def correlate_fermi_psf(image, max_offset, resolution=0.1, energy = 'None', energy_band=[10, 500]):
from astropy.coordinates import Angle
from astropy.units import Quantity
from gammapy.datasets import FermiGalacticCenter
from gammapy.irf import EnergyDependentTablePSF
# Parameters
filename = FermiGalacticCenter.filenames()['psf']
pixel_size = Angle(resolution, 'deg')
offset_max = Angle(max_offset, 'deg')
if energy == 'None':
energy_band = Quantity(energy_band, 'GeV')
fermi_psf = EnergyDependentTablePSF.read(filename)
psf = fermi_psf.table_psf_in_energy_band(energy_band=energy_band, spectral_index=2.5)
else:
energy = Quantity(energy, 'GeV')
fermi_psf = EnergyDependentTablePSF.read(filename)
psf = fermi_psf.table_psf_at_energy(energy=energy)
psf.normalize()
kernel = psf.kernel(pixel_size=pixel_size, offset_max=offset_max)
kernel_image = kernel.value/kernel.value.sum()
# TODO: Write unit test (this will be useful):
#kernel_image_integral = kernel_image.sum() * pixel_size.to('radian').value ** 2
#print('Kernel image integral: {0}'.format(kernel_image_integral))
#print('shape: {0}'.format(kernel_image.shape))
return convolve(image, kernel_image, mode='constant')
def correlate_fermi_psf(image,
max_offset,
resolution=0.1,
energy='None',
energy_band=[10, 500]):
from astropy.coordinates import Angle
from astropy.units import Quantity
from gammapy.datasets import FermiGalacticCenter
from gammapy.irf import EnergyDependentTablePSF
# Parameters
filename = FermiGalacticCenter.filenames()['psf']
pixel_size = Angle(resolution, 'deg')
offset_max = Angle(max_offset, 'deg')
if energy == 'None':
energy_band = Quantity(energy_band, 'GeV')
fermi_psf = EnergyDependentTablePSF.read(filename)
psf = fermi_psf.table_psf_in_energy_band(energy_band=energy_band,
spectral_index=2.5)
else:
energy = Quantity(energy, 'GeV')
fermi_psf = EnergyDependentTablePSF.read(filename)
psf = fermi_psf.table_psf_at_energy(energy=energy)
psf.normalize()
kernel = psf.kernel(pixel_size=pixel_size, offset_max=offset_max)
kernel_image = kernel.value / kernel.value.sum()
# TODO: Write unit test (this will be useful):
#kernel_image_integral = kernel_image.sum() * pixel_size.to('radian').value ** 2
#print('Kernel image integral: {0}'.format(kernel_image_integral))
#print('shape: {0}'.format(kernel_image.shape))
return convolve(image, kernel_image, mode='constant')
def main(self, figure, subplot):
filename = FermiGalacticCenter.filenames()['counts']
self.fits_figure = FITSFigure(filename,
hdu=1,
figure=figure,
subplot=subplot)
self.fits_figure.show_colorscale(vmin=1, vmax=10, cmap='afmhot')
self.fits_figure.ticks.set_xspacing(2)
from gammapy.irf import EnergyDependentTablePSF
from gammapy.image import make_empty_image, catalog_image, binary_disk
from gammapy.image.utils import cube_to_image, solid_angle
from gammapy.data import SpectralCube
from gammapy.image.utils import WCS
from gammapy.spectrum.flux_point import _energy_lafferty_power_law
# *** PREPARATION ***
# Parameters
CORRELATION_RADIUS = 3 # pix
SIGNIFICANCE_THRESHOLD = 5
MASK_DILATION_RADIUS = 0.3
psf_file = FermiGalacticCenter.filenames()['psf']
psf = EnergyDependentTablePSF.read(psf_file)
# *** LOADING INPUT ***
# Counts must be provided as a counts ImageHDU
flux_file = raw_input('Flux Map: ')
exposure_file = raw_input('Exposure Map: ')
spec_ind = input('Spectral Index (for reprojection): ')
flux_hdu = fits.open(flux_file)[1]
flux_wcs = WCS(flux_hdu.header)
energy_flux = Quantity([_energy_lafferty_power_law(10000, 500000, spec_ind)],
'MeV')
flux_data = np.zeros((1, 1800, 3600))
flux_data[0] = Quantity(flux_hdu.data, '')
flux_spec_cube = SpectralCube(data=flux_data, wcs=flux_wcs, energy=energy_flux)
from gammapy.irf import EnergyDependentTablePSF
from gammapy.image import make_empty_image, catalog_image, binary_disk
from gammapy.image.utils import cube_to_image, solid_angle
from gammapy.data import SpectralCube
from gammapy.image.utils import WCS
from gammapy.spectrum.flux_point import _energy_lafferty_power_law
# *** PREPARATION ***
# Parameters
CORRELATION_RADIUS = 3 # pix
SIGNIFICANCE_THRESHOLD = 5
MASK_DILATION_RADIUS = 0.3
psf_file = FermiGalacticCenter.filenames()["psf"]
psf = EnergyDependentTablePSF.read(psf_file)
# *** LOADING INPUT ***
# Counts must be provided as a counts ImageHDU
flux_file = raw_input("Flux Map: ")
exposure_file = raw_input("Exposure Map: ")
spec_ind = input("Spectral Index (for reprojection): ")
flux_hdu = fits.open(flux_file)[1]
flux_wcs = WCS(flux_hdu.header)
energy_flux = Quantity([_energy_lafferty_power_law(10000, 500000, spec_ind)], "MeV")
flux_data = np.zeros((1, 1800, 3600))
flux_data[0] = Quantity(flux_hdu.data, "")
flux_spec_cube = SpectralCube(data=flux_data, wcs=flux_wcs, energy=energy_flux)
from gammapy.irf import EnergyDependentTablePSF
from gammapy.image import make_empty_image, catalog_image, binary_disk
from gammapy.image.utils import cube_to_image, solid_angle
from gammapy.data import SpectralCube
from gammapy.image.utils import WCS
from gammapy.spectrum.flux_point import _energy_lafferty_power_law
# *** PREPARATION ***
# Parameters
CORRELATION_RADIUS = 3 # pix
SIGNIFICANCE_THRESHOLD = 5
MASK_DILATION_RADIUS = 0.3
psf_file = FermiGalacticCenter.filenames()['psf']
psf = EnergyDependentTablePSF.read(psf_file)
# *** LOADING INPUT ***
# Counts must be provided as a counts ImageHDU
flux_file = raw_input('Flux Map: ')
exposure_file = raw_input('Exposure Map: ')
spec_ind = input('Spectral Index (for reprojection): ')
flux_hdu = fits.open(flux_file)[1]
flux_wcs = WCS(flux_hdu.header)
energy_flux = Quantity([_energy_lafferty_power_law(10000, 500000, spec_ind)], 'MeV')
flux_data = np.zeros((1, 101, 2001))
flux_data[0] = Quantity(flux_hdu.data, '')
flux_spec_cube = SpectralCube(data=flux_data, wcs=flux_wcs, energy=energy_flux)
"""Test npred model image computation. """ from astropy.coordinates import Angle from gammapy.datasets import FermiGalacticCenter from gammapy.utils.energy import EnergyBounds from gammapy.irf import EnergyDependentTablePSF from gammapy.cube import SkyCube, compute_npred_cube, convolve_cube filenames = FermiGalacticCenter.filenames() flux_cube = SkyCube.read(filenames['diffuse_model']) exposure_cube = SkyCube.read(filenames['exposure_cube']) psf = EnergyDependentTablePSF.read(filenames['psf']) flux_cube = flux_cube.reproject_to(exposure_cube) energy_bounds = EnergyBounds([10, 30, 100, 500], 'GeV') npred_cube = compute_npred_cube(flux_cube, exposure_cube, energy_bounds) offset_max = Angle(1, 'deg') npred_cube_convolved = convolve_cube(npred_cube, psf, offset_max)
def main(self, figure, subplot):
filename = FermiGalacticCenter.filenames()['counts']
self.fits_figure = FITSFigure(filename, hdu=1, figure=figure, subplot=subplot)
self.fits_figure.show_colorscale(vmin=1, vmax=10, cmap='afmhot')
self.fits_figure.ticks.set_xspacing(2)
def main(self, figure, box):
filename = FermiGalacticCenter.filenames()['counts']
self.fits_figure = FITSFigure(filename, figure=figure, subplot=box)
self.fits_figure.show_colorscale(vmin=1, vmax=10)
