Adding custom functionality¶

from impact.parsers import Parser, parse_raw_identifier, parse_time_point_list
from impact import TimePoint

def new_parser(experiment, data, id_type='traverse'):
    # Define the layout of our data
    first_row_index = 0
    plate_size = 8
    spacing = 1
    time_row_col = [0,0]
    data_row_col = [1,0]

    # Define the type of data this parser accepts
    analyte_name = 'OD600'
    analyte_type = 'biomass'

    # In this case, we can first prepare the data by extracting the relevant information from each sheet
    unparsed_identifiers = data['identifiers']
    raw_data = data['data']

    # The data starts at (1,1) and is in a 8x12 format
    timepoint_list = []

    # We first parse the identifiers, as these can be recycled (the only thing that is changing is the time)
    identifiers = []
    for i, row in enumerate(unparsed_identifiers):
        parsed_row = []
        for j, data in enumerate(row):
            # Here we can implement logic to exclude any data which is not present, for example when a plate is not full
            # In this case, any cell which is empty, 0, or None will be excluded
            if unparsed_identifiers[i][j] not in ['', 0, '0', None]:
                temp_trial_identifier = parse_raw_identifier(unparsed_identifiers[i][j], id_type)
                parsed_row.append(temp_trial_identifier)
            else:
                parsed_row.append(None)
        identifiers.append(parsed_row)


    for start_row_index in range(first_row_index, len(raw_data), plate_size+spacing):
        if raw_data[start_row_index][0] != '~End':
            time = int(raw_data[start_row_index+time_row_col[0]][time_row_col[1]])

            # Define the data for a single plate, single timepoint
            plate_data = [row[2:14] for row in raw_data[start_row_index:start_row_index+plate_size]]

            # Load the data point by point
            for i, row in enumerate(plate_data):
                for j, data in enumerate(row):
                    # Skip wells where no identifier is listed or no data present
                    if identifiers[i][j] is not None and data not in [None,'']:
                        ti = identifiers[i][j]
                        ti.analyte_type, ti.analyte_name = analyte_type, analyte_name
                        time_point = TimePoint(ti, time, float(data))
                        timepoint_list.append(time_point)
        else:
            break

    # Finally we parse all of the time points (into their logical strucutre based on identifiers)
    # And add them to the experiment
    replicate_trial_list = parse_time_point_list(timepoint_list)
    for rep in replicate_trial_list:
        experiment.add_replicate_trial(rep)

Parser.register_parser('my_new_format',new_parser)
expt = Parser.parse_raw_data('my_new_format',file_name='../tests/test_data/sample_parser_docs_data.xlsx')

print(expt)