def final_deconv(TMP_FOLDER,
standardized_path,
standardized_params,
fname_templates):
logger = logging.getLogger(__name__)
if not os.path.exists(TMP_FOLDER):
os.makedirs(TMP_FOLDER)
''' **********************************************
************** DECONVOLUTION *****************
**********************************************
'''
# run deconvolution
logger.info('FINAL DECONV')
(fname_templates,
fname_spike_train,
fname_templates_up,
fname_spike_train_up,
fname_shifts) = deconvolve.run(
fname_templates,
os.path.join(TMP_FOLDER,
'deconv'),
standardized_path,
standardized_params['dtype'])
# compute residual
logger.info('RESIDUAL COMPUTATION')
fname_residual, residual_dtype = residual.run(
fname_shifts,
fname_templates_up,
fname_spike_train_up,
os.path.join(TMP_FOLDER,
'residual'),
standardized_path,
standardized_params['dtype'],
dtype_out='float32')
#logger.info('FINAL MERGE')
fname_templates, fname_spike_train = merge.run(
os.path.join(TMP_FOLDER,
'post_deconv_merge'),
False,
fname_spike_train,
fname_templates,
fname_spike_train_up,
fname_templates_up,
standardized_path,
standardized_params['dtype'],
fname_residual,
residual_dtype)
return (fname_templates, fname_spike_train, fname_templates_up,
fname_spike_train_up, fname_residual, residual_dtype)
def final_deconv(TMP_FOLDER, standardized_path, standardized_dtype,
fname_templates):
logger = logging.getLogger(__name__)
if not os.path.exists(TMP_FOLDER):
os.makedirs(TMP_FOLDER)
''' **********************************************
************** DECONVOLUTION *****************
**********************************************
'''
# run deconvolution
logger.info('FINAL DECONV')
(fname_templates, fname_spike_train, fname_templates_up,
fname_spike_train_up,
fname_shifts) = deconvolve.run(fname_templates,
os.path.join(TMP_FOLDER, 'deconv'),
standardized_path, standardized_dtype)
# compute residual
logger.info('RESIDUAL COMPUTATION')
fname_residual, residual_dtype = residual.run(fname_shifts,
fname_templates,
fname_spike_train,
os.path.join(
TMP_FOLDER, 'residual'),
standardized_path,
standardized_dtype,
dtype_out='float32')
logger.info('SOFT NOISE ASSIGNMENT')
fname_soft_assignment = noise.run(
fname_templates, fname_spike_train, fname_shifts,
os.path.join(TMP_FOLDER, 'soft_assignment'), fname_residual,
residual_dtype)
logger.info('FINAL MERGE')
(fname_templates, fname_spike_train, fname_soft_assignment) = merge.run(
os.path.join(TMP_FOLDER, 'post_deconv_merge'), fname_spike_train,
fname_templates, fname_soft_assignment, fname_residual, residual_dtype)
return (fname_templates, fname_spike_train, fname_soft_assignment)
def single_block(TMP_FOLDER, standardized_path, standardized_params,
fname_templates, run_chunk_sec):
logger = logging.getLogger(__name__)
if not os.path.exists(TMP_FOLDER):
os.makedirs(TMP_FOLDER)
# run deconvolution
logger.info('DECONV' + str(run_chunk_sec))
(fname_templates, fname_spike_train, fname_templates_up,
fname_spike_train_up,
fname_shifts) = deconvolve.run(fname_templates,
os.path.join(TMP_FOLDER, 'deconv'),
standardized_path,
standardized_params['dtype'],
run_chunk_sec=run_chunk_sec)
# compute residual
logger.info('RESIDUAL COMPUTATION')
fname_residual, residual_dtype = residual.run(fname_shifts,
fname_templates_up,
fname_spike_train_up,
os.path.join(
TMP_FOLDER, 'residual'),
standardized_path,
standardized_params['dtype'],
dtype_out='float32',
run_chunk_sec=run_chunk_sec)
logger.info('BLOCK1 MERGE')
fname_templates_up, fname_spike_train_up = merge.run(
os.path.join(TMP_FOLDER, 'post_deconv_merge'), False,
fname_spike_train, fname_templates, fname_spike_train_up,
fname_templates_up, standardized_path, standardized_params['dtype'],
fname_residual, residual_dtype)
fname_templates = fname_templates_up
fname_spike_train = fname_spike_train_up
return (fname_templates, fname_spike_train, fname_templates_up,
fname_spike_train_up, fname_residual, residual_dtype)
def iterative_block(TMP_FOLDER, standardized_path, standardized_dtype,
fname_templates, run_chunk_sec):
logger = logging.getLogger(__name__)
if not os.path.exists(TMP_FOLDER):
os.makedirs(TMP_FOLDER)
# run deconvolution
logger.info('DECONV')
(fname_templates, fname_spike_train, fname_templates_up,
fname_spike_train_up,
fname_shifts) = deconvolve.run(fname_templates,
os.path.join(TMP_FOLDER, 'deconv'),
standardized_path,
standardized_dtype,
run_chunk_sec=run_chunk_sec)
# compute residual
logger.info('RESIDUAL COMPUTATION')
fname_residual, residual_dtype = residual.run(fname_shifts,
fname_templates,
fname_spike_train,
os.path.join(
TMP_FOLDER, 'residual'),
standardized_path,
standardized_dtype,
dtype_out='float32',
run_chunk_sec=run_chunk_sec)
#logger.info('KILL NOISE')
#fname_spike_train2 = noise.run(
# fname_templates,
# fname_spike_train,
# fname_shifts,
# os.path.join(TMP_FOLDER,
# 'noise_kill'),
# fname_residual,
# residual_dtype)
if False:
logger.info('SOFT NOISE ASSIGNMENT')
fname_soft_assignment = noise.run(
fname_templates, fname_spike_train, fname_shifts,
os.path.join(TMP_FOLDER, 'soft_assignment'), fname_residual,
residual_dtype)
logger.info('BLOCK1 MERGE')
_, _, _ = merge.run(os.path.join(TMP_FOLDER, 'post_deconv_merge'),
fname_spike_train, fname_templates,
fname_soft_assignment, fname_residual,
residual_dtype)
# cluster
logger.info('RECLUSTERING')
fname_templates, fname_spike_train = cluster.run(
os.path.join(TMP_FOLDER, 'cluster'),
standardized_path,
standardized_dtype,
fname_residual=fname_residual,
residual_dtype=residual_dtype,
fname_spike_index=None,
fname_templates=fname_templates,
fname_spike_train=fname_spike_train,
raw_data=False,
full_run=True)
methods = ['off_center', 'high_mad', 'duplicate_l2', 'duplicate']
fname_templates, fname_spike_train = postprocess.run(
methods, fname_templates, fname_spike_train,
os.path.join(TMP_FOLDER, 'cluster_post_process'), standardized_path,
standardized_dtype)
return fname_templates, fname_spike_train
def iterative_block(TMP_FOLDER,
standardized_path,
standardized_params,
fname_templates,
run_chunk_sec):
logger = logging.getLogger(__name__)
if not os.path.exists(TMP_FOLDER):
os.makedirs(TMP_FOLDER)
# run deconvolution
logger.info('DECONV')
(fname_templates,
fname_spike_train,
fname_templates_up,
fname_spike_train_up,
fname_shifts) = deconvolve.run(
fname_templates,
os.path.join(TMP_FOLDER,
'deconv'),
standardized_path,
standardized_params['dtype'],
run_chunk_sec=run_chunk_sec)
# compute residual
logger.info('RESIDUAL COMPUTATION')
fname_residual, residual_dtype = residual.run(
fname_shifts,
fname_templates_up,
fname_spike_train_up,
os.path.join(TMP_FOLDER,
'residual'),
standardized_path,
standardized_params['dtype'],
dtype_out='float32',
run_chunk_sec=run_chunk_sec)
logger.info('BLOCK1 MERGE')
fname_templates_up, fname_spike_train_up = merge.run(
os.path.join(TMP_FOLDER,
'post_deconv_merge'),
False,
fname_spike_train,
fname_templates,
fname_spike_train_up,
fname_templates_up,
standardized_path,
standardized_params['dtype'],
fname_residual,
residual_dtype)
fname_templates = fname_templates_up
fname_spike_train = fname_spike_train_up
# cluster
logger.info('RECLUSTERING')
raw_data = False
full_run = True
fname_templates, fname_spike_train = cluster.run(
fname_spike_train,
standardized_path,
standardized_params['dtype'],
os.path.join(TMP_FOLDER, 'cluster'),
raw_data,
full_run,
fname_residual=fname_residual,
residual_dtype=residual_dtype,
fname_templates_up=fname_templates_up,
fname_spike_train_up=fname_spike_train_up)
methods = ['duplicate', 'high_mad', 'collision']
fname_templates, fname_spike_train = postprocess.run(
methods,
fname_templates,
fname_spike_train,
os.path.join(TMP_FOLDER,
'cluster_post_process'),
standardized_path,
standardized_params['dtype'])
return fname_templates, fname_spike_train
def pre_final_deconv(TMP_FOLDER,
standardized_path,
standardized_dtype,
fname_templates,
run_chunk_sec):
logger = logging.getLogger(__name__)
if not os.path.exists(TMP_FOLDER):
os.makedirs(TMP_FOLDER)
''' **********************************************
************** DECONVOLUTION *****************
**********************************************
'''
# run deconvolution
logger.info('DECONV')
(fname_templates,
fname_spike_train,
fname_templates_up,
fname_spike_train_up,
fname_shifts) = deconvolve.run(
fname_templates,
os.path.join(TMP_FOLDER,
'deconv'),
standardized_path,
standardized_dtype,
run_chunk_sec=run_chunk_sec)
# compute residual
logger.info('RESIDUAL COMPUTATION')
fname_residual, residual_dtype = residual.run(
fname_shifts,
fname_templates,
fname_spike_train,
os.path.join(TMP_FOLDER,
'residual'),
standardized_path,
standardized_dtype,
dtype_out='float32',
run_chunk_sec=run_chunk_sec)
logger.info('SOFT NOISE ASSIGNMENT')
fname_soft_assignment = noise.run(
fname_templates,
fname_spike_train,
fname_shifts,
os.path.join(TMP_FOLDER,
'soft_assignment'),
fname_residual,
residual_dtype)
logger.info('POST DECONV MERGE')
(fname_templates,
fname_spike_train,
fname_soft_assignment) = merge.run(
os.path.join(TMP_FOLDER,
'post_deconv_merge'),
fname_spike_train,
fname_templates,
fname_soft_assignment,
fname_residual,
residual_dtype)
logger.info('Remove Low Firing Rate Units')
methods = ['low_fr']
fname_templates, fname_spike_train = postprocess.run(
methods,
os.path.join(TMP_FOLDER,
'post_deconv_post_process'),
standardized_path,
standardized_dtype,
fname_templates,
fname_spike_train,
fname_soft_assignment)
return (fname_templates,
fname_spike_train)