add logging and delay as metadata

src/specsanalyzer/convert.py

@@ -1,9 +1,14 @@
 """Specsanalyzer image conversion module"""
 from __future__ import annotations
 
+import logging
+
 import numpy as np
 from scipy.ndimage import map_coordinates
 
+# Configure logging
+logger = logging.getLogger("specsanalyzer.specsscan")
+
 
 def get_damatrix_from_calib2d(
     lens_mode: str,
@@ -82,7 +87,7 @@ def get_damatrix_from_calib2d(
 
     elif lens_mode in supported_space_modes:
         # use the mode defaults
-        print("This is a spatial mode, using default " + lens_mode + " config")
+        logger.info("This is a spatial mode, using default " + lens_mode + " config")
         rr_vec, da_matrix_full = get_rr_da(lens_mode, calib2d_dict)
         a_inner = da_matrix_full[0][0]
         da_matrix = da_matrix_full[1:][:]

src/specsanalyzer/core.py

@@ -20,9 +20,14 @@
 from specsanalyzer.convert import physical_unit_data
 from specsanalyzer.img_tools import crop_xarray
 from specsanalyzer.img_tools import fourier_filter_2d
+from specsanalyzer.logging import set_verbosity
+from specsanalyzer.logging import setup_logging
 
 package_dir = os.path.dirname(__file__)
 
+# Configure logging
+logger = setup_logging("specsanalyzer")
+
 
 class SpecsAnalyzer:
     """SpecsAnalyzer: A class to convert photoemission data from a SPECS Phoibos analyzer from
@@ -38,19 +43,22 @@ def __init__(
         self,
         metadata: dict[Any, Any] = {},
         config: dict[Any, Any] | str = {},
+        verbose: bool = True,
         **kwds,
     ):
         """SpecsAnalyzer constructor.
 
         Args:
             metadata (dict, optional): Metadata dictionary. Defaults to {}.
             config (dict | str, optional): Metadata dictionary or file path. Defaults to {}.
+            verbose (bool, optional): Disable info logs if set to False.
             **kwds: Keyword arguments passed to ``parse_config``.
         """
         self._config = parse_config(
             config,
             **kwds,
         )
+        set_verbosity(logger, verbose)
         self.metadata = metadata
         self._data_array = None
         self.print_msg = True
@@ -286,7 +294,7 @@ def convert_image(
                 ek_min = range_dict["ek_min"]
                 ek_max = range_dict["ek_max"]
                 if self.print_msg:
-                    print("Using saved crop parameters...")
+                    logger.info("Using saved crop parameters...")
                 data_array = crop_xarray(data_array, ang_min, ang_max, ek_min, ek_max)
             except KeyError:
                 try:
@@ -343,11 +351,13 @@ def convert_image(
                         + data_array.coords[data_array.dims[1]][0]
                     )
                     if self.print_msg:
-                        print("Cropping parameters not found, using cropping ranges from config...")
+                        logger.info(
+                            "Cropping parameters not found, using cropping ranges from config...",
+                        )
                     data_array = crop_xarray(data_array, ang_min, ang_max, ek_min, ek_max)
                 except KeyError:
                     if self.print_msg:
-                        print(
+                        logger.warning(
                             "Warning: Cropping parameters not found, "
                             "use method crop_tool() after loading.",
                         )
@@ -402,7 +412,7 @@ def crop_tool(
         try:
             mesh_obj = data_array.plot(ax=ax)
         except AttributeError:
-            print("Load the scan first!")
+            logger.info("Load the scan first!")
             raise
 
         lineh1 = ax.axhline(y=data_array.Angle[0])
@@ -650,7 +660,7 @@ def fft_tool(
 
             filtered = fourier_filter_2d(raw_image, peaks=fft_filter_peaks, ret="filtered")
         except IndexError:
-            print("Load the scan first!")
+            logger.warning("Load the scan first!")
             raise
 
         fig = plt.figure()

src/specsscan/core.py

@@ -21,6 +21,7 @@
 from specsanalyzer.io import to_h5
 from specsanalyzer.io import to_nexus
 from specsanalyzer.io import to_tiff
+from specsanalyzer.logging import set_verbosity
 from specsanalyzer.logging import setup_logging
 from specsscan.helpers import get_coords
 from specsscan.helpers import get_scan_path
@@ -50,13 +51,15 @@ def __init__(
         self,
         metadata: dict = {},
         config: dict | str = {},
+        verbose: bool = True,
         **kwds,
     ):
         """SpecsScan constructor.
 
         Args:
             metadata (dict, optional): Metadata dictionary. Defaults to {}.
             config (Union[dict, str], optional): Metadata dictionary or file path. Defaults to {}.
+            verbose (bool, optional): Disable info logs if set to False.
             **kwds: Keyword arguments passed to ``parse_config``.
         """
         self._config = parse_config(
@@ -65,6 +68,8 @@ def __init__(
             **kwds,
         )
 
+        set_verbosity(logger, verbose)
+
         self.metadata = metadata
 
         self._scan_info: dict[Any, Any] = {}
@@ -75,12 +80,14 @@ def __init__(
                 folder_config={},
                 user_config={},
                 system_config={},
+                verbose=verbose,
             )
         except KeyError:
             self.spa = SpecsAnalyzer(
                 folder_config={},
                 user_config={},
                 system_config={},
+                verbose=verbose,
             )
 
         self._result: xr.DataArray = None
@@ -242,10 +249,11 @@ def load_scan(
             k: coordinate_mapping[k] for k in coordinate_mapping.keys() if k in res_xarray.dims
         }
         depends_dict = {
-            rename_dict[k]: coordinate_depends[k]
+            rename_dict.get(k, k): coordinate_depends[k]
             for k in coordinate_depends.keys()
             if k in res_xarray.dims
         }
+
         res_xarray = res_xarray.rename(rename_dict)
         for k, v in coordinate_mapping.items():
             if k in fast_axes:
@@ -260,6 +268,7 @@ def load_scan(
             "/entry/sample/transformations/sample_polar": "Polar",
             "/entry/sample/transformations/sample_tilt": "Tilt",
             "/entry/sample/transformations/sample_azimuth": "Azimuth",
+            "/entry/instrument/beam_pump/pulse_delay": "delay",
         }
 
         # store data for resolved axis coordinates

src/specsscan/helpers.py

@@ -2,17 +2,22 @@
 from __future__ import annotations
 
 import datetime as dt
+import logging
 from pathlib import Path
 from typing import Any
 from typing import Sequence
 
 import numpy as np
 import pandas as pd
+import xarray as xr
 from tqdm.auto import tqdm
 
 from specsanalyzer.config import complete_dictionary
 from specsscan.metadata import MetadataRetriever
 
+# Configure logging
+logger = logging.getLogger("specsanalyzer.specsscan")
+
 
 def get_scan_path(path: Path | str, scan: int, basepath: Path | str) -> Path:
     """Returns the path to the given scan.
@@ -123,7 +128,7 @@ def load_images(
                 "load_scan method.",
             ) from exc
 
-        print(f"Averaging over {avg_dim}...")
+        logger.info(f"Averaging over {avg_dim}...")
         for dim in tqdm(raw_2d_sliced):
             avg_list = []
             for image in tqdm(dim, leave=False, disable=not tqdm_enable_nested):
@@ -210,14 +215,14 @@ def parse_lut_to_df(scan_path: Path) -> pd.DataFrame:
         df_lut.reset_index(inplace=True)
 
         new_cols = df_lut.columns.to_list()[1:]
-        new_cols[new_cols.index("delaystage")] = "Delay"
+        new_cols[new_cols.index("delaystage")] = "DelayStage"
         new_cols.insert(3, "delay (fs)")  # Create label to drop the column later
 
         df_lut = df_lut.set_axis(new_cols, axis="columns")
         df_lut.drop(columns="delay (fs)", inplace=True)
 
     except FileNotFoundError:
-        print(
+        logger.info(
             "LUT.txt not found. Storing metadata from info.txt",
         )
         return None
@@ -265,7 +270,7 @@ def get_coords(
             return (np.array([]), "")
 
         if df_lut is not None:
-            print("scanvector.txt not found. Obtaining coordinates from LUT")
+            logger.info("scanvector.txt not found. Obtaining coordinates from LUT")
 
             df_new: pd.DataFrame = df_lut.loc[:, df_lut.columns[2:]]
 
@@ -276,13 +281,18 @@ def get_coords(
             raise FileNotFoundError("scanvector.txt file not found!") from exc
 
     if scan_type == "delay":
-        t_0 = scan_info["TimeZero"]
-        coords -= t_0
-        coords *= 2 / 3e11 * 1e15
+        t0 = scan_info["TimeZero"]
+        coords = mm_to_fs(coords, t0)
 
     return coords, dim
 
 
+def mm_to_fs(delaystage: xr.DataArray | np.ndarray | float, t0: float) -> float:
+    delay = delaystage - t0
+    delay *= 2 / 2.99792458e11 * 1e15
+    return delay
+
+
 def compare_coords(axis_data: np.ndarray) -> tuple[np.ndarray, int]:
     """Identifies the most changing column in a given 2-D numpy array.
 
@@ -338,6 +348,9 @@ def parse_info_to_dict(path: Path) -> dict:
     except FileNotFoundError as exc:
         raise FileNotFoundError("info.txt file not found.") from exc
 
+    if "DelayStage" in info_dict and "TimeZero" in info_dict:
+        info_dict["delay"] = mm_to_fs(info_dict["DelayStage"], info_dict["TimeZero"])
+
     return info_dict
 
 
@@ -377,7 +390,7 @@ def handle_meta(
     if metadata is None:
         metadata = {}
 
-    print("Gathering metadata from different locations")
+    logger.info("Gathering metadata from different locations")
     # get metadata from LUT dataframe
     lut_meta = {}
     energy_scan_mode = "snapshot"
@@ -395,10 +408,10 @@ def handle_meta(
 
     metadata["scan_info"] = complete_dictionary(
         metadata.get("scan_info", {}),
-        complete_dictionary(lut_meta, scan_info),
+        complete_dictionary(scan_info, lut_meta),
     )  # merging dictionaries
 
-    print("Collecting time stamps...")
+    logger.info("Collecting time stamps...")
     if "time" in metadata["scan_info"]:
         time_list = [metadata["scan_info"]["time"][0], metadata["scan_info"]["time"][-1]]
     elif "StartTime" in metadata["scan_info"]:
@@ -445,8 +458,6 @@ def handle_meta(
     metadata["scan_info"]["slow_axes"] = slow_axes
     metadata["scan_info"]["fast_axes"] = fast_axes
 
-    print("Done!")
-
     return metadata
 
 
@@ -460,7 +471,7 @@ def find_scan(path: Path, scan: int) -> list[Path]:
     Returns:
         List[Path]: scan_path: Path object pointing to the scan folder
     """
-    print("Scan path not provided, searching directories...")
+    logger.info("Scan path not provided, searching directories...")
     for file in path.iterdir():
         if file.is_dir():
             try:
@@ -474,7 +485,7 @@ def find_scan(path: Path, scan: int) -> list[Path]:
                     file.glob(f"*/*/Raw Data/{scan}"),
                 )
                 if scan_path:
-                    print("Scan found at path:", scan_path[0])
+                    logger.info(f"Scan found at path: {scan_path[0]}")
                     break
     else:
         scan_path = []

src/specsscan/metadata.py

@@ -90,7 +90,7 @@ def fetch_epics_metadata(self, ts_from: float, ts_to: float, metadata: dict) ->
             for key in list(metadata["scan_info"]):
                 if key.lower() in replace_dict:
                     metadata["scan_info"][replace_dict[key.lower()]] = metadata["scan_info"][key]
-                    metadata["scan_info"].pop(key)
+                    del metadata["scan_info"][key]
             epics_channels = replace_dict.values()
         except KeyError:
             epics_channels = []