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276 lines
7.6 KiB
276 lines
7.6 KiB
""" Stub file for testing the project """ |
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import numpy |
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import pytest |
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from .conftest import EXAMPLE_DIR_WO_PARAMS, EXAMPLE_DIR_WITH_PARAMS |
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@pytest.mark.parametrize( |
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"sub_dir, file_name", |
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[ |
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( |
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EXAMPLE_DIR_WO_PARAMS, |
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"160218_SG2-013-001_Regen1_Cy3-100_1_A1_1.csv", |
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), |
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( |
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EXAMPLE_DIR_WITH_PARAMS, |
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"160210_SG2-010-001_Regen_cy3100_1_A1_1.csv", |
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), |
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], |
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) |
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def test_parse_csv(example_dir, sub_dir, file_name): |
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from sensospot_data.parser import _parse_csv |
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result = _parse_csv(example_dir / sub_dir / file_name) |
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columns = { |
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" ID ": numpy.int64, |
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"Pos.X": numpy.int64, |
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"Pos.Y": numpy.int64, |
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"Bkg.Mean": float, |
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"Spot.Mean": float, |
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"Bkg.Median": float, |
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"Spot.Median": float, |
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"Bkg.StdDev": float, |
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"Spot.StdDev": float, |
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"Bkg.Sum": numpy.int64, |
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"Spot.Sum": numpy.int64, |
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"Bkg.Area": numpy.int64, |
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"Spot.Area": numpy.int64, |
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"Spot.Sat. (%)": numpy.int64, |
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"Found": numpy.bool_, |
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"Pos.Nom.X": numpy.int64, |
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"Pos.Nom.Y": numpy.int64, |
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"Dia.": numpy.int64, |
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"Rect.": str, |
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"Contour": object, # ignore the type of contour |
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} |
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assert set(result.columns) == set(columns.keys()) |
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assert len(result[" ID "].unique()) == 100 |
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assert len(result) == 100 |
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for column, value_type in columns.items(): |
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assert isinstance(result[column][0], value_type) |
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def test_parse_csv_no_array(example_dir): |
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from sensospot_data.parser import _parse_csv |
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result = _parse_csv(example_dir / "no_array_A1_1.csv") |
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assert len(result) == 1 |
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assert result[" ID "][0] == 0 |
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@pytest.mark.parametrize( |
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"input, expected", [("", "."), ("..,", "."), (".,,", ","), ("..,,", ".")] |
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) |
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def test_guess_decimal_separator_returns_correct_separator(input, expected): |
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from io import StringIO |
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from sensospot_data.parser import _guess_decimal_separator |
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handle = StringIO(f"header\n{input}\n") |
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result = _guess_decimal_separator(handle) |
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assert result == expected |
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def test_guess_decimal_separator_rewinds_handle(): |
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from io import StringIO |
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from sensospot_data.parser import _guess_decimal_separator |
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handle = StringIO("\n".join(["header", "data_line"])) |
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_guess_decimal_separator(handle) |
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assert next(handle) == "header\n" |
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def test_well_regex_ok(): |
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from sensospot_data.parser import REGEX_WELL |
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result = REGEX_WELL.match("AbC123") |
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assert result["row"] == "AbC" |
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assert result["column"] == "123" |
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@pytest.mark.parametrize("input", ["", "A", "1", "1A", "-1", "A-"]) |
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def test_well_regex_no_match(input): |
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from sensospot_data.parser import REGEX_WELL |
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result = REGEX_WELL.match(input) |
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assert result is None |
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@pytest.mark.parametrize( |
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"filename, expected", |
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[("A1_1.csv", ("A", 1, 1)), ("test/measurement_1_H12_2", ("H", 12, 2))], |
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) |
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def test_extract_measurement_info_ok(filename, expected): |
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from sensospot_data.parser import _extract_measurement_info |
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result = _extract_measurement_info(filename) |
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assert result == expected |
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@pytest.mark.parametrize("filename", ["wrong_exposure_A1_B", "no_well_XX_1"]) |
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def test_extract_measurement_info_raises_error(filename): |
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from sensospot_data.parser import _extract_measurement_info |
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with pytest.raises(ValueError): |
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_extract_measurement_info(filename) |
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def test_cleanup_data_columns(): |
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from pandas import DataFrame |
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from sensospot_data.parser import _cleanup_data_columns |
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columns = ["Rect.", "Contour", " ID ", "Found", "Dia."] |
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data = {col: [i] for i, col in enumerate(columns)} |
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data_frame = DataFrame(data=data) |
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result = _cleanup_data_columns(data_frame) |
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assert set(result.columns) == {"Pos.Id", "Spot.Found", "Spot.Diameter"} |
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assert result["Pos.Id"][0] == 2 |
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assert result["Spot.Found"][0] == 3 |
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assert result["Spot.Diameter"][0] == 4 |
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def test_parse_file(example_file): |
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from sensospot_data.parser import parse_file |
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result = parse_file(example_file) |
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columns = { |
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"Pos.Id", |
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"Pos.X", |
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"Pos.Y", |
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"Bkg.Mean", |
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"Spot.Mean", |
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"Bkg.Median", |
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"Spot.Median", |
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"Bkg.StdDev", |
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"Spot.StdDev", |
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"Bkg.Sum", |
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"Spot.Sum", |
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"Bkg.Area", |
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"Spot.Area", |
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"Spot.Saturation", |
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"Spot.Found", |
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"Pos.Nom.X", |
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"Pos.Nom.Y", |
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"Spot.Diameter", |
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"Well.Row", |
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"Well.Column", |
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"Exposure.Id", |
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} |
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assert set(result.columns) == columns |
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assert result["Well.Row"][0] == "A" |
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assert result["Well.Column"][0] == 1 |
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assert result["Exposure.Id"][0] == 1 |
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@pytest.mark.parametrize( |
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"file_list", |
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[ |
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[ |
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"160218_SG2-013-001_Regen1_Cy3-100_1_A1_1.csv", |
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"160218_SG2-013-001_Regen1_Cy3-100_1_A1_2.csv", |
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], |
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["160218_SG2-013-001_Regen1_Cy3-100_1_A1_1.csv"], |
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], |
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) |
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def testparse_multiple_files_ok(example_dir, file_list): |
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from sensospot_data.parser import parse_multiple_files |
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sub_dir = example_dir / EXAMPLE_DIR_WO_PARAMS |
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files = [sub_dir / file for file in file_list] |
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data_frame = parse_multiple_files(files) |
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print(data_frame["Exposure.Id"].unique()) |
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assert len(data_frame) == 100 * len(files) |
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assert len(data_frame["Exposure.Id"].unique()) == len(files) |
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def testparse_multiple_files_empty_file_list(): |
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from sensospot_data.parser import parse_multiple_files |
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with pytest.raises(ValueError): |
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parse_multiple_files([]) |
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def testparse_multiple_files_empty_array(example_dir): |
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from sensospot_data.parser import parse_multiple_files |
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files = [example_dir / "no_array_A1_1.csv"] |
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data_frame = parse_multiple_files(files) |
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print(data_frame["Exposure.Id"].unique()) |
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assert len(data_frame) == 1 |
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def test_list_csv_files(example_dir): |
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from sensospot_data.parser import list_csv_files |
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result = list(list_csv_files(example_dir / EXAMPLE_DIR_WITH_PARAMS)) |
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assert len(result) == 36 * 3 |
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assert all(str(item).endswith(".csv") for item in result) |
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assert all(not item.stem.startswith(".") for item in result) |
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def test_parse_folder(example_dir): |
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from sensospot_data.parser import parse_folder |
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data_frame = parse_folder(example_dir / EXAMPLE_DIR_WITH_PARAMS) |
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assert len(data_frame) == 36 * 3 * 100 |
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assert len(data_frame["Well.Row"].unique()) == 3 |
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assert len(data_frame["Well.Column"].unique()) == 12 |
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assert len(data_frame["Exposure.Id"].unique()) == 3 |
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assert len(data_frame["Pos.Id"].unique()) == 100 |
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assert len(data_frame["Parameters.Channel"].unique()) == 2 |
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assert len(data_frame["Parameters.Time"].unique()) == 3 |
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def test_sanity_check_ok(example_dir): |
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from sensospot_data.parser import _sanity_check, parse_multiple_files |
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sub_dir = example_dir / EXAMPLE_DIR_WO_PARAMS |
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file_list = [ |
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"160218_SG2-013-001_Regen1_Cy3-100_1_A1_1.csv", |
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"160218_SG2-013-001_Regen1_Cy3-100_1_A1_2.csv", |
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] |
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files = [sub_dir / file for file in file_list] |
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data_frame = parse_multiple_files(files) |
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result = _sanity_check(data_frame) |
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assert len(result) == len(data_frame) |
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def test_sanity_check_raises_value_error(example_dir): |
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from sensospot_data.parser import _sanity_check, parse_multiple_files |
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sub_dir = example_dir / EXAMPLE_DIR_WO_PARAMS |
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file_list = [ |
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"160218_SG2-013-001_Regen1_Cy3-100_1_A1_1.csv", |
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"160218_SG2-013-001_Regen1_Cy3-100_1_A1_2.csv", |
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] |
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files = [sub_dir / file for file in file_list] |
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data_frame = parse_multiple_files(files) |
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data_frame = data_frame.drop(data_frame.index[1]) |
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with pytest.raises(ValueError): |
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_sanity_check(data_frame)
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