Aquila-Consortium/csiborgtools
0
0
Fork 0
mirror of https://github.com/Richard-Sti/csiborgtools.git synced 2025-04-19 08:20:53 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

Add

Browse source
This commit is contained in:
rstiskalek 2024-09-21 13:50:46 +01:00
parent 8b8c6bb3e4
commit cf8c1f2bb0
1 changed files with 3 additions and 9 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

12
csiborgtools/flow/flow_model.py
View file

@ -902,7 +902,7 @@ class PV_LogLikelihood(BaseFlowValidationModel):
else:
raise ValueError(f"Unknown kind: `{self.kind}`.")
h = field_calibration_params["h"]
# h = field_calibration_params["h"]
# ----------------------------------------------------------------
# 2. Log-likelihood of the true distance and observed redshifts.
# The marginalisation of the true distance can be done numerically.
@ -910,24 +910,18 @@ class PV_LogLikelihood(BaseFlowValidationModel):
if self.with_num_dist_marginalisation:
if field_calibration_params["sample_h"]:
raise NotImplementedError("Sampling of h not implemented.")
# Rescale the grid to account for the sampled H0. For distance
# modulus going from Mpc / h to Mpc implies larger numerical
# values, so there has to be a minus sign since h < 1.
mu_xrange = self.mu_xrange - 5 * jnp.log(h)
# mu_xrange = self.mu_xrange - 5 * jnp.log(h)
# The redshift should also be boosted since now the object are
# further away?
# Actually, the redshift ought to remain the same?
# TODO: finish this
r_range = self.r_xrange * h
# Actually no need to do this.
z_range = dist2redshift(r_range, self.Omega_m, h)
else:
mu_xrange = self.mu_xrange
z_range = self.z_xrange
# Calculate p(r) (Malmquist bias). Shape is (ndata, nxrange)
log_ptilde = log_ptilde_wo_bias(