diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 55ad1bb..372083c 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -33,7 +33,7 @@ repos: pass_filenames: false - id: flake8 name: flake8 test - entry: flake8 --ignore S101 tests + entry: flake8 --ignore S101,W503 tests language: system pass_filenames: false - id: pytest diff --git a/Makefile b/Makefile index 866a958..be53078 100644 --- a/Makefile +++ b/Makefile @@ -58,7 +58,7 @@ lint: ## reformat with black and check style with flake8 isort tests black src tests flake8 --ignore E231,W503,E402 src - flake8 --ignore S101 tests + flake8 --ignore S101,W503 tests test: lint ## run tests quickly, stop on first error pytest tests -x -l --last-failed --disable-warnings -m "not functional" diff --git a/README.md b/README.md index f2a7ee0..cd7a5fc 100644 --- a/README.md +++ b/README.md @@ -44,12 +44,16 @@ There is a `columns` module available, providing constans that define the column ## Avaliable public functions: - **parse_folder(path_to_folder)** + Tries the `parse_xml_folder()` function first and if an error occurs, + it falls back to the `parse_csv_folder()` + - **parse_xml_folder(path_to_folder)** + Searches the folder for a parsable Sensospot XML result file and parses it into + a pandas data frame. It will add additional meta data from parameters folder, + if it is present. + - **parse_csv_folder(path_to_folder)** Searches the folder for parsable Sensospot .csv files, parses them into one big pandas data frame and will add additional meta data from parameters folder, if it is present. -- **parse_file(path_to_csv_file)** - Parses a Sensospot csv file into a pandas data frame and will add some additional - meta data from the file name. Is internally also used by `parse_folder()` ## CLI @@ -63,8 +67,8 @@ Arguments: SOURCES: One or more folders with Sensospot measurements Options: - -o, --output FILE Output file path, defaults to 'collected_data.csv' - -q, --quiet Ignore Sanity Check + -o, --output FILE Output file path, defaults to 'collected_data.csv' + -q, --quiet Ignore sanity check for csv file parsing --help Show this message and exit. ``` diff --git a/example_data/mtp_with_parameters/160210_SG2-010-001_Regen_cy3100_1_A10_1.csv b/example_data/csv_with_parameters/160210_SG2-010-001_Regen_cy3100_1_A10_1.csv old mode 100755 new mode 100644 similarity index 100% rename from example_data/mtp_with_parameters/160210_SG2-010-001_Regen_cy3100_1_A10_1.csv rename to example_data/csv_with_parameters/160210_SG2-010-001_Regen_cy3100_1_A10_1.csv diff --git a/example_data/mtp_with_parameters/160210_SG2-010-001_Regen_cy3100_1_A10_2.csv b/example_data/csv_with_parameters/160210_SG2-010-001_Regen_cy3100_1_A10_2.csv old mode 100755 new mode 100644 similarity index 100% rename from example_data/mtp_with_parameters/160210_SG2-010-001_Regen_cy3100_1_A10_2.csv rename to example_data/csv_with_parameters/160210_SG2-010-001_Regen_cy3100_1_A10_2.csv diff --git a/example_data/mtp_with_parameters/160210_SG2-010-001_Regen_cy3100_1_A10_3.csv b/example_data/csv_with_parameters/160210_SG2-010-001_Regen_cy3100_1_A10_3.csv old mode 100755 new mode 100644 similarity index 100% rename from example_data/mtp_with_parameters/160210_SG2-010-001_Regen_cy3100_1_A10_3.csv rename to example_data/csv_with_parameters/160210_SG2-010-001_Regen_cy3100_1_A10_3.csv diff --git a/example_data/mtp_with_parameters/160210_SG2-010-001_Regen_cy3100_1_A11_1.csv b/example_data/csv_with_parameters/160210_SG2-010-001_Regen_cy3100_1_A11_1.csv old mode 100755 new mode 100644 similarity index 100% rename from example_data/mtp_with_parameters/160210_SG2-010-001_Regen_cy3100_1_A11_1.csv rename to 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a/src/sensospot_parser/__init__.py b/src/sensospot_parser/__init__.py index 8124da2..9a8cf36 100644 --- a/src/sensospot_parser/__init__.py +++ b/src/sensospot_parser/__init__.py @@ -3,19 +3,43 @@ Parsing the numerical output from Sensovations Sensospot image analysis. """ -__version__ = "1.0.1" +__version__ = "2.0.0" import pathlib +from typing import Union import click import pandas from . import columns # noqa: F401 -from .parser import parse_file, parse_folder # noqa: F401 +from .csv_parser import parse_csv_folder +from .xml_parser import parse_xml_folder DEFAULT_OUTPUT_FILENAME = "collected_data.csv" +PathLike = Union[str, pathlib.Path] + + +def parse_folder(source: PathLike, quiet: bool = False) -> pandas.DataFrame: + """parses an assay result folder + + The function will first try to use an assay results xml file, and will + fall back to parsing csv files if the xml file could not be parsed. + + Args: + folder: path of folder containing the assay result + quiet: skip sanity check for csv files, defaults to False + + Returns: + a pandas data frame with parsed data + """ + try: + return parse_xml_folder(source) + except ValueError: + pass + return parse_csv_folder(source, quiet) + @click.command() @click.argument( @@ -42,18 +66,22 @@ DEFAULT_OUTPUT_FILENAME = "collected_data.csv" "--quiet", is_flag=True, default=False, - help="Ignore Sanity Check", + help="Ignore sanity check for csv file parsing", ) def main(sources, output, quiet=False): """Parses the measurement results of the Sensospot reader The resulting output is either echoed to stdout or saved to a file. + At first parsing the assay result xml file is tried. + I this doesn't work, the fallback is to parse the csv files. """ paths = (pathlib.Path(source) for source in sources) collection = (parse_folder(source, quiet) for source in paths) - result = pandas.concat(collection, ignore_index=True).to_csv( - output, sep="\t", index=False + result = ( + pandas.concat(collection, ignore_index=True) + .reset_index() + .to_csv(output, sep="\t", index=False) ) # if 'output' is None, the call to 'to_csv()' returns the csv as text # if 'output' is not None, 'to_csv()' writes to the file and returns None diff --git a/src/sensospot_parser/columns.py b/src/sensospot_parser/columns.py index 9897d32..5d4391e 100644 --- a/src/sensospot_parser/columns.py +++ b/src/sensospot_parser/columns.py @@ -1,5 +1,7 @@ """ Column name definitions """ +import pandas + # original, unmodified column names POS_X = "Pos.X" POS_Y = "Pos.Y" @@ -121,3 +123,17 @@ INDEX_COLUMNS_POS = ( WELL_ROW, POS_ID, ) + + +def _cleanup_data_columns(data_frame: pandas.DataFrame) -> pandas.DataFrame: + """renames some data columns for consistency and drops unused columns + + Args: + data_frame: pandas DataFrame with parsed measurement data + + Returns: + pandas DataFrame, column names cleaned up + """ + renamed = data_frame.rename(columns=CSV_RENAME_MAP) + surplus_columns = set(renamed.columns) - PARSED_DATA_COLUMN_SET + return renamed.drop(columns=surplus_columns) diff --git a/src/sensospot_parser/parser.py b/src/sensospot_parser/csv_parser.py similarity index 84% rename from src/sensospot_parser/parser.py rename to src/sensospot_parser/csv_parser.py index 73f0656..267bfea 100644 --- a/src/sensospot_parser/parser.py +++ b/src/sensospot_parser/csv_parser.py @@ -1,6 +1,6 @@ """ Sensospot Data Parser -Parsing the numerical output from Sensovations Sensospot image analysis. +Parsing the csv result files from Sensovations Sensospot image analysis. """ import re @@ -12,7 +12,6 @@ import pandas from . import columns from .parameters import add_measurement_parameters -from .recordtime import add_record_time PathLike = Union[str, pathlib.Path] @@ -85,21 +84,7 @@ def _extract_measurement_info(data_file: PathLike) -> FileInfo: return FileInfo(row, column, exposure) -def _cleanup_data_columns(data_frame: pandas.DataFrame) -> pandas.DataFrame: - """renames some data columns for consistency and drops unused columns - - Args: - data_frame: pandas DataFrame with parsed measurement data - - Returns: - pandas DataFrame, column names cleaned up - """ - renamed = data_frame.rename(columns=columns.CSV_RENAME_MAP) - surplus_columns = set(renamed.columns) - columns.PARSED_DATA_COLUMN_SET - return renamed.drop(columns=surplus_columns) - - -def parse_file(data_file: PathLike) -> pandas.DataFrame: +def parse_csv_file(data_file: PathLike) -> pandas.DataFrame: """parses one data file and adds metadata to result will race a ValueError, if metadata could not be extracted @@ -125,10 +110,12 @@ def parse_file(data_file: PathLike) -> pandas.DataFrame: data_frame[columns.EXPOSURE_ID] = measurement_info.exposure data_frame[columns.ANALYSIS_NAME] = data_path.parent.name data_frame[columns.ANALYSIS_IMAGE] = data_path.with_suffix(".tif").name - return _cleanup_data_columns(data_frame) + return columns._cleanup_data_columns(data_frame) -def _parse_file_silenced(data_file: PathLike) -> Optional[pandas.DataFrame]: +def _parse_csv_file_silenced( + data_file: PathLike, +) -> Optional[pandas.DataFrame]: """parses one data file and adds metadata Safety checks are supressed @@ -140,12 +127,14 @@ def _parse_file_silenced(data_file: PathLike) -> Optional[pandas.DataFrame]: pandas data frame with the parsed data or None on error """ try: - return parse_file(data_file) + return parse_csv_file(data_file) except ValueError: return None -def parse_multiple_files(file_list: Sequence[PathLike]) -> pandas.DataFrame: +def parse_multiple_csv_files( + file_list: Sequence[PathLike], +) -> pandas.DataFrame: """parses a list of file paths to one combined data frame Args: @@ -155,7 +144,7 @@ def parse_multiple_files(file_list: Sequence[PathLike]) -> pandas.DataFrame: """ if not file_list: raise ValueError("Empty file list provided") - collection = (_parse_file_silenced(path) for path in file_list) + collection = (_parse_csv_file_silenced(path) for path in file_list) filtered = (frame for frame in collection if frame is not None) data_frame = pandas.concat(filtered, ignore_index=True).reset_index() data_frame[columns.WELL_ROW] = data_frame[columns.WELL_ROW].astype( @@ -206,7 +195,9 @@ def _sanity_check(data_frame: pandas.DataFrame) -> pandas.DataFrame: return data_frame -def parse_folder(folder: PathLike, quiet: bool = False) -> pandas.DataFrame: +def parse_csv_folder( + folder: PathLike, quiet: bool = False +) -> pandas.DataFrame: """parses all csv files in a folder to one large dataframe Will raise an ValueError, if no sensospot data could be found in @@ -222,11 +213,18 @@ def parse_folder(folder: PathLike, quiet: bool = False) -> pandas.DataFrame: folder_path = pathlib.Path(folder) file_list = find_csv_files(folder_path) try: - data_frame = parse_multiple_files(file_list) + data_frame = parse_multiple_csv_files(file_list) except ValueError: raise ValueError(f"No sensospot data found in folder '{folder}'") + data_frame = add_measurement_parameters(data_frame, folder_path) - data_frame = add_record_time(data_frame, folder_path) + + # The csv parser is only used if the xml analysis file is not present + # the xml file would hold the Analysis.Datetime value + data_frame[columns.ANALYSIS_DATETIME] = None + + data_frame = columns._cleanup_data_columns(data_frame) + if quiet: return data_frame return _sanity_check(data_frame) diff --git a/src/sensospot_parser/recordtime.py b/src/sensospot_parser/recordtime.py deleted file mode 100644 index 6bda6c8..0000000 --- a/src/sensospot_parser/recordtime.py +++ /dev/null @@ -1,98 +0,0 @@ -""" Sensospot Data Parser - -Parsing the numerical output from Sensovations Sensospot image analysis. -""" - -import pathlib -from typing import Tuple, Union, Iterable, Optional - -import numpy -import pandas -from defusedxml import ElementTree - -from . import columns - -PathLike = Union[str, pathlib.Path] - - -def _search_records_file(folder: PathLike) -> Optional[pathlib.Path]: - """searches for a the records xml file in a folder - - Args: - folder: directory to search - - Returns: - the path to the settings file or None - """ - folder_path = pathlib.Path(folder) - files = (item for item in folder_path.iterdir() if item.suffix == ".xsl") - xls_files = [path for path in files if not path.name.startswith(".")] - if len(xls_files) == 1: - xml_file = xls_files[0].with_suffix(".xml") - if xml_file.is_file(): - return xml_file - return None - - -def _iter_records(records_file: PathLike) -> Iterable[Tuple[str, str]]: - """parses the information from a records file - - Args: - records_file: path to the records file - - Yields: - tuples, filename as first element and the datetime string as second - """ - records_path = pathlib.Path(records_file) - tree = ElementTree.parse(records_path) - for channel_config in tree.findall(".//*[ImageFileName]"): - image_tag = channel_config.find("ImageFileName") - image_name = None if image_tag is None else image_tag.text - datetime_tag = channel_config.find("Timestamp") - datetime_str = None if datetime_tag is None else datetime_tag.text - yield image_name, datetime_str - - -def _parse_records_file(records_file: PathLike) -> pandas.DataFrame: - """parses the information from a records file - - Args: - records_file: path to the records file - - Returns: - pandas data frame with the parsed information - """ - data = _iter_records(records_file) - data_frame = pandas.DataFrame( - data, columns=[columns.ANALYSIS_IMAGE, columns.ANALYSIS_DATETIME] - ) - data_frame[columns.ANALYSIS_DATETIME] = pandas.to_datetime( - data_frame[columns.ANALYSIS_DATETIME] - ) - return data_frame - - -def add_record_time( - measurement: pandas.DataFrame, folder: PathLike -) -> pandas.DataFrame: - """adds the recoding datetime to the data frame - - The returned DataFrame will contain one more column for parsed datetime - - If the parameters could not be foundor do not match up with the - measurement data, the additional collumn will contain NaN. - - Argumentss: - measurement: the parsed measurement data - folder: the folder of the measurement data - - Returns: - the measurement data with parameters added - """ - record_path = _search_records_file(folder) - if record_path is None: - measurement[columns.ANALYSIS_DATETIME] = numpy.NAN - return measurement - - data_frame = _parse_records_file(record_path) - return measurement.merge(data_frame, how="left", on=columns.ANALYSIS_IMAGE) diff --git a/src/sensospot_parser/xml_parser.py b/src/sensospot_parser/xml_parser.py new file mode 100644 index 0000000..d097944 --- /dev/null +++ b/src/sensospot_parser/xml_parser.py @@ -0,0 +1,192 @@ +""" Sensospot Data Parser + +Parsing the csv result files from Sensovations Sensospot image analysis. +""" + +import pathlib +from typing import Union, Optional +from datetime import datetime + +import pandas +from defusedxml import ElementTree + +from . import columns, parameters + +PathLike = Union[str, pathlib.Path] + +RESULT_TAG_TYPES = { + "System.Int32": int, + "System.UInt32": int, + "System.Double": float, + "System.Boolean": lambda x: x.lower() == "true", +} + +DATETIME_XML_FORMAT = "%m/%d/%Y %I:%M:%S %p" + + +class ParserTarget: + """Class to parse the event stream emitted by ElementTree.XMLParser + + The methods "start()", "data()", "end()" and "close()" are defined + according to the requirements of the ElementTree.XMLParser + """ + + def __init__(self): + """initialization of the object instance""" + self.collected = [] + self._current = {} + self._data_func = None + + def start(self, tag: str, attributes: dict[str:str]) -> None: + """start of an xml tag + + The sensovation software uses sometimes the attributes of a tag to + store relevant data and sometimes the data part of the xml tree. + + This methods extracts the data from the attributes or preparse the + parsing of the data section + + Args: + tag: the name of the tag + attributes: the attributes of the tag as a dict + """ + if tag == "ScanJobResult": + self._current[columns.ANALYSIS_NAME] = attributes["ID"] + elif tag == "AssayResult": + well = attributes["ID"] + self._current[columns.WELL_NAME] = attributes["ID"] + self._current[columns.WELL_ROW] = well[0] + self._current[columns.WELL_COLUMN] = int(well[1:]) + elif tag.startswith("ChannelConfig"): + self._current[columns.EXPOSURE_ID] = int(tag[13:]) + elif tag == "Spot": + self._current[columns.POS_ID] = int(attributes["ID"]) + elif tag == "Result": + self._result_attributes_parser(attributes) + elif tag == "Timestamp": + self._data_func = self._data_timestamp_parser + elif tag == "ImageFileName": + self._data_func = self._data_image_name_parser + + def _result_attributes_parser(self, data: dict[str:str]) -> None: + """parses the attributes of the "Result" tag""" + label = data["Label"] + converter = RESULT_TAG_TYPES.get(data["Type"], str) + self._current[label] = converter(data["Value"]) + + def _data_timestamp_parser(self, data: str) -> None: + """parses the data section of a "Timestamp" tag""" + timestamp = datetime.strptime(data.strip(), DATETIME_XML_FORMAT) + self._current[columns.ANALYSIS_DATETIME] = timestamp + + def _data_image_name_parser(self, data: str) -> None: + """parses the data section of a "ImageFileName" tag""" + self._current[columns.ANALYSIS_IMAGE] = data.strip() + + def data(self, data: str) -> None: + """parses the data section of the xml tree + + The data sections in the xml tree of the sensovation software are + not often used. + + The "start()" method sets a parser for the upcoming data section and + this parser is removed after it was called. + """ + if self._data_func: + self._data_func(data) + self._data_func = None + + def end(self, tag: str) -> None: + """the end of a tag is reached + + If it is the end of a "Spot" tag, a copy of the current data is added + to the collected data property. + """ + if tag == "Spot": + spot_data = dict(self._current) + self.collected.append(spot_data) + + def closed(self) -> None: + """the end of the xml file is reached""" + pass + + +def _find_result_xml_file(folder: PathLike) -> Optional[pathlib.Path]: + """searches a results folder for the analysis xml file + + There may be multiple xml files in the folder, but only one xsl file with + the same (base) name as the xml file we are looking for. This is why we + first look for the xsl file and then derive the path from the xml file + from it. + + Args: + folder: path of folder containing data files + + Returns: + Path to xml assay result file or None if it could not be found + """ + source = pathlib.Path(folder) + files = (i for i in source.iterdir() if i.is_file()) + not_hidden = (f for f in files if not f.name.startswith(".")) + xsl_files = [f for f in not_hidden if f.suffix == ".xsl"] + if len(xsl_files) != 1: + # multiple xsl files in a folder + # this does not to be a "normal" results folder + return None + xsl_file = xsl_files[0] + xml_file = xsl_file.with_suffix(".xml") + return xml_file if xml_file.is_file() else None + + +def parse_xml_file(xml_file: PathLike) -> pandas.DataFrame: + """parses an assay result xml file into a pandas data frame + + Will raise a ValueError on a non-parsable xml file. + + Args: + xml_file: path to the xml file + + Returns: + A pandas DataFrame with the parsed data + + Raises: + ValueError if the xml file could not be parsed + """ + xml_file = pathlib.Path(xml_file) + if not xml_file.is_file(): + raise ValueError("Xml file does not exist") + + target = ParserTarget() + parser = ElementTree.DefusedXMLParser(target=target) + + try: + parser.feed(xml_file.read_text()) + except (IndexError, KeyError, ValueError, TypeError) as e: + raise ValueError("Malformed data in xml file") from e + + data_frame = pandas.DataFrame(data=target.collected).reset_index() + if data_frame.empty: + raise ValueError("Could not parse assay results xml file") + + return columns._cleanup_data_columns(data_frame) + + +def parse_xml_folder(folder: PathLike) -> pandas.DataFrame: + """parses the xml result file in a folder to one large dataframe + + Will raise an ValueError, if no sensospot data could be found in + the folder + + Args: + folder: path of folder containing data files + + Returns: + a pandas data frame with parsed data + """ + folder = pathlib.Path(folder) + xml_file = _find_result_xml_file(folder) + if xml_file is None: + raise ValueError("Could not find assay results xml file") + data_frame = parse_xml_file(xml_file) + data_frame = parameters.add_measurement_parameters(data_frame, folder) + return columns._cleanup_data_columns(data_frame) diff --git a/tests/conftest.py b/tests/conftest.py index 19d2ce6..3c575a1 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -5,9 +5,10 @@ from pathlib import Path import pandas import pytest -EXAMPLE_DIR_WO_PARAMS = "mtp_wo_parameters" -EXAMPLE_DIR_WITH_PARAMS = "mtp_with_parameters" -EXAMPLE_DIR_WITH_RECORD = "record_time" +EXAMPLE_DIR_CSV_WO_PARAMS = "csv_wo_parameters" +EXAMPLE_DIR_CSV_WITH_PARAMS = "csv_with_parameters" +EXAMPLE_DIR_XML_WO_PARAMS = "xml_wo_parameters" +EXAMPLE_DIR_XML_WITH_PARAMS = "xml_with_parameters" @pytest.fixture(scope="session") @@ -18,7 +19,7 @@ def example_dir(request): @pytest.fixture def example_file(example_dir): - data_dir = example_dir / EXAMPLE_DIR_WO_PARAMS + data_dir = example_dir / EXAMPLE_DIR_CSV_WO_PARAMS yield data_dir / "160218_SG2-013-001_Regen1_Cy3-100_1_A1_1.csv" @@ -93,16 +94,16 @@ def normalization_data_frame(): @pytest.fixture(scope="session") def parsed_data_frame_with_params(example_dir): - from sensospot_parser.parser import parse_folder + from sensospot_parser.csv_parser import parse_csv_folder - return parse_folder(example_dir / EXAMPLE_DIR_WITH_PARAMS) + return parse_csv_folder(example_dir / EXAMPLE_DIR_CSV_WITH_PARAMS) @pytest.fixture(scope="session") def parsed_data_frame_without_params(example_dir): - from sensospot_parser.parser import parse_folder + from sensospot_parser.csv_parser import parse_csv_folder - return parse_folder(example_dir / EXAMPLE_DIR_WO_PARAMS) + return parse_csv_folder(example_dir / EXAMPLE_DIR_CSV_WO_PARAMS) @pytest.fixture diff --git a/tests/test_columns.py b/tests/test_columns.py new file mode 100644 index 0000000..499c221 --- /dev/null +++ b/tests/test_columns.py @@ -0,0 +1,15 @@ +def test_cleanup_data_columns(): + from pandas import DataFrame + + from sensospot_parser.columns 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 diff --git a/tests/test_parser.py b/tests/test_csv_parser.py similarity index 65% rename from tests/test_parser.py rename to tests/test_csv_parser.py index c9659b1..371bf7f 100644 --- a/tests/test_parser.py +++ b/tests/test_csv_parser.py @@ -4,28 +4,24 @@ import numpy import pytest -from .conftest import ( - EXAMPLE_DIR_WO_PARAMS, - EXAMPLE_DIR_WITH_PARAMS, - EXAMPLE_DIR_WITH_RECORD, -) +from .conftest import EXAMPLE_DIR_CSV_WO_PARAMS, EXAMPLE_DIR_CSV_WITH_PARAMS @pytest.mark.parametrize( "sub_dir, file_name", [ ( - EXAMPLE_DIR_WO_PARAMS, + EXAMPLE_DIR_CSV_WO_PARAMS, "160218_SG2-013-001_Regen1_Cy3-100_1_A1_1.csv", ), ( - EXAMPLE_DIR_WITH_PARAMS, + 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.parser import _parse_csv + from sensospot_parser.csv_parser import _parse_csv result = _parse_csv(example_dir / sub_dir / file_name) @@ -60,7 +56,7 @@ def test_parse_csv(example_dir, sub_dir, file_name): def test_parse_csv_no_array(example_dir): - from sensospot_parser.parser import _parse_csv + from sensospot_parser.csv_parser import _parse_csv result = _parse_csv(example_dir / "no_array_A1_1.csv") @@ -74,7 +70,7 @@ def test_parse_csv_no_array(example_dir): def test_guess_decimal_separator_returns_correct_separator(input, expected): from io import StringIO - from sensospot_parser.parser import _guess_decimal_separator + from sensospot_parser.csv_parser import _guess_decimal_separator handle = StringIO(f"header\n{input}\n") result = _guess_decimal_separator(handle) @@ -85,7 +81,7 @@ def test_guess_decimal_separator_returns_correct_separator(input, expected): def test_guess_decimal_separator_rewinds_handle(): from io import StringIO - from sensospot_parser.parser import _guess_decimal_separator + from sensospot_parser.csv_parser import _guess_decimal_separator handle = StringIO("\n".join(["header", "data_line"])) _guess_decimal_separator(handle) @@ -94,7 +90,7 @@ def test_guess_decimal_separator_rewinds_handle(): def test_well_regex_ok(): - from sensospot_parser.parser import REGEX_WELL + from sensospot_parser.csv_parser import REGEX_WELL result = REGEX_WELL.match("AbC123") @@ -104,7 +100,7 @@ def test_well_regex_ok(): @pytest.mark.parametrize("input", ["", "A", "1", "1A", "-1", "A-"]) def test_well_regex_no_match(input): - from sensospot_parser.parser import REGEX_WELL + from sensospot_parser.csv_parser import REGEX_WELL result = REGEX_WELL.match(input) @@ -116,7 +112,7 @@ def test_well_regex_no_match(input): [("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.parser import _extract_measurement_info + from sensospot_parser.csv_parser import _extract_measurement_info result = _extract_measurement_info(filename) @@ -125,33 +121,16 @@ def test_extract_measurement_info_ok(filename, expected): @pytest.mark.parametrize("filename", ["wrong_exposure_A1_B", "no_well_XX_1"]) def test_extract_measurement_info_raises_error(filename): - from sensospot_parser.parser import _extract_measurement_info + from sensospot_parser.csv_parser import _extract_measurement_info with pytest.raises(ValueError): _extract_measurement_info(filename) -def test_cleanup_data_columns(): - from pandas import DataFrame - - from sensospot_parser.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_parser.parser import parse_file + from sensospot_parser.csv_parser import parse_csv_file - result = parse_file(example_file) + result = parse_csv_file(example_file) columns = { "Pos.Id", @@ -185,26 +164,28 @@ def test_parse_file(example_file): assert result["Well.Row"][0] == "A" assert result["Well.Column"][0] == 1 assert result["Exposure.Id"][0] == 1 - assert result["Analysis.Name"][0] == "mtp_wo_parameters" + 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.parser import parse_file + from sensospot_parser.csv_parser import parse_csv_file csv_file = ( - example_dir / EXAMPLE_DIR_WITH_PARAMS / "should_raise_value_error.csv" + example_dir + / EXAMPLE_DIR_CSV_WITH_PARAMS + / "should_raise_value_error.csv" ) with pytest.raises(ValueError): - parse_file(csv_file) + parse_csv_file(csv_file) def test_parse_file_silenced_returns_data_frame(example_file): - from sensospot_parser.parser import _parse_file_silenced + from sensospot_parser.csv_parser import _parse_csv_file_silenced - result = _parse_file_silenced(example_file) + result = _parse_csv_file_silenced(example_file) assert result["Well.Row"][0] == "A" assert result["Well.Column"][0] == 1 @@ -212,13 +193,15 @@ def test_parse_file_silenced_returns_data_frame(example_file): def test_parse_file_silenced_returns_none_on_error(example_dir): - from sensospot_parser.parser import _parse_file_silenced + from sensospot_parser.csv_parser import _parse_csv_file_silenced csv_file = ( - example_dir / EXAMPLE_DIR_WITH_PARAMS / "should_raise_value_error.csv" + example_dir + / EXAMPLE_DIR_CSV_WITH_PARAMS + / "should_raise_value_error.csv" ) - result = _parse_file_silenced(csv_file) + result = _parse_csv_file_silenced(csv_file) assert result is None @@ -234,12 +217,12 @@ def test_parse_file_silenced_returns_none_on_error(example_dir): ], ) def testparse_multiple_files_ok(example_dir, file_list): - from sensospot_parser.parser import parse_multiple_files + from sensospot_parser.csv_parser import parse_multiple_csv_files - sub_dir = example_dir / EXAMPLE_DIR_WO_PARAMS + sub_dir = example_dir / EXAMPLE_DIR_CSV_WO_PARAMS files = [sub_dir / file for file in file_list] - data_frame = parse_multiple_files(files) + data_frame = parse_multiple_csv_files(files) print(data_frame["Exposure.Id"].unique()) assert len(data_frame) == 100 * len(files) @@ -247,27 +230,27 @@ def testparse_multiple_files_ok(example_dir, file_list): def testparse_multiple_files_empty_file_list(): - from sensospot_parser.parser import parse_multiple_files + from sensospot_parser.csv_parser import parse_multiple_csv_files with pytest.raises(ValueError): - parse_multiple_files([]) + parse_multiple_csv_files([]) def testparse_multiple_files_empty_array(example_dir): - from sensospot_parser.parser import parse_multiple_files + from sensospot_parser.csv_parser import parse_multiple_csv_files files = [example_dir / "no_array_A1_1.csv"] - data_frame = parse_multiple_files(files) + data_frame = parse_multiple_csv_files(files) print(data_frame["Exposure.Id"].unique()) assert len(data_frame) == 1 def test_find_csv_files(example_dir): - from sensospot_parser.parser import find_csv_files + from sensospot_parser.csv_parser import find_csv_files - result = list(find_csv_files(example_dir / EXAMPLE_DIR_WITH_PARAMS)) + 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) @@ -275,9 +258,9 @@ def test_find_csv_files(example_dir): def test_parse_folder_no_datetime_records(example_dir): - from sensospot_parser.parser import parse_folder + from sensospot_parser.csv_parser import parse_csv_folder - data_frame = parse_folder(example_dir / EXAMPLE_DIR_WITH_PARAMS) + data_frame = parse_csv_folder(example_dir / EXAMPLE_DIR_CSV_WITH_PARAMS) assert len(data_frame) == 36 * 3 * 100 assert len(data_frame["Well.Row"].unique()) == 3 @@ -289,31 +272,19 @@ def test_parse_folder_no_datetime_records(example_dir): assert len(data_frame["Analysis.Datetime"].unique()) == 1 -def test_parse_folder_with_datetime_records(example_dir): - from sensospot_parser.parser import parse_folder - - data_frame = parse_folder(example_dir / EXAMPLE_DIR_WITH_RECORD) - - assert len(data_frame) == 8 * 4 * 100 - assert len(data_frame["Well.Row"].unique()) == 2 - assert len(data_frame["Well.Column"].unique()) == 4 - assert len(data_frame["Exposure.Id"].unique()) == 4 - assert len(data_frame["Pos.Id"].unique()) == 100 - assert len(data_frame["Parameters.Channel"].unique()) == 1 - assert len(data_frame["Parameters.Time"].unique()) == 1 - assert len(data_frame["Analysis.Datetime"].unique()) == 8 - - def test_sanity_check_ok(example_dir): - from sensospot_parser.parser import _sanity_check, parse_multiple_files + from sensospot_parser.csv_parser import ( + _sanity_check, + parse_multiple_csv_files, + ) - sub_dir = example_dir / EXAMPLE_DIR_WO_PARAMS + 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 = parse_multiple_csv_files(files) result = _sanity_check(data_frame) @@ -321,15 +292,18 @@ def test_sanity_check_ok(example_dir): def test_sanity_check_raises_value_error(example_dir): - from sensospot_parser.parser import _sanity_check, parse_multiple_files + from sensospot_parser.csv_parser import ( + _sanity_check, + parse_multiple_csv_files, + ) - sub_dir = example_dir / EXAMPLE_DIR_WO_PARAMS + 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 = parse_multiple_csv_files(files) data_frame = data_frame.drop(data_frame.index[1]) with pytest.raises(ValueError): diff --git a/tests/test_parameters.py b/tests/test_parameters.py index b91fd92..ea291e4 100644 --- a/tests/test_parameters.py +++ b/tests/test_parameters.py @@ -1,12 +1,12 @@ import pandas -from .conftest import EXAMPLE_DIR_WO_PARAMS, EXAMPLE_DIR_WITH_PARAMS +from .conftest import EXAMPLE_DIR_CSV_WO_PARAMS, EXAMPLE_DIR_CSV_WITH_PARAMS def test_search_params_file_ok(example_dir): from sensospot_parser.parameters import _search_params_file - result = _search_params_file(example_dir / EXAMPLE_DIR_WITH_PARAMS) + result = _search_params_file(example_dir / EXAMPLE_DIR_CSV_WITH_PARAMS) assert result.suffix == ".svexp" @@ -14,7 +14,7 @@ def test_search_params_file_ok(example_dir): def test_search_params_file_no_parameters_folder(example_dir): from sensospot_parser.parameters import _search_params_file - result = _search_params_file(example_dir / EXAMPLE_DIR_WO_PARAMS) + result = _search_params_file(example_dir / EXAMPLE_DIR_CSV_WO_PARAMS) assert result is None @@ -36,7 +36,7 @@ def test_parse_channel_info(example_dir): _parse_measurement_params, ) - params = _search_params_file(example_dir / EXAMPLE_DIR_WITH_PARAMS) + params = _search_params_file(example_dir / EXAMPLE_DIR_CSV_WITH_PARAMS) result = _parse_measurement_params(params) expected = pandas.DataFrame( @@ -53,7 +53,7 @@ def test_parse_channel_info(example_dir): def test_get_measurement_params_file_found(example_dir): from sensospot_parser.parameters import get_measurement_params - result = get_measurement_params(example_dir / EXAMPLE_DIR_WITH_PARAMS) + result = get_measurement_params(example_dir / EXAMPLE_DIR_CSV_WITH_PARAMS) expected = pandas.DataFrame( { @@ -69,7 +69,7 @@ def test_get_measurement_params_file_found(example_dir): def test_get_measurement_params_file_not_found(example_dir): from sensospot_parser.parameters import get_measurement_params - result = get_measurement_params(example_dir / EXAMPLE_DIR_WO_PARAMS) + result = get_measurement_params(example_dir / EXAMPLE_DIR_CSV_WO_PARAMS) assert result is None @@ -77,7 +77,7 @@ def test_get_measurement_params_file_not_found(example_dir): def test_add_measurement_parameters_with_params_file(exposure_df, example_dir): from sensospot_parser.parameters import add_measurement_parameters - folder = example_dir / EXAMPLE_DIR_WITH_PARAMS + folder = example_dir / EXAMPLE_DIR_CSV_WITH_PARAMS exposure_df = add_measurement_parameters(exposure_df, folder) expected = [(1, "green", 100), (2, "red", 150), (3, "red", 15)] @@ -93,7 +93,7 @@ def test_add_measurement_parameters_without_params_file( ): from sensospot_parser.parameters import add_measurement_parameters - folder = example_dir / EXAMPLE_DIR_WO_PARAMS + folder = example_dir / EXAMPLE_DIR_CSV_WO_PARAMS exposure_df = add_measurement_parameters(exposure_df, folder) for exposure_id in range(1, 4): diff --git a/tests/test_recordtime.py b/tests/test_recordtime.py deleted file mode 100644 index 6a998da..0000000 --- a/tests/test_recordtime.py +++ /dev/null @@ -1,98 +0,0 @@ -import pandas -import pytest - -from .conftest import EXAMPLE_DIR_WITH_PARAMS, EXAMPLE_DIR_WITH_RECORD - - -@pytest.fixture -def file_list(example_dir): - import pathlib - - path = pathlib.Path(example_dir / EXAMPLE_DIR_WITH_RECORD) - tifs = (i.with_suffix(".tif") for i in path.glob("*.csv")) - return [i.name for i in tifs] - - -def test_search_records_file_ok(example_dir): - from sensospot_parser.recordtime import _search_records_file - - result = _search_records_file(example_dir / EXAMPLE_DIR_WITH_RECORD) - - assert result.suffix == ".xml" - - -def test_search_records_file_not_found(example_dir): - from sensospot_parser.recordtime import _search_records_file - - result = _search_records_file(example_dir / EXAMPLE_DIR_WITH_PARAMS) - - assert result is None - - -def test_iter_records(example_dir): - from sensospot_parser.recordtime import _iter_records, _search_records_file - - path = _search_records_file(example_dir / EXAMPLE_DIR_WITH_RECORD) - - result = list(_iter_records(path)) - - assert ( - result[0][0] == "220307_SN0801_CHECK-01_SL1,11,9,14_MS_1_1_A01_1.tif" - ) - assert result[0][1] == "3/7/2022 5:31:47 PM" - assert ( - result[-1][0] == "220307_SN0801_CHECK-01_SL1,11,9,14_MS_1_1_D04_4.tif" - ) - assert result[-1][1] == "3/7/2022 5:33:41 PM" - - -def test_parse_records_file(example_dir): - from sensospot_parser.recordtime import ( - _parse_records_file, - _search_records_file, - ) - - path = _search_records_file(example_dir / EXAMPLE_DIR_WITH_RECORD) - - result = _parse_records_file(path) - - assert isinstance(result, pandas.DataFrame) - assert list(result.columns) == ["Analysis.Image", "Analysis.Datetime"] - assert len(result) == 64 - - -def test_add_record_time_ok(example_dir, file_list): - from sensospot_parser.recordtime import add_record_time - - df = pandas.DataFrame(file_list, columns=["Analysis.Image"]) - - result = add_record_time(df, example_dir / EXAMPLE_DIR_WITH_RECORD) - - assert len(df) == len(result) - assert list(result.columns) == ["Analysis.Image", "Analysis.Datetime"] - assert not result["Analysis.Datetime"].hasnans - - -def test_add_record_time_unknown_file(example_dir, file_list): - from sensospot_parser.recordtime import add_record_time - - extended_list = file_list + ["unknown file"] - df = pandas.DataFrame(extended_list, columns=["Analysis.Image"]) - - result = add_record_time(df, example_dir / EXAMPLE_DIR_WITH_RECORD) - - assert len(df) == len(result) - assert list(result.columns) == ["Analysis.Image", "Analysis.Datetime"] - assert result["Analysis.Datetime"].hasnans - - -def test_add_record_time_no_record_xml(example_dir, file_list): - from sensospot_parser.recordtime import add_record_time - - df = pandas.DataFrame(file_list, columns=["Analysis.Image"]) - - result = add_record_time(df, example_dir / EXAMPLE_DIR_WITH_PARAMS) - - assert len(df) == len(result) - assert list(result.columns) == ["Analysis.Image", "Analysis.Datetime"] - assert result["Analysis.Datetime"].hasnans diff --git a/tests/test_sensospot_data.py b/tests/test_sensospot_data.py index 549de0d..61a83a3 100644 --- a/tests/test_sensospot_data.py +++ b/tests/test_sensospot_data.py @@ -1,8 +1,50 @@ """ testing the __ini__ file """ +import pytest + +from .conftest import EXAMPLE_DIR_CSV_WO_PARAMS, EXAMPLE_DIR_XML_WO_PARAMS def test_import_api(): from sensospot_parser import main # noqa: F401 from sensospot_parser import columns # noqa: F401 - from sensospot_parser import parse_file # noqa: F401 from sensospot_parser import parse_folder # noqa: F401 + from sensospot_parser import parse_csv_folder # noqa: F401 + from sensospot_parser import parse_xml_folder # noqa: F401 + + +def test_compare_xml_to_csv(example_dir): + import pandas + + from sensospot_parser import parse_csv_folder, parse_xml_folder + + folder = example_dir / EXAMPLE_DIR_XML_WO_PARAMS + + csv_df = parse_csv_folder(folder) + xml_df = parse_xml_folder(folder) + + assert isinstance(csv_df, pandas.DataFrame) + assert isinstance(xml_df, pandas.DataFrame) + + assert len(csv_df) == len(xml_df) + assert set(csv_df["Well.Name"]) == set(xml_df["Well.Name"]) + assert set(csv_df["Exposure.Id"]) == set(xml_df["Exposure.Id"]) + assert set(csv_df["Spot.Diameter"]) == set(xml_df["Spot.Diameter"]) + + +@pytest.mark.parametrize( + "folder, length, hasnans", + [ + (EXAMPLE_DIR_XML_WO_PARAMS, 6400, False), + (EXAMPLE_DIR_CSV_WO_PARAMS, 28800, True), + ], +) +def test_parse_folder_switches_parser(example_dir, folder, length, hasnans): + import pandas + + from sensospot_parser import parse_folder + + result = parse_folder(example_dir / folder) + + assert isinstance(result, pandas.DataFrame) + assert len(result) == length + assert result["Analysis.Datetime"].hasnans == hasnans diff --git a/tests/test_xml_parser.py b/tests/test_xml_parser.py new file mode 100644 index 0000000..a485ddf --- /dev/null +++ b/tests/test_xml_parser.py @@ -0,0 +1,341 @@ +from datetime import datetime + +import pytest + +from .conftest import EXAMPLE_DIR_XML_WO_PARAMS, EXAMPLE_DIR_XML_WITH_PARAMS + + +class DummyDataFunc: + def __init__(self, as_bool): + self.data = None + self.as_bool = as_bool + + def __call__(self, data): + self.data = data + + def __bool__(self): + return self.as_bool + + +def test_parser_target_init(): + from sensospot_parser.xml_parser import ParserTarget + + target = ParserTarget() + + assert target.collected == [] + assert target._current == {} + assert target._data_func is None + + +@pytest.mark.parametrize( + "tag, attributes, expected", + [ + ("UnknownTag", {"ID": "something"}, {}), + ( + "ScanJobResult", + {"ID": "scan job 1"}, + {"Analysis.Name": "scan job 1"}, + ), + ( + "AssayResult", + {"ID": "C03"}, + {"Well.Name": "C03", "Well.Row": "C", "Well.Column": 3}, + ), + ("ChannelConfig1", {}, {"Exposure.Id": 1}), + ("Spot", {"ID": "456"}, {"Pos.Id": 456}), + ( + "Result", + {"Label": "a label", "Type": "Unknown", "Value": "a value"}, + {"a label": "a value"}, + ), + ], +) +@pytest.mark.parametrize("additionals", [{}, {"Ignored": "value"}]) +def test_parser_target_start_simple_attributes( + tag, attributes, additionals, expected +): + from sensospot_parser.xml_parser import ParserTarget + + target = ParserTarget() + attributes.update(additionals) + + target.start(tag, attributes) # stateful operation + + assert target._current == expected + assert target._data_func is None + + +def test_parser_target_start_timestamp(): + from sensospot_parser.xml_parser import ParserTarget + + target = ParserTarget() + target.start("Timestamp", {}) + + assert target._data_func == target._data_timestamp_parser + + +def test_parser_target_start_image_file_name(): + from sensospot_parser.xml_parser import ParserTarget + + target = ParserTarget() + target.start("ImageFileName", {}) + + assert target._data_func == target._data_image_name_parser + + +@pytest.mark.parametrize( + "data_type, value, expected", + [ + ("unknown type", 1, "1"), + ("System.Int32", "12", 12), + ("System.UInt32", "23", 23), + ("System.Double", "4.56", 4.56), + ("System.Boolean", "true", True), + ("System.Boolean", "True", True), + ("System.Boolean", "Xrue", False), + ], +) +def test_parser_target_result_attributes_parser(data_type, value, expected): + from sensospot_parser.xml_parser import ParserTarget + + target = ParserTarget() + data = {"Label": "some label", "Type": data_type, "Value": value} + + target._result_attributes_parser(data) # stateful operation + + assert target._current == {"some label": expected} + assert type(target._current["some label"]) == type(expected) + + +@pytest.mark.parametrize( + "value, expected", + [ + ("3/7/2022 5:31:47 PM", datetime(2022, 3, 7, 17, 31, 47)), + ("03/7/2022 5:31:47 PM", datetime(2022, 3, 7, 17, 31, 47)), + ("3/07/2022 5:31:47 PM", datetime(2022, 3, 7, 17, 31, 47)), + ("03/07/2022 5:31:47 PM", datetime(2022, 3, 7, 17, 31, 47)), + ("3/7/2022 5:3:47 PM", datetime(2022, 3, 7, 17, 3, 47)), + ("3/7/2022 5:31:4 PM", datetime(2022, 3, 7, 17, 31, 4)), + ("3/7/2022 5:31:47 pm", datetime(2022, 3, 7, 17, 31, 47)), + ("3/7/2022 5:31:47 AM", datetime(2022, 3, 7, 5, 31, 47)), + ], +) +def test_parser_target_data_timestamp_parser(value, expected): + from sensospot_parser.xml_parser import ParserTarget + + target = ParserTarget() + + target._data_timestamp_parser(value) # stateful operation + + assert target._current == {"Analysis.Datetime": expected} + + +def test_parser_target_data_image_name_parser(): + from sensospot_parser.xml_parser import ParserTarget + + target = ParserTarget() + + target._data_image_name_parser(" some file path ") # stateful operation + + assert target._current == {"Analysis.Image": "some file path"} + + +def test_parser_target_data_does_not_call_function(): + from sensospot_parser.xml_parser import ParserTarget + + target = ParserTarget() + dummy = DummyDataFunc(as_bool=False) + target._data_func = dummy + + target.data("some data") # the NotImplementedError is not raised + + assert dummy.data is None + + +def test_parser_target_data_does_call_function(): + from sensospot_parser.xml_parser import ParserTarget + + target = ParserTarget() + dummy = DummyDataFunc(as_bool=True) + target._data_func = dummy + + target.data("some data") # stateful operation + + assert dummy.data == "some data" + + +def test_parser_target_data_reacts_on_spot(): + from sensospot_parser.xml_parser import ParserTarget + + target = ParserTarget() + target._current = {"some current": "data values"} + + target.end("Spot") # stateful operation + + assert target.collected == [{"some current": "data values"}] + assert target.collected[0] is not target._current + + +def test_parser_target_data_does_only_react_on_spot(): + from sensospot_parser.xml_parser import ParserTarget + + target = ParserTarget() + target._current = {"some current": "data values"} + + target.end("NonSpotTag") # stateful operation + + assert target.collected == [] + + +def test_parser_target_closed(): + from sensospot_parser.xml_parser import ParserTarget + + target = ParserTarget() + + target.closed() # stateful operation, must be callable + + +def test_find_result_xml_file_ok(tmp_path): + from sensospot_parser.xml_parser import _find_result_xml_file + + xls_file = tmp_path / "result.xsl" + xls_file.touch() + xml_file = tmp_path / "result.xml" + xml_file.touch() + + print(list(tmp_path.iterdir())) + + result = _find_result_xml_file(tmp_path) + + assert result == xml_file + + +def test_find_result_xml_file_no_matching_xml_file(tmp_path): + from sensospot_parser.xml_parser import _find_result_xml_file + + xls_file = tmp_path / "result.xsl" + xls_file.touch() + xml_file = tmp_path / "other.xml" + xml_file.touch() + + result = _find_result_xml_file(tmp_path) + + assert result is None + + +def test_find_result_xml_file_no_xsl_file(tmp_path): + from sensospot_parser.xml_parser import _find_result_xml_file + + xml_file = tmp_path / "result.xml" + xml_file.touch() + + result = _find_result_xml_file(tmp_path) + + assert result is None + + +def test_find_result_xml_file_multiple_xsl_files(tmp_path): + from sensospot_parser.xml_parser import _find_result_xml_file + + xls_file = tmp_path / "result.xsl" + xls_file.touch() + surplus_file = tmp_path / "surplus.xsl" + surplus_file.touch() + xml_file = tmp_path / "result.xml" + xml_file.touch() + + result = _find_result_xml_file(tmp_path) + + assert result is None + + +def test_find_result_hidden_xsl_file(tmp_path): + from sensospot_parser.xml_parser import _find_result_xml_file + + xls_file = tmp_path / ".result.xsl" + xls_file.touch() + xml_file = tmp_path / ".result.xml" + xml_file.touch() + + print(list(tmp_path.iterdir())) + + result = _find_result_xml_file(tmp_path) + + assert result is None + + +def test_parse_xml_file_ok(example_dir): + import pandas + + from sensospot_parser.xml_parser import ( + parse_xml_file, + _find_result_xml_file, + ) + + folder = example_dir / EXAMPLE_DIR_XML_WO_PARAMS + xml_file = _find_result_xml_file(folder) + + result = parse_xml_file(xml_file) + + assert isinstance(result, pandas.DataFrame) + assert len(result) == 4 * 4 * 4 * 100 + assert set(result["Well.Row"]) == set("ABCD") + assert set(result["Well.Column"]) == {1, 2, 3, 4} + assert set(result["Exposure.Id"]) == {1, 2, 3, 4} + assert min(result["Spot.Diameter"]) == 22 + assert max(result["Spot.Diameter"]) == 34 + assert "Parameters.Time" not in result + + +@pytest.mark.parametrize( + "file_name, message", + [ + ("not_existing.xml", "Xml file does not exist"), + ("incomplete.xml", "Could not parse assay results xml file"), + ("malformed_data.xml", "Malformed data in xml file"), + ], +) +def test_parse_xml_file_raies_error(file_name, message, example_dir): + from sensospot_parser.xml_parser import parse_xml_file + + xml_file = example_dir / file_name + + with pytest.raises(ValueError) as e: + parse_xml_file(xml_file) + assert message in str(e) + + +def test_parse_xml_folder_with_params(example_dir): + import pandas + + from sensospot_parser.xml_parser import parse_xml_folder + + folder = example_dir / EXAMPLE_DIR_XML_WITH_PARAMS + + result = parse_xml_folder(folder) + + assert isinstance(result, pandas.DataFrame) + assert len(result) == 4 * 4 * 4 * 100 + assert not result["Parameters.Time"].hasnans + + +def test_parse_xml_folder_without_params(example_dir): + import pandas + + from sensospot_parser.xml_parser import parse_xml_folder + + folder = example_dir / EXAMPLE_DIR_XML_WO_PARAMS + + result = parse_xml_folder(folder) + + assert isinstance(result, pandas.DataFrame) + assert len(result) == 4 * 4 * 4 * 100 + assert result["Parameters.Time"].hasnans + + +def test_parse_xml_folder_non_existing_xml_file(tmp_path): + from sensospot_parser.xml_parser import parse_xml_folder + + with pytest.raises(ValueError) as e: + parse_xml_folder(tmp_path) + assert "Could not find assay results xml file" in str(e)