csiborgtools/notebooks/flow/flow_calibration.py
Richard Stiskalek c4557cf35b
Matching of observations (#127)
* Rename file

* Add indents

* Update imports

* Add counting

* Docs

* Add nb

* Rename nb

* Update nb

* Add PV processing

* Update nb

* Add Pantheon+groups

* Update submission scripts

* Add Pantheon+zSN

* Update nb

* Edit param

* Matchin SFI

* Update nb

* Fix path bug

* Add list of clusters

* Update imports

* Update imports

* Add cartesian & mass of clusters

* Add observation to halo matching

* Add nb

* Add inverse CDF

* Add import

* Update nb

* Add comments
2024-04-23 12:02:09 +01:00

194 lines
7.8 KiB
Python

# Copyright (C) 2024 Richard Stiskalek
# This program is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by the
# Free Software Foundation; either version 3 of the License, or (at your
# option) any later version.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
# Public License for more details.
#
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
"""Script to help with plots in `flow_calibration.ipynb`."""
from copy import copy
from os.path import join, exists
import numpy as np
from getdist import MCSamples
from h5py import File
import csiborgtools
def read_samples(catalogue, simname, ksmooth, include_calibration=False,
return_MCsamples=False, subtract_LG_velocity=-1):
print(f"\nReading {catalogue} fitted to {simname} with ksmooth = {ksmooth}.", flush=True) # noqa
paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
nsims = paths.get_ics(simname)
# The last simulation was used to draw the mocks.
if catalogue in ["CB2_small", "CB2_large"]:
nsims = nsims[:-5]
FDIR_LG = "/mnt/extraspace/rstiskalek/csiborg_postprocessing/peculiar_velocity/observer" # noqa
Vx, Vy, Vz, beta, sigma_v, alpha = [], [], [], [], [], []
BIC, AIC, logZ, chi2 = [], [], [], []
if catalogue in ["LOSS", "Foundation"] or "Pantheon+" in catalogue:
alpha_cal, beta_cal, mag_cal, e_mu_intrinsic = [], [], [], []
elif catalogue in ["2MTF", "SFI_gals", "SFI_gals_masked"]:
a, b, e_mu_intrinsic = [], [], []
elif catalogue == "SFI_groups":
h = []
elif catalogue in ["CB2_small", "CB2_large"]:
pass
else:
raise ValueError(f"Catalogue {catalogue} not recognized.")
fname = f"/mnt/extraspace/rstiskalek/csiborg_postprocessing/peculiar_velocity/flow_samples_{catalogue}_{simname}_smooth_{ksmooth}.hdf5" # noqa
with File(fname, 'r') as f:
for i, nsim in enumerate(nsims):
Vx.append(f[f"sim_{nsim}/Vext_x"][:])
Vy.append(f[f"sim_{nsim}/Vext_y"][:])
Vz.append(f[f"sim_{nsim}/Vext_z"][:])
alpha.append(f[f"sim_{nsim}/alpha"][:])
beta.append(f[f"sim_{nsim}/beta"][:])
sigma_v.append(f[f"sim_{nsim}/sigma_v"][:])
if subtract_LG_velocity >= 0:
fname = join(FDIR_LG, f"{simname}_{nsim}_observer_velocity.npz") # noqa
if not exists(fname):
raise FileNotFoundError(f"File {fname} not found.")
d = np.load(fname)
R = d["smooth_scales"][subtract_LG_velocity]
if i == 0:
print(f"Subtracting LG velocity with kernel {R} Mpc / h.", flush=True) # noqa
Vx_LG, Vy_LG, Vz_LG = d["vobs"][subtract_LG_velocity]
if simname == "Carrick2015":
Vx[-1] += beta[-1] * Vx_LG
Vy[-1] += beta[-1] * Vy_LG
Vz[-1] += beta[-1] * Vz_LG
else:
Vx[-1] += Vx_LG
Vy[-1] += Vy_LG
Vz[-1] += Vz_LG
BIC.append(f[f"sim_{nsim}/BIC"][...])
AIC.append(f[f"sim_{nsim}/AIC"][...])
logZ.append(f[f"sim_{nsim}/logZ"][...])
try:
chi2.append(f[f"sim_{nsim}/chi2"][...])
except KeyError:
chi2.append([0.])
if catalogue in ["LOSS", "Foundation"] or "Pantheon+" in catalogue: # noqa
alpha_cal.append(f[f"sim_{nsim}/alpha_cal"][:])
beta_cal.append(f[f"sim_{nsim}/beta_cal"][:])
mag_cal.append(f[f"sim_{nsim}/mag_cal"][:])
e_mu_intrinsic.append(f[f"sim_{nsim}/e_mu_intrinsic"][:])
elif catalogue in ["2MTF", "SFI_gals"]:
a.append(f[f"sim_{nsim}/a"][:])
b.append(f[f"sim_{nsim}/b"][:])
e_mu_intrinsic.append(f[f"sim_{nsim}/e_mu_intrinsic"][:])
elif catalogue == "SFI_groups":
h.append(f[f"sim_{nsim}/h"][:])
elif catalogue in ["CB2_small", "CB2_large"]:
pass
else:
raise ValueError(f"Catalogue {catalogue} not recognized.")
Vx, Vy, Vz, alpha, beta, sigma_v = np.hstack(Vx), np.hstack(Vy), np.hstack(Vz), np.hstack(alpha), np.hstack(beta), np.hstack(sigma_v) # noqa
gof = np.hstack(BIC), np.hstack(AIC), np.hstack(logZ), np.hstack(chi2)
if catalogue in ["LOSS", "Foundation"] or "Pantheon+" in catalogue:
alpha_cal, beta_cal, mag_cal, e_mu_intrinsic = np.hstack(alpha_cal), np.hstack(beta_cal), np.hstack(mag_cal), np.hstack(e_mu_intrinsic) # noqa
elif catalogue in ["2MTF", "SFI_gals", "SFI_gals_masked"]:
a, b, e_mu_intrinsic = np.hstack(a), np.hstack(b), np.hstack(e_mu_intrinsic) # noqa
elif catalogue == "SFI_groups":
h = np.hstack(h)
elif catalogue in ["CB2_small", "CB2_large"]:
pass
else:
raise ValueError(f"Catalogue {catalogue} not recognized.")
# Calculate magnitude of V_ext
Vmag = np.sqrt(Vx**2 + Vy**2 + Vz**2)
# Calculate direction in galactic coordinates of V_ext
V = np.vstack([Vx, Vy, Vz]).T
V = csiborgtools.cartesian_to_radec(V)
l, b = csiborgtools.radec_to_galactic(V[:, 1], V[:, 2])
data = [alpha, beta, Vmag, l, b, sigma_v]
names = ["alpha", "beta", "Vmag", "l", "b", "sigma_v"]
if include_calibration:
if catalogue in ["LOSS", "Foundation"] or "Pantheon+" in catalogue:
data += [alpha_cal, beta_cal, mag_cal, e_mu_intrinsic]
names += ["alpha_cal", "beta_cal", "mag_cal", "e_mu_intrinsic"]
elif catalogue in ["2MTF", "SFI_gals", "SFI_gals_masked"]:
data += [a, b, e_mu_intrinsic]
names += ["a", "b", "e_mu_intrinsic"]
elif catalogue == "SFI_groups":
data += [h]
names += ["h"]
else:
raise ValueError(f"Catalogue {catalogue} not recognized.")
print("BIC = {:4f} +- {:4f}".format(np.mean(gof[0]), np.std(gof[0])))
print("AIC = {:4f} +- {:4f}".format(np.mean(gof[1]), np.std(gof[1])))
print("logZ = {:4f} +- {:4f}".format(np.mean(gof[2]), np.std(gof[2])))
print("chi2 = {:4f} +- {:4f}".format(np.mean(gof[3]), np.std(gof[3])))
data = np.vstack(data).T
if return_MCsamples:
simname = simname_to_pretty(simname)
if ksmooth == 1:
simname = fr"{simname} (2)"
if subtract_LG_velocity >= 0:
simname += " (LG)"
label = fr"{catalogue}, {simname}, $\log \mathcal{{Z}} = {np.mean(gof[2]):.1f}$" # noqa
return MCSamples(samples=data, names=names,
labels=names_to_latex(names), label=label)
return data, names, gof
def simname_to_pretty(simname):
ltx = {"Carrick2015": "C+15",
"csiborg1": "CB1",
"csiborg2_main": "CB2",
}
return ltx[simname] if simname in ltx else simname
def names_to_latex(names, for_corner=False):
ltx = {"alpha": "\\alpha",
"beta": "\\beta",
"Vmag": "V_{\\rm ext} ~ [\\mathrm{km} / \\mathrm{s}]",
"sigma_v": "\\sigma_v ~ [\\mathrm{km} / \\mathrm{s}]",
}
ltx_corner = {"alpha": r"$\alpha$",
"beta": r"$\beta$",
"Vmag": r"$V_{\rm ext}$",
"sigma_v": r"$\sigma_v$",
"h": r"$h$",
}
labels = copy(names)
for i, label in enumerate(names):
if label in ltx:
labels[i] = ltx_corner[label] if for_corner else ltx[label]
return labels