def filter_subsample_timepoints(experiment_dir, interval=3):
'''
interval - subsampling interval in hours
'''
e_metadata = load_data.read_metadata(experiment_dir)
timestamps = numpy.array(e_metadata['timestamps'])
timepoints = e_metadata['timepoints']
expt_start = timestamps[0]
expt_end = timestamps[-1]
step = interval * 3600 #sec
i = 1
timepoints_to_load = []
while expt_start + step * i < expt_end:
timepoints_to_load.append(
timepoints[abs(timestamps - (expt_start + step * i)).argmin()])
i += 1
def filter(position_name, position_annotations, timepoint_annotations):
if position_annotations['exclude']:
return False
return [
timepoint in timepoints_to_load
for timepoint in timepoint_annotations
]
return filter
def reset_positions_with_offset(experiment_dir, offset):
''' Modify position coordinates based on a fixed x-y offset
Parameters:
experiment_dir - str/pathlib.Path to experiment root
offset - list giving the x-y offset
'''
experiment_dir = pathlib.Path(experiment_dir)
print(f'Modifying positions for {experiment_dir.name}')
metadata = load_data.read_metadata(experiment_dir)
new_metadata = metadata.copy()
if len(offset) == 2:
offset.extend([0])
try:
time_label = time.strftime('%Y%m%d-%H%M-%S')
for position in metadata['positions']:
position_coords = metadata['positions'][position]
new_metadata['positions'][position] = [
position_coords[0] + offset[0], position_coords[1] + offset[1],
position_coords[2] + offset[2]
]
with (experiment_dir /
f'experiment_metadata_beforechangingpositions_{time_label}.json'
).open('w') as mdata_file:
datafile.json_encode_legible_to_file(metadata, mdata_file)
load_data.write_metadata(new_metadata, experiment_dir)
except KeyboardInterrupt:
pass
def make_multipass_measurements(experiment_root, annotations, adult_only=True):
experiment_metadata = load_data.read_metadata(experiment_root)
microns_per_pixel = 1.3 * 5 / (experiment_metadata['objective'] *
experiment_metadata['optocoupler'])
measures = [MultipassPoseMeasurements(microns_per_pixel=microns_per_pixel)]
measurement_name = 'multipass_measures'
if adult_only:
annotations = load_data.filter_annotations(
annotations, elegant_filters.filter_by_stage('adult')).copy()
process_data.measure_worms(experiment_root, annotations, measures,
measurement_name)
def reset_positions_manual(scope,
experiment_dir,
*annotation_filters,
revert_z=False):
'''Reset positions manually for an experiment (i.e. with a separate ris_widget window open)
Parameters:
scope - ScopeClient object as defined by scope.scope_client
experiment_dir - str/pathlib.Path to experiment
annotation_filters - Optional variable filters to use to isolate specific positions of interest
Call with annotation filters like so:
reset_position.reset_positions(scope, experiment_dir, elegant_filters.filter_excluded, elegant_filters.filter_live_animals)
'''
experiment_dir = pathlib.Path(experiment_dir)
print(f'Traversing {experiment_dir.name}')
metadata = load_data.read_metadata(experiment_dir)
if annotation_filters:
experiment_annotations = load_data.read_annotations(experiment_dir)
for filter in annotation_filters:
experiment_annotations = load_data.filter_annotations(
experiment_annotations, filter)
positions = experiment_annotations.keys()
else:
positions = metadata['positions'].keys()
new_positions = poll_positions(scope,
metadata,
positions,
revert_z=revert_z)
if new_positions:
try:
input(f'\nPress any key to save positions; ctrl-c to abort')
time_label = time.strftime('%Y%m%d-%H%M-%S')
with (experiment_dir /
f'experiment_metadata_beforechangingpositions_{time_label}.json'
).open('w') as mdata_file:
datafile.json_encode_legible_to_file(metadata, mdata_file)
metadata['positions'].update(new_positions)
load_data.write_metadata(metadata, experiment_dir)
except KeyboardInterrupt:
pass
else:
print('No positions found to reset')
def _check_metadata_for_timepoints(experiment_root):
pm_files = list(experiment_root.glob('*/position_metadata.json'))
with pm_files[0].open('r') as pm_fp:
position_metadata = json.load(pm_fp)
if 'timepoint' not in position_metadata[0]:
experiment_metadata = load_data.read_metadata(experiment_root)
for pm_file in pm_files:
position_root = pm_file.parent
if not (position_root /
'position_metadata_original.json').exists():
shutil.copyfile(
str(pm_file),
str(position_root / 'position_metadata_original.json'))
with pm_file.open('r') as pm_fp:
position_metadata = json.load(pm_fp)
for metadata_entry, timepoint in zip(
position_metadata, experiment_metadata['timepoint']):
# Was there a bug with the purging code that breaks this?
metadata_entry['timepoint'] = timepoint
with pm_file.open('w') as pm_fp:
json.dump(position_metadata, pm_fp)
def make_mask_measurements(experiment_root, annotations=None, adult_only=True):
#process_data.annotate(experiment_root, annotators=[annotate_timepoints]) # Why?
experiment_metadata = load_data.read_metadata(experiment_root)
microns_per_pixel = 1.3 * 5 / (experiment_metadata['objective'] *
experiment_metadata['optocoupler'])
measures = [MaskPoseMeasurements(microns_per_pixel=microns_per_pixel)]
measurement_name = 'mask_measures'
if annotations is None:
annotations = load_data.read_annotations(experiment_root)
annotations = load_data.filter_annotations(annotations,
filter_excluded)
annotations = load_data.filter_annotations(
annotations, elegant_filters.filter_living_timepoints)
if adult_only:
annotations = load_data.filter_annotations(
annotations, elegant_filters.filter_by_stage('adult'))
process_data.measure_worms(experiment_root, annotations, measures,
measurement_name)
return experiment_images
if __name__ == "__main__":
expt_dir = pathlib.Path(sys.argv[1])
show_poses = True
try:
rw
except NameError:
rw = ris_widget.RisWidget()
if hasattr(rw, 'annotator'):
rw.annotator.close()
del(rw.annotator)
# measurement_pipeline.propagate_stages(expt_dir)
experiment_images = load_masks(expt_dir)
annotation_fields = []
annotation_fields.append(stage_field.StageField())
if show_poses:
metadata = load_data.read_metadata(expt_dir)
pa = pose_annotation.PoseAnnotation.from_experiment_metadata(metadata, rw)
annotation_fields.append(pa)
ea = experiment_annotator.ExperimentAnnotator(rw, expt_dir.parts[-1],
experiment_images, annotation_fields)
def process_experiment_with_filter(experiment_root,
model,
image_filter,
mask_root=None,
overwrite_existing=False,
channels='bf',
make_masks=True,
do_annotations=True):
'''
image_filter - filter for scan_experiment_dir
'''
if mask_root is None:
mask_root = pathlib.Path(experiment_root) / 'derived_data' / 'mask'
# Temporary hacks until migration to new elegant complete (while zpl-9000 no longer updates annotations automatically)
process_data.update_annotations(experiment_root)
elegant_hacks.propagate_stages(experiment_root)
start_t = time.time()
positions = load_data.scan_experiment_dir(experiment_root,
timepoint_filter=image_filter,
channels=channels)
scan_t = time.time()
print(f'scanning done after {(scan_t-start_t)} s')
if make_masks:
process = segment_images.segment_positions(positions,
model,
mask_root,
use_gpu=True,
overwrite_existing=False)
if process.stderr:
print(f'Errors during segmentation: {process.stderr}'
) #raise Exception)
#raise Exception()
segment_t = time.time()
print(f'segmenting done after {(segment_t-scan_t)} s')
with (mask_root / 'notes.txt').open('a+') as notes_file:
notes_file.write(
f'{datetime.datetime.today().strftime("%Y-%m-%dt%H%M")} These masks were segmented with model {model}\n'
)
else:
print(f'No segmenting performed')
if do_annotations:
annotations = load_data.read_annotations(experiment_root)
metadata = load_data.read_metadata(experiment_root)
age_factor = metadata.get('age_factor', 1)
width_estimator = worm_widths.WidthEstimator.from_experiment_metadata(
metadata, age_factor)
segment_images.annotate_poses_from_masks(positions, mask_root,
annotations,
overwrite_existing,
width_estimator)
load_data.write_annotations(experiment_root, annotations)
annotation_t = time.time()
print(
f'annotation done after {(annotation_t - segment_t)} s') # ~3.5 hr
else:
print('No annotations done')