def compile_day_metadata(aux_dir, day):
""" Compile experiment day metadata from wormsorter and hydra rig metadata for a given day in
'AuxiliaryFiles' directory
Parameters
----------
aux_dir : str
Path to "AuxiliaryFiles" containing metadata
day : str, None
Experiment day folder in format 'YYYYMMDD'
Returns
-------
compiled_day_metadata : pandas.DataFrame
Compiled metadata dataframe for given imaging date
"""
day_dir = Path(aux_dir) / str(day)
wormsorter_meta = day_dir / (str(day) + '_wormsorter.csv')
hydra_meta = day_dir / (str(day) + '_manual_metadata.csv')
# expand wormsorter metadata to have separate row for each well
plate_metadata = populate_96WPs(wormsorter_meta)
day_metadata = get_day_metadata(complete_plate_metadata=plate_metadata,
hydra_metadata_file=hydra_meta,
merge_on=['imaging_plate_id'],
n_wells=96,
run_number_regex='run\\d+_',
saveto=None,
del_if_exists=False,
include_imgstore_name=True,
raw_day_dir=None)
return day_metadata
print('Calculating metadata for {} days of experiments'.format(
len(day_root_dirs)))
for count, day in enumerate(day_root_dirs):
exp_date = re.findall(date_regex, str(day))[0]
manualmetadata_file = list(day.rglob('*_manual_metadata.csv'))[0]
assert (exp_date in str(manualmetadata_file))
wormsorter_file = list(day.rglob('*_wormsorter.csv'))[0]
assert (exp_date in str(wormsorter_file))
bad_wells_file = list(day.rglob('*_robot_bad_imaging_wells.csv'))[0]
assert (exp_date in str(bad_wells_file))
print('Collating wormsorter files: {}'.format(wormsorter_file))
plate_metadata = populate_96WPs(wormsorter_file,
del_if_exists=True,
saveto='default')
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)
metadata_file = day / '{}_day_metadata_test.csv'.format(exp_date)
print('Generating day metadata: {}'.format(metadata_file))
try:
day_metadata = get_day_metadata(plate_metadata,
def compile_day_metadata(aux_dir,
day,
n_wells=96,
from_source_plate=False,
from_robot_runlog=False):
""" Compile experiment day metadata from wormsorter and hydra rig metadata for a given day in
'AuxiliaryFiles' directory
Parameters
----------
aux_dir : str
Path to "AuxiliaryFiles" containing metadata
day : str, None
Experiment day folder in format 'YYYYMMDD'
from_source_plate : bool
Compile day metadata using source plate metadata ('source_plate.csv') and mapping for
each imaging plate ID ('source2imaging.csv')
from_robot_runlog : bool
Compile plate metadata from OpenTrons run log files (eg. for randomised plates)
Returns
-------
day_metadata : pandas.DataFrame
Compiled day metadata
"""
from tierpsytools.hydra.compile_metadata import (
populate_6WPs,
populate_24WPs,
populate_96WPs,
get_day_metadata,
get_source_metadata,
merge_basic_and_source_meta,
#merge_robot_metadata,
#merge_robot_wormsorter,
number_wells_per_plate,
day_metadata_check)
day_dir = Path(aux_dir) / str(day)
wormsorter_meta = day_dir / (str(day) + '_wormsorter.csv')
hydra_meta = day_dir / (str(day) + '_manual_metadata.csv')
# Expand wormsorter metadata to have separate row for each well (96-well or 6-well plate format)
if n_wells == 6:
plate_metadata = populate_6WPs(wormsorter_meta)
elif n_wells == 24:
plate_metadata = populate_24WPs(wormsorter_meta)
elif n_wells == 96:
plate_metadata = populate_96WPs(wormsorter_meta)
else:
raise ValueError("Please choose n_wells from: [6, 24, 96]")
from_source_plate = True if from_robot_runlog else from_source_plate
if from_source_plate:
source_plate_meta = day_dir / 'source_plates.csv'
plate_mapping_meta = day_dir / 'source2plate.csv'
source_metadata = get_source_metadata(
sourceplates_file=source_plate_meta,
imaging2source_file=plate_mapping_meta)
plate_metadata = merge_basic_and_source_meta(
plate_metadata,
source_metadata,
merge_on=['imaging_plate_id', 'well_name'],
saveto=None,
del_if_exists=False)
# =============================================================================
# if from_robot_runlog:
# robot_runlog_meta = day_dir / 'robot_runlog.csv'
#
# drug_metadata = merge_robot_metadata(robot_runlog_meta,
# randomized_by='column',
# saveto=None,
# drug_by_column=True,
# compact_drug_plate=False,
# del_if_exists=False)
#
# plate_metadata = merge_robot_wormsorter(day_dir,
# drug_metadata,
# plate_metadata,
# bad_wells_csv=None,
# merge_on=['imaging_plate_id', 'well_name'],
# saveto=None,
# del_if_exists=False)
# =============================================================================
day_metadata = get_day_metadata(complete_plate_metadata=plate_metadata,
hydra_metadata_file=hydra_meta,
merge_on=['imaging_plate_id'],
n_wells=n_wells,
run_number_regex='run\\d+_',
saveto=None,
del_if_exists=False,
include_imgstore_name=True,
raw_day_dir=None)
day_metadata_check(day_metadata,
day_dir) # check day metadata is correct dimension
print(number_wells_per_plate(day_metadata, day_dir))
return day_metadata