def evaluate(self, x, y, z, lon0, lat0, rdiff0, rinj, delta, b, piv, piv2):
lon, lat = x, y
energy = z
# energy in kev -> TeV.
# NOTE: the use of piv2 is necessary to preserve dimensional correctness: the logarithm can only be taken
# of a dimensionless quantity, so there must be a pivot there.
e_energy_piv2 = 17. * \
np.power(old_div(energy, piv2), 0.54 + 0.046 *
np.log10(old_div(energy, piv2)))
e_piv_piv2 = 17. * \
np.power(old_div(piv, piv2), 0.54 + 0.046 *
np.log10(old_div(piv, piv2)))
rdiff_c = rdiff0 * np.power(old_div(e_energy_piv2, e_piv_piv2), old_div((delta - 1.), 2.)) * \
np.sqrt(b * b / 8. / np.pi * 0.624 + 0.26 * np.power(1. + 0.0107 * e_piv_piv2, -1.5)) / \
np.sqrt(b * b / 8. / np.pi * 0.624 + 0.26 *
np.power(1. + 0.0107 * e_energy_piv2, -1.5))
rdiff_i = rdiff0 * rinj * \
np.power(old_div(e_energy_piv2, e_piv_piv2), old_div(delta, 2.))
rdiff = np.minimum(rdiff_c, rdiff_i)
angsep = angular_distance_fast(lon, lat, lon0, lat0)
pi = np.pi
rdiffs, angseps = np.meshgrid(rdiff, angsep)
return np.power(old_div(180.0, pi), 2) * 1.2154 / (pi * np.sqrt(pi) * rdiffs * (angseps + 0.06 * rdiffs)) * \
np.exp(old_div(-np.power(angseps, 2), rdiffs ** 2))
def evaluate(self, x, y, z, lon0, lat0, rdiff0, delta, b, piv, piv2, incl, elongation):
lon, lat = x, y
energy = z
# energy in kev -> TeV.
# NOTE: the use of piv2 is necessary to preserve dimensional correctness: the logarithm can only be taken
# of a dimensionless quantity, so there must be a pivot there.
e_energy_piv2 = 17. * \
np.power(old_div(energy, piv2), 0.54 + 0.046 *
np.log10(old_div(energy, piv2)))
e_piv_piv2 = 17. * \
np.power(old_div(piv, piv2), 0.54 + 0.046 *
np.log10(old_div(piv, piv2)))
try:
rdiff_a = rdiff0 * np.power(old_div(e_energy_piv2, e_piv_piv2), old_div((delta - 1.), 2.)) * \
np.sqrt(b * b / 8. / np.pi * 0.624 + 0.26 * np.power(1. + 0.0107 * e_piv_piv2, -1.5)) / \
np.sqrt(b * b / 8. / np.pi * 0.624 + 0.26 *
np.power(1. + 0.0107 * e_energy_piv2, -1.5))
except ValueError:
# This happens when using units, because astropy.units fails with the message:
# "ValueError: Quantities and Units may only be raised to a scalar power"
# Work around the problem with this loop, which is slow but using units is only for testing purposes or
# single calls, so it shouldn't matter too much
rdiff_a = np.array([(rdiff0 * np.power(old_div(e_energy_piv2, e_piv_piv2), x)).value for x in (delta - 1.) / 2. * np.sqrt(b * b / 8. / np.pi * 0.624 + 0.26 * np.power(1. + 0.0107 * e_piv_piv2, -1.5)) /
np.sqrt(b * b / 8. / np.pi * 0.624 + 0.26 * np.power(1. + 0.0107 * e_energy_piv2, -1.5))]) * rdiff0.unit
rdiff_b = rdiff_a * elongation
pi = np.pi
angsep = angular_distance_fast(lon, lat, lon0, lat0)
ang = np.arctan2(lat - lat0, (lon - lon0) *
np.cos(lat0 * np.pi / 180.))
theta = np.arctan2(old_div(np.sin(ang-incl*np.pi/180.),
elongation), np.cos(ang-incl*np.pi/180.))
rdiffs_a, thetas = np.meshgrid(rdiff_a, theta)
rdiffs_b, angseps = np.meshgrid(rdiff_b, angsep)
rdiffs = np.sqrt(rdiffs_a ** 2 * np.cos(thetas) **
2 + rdiffs_b ** 2 * np.sin(thetas) ** 2)
results = np.power(old_div(180.0, pi), 2) * 1.22 / (pi * np.sqrt(pi) * rdiffs_a * np.sqrt(
elongation) * (angseps + 0.06 * rdiffs)) * np.exp(old_div(-np.power(angseps, 2), rdiffs ** 2))
return results
def evaluate(self, x, y, z, lon0, lat0, rdiff0, delta, uratio, piv, piv2):
lon, lat = x, y
energy = z
# energy in kev -> TeV.
# NOTE: the use of piv2 is necessary to preserve dimensional correctness: the logarithm can only be taken
# of a dimensionless quantity, so there must be a pivot there.
e_energy_piv2 = 17. * np.power(
old_div(energy, piv2),
0.54 + 0.046 * np.log10(old_div(energy, piv2)))
e_piv_piv2 = 17. * np.power(
old_div(piv, piv2), 0.54 + 0.046 * np.log10(old_div(piv, piv2)))
try:
rdiff = rdiff0 * np.power(old_div(e_energy_piv2, e_piv_piv2), old_div((delta - 1.), 2.)) * \
np.sqrt(1. + uratio * np.power(1. + 0.0107 * e_piv_piv2, -1.5)) / \
np.sqrt(1. + uratio * np.power(1. + 0.0107 * e_energy_piv2, -1.5))
except ValueError:
# This happens when using units, because astropy.units fails with the message:
# "ValueError: Quantities and Units may only be raised to a scalar power"
# Work around the problem with this loop, which is slow but using units is only for testing purposes or
# single calls, so it shouldn't matter too much
rdiff = np.array([
(rdiff0 *
np.power(old_div(e_energy_piv2, e_piv_piv2), x)).value
for x in (delta - 1.) / 2. *
np.sqrt(1. +
uratio * np.power(1. + 0.0107 * e_piv_piv2, -1.5)) /
np.sqrt(1. +
uratio * np.power(1. + 0.0107 * e_energy_piv2, -1.5))
]) * rdiff0.unit
angsep = angular_distance_fast(lon, lat, lon0, lat0)
pi = np.pi
rdiffs, angseps = np.meshgrid(rdiff, angsep)
return np.power(old_div(180.0, pi), 2) * 1.2154 / (pi * np.sqrt(pi) * rdiffs * (angseps + 0.06 * rdiffs)) * \
np.exp(old_div(-np.power(angseps, 2), rdiffs ** 2))
def evaluate(self, x, y, z, K, lon0, lat0, *args):
lons = x
lats = y
energies = z
angsep = angular_distance_fast(lon0, lat0, lons, lats)
#if only one energy is passed, make sure we can iterate just once
if not isinstance(energies, np.ndarray):
energies = np.array(energies)
#transform energy from keV to MeV
#galprop likes MeV, 3ML likes keV
log_energies = np.log10(energies) - np.log10((u.MeV.to("keV")/u.keV).value)
#A = np.multiply(K, self._interpolate(lons, lats, log_energies, args)/(10**convert_val))
A = np.multiply(K, self._interpolate(log_energies, lons, lats, args)) #if templates are normalized no need to convert back
return A