pyview_test_data/AS_Till_2004/pyPROGS/export_traces.py

import view
import pandas as pd
import logging
import pathlib as pl

# this tells view all settings including the folder structure of your project
# On Windows, if you copy paths from the file explorer, make sure the string below is always of the form r"......"
# ymlfile = r"/Volumes/AG_Galizia/AjayramaKumaraswamy/Ana_RNPN_SampleSet/usage_till.yml"
ymlfile = r"/home/aj/UKN_network_drives/ag_galizia/AjayramaKumaraswamy/Ana_RNPN_SampleSet/usage_till.yml"

# any  manual changes to flags, add to dictionary as required
flags_to_update = {
    "RM_ROITrace": 0,  # MUST: look up the documentation of this flag
    # Other flag changes can be included, for example:
    # CTV_scalebar: True,
    # mv_individualScale: 2,
    # .....
}

# list of animals for which traces are to be exported
animals = [
    "A_5803a"
]

if __name__ == '__main__':

    # create a view object
    view_obj = view.VIEW()

    # load flags from yml file
    view_obj.update_flags_from_ymlfile(ymlfile)

    # update flags specified locally
    view_obj.update_flags(flags_to_update)

    # iterate over animals
    for animal in animals:

        # initialize view object with animal
        view_obj.initialize_animal(animal=animal)

        # initialize and empty data frame to accumulate data
        gdm_df = pd.DataFrame()

        # iterate over measurements of the animal
        for measu in view_obj.get_measus_for_current_animal(analyze_values_to_use=(1,)):

            # load a measurement for the animal
            view_obj.load_measurement_data_from_current_animal(measu)

            # create glodatamix for the loaded measurement
            gdm_df_this_measu = view_obj.get_glodatamix_for_current_animal()

            # accumulate
            gdm_df = gdm_df.append(gdm_df_this_measu, ignore_index=True, sort=False)

        # compose output file name
        output_file = view_obj.flags.get_gloDatamix_file_for_current_animal()
        pl.Path(output_file).parent.mkdir(exist_ok=True)

        # save gloDatamix file
        gdm_df.to_csv(output_file, sep=';', header=True, index=False)
        logging.info(f"Wrote gloDatamix to {output_file}")

        # backup this script and the yml file used next to the created GDMs
        view_obj.backup_script_flags_configs_for_GDMs(files=[__file__, ymlfile])