def __call__(self, RA, Dec, energy):
self.ncalls += 1
RA0 = self.parameters['RA0'].value
Dec0 = self.parameters['Dec0'].value
radius = self.parameters['radius'].getValue(energy)
return np.power(180 / np.pi, 2) * 1. / (np.pi * radius ** 2) * (angsep(RA, Dec, RA0, Dec0) < radius)
def matchsorted(ra, dec, ra1, dec1, tol):
""" Find closest ra,dec within tol to a target in an ra-sorted list of ra,dec.
Arguments:
ra - Right Ascension decimal degrees (numpy sorted in ascending order)
dec - Declination decimal degrees (numpy array)
ra1 - RA to match (scalar, decimal degrees)
ra1 - Dec to match (scalar, decimal degrees)
tol - Matching tolerance in decimal degrees.
Returns:
ibest - index of the best match within tol; -1 if no match within tol
sep - separation (defaults to tol if no match within tol)
"""
i1 = searchsorted(ra, ra1 - tol) - 1
i2 = searchsorted(ra, ra1 + tol) + 1
if i1 < 0:
i1 = 0
sep = angsep.angsep(ra[i1:i2], dec[i1:i2], ra1, dec1)
# print "tolerance ",tol
indices = argsort(sep)
# print sep
if sep[indices[0]] > tol:
return -1, tol
ibest = indices[0] + i1
return ibest, sep[indices[0]]
def __call__(self,RA,Dec,energy):
self.ncalls += 1
RA0 = self.parameters['RA0'].value
Dec0 = self.parameters['Dec0'].value
sigma = self.parameters['sigma'].getValue(energy)
return np.maximum( np.power(180/np.pi,2)*1./(2 * np.pi * sigma**2) * np.exp(-0.5 * np.power(angsep(RA,Dec,RA0,Dec0),2)/sigma**2), 1e-30)
