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107 lines
3.3 KiB
107 lines
3.3 KiB
""" Sensospot Data Parser |
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Parsing the numerical output from Sensovations Sensospot image analysis. |
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""" |
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from pathlib import Path |
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from collections import namedtuple |
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import numpy |
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import pandas |
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from defusedxml import ElementTree |
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from .columns import ( |
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META_DATA_EXPOSURE_ID, |
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META_DATA_PARAMETERS_TIME, |
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META_DATA_PARAMETERS_CHANNEL, |
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) |
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ExposureInfo = namedtuple("ExposureInfo", ["channel", "time"]) |
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def _search_measurement_params_file(folder): |
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"""searches for a exposure settings file in a folder""" |
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folder_path = Path(folder) |
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params_folder = folder_path / "Parameters" |
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if not params_folder.is_dir(): |
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return None |
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param_files = list(params_folder.glob("**/*.svexp")) |
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if len(param_files) == 1: |
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return param_files[0] |
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else: |
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return None |
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def _parse_measurement_params(params_file): |
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"""parses the cannel informations from a settings file""" |
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file_path = Path(params_file) |
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with file_path.open("r") as file_handle: |
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tree = ElementTree.parse(file_handle) |
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result = {} |
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for child in tree.find("Channels"): |
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# child.tag == "ChannelConfig1" |
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exposure = int(child.tag[-1]) |
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channel_description = child.attrib["Description"] |
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# channel_description == "[Cy3|Cy5] Green" |
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channel = channel_description.rsplit(" ", 1)[-1] |
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time = float(child.attrib["ExposureTimeMs"]) |
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result[exposure] = ExposureInfo(channel.lower(), time) |
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return result |
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def get_measurement_params(folder): |
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"""returns measurement parameters""" |
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params_file = _search_measurement_params_file(folder) |
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if params_file is not None: |
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return _parse_measurement_params(params_file) |
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return None |
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def _add_measurement_params(data_frame, params): |
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"""adds measurement parameters to a data frame""" |
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columns = [META_DATA_PARAMETERS_CHANNEL, META_DATA_PARAMETERS_TIME] |
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map = {k: dict(zip(columns, v)) for k, v in params.items()} |
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return _apply_map(data_frame, map, META_DATA_EXPOSURE_ID) |
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def _apply_map(data_frame, map, index_col): |
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"""adds a nested dictionary to a data frame on a specific index column |
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map: |
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keys: must be the same as the values in the index column, |
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values: dictionary with new column names as keys and the values |
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example: |
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>>> df = DataFrame(data={"MyIndex": [10, 10, 20]}) |
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>>> map = { |
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... 10: {"NewCol": "foo"}, |
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... 20: {"NewCol": "Bar"}, |
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... } |
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>>> apply_map(df, map, "MyIndex") |
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MyIndex NewCol |
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0 10 foo |
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1 10 foo |
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2 20 bar |
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""" |
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map_df = pandas.DataFrame.from_dict(map, orient="index") |
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return data_frame.merge( |
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map_df, |
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how="left", |
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left_on=index_col, |
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right_index=True, |
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) |
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def add_optional_measurement_parameters(data_frame, folder): |
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"""adds measurement params to the data frame, if they could be parsed""" |
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params = get_measurement_params(folder) |
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if params: |
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available_exposures = set(data_frame[META_DATA_EXPOSURE_ID].unique()) |
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if available_exposures == set(params.keys()): |
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return _add_measurement_params(data_frame, params) |
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else: |
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data_frame[META_DATA_PARAMETERS_CHANNEL] = numpy.nan |
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data_frame[META_DATA_PARAMETERS_TIME] = numpy.nan |
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return data_frame
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