You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
304 lines
8.5 KiB
304 lines
8.5 KiB
""" Stub file for testing the project """ |
|
|
|
|
|
import numpy |
|
import pytest |
|
|
|
from .conftest import EXAMPLE_DIR_CSV_WO_PARAMS, EXAMPLE_DIR_CSV_WITH_PARAMS |
|
|
|
|
|
@pytest.mark.parametrize( |
|
"sub_dir, file_name", |
|
[ |
|
( |
|
EXAMPLE_DIR_CSV_WO_PARAMS, |
|
"160218_SG2-013-001_Regen1_Cy3-100_1_A1_1.csv", |
|
), |
|
( |
|
EXAMPLE_DIR_CSV_WITH_PARAMS, |
|
"160210_SG2-010-001_Regen_cy3100_1_A1_1.csv", |
|
), |
|
], |
|
) |
|
def test_parse_csv(example_dir, sub_dir, file_name): |
|
from sensospot_parser.csv_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_parser.csv_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_parser.csv_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_parser.csv_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_parser.csv_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_parser.csv_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_parser.csv_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_parser.csv_parser import _extract_measurement_info |
|
|
|
with pytest.raises(ValueError): |
|
_extract_measurement_info(filename) |
|
|
|
|
|
def test_parse_file(example_file): |
|
from sensospot_parser.csv_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.Name", |
|
"Well.Row", |
|
"Well.Column", |
|
"Exposure.Id", |
|
"Analysis.Name", |
|
"Analysis.Image", |
|
} |
|
|
|
assert set(result.columns) == columns |
|
assert result["Well.Name"][0] == "A01" |
|
assert result["Well.Row"][0] == "A" |
|
assert result["Well.Column"][0] == 1 |
|
assert result["Exposure.Id"][0] == 1 |
|
assert result["Analysis.Name"][0] == "csv_wo_parameters" |
|
file_name = "160218_SG2-013-001_Regen1_Cy3-100_1_A1_1.tif" |
|
assert result["Analysis.Image"][0] == file_name |
|
|
|
|
|
def test_parse_file_raises_error(example_dir): |
|
from sensospot_parser.csv_parser import parse_file |
|
|
|
csv_file = ( |
|
example_dir |
|
/ EXAMPLE_DIR_CSV_WITH_PARAMS |
|
/ "should_raise_value_error.csv" |
|
) |
|
|
|
with pytest.raises(ValueError): |
|
parse_file(csv_file) |
|
|
|
|
|
def test_parse_file_silenced_returns_data_frame(example_file): |
|
from sensospot_parser.csv_parser import _parse_file_silenced |
|
|
|
result = _parse_file_silenced(example_file) |
|
|
|
assert result["Well.Row"][0] == "A" |
|
assert result["Well.Column"][0] == 1 |
|
assert result["Exposure.Id"][0] == 1 |
|
|
|
|
|
def test_parse_file_silenced_returns_none_on_error(example_dir): |
|
from sensospot_parser.csv_parser import _parse_file_silenced |
|
|
|
csv_file = ( |
|
example_dir |
|
/ EXAMPLE_DIR_CSV_WITH_PARAMS |
|
/ "should_raise_value_error.csv" |
|
) |
|
|
|
result = _parse_file_silenced(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_parser.csv_parser import parse_multiple_files |
|
|
|
sub_dir = example_dir / EXAMPLE_DIR_CSV_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_parser.csv_parser import parse_multiple_files |
|
|
|
with pytest.raises(ValueError): |
|
parse_multiple_files([]) |
|
|
|
|
|
def testparse_multiple_files_empty_array(example_dir): |
|
from sensospot_parser.csv_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_find_csv_files(example_dir): |
|
from sensospot_parser.csv_parser import find_csv_files |
|
|
|
result = list(find_csv_files(example_dir / EXAMPLE_DIR_CSV_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_no_datetime_records(example_dir): |
|
from sensospot_parser.csv_parser import parse_folder |
|
|
|
data_frame = parse_folder(example_dir / EXAMPLE_DIR_CSV_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 |
|
assert len(data_frame["Analysis.Datetime"].unique()) == 1 |
|
|
|
|
|
def test_sanity_check_ok(example_dir): |
|
from sensospot_parser.csv_parser import _sanity_check, parse_multiple_files |
|
|
|
sub_dir = example_dir / EXAMPLE_DIR_CSV_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_parser.csv_parser import _sanity_check, parse_multiple_files |
|
|
|
sub_dir = example_dir / EXAMPLE_DIR_CSV_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)
|
|
|