def make_image():
table = Table.read('acceptance_curve.fits')
table.pprint()
center = SkyCoord(83.63, 22.01, unit='deg').galactic
counts_image = make_empty_image(nxpix=1000, nypix=1000, binsz=0.01, xref=center.l.deg, yref=center.b.deg,
proj='TAN')
bkg_image = counts_image.copy()
data_store = DataStore.from_dir('$GAMMAPY_EXTRA/datasets/hess-crab4-hd-hap-prod2')
for events in data_store.load_all("events"):
center = events.pointing_radec.galactic
livetime = events.observation_live_time_duration
solid_angle = Angle(0.01, "deg") ** 2
counts_image.data += bin_events_in_image(events, counts_image).data
#interp_param = dict(bounds_error=False, fill_value=None)
acc_hdu = fill_acceptance_image(bkg_image.header, center, table["offset"], table["Acceptance"])
acc = Quantity(acc_hdu.data, table["Acceptance"].unit) * solid_angle * livetime
bkg_image.data += acc.decompose()
print(acc.decompose().sum())
counts_image.writeto("counts_image.fits", clobber=True)
bkg_image.writeto("bkg_image.fits", clobber=True)
def make_image():
table = Table.read('acceptance_curve.fits')
table.pprint()
center = SkyCoord(83.63, 22.01, unit='deg').galactic
counts_image = SkyMap.empty(nxpix=1000,
nypix=1000,
binsz=0.01,
xref=center.l.deg,
yref=center.b.deg,
proj='TAN').to_image_hdu()
bkg_image = counts_image.copy()
data_store = DataStore.from_dir(
'$GAMMAPY_EXTRA/datasets/hess-crab4-hd-hap-prod2')
for events in data_store.load_all("events"):
center = events.pointing_radec.galactic
livetime = events.observation_live_time_duration
solid_angle = Angle(0.01, "deg")**2
counts_image.data += bin_events_in_image(events, counts_image).data
# interp_param = dict(bounds_error=False, fill_value=None)
acc_hdu = fill_acceptance_image(bkg_image.header, center,
table["offset"], table["Acceptance"])
acc = Quantity(acc_hdu.data,
table["Acceptance"].unit) * solid_angle * livetime
bkg_image.data += acc.decompose()
print(acc.decompose().sum())
counts_image.writeto("counts_image_save.fits", clobber=True)
bkg_image.writeto("bkg_image_save.fits", clobber=True)
def make_bkg_cube(self, bkg_norm=True):
"""
Make the background image for one observation from a bkg model.
Parameters
----------
bkg_norm : bool
If true, apply the scaling factor from the number of counts
outside the exclusion region to the bkg image
"""
for i_E in range(len(self.energy_reco) - 1):
energy_band = Energy(
[self.energy_reco[i_E].value, self.energy_reco[i_E + 1].value],
self.energy_reco.unit)
table = self.bkg.acceptance_curve_in_energy_band(
energy_band=energy_band)
center = self.obs_center.galactic
bkg_hdu = fill_acceptance_image(self.header, center,
table["offset"],
table["Acceptance"],
self.offset_band[1])
bkg_image = Quantity(
bkg_hdu.data, table["Acceptance"].unit
) * self.bkg_cube.sky_image_ref.solid_angle() * self.livetime
self.bkg_cube.data[i_E, :, :] = bkg_image.decompose().value
if bkg_norm:
scale = self.background_norm_factor()
self.bkg_cube.data = scale * self.bkg_cube.data
if self.save_bkg_scale:
self.table_bkg_scale.add_row([self.obs_id, scale])
def make_bkg_cube(self, bkg_norm=True):
"""
Make the background image for one observation from a bkg model.
Parameters
----------
bkg_norm : bool
If true, apply the scaling factor from the number of counts
outside the exclusion region to the bkg image
"""
for i_E in range(len(self.energy_reco) - 1):
energy_band = Energy(
[self.energy_reco[i_E].value, self.energy_reco[i_E + 1].value],
self.energy_reco.unit)
table = self.bkg.acceptance_curve_in_energy_band(
energy_band=energy_band)
center = self.obs_center.galactic
bkg_hdu = fill_acceptance_image(self.header, center,
table["offset"],
table["Acceptance"],
self.offset_band[1])
bkg_image = Quantity(bkg_hdu.data, table[
"Acceptance"].unit) * self.bkg_cube.sky_image_ref.solid_angle() * self.livetime
self.bkg_cube.data[i_E, :, :] = bkg_image.decompose().value
if bkg_norm:
scale = self.background_norm_factor()
self.bkg_cube.data = scale * self.bkg_cube.data
if self.save_bkg_scale:
self.table_bkg_scale.add_row([self.obs_id, scale])
def _mags_to_flux(mag,
zpt_flux: units.Quantity = 3630.7805 * units.Jy,
mag_err=None):
"""
Convert a magnitude to mJy
Args:
mag (column): magnitude
zpt_flux (Quantity, optional): Zero point flux for the magnitude.
Assumes AB mags by default (i.e. zpt_flux = 3630.7805 Jy).
mag_err (float, optional): uncertainty in magnitude
Returns:
flux (column): flux in mJy
flux_err (column): if mag_err is given, a corresponding
flux_err is returned.
"""
# Data validation -- check for Jy
assert (type(zpt_flux) == units.Quantity) * (
zpt_flux.decompose().unit == units.kg /
units.s**2), "zpt_flux units should be Jy or with dimensions kg/s^2."
# Prepare output column
flux = mag.copy()
# Convert fluxes
badmags = mag < -10
flux[badmags] = -99.
flux[~badmags] = zpt_flux.value * 10**(-mag[~badmags] / 2.5)
if mag_err is not None:
flux_err = mag_err.copy()
baderrs = (mag_err < 0) | (mag_err == 999.)
flux_err[baderrs] = -99.
flux_err[~baderrs] = flux[~baderrs] * (10**(mag_err[~baderrs] / 2.5) -
1)
return flux, flux_err
else:
return flux
