def setUp(self):
self.test_dir = os.path.dirname(os.path.realpath(__file__)) + '/'
self.blmequ = sv.read_real_alm(self.test_dir + 'blm5.bin')
self.blmax = 5
self.freq = 150. / 300. * 299.792458 #my correct answers are computed with c=300,so im rescaing freq here to compensate
self.zenithequ = sv.ctos(
np.fromfile(self.test_dir + 'zenith.bin', dtype='float32'))[1:]
self.zenithequ[0] = np.pi / 2 - self.zenithequ[0]
self.zenithequ = np.array(self.zenithequ)[::-1]
self.blvequ = np.fromfile(self.test_dir + 'blv.bin', dtype='float32')
self.correct_BB = sv.read_alm(self.test_dir + 'BB47.bin')
self.correct_cm = np.fromfile(self.test_dir + 'cm47.bin',
dtype='complex64')
self.correct_result = np.fromfile(
self.test_dir + 'final47.bin', dtype='complex64'
) # * (len(self.correct_cm))**0.5 #correct result did not use correct normalization n**0.5 in fourier
self.nside = 16
healpix = np.zeros(12 * self.nside**2)
healpix[420] = 1
healpix[752] = 1
self.alm = sv.convert_healpy_alm(hp.sphtfunc.map2alm(healpix),
3 * self.nside - 1)
self.vs = sv.Visibility_Simulator()
self.vs.initial_zenith = self.zenithequ
self.vs.Blm = sv.expand_real_alm(self.blmequ)
def test_speed(self):
self.test_dir = os.path.dirname(os.path.realpath(__file__)) + '/'
self.blmequ = sv.read_real_alm(self.test_dir + 'bx125.195.bin')
self.blmax = 5
self.freq = 125.195#my correct answers are computed with c=300,so im rescaing freq here to compensate
self.zenithequ = sv.ctos(np.fromfile(self.test_dir + 'zenith.bin', dtype = 'float32'))[1:]
self.zenithequ[0] = np.pi/2 - self.zenithequ[0]
self.zenithequ = np.array(self.zenithequ)[::-1]
self.correct_result = np.loadtxt(self.test_dir + 'Revised_Location_Visibilties_for_21_m_south_21_m_east_0_m_up_xx_pol_125.195_MHz.dat')
self.correct_result = self.correct_result[:-1, 1] + 1j * self.correct_result[:-1, 2]
self.nside = 128
self.vs = sv.Visibility_Simulator()
self.vs.initial_zenith = self.zenithequ
self.vs.Blm = sv.expand_real_alm(self.blmequ)
self.rot = np.fromfile(self.test_dir + 'x5rot.bin', dtype = 'float32').reshape((3,3))
nside = self.nside
print "Reading fits...",
sys.stdout.flush()
pca1 = hp.fitsfunc.read_map(self.test_dir + '/../data/gsm1.fits' + str(nside))
pca2 = hp.fitsfunc.read_map(self.test_dir + '/../data/gsm2.fits' + str(nside))
pca3 = hp.fitsfunc.read_map(self.test_dir + '/../data/gsm3.fits' + str(nside))
gsm = 422.952*(0.307706*pca1+-0.281772*pca2+0.0123976*pca3)
print "Done reading"
sys.stdout.flush()
equatorial_GSM = np.zeros(12*nside**2,'float')
#rotate sky map
print "Rotating map...",
sys.stdout.flush()
for i in range(12*nside**2):
ang = hp.rotator.Rotator(coord='cg')(hpf.pix2ang(nside,i))
pixindex, weight = hpf.get_neighbours(nside,ang[0],ang[1])
for pix in range(len(pixindex)):
equatorial_GSM[i] += weight[pix]*gsm[pixindex[pix]]
print "Done rotating"
sys.stdout.flush()
print "Creating map alm...",
sys.stdout.flush()
self.alm = sv.convert_healpy_alm(hp.sphtfunc.map2alm(equatorial_GSM), 3 * nside - 1)
print "Done alm"
sys.stdout.flush()
print "Computing visibilities...",
sys.stdout.flush()
timer = time.time()
self.result = self.vs.calculate_visibility(sv.expand_real_alm(self.alm), d=self.rot.dot(np.array([21.0,21.0,0.0])), freq=self.freq, nt=len(self.correct_result), L = 3*self.nside-1, verbose = True)
print "done", (time.time() - timer)/60, 'min'
sys.stdout.flush()
#print len(self.result), np.argmax(np.real(self.result)) - np.argmax(np.real(self.correct_result)), np.argmax(np.imag(self.result)) - np.argmax(np.imag(self.correct_result))
plt.plot(np.real(self.result), 'r--', np.real(self.correct_result), 'b--')
plt.show()
plt.plot(np.imag(self.result), 'r--', np.imag(self.correct_result), 'b--')
plt.show()
def setUp(self):
self.test_dir = os.path.dirname(os.path.realpath(__file__)) + '/'
self.blmequ = sv.read_real_alm(self.test_dir + 'blm5.bin')
self.blmax = 5
self.freq = 150./300.*299.792458#my correct answers are computed with c=300,so im rescaing freq here to compensate
self.zenithequ = sv.ctos(np.fromfile(self.test_dir + 'zenith.bin', dtype = 'float32'))[1:]
self.zenithequ[0] = np.pi/2 - self.zenithequ[0]
self.zenithequ = np.array(self.zenithequ)[::-1]
self.blvequ = np.fromfile(self.test_dir + 'blv.bin', dtype = 'float32')
self.correct_BB = sv.read_alm(self.test_dir + 'BB47.bin')
self.correct_cm = np.fromfile(self.test_dir + 'cm47.bin', dtype = 'complex64')
self.correct_result = np.fromfile(self.test_dir + 'final47.bin', dtype = 'complex64')# * (len(self.correct_cm))**0.5 #correct result did not use correct normalization n**0.5 in fourier
self.nside = 16
healpix = np.zeros(12*self.nside**2)
healpix[420] = 1
healpix[752] = 1
self.alm = sv.convert_healpy_alm(hp.sphtfunc.map2alm(healpix), 3 * self.nside - 1)
self.vs = sv.Visibility_Simulator()
self.vs.initial_zenith = self.zenithequ
self.vs.Blm = sv.expand_real_alm(self.blmequ)
def setUp(self):
self.test_dir = os.path.dirname(os.path.realpath(__file__)) + '/'
self.blmequ = sv.read_real_alm(self.test_dir + 'bx125.195.bin')
self.blmax = 23
self.pol = 'xx'
beam_healpixs = {}
self.freq = 158.008 #my correct answers are computed with c=300,so im rescaing freq here to compensate
self.zenithequ = sv.ctos(
np.fromfile(self.test_dir + 'zenith.bin', dtype='float32'))[1:]
self.zenithequ[0] = np.pi / 2 - self.zenithequ[0]
self.zenithequ = np.array(self.zenithequ)[::-1]
self.rot = np.fromfile(self.test_dir + 'x5rot.bin',
dtype='float32').reshape(
(3, 3)) #fine tune rotation for ant array
self.correct_result = np.loadtxt(
self.test_dir +
'Revised_Location_Visibilties_for_15_m_south_21_m_east_0_m_up_xx_pol_158.008_MHz.dat'
)
self.correct_result = self.correct_result[:-1,
1] + 1j * self.correct_result[:
-1,
2]
self.vs = sv.Visibility_Simulator()
self.vs.initial_zenith = np.array([0, 45.2977 * np.pi / 180
]) #self.zenithequ
for f in range(110, 200, 10):
beam_healpixs[f] = np.fromfile(
self.test_dir +
'../data/MWA_beam_in_healpix_horizontal_coor/nside=%i_freq=%i_%s.bin'
% ((self.blmax + 1) / 3, f, self.pol),
dtype='float32')
freqa = int(np.floor(self.freq / 10.) * 10)
freqb = freqa + 10
beam_healpix = beam_healpixs[freqa] + (self.freq - freqa) * (
beam_healpixs[freqb] - beam_healpixs[freqa]) / (
freqb - freqa) #linear interpolation
self.vs.import_beam(beam_healpix)
def setUp(self):
self.test_dir = os.path.dirname(os.path.realpath(__file__)) + '/'
self.blmequ = sv.read_real_alm(self.test_dir + 'bx125.195.bin')
self.blmax = 23
self.pol = 'xx'
beam_healpixs = {}
self.freq = 125.195#my correct answers are computed with c=300,so im rescaing freq here to compensate
self.zenithequ = sv.ctos(np.fromfile(self.test_dir + 'zenith.bin', dtype = 'float32'))[1:]
self.zenithequ[0] = np.pi/2 - self.zenithequ[0]
self.zenithequ = np.array(self.zenithequ)[::-1]
self.rot = np.fromfile(self.test_dir + 'x5rot.bin', dtype = 'float32').reshape((3,3))#fine tune rotation for ant array
self.correct_result = np.loadtxt(self.test_dir + 'Revised_Location_Visibilties_for_6_m_south_3_m_east_0_m_up_xx_pol_125.195_MHz.dat')
self.correct_result = self.correct_result[:-1, 1] + 1j * self.correct_result[:-1, 2]
self.vs = sv.Visibility_Simulator()
self.vs.initial_zenith = np.array([0,45.2977*np.pi/180])#self.zenithequ
for f in range(110,200,10):
beam_healpixs[f] = np.fromfile(self.test_dir + '../data/MWA_beam_in_healpix_horizontal_coor/nside=%i_freq=%i_%s.bin'%((self.blmax + 1)/3, f, self.pol), dtype='float32')
freqa = int(np.floor(self.freq/10.) * 10)
freqb = freqa + 10
beam_healpix = beam_healpixs[freqa] + (self.freq - freqa) * (beam_healpixs[freqb] - beam_healpixs[freqa]) / (freqb - freqa) #linear interpolation
self.vs.import_beam(beam_healpix)
