def test_01_pix2ang(self):
pix = np.random.randint(0, self.npix, self.stat)
phi, theta = hpt.pix2ang(self.nside, pix)
phi_range = (phi >= -np.pi).all() and (phi <= np.pi).all()
theta_range = (theta >= -np.pi / 2.).all() and (theta <=
np.pi / 2.).all()
self.assertTrue(phi_range and theta_range)
def test_ang2pix_ring(self):
# ensure nside = 1 << 23 is correctly calculated
# by comparing the original theta phi are restored.
# NOTE: nside needs to be sufficiently large!
id = hpt.ang2pix(1048576 * 8, self.phi0, self.theta0, nest=False)
phi1, theta1 = hpt.pix2ang(1048576 * 8, id, nest=False)
np.testing.assert_array_almost_equal(theta1, self.theta0, decimal=5)
np.testing.assert_array_almost_equal(phi1, self.phi0, decimal=5)
def test_ang2pix_nest(self):
# ensure nside = 1 << 23 is correctly calculated
# by comparing the original theta phi are restored.
# NOTE: nside needs to be sufficiently large!
# NOTE: with Healpy_Base this will fail because nside
# is limited to 1 << 13 with Healpy_Base.
id = hpt.ang2pix(1048576 * 8, self.phi0, self.theta0, nest=True)
phi1, theta1 = hpt.pix2ang(1048576 * 8, id, nest=True)
np.testing.assert_array_almost_equal(theta1, self.theta0)
np.testing.assert_array_almost_equal(phi1, self.phi0)
def _direction_transformation(self, similar_key, orig_key):
"""
Helper function to get values stored under a different physical key in the correctly
transformed way specifically only for directions
"""
nside = self.general_object_store['nside'] if 'nside' in self.keys() else 64
store = self.shape_array if similar_key in list(self.shape_array.dtype.names) else self.general_object_store
if orig_key == 'vecs':
if ('lon' in similar_key) or ('lat' in similar_key):
return hpt.ang2vec(store['lon'], store['lat'])
return hpt.pix2vec(nside, store[similar_key])
if ('pix' in orig_key):
if 'pix' in similar_key:
return store[similar_key]
if similar_key == 'vecs':
return hpt.vec2pix(nside, store['vecs'])
return hpt.ang2pix(nside, store['lon'], store['lat'])
if similar_key == 'vecs':
lon, lat = hpt.vec2ang(store['vecs'])
else:
lon, lat = hpt.pix2ang(nside, store[similar_key])
return lon if orig_key == 'lon' else lat
print("Test: module cosmic_rays.py")
# This module provides a data container for cosmic ray observables and can be used
# to simply visualize, share, save and load data in an efficient way. There are
# two classes, the CosmicRaysBase and the CosmicRaysSets.
# If you just have a single cosmic ray set you want to use the ComicRaysBase. You can
# set arbitrary content in the container. Objects with shape (self.crs) will be
# stored in an internal array called 'shape_array', all other data in a
# dictionary called 'general_object_store'.
nside = 64
npix = hpt.nside2npix(nside)
ncrs = 5000
exposure = hpt.exposure_pdf(nside)
lon, lat = hpt.pix2ang(nside, hpt.rand_pix_from_map(exposure, n=ncrs))
crs = cosmic_rays.CosmicRaysBase(ncrs) # Initialize cosmic ray container
# you can set arbitrary content in the container. Objects with different shape
# than (ncrs) will be stored in an internal dictionary called 'general_object_store'
crs['lon'], crs['lat'] = lon, lat
crs['date'] = 'today'
crs['log10e'] = auger.rand_energy_from_auger(log10e_min=19, n=ncrs)
crs.set('vecs', coord.ang2vec(lon, lat)) # another possibility to set content
crs.keys() # will print the keys that are existing
# Save, load and plot cosmic ray base container
opath = 'cr_base_container.npz'
crs.save(opath)
crs_load = cosmic_rays.CosmicRaysBase(opath)
crs_load.plot_heatmap(opath='cr_base_healpy.png')
crs_load.plot_eventmap(opath='cr_base_eventmap.png')