def __init__(self, batch_path, UUID, viewer_ref):
vi = ViewerUtils(viewer_ref)
if not vi.discard_workEnv():
return
vi.viewer.status_bar_label.showMessage('Please wait, loading image data...')
pik_path = os.path.join(batch_path, f'{UUID}_input.pik')
tiff_path = os.path.join(batch_path, f'{UUID}_input.tiff')
vi.viewer.workEnv = ViewerWorkEnv.from_pickle(pik_path, tiff_path)
vi.update_workEnv()
vi.viewer.status_bar_label.showMessage('Finished loading image data...')
input_params_path = os.path.join(batch_path, f'{UUID}.params')
input_params = pickle.load(open(input_params_path, 'rb'))
if input_params['is_3d']:
roi_manager_gui = vi.viewer.parent().get_module('roi_manager')
manager = roi_manager_gui.start_backend('VolMultiCNMFROI')
cnmf_data_dicts = \
[
load_dict_from_hdf5(
os.path.join(batch_path, f'{UUID}_results_z{z}.hdf5')
)
# for z in range(5)
for z in range(vi.viewer.workEnv.imgdata.z_max + 1)
]
manager.add_all_components(
cnmf_data_dicts,
input_params
)
else:
cnmf_data = load_dict_from_hdf5(
os.path.join(batch_path, f'{UUID}_results.hdf5')
)
roi_manager_gui = vi.viewer.parent().get_module('roi_manager')
roi_manager_gui.start_backend('CNMFROI')
roi_manager_gui.manager.add_all_components(
cnmf_data,
input_params_dict=input_params,
)
name = input_params['item_name']
vi.viewer.ui.label_curr_img_seq_name.setText(f'CNMF: {name}')
vi.viewer.workEnv.history_trace.append({'cnmf': input_params})
vi.enable_ui(True)
def import_cnmfe_into_viewer(self):
vi = ViewerUtils(self.viewer_ref)
if not vi.discard_workEnv():
return
cnmf_data = load_dict_from_hdf5(
os.path.join(self.batch_dir, f'{self.UUID}_results.hdf5'))
vi.viewer.status_bar_label.showMessage(
'Loading CNMFE data, please wait...')
pickle_file_path = os.path.join(self.batch_dir,
f'{self.UUID}_input.pik')
tiff_path = os.path.join(self.batch_dir, f'{self.UUID}_input.tiff')
vi.viewer.workEnv = ViewerWorkEnv.from_pickle(pickle_file_path,
tiff_path)
vi.update_workEnv()
input_params = pickle.load(
open(os.path.join(self.batch_dir, f'{self.UUID}.params'), 'rb'))
vi.viewer.workEnv.history_trace.append({'cnmfe': input_params})
roi_manager_gui = vi.viewer.parent().get_module('roi_manager')
roi_manager_gui.start_backend('CNMFROI')
roi_manager_gui.manager.add_all_components(
cnmf_data,
input_params_dict=input_params,
calc_raw_min_max=self.checkbox_calc_raw_min_max.isChecked())
vi.viewer.ui.label_curr_img_seq_name.setText('CNMFE of: ' +
input_params['item_name'])
self.close()
def run(batch_dir: str, UUID: str):
logging.basicConfig(
stream=sys.stdout,
level=logging.DEBUG,
format=
"%(relativeCreated)12d [%(filename)s:%(funcName)20s():%(lineno)s] [%(process)d] %(message)s"
)
start_time = time()
output = {'status': 0, 'output_info': ''}
n_processes = os.environ['_MESMERIZE_N_THREADS']
n_processes = int(n_processes)
file_path = os.path.join(batch_dir, UUID)
filename = [file_path + '_input.tiff']
input_params = pickle.load(open(file_path + '.params', 'rb'))
# If Ain is specified
if input_params['do_cnmfe']:
Ain = None
item_uuid = input_params['cnmfe_kwargs'].pop('Ain')
if item_uuid:
print('>> Ain specified, looking for cnm-A file <<')
parent_batch_dir = os.environ['CURR_BATCH_DIR']
item_out_file = os.path.join(parent_batch_dir, f'{item_uuid}.out')
t0 = time()
timeout = 60
while not os.path.isfile(item_out_file):
print('>>> cnm-A not found, waiting for 15 seconds <<<')
sleep(15)
if time() - t0 > timeout:
output.update({
'status':
0,
'output_info':
'Timeout exceeding in waiting for Ain input file'
})
raise TimeoutError(
'Timeout exceeding in waiting for Ain input file')
if os.path.isfile(item_out_file):
if json.load(open(item_out_file, 'r'))['status']:
Ain_path = os.path.join(parent_batch_dir,
item_uuid + '_results.hdf5')
Ain = load_dict_from_hdf5(Ain_path)['estimates']['A']
print('>>> Found Ain file <<<')
else:
raise FileNotFoundError(
'>>> Could not find specified Ain file <<<')
print('*********** Creating Process Pool ***********')
c, dview, n_processes = cm.cluster.setup_cluster(backend='local',
n_processes=n_processes,
single_thread=False
#ignore_preexisting=True
)
try:
print('Creating memmap')
# memmap_path = cm.save_memmap_each(
# filename,
# base_name='memmap-' + UUID,
# order='C',
# border_to_0=input_params['border_pix'],
# dview=dview)
# memmap_path = cm.save_memmap_join(memmap_path, base_name='memmap-' + UUID, dview=dview)
# # load memory mappable file
# Yr, dims, T = cm.load_memmap(memmap_path)
# Y = Yr.T.reshape((T,) + dims, order='F')
memmap_path = cm.save_memmap(
filename,
base_name=f'memmap-',
order='C',
dview=dview,
border_to_0=input_params['border_pix'],
)
Yr, dims, T = cm.load_memmap(memmap_path)
Y = np.reshape(Yr.T, [T] + list(dims), order='F')
if input_params['do_cnmfe']:
gSig = input_params['cnmfe_kwargs']['gSig'][0]
else:
gSig = input_params['corr_pnr_kwargs']['gSig']
cn_filter, pnr = cm.summary_images.correlation_pnr(Y,
swap_dim=False,
gSig=gSig)
if not input_params['do_cnmfe'] and input_params['do_corr_pnr']:
pickle.dump(cn_filter,
open(UUID + '_cn_filter.pikl', 'wb'),
protocol=4)
pickle.dump(pnr, open(UUID + '_pnr.pikl', 'wb'), protocol=4)
output_file_list = \
[
UUID + '_pnr.pikl',
UUID + '_cn_filter.pikl',
]
output.update({
'output': UUID,
'status': 1,
'output_info': 'inspect correlation & pnr',
'output_files': output_file_list
})
dview.terminate()
for mf in glob(batch_dir + '/memmap-*'):
os.remove(mf)
end_time = time()
processing_time = (end_time - start_time) / 60
output.update({'processing_time': processing_time})
json.dump(output, open(file_path + '.out', 'w'))
return
cnm = cnmf.CNMF(
n_processes=n_processes,
method_init='corr_pnr',
dview=dview,
Ain=Ain,
only_init_patch=True, # just leave it as is
normalize_init=False,
center_psf=True,
**input_params['cnmfe_kwargs'],
)
cnm.fit(Y)
# DISCARD LOW QUALITY COMPONENTS
cnm.params.set('quality', {
'use_cnn': False,
**input_params['eval_kwargs']
})
cnm.estimates.evaluate_components(Y, cnm.params, dview=dview)
out_filename = f'{UUID}_results.hdf5'
cnm.save(out_filename)
pickle.dump(pnr, open(UUID + '_pnr.pikl', 'wb'), protocol=4)
pickle.dump(cn_filter,
open(UUID + '_cn_filter.pikl', 'wb'),
protocol=4)
output.update({
'output':
filename[:-5],
'status':
1,
'output_files': [
out_filename,
UUID + '_pnr.pikl',
UUID + '_cn_filter.pikl',
]
})
except Exception as e:
output.update({
'status': 0,
'Y.shape': Y.shape,
'output_info': traceback.format_exc()
})
dview.terminate()
for mf in glob(batch_dir + '/memmap-*'):
try:
os.remove(mf)
except: # Windows doesn't like removing the memmaps
pass
end_time = time()
processing_time = (end_time - start_time) / 60
output.update({'processing_time': processing_time})
json.dump(output, open(file_path + '.out', 'w'))