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rstiskalek 2024-09-20 08:54:51 +01:00
parent 3f4a63d3de
commit 8b8c6bb3e4
1 changed files with 25 additions and 3 deletions
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28
csiborgtools/flow/flow_model.py
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@ -313,13 +313,13 @@ def radial_velocity_los(los_velocity, ra, dec):
# JAX Flow model # # JAX Flow model #
############################################################################### ###############################################################################
def dist2redshift(dist, Omega_m): def dist2redshift(dist, Omega_m, h=1.):
""" """
Convert comoving distance to cosmological redshift if the Universe is Convert comoving distance to cosmological redshift if the Universe is
flat and z << 1. flat and z << 1.
""" """
eta = 3 * Omega_m / 2 eta = 3 * Omega_m / 2
return 1 / eta * (1 - (1 - 2 * H0 * dist / SPEED_OF_LIGHT * eta)**0.5) return 1 / eta * (1 - (1 - 2 * 100 * h * dist / SPEED_OF_LIGHT * eta)**0.5)
def redshift2dist(z, Omega_m): def redshift2dist(z, Omega_m):
@ -902,14 +902,36 @@ class PV_LogLikelihood(BaseFlowValidationModel):
else: else:
raise ValueError(f"Unknown kind: `{self.kind}`.") raise ValueError(f"Unknown kind: `{self.kind}`.")
h = field_calibration_params["h"]
# ---------------------------------------------------------------- # ----------------------------------------------------------------
# 2. Log-likelihood of the true distance and observed redshifts. # 2. Log-likelihood of the true distance and observed redshifts.
# The marginalisation of the true distance can be done numerically. # The marginalisation of the true distance can be done numerically.
# ---------------------------------------------------------------- # ----------------------------------------------------------------
if self.with_num_dist_marginalisation: if self.with_num_dist_marginalisation:
if field_calibration_params["sample_h"]:
# 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)
# 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) # Calculate p(r) (Malmquist bias). Shape is (ndata, nxrange)
log_ptilde = log_ptilde_wo_bias( log_ptilde = log_ptilde_wo_bias(
self.mu_xrange[None, :], mu[:, None], e2_mu[:, None], mu_xrange[None, :], mu[:, None], e2_mu[:, None],
self.log_r2_xrange[None, :]) self.log_r2_xrange[None, :])
# Inhomogeneous Malmquist bias. Shape: (nsims, ndata, nxrange) # Inhomogeneous Malmquist bias. Shape: (nsims, ndata, nxrange)