fix tests

pyHalo/Cosmology/geometry.py

@@ -101,12 +101,6 @@ def _volume_integrand_comoving(self, z, radius_arcsec):
         dR = self.cosmo.astropy.hubble_distance.value * self.cosmo.astropy.efunc(z) ** -1
         return area_comoving * dR
 
-    def _angle_to_arcsec_area(self, radius_arcsec, z):
-
-        theta = self._angle_to_arcsec_radius(radius_arcsec, z)
-
-        return np.pi * theta ** 2
-
     def angle_to_comoving_area(self, radius_arcsec, z):
         """
         computes the area corresponding to the angular radius of a plane at redshift z for a double cone with base at z_base
@@ -135,14 +129,6 @@ def angle_to_physical_area(self, radius_arcsec, z):
 
         return area_comoving * a_z ** 2
 
-    def _angle_to_arcsec_radius(self, radius_arcsec, z):
-
-        r_co_mpc = self.angle_to_comovingradius(radius_arcsec, z)
-        r_co_kpc = r_co_mpc * 1000
-        asec_per_kpc = self.cosmo.astropy.arcsec_per_kpc_comoving(z).value
-
-        return r_co_kpc * asec_per_kpc
-
 class Cone(object):
 
     def __init__(self, cosmology, z_lens, z_source, opening_angle, angle_pad):

pyHalo/preset_models.py

@@ -735,11 +735,9 @@ def WDMGeneral(z_lens, z_source, log_mc, dlogT_dlogk, sigma_sub=0.025, log_mlow=
     # SET THE SPATIAL DISTRIBUTION MODELS FOR SUBHALOS AND FIELD HALOS:
     subhalo_spatial_distribution = ProjectedNFW
     fieldhalo_spatial_distribution = LensConeUniform
-
     kwargs_model_dlogT_dlogk = {'dlogT_dlogk': dlogT_dlogk}
     mass_function_model_subhalos, kwargs_mfunc_subs = preset_mass_function_models('STUCKER_SHMF', kwargs_model_dlogT_dlogk)
     mass_function_model_fieldhalos, kwargs_mfunc_field = preset_mass_function_models('STUCKER', kwargs_model_dlogT_dlogk)
-
     # SET THE CONCENTRATION-MASS RELATION FOR SUBHALOS AND FIELD HALOS
     concentration_model = 'FROM_FORMATION_HISTORY'
     model_subhalos, kwargs_concentration_model_subhalos = preset_concentration_models(concentration_model,
@@ -757,11 +755,9 @@ def WDMGeneral(z_lens, z_source, log_mc, dlogT_dlogk, sigma_sub=0.025, log_mlow=
     kwargs_concentration_model_fieldhalos['log_mc'] = log_mc
     concentration_model_fieldhalos = model_fieldhalos(**kwargs_concentration_model_fieldhalos)
     c_host = concentration_model_fieldhalos.nfw_concentration(10 ** log_m_host, z_lens)
-
     # SET THE TRUNCATION RADIUS FOR SUBHALOS AND FIELD HALOS
     kwargs_truncation_model_subhalos['lens_cosmo'] = pyhalo.lens_cosmo
     kwargs_truncation_model_fieldhalos['lens_cosmo'] = pyhalo.lens_cosmo
-
     model_subhalos, kwargs_trunc_subs = truncation_models(truncation_model_subhalos)
     kwargs_trunc_subs.update(kwargs_truncation_model_subhalos)
     if truncation_model_subhalos == 'TRUNCATION_GALACTICUS':
@@ -770,10 +766,8 @@ def WDMGeneral(z_lens, z_source, log_mc, dlogT_dlogk, sigma_sub=0.025, log_mlow=
     model_fieldhalos, kwargs_trunc_field = truncation_models(truncation_model_fieldhalos)
     kwargs_trunc_field.update(kwargs_truncation_model_fieldhalos)
     truncation_model_fieldhalos = model_fieldhalos(**kwargs_trunc_field)
-
     # NOW THAT THE CLASSES ARE SPECIFIED, WE SORT THE KEYWORD ARGUMENTS AND CLASSES INTO LISTS
     population_model_list = ['SUBHALOS', 'LINE_OF_SIGHT', 'TWO_HALO']
-
     mass_function_class_list = [mass_function_model_subhalos,
                                 mass_function_model_fieldhalos,
                                 mass_function_model_fieldhalos]

pyHalo/realization_extensions.py

@@ -341,9 +341,7 @@ def add_primordial_black_holes(self, pbh_mass_fraction, kwargs_pbh_mass_function
         realization_smooth = Realization(masses, xcoords, ycoords, r3d, mdefs, redshifts, subhalo_flag,
                                          self._realization.lens_cosmo, kwargs_halo_model=kwargs_halo_model,
                                          mass_sheet_correction=False)
-
         kwargs_pbh_mass_function['mass_fraction'] = mass_fraction_clumpy
-
         for ii, (x_image_interp, y_image_interp, r_max) in enumerate(zip(x_image_interp_list, y_image_interp_list, r_max_arcsec)):
             realization_with_clustering_temp = self.add_correlated_structure(DeltaFunction,
                                  kwargs_pbh_mass_function,
@@ -421,7 +419,6 @@ def _get_fluctuation_halos(realization, fluctuation_amplitude, fluctuation_size,
     fluctuation_size_variance_angle = fluctuation_size_variance / kpc_per_arcsec
 
     if shape != 'aperture':
-
         sigs = np.abs(np.random.normal(fluc_var_angle,fluctuation_size_variance_angle,n_flucs)) #random widths
         kappa0 = np.random.normal(0, fluctuation_amplitude, n_flucs)
         # kappa0 = amp / (2 * np.pi * sigma ** 2)
@@ -441,28 +438,20 @@ def _get_fluctuation_halos(realization, fluctuation_amplitude, fluctuation_size,
         ys = aa*np.cos(angles)*np.sin(args['angle'])+bb*np.sin(angles)*np.cos(args['angle']) #random y positions
 
     if shape == 'aperture':
-
         amps, sigs, xs, ys = np.array([]), np.array([]), np.array([]), np.array([])
-
         for i in range(0, len(n_flucs)): #loop through each image
-
             sigs_i = np.random.normal(fluc_var_angle,fluctuation_size_variance_angle,n_flucs[i])
             sigs_i = np.absolute(sigs_i)
-
             kappa0 = np.random.normal(0, fluctuation_amplitude, n_flucs[i])
             amps_i = kappa0 * 2*np.pi*sigs_i**2
-
             angles_i = np.random.uniform(0, 2*np.pi, n_flucs[i])  # random angles
             r = np.random.uniform(0, args['aperture'] ** 2, int(n_flucs[i]))
             xs_i = r ** 0.5 * np.sin(angles_i) + args['x_images'][i]
             ys_i = r ** 0.5 * np.cos(angles_i) + args['y_images'][i]
             amps, sigs, xs, ys= np.append(amps, amps_i), np.append(sigs, sigs_i), np.append(xs, xs_i), np.append(ys, ys_i)
 
     args_fluc=[{'amp': amps[i], 'sigma': sigs[i], 'center_x': xs[i], 'center_y': ys[i]} for i in range(len(amps))]
-    # kappa(r) = kappa * exp(-0.5 * r^2/sigma^2)
-    #sigma_crit = realization.lens_cosmo.sigmacrit # in units M_sun / arcsec^2
     masses = np.absolute(amps)
-    #masses = [10 ** 8.0] * len(xs)
     fluctuations = [Gaussian(masses[i], xs[i], ys[i], None, realization.lens_cosmo.z_lens,
                              True, realization.lens_cosmo, args_fluc[i],
                              truncation_class=None, concentration_class=None,

tests/test_cosmology/test_cone_geometry.py

@@ -118,6 +118,21 @@ def test_total_volume(self):
         volume_true = 1./3 * np.pi * radius_radians ** 2 * dz ** 2 * ds
         npt.assert_almost_equal(volume_true, volume_pyhalo, 3)
 
+    def test_cone(self):
+
+        cone_arcsec = 4
+        radius_radians = cone_arcsec * 0.5 * self.cosmo.arcsec
+        geo = Geometry(self.cosmo, 0.5, 1.5, cone_arcsec, 'CONE', angle_pad=1.)
+        volume_pyhalo = 0
+        z = np.linspace(0.0, 1.5, 200)
+        for i in range(0, len(z)-1):
+            delta_z = z[i+1] - z[i]
+            volume_pyhalo += geo.volume_element_comoving(z[i], delta_z)
+
+        ds = self.cosmo.D_C_z(1.5)
+        volume_true = 1./3 * np.pi * radius_radians ** 2 * ds ** 3
+        npt.assert_almost_equal(volume_true, volume_pyhalo, 3)
+
 
 if __name__ == '__main__':
       pytest.main()