def convert_obs_groups_binning_def_michi_to_default():
"""Convert observation groups binning definition "michi" to "default".
"""
# observation groups binning definition "michi"
# alt az bin edges definitions
altitude_edges = Angle(
[0, 20, 23, 27, 30, 33, 37, 40, 44, 49, 53, 58, 64, 72, 90], 'degree')
azimuth_edges = Angle([-90, 90, 270], 'degree')
# convert observation groups binning definition "michi" to "default"
list_obs_group_axis = [
ObservationGroupAxis('ALT', altitude_edges, fmt='edges'),
ObservationGroupAxis('AZ', azimuth_edges, fmt='edges')
]
obs_groups_michi = ObservationGroups(list_obs_group_axis)
print("Observation groups 'michi':")
print(obs_groups_michi.obs_groups_table)
# save
outfile = 'bg_observation_groups_michi.ecsv'
print('Writing {}'.format(outfile))
obs_groups_michi.write(outfile)
# lookup table: equivalences in group/file naming "defualt" <-> "michi"
# 3 columns: GROUP_ID, ALT_ID, AZ_ID
# 28 rows: 1 per GROUP_ID
lookup_obs_groups_michi = Table()
n_cols = 1 + len(list_obs_group_axis)
n_rows = obs_groups_michi.n_groups
lookup_obs_groups_michi['GROUP_ID'] = np.zeros(n_rows, dtype=np.int)
lookup_obs_groups_michi['ALT_ID'] = np.zeros(n_rows, dtype=np.int)
lookup_obs_groups_michi['AZ_ID'] = np.zeros(n_rows, dtype=np.int)
# loop over each observation group axis
count_groups = 0
for alt_id in np.arange(len(altitude_edges) - 1):
for az_id in np.arange(len(azimuth_edges) - 1):
lookup_obs_groups_michi['GROUP_ID'][count_groups] = count_groups
lookup_obs_groups_michi['ALT_ID'][count_groups] = alt_id
lookup_obs_groups_michi['AZ_ID'][count_groups] = az_id
count_groups += 1
print("lookup table:")
print(lookup_obs_groups_michi)
# save
outfile = 'lookup_obs_groups_michi.ecsv'
print('Writing {}'.format(outfile))
# `~astropy.io.ascii` always overwrites the file
ascii.write(lookup_obs_groups_michi,
outfile,
format='ecsv',
fast_writer=False)
def create_dummy_observation_grouping():
"""Define dummy observation grouping.
Define an observation grouping with only one group.
Returns
-------
obs_groups : `~gammapy.data.ObservationGroups`
Observation grouping.
"""
alt_axis = ObservationGroupAxis('ALT', ALT_RANGE, fmt='edges')
az_axis = ObservationGroupAxis('AZ', AZ_RANGE, fmt='edges')
obs_groups = ObservationGroups([alt_axis, az_axis])
obs_groups.obs_groups_table['GROUP_ID'][0] = GROUP_ID
return obs_groups
#get required runs
agnid=list(set(obsid)-set(LMCid)-set(SNid))
mylist=datastore.obs_list(agnid)
zen_ang=[o1.pointing_zen.value for o1 in mylist]
# Define the grouping
nbins=10
zenith_bins=[0,10,20,30,40,50,90]
#zenith_bins=[min(zen_ang), 10.0, 20.0, 30.0, 45.0, 60.0, max(zen_ang)]
zenith_bins=zenith_bins*u.deg
axes = [ObservationGroupAxis('ZEN_PNT', zenith_bins, fmt='edges')]
# Create the ObservationGroups object
obs_groups = ObservationGroups(axes)
# write it to file
filename = str(outdir + "/group-def.fits")
obs_groups.obs_groups_table.write(filename, overwrite=True)
obs_table_with_group_id = obs_groups.apply(datastore.obs_table.select_obs_id(agnid))
#gammacat exclusion mask
fil_gammacat="/Users/asinha/Gammapy-dev/gammapy-extra/datasets/catalogs/gammacat/gammacat.fits.gz"
cat = SourceCatalogGammaCat(filename=fil_gammacat)
exclusion_table = cat.table.copy()
exclusion_table.rename_column('ra', 'RA')
exclusion_table.rename_column('dec', 'DEC')
radius = exclusion_table['morph_sigma'].data
radius[np.isnan(radius)] = 0.3
def make_cubes(ereco, etrue, use_etrue, center):
tmpdir = os.path.expandvars('$GAMMAPY_EXTRA') + "/test_datasets/cube/data"
outdir = tmpdir
outdir2 = os.path.expandvars(
'$GAMMAPY_EXTRA') + '/test_datasets/cube/background'
if os.path.isdir("data"):
shutil.rmtree("data")
if os.path.isdir("background"):
shutil.rmtree("background")
Path(outdir2).mkdir()
ds = DataStore.from_dir("$GAMMAPY_EXTRA/datasets/hess-crab4-hd-hap-prod2")
ds.copy_obs(ds.obs_table, tmpdir)
data_store = DataStore.from_dir(tmpdir)
# Create a background model from the 4 crab run for the counts ouside the exclusion region. it's just for test, normaly you take 8000 thousands AGN runs to build this kind of model
axes = [ObservationGroupAxis('ZEN_PNT', [0, 49, 90], fmt='edges')]
obs_groups = ObservationGroups(axes)
obs_table_with_group_id = obs_groups.apply(data_store.obs_table)
obs_groups.obs_groups_table.write(outdir2 + "/group-def.fits",
overwrite=True)
# Exclusion sources table
cat = SourceCatalogGammaCat()
exclusion_table = cat.table
exclusion_table.rename_column('ra', 'RA')
exclusion_table.rename_column('dec', 'DEC')
radius = exclusion_table['morph_sigma']
radius.value[np.isnan(radius)] = 0.3
exclusion_table['Radius'] = radius
exclusion_table = Table(exclusion_table)
bgmaker = OffDataBackgroundMaker(data_store,
outdir2,
run_list=None,
obs_table=obs_table_with_group_id,
ntot_group=obs_groups.n_groups,
excluded_sources=exclusion_table)
bgmaker.make_model("2D")
bgmaker.smooth_models("2D")
bgmaker.save_models("2D")
bgmaker.save_models(modeltype="2D", smooth=True)
shutil.move(str(outdir2), str(outdir))
fn = outdir + '/background/group-def.fits'
hdu_index_table = bgmaker.make_total_index_table(
data_store=data_store,
modeltype='2D',
out_dir_background_model="background",
filename_obs_group_table=fn,
smooth=True)
fn = outdir + '/hdu-index.fits.gz'
hdu_index_table.write(fn, overwrite=True)
offset_band = Angle([0, 2.49], 'deg')
ref_cube_images = make_empty_cube(image_size=50,
energy=ereco,
center=center)
ref_cube_exposure = make_empty_cube(image_size=50,
energy=etrue,
center=center,
data_unit="m2 s")
data_store = DataStore.from_dir(tmpdir)
refheader = ref_cube_images.sky_image_ref.to_image_hdu().header
exclusion_mask = SkyMask.read(
'$GAMMAPY_EXTRA/datasets/exclusion_masks/tevcat_exclusion.fits')
exclusion_mask = exclusion_mask.reproject(reference=refheader)
# Pb with the load psftable for one of the run that is not implemented yet...
data_store.hdu_table.remove_row(14)
cube_maker = StackedObsCubeMaker(empty_cube_images=ref_cube_images,
empty_exposure_cube=ref_cube_exposure,
offset_band=offset_band,
data_store=data_store,
obs_table=data_store.obs_table,
exclusion_mask=exclusion_mask,
save_bkg_scale=True)
cube_maker.make_cubes(make_background_image=True, radius=10.)
obslist = [data_store.obs(id) for id in data_store.obs_table["OBS_ID"]]
ObsList = ObservationList(obslist)
mean_psf_cube = make_mean_psf_cube(image_size=50,
energy_cube=etrue,
center_maps=center,
center=center,
ObsList=ObsList,
spectral_index=2.3)
if use_etrue:
mean_rmf = make_mean_rmf(energy_true=etrue,
energy_reco=ereco,
center=center,
ObsList=ObsList)
filename_mask = 'exclusion_mask.fits'
filename_counts = 'counts_cube.fits'
filename_bkg = 'bkg_cube.fits'
filename_significance = 'significance_cube.fits'
filename_excess = 'excess_cube.fits'
if use_etrue:
filename_exposure = 'exposure_cube_etrue.fits'
filename_psf = 'psf_cube_etrue.fits'
filename_rmf = 'rmf.fits'
mean_rmf.write(filename_rmf, clobber=True)
else:
filename_exposure = 'exposure_cube.fits'
filename_psf = 'psf_cube.fits'
exclusion_mask.write(filename_mask, clobber=True)
cube_maker.counts_cube.write(filename_counts,
format="fermi-counts",
clobber=True)
cube_maker.bkg_cube.write(filename_bkg,
format="fermi-counts",
clobber=True)
cube_maker.significance_cube.write(filename_significance,
format="fermi-counts",
clobber=True)
cube_maker.excess_cube.write(filename_excess,
format="fermi-counts",
clobber=True)
cube_maker.exposure_cube.write(filename_exposure,
format="fermi-counts",
clobber=True)
mean_psf_cube.write(filename_psf, format="fermi-counts", clobber=True)
d1
d1.obs_table['OBS_ID']
d1
print d1
crab_pos = SkyCoord.from_name('crab')
crab_pos
datastore
datastore.table
datastore.Table
datastore.obs_table
datastore.obs_table["ZEN_PNT"]<20.0
from gammapy.data import ObservationGroups, ObservationGroupAxis
zenith = Angle([0, 30, 40, 50], 'deg')
ntels = [3, 4]
obs_groups = ObservationGroups([
ObservationGroupAxis('ZENITH', zenith, fmt='edges'),
ObservationGroupAxis('N_TELS', ntels, fmt='values'),
])
print(obs_groups.info)
obs1=obs_groups.apply(datastore.obs_table)
zenith = Angle([0, 30, 40, 50], 'deg')
ntels = [3, 4]
obs_groups = ObservationGroups([
ObservationGroupAxis('ZEN_PNT', zenith, fmt='edges'),
ObservationGroupAxis('N_TELS', ntels, fmt='values'),
])
obs_table
zenith = Angle([0, 30, 40, 50], 'deg')
ntels = [3, 4]
obs_groups = ObservationGroups([
ObservationGroupAxis('ZEN_PNT', zenith, fmt='edges'),
