def ui_imagearray(header, index=0):
"Return image array from the header object and event index."
e = blank_events(header)[index]
fill_event(e)
nm = [k for k in e.data if k.endswith('image_lightfield')][0]
rv = e.data[nm][0]
return rv
def export(headers, filename):
"""
Parameters
----------
headers : a Header or a list of Headers
objects retruned by the Data Broker
filename : string
path to a new or existing HDF5 file
"""
with h5py.File(filename) as f:
for header in headers:
assert isinstance(header, MutableMapping)
header = copy.deepcopy(header)
try:
descriptors = header.pop('event_descriptors')
except KeyError:
warnings.warn("Header with uid {header.uid} contains no "
"data.".format(header), UserWarning)
continue
top_group_name = repr(header).replace(' ', '_')[1:-1]
group = f.create_group(top_group_name)
_safe_attrs_assignment(group, header)
for i, descriptor in enumerate(descriptors):
desc_group = group.create_group('Event_Stream_{0}'.format(i))
data_keys = descriptor.pop('data_keys')
_safe_attrs_assignment(desc_group, descriptor)
events = list(find_events(descriptor=descriptor))
event_times = [e['time'] for e in events]
desc_group.create_dataset('event_times', event_times)
data_group = desc_group.create_group('data')
ts_group = desc_group.create_group('timestamps')
[fill_event(e) for e in events]
for key, value in data_keys.items():
print('data key = %s' % key)
timestamps = [e['timestamps'][key] for e in events]
ts_group.create_dataset(key, data=timestamps)
data = [e['data'][key] for e in events]
dataset = data_group.create_dataset(key, data=data)
def events_generator(header):
"Return a generator of Events. Large (nonscalar) data is lazy-loaded."
for e in blank_events(header):
fill_event(e)
yield e
def fill_all_events(*args, **kwargs):
events = func(*args, **kwargs)
for event in events:
fill_event(event)
return events
