def test_05_set_n_random_sources(self):
n = 5
fluxes = np.random.random(n)
sim = ObservedBound(self.nside, self.nsets, self.ncrs)
sim.set_sources(n, fluxes=fluxes)
self.assertTrue(sim.sources.shape[1] == n)
self.assertTrue(np.allclose(fluxes, sim.source_fluxes))
def test_06_set_n_sources(self):
v_src = np.random.rand(30).reshape((3, 10))
fluxes = np.random.random(10)
sim = ObservedBound(self.nside, self.nsets, self.ncrs)
sim.set_sources(v_src, fluxes=fluxes)
self.assertTrue(np.allclose(v_src, sim.sources))
self.assertTrue(np.allclose(fluxes, sim.source_fluxes))
def test_16_high_nside(self):
nside_high = 256
sim = ObservedBound(nside_high, nsets=self.nsets, ncrs=self.ncrs)
self.assertTrue(sim.crs['nside'] == nside_high)
self.assertTrue(sim.crs.nside() == nside_high)
sim.arrival_setup(1.)
self.assertTrue(np.max(sim.crs['pixel']) >= 0.8 * sim.npix)
def test_08_isotropy(self):
sim = ObservedBound(self.nside, self.nsets, self.ncrs)
sim.arrival_setup(0.)
crs = sim.get_data(convert_all=True)
x = np.abs(np.mean(crs['vecs'][0]))
y = np.abs(np.mean(crs['vecs'][1]))
z = np.abs(np.mean(crs['vecs'][2]))
self.assertTrue((x < 0.03) & (y < 0.03) & (z < 0.03))
def test_17_energy_rigidity_set(self):
ncrs = 100
e = 19.5
sim = ObservedBound(self.nside, self.nsets, ncrs)
sim.set_energy(e * np.ones((self.nsets, ncrs)))
sim.set_charges(2)
sim.set_rigidity_bins(np.linspace(17., 20.48, 175))
self.assertTrue((sim.crs['log10e'] == e).all())
def test_20_exposure_issue(self):
sim = ObservedBound(nside=4, nsets=nsets, ncrs=ncrs)
sim.apply_exposure(a0=-35.25, zmax=60)
sim.arrival_setup(0.)
crs = sim.get_data(convert_all=True)
_, dec = coord.vec2ang(coord.gal2eq(crs['vecs'].reshape(3, -1)))
self.assertTrue(np.sum(coord.exposure_equatorial(dec, a0=-35.25, zmax=60) <= 0) == 0)
def test_09_exposure(self):
sim = ObservedBound(self.nside, self.nsets, self.ncrs)
sim.apply_exposure()
sim.arrival_setup(0.)
crs = sim.get_data(convert_all=True)
vecs_eq = coord.gal2eq(coord.ang2vec(np.hstack(crs['lon']), np.hstack(crs['lat'])))
lon_eq, lat_eq = coord.vec2ang(vecs_eq)
self.assertTrue(np.abs(np.mean(lon_eq)) < 0.05)
self.assertTrue((np.mean(lat_eq) < -0.5) & (np.mean(lat_eq) > - 0.55))
def test_18_energy_spectra(self):
nsets = 100
sim = ObservedBound(self.nside, nsets, self.ncrs)
log10e_power_3 = sim.set_energy(log10e_min=19., log10e_max=21., energy_spectrum='power_law', gamma=-3)
ebin = 0.1
for e in np.arange(19.1, 20.1, ebin):
sum_low = np.sum((log10e_power_3 >= e-ebin) & (log10e_power_3 < e))
sum_high = np.sum((log10e_power_3 >= e) & (log10e_power_3 < e+ebin))
self.assertTrue(sum_low > sum_high)
sim2 = ObservedBound(self.nside, nsets, self.ncrs)
log10e_power_4 = sim2.set_energy(log10e_min=19., log10e_max=21., energy_spectrum='power_law', gamma=-4)
# higher energies for flatter spectrum
self.assertTrue(np.mean(log10e_power_3) > np.mean(log10e_power_4))
sim3 = ObservedBound(self.nside, nsets, self.ncrs)
log10e_auger_fit = sim3.set_energy(log10e_min=19., log10e_max=21., energy_spectrum='auger_fit')
self.assertTrue(np.mean(log10e_power_3) > np.mean(log10e_auger_fit))
self.assertTrue(np.mean(log10e_power_4) < np.mean(log10e_auger_fit))
def test_22_shuffle(self):
sim = ObservedBound(self.nside, self.nsets, self.ncrs)
src_vecs = np.array([1, 1, 1])
src_pix = hpt.vec2pix(sim.nside, src_vecs)
sim.set_sources(src_vecs[:, np.newaxis])
sim.arrival_setup(fsig=0.1)
crs = sim.get_data(convert_all=False, shuffle=True)
self.assertTrue(np.all(src_pix == crs['pixel'][sim.signal_label]))
self.assertTrue(np.all(src_pix == crs['pixel'][crs['signal_label'].astype(bool)]))
def test_15_exposure(self):
nsets = 100
sim = ObservedBound(self.nside, nsets, self.ncrs)
sim.apply_exposure(a0=-35.25, zmax=60)
sim.arrival_setup(0.2)
crs = sim.get_data(convert_all=True)
lon, lat = np.hstack(crs['lon']), np.hstack(crs['lat'])
ra, dec = coord.vec2ang(coord.gal2eq(coord.ang2vec(lon, lat)))
exp = coord.exposure_equatorial(dec, a0=-35.25, zmax=60)
self.assertTrue((exp > 0).all())
def test_07_smear_sources_dynamically(self):
sim = ObservedBound(self.nside, self.nsets, self.ncrs)
sim.set_energy(log10e_min=19.)
sim.set_charges('AUGER')
sim.set_sources(1)
sim.set_rigidity_bins(np.arange(17., 20.5, 0.02))
sim.smear_sources(delta=0.1, dynamic=True)
sim.arrival_setup(1.)
crs = sim.get_data(convert_all=True)
rigs = sim.rigidities
rig_med = np.median(rigs)
vecs1 = coord.ang2vec(crs['lon'][rigs >= rig_med], crs['lat'][rigs >= rig_med])
vecs2 = coord.ang2vec(crs['lon'][rigs < rig_med], crs['lat'][rigs < rig_med])
# Higher rigidities experience higher deflections
self.assertTrue(np.mean(coord.angle(vecs1, sim.sources)) < np.mean(coord.angle(vecs2, sim.sources)))
def test_10_charge(self):
sim = ObservedBound(self.nside, self.nsets, self.ncrs)
charge = 2
sim.set_charges(charge)
self.assertTrue(np.all(sim.crs['charge'] == charge))
def test_11_xmax_setup(self):
sim1 = ObservedBound(self.nside, self.nsets, self.ncrs)
sim1.set_energy(19.)
sim1.set_charges(2)
sim1.set_xmax('stable')
check1 = (sim1.crs['xmax'] > 500) & (sim1.crs['xmax'] < 1200)
sim2 = ObservedBound(self.nside, self.nsets, self.ncrs)
sim2.set_energy(19.)
sim2.set_charges(2)
sim2.set_xmax('stable')
check2 = (sim2.crs['xmax'] > 500) & (sim2.crs['xmax'] < 1200)
sim3 = ObservedBound(self.nside, self.nsets, self.ncrs)
sim3.set_energy(19.)
sim3.set_charges(2)
sim3.set_xmax('empiric')
check3 = (sim3.crs['xmax'] > 500) & (sim3.crs['xmax'] < 1200)
sim4 = ObservedBound(self.nside, self.nsets, self.ncrs)
sim4.set_energy(19.)
sim4.set_charges(2)
sim4.set_xmax('double')
check4 = (sim4.crs['xmax'] > 500) & (sim4.crs['xmax'] < 1200)
self.assertTrue(check1.all() and check2.all() and check3.all() and check4.all())
def test_04_set_energy_charge_arrays(self):
sim = ObservedBound(self.nside, self.nsets, self.ncrs)
log10e = np.random.random(size=self.shape)
charge = np.random.randint(0, 10, size=self.shape)
sim.set_energy(log10e_min=log10e)
sim.set_charges(charge=charge)
crs = sim.get_data()
self.assertTrue(np.allclose(crs['log10e'], log10e) and np.allclose(crs['charge'], charge))
sim2 = ObservedBound(self.nside, self.nsets, self.ncrs)
log10e = np.random.random(self.ncrs)
charge = np.random.random(self.ncrs)
sim2.set_energy(log10e)
sim2.set_charges(charge)
self.assertTrue(np.allclose(sim2.crs['log10e'], log10e) and np.allclose(sim2.crs['charge'], charge))
sim3 = ObservedBound(self.nside, self.nsets, self.ncrs)
log10e = np.random.random(self.nsets)
charge = np.random.random(self.nsets)
with self.assertRaises(Exception):
sim3.set_energy(log10e)
sim3.set_charges(log10e)
sim4 = ObservedBound(self.nside, self.nsets, self.ncrs)
sim4.set_charges({'h': 0.5, 'he': 0.25, 'n': 0.24, 'si': 0.01})
self.assertTrue(np.abs(np.sum(sim4.crs['charge'] == 1) / float(self.nsets * self.ncrs) - 0.5) < 0.02)
self.assertTrue(np.abs(np.sum(sim4.crs['charge'] == 2) / float(self.nsets * self.ncrs) - 0.25) < 0.02)
self.assertTrue(np.abs(np.sum(sim4.crs['charge'] == 7) / float(self.nsets * self.ncrs) - 0.25) < 0.02)
self.assertTrue(np.abs(np.sum(sim4.crs['charge'] == 14) / float(self.nsets * self.ncrs) - 0.01) < 0.01)
def test_03_keyword_setup(self):
sim = ObservedBound(self.nside, self.nsets, self.ncrs)
sim.set_energy(log10e_min=19.)
sim.set_charges(charge='mixed')
sim.set_xmax('double')
sim.set_sources(sources='sbg')
sim.smear_sources(delta=0.1)
sim.apply_exposure()
sim.arrival_setup(fsig=0.4)
crs = sim.get_data(convert_all=True)
self.assertEqual(crs['pixel'].shape, crs['lon'].shape, crs['log10e'].shape)
def test_21_convert_all(self):
sim = ObservedBound(nside=4, nsets=nsets, ncrs=ncrs)
sim.arrival_setup(0.)
crs = sim.get_data(convert_all=False)
keys = crs.keys()
self.assertTrue('vecs' not in keys and 'lon' not in keys and 'lat' not in keys)
vecs = crs['vecs'] # automatic from pixel center
sim.convert_pixel('angles') # converts pixel to lon / lat
crs = sim.get_data(convert_all=False)
keys = crs.keys()
self.assertTrue('vecs' not in keys and 'lon' in keys and 'lat' in keys)
_lon, _lat = coord.vec2ang(vecs)
self.assertTrue(np.mean(abs(crs['lon'] - _lon) < 0.5))
self.assertTrue(np.mean(abs(crs['lat'] - _lat) < 0.5))
self.assertTrue(np.mean(abs(crs['lon'] - _lon) > 0))
self.assertTrue(np.mean(abs(crs['lat'] - _lat) > 0))
sim = ObservedBound(nside=4, nsets=nsets, ncrs=ncrs)
sim.apply_exposure(a0=-35.25, zmax=60)
sim.arrival_setup(0.)
crs = sim.get_data(convert_all=True)
keys = crs.keys()
self.assertTrue('vecs' in keys and 'lon' in keys and 'lat' in keys)
def test_12_xmax_mass(self):
sim1 = ObservedBound(self.nside, self.nsets, self.ncrs)
sim2 = ObservedBound(self.nside, self.nsets, self.ncrs)
sim1.set_energy(19.)
sim2.set_energy(19.)
sim1.set_charges('equal')
sim2.set_charges(26)
sim1.set_xmax('double')
sim2.set_xmax('double')
# Xmax of iron should be smaller (interact higher in atmosphere)
self.assertTrue(np.mean(sim1.crs['xmax']) > np.mean(sim2.crs['xmax']))
def test_02_nsets(self):
sim = ObservedBound(self.nside, self.nsets, self.ncrs)
self.assertEqual(sim.nsets, self.nsets)
def test_19_apply_uncertainties(self):
sim = ObservedBound(self.nside, self.nsets, self.ncrs)
log10e = sim.set_energy(log10e_min=19., log10e_max=21., energy_spectrum='power_law', gamma=-3)
sim.set_charges('mixed')
xmax = sim.set_xmax()
sim.set_sources(10)
sim.set_rigidity_bins(np.arange(17., 20.5, 0.02))
sim.smear_sources(delta=0.1, dynamic=True)
sim.arrival_setup(1.)
vecs = hpt.pix2vec(sim.nside, np.hstack(sim.crs['pixel']))
sim.apply_uncertainties(err_e=0.1, err_a=1, err_xmax=10)
# check that array are not equal but deviations are smaller than 5 sigma
self.assertTrue(not (log10e == sim.crs['log10e']).all())
self.assertTrue((np.abs(10**(log10e - 18) - 10**(sim.crs['log10e'] - 18)) < 5*0.1*10**(log10e - 18)).all())
self.assertTrue(not (xmax == sim.crs['xmax']).all())
self.assertTrue((np.abs(xmax - sim.crs['xmax']) < 50).all())
vec_unc = coord.ang2vec(np.hstack(sim.crs['lon']), np.hstack(sim.crs['lat']))
self.assertTrue(not (coord.angle(vecs, vec_unc) == 0).all())
self.assertTrue((coord.angle(vecs, vec_unc) < np.deg2rad(10)).all())
def test_13_xmax_energy(self):
sim1 = ObservedBound(self.nside, self.nsets, self.ncrs)
sim2 = ObservedBound(self.nside, self.nsets, self.ncrs)
sim1.set_energy(20. * np.ones(self.shape))
sim2.set_energy(19. * np.ones(self.shape))
sim1.set_charges(1)
sim2.set_charges(1)
sim1.set_xmax('double')
sim2.set_xmax('double')
# Xmax for higher energy is bigger
self.assertTrue(np.mean(sim1.crs['xmax']) > np.mean(sim2.crs['xmax']))
def test_14_lensing_map(self):
lens_path = os.path.dirname(os.path.realpath(__file__)) + '/toy-lens/jf12-regular.cfg'
toy_lens = gamale.Lens(lens_path)
nside = toy_lens.nside
sim = ObservedBound(nside, self.nsets, self.ncrs)
sim.set_energy(19.*np.ones(self.shape))
sim.set_charges(1)
sim.set_xmax('empiric')
sim.set_sources('gamma_agn')
sim.lensing_map(toy_lens)
# Xmax for higher energy is bigger
self.assertTrue(sim.lensed)
self.assertTrue(np.shape(sim.cr_map) == (1, sim.npix))
self.assertAlmostEqual(np.sum(sim.cr_map), 1.)
self.assertTrue(np.min(sim.cr_map) < np.max(sim.cr_map))
def test_01_n_cosmic_rays(self):
sim = ObservedBound(self.nside, self.nsets, self.ncrs)
self.assertEqual(sim.ncrs, self.ncrs)