def test_map_data_ranges():
map_data_table = compare_survey_footprints.load_map_data(TEST_MAP_PATH)
for column in map_data_table.columns:
map_data = map_data = getattr(map_data_table, column.name)
print(column.name, map_data.min(), map_data.max())
def test_NObsPriority():
runName = os.path.split(TEST_DB_PATH)[-1].replace('.db', '')
opsim_db = maf.OpsimDatabase(TEST_DB_PATH)
map_data_table = compare_survey_footprints.load_map_data(TEST_MAP_PATH)
#print(map_data_table.columns)
mapName = 'combined_map'
tau_obs = 20.0
log = open('./results/test_data.log', 'w')
nLoop = 10
for i in range(0, nLoop, 1):
log.write('mapName: ' + mapName + '\n')
log.write('runName: ' + runName + '\n')
log.write('tau_obs: ' + str(tau_obs) + '\n')
FoM = compare_survey_footprints.FiguresOfMerit()
bundleDict = compare_survey_footprints.calcNVisits(
opsim_db, runName, mapName)
rootName = 'GalplaneFootprintMetric_' + mapName + '_'
#outputName = rootName+'NObsPriority'
outputName = rootName + 'Tau_' + str(tau_obs).replace('.', '_')
log.write('OutputName: ' + outputName + '\n')
metricData = bundleDict[outputName].metricValues
log.write('metricData: ' + repr(metricData) + '\n')
rubin_visibility_zone = compare_survey_footprints.calc_rubin_visibility(
bundleDict, runName)
log.write('rubin_visibility_zone: ' + repr(rubin_visibility_zone) +
'\n')
map_data = getattr(map_data_table, mapName)
log.write('map_data: ' + repr(map_data) + '\n')
desired_healpix = compare_survey_footprints.calc_desired_survey_map(
mapName, map_data, rubin_visibility_zone)
log.write('N survey pixels: ' + str(len(desired_healpix)) + '\n')
#log.write('Desired survey pixels: '+repr(desired_healpix)+'\n')
FoM = compare_survey_footprints.calcFootprintOverlap(
runName, mapName, tau_obs, desired_healpix, bundleDict, FoM)
log.write('Overlap pixels: ' + str(FoM.overlap_healpix) + '\n')
log.write('Overlap percent: ' + str(FoM.overlap_percent) + '\n')
log.write('Missing pixels: ' + str(FoM.missing_healpix) + '\n')
log.write('Missing percent: ' + str(FoM.missing_percent) + '\n')
idx = np.argwhere(np.isnan(metricData))
log.write('NaN values: ' + repr(idx) + '\n')
log.write('metricData entries: ' + repr(metricData[idx]) + '\n')
log.write('Metric sum values: ' + repr(metricData.sum()) + '\n')
log.write('-------------------------------------------\n')
log.close()
def time_per_filter():
params = get_args()
# Load the current OpSim database
runName = os.path.split(params['opSim_db_file'])[-1].replace('.db', '')
opsim_db = maf.OpsimDatabase(params['opSim_db_file'])
# Load the Galactic Plane Survey footprint map data
map_data_table = compare_survey_footprints.load_map_data(
params['map_file_path'])
print('Total number of pixels in map: ' + str(len(map_data_table)))
# Start logfile
logfile = open(
os.path.join(output_dir, runName + '_time_per_filter_metric_data.txt'),
'w')
logfile.write(
'runName mapName filter mean(fexpt_ratio) stddev(fexpt_ratio) npix_obs %desired_pixels\n'
)
# Loop over all science maps:
for mapName in SCIENCE_MAPS:
map_data = getattr(map_data_table, mapName)
# Compute metrics
bundleDict = calc_filter_metric(opsim_db, runName, mapName)
print(bundleDict.keys())
# Calculate the Rubin visibility zone:
rubin_visibility_zone = compare_survey_footprints.calc_rubin_visibility(
bundleDict, runName)
# Determine the HEALpix index of the desired science survey region,
# taking the Rubin visbility zone into account:
desired_healpix = compare_survey_footprints.calc_desired_survey_map(
mapName, map_data, rubin_visibility_zone)
eval_filters_by_region(params, bundleDict, runName, mapName, map_data,
desired_healpix)
logfile.close()
def eval_nobs_priority_function():
params = get_args()
# Load the current OpSim database
runName = os.path.split(params['opSim_db_file'])[-1].replace('.db', '')
opsim_db = maf.OpsimDatabase(params['opSim_db_file'])
# Load the Galactic Plane Survey footprint map data
map_data_table = compare_survey_footprints.load_map_data(
params['map_file_path'])
mapName = 'combined_map'
map_data = getattr(map_data_table, mapName)
# Compute metric data:
bundleDict = calcMetrics(opsim_db, runName, mapName)
# Plot the number of visits per HEALpixel as a function of space and
# scientific priority:
plot_3d_healpix_nvis_priority(runName, bundleDict, map_data)
def test_metric_calculation():
runName = os.path.split(TEST_DB_PATH)[-1].replace('.db', '')
opsim_db = maf.OpsimDatabase(TEST_DB_PATH)
map_data_table = compare_survey_footprints.load_map_data(TEST_MAP_PATH)
#print(map_data_table.columns)
mapName = 'combined_map'
tau_obs = 11.0
tau_var = tau_obs * 5.0
log = open('./cadence_results/test_data.log', 'w')
nLoop = 10
for i in range(0, nLoop, 1):
log.write('mapName: ' + mapName + '\n')
log.write('runName: ' + runName + '\n')
log.write('tau_obs: ' + str(tau_obs) + '\n')
FoM = eval_survey_cadence.TimeFiguresOfMerit()
bundleDict = eval_survey_cadence.calc_cadence_metrics(
opsim_db, runName, mapName)
outputName1 = 'GalPlaneVisitIntervalsTimescales_' + mapName + '_Tau_' + str(
tau_obs).replace('.', '_')
outputName2 = 'GalPlaneSeasonGapsTimescales_' + mapName + '_Tau_' + str(
tau_var).replace('.', '_')
metric1_data = bundleDict[outputName1].metricValues
metric2_data = bundleDict[outputName2].metricValues
np.savetxt(
os.path.join('./cadence_results/',
outputName1 + '_run' + str(i) + '.txt'), metric1_data)
np.savetxt(
os.path.join('./cadence_results/',
outputName2 + '_run' + str(i) + '.txt'), metric2_data)
log.write('OutputName: ' + outputName1 + '\n')
log.write('OutputName: ' + outputName2 + '\n')
log.write('metricData 1: ' + repr(metric1_data) + '\n')
log.write('metricData 2: ' + repr(metric2_data) + '\n')
rubin_visibility_zone = compare_survey_footprints.calc_rubin_visibility(
bundleDict, runName)
log.write('rubin_visibility_zone: ' + repr(rubin_visibility_zone) +
'\n')
log.write('Npix rubin_visibility_zone: ' +
str(len(rubin_visibility_zone)) + '\n')
map_data = getattr(map_data_table, mapName)
log.write('map_data: ' + repr(map_data) + '\n')
log.write('Npix map_data: ' + str(len(map_data)) + '\n')
desired_healpix = compare_survey_footprints.calc_desired_survey_map(
mapName, map_data, rubin_visibility_zone)
log.write('N survey pixels: ' + str(len(desired_healpix)) + '\n')
log.write('Desired survey pixels: ' + repr(desired_healpix[0:10]) +
'\n')
FoM = eval_survey_cadence.eval_metrics_by_region(bundleDict,
map_data,
runName,
mapName,
tau_obs,
rubin_visibility_zone,
desired_healpix,
datalog=log)
log.write('VIM: ' + str(FoM.sumVIM) + '\n')
log.write('Percent VIM: ' + str(FoM.percent_sumVIM) + '\n')
log.write('SVGM: ' + str(FoM.sumSVGM) + '\n')
log.write('Percent SVGM: ' + str(FoM.percent_sumSVGM) + '\n')
log.write('VIP: ' + str(FoM.sumVIP) + '\n')
log.write('Percent VIP: ' + str(FoM.percent_sumVIP) + '\n')
idx = np.argwhere(np.isnan(metric1_data))
log.write('NaN values metric 1: ' + repr(idx) + '\n')
log.write('metricData entries: ' + repr(metric1_data[idx]) + '\n')
log.write('Metric sum values: ' + repr(metric1_data.sum()) + '\n')
log.write('-------------------------------------------\n')
log.close()