def from_levelb(cls, levelb, parent=''):
packets, idb_versions = GenericProduct.getLeveL0Packets(levelb)
control = Control()
control['scet_coarse'] = packets.get('scet_coarse')
control['scet_fine'] = packets.get('scet_fine')
control['index'] = np.arange(len(control)).astype(get_min_uint(len(control)))
# When the packets are parsed empty packets are dropped but in LB we don't parse so this
# is not known need to compare control and levelb.control and only use matching rows
if len(levelb.control) > len(control):
matching_index = np.argwhere(
np.in1d(levelb.control['scet_coarse'], np.array(packets.get('scet_coarse'))))
control['raw_file'] = levelb.control['raw_file'][matching_index].reshape(-1)
control['packet'] = levelb.control['packet'][matching_index].reshape(-1)
else:
control['raw_file'] = levelb.control['raw_file'].reshape(-1)
control['packet'] = levelb.control['packet'].reshape(-1)
control['parent'] = parent
tmp = Data()
tmp.add_basic(name='ubsd_counter', nix='NIX00285', packets=packets, dtype=np.uint32)
tmp.add_basic(name='pald_counter', nix='NIX00286', packets=packets, dtype=np.uint32)
tmp.add_basic(name='num_flares', nix='NIX00294', packets=packets, dtype=np.uint16)
colnames = ['start_scet_coarse', 'end_scet_coarse', 'highest_flareflag', 'tm_byte_volume',
'average_z_loc', 'average_y_loc', 'processing_mask']
flares = Data()
if tmp['num_flares'].sum() > 0:
flares.add_basic(name='start_scet_coarse', nix='NIX00287', packets=packets)
flares.add_basic(name='end_scet_coarse', nix='NIX00288', packets=packets)
flares.add_basic(name='highest_flareflag', nix='NIX00289', packets=packets,
dtype=np.byte)
flares.add_basic(name='tm_byte_volume', nix='NIX00290', packets=packets, dtype=np.byte)
flares.add_basic(name='average_z_loc', nix='NIX00291', packets=packets, dtype=np.byte)
flares.add_basic(name='average_y_loc', nix='NIX00292', packets=packets, dtype=np.byte)
flares.add_basic(name='processing_mask', nix='NIX00293', packets=packets, dtype=np.byte)
tmp_data = defaultdict(list)
start = 0
for i, (ubsd, pald, n_flares) in enumerate(tmp):
end = start + n_flares
if n_flares == 0:
tmp_data['control_index'].append(i)
tmp_data['coarse'].append(control['scet_coarse'][i])
tmp_data['fine'].append(control['scet_fine'][i])
tmp_data['ubsd'].append(ubsd)
tmp_data['pald'].append(pald)
for name in colnames:
tmp_data[name].append(0)
else:
tmp_data['control_index'].append([i] * n_flares)
tmp_data['coarse'].append([control['scet_coarse'][i]] * n_flares)
tmp_data['fine'].append([control['scet_fine'][i]] * n_flares)
ubsd['ubsd']([ubsd] * n_flares)
pald['pald'].append([pald] * n_flares)
for name in colnames:
tmp_data[name].extend(flares[name][start:end])
start = end
data = Data(tmp_data)
data['time'] = SCETime(tmp_data['coarse'], tmp_data['fine'])
data['timedel'] = SCETimeDelta(np.full(len(data), 0), np.full(len(data), 0))
data.remove_columns(['coarse', 'fine'])
return cls(service_type=packets.service_type,
service_subtype=packets.service_subtype,
ssid=packets.ssid,
control=control,
data=data,
idb_versions=idb_versions,
packets=packets)
def from_levelb(cls, levelb, parent=''):
packets, idb_versions, control = ScienceProduct.from_levelb(
levelb, parent=parent)
data = Data()
data['start_time'] = packets.get_value('NIX00404').astype(np.uint32)
data.add_meta(name='start_time', nix='NIX00404', packets=packets)
data.add_basic(name='rcr',
nix='NIX00401',
attr='value',
packets=packets,
dtype=np.ubyte)
# NIX00405 in BSD is 1 indexed
data['integration_time'] = packets.get_value('NIX00405').astype(
np.uint16)
data.add_meta(name='integration_time', nix='NIX00405', packets=packets)
data.add_data('pixel_masks', _get_pixel_mask(packets, 'NIXD0407'))
data.add_data('detector_masks', _get_detector_mask(packets))
data['triggers'] = np.array(
[packets.get_value(f'NIX00{i}') for i in range(408, 424)]).T
data['triggers'].dtype = get_min_uint(data['triggers'])
data['triggers'].meta = {
'NIXS': [f'NIX00{i}' for i in range(408, 424)]
}
data.add_basic(name='num_samples',
nix='NIX00406',
packets=packets,
dtype=np.uint16)
num_detectors = 32
num_energies = 32
num_pixels = 12
# Data
tmp = dict()
tmp['pixel_id'] = np.array(packets.get_value('NIXD0158'), np.ubyte)
tmp['detector_id'] = np.array(packets.get_value('NIXD0153'), np.ubyte)
tmp['channel'] = np.array(packets.get_value('NIXD0154'), np.ubyte)
tmp['continuation_bits'] = np.array(packets.get_value('NIXD0159'),
np.ubyte)
control['energy_bin_mask'] = np.full((1, 32), False, np.ubyte)
all_energies = set(tmp['channel'])
control['energy_bin_mask'][:, list(all_energies)] = True
# Find contiguous time indices
unique_times = np.unique(data['start_time'])
time_indices = np.searchsorted(unique_times, data['start_time'])
counts_1d = packets.get_value('NIX00065')
end_inds = np.cumsum(data['num_samples'])
start_inds = np.hstack([0, end_inds[:-1]])
dd = [(tmp['pixel_id'][s:e], tmp['detector_id'][s:e],
tmp['channel'][s:e], counts_1d[s:e])
for s, e in zip(start_inds.astype(int), end_inds)]
counts = np.zeros(
(len(unique_times), num_detectors, num_pixels, num_energies),
np.uint32)
for i, (pid, did, cid, cc) in enumerate(dd):
counts[time_indices[i], did, pid, cid] = cc
data['detector_masks'] = fix_detector_mask(control,
data['detector_masks'])
sub_index = np.searchsorted(data['start_time'], unique_times)
data = data[sub_index]
data['time'] = control["time_stamp"][0] \
+ data['start_time'] + data['integration_time'] / 2
data['timedel'] = SCETimeDelta(data['integration_time'])
data['counts'] = (counts * u.ct).astype(get_min_uint(counts))
# data.add_meta(name='counts', nix='NIX00065', packets=packets)
data['control_index'] = control['index'][0]
data.remove_columns(['start_time', 'integration_time', 'num_samples'])
return cls(service_type=packets.service_type,
service_subtype=packets.service_subtype,
ssid=packets.ssid,
control=control,
data=data,
idb_versions=idb_versions)