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 generate_pipeline_input(cell_dir=None,
specimen_id=None,
input_nwb_file=None,
plot_figures=False,
qc_fig_dirname="qc_figs",
qc_criteria_file=None,
stimulus_ontology_file=None):
se_input = generate_se_input(cell_dir,
specimen_id=specimen_id,
input_nwb_file=input_nwb_file)
pipe_input = dict(se_input)
if specimen_id:
pipe_input['manual_sweep_states'] = lq.get_sweep_states(specimen_id)
elif input_nwb_file:
pipe_input['manual_sweep_states'] = []
if plot_figures:
pipe_input['qc_fig_dir'] = os.path.join(cell_dir, qc_fig_dirname)
pipe_input['output_nwb_file'] = os.path.join(cell_dir, "output.nwb")
pipe_input['stimulus_ontology_file'] = stimulus_ontology_file
if qc_criteria_file is not None:
pipe_input['qc_criteria'] = ju.read(qc_criteria_file)
else:
pipe_input['qc_criteria'] = ju.read(qcp.DEFAULT_QC_CRITERIA_FILE)
return pipe_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)