def get_bot_amp_data(run, schema_name, field_name):
"""
Get the amp values for the specified run, schema_name, and field_name
for BOT data.
"""
results = siteUtils.ETResults(run=run)
return results.get_amp_data(schema_name, field_name)
def _get_gains_from_run(self, et_results_file):
if not os.path.isfile(et_results_file):
self.et_results = siteUtils.ETResults(self.run)
with open(et_results_file, 'wb') as fd:
pickle.dump(self.et_results, fd)
else:
with open(et_results_file, 'rb') as fd:
self.et_results = pickle.load(fd)
if self.verbose:
print("GetAmplifierGains: Using gains from run", self.run)
def test_plot_focal_plane(self):
"""
An operational test of generating a png image of the focal plane.
"""
run = '6549D'
results = siteUtils.ETResults(run)
gains = results.get_amp_data('fe55_BOT_analysis', 'gain')
fig = plt.figure(figsize=(12, 10))
ax = fig.add_subplot(1, 1, 1)
plot_focal_plane(ax, gains, camera=self.camera, z_range=(0.5, 1.2))
plt.savefig(self.pngfile)
def get_ts8_amp_data(schema_name, field_name):
"""
Get the amp values for the specified schema_name and field_name
(e.g., 'fe55_raft_analysis' and 'gain') for the good TS8 runs.
"""
raft_info = get_raft_slot_info()
amp_data = defaultdict(dict)
for raft_slot, (_, run) in raft_info.items():
df = siteUtils.ETResults(run=run)[schema_name]
for _, row in df.iterrows():
det_name = f'{raft_slot}_{row.slot}'
channel = 'C' + imutils.channelIds[row.amp]
amp_data[det_name][channel] = row[field_name]
if raft_slot in ts8_gain_scale_factors:
amp_data[det_name][channel] *= ts8_gain_scale_factors[
raft_slot]
return amp_data
def make_focal_plane_plots():
#
# Focal plane heat maps
#
fp_configs = {
'fe55_BOT_analysis':
(('gain', 'psf_sigma'), ('clipped_autoscale', (3, 5.5)),
('e-/ADU', 'micron'), (False, False), ('1', '1')),
'read_noise_BOT':
(('read_noise', ), ((0, 20), ), ('e-', ), (False, ), ('1', )),
'bright_defects_BOT':
(('bright_pixels', 'bright_columns'), (None, None), (None, None),
(True, True), ('1', '1')),
'dark_defects_BOT': (('dark_pixels', 'dark_columns'), (None, None),
(None, None), (True, True), ('1', '1')),
'dark_current_BOT': (('dark_current_95CL', ), ((0, 0.3), ),
('e-/pix/s', ), (False, ), ('1', )),
'dark_current_fit_BOT':
(('dark_current_slope', 'dark_current_intercept'), ((0, 0.1), (-1, 1)),
('e-/pix/s', 'e-/pix'), (False, False), ('1', '1')),
'traps_BOT': (('num_traps', ), (None, ), (None, ), (False, ), ('1', )),
'cte_BOT': (('cti_high_serial', 'cti_high_parallel', 'cti_low_serial',
'cti_low_parallel'), ((0, 1e-5), (0, 1e-5), (0, 1e-5),
(0, 1e-5)),
(None, None, None, None), (False, False, False, False),
('1e-6', '1e-6', '1e-6', '1e-6')),
'flat_pairs_BOT':
(('max_frac_dev', 'max_observed_signal', 'row_mean_var_slope',
'linearity_turnoff'), ((0, 0.05), (5e4, 2.e5), (0, 2), (5e4, 2.e5)),
(None, 'ADU', None, 'ADU'), (False, False, False, False), ('1', '1',
'1', '1')),
'ptc_BOT': (('ptc_gain', 'ptc_a00',
'ptc_turnoff'), ('clipped_autoscale', (0, 5e-6),
(5e4, 2e5)), ('e-/ADU', None, 'ADU'),
(False, False, False), ('1', '1', '1')),
'brighter_fatter_BOT': (('bf_xcorr', 'bf_ycorr'), ((-5, 5), (-5, 5)),
(None, None), (False, False), ('1', '1')),
'tearing_stats_BOT': (('tearing_detections', ), (None, ), (None, ),
(False, ), ('1', )),
'divisadero_tearing_BOT': (('divisadero_max_dev', ), ((0, 0.05), ),
(None, ), (False, ), ('1', ))
}
camera = camera_info.camera_object
run = siteUtils.getRunNumber()
acq_run = os.environ.get('LCATR_ACQ_RUN', None)
unit_id = siteUtils.getUnitId()
et_results = siteUtils.ETResults(run)
for schema_name, configs in fp_configs.items():
for column, z_range, units, use_log10, scale_factor in zip(*configs):
fig = plt.figure(figsize=(12, 10))
ax = fig.add_subplot(1, 1, 1)
try:
amp_data = et_results.get_amp_data(schema_name, column)
except KeyError:
print("No focal plane results for {}: {} in eTraveler.".format(
schema_name, column))
else:
if units is not None:
title = 'Run {}, {} ({})'.format(run, column, units)
else:
title = 'Run {}, {}'.format(run, column)
if acq_run is not None:
title += f' (acq {acq_run})'
plot_focal_plane(ax,
amp_data,
camera=camera,
z_range=z_range,
use_log10=use_log10,
scale_factor=scale_factor)
plt.title(title)
outfile = '{}_{}_{}.png'.format(unit_id, run, column)
plt.savefig(outfile)
# Histogram the amp-level data.
plt.figure()
hist_range = None if z_range == 'clipped_autoscale' \
else z_range
hist_amp_data(amp_data,
column,
hist_range=hist_range,
use_log10=use_log10,
scale_factor=scale_factor)
plt.title(title)
outfile = '{}_{}_{}_hist.png'.format(unit_id, run, column)
plt.savefig(outfile)