma2 += abun * CustomEnvDependences.get( 'gamma_HT_2_%s_%d' % (species_lower, TrefHT), Gamma2DB * (p / pref)) @@ -10915,23 +9522,23 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti 'delta_HT_2_%s_%d' % (species_lower, TrefHT)][RowID] if VARIABLES['DEBUG']: print('absorptionCoefficient_HT: Shift2DB=%f (found as %s)' % ( - Shift2DB, 'delta_HT_2_%s_%d' % (species_lower, TrefHT))) + Shift2DB, 'delta_HT_2_%s_%d' % (species_lower, TrefHT))) except KeyError: Shift2DB = 0. if VARIABLES['DEBUG']: print( - 'absorptionCoefficient_HT: Shift2DB=%f (not found in database)' % Shift2DB) + 'absorptionCoefficient_HT: Shift2DB=%f (not found in database)' % + Shift2DB) Shift2 += abun * CustomEnvDependences.get( - 'delta_HT_2_%s_%d' % (species_lower, TrefHT), - Shift2DB * p / pref) + 'delta_HT_2_%s_%d' % (species_lower, TrefHT), Shift2DB * p / pref) # Search for frequency of VC try: NuVCDB = LOCAL_TABLE_CACHE[TableName]['data']['nu_HT_%s' % species_lower][RowID] if VARIABLES['DEBUG']: print('absorptionCoefficient_HT: NuVCDB=%f (found as %s)' % ( - NuVCDB, 'nu_HT_%s' % species_lower)) + NuVCDB, 'nu_HT_%s' % species_lower)) except KeyError: NuVCDB = 0. if VARIABLES['DEBUG']: @@ -10944,12 +9551,13 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti RowID] if VARIABLES['DEBUG']: print('absorptionCoefficient_HT: KappaDB=%f (found as %s)' % ( - KappaDB, 'kappa_HT_%s' % species_lower)) + KappaDB, 'kappa_HT_%s' % species_lower)) except KeyError: KappaDB = 0. if VARIABLES['DEBUG']: print( - 'absorptionCoefficient_HT: KappaDB=%f (not found in database)' % KappaDB) + 'absorptionCoefficient_HT: KappaDB=%f (not found in database)' % + KappaDB) NuVC += abun * CustomEnvDependences.get('nu_HT_%s' % species_lower, NuVCDB * (Tref / T) ** KappaDB * p) @@ -10959,7 +9567,7 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti EtaDB = LOCAL_TABLE_CACHE[TableName]['data']['eta_HT_%s' % species_lower][RowID] if VARIABLES['DEBUG']: print('absorptionCoefficient_HT: EtaDB=%f (found as %s)' % ( - EtaDB, 'eta_HT_%s' % species_lower)) + EtaDB, 'eta_HT_%s' % species_lower)) except KeyError: EtaDB = 0. if VARIABLES['DEBUG']: @@ -10975,12 +9583,11 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti BoundIndexLower = bisect(Omegas, LineCenterDB - OmegaWingF) BoundIndexUpper = bisect(Omegas, LineCenterDB + OmegaWingF) lineshape_vals = \ - PROFILE_HT(LineCenterDB, GammaD, Gamma0, Gamma2, Shift0, Shift2, NuVC, Eta, - Omegas[BoundIndexLower:BoundIndexUpper])[0] + PROFILE_HT(LineCenterDB, GammaD, Gamma0, Gamma2, Shift0, Shift2, NuVC, Eta, + Omegas[BoundIndexLower:BoundIndexUpper])[0] Xsect[BoundIndexLower:BoundIndexUpper] += factor / NATURAL_ABUNDANCES[ - (MoleculeNumberDB, IsoNumberDB)] * \ - ABUNDANCES[(MoleculeNumberDB, IsoNumberDB)] * \ - LineIntensity * lineshape_vals + (MoleculeNumberDB, IsoNumberDB)] * ABUNDANCES[( + MoleculeNumberDB, IsoNumberDB)] * LineIntensity * lineshape_vals if File: save_to_file(File, Format, Omegas, Xsect) @@ -10990,12 +9597,11 @@ def absorptionCoefficient_HT(Components=None, SourceTables=None, partitionFuncti def absorptionCoefficient_SDVoigt(Components=None, SourceTables=None, partitionFunction=PYTIPS, Environment=None, OmegaRange=None, OmegaStep=None, OmegaWing=None, IntensityThreshold=DefaultIntensityThreshold, - OmegaWingHW=DefaultOmegaWingHW, - GammaL='gamma_air', HITRAN_units=True, LineShift=True, - File=None, Format=None, OmegaGrid=None, - WavenumberRange=None, WavenumberStep=None, WavenumberWing=None, - WavenumberWingHW=None, WavenumberGrid=None, - Diluent={ }, EnvDependences=None): + OmegaWingHW=DefaultOmegaWingHW, GammaL='gamma_air', + HITRAN_units=True, LineShift=True, File=None, Format=None, + OmegaGrid=None, WavenumberRange=None, WavenumberStep=None, + WavenumberWing=None, WavenumberWingHW=None, WavenumberGrid=None, + Diluent={}, EnvDependences=None): """ INPUT PARAMETERS: Components: list of tuples [(M,I,D)], where @@ -11056,10 +9662,10 @@ def absorptionCoefficient_SDVoigt(Components=None, SourceTables=None, partitionF SourceTables = listOfTuples(SourceTables) # determine final input values - Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, \ - IntensityThreshold, Format = \ - getDefaultValuesForXsect(Components, SourceTables, Environment, OmegaRange, - OmegaStep, OmegaWing, IntensityThreshold, Format) + Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, IntensityThreshold, \ + Format = getDefaultValuesForXsect( + Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, IntensityThreshold, + Format) # warn user about too large omega step if OmegaStep > 0.1: @@ -11085,8 +9691,8 @@ def absorptionCoefficient_SDVoigt(Components=None, SourceTables=None, partitionF p = Environment['p'] # atm # create dictionary from Components - ABUNDANCES = { } - NATURAL_ABUNDANCES = { } + ABUNDANCES = {} + NATURAL_ABUNDANCES = {} for Component in Components: M = Component[0] I = Component[1] @@ -11108,7 +9714,7 @@ def absorptionCoefficient_SDVoigt(Components=None, SourceTables=None, partitionF # setup the default empty environment dependence function if not EnvDependences: - EnvDependences = lambda ENV, LINE: { } + EnvDependences = lambda ENV, LINE: {} Env = Environment.copy() Env['Tref'] = Tref Env['pref'] = pref @@ -11117,9 +9723,9 @@ def absorptionCoefficient_SDVoigt(Components=None, SourceTables=None, partitionF GammaL = GammaL.lower() if not Diluent: if GammaL == 'gamma_air': - Diluent = { 'air': 1. } + Diluent = {'air': 1.} elif GammaL == 'gamma_self': - Diluent = { 'self': 1. } + Diluent = {'self': 1.} else: raise Exception('Unknown GammaL value: %s' % GammaL) @@ -11142,7 +9748,7 @@ def absorptionCoefficient_SDVoigt(Components=None, SourceTables=None, partitionF for RowID in range(nline): # Get the custom environment dependences - Line = { } + Line = {} for parname in parnames: Line[parname] = LOCAL_TABLE_CACHE[TableName]['data'][parname][RowID] CustomEnvDependences = EnvDependences(Env, Line) @@ -11169,8 +9775,8 @@ def absorptionCoefficient_SDVoigt(Components=None, SourceTables=None, partitionF LineIntensity = CustomEnvDependences['sw'] else: LineIntensity = EnvironmentDependency_Intensity(LineIntensityDB, T, Tref, SigmaT, - SigmaTref, - LowerStateEnergyDB, LineCenterDB) + SigmaTref, LowerStateEnergyDB, + LineCenterDB) # FILTER by LineIntensity: compare it with IntencityThreshold if LineIntensity < IntensityThreshold: @@ -11228,7 +9834,7 @@ def absorptionCoefficient_SDVoigt(Components=None, SourceTables=None, partitionF Shift0 += abun * CustomEnvDependences.get(delta_name, # default -> ((Shift0DB + deltap * ( - T - Tref)) * p / pref)) + T - Tref)) * p / pref)) SD_name = 'SD_' + species_lower try: @@ -11247,9 +9853,8 @@ def absorptionCoefficient_SDVoigt(Components=None, SourceTables=None, partitionF lineshape_vals = PROFILE_SDVOIGT(LineCenterDB, GammaD, Gamma0, Gamma2, Shift0, Shift2, Omegas[BoundIndexLower:BoundIndexUpper])[0] Xsect[BoundIndexLower:BoundIndexUpper] += factor / NATURAL_ABUNDANCES[ - (MoleculeNumberDB, IsoNumberDB)] * \ - ABUNDANCES[(MoleculeNumberDB, IsoNumberDB)] * \ - LineIntensity * lineshape_vals + (MoleculeNumberDB, IsoNumberDB)] * ABUNDANCES[( + MoleculeNumberDB, IsoNumberDB)] * LineIntensity * lineshape_vals if File: save_to_file(File, Format, Omegas, Xsect) @@ -11259,12 +9864,11 @@ def absorptionCoefficient_SDVoigt(Components=None, SourceTables=None, partitionF def absorptionCoefficient_Voigt(Components=None, SourceTables=None, partitionFunction=PYTIPS, Environment=None, OmegaRange=None, OmegaStep=None, OmegaWing=None, IntensityThreshold=DefaultIntensityThreshold, - OmegaWingHW=DefaultOmegaWingHW, - GammaL='gamma_air', HITRAN_units=True, LineShift=True, - File=None, Format=None, OmegaGrid=None, - WavenumberRange=None, WavenumberStep=None, WavenumberWing=None, - WavenumberWingHW=None, WavenumberGrid=None, - Diluent={ }, EnvDependences=None): + OmegaWingHW=DefaultOmegaWingHW, GammaL='gamma_air', + HITRAN_units=True, LineShift=True, File=None, Format=None, + OmegaGrid=None, WavenumberRange=None, WavenumberStep=None, + WavenumberWing=None, WavenumberWingHW=None, WavenumberGrid=None, + Diluent={}, EnvDependences=None): """ INPUT PARAMETERS: Components: list of tuples [(M,I,D)], where @@ -11323,10 +9927,10 @@ def absorptionCoefficient_Voigt(Components=None, SourceTables=None, partitionFun SourceTables = listOfTuples(SourceTables) # determine final input values - Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, \ - IntensityThreshold, Format = \ - getDefaultValuesForXsect(Components, SourceTables, Environment, OmegaRange, - OmegaStep, OmegaWing, IntensityThreshold, Format) + Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, IntensityThreshold, \ + Format = getDefaultValuesForXsect( + Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, IntensityThreshold, + Format) # warn user about too large omega step if OmegaStep > 0.1: @@ -11352,8 +9956,8 @@ def absorptionCoefficient_Voigt(Components=None, SourceTables=None, partitionFun p = Environment['p'] # atm # create dictionary from Components - ABUNDANCES = { } - NATURAL_ABUNDANCES = { } + ABUNDANCES = {} + NATURAL_ABUNDANCES = {} for Component in Components: M = Component[0] I = Component[1] @@ -11375,7 +9979,7 @@ def absorptionCoefficient_Voigt(Components=None, SourceTables=None, partitionFun # setup the default empty environment dependence function if not EnvDependences: - EnvDependences = lambda ENV, LINE: { } + EnvDependences = lambda ENV, LINE: {} Env = Environment.copy() Env['Tref'] = Tref Env['pref'] = pref @@ -11384,9 +9988,9 @@ def absorptionCoefficient_Voigt(Components=None, SourceTables=None, partitionFun GammaL = GammaL.lower() if not Diluent: if GammaL == 'gamma_air': - Diluent = { 'air': 1. } + Diluent = {'air': 1.} elif GammaL == 'gamma_self': - Diluent = { 'self': 1. } + Diluent = {'self': 1.} else: raise Exception('Unknown GammaL value: %s' % GammaL) @@ -11409,7 +10013,7 @@ def absorptionCoefficient_Voigt(Components=None, SourceTables=None, partitionFun for RowID in range(nline): # Get the custom environment dependences - Line = { } + Line = {} for parname in parnames: Line[parname] = LOCAL_TABLE_CACHE[TableName]['data'][parname][RowID] CustomEnvDependences = EnvDependences(Env, Line) @@ -11436,8 +10040,8 @@ def absorptionCoefficient_Voigt(Components=None, SourceTables=None, partitionFun LineIntensity = CustomEnvDependences['sw'] else: LineIntensity = EnvironmentDependency_Intensity(LineIntensityDB, T, Tref, SigmaT, - SigmaTref, - LowerStateEnergyDB, LineCenterDB) + SigmaTref, LowerStateEnergyDB, + LineCenterDB) # FILTER by LineIntensity: compare it with IntencityThreshold if LineIntensity < IntensityThreshold: @@ -11493,7 +10097,7 @@ def absorptionCoefficient_Voigt(Components=None, SourceTables=None, partitionFun Shift0 += abun * CustomEnvDependences.get(delta_name, # default -> ((Shift0DB + deltap * ( - T - Tref)) * p / pref)) + T - Tref)) * p / pref)) # get final wing of the line according to Gamma0, OmegaWingHW and OmegaWing OmegaWingF = max(OmegaWing, OmegaWingHW * Gamma0, OmegaWingHW * GammaD) @@ -11503,9 +10107,8 @@ def absorptionCoefficient_Voigt(Components=None, SourceTables=None, partitionFun lineshape_vals = PROFILE_VOIGT(LineCenterDB + Shift0, GammaD, Gamma0, Omegas[BoundIndexLower:BoundIndexUpper])[0] Xsect[BoundIndexLower:BoundIndexUpper] += factor / NATURAL_ABUNDANCES[ - (MoleculeNumberDB, IsoNumberDB)] * \ - ABUNDANCES[(MoleculeNumberDB, IsoNumberDB)] * \ - LineIntensity * lineshape_vals + (MoleculeNumberDB, IsoNumberDB)] * ABUNDANCES[( + MoleculeNumberDB, IsoNumberDB)] * LineIntensity * lineshape_vals if File: save_to_file(File, Format, Omegas, Xsect) @@ -11515,12 +10118,11 @@ def absorptionCoefficient_Voigt(Components=None, SourceTables=None, partitionFun def absorptionCoefficient_Lorentz(Components=None, SourceTables=None, partitionFunction=PYTIPS, Environment=None, OmegaRange=None, OmegaStep=None, OmegaWing=None, IntensityThreshold=DefaultIntensityThreshold, - OmegaWingHW=DefaultOmegaWingHW, - GammaL='gamma_air', HITRAN_units=True, LineShift=True, - File=None, Format=None, OmegaGrid=None, - WavenumberRange=None, WavenumberStep=None, WavenumberWing=None, - WavenumberWingHW=None, WavenumberGrid=None, - Diluent={ }, EnvDependences=None): + OmegaWingHW=DefaultOmegaWingHW, GammaL='gamma_air', + HITRAN_units=True, LineShift=True, File=None, Format=None, + OmegaGrid=None, WavenumberRange=None, WavenumberStep=None, + WavenumberWing=None, WavenumberWingHW=None, WavenumberGrid=None, + Diluent={}, EnvDependences=None): """ INPUT PARAMETERS: Components: list of tuples [(M,I,D)], where @@ -11579,10 +10181,10 @@ def absorptionCoefficient_Lorentz(Components=None, SourceTables=None, partitionF SourceTables = listOfTuples(SourceTables) # determine final input values - Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, \ - IntensityThreshold, Format = \ - getDefaultValuesForXsect(Components, SourceTables, Environment, OmegaRange, - OmegaStep, OmegaWing, IntensityThreshold, Format) + Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, IntensityThreshold, \ + Format = getDefaultValuesForXsect( + Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, IntensityThreshold, + Format) # warn user about too large omega step if OmegaStep > 0.1: @@ -11608,8 +10210,8 @@ def absorptionCoefficient_Lorentz(Components=None, SourceTables=None, partitionF p = Environment['p'] # atm # create dictionary from Components - ABUNDANCES = { } - NATURAL_ABUNDANCES = { } + ABUNDANCES = {} + NATURAL_ABUNDANCES = {} for Component in Components: M = Component[0] I = Component[1] @@ -11631,7 +10233,7 @@ def absorptionCoefficient_Lorentz(Components=None, SourceTables=None, partitionF # setup the default empty environment dependence function if not EnvDependences: - EnvDependences = lambda ENV, LINE: { } + EnvDependences = lambda ENV, LINE: {} Env = Environment.copy() Env['Tref'] = Tref Env['pref'] = pref @@ -11640,9 +10242,9 @@ def absorptionCoefficient_Lorentz(Components=None, SourceTables=None, partitionF GammaL = GammaL.lower() if not Diluent: if GammaL == 'gamma_air': - Diluent = { 'air': 1. } + Diluent = {'air': 1.} elif GammaL == 'gamma_self': - Diluent = { 'self': 1. } + Diluent = {'self': 1.} else: raise Exception('Unknown GammaL value: %s' % GammaL) @@ -11665,7 +10267,7 @@ def absorptionCoefficient_Lorentz(Components=None, SourceTables=None, partitionF for RowID in range(nline): # Get the custom environment dependences - Line = { } + Line = {} for parname in parnames: Line[parname] = LOCAL_TABLE_CACHE[TableName]['data'][parname][RowID] CustomEnvDependences = EnvDependences(Env, Line) @@ -11692,8 +10294,8 @@ def absorptionCoefficient_Lorentz(Components=None, SourceTables=None, partitionF LineIntensity = CustomEnvDependences['sw'] else: LineIntensity = EnvironmentDependency_Intensity(LineIntensityDB, T, Tref, SigmaT, - SigmaTref, - LowerStateEnergyDB, LineCenterDB) + SigmaTref, LowerStateEnergyDB, + LineCenterDB) # FILTER by LineIntensity: compare it with IntencityThreshold if LineIntensity < IntensityThreshold: @@ -11744,7 +10346,7 @@ def absorptionCoefficient_Lorentz(Components=None, SourceTables=None, partitionF Shift0 += abun * CustomEnvDependences.get(delta_name, # default -> ((Shift0DB + deltap * ( - T - Tref)) * p / pref)) + T - Tref)) * p / pref)) # get final wing of the line according to Gamma0, OmegaWingHW and OmegaWing OmegaWingF = max(OmegaWing, OmegaWingHW * Gamma0) @@ -11754,9 +10356,8 @@ def absorptionCoefficient_Lorentz(Components=None, SourceTables=None, partitionF lineshape_vals = PROFILE_LORENTZ(LineCenterDB + Shift0, Gamma0, Omegas[BoundIndexLower:BoundIndexUpper]) Xsect[BoundIndexLower:BoundIndexUpper] += factor / NATURAL_ABUNDANCES[ - (MoleculeNumberDB, IsoNumberDB)] * \ - ABUNDANCES[(MoleculeNumberDB, IsoNumberDB)] * \ - LineIntensity * lineshape_vals + (MoleculeNumberDB, IsoNumberDB)] * ABUNDANCES[( + MoleculeNumberDB, IsoNumberDB)] * LineIntensity * lineshape_vals if File: save_to_file(File, Format, Omegas, Xsect) @@ -11778,10 +10379,10 @@ def absorptionCoefficient_Doppler(Components=None, SourceTables=None, partitionF OmegaWingHW=DefaultOmegaWingHW, ParameterBindings=DefaultParameterBindings, EnvironmentDependencyBindings=DefaultEnvironmentDependencyBindings, - GammaL='dummy', HITRAN_units=True, LineShift=True, - File=None, Format=None, OmegaGrid=None, - WavenumberRange=None, WavenumberStep=None, WavenumberWing=None, - WavenumberWingHW=None, WavenumberGrid=None): + GammaL='dummy', HITRAN_units=True, LineShift=True, File=None, + Format=None, OmegaGrid=None, WavenumberRange=None, + WavenumberStep=None, WavenumberWing=None, WavenumberWingHW=None, + WavenumberGrid=None): """ INPUT PARAMETERS: Components: list of tuples [(M,I,D)], where @@ -11838,10 +10439,10 @@ def absorptionCoefficient_Doppler(Components=None, SourceTables=None, partitionF SourceTables = listOfTuples(SourceTables) # determine final input values - Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, \ - IntensityThreshold, Format = \ - getDefaultValuesForXsect(Components, SourceTables, Environment, OmegaRange, - OmegaStep, OmegaWing, IntensityThreshold, Format) + Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, IntensityThreshold, \ + Format = getDefaultValuesForXsect( + Components, SourceTables, Environment, OmegaRange, OmegaStep, OmegaWing, IntensityThreshold, + Format) # special for Doppler case: set OmegaStep to a smaller value if not OmegaStep: OmegaStep = 0.001 @@ -11870,8 +10471,8 @@ def absorptionCoefficient_Doppler(Components=None, SourceTables=None, partitionF p = Environment['p'] # atm # create dictionary from Components - ABUNDANCES = { } - NATURAL_ABUNDANCES = { } + ABUNDANCES = {} + NATURAL_ABUNDANCES = {} for Component in Components: M = Component[0] I = Component[1] @@ -11924,8 +10525,8 @@ def absorptionCoefficient_Doppler(Components=None, SourceTables=None, partitionF # intensity LineIntensity = EnvironmentDependency_Intensity(LineIntensityDB, T, Tref, SigmaT, - SigmaTref, - LowerStateEnergyDB, LineCenterDB) + SigmaTref, LowerStateEnergyDB, + LineCenterDB) # FILTER by LineIntensity: compare it with IntencityThreshold # TODO: apply wing narrowing instead of filtering, this would be more appropriate @@ -11950,9 +10551,8 @@ def absorptionCoefficient_Doppler(Components=None, SourceTables=None, partitionF lineshape_vals = PROFILE_DOPPLER(LineCenterDB + Shift0, GammaD, Omegas[BoundIndexLower:BoundIndexUpper]) Xsect[BoundIndexLower:BoundIndexUpper] += factor / NATURAL_ABUNDANCES[ - (MoleculeNumberDB, IsoNumberDB)] * \ - ABUNDANCES[(MoleculeNumberDB, IsoNumberDB)] * \ - LineIntensity * lineshape_vals + (MoleculeNumberDB, IsoNumberDB)] * ABUNDANCES[( + MoleculeNumberDB, IsoNumberDB)] * LineIntensity * lineshape_vals if File: save_to_file(File, Format, Omegas, Xsect) @@ -11966,38 +10566,38 @@ def absorptionCoefficient_Doppler(Components=None, SourceTables=None, partitionF absorptionCoefficient_Gauss = absorptionCoefficient_Doppler -def abscoef_HT(table=None, step=None, grid=None, env={ 'T': 296., 'p': 1. }, file=None): - return absorptionCoefficient_HT(SourceTables = table, OmegaStep = step, OmegaGrid = grid, - Environment = env, File = file) +def abscoef_HT(table=None, step=None, grid=None, env={'T': 296., 'p': 1.}, file=None): + return absorptionCoefficient_HT(SourceTables=table, OmegaStep=step, OmegaGrid=grid, + Environment=env, File=file) -def abscoef_Voigt(table=None, step=None, grid=None, env={ 'T': 296., 'p': 1. }, file=None): - return absorptionCoefficient_Voigt(SourceTables = table, OmegaStep = step, OmegaGrid = grid, - Environment = env, File = file) +def abscoef_Voigt(table=None, step=None, grid=None, env={'T': 296., 'p': 1.}, file=None): + return absorptionCoefficient_Voigt(SourceTables=table, OmegaStep=step, OmegaGrid=grid, + Environment=env, File=file) -def abscoef_Lorentz(table=None, step=None, grid=None, env={ 'T': 296., 'p': 1. }, file=None): - return absorptionCoefficient_Lorentz(SourceTables = table, OmegaStep = step, OmegaGrid = grid, - Environment = env, File = file) +def abscoef_Lorentz(table=None, step=None, grid=None, env={'T': 296., 'p': 1.}, file=None): + return absorptionCoefficient_Lorentz(SourceTables=table, OmegaStep=step, OmegaGrid=grid, + Environment=env, File=file) -def abscoef_Doppler(table=None, step=None, grid=None, env={ 'T': 296., 'p': 1. }, file=None): - return absorptionCoefficient_Doppler(SourceTables = table, OmegaStep = step, OmegaGrid = grid, - Environment = env, File = file) +def abscoef_Doppler(table=None, step=None, grid=None, env={'T': 296., 'p': 1.}, file=None): + return absorptionCoefficient_Doppler(SourceTables=table, OmegaStep=step, OmegaGrid=grid, + Environment=env, File=file) abscoef_Gauss = abscoef_Doppler -def abscoef(table=None, step=None, grid=None, env={ 'T': 296., 'p': 1. }, file=None): # default - return absorptionCoefficient_Lorentz(SourceTables = table, OmegaStep = step, OmegaGrid = grid, - Environment = env, File = file) +def abscoef(table=None, step=None, grid=None, env={'T': 296., 'p': 1.}, file=None): # default + return absorptionCoefficient_Lorentz(SourceTables=table, OmegaStep=step, OmegaGrid=grid, + Environment=env, File=file) # --------------------------------------------------------------------------- -def transmittanceSpectrum(Omegas, AbsorptionCoefficient, Environment={ 'l': 100. }, - File=None, Format='%e %e', Wavenumber=None): +def transmittanceSpectrum(Omegas, AbsorptionCoefficient, Environment={'l': 100.}, File=None, + Format='%e %e', Wavenumber=None): """ INPUT PARAMETERS: Wavenumber/Omegas: wavenumber grid (required) @@ -12030,8 +10630,8 @@ def transmittanceSpectrum(Omegas, AbsorptionCoefficient, Environment={ 'l': 100. return Omegas, Xsect -def absorptionSpectrum(Omegas, AbsorptionCoefficient, Environment={ 'l': 100. }, - File=None, Format='%e %e', Wavenumber=None): +def absorptionSpectrum(Omegas, AbsorptionCoefficient, Environment={'l': 100.}, File=None, + Format='%e %e', Wavenumber=None): """ INPUT PARAMETERS: Wavenumber/Omegas: wavenumber grid (required) @@ -12064,8 +10664,8 @@ def absorptionSpectrum(Omegas, AbsorptionCoefficient, Environment={ 'l': 100. }, return Omegas, Xsect -def radianceSpectrum(Omegas, AbsorptionCoefficient, Environment={ 'l': 100., 'T': 296. }, - File=None, Format='%e %e', Wavenumber=None): +def radianceSpectrum(Omegas, AbsorptionCoefficient, Environment={'l': 100., 'T': 296.}, File=None, + Format='%e %e', Wavenumber=None): """ INPUT PARAMETERS: Wavenumber/Omegas: wavenumber grid (required) @@ -12298,7 +10898,7 @@ def convolveSpectrum(Omega, CrossSection, Resolution=0.1, AF_wing=10., slit /= sum(slit) * step # simple normalization left_bnd = len(slit) / 2 right_bnd = len(Omega) - len(slit) / 2 - CrossSectionLowRes = convolve(CrossSection, slit, mode = 'same') * step + CrossSectionLowRes = convolve(CrossSection, slit, mode='same') * step return Omega[left_bnd:right_bnd], CrossSectionLowRes[ left_bnd:right_bnd], left_bnd, right_bnd, slit @@ -12321,7 +10921,7 @@ def convolveSpectrumSame(Omega, CrossSection, Resolution=0.1, AF_wing=10., slit /= sum(slit) * step # simple normalization left_bnd = 0 right_bnd = len(Omega) - CrossSectionLowRes = convolve(CrossSection, slit, mode = 'same') * step + CrossSectionLowRes = convolve(CrossSection, slit, mode='same') * step return Omega[left_bnd:right_bnd], CrossSectionLowRes[ left_bnd:right_bnd], left_bnd, right_bnd, slit @@ -12340,7 +10940,7 @@ def convolveSpectrumFull(Omega, CrossSection, Resolution=0.1, AF_wing=10., print(x) print('slitfunc=') print(SlitFunction) - CrossSectionLowRes = convolve(CrossSection, slit, mode = 'full') * step + CrossSectionLowRes = convolve(CrossSection, slit, mode='full') * step return Omega, CrossSectionLowRes, None, None # ------------------------------------------------------------------ diff --git a/src/metadata/config.py b/src/metadata/config.py index 724adf5..df3fbff 100644 --- a/src/metadata/config.py +++ b/src/metadata/config.py @@ -10,88 +10,76 @@ class Config(): configurable settings. """ - config_options = { - ## The number of values to display along the x axis in graphs - 'axisx_ticks': { - 'default_value': 5, - 'display_name': 'X-Axis Ticks', - 'tool_tip': 'The number of ticks that will be displayed along the x axis.', - 'type': int - }, - - ## The number of values to display along the y axis in graphs - 'axisy_ticks': { - 'default_value': 5, - 'display_name': 'Y-Axis Ticks', - 'tool_tip': 'The number of ticks that will be displayed along the y axis.', - 'type': int - }, - - ## The folder where data is stored - 'data_folder': { - 'default_value': 'data', - 'display_name': 'Data Folder', - 'tool_tip': 'The path to the folder where data downloaded from HITRAN will be ' - 'stored.', - 'type': str - }, - - ## Whether the program should be ran with high-dpi scaling enabled. - 'high_dpi': { - 'default_value': False, - 'display_name': 'High DPI Mode', - 'tool_tip': 'Whether to use high DPI mode or not. If the program looks strange ' - 'on your screen you may want ' - 'to enable this.', - 'type': bool - }, - - ## The number of rows that tables should be paginated with. - 'select_page_length': { - 'default_value': 100, - 'display_name': 'View Page Length', - 'tool_tip': 'The number of rows to show per page in the view table.', - 'type': int - }, - - 'hapi_api_key': { - 'default_value': '0000', - 'display_name': 'HAPI API Key', + config_options = {# The number of values to display along the x axis in graphs + 'axisx_ticks': {'default_value': 5, + 'display_name': + 'X-Axis Ticks', + 'tool_tip': + 'The number of ' + 'ticks that will ' + 'be displayed ' + 'along the x ' + 'axis.', + 'type': int}, + + # The number of values to display along the y axis in graphs + 'axisy_ticks': {'default_value': 5, + 'display_name': + 'Y-Axis Ticks', + 'tool_tip': + 'The number of ' + 'ticks that will ' + 'be displayed ' + 'along the y ' + 'axis.', + 'type': int}, + + # The folder where data is stored + 'data_folder': { + 'default_value': 'data', 'display_name': 'Data Folder', + 'tool_tip': 'The path to the folder where data downloaded from HITRAN will be ' + 'stored.', 'type': str}, + + # Whether the program should be ran with high-dpi scaling enabled. + 'high_dpi': {'default_value': False, + 'display_name': 'High DPI Mode', + 'tool_tip': 'Whether to use high DPI mode or not. If the program looks strange ' + 'on your screen you may want ' + 'to enable this.', 'type': bool}, + + # The number of rows that tables should be paginated with. + 'select_page_length': {'default_value': 100, + 'display_name': + 'View Page Length', + 'tool_tip': + 'The number of ' + 'rows to show ' + 'per page in the ' + 'view table.', + 'type': int}, + + 'hapi_api_key': { + 'default_value': '0000', 'display_name': 'HAPI API Key', 'tool_tip': 'The HAPI API key that is needed to use HAPI v2 functionality.', - 'type': str - }, - 'axisx_label_format': { - 'default_value': '%.3E', - 'display_name': 'Axis-X Tick Label Format', - 'tool_tip': 'Format specifier for the tick labels. This should be a C-Style ' - 'format.', - 'type': str - }, - - 'axisx_log_label_format': { - 'default_value': '%.3E', - 'display_name': 'Log Axis-X Tick Label Format', - 'tool_tip': 'Format specifier for the tick labels. This should be a C-Style ' - 'format.', - 'type': str - }, - - 'axisy_label_format': { - 'default_value': '%.3E', - 'display_name': 'Axis-Y Tick Label Format', - 'tool_tip': 'Format specifier for the tick labels. This should be a C-Style ' - 'format.', - 'type': str - }, - - 'axisy_log_label_format': { - 'default_value': '%.3E', - 'display_name': 'Log Axis-Y Tick Label Format', - 'tool_tip': 'Format specifier for the tick labels. This should be a C-Style ' - 'format.', - 'type': str - }, - } + 'type': str}, 'axisx_label_format': { + 'default_value': '%.3E', 'display_name': 'Axis-X Tick Label Format', + 'tool_tip': 'Format specifier for the tick labels. This should be a C-Style ' + 'format.', 'type': str}, + + 'axisx_log_label_format': { + 'default_value': '%.3E', 'display_name': 'Log Axis-X Tick Label Format', + 'tool_tip': 'Format specifier for the tick labels. This should be a C-Style ' + 'format.', 'type': str}, + + 'axisy_label_format': { + 'default_value': '%.3E', 'display_name': 'Axis-Y Tick Label Format', + 'tool_tip': 'Format specifier for the tick labels. This should be a C-Style ' + 'format.', 'type': str}, + + 'axisy_log_label_format': { + 'default_value': '%.3E', 'display_name': 'Log Axis-Y Tick Label Format', + 'tool_tip': 'Format specifier for the tick labels. This should be a C-Style ' + 'format.', 'type': str}, } DEFAULT_CONFIG = "" @@ -126,11 +114,10 @@ def config_init(): """ Reads in the config file. If it doesn't eist, it will create it with the default settings set. - """ for name, meta in Config.config_options.items(): - setattr(Config, name, meta['default_value']) - # Config.__dict__[name] = meta['default_value'] + setattr(Config, name, + meta['default_value']) # Config.__dict__[name] = meta['default_value'] Config.DEFAULT_CONFIG = Config.gen_config_string() @@ -163,29 +150,24 @@ def set_values(dict): Sets values from a parsed toml dictionary. :param dict The parsed toml key-value dictionary - """ for key, _ in Config.config_options.items(): - if key in dict['hapiest'] \ - and key in Config.config_options \ - and type(dict['hapiest'][key]) == Config.config_options[key]['type']: + if key in dict['hapiest'] and key in Config.config_options and type( + dict['hapiest'][key]) == Config.config_options[key]['type']: setattr(Config, key, dict['hapiest'][key]) - # Config.data_folder = dict['hapiest']['data_folder'] - # Config.high_dpi = dict['hapiest']['high_dpi'] - # Config.select_page_length = dict['hapiest']['select_page_length'] - # Config.hapi_api_key = dict['hapiest']['hapi_api_key'] + # Config.data_folder = dict['hapiest']['data_folder'] # Config.high_dpi = dict[ + # 'hapiest']['high_dpi'] # Config.select_page_length = dict['hapiest'][ + # 'select_page_length'] # Config.hapi_api_key = dict['hapiest']['hapi_api_key'] # Tries to load a configuration, if it fails @staticmethod def load_config(config_text): """ Attempts to load a configuration from the supplied text. If it fails to do so, - it sets unspecified values to - their defaults. + it sets unspecified values to their defaults. :param config_text The text of the configuration file - """ try: parsed = toml.loads(config_text) diff --git a/src/metadata/hapi_metadata.py b/src/metadata/hapi_metadata.py index 8ab1197..68cef0f 100644 --- a/src/metadata/hapi_metadata.py +++ b/src/metadata/hapi_metadata.py @@ -1,20 +1,21 @@ from metadata.isotopologue_meta import * +import toml -class HapiMetaData(): +class HapiMetaData: """ - Hapiest Meta Data class - to be paired with the .data and .header files generated - with each fetch request. + Hapiest Meta Data class - to be paired with the .data and .header files generated with each + fetch request. """ HMD_FILEDS = ['numin', 'numax', 'table_name', 'isos', 'dirty_cells'] def __init__(self, table_name: str, iso_id_list: List[GlobalIsotopologueId] = None, - numin: float = None, - numax: float = None, dirty_cells: List[Tuple[int, int]] = []): + numin: float = None, numax: float = None, dirty_cells: List[Tuple[int, int]] = ()): + self.iso_tuples = () self.table_name = table_name self.dirty_cells = set([]) - if iso_id_list == None: + if iso_id_list is None: if not self.initialize_from_file(): # This should hopefully only be executed in the worker process (since the # LOCAL_TABLE_CACHE is not @@ -50,7 +51,7 @@ def initialize_from_file(self): self.initialize_from_toml_dict(toml.loads(text)) return True except Exception as e: - print('Encoutnered error: {}'.format(str(e))) + print('Encountered error: {}'.format(str(e))) print('No HMD file found for table \'{}\'.'.format(self.table_name)) return False @@ -60,7 +61,7 @@ def initialize_from_hapi_table(self, table_name): molec_ids = data['molec_id'] local_ids = data['local_iso_id'] nrows = LOCAL_TABLE_CACHE[table_name]['header']['number_of_rows'] - iso_tuples = { } + iso_tuples = {} for i in range(0, nrows): tup = (molec_ids[i], local_ids[i]) if tup not in iso_tuples: @@ -76,14 +77,13 @@ def initialize_from_hapi_table(self, table_name): else: print('Failed to initialize from LOCAL_TABLE_CACHE') - def initialize_from_toml_dict(self, dict): + def initialize_from_toml_dict(self, dictionary): """ - Initializes all of the values in this HapiMetaData object from a dictonary that was read - from a toml formatted - file. + Initializes all of the values in this HapiMetaData object from a dictionary that was read + from a toml file. """ for field in HapiMetaData.HMD_FILEDS: - self.__dict__[field] = dict[field] + self.__dict__[field] = dictionary[field] if 'dirty_cells' not in self.__dict__: self.dirty_cells = set([]) else: @@ -91,7 +91,7 @@ def initialize_from_toml_dict(self, dict): self.populate_iso_tuples() def as_dict(self): - dict = { } + dict = {} for field in HapiMetaData.HMD_FILEDS: dict[field] = self.__dict__[field] return dict @@ -107,8 +107,8 @@ def save(self): def save_as(self, new_table_name): # Must convert the list of tuples to a list of lists, since the toml library doesn't - # properly serialize tuples. - # Must keep them as tuples because lists aren't hashable for some reason. + # properly serialize tuples. Must keep them as tuples because lists aren't hashable for + # some reason. self.dirty_cells = list(map(list, self.dirty_cells)) old_table_name = self.table_name self.table_name = new_table_name diff --git a/src/metadata/isotopologue_meta.py b/src/metadata/isotopologue_meta.py index b69a531..7dcdbfd 100644 --- a/src/metadata/isotopologue_meta.py +++ b/src/metadata/isotopologue_meta.py @@ -2,6 +2,7 @@ from hapi import * from utils.hapiest_util import * +from utils.log import log MoleculeId = int @@ -10,64 +11,62 @@ IsoName = AnyStr -class IsotopologueMeta(): +class IsotopologueMeta: """ Static members. Data scraped using the scrape.js function. The first element in the tuple is the minimum wave number to get data, and the second is the maximum wave number. """ - MOLECULE_DATA_RANGE: Dict[MoleculeId, Tuple[float, float]] = { - 1: (8.400e-5, 25710.825), - 2: (0.757, 14075.298), - 3: (0.026, 6996.681), - 4: (0.791, 10363.675), - 5: (3.402, 14477.377), - 6: (0.001, 11501.872), - 7: (6.440e-7, 17272.060), - 8: (1.000e-6, 9273.214), - 9: (0.017, 4092.948), - 10: (0.498, 3074.153), - 11: (0.058, 10348.719), - 12: (0.007, 1769.982), - 13: (0.003, 35874.955), - 14: (13.620, 32351.592), - 15: (5.342, 20231.245), - 16: (7.656, 16033.492), - 17: (5.888, 13907.689), - 18: (0.015, 1207.639), - 19: (0.396, 7821.109), - 20: (1.000e-6, 3099.958), - 21: (1.081, 3799.682), - 22: (11.541, 9354.200), - 23: (0.015, 17585.789), - 24: (0.873, 3197.961), - 25: (0.043, 1730.371), - 26: (1.983, 9889.038), - 27: (225.045, 3000.486), - 28: (1.901e-6, 3601.652), - 29: (686.731, 2001.348), - 30: (580.000, 996.000), - 31: (2.985, 11329.780), - 32: (10.018, 1889.334), - 33: (0.173, 3675.819), - 34: (68.716, 158.303), - 35: (763.641, 797.741), - 36: (3.976, 2530.462), - 37: (0.155, 315.908), - 38: (614.740, 3242.172), - 39: (0.019, 1407.206), - 40: (794.403, 1705.612), - 41: (890.052, 945.665), - 42: (582.830, 1518.016), - 43: (0.053, 1302.217), - 44: (4.360e-4, 759.989), - 45: (3.227, 36405.367), - 46: (1.532, 2585.247), - 47: (0.040, 2824.347), - 48: (200.772, 307.374), - 49: (793.149, 899.767) - } + MOLECULE_DATA_RANGE: Dict[MoleculeId, Tuple[float, float]] = {1: (8.400e-5, 25710.825), + 2: (0.757, 14075.298), + 3: (0.026, 6996.681), + 4: (0.791, 10363.675), + 5: (3.402, 14477.377), + 6: (0.001, 11501.872), + 7: (6.440e-7, 17272.060), + 8: (1.000e-6, 9273.214), + 9: (0.017, 4092.948), + 10: (0.498, 3074.153), + 11: (0.058, 10348.719), + 12: (0.007, 1769.982), + 13: (0.003, 35874.955), + 14: (13.620, 32351.592), + 15: (5.342, 20231.245), + 16: (7.656, 16033.492), + 17: (5.888, 13907.689), + 18: (0.015, 1207.639), + 19: (0.396, 7821.109), + 20: (1.000e-6, 3099.958), + 21: (1.081, 3799.682), + 22: (11.541, 9354.200), + 23: (0.015, 17585.789), + 24: (0.873, 3197.961), + 25: (0.043, 1730.371), + 26: (1.983, 9889.038), + 27: (225.045, 3000.486), + 28: (1.901e-6, 3601.652), + 29: (686.731, 2001.348), + 30: (580.000, 996.000), + 31: (2.985, 11329.780), + 32: (10.018, 1889.334), + 33: (0.173, 3675.819), + 34: (68.716, 158.303), + 35: (763.641, 797.741), + 36: (3.976, 2530.462), + 37: (0.155, 315.908), + 38: (614.740, 3242.172), + 39: (0.019, 1407.206), + 40: (794.403, 1705.612), + 41: (890.052, 945.665), + 42: (582.830, 1518.016), + 43: (0.053, 1302.217), + 44: (4.360e-4, 759.989), + 45: (3.227, 36405.367), + 46: (1.532, 2585.247), + 47: (0.040, 2824.347), + 48: (200.772, 307.374), + 49: (793.149, 899.767)} # Indices defined in hapi ID_LOC: int = 0 @@ -80,21 +79,22 @@ class IsotopologueMeta(): all_isotopologues: List['IsotopologueMeta'] = [] # Maps molecule id to a list of all isotopologues of that molecule - molecules: Dict[MoleculeId, List['IsotopologueMeta']] = { } + molecules: Dict[MoleculeId, List['IsotopologueMeta']] = {} # Maps pointing to Isotopologue objects given name, id, global id, etc. # Maps molecule id to Isotopologue object for a normal molecule - FROM_MOL_ID: Dict[MoleculeId, 'IsotopologueMeta'] = { } + FROM_MOL_ID: Dict[MoleculeId, 'IsotopologueMeta'] = {} # Maps the name of an isotopologue to the Isotopologue object representing it - FROM_ISO_NAME: Dict[str, 'IsotopologueMeta'] = { } + FROM_ISO_NAME: Dict[str, 'IsotopologueMeta'] = {} # Maps the global id of an iso to the Isotopologue object representing it - FROM_GLOBAL_ID: Dict[GlobalIsotopologueId, 'IsotopologueMeta'] = { } + FROM_GLOBAL_ID: Dict[GlobalIsotopologueId, 'IsotopologueMeta'] = {} # Maps the pair (molecule_id, iso_id) to the Isotopologue object representing it - FROM_MOL_ID_ISO_ID: Dict[Tuple[MoleculeId, IsotopologueId], 'IsotopologueMeta'] = { } + FROM_MOL_ID_ISO_ID: Dict[Tuple[MoleculeId, IsotopologueId], 'IsotopologueMeta'] = {} # Maps molecule name to the Isotopologue object representing it - FROM_MOL_NAME: Dict[str, 'IsotopologueMeta'] = { } + FROM_MOL_NAME: Dict[str, 'IsotopologueMeta'] = {} # Regular expressions to create HTML from a molecules chemical definition + # Found this on the internet ELEMENT_REGEX: str = 'A[cglmrstu]|B[aehikr]?|C[adeflmnorsu]?|D[bsy]?|E[rsu]|F[elmr]?|G[' \ 'ade]|H[efgos]?|I[nr]?|Kr?|L[airuv]|M[dgnot]|N[abdeiop]?|O(s)?|P[' \ 'abdmortu]?|R[abefghnu]|S[bcegimnr]?|T[abcehilm]|U(u[' \ @@ -109,11 +109,11 @@ class IsotopologueMeta(): ISO_TO_HTML_REGEX: re = re.compile(CHUNK_REGEX) @staticmethod - def create_html(_iso: str) -> str: + def create_html(the_iso: str) -> str: """ *Creates html for isotopologues on fetch window.* """ - iso = '%s' % _iso + iso = '%s' % the_iso html = '' start = 0 @@ -143,7 +143,7 @@ def create_html(_iso: str) -> str: iso = iso[start:] # This is an isotope - handle it as such - if dat['neutrons'] != None: + if dat['neutrons'] is not None: html += ' ' + dat['neutrons'] + '' html += dat['iso_element'] @@ -152,7 +152,7 @@ def create_html(_iso: str) -> str: html += dat['element'] # How many of the element / isotope - if dat['count'] != None: + if dat['count'] is not None: html += '' + dat['count'] + '' return html @@ -189,11 +189,11 @@ def from_iso_name(iso_name: str) -> 'IsotopologueMeta': return IsotopologueMeta.FROM_ISO_NAME[iso_name] @staticmethod - def from_molecule_id(id: int) -> 'IsotopologueMeta': + def from_molecule_id(mid: int) -> 'IsotopologueMeta': """ *Converts an integer molecule id into an Isotopologue object* """ - return IsotopologueMeta.FROM_MOL_ID[id] + return IsotopologueMeta.FROM_MOL_ID[mid] @staticmethod def from_mol_id_iso_id(mid: int, iid: int) -> 'IsotopologueMeta': @@ -217,7 +217,7 @@ def get_wn_range(self) -> Tuple[float, float]: return IsotopologueMeta.MOLECULE_DATA_RANGE[self.molecule_id] else: log('No wavenumber range-data for molecule id ', self.molecule_id) - return (0, 100000000) + return 0, 100000000 def get_iso_count(self) -> int: """ @@ -265,7 +265,7 @@ def __init__(self, molecule_id: int, isotopologue_id: int): IsotopologueMeta.FROM_MOL_ID_ISO_ID[(molecule_id, isotopologue_id)] = self def iso_tuple(self): - return (self.molecule_id, self.iso_id) + return self.molecule_id, self.iso_id IsotopologueMeta.populate() diff --git a/src/metadata/molecule_meta.py b/src/metadata/molecule_meta.py index aab0a00..903ffb1 100644 --- a/src/metadata/molecule_meta.py +++ b/src/metadata/molecule_meta.py @@ -16,14 +16,14 @@ class MoleculeMeta: @staticmethod def __initialize_molecule_metadata(): api = CrossSectionApi() - cache = JsonCache(".molm", api.request_molecule_meta, timedelta(days = 1)) + cache = JsonCache(".molm", api.request_molecule_meta, timedelta(days=1)) if cache.ok(): data = cache.data() else: return - MoleculeMeta.__FORMULA_TO_MID = { } - MoleculeMeta.__MOLECULE_METADATA = { } - MoleculeMeta.__NAME_TO_MID = { } + MoleculeMeta.__FORMULA_TO_MID = {} + MoleculeMeta.__MOLECULE_METADATA = {} + MoleculeMeta.__NAME_TO_MID = {} for molecule in data: MoleculeMeta.__NAME_TO_MID[molecule['common_name']] = molecule['id'] @@ -42,6 +42,10 @@ def has_xscs(name): r = [name for name in MoleculeMeta.all_names() if has_xscs(name)] return r + @staticmethod + def all_formulas() -> List[str]: + return list(MoleculeMeta.__FORMULA_TO_MID.keys()) + def __init__(self, molecule_id: Union[int, str]): if MoleculeMeta.__MOLECULE_METADATA is None: MoleculeMeta.__initialize_molecule_metadata() @@ -64,6 +68,3 @@ def __init__(self, molecule_id: Union[int, str]): def is_populated(self): return self.populated - - def all_formulas(self) -> List[str]: - return list(MoleculeMeta.__FORMULA_TO_MID.keys()) diff --git a/src/metadata/xsc_meta.py b/src/metadata/xsc_meta.py index 9209daf..de2665f 100644 --- a/src/metadata/xsc_meta.py +++ b/src/metadata/xsc_meta.py @@ -48,9 +48,8 @@ class CrossSectionMeta: """ - ## # A dictionary that maps molecule id to a list of cross section meta info. - molecule_metas = { } + molecule_metas = {} @staticmethod def add_meta_objects(meta_objs: List[Dict]): @@ -58,8 +57,8 @@ def insert(meta_obj): ind = meta_obj['molecule_id'] # If there is no key 'ind' in molecule_metas and an identical # meta_obj hasn't already been added. - if ind in CrossSectionMeta.molecule_metas and \ - meta_obj not in CrossSectionMeta.molecule_metas[ind]: + if ind in CrossSectionMeta.molecule_metas and meta_obj not in \ + CrossSectionMeta.molecule_metas[ind]: CrossSectionMeta.molecule_metas[ind].append(meta_obj) else: CrossSectionMeta.molecule_metas[ind] = [meta_obj] @@ -79,8 +78,7 @@ def __init__(self, molecule_id): self.api = CrossSectionApi() - self.cache = \ - JsonCache(".xscm", self.api.request_xsc_meta, timedelta(days = 1.0)) + self.cache = JsonCache(".xscm", self.api.request_xsc_meta, timedelta(days=1.0)) if not self.cache.ok(): err_log("Failed to load xscm from cache.") else: diff --git a/src/test/__init__.py b/src/test/__init__.py index d3c680c..3d817d5 100644 --- a/src/test/__init__.py +++ b/src/test/__init__.py @@ -13,16 +13,8 @@ from test.throw_test import ThrowTest -tests: List[Test] = [ - Test(), - FailTest(), - ThrowTest(), - HapiSourcesTest(), - MoleculeInfoTest(), - GraphDisplayTest(), - BandDisplayTest(), - ConfigEditorTest() - ] +tests: List[Test] = [Test(), FailTest(), ThrowTest(), HapiSourcesTest(), MoleculeInfoTest(), + GraphDisplayTest(), BandDisplayTest(), ConfigEditorTest()] def run_tests(): @@ -33,10 +25,12 @@ def run_tests(): q = multiprocessing.Queue() for test in tests: print(name_fmt.format(test.name())) - p = Process(target = test.run, args = (q,)) + p = Process(target=test.run, args=(q,)) p.start() p.join() result: Union[bool, Tuple[type, Exception, TracebackType]] = q.get() + # Result is on object, so don't replace 'result == False' with 'not result' since that will + # be true if result is an exception. if test.should_fail(): if result == False: print(result_fmt.format('', 'Ok!')) @@ -51,8 +45,7 @@ def run_tests(): print(result_fmt.format('', 'Failed (should throw)')) else: traceback = result - print(result_fmt.format('', 'Ok!')) - # print(traceback) + print(result_fmt.format('', 'Ok!')) # print(traceback) else: if result == True: print(result_fmt.format('', 'Ok!')) diff --git a/src/test/band_display_test.py b/src/test/band_display_test.py index a90d7db..c3792eb 100644 --- a/src/test/band_display_test.py +++ b/src/test/band_display_test.py @@ -11,6 +11,7 @@ class BandDisplayTest(Test): + def __init__(self): Test.__init__(self) @@ -46,7 +47,7 @@ def random_band(): for i in range(0, 10): bands2.add_band(random_band()) - t = threading.Thread(target = close_window) + t = threading.Thread(target=close_window) t.start() widget.setMinimumSize(256, 256) widget.add_bands(bands1) diff --git a/src/test/config_editor_test.py b/src/test/config_editor_test.py index 8696feb..accb276 100644 --- a/src/test/config_editor_test.py +++ b/src/test/config_editor_test.py @@ -6,7 +6,9 @@ from test.test import Test from widgets.config_editor_widget import ConfigEditorWidget + class ConfigEditorTest(Test): + def __init__(self): Test.__init__(self) @@ -22,7 +24,7 @@ def close_window(): sleep(0.25) window.deleteLater() - t = threading.Thread(target = close_window) + t = threading.Thread(target=close_window) t.start() widget = ConfigEditorWidget(None) widget.setMinimumSize(256, 256) diff --git a/src/test/fail_test.py b/src/test/fail_test.py index 00bcd1c..464844a 100644 --- a/src/test/fail_test.py +++ b/src/test/fail_test.py @@ -2,6 +2,7 @@ class FailTest(Test): + def __init__(self): Test.__init__(self) diff --git a/src/test/graph_display_test.py b/src/test/graph_display_test.py index d347fc0..571a361 100644 --- a/src/test/graph_display_test.py +++ b/src/test/graph_display_test.py @@ -10,6 +10,7 @@ class GraphDisplayTest(Test): + def __init__(self): Test.__init__(self) @@ -36,14 +37,13 @@ def random_graph(): y[i] = amp * math.sin(freq * x[i]) return (x, y) - t = threading.Thread(target = close_window) + t = threading.Thread(target=close_window) t.start() widget = GraphDisplayWindowGui('a', 'h') widget.setMinimumSize(256, 256) # def add_graph(self, x, y, title, xtitle, ytitle, name, args): - args = { 'Diluent': { 'self': 1.0, 'air': 0.0 }, 'graph_fn': '', - 'Environment': { 'T': 1, 'p': 0 } - } + args = {'Diluent': {'self': 1.0, 'air': 0.0}, 'graph_fn': '', + 'Environment': {'T': 1, 'p': 0}} x, y = random_graph() widget.add_graph(x, y, '1', 'x', 'y', 'oof', args) x, y = random_graph() diff --git a/src/test/hapi_sources_test.py b/src/test/hapi_sources_test.py index b4d828c..e2a8a64 100644 --- a/src/test/hapi_sources_test.py +++ b/src/test/hapi_sources_test.py @@ -3,28 +3,23 @@ from time import sleep -sources = { - 'hapi': { - 'authors': ['R.V. Kochanov', 'I.E. Gordon', 'L.S. Rothman', 'P. Wcislo', 'C. Hill', - 'J.S. Wilzewski'], - 'title': 'HITRAN Application Programming Interface (HAPI): A comprehensive approach ' - 'to working with spectroscopic data', - 'year': '2016', - 'journal': 'J. Quant. Spectrosc. Radiat. Transfer', - 'volume': 177, - 'page_start': 15, - 'page_end': 30, - 'doi': '10.1016/j.jqsrt.2016.03.005' - }, - 'hapiest': { +sources = {'hapi': { + 'authors': ['R.V. Kochanov', 'I.E. Gordon', + 'L.S. Rothman', 'P. Wcislo', + 'C. Hill', 'J.S. Wilzewski'], + 'title': 'HITRAN Application Programming ' + 'Interface (HAPI): A comprehensive ' + 'approach ' + 'to working with spectroscopic data', + 'year': '2016', + 'journal': 'J. Quant. Spectrosc. Radiat. ' + 'Transfer', + 'volume': 177, 'page_start': 15, 'page_end': 30, + 'doi': '10.1016/j.jqsrt.2016.03.005'}, + 'hapiest': { 'authors': ['W. Matt', 'J. Karns', 'B. Cairo', 'M. Sova', 'E. Messer', 'D. Lohmann', - 'R.V. Kochanov', - 'I.E. Gordon', 'B. Tenbergen', 'S. Kanbur'], - 'title': 'HAPIEST: A GUI for HAPI', - 'year': '2018', - 'doi': None - } - } + 'R.V. Kochanov', 'I.E. Gordon', 'B. Tenbergen', 'S. Kanbur'], + 'title': 'HAPIEST: A GUI for HAPI', 'year': '2018', 'doi': None}} from test.test import Test from PyQt5 import QtWidgets @@ -32,6 +27,7 @@ class HapiSourcesTest(Test): + def __init__(self): Test.__init__(self) @@ -49,7 +45,7 @@ def close_window(): window.deleteLater() pass - t = threading.Thread(target = close_window) + t = threading.Thread(target=close_window) t.start() items = QtWidgets.QWidget(window) layout = QtWidgets.QVBoxLayout() diff --git a/src/test/molecule_info_test.py b/src/test/molecule_info_test.py index d720d2d..458cc5f 100644 --- a/src/test/molecule_info_test.py +++ b/src/test/molecule_info_test.py @@ -2,24 +2,20 @@ from time import sleep -sources = { - 'hapi': { - 'authors': ['R.V. Kochanov', 'I.E. Gordon', 'L.S. Rothman', 'P. Wcislo', 'C. Hill', - 'J.S. Wilzewski'], - 'title': 'HITRAN Application Programming Interface (HAPI): A comprehensive approach to ' - 'working with spectroscopic data', - 'year': '2016', - 'doi': '10.1016/j.jqsrt.2016.03.005' - }, - 'hapiest': { +sources = {'hapi': { + 'authors': ['R.V. Kochanov', 'I.E. Gordon', + 'L.S. Rothman', 'P. Wcislo', 'C. Hill', + 'J.S. Wilzewski'], + 'title': 'HITRAN Application Programming ' + 'Interface (HAPI): A comprehensive ' + 'approach to ' + 'working with spectroscopic data', + 'year': '2016', + 'doi': '10.1016/j.jqsrt.2016.03.005'}, + 'hapiest': { 'authors': ['W. Matt', 'J. Karns', 'B. Cairo', 'M. Sova', 'E. Messer', 'D. Lohmann', - 'R.V. Kochanov', - 'I.E. Gordon', 'B. Tenbergen', 'S. Kanbur'], - 'title': 'HAPIEST: A GUI for HAPI', - 'year': '2018', - 'doi': None - } - } + 'R.V. Kochanov', 'I.E. Gordon', 'B. Tenbergen', 'S. Kanbur'], + 'title': 'HAPIEST: A GUI for HAPI', 'year': '2018', 'doi': None}} from test.test import Test from PyQt5 import QtWidgets @@ -28,6 +24,7 @@ class MoleculeInfoTest(Test): + def __init__(self): Test.__init__(self) @@ -45,7 +42,7 @@ def close_window(): # Necessary initialization _ = MoleculeMeta(0) - t = threading.Thread(target = close_window) + t = threading.Thread(target=close_window) t.start() widget = MoleculeInfoWidget('CO2') window.setCentralWidget(widget) diff --git a/src/test/test.py b/src/test/test.py index 73b9a01..95050c6 100644 --- a/src/test/test.py +++ b/src/test/test.py @@ -4,6 +4,7 @@ class Test: + def __init__(self): pass diff --git a/src/test/throw_test.py b/src/test/throw_test.py index 97b69f5..e9f9257 100644 --- a/src/test/throw_test.py +++ b/src/test/throw_test.py @@ -2,6 +2,7 @@ class ThrowTest(Test): + def __init__(self): Test.__init__(self) diff --git a/src/utils/colors.py b/src/utils/colors.py index ad67bb8..a7c326c 100644 --- a/src/utils/colors.py +++ b/src/utils/colors.py @@ -2,15 +2,14 @@ class Colors: - ## Some handsome hex colors taken from this stack overflow thread: + # Some handsome hex colors taken from this stack overflow thread: # https://graphicdesign.stackexchange.com/questions/3682/where-can-i-find-a-large-palette-set # -of-contrasting-colors-for-coloring-many-d # It seems like it may be a good future resource as well. colors = [0xff0000, 0xb00000, 0x870000, 0x550000, 0xe4e400, 0xbaba00, 0x878700, 0x545400, - 0x00ff00, 0x00b000, - 0x008700, 0x005500, 0x00ffff, 0x00b0b0, 0x008787, 0x005555, 0xb0b0ff, 0x8484ff, - 0x4949ff, 0x0000ff, - 0xff00ff, 0xb000b0, 0x870087, 0x550055, 0xe4e4e4, 0xbababa, 0x878787, 0x545454] + 0x00ff00, 0x00b000, 0x008700, 0x005500, 0x00ffff, 0x00b0b0, 0x008787, 0x005555, + 0xb0b0ff, 0x8484ff, 0x4949ff, 0x0000ff, 0xff00ff, 0xb000b0, 0x870087, 0x550055, + 0xe4e4e4, 0xbababa, 0x878787, 0x545454] __trash = shuffle(colors) __color_index = -1 diff --git a/src/utils/dsl.py b/src/utils/dsl.py index 4d7c40a..8d7a82b 100644 --- a/src/utils/dsl.py +++ b/src/utils/dsl.py @@ -4,34 +4,30 @@ class DSL: """ hapi has support for a small lisp-like Domain Specific Language implemented using nested - python tuples. The - following grammar was made in order to make the language look like a more proper lisp. The - grammar is not perfect, - there are a few optimizations that could be made quite readily (e.g. use case-independent - regex instead of checking - for upper and lower case). The DSL is used by hapi to query and filter tables stored in memory. - - The DSL class contains a static parser object for the DSL. - + python tuples. The following grammar was made in order to make the language look like a more + proper lisp. The grammar is not perfect, there are a few optimizations that could be made + quite readily (e.g. use case-independent regex instead of checking for upper and lower case). + The DSL is used by hapi to query and filter tables stored in memory. The DSL class contains a + static parser object for the DSL. """ - ## Whitespace.. + # Whitespace.. whitespace_parse = whitespace.optional() - ## Literals / Constants + # Literals / Constants int_parse = regex('[-+]?(0|([1-9][0-9]*))').map(int) float_parse = regex('[-+]?((\\d*\\.\\d+)|(\\d+(\\.\\d*)?))([Ee][+-]?\\d+)?').map(float) string_parse = regex( "(\"((\\\\[\\\\a-zA-Z\'])|[^\"])*\")|('((\\\\[\\\\a-zA-Z\'])|[^'])*')").map(eval) name_parse = regex('[a-zA-Z][a-zA-Z_\\-0-9]*') - ## Arithmetic + # Arithmetic add_parse = regex('\\+|(add)|(ADD)|(sum)|(SUM)').map(lambda x: '+') sub_parse = regex('\\-|(sub)|(SUB)|(diff)|(DIFF)').map(lambda x: '-') mul_parse = regex('\\*|(mul)|(MUL)').map(lambda x: '*') div_parse = regex('\\/|(DIV)|(div)').map(lambda x: '/') - ## Comparison / Conditionals + # Comparison / Conditionals between_parse = regex('(range)|(RANGE)|(between)|(BETWEEN)').map(lambda x: 'range') subset_parse = regex('(in)|(IN)|(subset)|(SUBSET)').map(lambda x: 'in') and_parse = regex('(and)|(AND)|(&&?)').map(lambda x: 'and') @@ -42,32 +38,31 @@ class DSL: lte_parse = regex('(<=)|(lessorequal)|(LESSOREQUAL)|(lte)|(LTE)').map(lambda x: '<=') gte_parse = regex( '(>=)|(moreorequal)|(MOREOREQUAL)|(gte)|(GTE)|(greaterorequal)|(GREATEROREQUAL)').map( - lambda x: '>=') + lambda x: '>=') equal_parse = regex('(==?)|(eq)|(EQ)|(equal)|(EQUAL)').map(lambda x: '=') neq_parse = regex('(!=)|(<>)|(~=)|(ne)|(NE)|(neq)|(NEQ)|(note)|(NOTE)').map(lambda x: '!=') - ## Casting + # Casting to_string_parse = regex('(to_string)|(TO_STRING)|(str)|(STR)|(string)|(STRING)').map( lambda x: 'str') to_list_parse = regex('(to_list)|(TO_LIST)|(list)|(LIST)').map(lambda x: 'list') - ## Search / Match / Count + # Search / Match / Count search_parse = regex('(search)|(SEARCH)').map(lambda x: 'search') match_parse = regex('(match)|(MATCH)|(like)|(LIKE)').map(lambda x: 'match') find_parse = regex('(findall)|(FINDALL)').map(lambda x: 'findall') count_parse = regex('(count)|(COUNT)').map(lambda: 'count') operation = add_parse | sub_parse | mul_parse | div_parse | between_parse | subset_parse | \ - and_parse | or_parse | \ - not_parse | lt_parse | gt_parse | lte_parse | gte_parse | equal_parse | neq_parse\ - | to_string_parse | \ - to_list_parse | search_parse | match_parse | find_parse | count_parse + and_parse | or_parse | not_parse | lt_parse | gt_parse | lte_parse | gte_parse | \ + equal_parse | neq_parse | to_string_parse | to_list_parse | search_parse | \ + match_parse | find_parse | count_parse p_open_parse = whitespace_parse >> string('(') >> whitespace_parse p_close_parse = whitespace_parse >> string(')') >> whitespace_parse list_parse = p_open_parse >> ( - (float_parse | int_parse | string_parse) << whitespace_parse).many().map( - list) << p_close_parse + (float_parse | int_parse | string_parse) << whitespace_parse).many().map( + list) << p_close_parse @generate def call_parse(): @@ -96,9 +91,9 @@ def parse_expression(expression): try: x = DSL.expression_list_parse.parse(expression) return x - except Exception as e: + except: try: z = DSL.expression_parse.parse(expression) return z - except Exception as e: + except: return None diff --git a/src/utils/fetch_error.py b/src/utils/fetch_error.py index 1331fb1..20cd9b1 100644 --- a/src/utils/fetch_error.py +++ b/src/utils/fetch_error.py @@ -8,7 +8,7 @@ class FetchErrorKind(Enum): BadNuMax = 4 # This wont be used BadConnection = 5 BadIsoList = 6 - FailedToRetreiveData = 7 + FailedToRetrieveData = 7 FailedToOpenThread = 8 EmptyName = 9 diff --git a/src/utils/hapi_api.py b/src/utils/hapi_api.py index 13df551..417c3e4 100644 --- a/src/utils/hapi_api.py +++ b/src/utils/hapi_api.py @@ -125,7 +125,8 @@ class CrossSectionApi: def __init__(self): pass - def __send_request(self, uri): + @staticmethod + def __send_request(uri): try: content = url.urlopen(uri).read() # TODO: Add more robust error handling here. It could be a bad connection or a bad API key. @@ -140,8 +141,8 @@ def request_molecule_meta(self) -> Union[bytes, HapiApiException]: :return: json text that contains information about every molecule in the HITRAN database. """ uri = f"{CrossSectionApi.BASE_URL}/{CrossSectionApi.API_ROUTE}/{Config.hapi_api_key}" \ - f"/{CrossSectionApi.MOLECULES_ROUTE}" - return self.__send_request(uri) + f"/{CrossSectionApi.MOLECULES_ROUTE}" + return CrossSectionApi.__send_request(uri) def request_xsc_meta(self, molecule_id: int = None) -> Union[bytes, HapiApiException]: """ @@ -153,9 +154,9 @@ def request_xsc_meta(self, molecule_id: int = None) -> Union[bytes, HapiApiExcep something like 400 molecules as of August 2018). :return: will return a dictionary on success, which will """ - uri = f"{CrossSectionApi.BASE_URL}/{CrossSectionApi.API_ROUTE}/" + \ - f"{Config.hapi_api_key}/{CrossSectionApi.XSC_META_ROUTE}" - return self.__send_request(uri) + uri = f"{CrossSectionApi.BASE_URL}/{CrossSectionApi.API_ROUTE}/" + f"{ + Config.hapi_api_key}/{CrossSectionApi.XSC_META_ROUTE}" + return CrossSectionApi.__send_request(uri) def request_xsc(self, xsc_name: str, filename: str): """ diff --git a/src/utils/hapiest_util.py b/src/utils/hapiest_util.py index 2e70dcd..1da3ca2 100644 --- a/src/utils/hapiest_util.py +++ b/src/utils/hapiest_util.py @@ -32,7 +32,7 @@ def get_all_data_names(): datas = [] for f in files: match = DATA_FILE_REGEX.match(f) - if match == None: + if match is None: continue if f.endswith('.xsc'): datas.append(match.string) diff --git a/src/utils/log.py b/src/utils/log.py index 49a6484..67f08bf 100644 --- a/src/utils/log.py +++ b/src/utils/log.py @@ -1,10 +1,11 @@ import sys from multiprocessing import Queue +from functools import reduce from PyQt5 import QtCore -class TextStream(): +class TextStream: """ Writes to the appropriate queues. @@ -33,16 +34,16 @@ class TextReceiver(QtCore.QObject): write_text_signal = QtCore.pyqtSignal(str) write_html_signal = QtCore.pyqtSignal(str) - ## An instance of a TextStream that has the queue that the worker thread reads from + # An instance of a TextStream that has the queue that the worker thread reads from TEXT_STREAM = None - ## Receives text and writes it to the status bar + # Receives text and writes it to the status bar TEXT_RECEIVER = None - ## The worker thread + # The worker thread TEXT_THREAD = None - ## A reference to the main window + # A reference to the main window WINDOW = None @staticmethod @@ -69,7 +70,7 @@ def init(main_window, *args, **kwargs): TextReceiver.TEXT_THREAD = QtCore.QThread() # Connect the signal to the console output handler in the main window # Connect the console output signals - TextReceiver.TEXT_RECEIVER.write_text_signal.connect(lambda str: main_window.text_log(str)) + TextReceiver.TEXT_RECEIVER.write_text_signal.connect(lambda st: main_window.text_log(st)) TextReceiver.TEXT_RECEIVER.write_html_signal.connect( lambda html: main_window.html_log(html)) # Move the receiver to the background thread @@ -109,22 +110,22 @@ def debug(*args, **kwargs): """ - print(*args, file = sys.stderr, **kwargs) + print(*args, file=sys.stderr, **kwargs) -def log(arg): +def log(*args): """ Prints to the console_output with a fancy lookin log label. """ - s = str(arg) - if TextReceiver.TEXT_STREAM != None: + s = reduce(lambda l, r: f"{l}, {r}", args) + if TextReceiver.TEXT_STREAM is not None: if len(s) > 128: s = s[0:128] print_html_to_status_bar(f'
[Log]
 {s}...') else: print_html_to_status_bar(f'
[Log]
 {s}') - print("[Log] ", s, file = sys.__stdout__) + print("[Log] ", s, file=sys.__stdout__) def err_log(dat): @@ -134,13 +135,13 @@ def err_log(dat): """ s = str(dat) - if TextReceiver.TEXT_STREAM != None: + if TextReceiver.TEXT_STREAM is not None: if len(s) > 128: s = s[0:128] print_html_to_status_bar(f'
[Error]
 {s}...') else: print_html_to_status_bar(f'
[Error]
 {s}') - print("[Err] ", str(dat), file = sys.__stdout__) + print("[Err] ", str(dat), file=sys.__stdout__) def debug_log(dat): @@ -149,10 +150,10 @@ def debug_log(dat): """ s = str(dat) - if TextReceiver.TEXT_STREAM != None: + if TextReceiver.TEXT_STREAM is not None: if len(s) > 128: s = s[0:128] print_html_to_status_bar(f'
[Debug]
 {s}...') else: print_html_to_status_bar(f'
[Debug]
 {s}') - print("[Debug] ", str(dat), file = sys.__stdout__) + print("[Debug] ", str(dat), file=sys.__stdout__) diff --git a/src/widgets/about_widget.py b/src/widgets/about_widget.py index 444cc27..d1e3a6d 100644 --- a/src/widgets/about_widget.py +++ b/src/widgets/about_widget.py @@ -4,6 +4,7 @@ class AboutWidget(QWidget): + def __init__(self, parent): QWidget.__init__(self, parent) self.text = QTextEdit() diff --git a/src/widgets/config_editor_widget.py b/src/widgets/config_editor_widget.py index 1ee6f5d..08f69f4 100644 --- a/src/widgets/config_editor_widget.py +++ b/src/widgets/config_editor_widget.py @@ -46,7 +46,7 @@ def __init__(self, parent): input.setToolTip(meta['tool_tip']) layout.addWidget(input) - setattr(self, key, { 'input': input, 'layout': layout }) + setattr(self, key, {'input': input, 'layout': layout}) # self.__dict__[key] = { # 'input': input, # 'layout': layout @@ -78,8 +78,7 @@ def __on_save_clicked(self, *_args): value = self.__dict__[key]['input'].isChecked() else: value = None - setattr(Config, key, value) - # Config.__dict__[key] = value + setattr(Config, key, value) # Config.__dict__[key] = value Config.write_config(Config.gen_config_string()) self.close() diff --git a/src/widgets/cross_section_fetch_widget.py b/src/widgets/cross_section_fetch_widget.py index 1611ca1..65100e2 100644 --- a/src/widgets/cross_section_fetch_widget.py +++ b/src/widgets/cross_section_fetch_widget.py @@ -124,7 +124,7 @@ def __on_fetch_clicked(self, _checked: bool): xscs = self.get_selected_xscs() if len(xscs) == 0: return - args = HapiWorker.echo(xscs = xscs, molecule_name = self.molecule.currentText()) + args = HapiWorker.echo(xscs=xscs, molecule_name=self.molecule.currentText()) self.fetch_button.setDisabled(True) self.worker = HapiWorker(WorkRequest.DOWNLOAD_XSCS, args, self.__on_fetch_xsc_done) self.worker.start() @@ -158,8 +158,7 @@ def set_cross_section_list_items(self, xscs: List[str]): range(self.cross_section_list.count()))) for xsc in xscs: item = QtWidgets.QListWidgetItem(xsc) - item.setFlags(item.flags() | - QtCore.Qt.ItemIsUserCheckable | QtCore.Qt.ItemIsEnabled) + item.setFlags(item.flags() | QtCore.Qt.ItemIsUserCheckable | QtCore.Qt.ItemIsEnabled) item.setCheckState(QtCore.Qt.Unchecked) diff --git a/src/widgets/fetch_widget.py b/src/widgets/fetch_widget.py index e3ea35c..dcafdd5 100644 --- a/src/widgets/fetch_widget.py +++ b/src/widgets/fetch_widget.py @@ -82,21 +82,19 @@ def populate_parameter_lists(self): that HITRAN has to offer. """ - for group in [item for item in sorted(PARAMETER_GROUPS.keys(), key = str.lower) if + for group in [item for item in sorted(PARAMETER_GROUPS.keys(), key=str.lower) if item[0].isalpha()]: item = QtWidgets.QListWidgetItem(group) - item.setFlags(item.flags() | - QtCore.Qt.ItemIsUserCheckable | QtCore.Qt.ItemIsEnabled) + item.setFlags(item.flags() | QtCore.Qt.ItemIsUserCheckable | QtCore.Qt.ItemIsEnabled) item.setCheckState(QtCore.Qt.Unchecked) self.param_group_list.addItem(item) # Add all parameter groups to the parameter groups list. - for par in sorted(PARLIST_ALL, key = str.lower): + for par in sorted(PARLIST_ALL, key=str.lower): item = QtWidgets.QListWidgetItem(par) - item.setFlags(item.flags() | - QtCore.Qt.ItemIsUserCheckable | QtCore.Qt.ItemIsEnabled) + item.setFlags(item.flags() | QtCore.Qt.ItemIsUserCheckable | QtCore.Qt.ItemIsEnabled) item.setCheckState(QtCore.Qt.Unchecked) @@ -137,14 +135,13 @@ def fetch_done(self, work_result: WorkResult): for err in errs: # This means the wavenumber range was too small (probably), so # we'll tell the user it is too small - if err.error == FetchErrorKind.FailedToRetreiveData: + if err.error == FetchErrorKind.FailedToRetrieveData: err_log('The entered wavenumber range is too small, try increasing it') # Not much to do in regards to user feedback in this case.... elif err.error == FetchErrorKind.FailedToOpenThread: err_log('Failed to open thread to make query HITRAN') elif err.error == FetchErrorKind.BadConnection: - err_log( - 'Error: Failed to connect to HITRAN. Check your internet connection ' + err_log('Error: Failed to connect to HITRAN. Check your internet connection ' 'and try again.') elif err.error == FetchErrorKind.BadIsoList: err_log(' Error: You must select at least one isotopologue.') @@ -236,9 +233,9 @@ def __molecule_id_index_changed(self): # Make sure there is a key associated with the item so we can use it later item.setData(QtCore.Qt.UserRole, isotopologue.id) - item.setFlags(item.flags() | - QtCore.Qt.ItemIsUserCheckable | QtCore.Qt.ItemIsEnabled | - QtCore.Qt.ItemIsSelectable) + item.setFlags( + item.flags() | QtCore.Qt.ItemIsUserCheckable | QtCore.Qt.ItemIsEnabled | + QtCore.Qt.ItemIsSelectable) # The normal molecule is always at index 1, and we always want that # molecule to be selected @@ -277,14 +274,9 @@ def __handle_fetch_clicked(self): return self.disable_fetch_button() - work = HapiWorker.echo( - data_name = self.get_data_name(), - iso_id_list = selected_isos, - numin = numin, - numax = numax, - parameter_groups = parameter_groups, - parameters = parameters) - self.worker = HapiWorker(WorkRequest.FETCH, work, callback = self.fetch_done) + work = HapiWorker.echo(data_name=self.get_data_name(), iso_id_list=selected_isos, + numin=numin, numax=numax, parameter_groups=parameter_groups, parameters=parameters) + self.worker = HapiWorker(WorkRequest.FETCH, work, callback=self.fetch_done) self.parent.workers.append(self.worker) self.worker.start() diff --git a/src/widgets/graphing/band_display_window_gui.py b/src/widgets/graphing/band_display_window_gui.py index c180646..2d54832 100644 --- a/src/widgets/graphing/band_display_window_gui.py +++ b/src/widgets/graphing/band_display_window_gui.py @@ -45,13 +45,13 @@ def add_bands(self, bands: Bands): cur_series.setName(band.band_id) series.append(cur_series) - cur_series.hovered.connect(lambda point, state: - self.__on_series_hover(cur_series, point, state)) + cur_series.hovered.connect( + lambda point, state: self.__on_series_hover(cur_series, point, state)) cur_series.setName(band.band_id) cur_series.setUseOpenGL(True) self.chart = QChart() - self.band_series = { } + self.band_series = {} self.legend = BandLegend(self.chart) self.chart.legend().setVisible(False) @@ -96,8 +96,8 @@ def add_bands(self, bands: Bands): cur_series.series.setMarkerSize(LegendItem.NORMAL_WIDTH) series.append(cur_series) - cur_series.hovered.connect(lambda point, state: - self.__on_series_hover(cur_series, point, state)) + cur_series.hovered.connect( + lambda point, state: self.__on_series_hover(cur_series, point, state)) cur_series.setName(band.band_id) cur_series.setUseOpenGL(True) diff --git a/src/widgets/graphing/band_legend.py b/src/widgets/graphing/band_legend.py index fc91106..0fd534c 100644 --- a/src/widgets/graphing/band_legend.py +++ b/src/widgets/graphing/band_legend.py @@ -116,8 +116,8 @@ def on_toggle_all_bold_toggled(checked: bool): self.layout.addLayout(self.toggle_all_layout) for band_item in self.band_widgets: - self.layout.addWidget(band_item) - # The hover-to-bolden feature has been replaced + self.layout.addWidget( + band_item) # The hover-to-bolden feature has been replaced # # band_item.installEventFilter(self) self.layout.addSpacerItem(QSpacerItem(1, 1, QSizePolicy.Expanding, QSizePolicy.Expanding)) diff --git a/src/widgets/graphing/graph_display_window_gui.py b/src/widgets/graphing/graph_display_window_gui.py index 0b6a73c..ffc054e 100644 --- a/src/widgets/graphing/graph_display_window_gui.py +++ b/src/widgets/graphing/graph_display_window_gui.py @@ -117,11 +117,9 @@ def add_graph(self, x, y, title, xtitle, ytitle, name, args): series.setName(name) else: series.setName( - name + ' -
Function: {},
T: {:.2f} K, P: {:.2f} atm
air: {:.2f}, ' - 'self: {:.2f}'.format( - args['graph_fn'], args['Environment']['T'], - args['Environment']['p'], - args['Diluent']['air'], args['Diluent']['self'])) + name + ' -
Function: {},
T: {:.2f} K, P: {:.2f} atm
air: {:.2f}, ' + 'self: {:.2f}'.format(args['graph_fn'], args['Environment']['T'], + args['Environment']['p'], args['Diluent']['air'], args['Diluent']['self'])) series.setUseOpenGL(True) self.chart = QChart() @@ -169,12 +167,10 @@ def add_graph(self, x, y, title, xtitle, ytitle, name, args): if 'xsc' in args and args['xsc']: series.setName(name) else: - series.setName( - name + ' -
Function={},
T={:.2f}, P={:.2f}
air: {:.2f}, ' - 'self: {:.2f}'.format( - args['graph_fn'], args['Environment']['T'], args['Environment']['p'], - args['Diluent']['air'], - args['Diluent']['self'])) + series.setName(name + ' -
Function={},
T={:.2f}, P={:.2f}
air: {:.2f}, ' + 'self: {:.2f}'.format(args['graph_fn'], + args['Environment']['T'], args['Environment']['p'], args['Diluent']['air'], + args['Diluent']['self'])) series.setUseOpenGL(True) series.add_to_chart(self.chart) @@ -406,15 +402,14 @@ def to_x_y_arrays(series): for point in points_vector: x.append(point.x()) y.append(point.y()) - return { 'x': x, 'y': y } + return {'x': x, 'y': y} - dict = { } - series_lists = list(map(lambda series: dict.update({ - series.name(): to_x_y_arrays(series) - }), self.all_series())) + dict = {} + series_lists = list(map(lambda series: dict.update({series.name(): to_x_y_arrays(series)}), + self.all_series())) try: with open(filename, 'w') as file: - file.write(json.dumps(dict, indent = 4)) + file.write(json.dumps(dict, indent=4)) except Exception as e: print("Encountered error {} while saving to file".format(str(e))) diff --git a/src/widgets/graphing/graphing_widget.py b/src/widgets/graphing/graphing_widget.py index 4589193..7e0816a 100644 --- a/src/widgets/graphing/graphing_widget.py +++ b/src/widgets/graphing/graphing_widget.py @@ -20,13 +20,11 @@ class GraphingWidget(GUI, QtWidgets.QWidget): RADIANCE_SPECTRUM_STRING: str = "Radiance Spectrum" BANDS_STRING: str = "Bands" - str_to_graph_ty = { - ABSORPTION_COEFFICIENT_STRING: GraphType.ABSORPTION_COEFFICIENT, - ABSORPTION_SPECTRUM_STRING: GraphType.ABSORPTION_SPECTRUM, - TRANSMITTANCE_SPECTRUM_STRING: GraphType.TRANSMITTANCE_SPECTRUM, - RADIANCE_SPECTRUM_STRING: GraphType.RADIANCE_SPECTRUM, - BANDS_STRING: GraphType.BANDS - } + str_to_graph_ty = {ABSORPTION_COEFFICIENT_STRING: GraphType.ABSORPTION_COEFFICIENT, + ABSORPTION_SPECTRUM_STRING: GraphType.ABSORPTION_SPECTRUM, + TRANSMITTANCE_SPECTRUM_STRING: GraphType.TRANSMITTANCE_SPECTRUM, + RADIANCE_SPECTRUM_STRING: GraphType.RADIANCE_SPECTRUM, + BANDS_STRING: GraphType.BANDS} def __init__(self, parent): QtWidgets.QWidget.__init__(self) @@ -93,17 +91,16 @@ def __init__(self, parent): uic.loadUi('layouts/graphing_widget.ui', self) self.wn_step_enabled.toggled.connect( - lambda: self.__handle_checkbox_toggle(self.wn_step_enabled, self.wn_step)) + lambda: self.__handle_checkbox_toggle(self.wn_step_enabled, self.wn_step)) self.wn_wing_enabled.toggled.connect( - lambda: self.__handle_checkbox_toggle(self.wn_wing_enabled, self.wn_wing)) + lambda: self.__handle_checkbox_toggle(self.wn_wing_enabled, self.wn_wing)) self.wn_wing_hw_enabled.toggled.connect( - lambda: self.__handle_checkbox_toggle(self.wn_wing_hw_enabled, self.wn_wing_hw)) + lambda: self.__handle_checkbox_toggle(self.wn_wing_hw_enabled, self.wn_wing_hw)) self.intensity_threshold_enabled.toggled.connect( - lambda: self.__handle_checkbox_toggle(self.intensity_threshold_enabled, - self.intensity_threshold)) + lambda: self.__handle_checkbox_toggle(self.intensity_threshold_enabled, + self.intensity_threshold)) self.use_existing_window.toggled.connect( - lambda: self.__handle_checkbox_toggle(self.use_existing_window, - self.selected_window)) + lambda: self.__handle_checkbox_toggle(self.use_existing_window, self.selected_window)) self.graph_button.clicked.connect(self.graph) self.graph_type.currentTextChanged.connect(self.__on_graph_type_changed) @@ -128,8 +125,8 @@ def __init__(self, parent): self.wn_step.setToolTip("Select increment for wave number (wn).") self.wn_wing.setToolTip( - "Set distance from the center of each line to the farthest point where the " - "profile is considered to be non zero.") + "Set distance from the center of each line to the farthest point where the " + "profile is considered to be non zero.") self.wn_wing_hw.setToolTip("Set relative value of the line wing in halfwidths") self.adjustSize() @@ -139,10 +136,10 @@ def get_standard_parameters(self): if self.xsc is not None: Components = [] SourceTables = [data_name] - Environment = { 'p': self.xsc.pressure, 'T': self.xsc.temp } + Environment = {'p': self.xsc.pressure, 'T': self.xsc.temp} WavenumberRange = (self.xsc.numin, self.xsc.numax) WavenumberStep = self.xsc.step - Diluent = { 'air': 0.0, 'self': 1.0 } + Diluent = {'air': 0.0, 'self': 1.0} # TODO: Verify that these are the proper values. WavenumberWing = 0.0 WavenumberWingHW = 0.0 @@ -150,7 +147,7 @@ def get_standard_parameters(self): hmd = HapiMetaData(data_name) Components = hmd.iso_tuples SourceTables = [data_name] - Environment = { 'p': self.get_pressure(), 'T': self.get_temp() } + Environment = {'p': self.get_pressure(), 'T': self.get_temp()} Diluent = self.get_diluent() WavenumberRange = self.get_wn_range() WavenumberStep = self.get_wn_step() @@ -159,18 +156,10 @@ def get_standard_parameters(self): graph_fn = self.get_line_profile() - return HapiWorker.echo( - graph_fn = graph_fn, - Components = Components, - SourceTables = SourceTables, - Environment = Environment, - Diluent = Diluent, - HITRAN_units = False, - WavenumberRange = WavenumberRange, - WavenumberStep = WavenumberStep, - WavenumberWing = WavenumberWing, - WavenumberWingHW = WavenumberWingHW - ) + return HapiWorker.echo(graph_fn=graph_fn, Components=Components, SourceTables=SourceTables, + Environment=Environment, Diluent=Diluent, HITRAN_units=False, + WavenumberRange=WavenumberRange, WavenumberStep=WavenumberStep, + WavenumberWing=WavenumberWing, WavenumberWingHW=WavenumberWingHW) def graph(self): standard_params = self.get_standard_parameters() @@ -189,9 +178,9 @@ def graph(self): self.graph_bands(standard_params) def graph_abs_coef(self, standard_parameters): - work = HapiWorker.echo(title = GraphingWidget.ABSORPTION_COEFFICIENT_STRING, - titlex = "Wavenumber (cm-1)", - titley = 'Absorption Coefficient ', **standard_parameters) + work = HapiWorker.echo(title=GraphingWidget.ABSORPTION_COEFFICIENT_STRING, + titlex="Wavenumber (cm-1)", + titley='Absorption Coefficient ', **standard_parameters) if work['SourceTables'][0].endswith('.xsc'): work['titley'] = 'molecules / cm2' @@ -217,21 +206,14 @@ def graph_as(self, standard_params): if standard_params['WavenumberStep'] is None: standard_params['WavenumberStep'] = Resolution / 2 elif standard_params['WavenumberStep'] <= Resolution: - standard_params['WavenumberStep'] = Resolution * 1.0001 - # err_log('Wavenumber Step must be less than Instrumental Resolution') - # self.done_graphing() - # return - - work = HapiWorker.echo( - title = GraphingWidget.ABSORPTION_SPECTRUM_STRING, - titlex = "Wavenumber (cm-1)", - titley = "Absorption Spectrum", - path_length = path_length, - instrumental_fn = instrumental_fn, - Resolution = Resolution, - AF_wing = AF_wing, - **standard_params - ) + standard_params[ + 'WavenumberStep'] = Resolution * 1.0001 # err_log('Wavenumber Step must be less + # than Instrumental Resolution') # self.done_graphing() # return + + work = HapiWorker.echo(title=GraphingWidget.ABSORPTION_SPECTRUM_STRING, + titlex="Wavenumber (cm-1)", titley="Absorption Spectrum", + path_length=path_length, instrumental_fn=instrumental_fn, Resolution=Resolution, + AF_wing=AF_wing, **standard_params) if self.use_existing_window.isChecked(): selected_window = self.selected_window.currentText() if selected_window in GraphDisplayWindow.graph_windows: @@ -254,21 +236,16 @@ def graph_rs(self, standard_params): elif standard_params['WavenumberStep'] <= Resolution: err_log('Wavenumber Step must be less than Instrumental Resolution') self.data_name_error.setText( - '' + 'Wavenumber Step must be less than the ' - 'Instrumental Resolution' + '') + '' + 'Wavenumber Step must be less than the ' + 'Instrumental Resolution' + '') self.done_graphing() return - work = HapiWorker.echo( - title = GraphingWidget.RADIANCE_SPECTRUM_STRING, - titlex = "Wavenumber (cm-1)", - titley = "Radiance (erg * c-1*cm-1)", - path_length = path_length, - instrumental_fn = instrumental_fn, - Resolution = Resolution, - AF_wing = AF_wing, - **standard_params - ) + work = HapiWorker.echo(title=GraphingWidget.RADIANCE_SPECTRUM_STRING, + titlex="Wavenumber (cm-1)", + titley="Radiance (erg * c-1*cm-1)", path_length=path_length, + instrumental_fn=instrumental_fn, Resolution=Resolution, AF_wing=AF_wing, + **standard_params) if self.use_existing_window.isChecked(): selected_window = self.selected_window.currentText() if selected_window in GraphDisplayWindow.graph_windows: @@ -291,21 +268,15 @@ def graph_ts(self, standard_params): elif standard_params['WavenumberStep'] <= Resolution: err_log('Wavenumber Step must be less than Instrumental Resolution') self.data_name_error.setText( - '' + 'Wavenumber Step must be less than the ' - 'Instrumental Resolution' + '') + '' + 'Wavenumber Step must be less than the ' + 'Instrumental Resolution' + '') self.done_graphing() return - work = HapiWorker.echo( - title = GraphingWidget.TRANSMITTANCE_SPECTRUM_STRING, - titlex = "Wavenumber (cm-1)", - titley = "Transmittance", - path_length = path_length, - instrumental_fn = instrumental_fn, - Resolution = Resolution, - AF_wing = AF_wing, - **standard_params - ) + work = HapiWorker.echo(title=GraphingWidget.TRANSMITTANCE_SPECTRUM_STRING, + titlex="Wavenumber (cm-1)", titley="Transmittance", path_length=path_length, + instrumental_fn=instrumental_fn, Resolution=Resolution, AF_wing=AF_wing, + **standard_params) if self.use_existing_window.isChecked(): selected_window = self.selected_window.currentText() if selected_window in GraphDisplayWindow.graph_windows: @@ -318,7 +289,7 @@ def graph_ts(self, standard_params): self.update_existing_window_items() def graph_bands(self, standard_params): - work = HapiWorker.echo(TableName = self.get_data_name(), title = "Bands") + work = HapiWorker.echo(TableName=self.get_data_name(), title="Bands") if self.use_existing_window.isChecked(): selected_window = self.selected_window.currentText() if selected_window in GraphDisplayWindow.graph_windows: @@ -329,7 +300,7 @@ def graph_bands(self, standard_params): def populate_data_names(self): """ - Retreive data file names from users data folder for display in the Graphing Window. + Retrieve data file names from users data folder for display in the Graphing Window. """ try: list(map(lambda name: self.data_name.addItem(name), get_all_data_names())) @@ -439,7 +410,7 @@ def callback(work_result): self.use_existing_window.setChecked(self.same_window_checked) - worker = HapiWorker(WorkRequest.TABLE_META_DATA, { 'table_name': new_table }, callback) + worker = HapiWorker(WorkRequest.TABLE_META_DATA, {'table_name': new_table}, callback) self.workers.append(worker) worker.start() @@ -475,7 +446,7 @@ def get_diluent(self): that is just gamma_air and gamma_self). """ gamma_air = self.gamma_air.value() - return { 'air': gamma_air, 'self': 1.0 - gamma_air } + return {'air': gamma_air, 'self': 1.0 - gamma_air} def get_data_name(self): """ @@ -644,8 +615,7 @@ def remove_worker_by_jid(self, jid: int): ## # Parameters that are required to graph hapi tables. These are not required to graph bands. parameters_required_to_graph = ['molec_id', 'local_iso_id', 'nu', 'sw', 'a', 'elower', - 'gamma_air', 'delta_air', - 'gamma_self', 'n_air', 'gp', 'gpp'] + 'gamma_air', 'delta_air', 'gamma_self', 'n_air', 'gp', 'gpp'] def update_existing_window_items(self): self.selected_window.clear() @@ -655,8 +625,7 @@ def update_existing_window_items(self): else: graph_ty = GraphingWidget.str_to_graph_ty[graph_ty_str] - fitting_graph_windows = list(builtins.filter(lambda window: - window.graph_ty == graph_ty, + fitting_graph_windows = list(builtins.filter(lambda window: window.graph_ty == graph_ty, GraphDisplayWindow.graph_windows.values())) if len(fitting_graph_windows) == 0: diff --git a/src/widgets/hapi_source_widget.py b/src/widgets/hapi_source_widget.py index 64c8b73..fab2326 100644 --- a/src/widgets/hapi_source_widget.py +++ b/src/widgets/hapi_source_widget.py @@ -7,8 +7,7 @@ class HapiSourceWidget(QtWidgets.QTextEdit): def __init__(self, title: str, authors: List[str], year: str, doi: Optional[str], journal: Optional[str] = None, volume: Optional[str] = None, - page_start: Optional[int] = None, - page_end: Optional[int] = None, **_kwargs): + page_start: Optional[int] = None, page_end: Optional[int] = None, **_kwargs): self.title = title self.authors = authors self.year = year diff --git a/src/widgets/hapi_table_view.py b/src/widgets/hapi_table_view.py index db3b85a..0f5aa83 100644 --- a/src/widgets/hapi_table_view.py +++ b/src/widgets/hapi_table_view.py @@ -114,7 +114,7 @@ def __init__(self, parent, table_name): if self.table_name != None: self.workers = [] - args = HapiWorker.echo(table_name = table_name) + args = HapiWorker.echo(table_name=table_name) self.start_worker = HapiWorker(WorkRequest.GET_TABLE, args, self.display_first_page) self.start_worker.start() @@ -127,8 +127,7 @@ def __init__(self, parent, table_name): # self.items = [] self.double_validator = QDoubleValidator() self.double_validator.setNotation(QDoubleValidator.ScientificNotation) - self.int_validator = QIntValidator() - # self.horizontalHeader().setStretchLastSection(True) + self.int_validator = QIntValidator() # self.horizontalHeader().setStretchLastSection(True) def get_widget(self, row, column): return self.indexWidget(self.table_model.createIndex(row, column)) @@ -215,8 +214,8 @@ def display_first_page(self, work_result: WorkResult): column_width = sum(map(int, itertools.filterfalse(lambda x: not x.isdigit(), ["".join(x) for _, x in itertools.groupby( - self.column_formats[column], - key = str.isdigit)]))) + self.column_formats[column], + key=str.isdigit)]))) if column_width == 0: column_width = 16 self.setColumnWidth(column, column_width) @@ -328,8 +327,7 @@ def save_table(self): # Name for the new table. output_name = self.view_widget.get_output_name() - worker = HapiWorker(WorkRequest.SAVE_TABLE, - { 'table': self.table, 'name': output_name }, + worker = HapiWorker(WorkRequest.SAVE_TABLE, {'table': self.table, 'name': output_name}, self.done_saving) self.hmd.save_as(output_name) diff --git a/src/widgets/main_window_gui.py b/src/widgets/main_window_gui.py index a083ca0..fea2b9a 100644 --- a/src/widgets/main_window_gui.py +++ b/src/widgets/main_window_gui.py @@ -1,5 +1,6 @@ from PyQt5.QtWidgets import QMainWindow, QAction, QStatusBar, QCompleter, QVBoxLayout, \ - QPushButton, QWidget + QPushButton, \ + QWidget from metadata.molecule_meta import MoleculeMeta from widgets.about_widget import AboutWidget diff --git a/src/widgets/molecule_info_widget.py b/src/widgets/molecule_info_widget.py index 47640aa..07e8957 100644 --- a/src/widgets/molecule_info_widget.py +++ b/src/widgets/molecule_info_widget.py @@ -96,7 +96,7 @@ def create_field(text): self.adjustSize() def restructure_aliases(self): - reformatted = { } + reformatted = {} for item in self.molecule.aliases: reformatted[item['type']] = item['alias'] self.molecule.aliases = reformatted diff --git a/src/widgets/select_widget.py b/src/widgets/select_widget.py index 303ec6d..d11312a 100644 --- a/src/widgets/select_widget.py +++ b/src/widgets/select_widget.py @@ -77,7 +77,7 @@ def __on_select_table_name_selection_changed(self, new_selection): if new_selection == '': return - args = HapiWorker.echo(table_name = new_selection) + args = HapiWorker.echo(table_name=new_selection) worker = HapiWorker(WorkRequest.TABLE_META_DATA, args, self.__on_select_table_name_complete) worker.start() @@ -98,8 +98,7 @@ def __on_select_table_name_complete(self, work_result): self.parameter_list.clear() for par in parameters: item = QtWidgets.QListWidgetItem(par) - item.setFlags(item.flags() | - QtCore.Qt.ItemIsUserCheckable | QtCore.Qt.ItemIsEnabled) + item.setFlags(item.flags() | QtCore.Qt.ItemIsUserCheckable | QtCore.Qt.ItemIsEnabled) item.setCheckState(QtCore.Qt.Unchecked) self.parameter_list.addItem(item) @@ -128,9 +127,8 @@ def __on_run_button_click(self): self.run_button.setDisabled(True) - args = HapiWorker.echo(ParameterNames = selected_params, TableName = table_name, - DestinationTableName = new_table_name, - Conditions = parsed_expression) + args = HapiWorker.echo(ParameterNames=selected_params, TableName=table_name, + DestinationTableName=new_table_name, Conditions=parsed_expression) worker = HapiWorker(WorkRequest.SELECT, args, self.__on_run_done) self.parent.workers.append(worker) diff --git a/src/windows/graph_display_window.py b/src/windows/graph_display_window.py index 9c91be2..136534d 100644 --- a/src/windows/graph_display_window.py +++ b/src/windows/graph_display_window.py @@ -11,15 +11,13 @@ class GraphDisplayWindow(Window): done_signal = QtCore.pyqtSignal(object) - graph_ty_to_work_ty = { - GraphType.ABSORPTION_COEFFICIENT: WorkRequest.ABSORPTION_COEFFICIENT, - GraphType.TRANSMITTANCE_SPECTRUM: WorkRequest.TRANSMITTANCE_SPECTRUM, - GraphType.RADIANCE_SPECTRUM: WorkRequest.RADIANCE_SPECTRUM, - GraphType.ABSORPTION_SPECTRUM: WorkRequest.ABSORPTION_SPECTRUM, - GraphType.BANDS: WorkRequest.BANDS - } + graph_ty_to_work_ty = {GraphType.ABSORPTION_COEFFICIENT: WorkRequest.ABSORPTION_COEFFICIENT, + GraphType.TRANSMITTANCE_SPECTRUM: WorkRequest.TRANSMITTANCE_SPECTRUM, + GraphType.RADIANCE_SPECTRUM: WorkRequest.RADIANCE_SPECTRUM, + GraphType.ABSORPTION_SPECTRUM: WorkRequest.ABSORPTION_SPECTRUM, + GraphType.BANDS: WorkRequest.BANDS} - graph_windows = { } + graph_windows = {} next_graph_window_id = 1 @@ -45,16 +43,14 @@ def __init__(self, graph_ty, work_object, parent): gui: BandDisplayWindowGui = BandDisplayWindowGui() self.workers = { '0': HapiWorker(GraphDisplayWindow.graph_ty_to_work_ty[graph_ty], work_object, - lambda x: [self.plot_bands(x), self.workers.pop('0')]) - } + lambda x: [self.plot_bands(x), self.workers.pop('0')])} else: gui: GraphDisplayWindowGui = GraphDisplayWindowGui(graph_ty, work_object['title'] + ' - ' + str( self.window_id)) self.workers = { '0': HapiWorker(GraphDisplayWindow.graph_ty_to_work_ty[graph_ty], work_object, - lambda x: [self.plot(x), self.workers.pop('0')]) - } + lambda x: [self.plot(x), self.workers.pop('0')])} Window.__init__(self, gui, parent) @@ -112,8 +108,7 @@ def plot(self, work_result: WorkResult): result = work_result.result (x, y) = result['x'], result['y'] self.gui.add_graph(x, y, result['title'], result['titlex'], result['titley'], - result['name'], - result['args']) + result['name'], result['args']) except Exception as e: err_log(e) diff --git a/src/windows/main_window.py b/src/windows/main_window.py index 034747a..6ccfdc0 100644 --- a/src/windows/main_window.py +++ b/src/windows/main_window.py @@ -3,6 +3,7 @@ class MainWindow(Window): + def __init__(self): Window.__init__(self, MainWindowGui(self), None) diff --git a/src/worker/hapi_worker.py b/src/worker/hapi_worker.py index 9230512..654fee8 100644 --- a/src/worker/hapi_worker.py +++ b/src/worker/hapi_worker.py @@ -86,7 +86,7 @@ def __run(self): return HapiWorker.job_results.append(work_result) except Exception as e: - self.step_signal.emit({ }) + self.step_signal.emit({}) finally: for work_result in HapiWorker.job_results: if work_result.job_id == self.job_id: diff --git a/src/worker/work_request.py b/src/worker/work_request.py index 6bd7b8a..2e580c7 100644 --- a/src/worker/work_request.py +++ b/src/worker/work_request.py @@ -8,6 +8,7 @@ class WorkRequest: + def __init__(self, job_id: int, work_type: Any, work_args: Dict[str, Any]): self.job_id = job_id self.work_type = work_type @@ -36,7 +37,7 @@ def __init__(self, job_id: int, work_type: Any, work_args: Dict[str, Any]): WORKER: 'Work' = None - WORK_FUNCTIONS: Dict[WorkType, Callable] = { } + WORK_FUNCTIONS: Dict[WorkType, Callable] = {} def do_work(self) -> Any: """ @@ -55,28 +56,30 @@ def start_work_process(): class Work: + @staticmethod def WORK_FUNCTION(workq: mp.Queue, resultq: mp.Queue) -> int: """ Handles the calling of most hapi functions. """ - WorkRequest.WORK_FUNCTIONS = { - WorkRequest.START_HAPI: WorkFunctions.start_hapi, - WorkRequest.FETCH: WorkFunctions.fetch, - WorkRequest.ABSORPTION_COEFFICIENT: WorkFunctions.graph_absorption_coefficient, - WorkRequest.GET_TABLE: WorkFunctions.get_table, - WorkRequest.SAVE_TABLE: WorkFunctions.save_table, - WorkRequest.TABLE_NAMES: WorkFunctions.table_names, - WorkRequest.TABLE_META_DATA: WorkFunctions.table_meta_data, - WorkRequest.SELECT: WorkFunctions.select, - WorkRequest.ABSORPTION_SPECTRUM: WorkFunctions.graph_absorption_spectrum, - WorkRequest.TRANSMITTANCE_SPECTRUM: WorkFunctions.graph_transmittance_spectrum, - WorkRequest.RADIANCE_SPECTRUM: WorkFunctions.graph_radiance_spectrum, - WorkRequest.BANDS: WorkFunctions.graph_bands, - WorkRequest.DOWNLOAD_XSCS: WorkFunctions.download_xscs - } - - WorkFunctions.start_hapi(**{ }) + WorkRequest.WORK_FUNCTIONS = {WorkRequest.START_HAPI: WorkFunctions.start_hapi, + WorkRequest.FETCH: WorkFunctions.fetch, + WorkRequest.ABSORPTION_COEFFICIENT: + WorkFunctions.graph_absorption_coefficient, + WorkRequest.GET_TABLE: WorkFunctions.get_table, + WorkRequest.SAVE_TABLE: WorkFunctions.save_table, + WorkRequest.TABLE_NAMES: WorkFunctions.table_names, + WorkRequest.TABLE_META_DATA: WorkFunctions.table_meta_data, + WorkRequest.SELECT: WorkFunctions.select, + WorkRequest.ABSORPTION_SPECTRUM: + WorkFunctions.graph_absorption_spectrum, + WorkRequest.TRANSMITTANCE_SPECTRUM: + WorkFunctions.graph_transmittance_spectrum, + WorkRequest.RADIANCE_SPECTRUM: WorkFunctions.graph_radiance_spectrum, + WorkRequest.BANDS: WorkFunctions.graph_bands, + WorkRequest.DOWNLOAD_XSCS: WorkFunctions.download_xscs} + + WorkFunctions.start_hapi(**{}) def print_tb(tb, exc_value): print('\n'.join([''] + traceback.format_tb(tb) + [str(exc_value)]).replace('\n', @@ -100,6 +103,6 @@ def print_tb(tb, exc_value): resultq.put(result) def __init__(self): - self.process: mp.Process = mp.Process(target = Work.WORK_FUNCTION, - args = (WorkRequest.WORKQ, WorkRequest.RESULTQ)) + self.process: mp.Process = mp.Process(target=Work.WORK_FUNCTION, + args=(WorkRequest.WORKQ, WorkRequest.RESULTQ)) self.process.start() diff --git a/src/worker/work_result.py b/src/worker/work_result.py index 3b4cd6f..d8aa088 100644 --- a/src/worker/work_result.py +++ b/src/worker/work_result.py @@ -2,6 +2,7 @@ class WorkResult: + def __init__(self, job_id: int, result: Any): self.job_id = job_id self.result = result