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* Switch to CB2 * Update for extrapolation * Add 'nan' extrapolation * Update nb * Update submits * Add Rmax to the models * Update nb * Add print statement * Update script settings * Update flow model to new method * Update printing * Update path * Update so that it works * Update nb * Update submit * Add Rmin for hollow bulk flows * Update script * Update script * Update scripts back * Update scripts back * Fix normalization bug * Update script * pep8
132 KiB
132 KiB
Calibrating the velocity field against observations¶
In [1]:
# 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.
import numpy as np
import matplotlib.pyplot as plt
from flow_bulk import *
%load_ext autoreload
%autoreload 2
%matplotlib inline
Enclosed monopole¶
In [6]:
plt.figure()
cols = plt.rcParams['axes.prop_cycle'].by_key()['color']
# Carrick+2015 must be multiplied by beta = 0.43
r, Vmono = read_enclosed_monopole("Carrick2015")
Vmono *= 0.4
plt.plot(r, Vmono[0], label="Carrick+2015", color=cols[0])
# r, Vmono = read_enclosed_monopole("Lilow2024")
# plt.plot(r, Vmono[0], label="Lilow+2024", color=cols[1])
# r, Vmono = read_enclosed_monopole("csiborg2X")
# ylow, ymed, yhigh = np.percentile(Vmono, [16, 50, 84], axis=0)
# plt.fill_between(r, ylow, yhigh, color=cols[2], alpha=0.5, label="Manticore")
plt.xlabel(r"$R ~ [\mathrm{Mpc} / h]$")
plt.ylabel(r"$V_{\mathrm{mono}}(r \leq R) ~ [\mathrm{km} / \mathrm{s}]$")
# plt.legend(loc="upper left")
plt.xlim(r.min(), r.max())
plt.tight_layout()
plt.savefig("../../plots/enclosed_monopole.png", dpi=450)
plt.show()
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Enclosed overdensity¶
In [24]:
plt.figure()
cols = plt.rcParamsDefault['axes.prop_cycle'].by_key()['color']
r, overdensity = read_enclosed_density("csiborg1")
c = cols[0]
ymin = np.percentile(overdensity, 16, axis=0)
ymed = np.median(overdensity, axis=0)
ymax = np.percentile(overdensity, 84, axis=0)
plt.fill_between(r, ymin, ymax, color=c, alpha=0.5, label="CB1")
r, overdensity = read_enclosed_density("csiborg2_main")
c = cols[1]
ymin = np.percentile(overdensity, 16, axis=0)
ymed = np.median(overdensity, axis=0)
ymax = np.percentile(overdensity, 84, axis=0)
plt.fill_between(r, ymin, ymax, color=c, alpha=0.5, label="CB2")
r, overdensity = read_enclosed_density("csiborg2_random")
c = cols[2]
ymin = np.percentile(overdensity, 16, axis=0)
ymed = np.median(overdensity, axis=0)
ymax = np.percentile(overdensity, 84, axis=0)
plt.fill_between(r, ymin, ymax, color=c, alpha=0.25, label="Random", zorder=-1)
r, overdensity = read_enclosed_density("csiborg2X")
c = cols[3]
ymin = np.percentile(overdensity, 16, axis=0)
ymed = np.median(overdensity, axis=0)
ymax = np.percentile(overdensity, 84, axis=0)
plt.fill_between(r, ymin, ymax, color=c, alpha=0.5, label="Manticore")
plt.xlabel(r"$R ~ [\mathrm{Mpc} / h]$")
plt.ylabel(r"$\delta_{\rm enc} (r \leq R)$")
plt.legend()
plt.xlim(0, r.max())
plt.ylim(-0.15, 0.075)
plt.axhline(0, c='k', ls='--', lw=1)
plt.tight_layout()
plt.savefig("../../plots/enclosed_density.png", dpi=450)
plt.show()
Enclosed bulk flow¶
In [37]:
r, Vmag, l, b = read_enclosed_flow("csiborg1")
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r, Vmag, l, b = read_enclosed_flow("csiborg2X")
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fig, axs = plt.subplots(1, 3, figsize=(14, 5))
cols = plt.rcParamsDefault['axes.prop_cycle'].by_key()['color']
thin_line_kwargs = {"lw": 0.3, "zorder": 0, "ls": "dotted"}
# CSiBORG1
r, Vmag, l, b = read_enclosed_flow("csiborg1")
c = cols[0]
for i, y in enumerate([Vmag, l, b]):
ymin, ymed, ymax = np.percentile(y, [16, 50, 84], axis=0)
axs[i].fill_between(r, ymin, ymax, color=c, alpha=0.5, label="CB1")
# CSiBORG2
r, Vmag, l, b = read_enclosed_flow("csiborg2_main")
c = cols[1]
for i, y in enumerate([Vmag, l, b]):
ymin, ymed, ymax = np.percentile(y, [16, 50, 84], axis=0)
axs[i].fill_between(r, ymin, ymax, color=c, alpha=0.5, label="CB2")
# Manticore
r, Vmag, l, b = read_enclosed_flow("csiborg2X")
c = cols[3]
for i, y in enumerate([Vmag, l, b]):
ymin, ymed, ymax = np.percentile(y, [16, 50, 84], axis=0)
axs[i].fill_between(r, ymin, ymax, color=c, alpha=0.5, label="Manticore")
# Random
r, Vmag, l, b = read_enclosed_flow("csiborg2_random")
c = cols[2]
ymin = np.percentile(Vmag, 16, axis=0)
ymax = np.percentile(Vmag, 84, axis=0)
ymed = np.median(Vmag, axis=0)
axs[0].fill_between(r, ymin, ymax, color=c, alpha=0.35, zorder=-1,
label="Random")
axs[0].legend()
for i in range(3):
axs[i].set_xlabel(r"$R ~ [\mathrm{Mpc} / h]$")
axs[i].set_xlim(0, r.max())
axs[0].set_ylim(0)
axs[0].set_ylabel(r"$V_{\rm enc} (r \leq R) ~ [\mathrm{km} / \mathrm{s}]$")
axs[1].set_ylabel(r"$l_{\rm enc} (r \leq R) ~ [\mathrm{deg}]$")
axs[2].set_ylabel(r"$b_{\rm enc} (r \leq R) ~ [\mathrm{deg}]$")
axs[1].set_ylim(0, 360)
fig.tight_layout()
fig.savefig("../../plots/enclosed_flow.png", dpi=450)
fig.show()
Enclosed overdensity $\texttt{BORG2}$ all¶
In [22]:
paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
nsims = paths.get_ics("borg2_all")
r, overdensity = read_enclosed_density("borg2_all")
overdensity_A = overdensity[:80]
overdensity_B = overdensity[80:][::30]
In [25]:
nsims[:80]
Out[25]:
In [40]:
plt.figure()
cols = plt.rcParamsDefault['axes.prop_cycle'].by_key()['color']
# r, overdensity = read_enclosed_density("csiborg1")
c = cols[0]
for i in range(len(overdensity_A)):
plt.plot(r, overdensity_A[i], c=c, lw=0.2, zorder=0, ls="dotted")
plt.plot(r, np.median(overdensity_A, axis=0), c=c, lw=2, label=r"Chain index: $7500$ to $15000$")
c = cols[1]
for i in range(len(overdensity_B)):
plt.plot(r, overdensity_B[i], c=c, lw=0.2, zorder=0, ls="dotted")
plt.plot(r, np.median(overdensity_B, axis=0), c=c, lw=2, label=r"Chain index: $15000$ to $17000$")
plt.xlabel(r"$R ~ [\mathrm{Mpc} / h]$")
plt.ylabel(r"$\delta_{\rm enc} (r \leq R)$")
plt.legend()
plt.xlim(0, r.max())
plt.ylim(-0.14, -0.005)
plt.axhline(0, c='k', ls='--', lw=1)
plt.tight_layout()
plt.savefig("../../plots/enclosed_density_BORG2.png", dpi=450)
plt.show()
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