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75 lines
2.5 KiB
75 lines
2.5 KiB
4 years ago
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""" 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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from defusedxml import ElementTree
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MeasurementParams = namedtuple("MeasurementParams", ["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 = int(child.attrib["ExposureTimeMs"])
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result[exposure] = MeasurementParams(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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for exposure_id, info in params.items():
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mask = data_frame["Exposure.Id"] == exposure_id
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data_frame.loc[mask, "Parameters.Channel"] = info.channel
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data_frame.loc[mask, "Parameters.Time"] = info.time
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data_frame["Parameters.Channel"] = data_frame["Parameters.Channel"].astype(
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"category"
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)
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return data_frame
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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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data_frame["Parameters.Channel"] = numpy.nan
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data_frame["Parameters.Time"] = numpy.nan
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params = _get_measurement_params(folder)
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if params:
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available_exposures = set(data_frame["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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return data_frame
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