print("main: building geometries")
polygon_params = defaults.polygon_params.copy()
polygon_params['n_double'] = 80
z_coarse = np.array([0., 3.])
#z_max = np.max(z_coarse)
z_max = 3.01
#z_fine = np.arange(0.0001,z_max,0.0001)
z_fine = np.linspace(0.001, z_max, 2)
print("main: building basis")
basis_params = defaults.basis_params.copy()
basis_params['n_bessel_oversample'] = 400000
basis_params['x_grid_size'] = 100000
r_max = C.D_comov(z_max)
k_cut = x_cut / r_max
k_tests = np.linspace(20. / r_max, k_cut, 25)
n_basis = np.zeros(k_tests.size)
variances = np.zeros((k_tests.size, z_coarse.size - 1, z_coarse.size - 1))
time4 = time()
basis = SphBasisK(r_max, C, k_cut, basis_params, l_ceil=l_max)
time5 = time()
time2 = time()
pixelated = True
if pixelated:
res_healpix = 9
max_n_pixels = 12 * (2**res_healpix)**2
#n_pixels = np.unique(np.hstack([np.logspace(3,np.log10(max_n_pixels),40).astype(np.int),np.linspace(1000,max_n_pixels,40).astype(np.int)]))
def test_half_sky():
"""do some tests with a half sky geo known results"""
#get dictionaries of parameters that various functions will need
cosmo = { 'Omegabh2':0.0222,
'Omegach2':0.1153,
'Omegab' :0.04283392714316876,
'Omegac' :0.22216607285683124,
'Omegamh2':0.13752999999999999,
'OmegaL' :0.735,
'OmegaLh2':0.38145113207547166,
'Omegam' :0.265,
'H0' :72.04034509047493,
'sigma8' : 0.8269877678406697, #from the code
'h' :0.7204034509047493,
'Omegak' : 0.0,
'Omegakh2': 0.0,
'Omegar' : 0.0,
'Omegarh2': 0.0,
'ns' : 0.9608,
'tau' : 0.081,
'Yp' :0.299,
'As' : 2.464*10**-9,
'LogAs' :-19.821479791275138,
'w' :-1.0,
'de_model':'constant_w',#dark energy model
'mnu' :0.}
cosmo['de_model'] = 'constant_w'
cosmo['wa'] = 0.
cosmo['w0'] = -1.
cosmo['w'] = -1.
p_space = 'jdem'
camb_params = defaults.camb_params.copy()
camb_params['force_sigma8'] = False
camb_params['maxkh'] = 100.
camb_params['kmax'] = 30.
camb_params['npoints'] = 10000
camb_params['pivot_scalar'] = 0.002
power_params = defaults.power_params.copy()
power_params.camb = camb_params
power_params.camb['accuracy'] = 1
#prior_params = defaults.prior_fisher_params.copy()
zs = np.array([0.0001,3.])
z_fine = np.linspace(0.0001,zs[-1],10000)
basis_params = defaults.basis_params.copy()
basis_params['n_bessel_oversample'] = 400000*10
#test with half sky using results calculated in mathematica
basis_params = defaults.basis_params.copy()
basis_params['n_bessel_oversample'] = 400000*10
C = CosmoPie(cosmo,p_space=p_space)
l_max = 4
x_cut = 10
z_max = z_fine[-1]+0.000001
r_max = C.D_comov(z_max)
k_cut = x_cut/r_max
geo1 = HalfSkyGeo(zs,C,z_fine)
P = MatterPower(C,power_params)
P.P_lin = 1./(P.k*r_max)
C.set_power(P)
basis = SphBasisK(r_max,C,k_cut,basis_params,l_ceil=l_max,needs_m=False)
basis2 = SphBasisK(r_max,C,k_cut,basis_params,l_ceil=l_max,needs_m=True)
ddbar = basis.get_ddelta_bar_ddelta_alpha(geo1,tomography=True)
ddbar2 = basis2.get_ddelta_bar_ddelta_alpha(geo1,tomography=True)
ddbar_got2 = basis.get_dO_I_ddelta_alpha(geo1,geo1.r_fine**2)*3./r_max**3
#ns = np.arange(1,ddbar.size+1)
cov_got = basis.get_covar_array()
cov_got2 = basis2.get_covar_array()
var_got = basis.get_variance(geo1)
var_got2 = basis2.get_variance(geo1)
cov_pred0 = np.array([[3.220393570704632e-11,-9.51309537893619e-12,9.955267964241254e-12],[-9.51309537893619e-12,5.937410951604845e-11,-1.2342996089442917e-11],[9.955267964241254e-12,-1.2342996089442917e-11,8.524795995567036e-11]])
cov_pred1 = np.array([[4.306831299006748e-11,-7.977015797357624e-12],[-7.977015797357624e-12,6.907871421795387e-11]])
cov_pred2 = np.array([[5.467066924435653e-11,-7.056047462103054e-12],[-7.056047462103054e-12,7.984696153964485e-11]])
cov_pred3 = np.array([[6.70079506270691e-11]])
cov_pred4 = np.array([[7.985214180284307e-11]])
cov_pred = np.zeros((ddbar.size,ddbar.size))
cov_pred[0:3,0:3] = cov_pred0
cov_pred[3:5,3:5] = cov_pred1
cov_pred[5:7,5:7] = cov_pred2
cov_pred[7,7] = cov_pred3
cov_pred[8,8] = cov_pred4
var_pred = np.dot(ddbar,np.dot(cov_pred,ddbar.T))
var_pred2 = np.dot(ddbar2,np.dot(cov_got2,ddbar2.T))
assert np.all(cov_got==cov_got.T)
assert np.all(cov_got2==cov_got2.T)
assert np.isclose(var_got[0,0],var_pred,atol=1.e-15,rtol=1.e-3)
assert np.isclose(var_got2[0,0],var_pred2,atol=1.e-15,rtol=1.e-3)
assert np.isclose(var_got2[0,0],var_pred,atol=1.e-15,rtol=1.e-3)
assert np.allclose(cov_pred,cov_got,atol=1.e-15,rtol=1.e-3)
assert np.allclose(ddbar,ddbar_got2,rtol=1.e-3,atol=1.e-15)
for itr in range(0,basis.C_id.shape[0]):
if basis.C_id[itr,0]>0 and np.mod(basis.C_id[itr,0],2)==0.:
assert ddbar[0,itr] == 0.
for itr in range(0,basis2.C_id.shape[0]):
if basis2.C_id[itr,0]>0 and np.mod(basis2.C_id[itr,0],2)==0.:
assert ddbar2[0,itr] == 0.
elif basis2.C_id[itr,2]!=0:
assert ddbar2[0,itr] == 0.
def test_full_sky():
"""do some tests with a full sky geo known results"""
#get dictionaries of parameters that various functions will need
#cosmo = defaults.cosmology_wmap.copy()
cosmo = { 'Omegabh2':0.02223,
'Omegach2':0.1153,
'Omegab' :0.04283392714316876,
'Omegac' :0.22216607285683124,
'Omegamh2':0.13752999999999999,
'OmegaL' :0.735,
'OmegaLh2':0.38145113207547166,
'Omegam' :0.265,
'H0' :72.04034509047493,
'sigma8' : 0.8269877678406697, #from the code
'h' :0.7204034509047493,
'Omegak' : 0.0,
'Omegakh2': 0.0,
'Omegar' : 0.0,
'Omegarh2': 0.0,
'ns' : 0.9608,
'tau' : 0.081,
'Yp' :0.299,
'As' : 2.464*10**-9,
'LogAs' :-19.821479791275138,
'w' :-1.0,
'de_model':'constant_w',#dark energy model
'mnu' :0.}
cosmo['de_model'] = 'constant_w'
cosmo['wa'] = 0.
cosmo['w0'] = -1.
cosmo['w'] = -1.
p_space = 'jdem'
camb_params = defaults.camb_params.copy()
camb_params['force_sigma8'] = False
camb_params['maxkh'] = 100.
camb_params['kmax'] = 30.
camb_params['npoints'] = 10000
camb_params['pivot_scalar'] = 0.002
power_params = defaults.power_params.copy()
power_params.camb = camb_params
power_params.camb['accuracy'] = 1
#prior_params = defaults.prior_fisher_params.copy()
zs = np.array([0.0001,3.])
z_fine = np.linspace(0.0001,zs[-1],10000)
basis_params = defaults.basis_params.copy()
basis_params['n_bessel_oversample'] = 400000*10
C = CosmoPie(cosmo,p_space=p_space)
l_max = 0
x_cut = 10*np.pi
z_max = z_fine[-1]+0.000001
r_max = C.D_comov(z_max)
k_cut = x_cut/r_max
P = MatterPower(C,power_params)
C.set_power(P)
geo1 = FullSkyGeo(zs,C,z_fine)
basis = SphBasisK(r_max,C,k_cut,basis_params,l_ceil=l_max,needs_m=True)
ddbar = basis.get_ddelta_bar_ddelta_alpha(geo1,tomography=True)
ns = np.arange(1,ddbar.size+1)
ddbar_pred = -3./(2.*np.pi**(5./2.))*(-1)**ns/ns**2
assert np.allclose(ddbar,ddbar_pred)
cov_pred = np.zeros((ns.size,ns.size))
xs = P.k*r_max
P_in = P.get_matter_power(np.array([0.]),pmodel='linear')[:,0]
for i1 in range(0,ns.size):
for i2 in range(i1,ns.size):
integrand1 = 8.*np.pi**3*(-1)**(ns[i1]+ns[i2])*ns[i1]**2*ns[i2]**2/r_max**3*np.sin(xs)**2/((ns[i1]**2*np.pi**2-xs**2)*(ns[i2]**2*np.pi**2-xs**2))
cov_pred[i1,i2] = np.trapz(integrand1*P_in,xs)
if i1!=i2:
cov_pred[i2,i1] = cov_pred[i1,i2]
cov_got = basis.get_covar_array()
var_pred = np.dot(ddbar_pred.T,np.dot(cov_pred,ddbar_pred))
var_got = basis.get_variance(geo1)
assert np.all(cov_got==cov_got.T)
assert np.allclose(basis.C_id[:,1],ns*np.pi/r_max)
assert np.allclose(cov_pred,cov_got,atol=1.e-15,rtol=1.e-3)
assert np.isclose(var_got[0,0],var_pred,atol=1.e-15,rtol=1.e-3)
ddbar_got2 = basis.get_dO_I_ddelta_alpha(geo1,geo1.r_fine**2)*3./r_max**3
assert np.allclose(ddbar,ddbar_got2,rtol=1.e-3)
def test_rotational_invariance():
"""test invariance of results under global rotations"""
camb_params = { 'npoints':2000,
'minkh':1.1e-4,
'maxkh':1.476511342960e+02,
'kmax':1.476511342960e+02,
'leave_h':False,
'force_sigma8':False,
'return_sigma8':False,
'accuracy':1,
'pivot_scalar':0.002
}
print("main: building cosmology")
power_params = defaults.power_params.copy()
power_params.camb = camb_params
power_params.camb['accuracy'] = 1
power_params.camb['maxkh'] = 100.
power_params.camb['kmax'] = 30.
power_params.camb['npoints'] = 1000
C = CosmoPie(defaults.cosmology.copy(),p_space='jdem')
P_lin = mps.MatterPower(C,power_params)
C.set_power(P_lin)
l_max = 23
x_cut = 30.
print("main: building geometries")
polygon_params = defaults.polygon_params.copy()
polygon_params['n_double'] = 80
z_coarse = np.array([0.2,1.,2.,3.])
zs_lsst = np.linspace(0.,1.2,3)
#z_max = np.max(z_coarse)
#z_fine = np.arange(0.0001,z_max,0.0001)
z_fine = np.linspace(0.001,3.,500)
z_max = z_fine[-1]+0.001
print("main: building basis")
basis_params = defaults.basis_params.copy()
basis_params['n_bessel_oversample'] = 400000
basis_params['x_grid_size'] = 100000
r_max = C.D_comov(z_max)
k_cut = x_cut/r_max
basis = SphBasisK(r_max,C,k_cut,basis_params,l_ceil=l_max)
geo1 = WFIRSTGeo(z_coarse,C,z_fine,l_max,polygon_params)#HalfSkyGeo(z_coarse,C,z_fine)
geo2 = LSSTGeo(zs_lsst,C,z_fine,l_max,polygon_params)#HalfSkyGeo(z_coarse,C,z_fine)
geo1_rot1 = AlmRotGeo(geo1,C,z_coarse,z_fine,np.array([0.,np.pi/2.,np.pi]),polygon_params['n_double'])
geo1_rot2 = AlmRotGeo(geo1_rot1,C,z_coarse,z_fine,np.array([0.,np.pi/2.,np.pi]),polygon_params['n_double'])
geo1_rot3 = AlmRotGeo(geo1_rot2,C,z_coarse,z_fine,np.array([0.005,1.2496,1.72]),polygon_params['n_double'])
geo2_rot1 = AlmRotGeo(geo2,C,zs_lsst,z_fine,np.array([0.,np.pi/2.,np.pi]),polygon_params['n_double'])
geo2_rot2 = AlmRotGeo(geo2_rot1,C,zs_lsst,z_fine,np.array([0.,np.pi/2.,np.pi]),polygon_params['n_double'])
geo2_rot3 = AlmRotGeo(geo2_rot2,C,zs_lsst,z_fine,np.array([0.005,1.2496,1.72]),polygon_params['n_double'])
assert np.allclose(geo1.get_alm_array(l_max),geo1_rot2.get_alm_array(l_max))
var_geo1 = basis.get_variance(geo1,k_cut_in=k_cut)
var_geo1_rot1 = basis.get_variance(geo1_rot1,k_cut_in=k_cut)
var_geo1_rot2 = basis.get_variance(geo1_rot2,k_cut_in=k_cut)
var_geo1_rot3 = basis.get_variance(geo1_rot3,k_cut_in=k_cut)
assert np.allclose(var_geo1,var_geo1_rot1,atol=1.e-20,rtol=1.e-8)
assert np.allclose(var_geo1,var_geo1_rot2,atol=1.e-20,rtol=1.e-8)
assert np.allclose(var_geo1,var_geo1_rot3,atol=1.e-20,rtol=1.e-8)
var_geo2 = basis.get_variance(geo2,k_cut_in=k_cut)
var_geo2_rot1 = basis.get_variance(geo2_rot1,k_cut_in=k_cut)
var_geo2_rot2 = basis.get_variance(geo2_rot2,k_cut_in=k_cut)
var_geo2_rot3 = basis.get_variance(geo2_rot3,k_cut_in=k_cut)
assert np.allclose(var_geo2,var_geo2_rot1,atol=1.e-20,rtol=1.e-8)
assert np.allclose(var_geo2,var_geo2_rot2,atol=1.e-20,rtol=1.e-8)
assert np.allclose(var_geo2,var_geo2_rot3,atol=1.e-20,rtol=1.e-8)
cosmo_par_list = np.array(['ns','Omegamh2','Omegabh2','OmegaLh2','LogAs','w'])
cosmo_par_eps = np.array([0.002,0.00025,0.0001,0.00025,0.1,0.01])
nz_params_wfirst_lens = defaults.nz_params_wfirst_lens.copy()
nz_params_wfirst_lens['i_cut'] = 26.3
nz_params_wfirst_lens['data_source'] = './data/CANDELS-GOODSS2.dat'
nz_wfirst_lens = NZWFirstEff(nz_params_wfirst_lens)
sw_params = defaults.sw_survey_params.copy()
lw_params = defaults.lw_survey_params.copy()
sw_observable_list = defaults.sw_observable_list.copy()
lw_observable_list = defaults.lw_observable_list.copy()
len_params = defaults.lensing_params.copy()
mf_params = defaults.hmf_params.copy()
mf_params['n_grid'] = 2000
mf_params['log10_min_mass'] = 10.
n_params_lsst = defaults.nz_params_lsst_use.copy()
n_params_lsst['i_cut'] = 24.1 #gold standard subset of LSST 1 year (10 year 25.3)
dn_params = defaults.dn_params.copy()
dn_params['nz_select'] = 'LSST'
dn_params['sigma0'] = 0.1
lw_param_list = np.array([{'dn_params':dn_params,'n_params':n_params_lsst,'mf_params':mf_params}])
prior_params = defaults.prior_fisher_params.copy()
sw_survey_geo1 = SWSurvey(geo1,'geo1',C,sw_params,cosmo_par_list,cosmo_par_eps,sw_observable_list,len_params,nz_wfirst_lens)
sw_survey_geo1_rot1 = SWSurvey(geo1_rot1,'geo1_rot1',C,sw_params,cosmo_par_list,cosmo_par_eps,sw_observable_list,len_params,nz_wfirst_lens)
sw_survey_geo1_rot2 = SWSurvey(geo1_rot2,'geo1_rot2',C,sw_params,cosmo_par_list,cosmo_par_eps,sw_observable_list,len_params,nz_wfirst_lens)
sw_survey_geo1_rot3 = SWSurvey(geo1_rot3,'geo1_rot3',C,sw_params,cosmo_par_list,cosmo_par_eps,sw_observable_list,len_params,nz_wfirst_lens)
survey_lw1 = LWSurvey(np.array([geo1,geo2]),'lw1',basis,C,lw_params,observable_list=lw_observable_list,param_list=lw_param_list)
survey_lw1_rot1 = LWSurvey(np.array([geo1_rot1,geo2_rot1]),'lw1',basis,C,lw_params,observable_list=lw_observable_list,param_list=lw_param_list)
survey_lw1_rot2 = LWSurvey(np.array([geo1_rot2,geo2_rot2]),'lw1',basis,C,lw_params,observable_list=lw_observable_list,param_list=lw_param_list)
survey_lw1_rot3 = LWSurvey(np.array([geo1_rot3,geo2_rot3]),'lw1',basis,C,lw_params,observable_list=lw_observable_list,param_list=lw_param_list)
SS_geo1 = SuperSurvey(np.array([sw_survey_geo1]),np.array([survey_lw1]),basis,C,prior_params,get_a=True,do_unmitigated=True,do_mitigated=True,include_sw=True)
SS_geo1_rot1 = SuperSurvey(np.array([sw_survey_geo1_rot1]),np.array([survey_lw1_rot1]),basis,C,prior_params,get_a=True,do_unmitigated=True,do_mitigated=True,include_sw=True)
SS_geo1_rot2 = SuperSurvey(np.array([sw_survey_geo1_rot2]),np.array([survey_lw1_rot2]),basis,C,prior_params,get_a=True,do_unmitigated=True,do_mitigated=True,include_sw=True)
SS_geo1_rot3 = SuperSurvey(np.array([sw_survey_geo1_rot3]),np.array([survey_lw1_rot3]),basis,C,prior_params,get_a=True,do_unmitigated=True,do_mitigated=True,include_sw=True)
for i in xrange(0,3):
for j in xrange(1,3):
assert np.allclose(SS_geo1.f_set_nopriors[i][j].get_covar(),SS_geo1_rot1.f_set_nopriors[i][j].get_covar(),atol=1.e-30,rtol=1.e-8)
assert np.allclose(SS_geo1.f_set_nopriors[i][j].get_covar(),SS_geo1_rot2.f_set_nopriors[i][j].get_covar(),atol=1.e-30,rtol=1.e-8)
assert np.allclose(SS_geo1.f_set_nopriors[i][j].get_covar(),SS_geo1_rot3.f_set_nopriors[i][j].get_covar(),atol=1.e-30,rtol=1.e-8)
a_geo1 = SS_geo1.multi_f.get_a_lw()
a_geo1_rot1 = SS_geo1_rot1.multi_f.get_a_lw()
a_geo1_rot2 = SS_geo1_rot2.multi_f.get_a_lw()
a_geo1_rot3 = SS_geo1_rot3.multi_f.get_a_lw()
assert np.allclose(a_geo1[0],a_geo1_rot1[0],atol=1.e-20,rtol=1.e-8)
assert np.allclose(a_geo1[1],a_geo1_rot1[1],atol=1.e-20,rtol=1.e-8)
assert np.allclose(a_geo1[0],a_geo1_rot2[0],atol=1.e-20,rtol=1.e-8)
assert np.allclose(a_geo1[1],a_geo1_rot2[1],atol=1.e-20,rtol=1.e-8)
assert np.allclose(a_geo1[0],a_geo1_rot3[0],atol=1.e-20,rtol=1.e-8)
assert np.allclose(a_geo1[1],a_geo1_rot3[1],atol=1.e-20,rtol=1.e-8)
assert np.allclose(a_geo1[0],var_geo1,atol=1.e-30,rtol=1.e-13)
assert np.allclose(a_geo1_rot1[0],var_geo1_rot1,atol=1.e-30,rtol=1.e-11)
assert np.allclose(a_geo1_rot2[0],var_geo1_rot2,atol=1.e-30,rtol=1.e-11)
assert np.allclose(a_geo1_rot3[0],var_geo1_rot3,atol=1.e-30,rtol=1.e-11)
for i in xrange(0,2):
for j in xrange(0,2):
eig_geo1 = SS_geo1.eig_set[i][j][0]
eig_geo1_rot1 = SS_geo1_rot1.eig_set[i][j][0]
eig_geo1_rot2 = SS_geo1_rot2.eig_set[i][j][0]
eig_geo1_rot3 = SS_geo1_rot3.eig_set[i][j][0]
assert np.allclose(eig_geo1,eig_geo1_rot1)
assert np.allclose(eig_geo1,eig_geo1_rot2)
assert np.allclose(eig_geo1,eig_geo1_rot3)