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