Exemple #1
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def test_sources(packages_path, skip_not_installed):
    camb = install_test_wrapper(skip_not_installed, get_camb, packages_path)
    from camb.sources import GaussianSourceWindow

    pars = camb.set_params(**params)
    pars.set_for_lmax(500)
    pars.SourceWindows = [
        GaussianSourceWindow(redshift=0.17, source_type='counts', bias=1.2, sigma=0.04)]
    results = camb.get_results(pars)
    dic = results.get_source_cls_dict()

    # noinspection PyDefaultArgument
    def test_likelihood(_self):
        assert abs(_self.provider.get_source_Cl()[('source1', 'source1')][100] / dic['W1xW1'][
            100] - 1) < 0.001, \
            "CAMB gaussian source window results do not match"
        return 0
    test_likelihood_requires = {
        'source_Cl': {'sources': {'source1':
                                  {'function': 'gaussian',
                                   'source_type': 'counts',
                                   'bias': 1.2,
                                   'redshift': 0.17,
                                   'sigma': 0.04}},
                      'limber': True, 'lmax': 500}}

    model = _get_model(
        packages_path,
        {'external': test_likelihood, 'requires': test_likelihood_requires},
        skip_not_installed)
    model.loglike({})
Exemple #2
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 def testSources(self):
     from camb.sources import GaussianSourceWindow, SplinedSourceWindow
     pars = camb.CAMBparams()
     pars.set_cosmology(H0=64, mnu=0)
     pars.set_for_lmax(1200)
     pars.Want_CMB = False
     pars.SourceWindows = [
         GaussianSourceWindow(redshift=0.17, source_type='counts', bias=1.2, sigma=0.04, dlog10Ndm=-0.2),
         GaussianSourceWindow(redshift=0.5, source_type='lensing', sigma=0.07, dlog10Ndm=0)]
     pars.SourceTerms.limber_windows = True
     results = camb.get_results(pars)
     cls = results.get_source_cls_dict()
     zs = np.arange(0, 0.5, 0.02)
     W = np.exp(-(zs - 0.17) ** 2 / 2 / 0.04 ** 2) / np.sqrt(2 * np.pi) / 0.04
     pars.SourceWindows[0] = SplinedSourceWindow(bias=1.2, dlog10Ndm=-0.2, z=zs, W=W)
     results = camb.get_results(pars)
     cls2 = results.get_source_cls_dict()
     self.assertTrue(np.allclose(cls2["W1xW1"][2:1200], cls["W1xW1"][2:1200], rtol=1e-3))
     pars.SourceWindows = [GaussianSourceWindow(redshift=1089, source_type='lensing', sigma=30)]
     results = camb.get_results(pars)
     cls = results.get_source_cls_dict()
     PP = cls['PxP']
     ls = np.arange(0, PP.shape[0])
     self.assertTrue(np.allclose(PP / 4 * (ls * (ls + 1)), cls['W1xW1'], rtol=1e-3))
     self.assertTrue(np.allclose(PP / 2 * np.sqrt(ls * (ls + 1)), cls['PxW1'], rtol=1e-3))
     # test something sharp with redshift distortions (tricky..)
     from scipy import signal
     zs = np.arange(1.9689, 2.1057, (2.1057 - 1.9689) / 2000)
     W = signal.tukey(len(zs), alpha=0.1)
     pars = camb.CAMBparams()
     pars.set_cosmology(H0=67.5, ombh2=0.022, omch2=0.122)
     pars.InitPower.set_params(As=2e-9, ns=0.965)
     pars.set_for_lmax(4000)
     pars.SourceWindows = [SplinedSourceWindow(z=zs, W=W, source_type='counts')]
     pars.SourceTerms.counts_redshift = True
     results = camb.get_results(pars)
     cls = results.get_source_cls_dict()
     self.assertAlmostEqual(np.sum(cls['PxW1'][10:3000:20]), 0.00020001, places=5)
     self.assertAlmostEqual(np.sum(cls['W1xW1'][10:3000:20]), 2.26348, places=3)
     self.assertAlmostEqual(np.sum(cls['W1xW1'][10]), 0.0001097, places=6)
Exemple #3
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def get_galaxy_power(l,z=0.7,b=1.):
    lmax = np.max([np.max(l),2000])
    pars = camb.CAMBparams()
    pars.set_cosmology(H0=67.5, ombh2=0.022, omch2=0.122)
    pars.InitPower.set_params(As=2e-9, ns=0.965)
    pars.set_for_lmax(lmax, lens_potential_accuracy=1)    
    pars.Want_CMB = False
    pars.NonLinear = model.NonLinear_both
    pars.SourceWindows = [GaussianSourceWindow(redshift=0.7, source_type='counts', sigma=0.1,dlog10Ndm=-0.2, bias = 1.0)]
    results = camb.get_results(pars)
    cls = results.get_source_cls_dict()
    l_model = np.arange(2,lmax+1)
    cl_model = cls['W1xW1'][2:lmax+1]
    # Interpolate this onto the provided grid.
    f = interp1d(l_model,cl_model,kind='cubic')
    return f(l)
Exemple #4
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    def testAssigments(self):
        ini = os.path.join(os.path.dirname(__file__), '..', 'inifiles', 'planck_2018.ini')
        if os.path.exists(ini):
            pars = camb.read_ini(ini)
            self.assertTrue(np.abs(camb.get_background(pars).cosmomc_theta() * 100 / 1.040909 - 1) < 2e-5)
        pars = camb.CAMBparams()
        pars.set_cosmology(H0=68.5, ombh2=0.022, mnu=0, omch2=0.1)
        self.assertAlmostEqual(pars.omegam, (0.022 + 0.1) / 0.685 ** 2)
        with self.assertRaises(AttributeError):
            # noinspection PyPropertyAccess
            pars.omegam = 1
        pars.InitPower.set_params(ns=0.01)
        data = camb.CAMBdata()
        data.Params = pars
        self.assertEqual(data.Params.InitPower.ns, pars.InitPower.ns)
        d = dark_energy.DarkEnergyFluid(w=-0.95)
        pars.DarkEnergy = d
        self.assertEqual(pars.DarkEnergy.w, -0.95)
        pars.DarkEnergy = dark_energy.AxionEffectiveFluid(w_n=0.4)
        data.Params = pars
        self.assertEqual(pars.DarkEnergy.w_n, 0.4)
        pars.z_outputs = [0.1, 0.4]
        self.assertEqual(pars.z_outputs[1], 0.4)
        pars.z_outputs[0] = 0.3
        self.assertEqual(pars.z_outputs[0], 0.3)
        pars.z_outputs = pars.z_outputs
        pars.z_outputs = []
        pars.z_outputs = None
        self.assertFalse(len(pars.z_outputs))
        with self.assertRaises(TypeError):
            pars.DarkEnergy = initialpower.InitialPowerLaw()
        pars.NonLinear = model.NonLinear_both
        printstr = str(pars)
        self.assertTrue('Want_CMB_lensing = True' in printstr and
                        "NonLinear = NonLinear_both" in printstr)
        pars.NonLinear = model.NonLinear_lens
        self.assertTrue(pars.NonLinear == model.NonLinear_lens)
        with self.assertRaises(ValueError):
            pars.NonLinear = 4
        pars.nu_mass_degeneracies = np.zeros(3)
        self.assertTrue(len(pars.nu_mass_degeneracies) == 3)
        pars.nu_mass_degeneracies = [1, 2, 3]
        self.assertTrue(pars.nu_mass_degeneracies[1] == 2)
        pars.nu_mass_degeneracies[1] = 5
        self.assertTrue(pars.nu_mass_degeneracies[1] == 5)
        with self.assertRaises(CAMBParamRangeError):
            pars.nu_mass_degeneracies = np.zeros(7)
        pars.nu_mass_eigenstates = 0
        self.assertFalse(len((pars.nu_mass_degeneracies[:1])))
        pars = camb.set_params(**{'InitPower.ns': 1.2, 'WantTransfer': True})
        self.assertEqual(pars.InitPower.ns, 1.2)
        self.assertTrue(pars.WantTransfer)
        pars.DarkEnergy = None

        from camb.sources import GaussianSourceWindow
        pars = camb.CAMBparams()
        pars.SourceWindows = [GaussianSourceWindow(), GaussianSourceWindow(redshift=1)]
        self.assertEqual(pars.SourceWindows[1].redshift, 1)
        pars.SourceWindows[0].redshift = 2
        self.assertEqual(pars.SourceWindows[0].redshift, 2)
        self.assertTrue(len(pars.SourceWindows) == 2)
        pars.SourceWindows[0] = GaussianSourceWindow(redshift=3)
        self.assertEqual(pars.SourceWindows[0].redshift, 3)
        self.assertTrue('redshift = 3.0' in str(pars))
        pars.SourceWindows = pars.SourceWindows[0:1]
        self.assertTrue(len(pars.SourceWindows) == 1)
        pars.SourceWindows = []
        self.assertTrue(len(pars.SourceWindows) == 0)
Exemple #5
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    def testAssigments(self):
        ini = os.path.join(os.path.dirname(__file__), '..', 'inifiles',
                           'planck_2018.ini')
        if os.path.exists(ini):
            pars = camb.read_ini(ini)
            self.assertTrue(
                np.abs(
                    camb.get_background(pars).cosmomc_theta() * 100 /
                    1.040909 - 1) < 2e-5)
        pars = camb.CAMBparams()
        pars.set_cosmology(H0=68.5, ombh2=0.022, mnu=0, omch2=0.1)
        self.assertAlmostEqual(pars.omegam, (0.022 + 0.1) / 0.685**2)
        with self.assertRaises(AttributeError):
            # noinspection PyPropertyAccess
            pars.omegam = 1
        pars.InitPower.set_params(ns=0.01)
        data = camb.CAMBdata()
        data.Params = pars
        self.assertEqual(data.Params.InitPower.ns, pars.InitPower.ns)
        d = dark_energy.DarkEnergyFluid(w=-0.95)
        pars.DarkEnergy = d
        self.assertEqual(pars.DarkEnergy.w, -0.95)
        pars.DarkEnergy = dark_energy.AxionEffectiveFluid(w_n=0.4)
        data.Params = pars
        self.assertEqual(pars.DarkEnergy.w_n, 0.4)
        pars.z_outputs = [0.1, 0.4]
        self.assertEqual(pars.z_outputs[1], 0.4)
        pars.z_outputs[0] = 0.3
        self.assertEqual(pars.z_outputs[0], 0.3)
        pars.z_outputs = pars.z_outputs
        pars.z_outputs = []
        pars.z_outputs = None
        # noinspection PyTypeChecker
        self.assertFalse(len(pars.z_outputs))
        with self.assertRaises(TypeError):
            pars.DarkEnergy = initialpower.InitialPowerLaw()
        pars.NonLinear = model.NonLinear_both
        printstr = str(pars)
        self.assertTrue('Want_CMB_lensing = True' in printstr
                        and "NonLinear = NonLinear_both" in printstr)
        pars.NonLinear = model.NonLinear_lens
        self.assertTrue(pars.NonLinear == model.NonLinear_lens)
        with self.assertRaises(ValueError):
            pars.NonLinear = 4
        pars.nu_mass_degeneracies = np.zeros(3)
        self.assertTrue(len(pars.nu_mass_degeneracies) == 3)
        pars.nu_mass_degeneracies = [1, 2, 3]
        self.assertTrue(pars.nu_mass_degeneracies[1] == 2)
        pars.nu_mass_degeneracies[1] = 5
        self.assertTrue(pars.nu_mass_degeneracies[1] == 5)
        with self.assertRaises(CAMBParamRangeError):
            pars.nu_mass_degeneracies = np.zeros(7)
        pars.nu_mass_eigenstates = 0
        self.assertFalse(len((pars.nu_mass_degeneracies[:1])))
        pars = camb.set_params(**{'InitPower.ns': 1.2, 'WantTransfer': True})
        self.assertEqual(pars.InitPower.ns, 1.2)
        self.assertTrue(pars.WantTransfer)
        pars.DarkEnergy = None
        pars = camb.set_params(**{
            'H0': 67,
            'ombh2': 0.002,
            'r': 0.1,
            'Accuracy.AccurateBB': True
        })
        self.assertEqual(pars.Accuracy.AccurateBB, True)

        from camb.sources import GaussianSourceWindow
        pars = camb.CAMBparams()
        pars.SourceWindows = [
            GaussianSourceWindow(),
            GaussianSourceWindow(redshift=1)
        ]
        self.assertEqual(pars.SourceWindows[1].redshift, 1)
        pars.SourceWindows[0].redshift = 2
        self.assertEqual(pars.SourceWindows[0].redshift, 2)
        self.assertTrue(len(pars.SourceWindows) == 2)
        pars.SourceWindows[0] = GaussianSourceWindow(redshift=3)
        self.assertEqual(pars.SourceWindows[0].redshift, 3)
        self.assertTrue('redshift = 3.0' in str(pars))
        pars.SourceWindows = pars.SourceWindows[0:1]
        self.assertTrue(len(pars.SourceWindows) == 1)
        pars.SourceWindows = []
        self.assertTrue(len(pars.SourceWindows) == 0)
        params = camb.get_valid_numerical_params()
        self.assertEqual(
            params, {
                'ombh2', 'deltazrei', 'omnuh2', 'tau', 'omk', 'zrei',
                'thetastar', 'nrunrun', 'meffsterile', 'nnu', 'ntrun',
                'HMCode_A_baryon', 'HMCode_eta_baryon', 'HMCode_logT_AGN',
                'cosmomc_theta', 'YHe', 'wa', 'cs2', 'H0', 'mnu', 'Alens',
                'TCMB', 'ns', 'nrun', 'As', 'nt', 'r', 'w', 'omch2'
            })
        params2 = camb.get_valid_numerical_params(
            dark_energy_model='AxionEffectiveFluid')
        self.assertEqual(params2.difference(params),
                         {'fde_zc', 'w_n', 'zc', 'theta_i'})