|
| 1 | +import netCDF4 as nc |
| 2 | +import numpy as np |
| 3 | +import pytest |
| 4 | + |
| 5 | +import iris |
| 6 | + |
| 7 | +NX, N_STRLEN = 3, 64 |
| 8 | +TEST_STRINGS = ["Münster", "London", "Amsterdam"] |
| 9 | +TEST_COORD_VALS = ["bun", "éclair", "sandwich"] |
| 10 | + |
| 11 | + |
| 12 | +def convert_chararray(string_array_1d, maxlen, encoding="utf-8"): |
| 13 | + bbytes = [text.encode(encoding) for text in string_array_1d] |
| 14 | + pad = b"\0" * maxlen |
| 15 | + bbytes = [(x + pad)[:maxlen] for x in bbytes] |
| 16 | + chararray = np.array([[bb[i : i + 1] for i in range(maxlen)] for bb in bbytes]) |
| 17 | + return chararray |
| 18 | + |
| 19 | + |
| 20 | +INCLUDE_COORD = True |
| 21 | +# INCLUDE_COORD = False |
| 22 | + |
| 23 | + |
| 24 | +def make_testfile(filepath, chararray, coordarray, encoding_str=None): |
| 25 | + with nc.Dataset(filepath, "w") as ds: |
| 26 | + ds.createDimension("x", NX) |
| 27 | + ds.createDimension("nstr", N_STRLEN) |
| 28 | + vx = ds.createVariable("x", int, dimensions=("x")) |
| 29 | + vx[:] = np.arange(NX) |
| 30 | + if INCLUDE_COORD: |
| 31 | + ds.createDimension("nstr2", N_STRLEN) |
| 32 | + v_co = ds.createVariable( |
| 33 | + "v_co", |
| 34 | + "S1", |
| 35 | + dimensions=( |
| 36 | + "x", |
| 37 | + "nstr2", |
| 38 | + ), |
| 39 | + ) |
| 40 | + v_co[:] = coordarray |
| 41 | + if encoding_str is not None: |
| 42 | + v_co._Encoding = encoding_str |
| 43 | + v = ds.createVariable( |
| 44 | + "v", |
| 45 | + "S1", |
| 46 | + dimensions=( |
| 47 | + "x", |
| 48 | + "nstr", |
| 49 | + ), |
| 50 | + ) |
| 51 | + v[:] = chararray |
| 52 | + if encoding_str is not None: |
| 53 | + v._Encoding = encoding_str |
| 54 | + if INCLUDE_COORD: |
| 55 | + v.coordinates = "v_co" |
| 56 | + |
| 57 | + |
| 58 | +def show_result(filepath): |
| 59 | + from pp_utils import ncdump |
| 60 | + |
| 61 | + print(f"File {filepath}") |
| 62 | + print("NCDUMP:") |
| 63 | + ncdump(filepath, "") |
| 64 | + # with nc.Dataset(filepath, "r") as ds: |
| 65 | + # v = ds.variables["v"] |
| 66 | + # print("\n----\nNetcdf data readback (basic)") |
| 67 | + # try: |
| 68 | + # print(repr(v[:])) |
| 69 | + # except UnicodeDecodeError as err: |
| 70 | + # print(repr(err)) |
| 71 | + # print("..raw:") |
| 72 | + # v.set_auto_chartostring(False) |
| 73 | + # print(repr(v[:])) |
| 74 | + print("\nAs iris cube..") |
| 75 | + try: |
| 76 | + cube = iris.load_cube(filepath) |
| 77 | + print(cube) |
| 78 | + if iris.loading.LOAD_PROBLEMS._problems: |
| 79 | + print(iris.loading.LOAD_PROBLEMS) |
| 80 | + print( |
| 81 | + "\n".join(iris.loading.LOAD_PROBLEMS._problems[0].stack_trace.format()) |
| 82 | + ) |
| 83 | + print("-data-") |
| 84 | + print(repr(cube.data)) |
| 85 | + if INCLUDE_COORD: |
| 86 | + print("-coord data-") |
| 87 | + try: |
| 88 | + print(repr(cube.coord("v_co").points)) |
| 89 | + except Exception as err2: |
| 90 | + print(repr(err2)) |
| 91 | + except UnicodeDecodeError as err: |
| 92 | + print(repr(err)) |
| 93 | + |
| 94 | + |
| 95 | +# tsts = (None, "ascii", "utf-8", "utf-32",) |
| 96 | +# tsts = ("utf-8",) |
| 97 | +# tsts = ("utf-8", "utf-32",) |
| 98 | +# tsts = ("utf-32",) |
| 99 | +tsts = ("utf-8", "ascii", "utf-8") |
| 100 | + |
| 101 | + |
| 102 | +@pytest.mark.parametrize("encoding", tsts) |
| 103 | +def test_encodings(encoding): |
| 104 | + print(f"\n=========\nTesting encoding: {encoding}") |
| 105 | + filepath = f"tmp_{str(encoding)}.nc" |
| 106 | + do_as = encoding |
| 107 | + if encoding != "utf-32": |
| 108 | + do_as = "utf-8" |
| 109 | + TEST_CHARARRAY = convert_chararray(TEST_STRINGS, N_STRLEN, encoding=do_as) |
| 110 | + TEST_COORDARRAY = convert_chararray(TEST_COORD_VALS, N_STRLEN, encoding=do_as) |
| 111 | + make_testfile(filepath, TEST_CHARARRAY, TEST_COORDARRAY, encoding_str=encoding) |
| 112 | + show_result(filepath) |
0 commit comments