def main():
"""
Usage:
> python generate_qc_input.py --specimen_id SPECIMEN_ID --cell_dir CELL_DIR
> python generate_qc_input.py --input_nwb_file input_nwb_file --cell_dir CELL_DIR
"""
args = parse_args()
se_input = generate_se_input(**args)
cell_dir = args['cell_dir']
if not os.path.exists(cell_dir):
os.makedirs(cell_dir)
lu.configure_logger(cell_dir)
ju.write(os.path.join(cell_dir,'se_input.json'), se_input)
se_output = run_sweep_extraction(se_input["input_nwb_file"],
se_input.get("input_h5_file",None),
se_input.get("stimulus_ontology_file", None))
ju.write(os.path.join(cell_dir,'se_output.json'),se_output)
sp.drop_tagged_sweeps(se_output["sweep_features"])
qc_input = generate_qc_input(se_input, se_output)
ju.write(os.path.join(cell_dir,'qc_input.json'), qc_input)
def main():
"""
Usage:
> python generate_fx_input.py --specimen_id SPECIMEN_ID --cell_dir CELL_DIR
> python generate_fx_input.py --input_nwb_file INPUT_NWB_FILE --cell_dir CELL_DIR
"""
kwargs = parse_args()
se_input = generate_se_input(**kwargs)
cell_dir = kwargs["cell_dir"]
lu.configure_logger(cell_dir)
if not os.path.exists(cell_dir):
os.makedirs(cell_dir)
ju.write(os.path.join(cell_dir, 'se_input.json'), se_input)
se_output = run_sweep_extraction(
se_input["input_nwb_file"], se_input.get("input_h5_file", None),
se_input.get("stimulus_ontology_file", None))
ju.write(os.path.join(cell_dir, 'se_output.json'), se_output)
sp.drop_tagged_sweeps(se_output["sweep_features"])
qc_input = generate_qc_input(se_input, se_output)
ju.write(os.path.join(cell_dir, 'qc_input.json'), qc_input)
qc_output = run_qc(qc_input.get("stimulus_ontology_file",
None), qc_input["cell_features"],
qc_input["sweep_features"], qc_input["qc_criteria"])
ju.write(os.path.join(cell_dir, 'qc_output.json'), qc_output)
if kwargs["specimen_id"]:
manual_sweep_states = lq.get_sweep_states(kwargs["specimen_id"])
elif kwargs["input_nwb_file"]:
manual_sweep_states = []
sp.override_auto_sweep_states(manual_sweep_states,
qc_output["sweep_states"])
sp.assign_sweep_states(qc_output["sweep_states"],
se_output["sweep_features"])
fx_input = generate_fx_input(se_input,
se_output,
cell_dir,
plot_figures=True)
ju.write(os.path.join(cell_dir, 'fx_input.json'), fx_input)
def run_pipeline(input_nwb_file,
output_nwb_file,
stimulus_ontology_file,
qc_fig_dir,
qc_criteria,
manual_sweep_states,
write_spikes=True,
update_ontology=True):
se_output = run_sweep_extraction(input_nwb_file,
stimulus_ontology_file,
update_ontology=update_ontology)
sweep_props.drop_tagged_sweeps(se_output["sweep_features"])
sweep_props.remove_sweep_feature("tags", se_output["sweep_features"])
qc_output = run_qc(stimulus_ontology_file, se_output["cell_features"],
se_output["sweep_features"], qc_criteria)
sweep_props.override_auto_sweep_states(manual_sweep_states,
qc_output["sweep_states"])
sweep_props.assign_sweep_states(qc_output["sweep_states"],
se_output["sweep_features"])
fx_output = run_feature_extraction(
input_nwb_file,
stimulus_ontology_file,
output_nwb_file,
qc_fig_dir,
se_output['sweep_features'],
se_output['cell_features'],
write_spikes,
)
log_pretty_header("Analysis completed!", level=1)
return {
"sweep_extraction": se_output,
"qc": qc_output,
"feature_extraction": fx_output
}
def run_pipeline(input_nwb_file, input_h5_file, output_nwb_file,
stimulus_ontology_file, qc_fig_dir, qc_criteria,
manual_sweep_states):
se_output = run_sweep_extraction(input_nwb_file, input_h5_file,
stimulus_ontology_file)
sp.drop_tagged_sweeps(se_output["sweep_features"])
sp.remove_sweep_feature("tags", se_output["sweep_features"])
qc_output = run_qc(stimulus_ontology_file, se_output["cell_features"],
se_output["sweep_features"], qc_criteria)
if qc_output["cell_state"]["failed_qc"]:
logging.warning("Failed QC. No ephys features extracted.")
return dict(
sweep_extraction=se_output,
qc=qc_output,
)
sp.override_auto_sweep_states(manual_sweep_states,
qc_output["sweep_states"])
sp.assign_sweep_states(qc_output["sweep_states"],
se_output["sweep_features"])
fx_output = run_feature_extraction(
input_nwb_file,
stimulus_ontology_file,
output_nwb_file,
qc_fig_dir,
se_output['sweep_features'],
se_output['cell_features'],
)
return dict(sweep_extraction=se_output,
qc=qc_output,
feature_extraction=fx_output)
