rlog.to_csv(file.parent / (file.stem + '_clean.csv'), index=False)
return
#%%
if __name__ == '__main__':
if PREPROCESSING_REQUIRED == True:
robot_logs = list(ROOT_DIR.rglob('*runlog.csv'))
preprocess_runlogs(robot_logs)
update_sourceplate_files(SOURCEPLATE_FILES)
#%%
for file in SOURCEPLATE_FILES:
robot_metadata = merge_robot_metadata(file,
saveto=None,
del_if_exists=True,
compact_drug_plate=True,
drug_by_column=False)
robot_metadata.sort_values(by=['source_plate_number',
'destination_well'],
ignore_index=True,
inplace=True)
robot_metadata['robot_run_number'] = robot_metadata.destination_slot.map(DSLOT_RUN_NUMBER_DICT)
# add in the unshuffled plate a plate 4
_p04 = pd.read_csv(file)
_p04['robot_run_number'] = 4
_p04.rename(columns={'source_well':'destination_well'},
inplace=True)
robot_metadata = pd.concat([robot_metadata, _p04], axis=0)
Created on Fri Nov 15 15:50:39 2019
@author: em812
"""
from tierpsytools.hydra.compile_metadata import merge_robot_metadata
from tierpsytools.hydra.compile_metadata import get_day_metadata
from tierpsytools import EXAMPLES_DIR
from pathlib import Path
if __name__=="__main__":
# Input
data_dir = Path(EXAMPLES_DIR) / 'hydra_metadata' / 'data'
day_root_dir = data_dir / 'AuxiliaryFiles' / 'day1'
sourceplate_file = day_root_dir / '20191107_sourceplates.csv'
manual_meta_file = day_root_dir / '20191108_manual_metadata.csv'
# Save to
#robot_metadata_file = day_root_dir.joinpath('20191107_robot_metadata.csv')
metadata_file = day_root_dir / '{}_day_metadata.csv'.format(
day_root_dir.stem)
# Run
robot_metadata = merge_robot_metadata(sourceplate_file, saveto=False)
day_metadata = get_day_metadata(
robot_metadata, manual_meta_file, saveto=metadata_file,
del_if_exists=True, include_imgstore_name = True,
raw_day_dir=data_dir / 'RawVideos' / 'day1')
print(
'Collating manual metadata files: {},'.format(sourceplates_file) +
'\n'
'{}'.format(wormsorter_file))
bad_wells_df = convert_bad_wells_lut(bad_wells_file)
plate_metadata = pd.merge(plate_metadata,
bad_wells_df,
on=['imaging_plate_id', 'well_name'],
how='outer')
plate_metadata['is_bad_well'].fillna(False, inplace=True)
robot_metadata = merge_robot_metadata(sourceplates_file,
del_if_exists=True)
metadata_file = day / '{}_day_metadata.csv'.format(exp_date)
assert robot_metadata['drug_type'].isna().sum() == 0
# plate_file = list(day.rglob("*plate_metadata.csv"))[0]
# plate_metadata = pd.read_csv(plate_file)
# robot_file = list(day.rglob("*robot_metadata.csv"))[0]
# robot_metadata = pd.read_csv(robot_file)
concat_metadata = merge_robot_wormsorter(day,
robot_metadata,
plate_metadata,
bad_wells_file,
del_if_exists=True)
sourceplate_files = [[file for file in d.glob('*_sourceplates.csv')]
for d in day_root_dirs]
manual_meta_files = [[file for file in d.glob('*_manual_metadata.csv')]
for d in day_root_dirs]
# Saveto
metadata_files = [
d.joinpath('{}_day_metadata.csv'.format(d.stem)) for d in day_root_dirs
]
# Run compilation of day metadata for all the days
for day, source, manual_meta, saveto in zip(day_root_dirs,
sourceplate_files,
manual_meta_files,
metadata_files):
if len(source) != 1:
print('There is not a unique sourceplates file ' +
'in day {}. Metadata cannot be compiled'.format(day))
continue
if len(manual_meta) != 1:
print('There is not a unique manual_metadata file ' +
'in day {}. Metadata cannot be compiled'.format(day))
continue
robot_metadata = merge_robot_metadata(source[0], saveto=False)
day_metadata = get_day_metadata(robot_metadata,
manual_meta[0],
saveto=saveto)
# Conactenate all metadata
concatenate_days_metadata(aux_root_dir)