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code-style bugs fixing
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@giorgiazagatti
giorgiazagatti committed Sep 5, 2024
1 parent 87ad85e commit 01ffcbb
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Showing 2 changed files with 78 additions and 48 deletions.
121 changes: 75 additions & 46 deletions soliket/halo_model/halo_model_fe/power_spectrum.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -32,11 +32,13 @@ def halo_terms_matter(self):
Pk_2h = np.zeros([len(self.k_array), len(self.redshift)])

for k in range(len(self.k_array)):
intmass_1h[k, :, :] = self.instance_200.dndM * (self.mass[np.newaxis, :]
* self.instance_200.u_k[:, :, k]) ** 2
intmass_2h[k, :, :] = self.instance_200.bias_cib * (self.instance_200.dndM *
self.mass[np.newaxis, :] *
self.instance_200.u_k[:, :, k])
intmass_1h[k, :, :] = (self.instance_200.dndM
* (self.mass[np.newaxis, :]
* self.instance_200.u_k[:, :, k]) ** 2)
intmass_2h[k, :, :] = (self.instance_200.bias_cib
* (self.instance_200.dndM
* self.mass[np.newaxis, :]
* self.instance_200.u_k[:, :, k]))

B = 1. - trapz(self.instance_200.bias_cib * self.instance_200.dndM *
self.mass[np.newaxis, :] / rho_mean, self.mass, axis=-1)
Expand Down Expand Up @@ -100,11 +102,13 @@ def halo_terms_galaxy(self):
* self.instance_HOD.Nsat_LP[np.newaxis, :]
* self.instance_200.u_k[:, :, k] ** 2))

intmass_2h_EP[k, :, :] = (self.instance_200.dndM * self.instance_200.bias_cib
intmass_2h_EP[k, :, :] = (self.instance_200.dndM
* self.instance_200.bias_cib
* self.instance_HOD.Nbra_EP[np.newaxis, :]
* self.instance_200.u_k[:, :, k])

intmass_2h_LP[k, :, :] = (self.instance_200.dndM * self.instance_200.bias_cib
intmass_2h_LP[k, :, :] = (self.instance_200.dndM
* self.instance_200.bias_cib
* self.instance_HOD.Nbra_LP[np.newaxis, :]
* self.instance_200.u_k[:, :, k])

Expand All @@ -113,16 +117,20 @@ def halo_terms_galaxy(self):
Pk_1h_LP[k, :] = (trapz(intmass_1h_LP[k, :, :], self.mass, axis=-1)
/ self.instance_HOD.ngal_LP_200c ** 2)
Pk_1h_mix[k, :] = (trapz(intmass_1h_mix[k, :, :], self.mass, axis=-1)
/ (self.instance_HOD.ngal_EP_200c * self.instance_HOD.ngal_LP_200c))
/ (self.instance_HOD.ngal_EP_200c
* self.instance_HOD.ngal_LP_200c))

Pk_2h_EP[k, :] = (self.Pk_array[:, k] * (trapz(intmass_2h_EP[k, :, :], self.mass, axis=-1)) ** 2
Pk_2h_EP[k, :] = (self.Pk_array[:, k]
* (trapz(intmass_2h_EP[k, :, :], self.mass, axis=-1)) ** 2
/ self.instance_HOD.ngal_EP_200c ** 2)
Pk_2h_LP[k, :] = (self.Pk_array[:, k] * (trapz(intmass_2h_LP[k, :, :], self.mass, axis=-1)) ** 2
Pk_2h_LP[k, :] = (self.Pk_array[:, k]
* (trapz(intmass_2h_LP[k, :, :], self.mass, axis=-1)) ** 2
/ self.instance_HOD.ngal_LP_200c ** 2)
Pk_2h_mix[k, :] = (self.Pk_array[:, k] * (trapz(intmass_2h_EP[k, :, :], self.mass, axis=-1)
* trapz(intmass_2h_LP[k, :, :], self.mass, axis=-1)
/ (self.instance_HOD.ngal_EP_200c
* self.instance_HOD.ngal_LP_200c)))
Pk_2h_mix[k, :] = (self.Pk_array[:, k]
* (trapz(intmass_2h_EP[k, :, :], self.mass, axis=-1)
* trapz(intmass_2h_LP[k, :, :], self.mass, axis=-1)
/ (self.instance_HOD.ngal_EP_200c
* self.instance_HOD.ngal_LP_200c)))

Pgal = Pk_1h_EP + Pk_1h_LP + Pk_1h_mix + Pk_2h_EP + Pk_2h_LP + Pk_2h_mix

Expand Down Expand Up @@ -150,7 +158,8 @@ def halo_terms_galaxy(self):

Pk_1h[k, :] = (trapz(intmass_1h[k, :, :], self.mass, axis=-1)
/ self.instance_HOD.ngal_EP_200c ** 2)
Pk_2h[k, :] = (self.Pk_array[:, k] * (trapz(intmass_2h[k, :, :], self.mass, axis=-1)) ** 2
Pk_2h[k, :] = (self.Pk_array[:, k]
* (trapz(intmass_2h[k, :, :], self.mass, axis=-1)) ** 2
/ self.instance_HOD.ngal_EP_200c ** 2)

Pgal = Pk_1h + Pk_2h
Expand Down Expand Up @@ -188,36 +197,48 @@ def halo_terms_matter_galaxy(self):
Pk_2h_LP = np.zeros([len(self.k_array), len(self.redshift)])

for k in range(len(self.k_array)):
intmass_2h_m[k, :, :] = (self.instance_200.dndM * self.instance_200.bias_cib
* self.mass[np.newaxis, :] * self.instance_200.u_k[:, :, k])

intmass_1h_EP[k, :, :] = (self.instance_200.dndM * self.instance_HOD.Nbra_EP[np.newaxis, :]
* self.mass[np.newaxis, :] * self.instance_200.u_k[:, :, k] ** 2)
intmass_2h_g_EP[k, :, :] = (self.instance_200.dndM * self.instance_200.bias_cib
* self.instance_HOD.Nbra_EP[np.newaxis, :] * self.instance_200.u_k[:, :, k])

intmass_1h_LP[k, :, :] = (self.instance_200.dndM * self.instance_HOD.Nbra_LP[np.newaxis, :]
* self.mass[np.newaxis, :] * self.instance_200.u_k[:, :, k] ** 2)
intmass_2h_g_LP[k, :, :] = (self.instance_200.dndM * self.instance_200.bias_cib
* self.instance_HOD.Nbra_LP[np.newaxis, :] * self.instance_200.u_k[:, :, k])
intmass_2h_m[k, :, :] = (self.instance_200.dndM
* self.instance_200.bias_cib
* self.mass[np.newaxis, :]
* self.instance_200.u_k[:, :, k])

intmass_1h_EP[k, :, :] = (self.instance_200.dndM
* self.instance_HOD.Nbra_EP[np.newaxis, :]
* self.mass[np.newaxis, :]
* self.instance_200.u_k[:, :, k] ** 2)
intmass_2h_g_EP[k, :, :] = (self.instance_200.dndM
* self.instance_200.bias_cib
* self.instance_HOD.Nbra_EP[np.newaxis, :]
* self.instance_200.u_k[:, :, k])

intmass_1h_LP[k, :, :] = (self.instance_200.dndM
* self.instance_HOD.Nbra_LP[np.newaxis, :]
* self.mass[np.newaxis, :]
* self.instance_200.u_k[:, :, k] ** 2)
intmass_2h_g_LP[k, :, :] = (self.instance_200.dndM
* self.instance_200.bias_cib
* self.instance_HOD.Nbra_LP[np.newaxis, :]
* self.instance_200.u_k[:, :, k])

B = (1. - trapz(self.instance_200.bias_cib * self.instance_200.dndM
* self.mass[np.newaxis, :]
/ rho_mean, self.mass, axis=-1))

Pk_1h_EP[k, :] = (trapz(intmass_1h_EP[k, :, :], self.mass, axis=-1)
/ (ngal_mean_EP * rho_mean))
Pk_2h_EP[k, :] = (self.Pk_array[:, k] * (trapz(intmass_2h_m[k, :, :], self.mass, axis=-1)
/ rho_mean + B)
* trapz(intmass_2h_g_EP[k, :, :], self.mass, axis=-1)
/ ngal_mean_EP)
Pk_2h_EP[k, :] = (self.Pk_array[:, k]
* (trapz(intmass_2h_m[k, :, :], self.mass, axis=-1)
/ rho_mean + B)
* trapz(intmass_2h_g_EP[k, :, :], self.mass, axis=-1)
/ ngal_mean_EP)

Pk_1h_LP[k, :] = (trapz(intmass_1h_LP[k, :, :], self.mass, axis=-1)
/ (ngal_mean_LP * rho_mean))
Pk_2h_LP[k, :] = (self.Pk_array[:, k] * (trapz(intmass_2h_m[k, :, :], self.mass, axis=-1)
/ rho_mean + B)
* trapz(intmass_2h_g_LP[k, :, :], self.mass, axis=-1)
/ ngal_mean_LP)
Pk_2h_LP[k, :] = (self.Pk_array[:, k]
* (trapz(intmass_2h_m[k, :, :], self.mass, axis=-1)
/ rho_mean + B)
* trapz(intmass_2h_g_LP[k, :, :], self.mass, axis=-1)
/ ngal_mean_LP)

Pmg = Pk_1h_EP + Pk_1h_LP + Pk_2h_EP + Pk_2h_LP

Expand All @@ -241,22 +262,30 @@ def halo_terms_matter_galaxy(self):
Pk_2h = np.zeros([len(self.k_array), len(self.redshift)])

for k in range(len(self.k_array)):
intmass_1h[k, :, :] = (self.instance_200.dndM * self.instance_HOD.Nbra_EP[np.newaxis, :]
* self.mass[np.newaxis, :] * self.instance_200.u_k[:, :, k] ** 2)
intmass_2h_m[k, :, :] = (self.instance_200.dndM * self.instance_200.bias_cib
* self.mass[np.newaxis, :] * self.instance_200.u_k[:, :, k])
intmass_2h_g[k, :, :] = (self.instance_200.dndM * self.instance_200.bias_cib
* self.instance_HOD.Nbra_EP[np.newaxis, :] * self.instance_200.u_k[:, :, k])
intmass_1h[k, :, :] = (self.instance_200.dndM
* self.instance_HOD.Nbra_EP[np.newaxis, :]
* self.mass[np.newaxis, :]
* self.instance_200.u_k[:, :, k] ** 2)
intmass_2h_m[k, :, :] = (self.instance_200.dndM
* self.instance_200.bias_cib
* self.mass[np.newaxis, :]
* self.instance_200.u_k[:, :, k])
intmass_2h_g[k, :, :] = (self.instance_200.dndM
* self.instance_200.bias_cib
* self.instance_HOD.Nbra_EP[np.newaxis, :]
* self.instance_200.u_k[:, :, k])

B = (1. - trapz(self.instance_200.bias_cib * self.instance_200.dndM
* self.mass[np.newaxis, :] / rho_mean, self.mass, axis=-1))
* self.mass[np.newaxis, :]
/ rho_mean, self.mass, axis=-1))

Pk_1h[k, :] = (trapz(intmass_1h[k, :, :], self.mass, axis=-1)
/ (ngal_mean_EP * rho_mean))
Pk_2h[k, :] = (self.Pk_array[:, k] * (trapz(intmass_2h_m[k, :, :], self.mass, axis=-1)
/ rho_mean + B)
* trapz(intmass_2h_g[k, :, :], self.mass, axis=-1)
/ ngal_mean_EP)
Pk_2h[k, :] = (self.Pk_array[:, k]
* (trapz(intmass_2h_m[k, :, :], self.mass, axis=-1)
/ rho_mean + B)
* trapz(intmass_2h_g[k, :, :], self.mass, axis=-1)
/ ngal_mean_EP)

Pmg = Pk_1h + Pk_2h

Expand Down
5 changes: 3 additions & 2 deletions soliket/halo_model/halo_model_fe/utils.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -55,7 +55,7 @@ def sigma(self, rad, red, zeta):
lnk = np.log(k)
uW = self.W(rk)
integ = rest * uW ** 2
sigm = (0.5 / np.pi ** 2) * trapz(integ, x=lnk, axis=-1) ####################################### gz
sigm = (0.5 / np.pi ** 2) * trapz(integ, x=lnk, axis=-1)
#sigm = (0.5 / np.pi ** 2) * scipy.integrate.simps(integ, x=lnk, axis=-1)
return np.sqrt(sigm)

Expand Down Expand Up @@ -325,7 +325,8 @@ def compute_fsigma(self):

def dn_dm(self, red, zeta):
rad = self.mass_to_radius()
return self.fsigma(rad, red, zeta) * self.mean_density() * np.abs(self.dlns_dlnm(rad, red, zeta)) / self.mh**2 #using un-normalized T08 hmf
return (self.fsigma(rad, red, zeta) * self.mean_density()
* np.abs(self.dlns_dlnm(rad, red, zeta)) / self.mh**2)

def dn_dlnm(self, red, zeta):
return self.mh * self.dn_dm(red, zeta)
Expand Down

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