csiborgtools/notebooks/flow/flow_calibration.ipynb
Richard Stiskalek 779f2e76ac
Calculate upglade redshifts (#128)
* Update redshift reading

* Add helio to CMB redshift

* Update imports

* Update nb

* Run for Quijote

* Add script

* Update

* Update .gitignore

* Update imports

* Add Peery estimator

* Add bulk flow scripts

* Update typs

* Add comment

* Add blank space

* Update submission script

* Update description

* Add barriers

* Update nb

* Update nb

* Rename script

* Move to old

* Update imports

* Add nb

* Update script

* Fix catalogue key

* Update script

* Update submit

* Update comment

* Update .gitignore

* Update nb

* Update for stationary obsrevers

* Update submission

* Add nb

* Add better verbose control

* Update nb

* Update submit

* Update nb

* Add SN errors

* Add draft of the script

* Update verbosity flags

* Add submission script

* Debug script

* Quickfix

* Remove comment

* Update nb

* Update submission

* Update nb

* Processed UPGLADE
2024-06-20 14:33:00 +01:00

526 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
import jax
from numpyro.infer import MCMC, NUTS, init_to_median
import corner
from getdist import plots
from scipy.stats import multivariate_normal

import csiborgtools

from flow_calibration import *

%load_ext autoreload
%autoreload 2
%matplotlib inline

paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)

LOS density & radial velocity plots

In [ ]:
# fpath = "/mnt/extraspace/rstiskalek/catalogs/A2.h5"
fpath = "/mnt/extraspace/rstiskalek/catalogs/PV_compilation_Supranta2019.hdf5"

loader_carrick = csiborgtools.flow.DataLoader("Carrick2015", "LOSS", fpath, paths, ksmooth=0)
loader_csiborg = csiborgtools.flow.DataLoader("csiborg1", "LOSS", fpath, paths, ksmooth=0)
loader_csiborg2 = csiborgtools.flow.DataLoader("csiborg2_main", "LOSS", fpath, paths, ksmooth=0)
In [ ]:
# ks = [115,  53,  77, 105,  26,  61,  86,  29,  80,  21]
ks = [19,  8, 15,  0, 16,  6, 48, 38, 26, 44]
# ks = [19]
# ks = np.random.choice(50, 10, replace=False)

# k = 6
for k in []:
    fig, axs = plt.subplots(2, 1, figsize=(7, 7), sharex=True)
    # Get rid of vertical spacing
    fig.subplots_adjust(wspace=0)

    # Plot CSiBORG
    for i in range(loader_csiborg.los_density.shape[1]):
        axs[0].plot(loader_csiborg.rdist, loader_csiborg.los_density[k, i, :], alpha=0.1, color="black")
        axs[1].plot(loader_csiborg.rdist, loader_csiborg.los_radial_velocity[k, i, :], alpha=0.1, color="black")

    # CSiBORG1
    axs[0].plot(loader_csiborg.rdist, loader_csiborg.los_density[k, :, :].mean(axis=0), color="red", label="CSiBORG1")
    axs[1].plot(loader_csiborg.rdist, loader_csiborg.los_radial_velocity[k, :, :].mean(axis=0), color="red")

    # CSiBORG2
    axs[0].plot(loader_csiborg2.rdist, loader_csiborg2.los_density[k, :, :].mean(axis=0), color="violet", label="CSiBORG2")
    axs[1].plot(loader_csiborg2.rdist, loader_csiborg2.los_radial_velocity[k, :, :].mean(axis=0), color="violet")

    # Plot Carrick+2015
    axs[0].plot(loader_carrick.rdist, loader_carrick.los_density[k, 0, :], color="blue", label="Carrick+2015")
    axs[1].plot(loader_carrick.rdist, loader_carrick.los_radial_velocity[k, 0, :] * 0.43, color="blue")


    # for i in range(2):
    #     label = "SN"
    #     rdist = loader_csiborg.cat["r_hMpc"][k]
    #     axs[i].axvline(rdist, color="violet", linestyle="--",
    #                 zorder=0, label=label)

    axs[1].set_xlabel(r"$r ~ [\mathrm{Mpc} / h]$")
    axs[0].set_ylabel(r"$\rho_{\rm LOS} / \langle \rho_{\rm matter} \rangle$")
    axs[1].set_ylabel(r"$v_{\rm LOS} ~ [\mathrm{km/s}]$")

    axs[0].set_yscale("log")

    axs[0].legend(loc="upper right")
    axs[0].set_xlim(0, 200)

    fig.tight_layout(w_pad=0, h_pad=0)
    fig.savefig(f"../plots/LOSS_los_{k}.png", dpi=500, bbox_inches="tight")

    fig.show()

Test running a model

In [ ]:
fpath_data = "/mnt/extraspace/rstiskalek/catalogs/PV_compilation.hdf5"
# fpath_data = "/mnt/extraspace/rstiskalek/catalogs/A2.h5"
# fpath_data = "/mnt/extraspace/rstiskalek/catalogs/PV_mock_CB2_17417_large.hdf5"

simname = "Carrick2015"
catalogue = "Pantheon+"
loader = csiborgtools.flow.DataLoader(simname, 0, catalogue, fpath_data, paths, ksmooth=0)
get_model_kwargs = {"zcmb_max": 0.05}

Running HMC

In [ ]:
model = csiborgtools.flow.get_model(loader, **get_model_kwargs)
model_kwargs = {"sample_alpha": False, "sample_beta": True}
In [ ]:
kernel = NUTS(model, init_strategy=init_to_median(num_samples=100))
mcmc = MCMC(kernel, num_warmup=250, num_samples=500)

rng_key = jax.random.PRNGKey(5)
In [ ]:
mcmc.run(rng_key, **model_kwargs)
In [ ]:
mcmc.print_summary()
samples = mcmc.get_samples(group_by_chain=False)
# print(csiborgtools.numpyro_gof(model, mcmc, model_kwargs))
In [ ]:
Vmag = np.sqrt(samples["Vext_x"]**2 + samples["Vext_y"]**2 + samples["Vext_z"]**2)

V = np.vstack([samples["Vext_x"], samples["Vext_y"], samples["Vext_z"]]).T
V = csiborgtools.cartesian_to_radec(V)

l, b = csiborgtools.flow.radec_to_galactic(V[:, 1], V[:, 2])

print(f"|V|  = {np.mean(Vmag)} +- {np.std(Vmag)}")
print(f"l    = {np.mean(l)} +- {np.std(l)}")
print(f"b    = {np.mean(b)} +- {np.std(b)}")
if "beta" in samples:
    print(f"beta = {np.mean(samples['beta'])} +- {np.std(samples['beta'])}")
In [ ]:
data = [l, b, Vmag]
labels = [r"$l$", r"$b$", r"$|\bf{V}_{\rm ext}|$"]
if "alpha" in samples:
    data.append(samples["alpha"])
    labels.append(r"$\alpha$")

if "beta" in samples:
    data.append(samples["beta"])
    labels.append(r"$\beta$")

if "h" in samples:
    data.append(samples["h"])
    labels.append(r"$h$")

data = np.vstack(data).T
fig = corner.corner(data, labels=labels, show_titles=True, title_fmt=".3f", title_kwargs={"fontsize": 12}, smooth=1)
# fig.savefig(f"../../plots/mock_{simname}_{catalogue}.png", dpi=500, bbox_inches="tight")

Vizualize the results

In [ ]:
data, names, gof = read_samples("Pantheon+_groups", "Carrick2015", 0)

fig = corner.corner(data, labels=names_to_latex(names, True), show_titles=True,
                    title_fmt=".3f", title_kwargs={"fontsize": 12}, smooth=1)

$\texttt{LOSS}$ comparison

In [ ]:
LOSS_Carrick_0 = read_samples("LOSS", "Carrick2015", 0, return_MCsamples=True)
LOSS_Carrick_1 = read_samples("LOSS", "Carrick2015", 1, return_MCsamples=True)

LOSS_CB1_0 = read_samples("LOSS", "csiborg1", 0, return_MCsamples=True)
LOSS_CB1_1 = read_samples("LOSS", "csiborg1", 1, return_MCsamples=True)

LOSS_CB2_0 = read_samples("LOSS", "csiborg2_main", 0, return_MCsamples=True)
LOSS_CB2_1 = read_samples("LOSS", "csiborg2_main", 1, return_MCsamples=True)
In [ ]:
X = [
     LOSS_Carrick_0,
     # LOSS_Carrick_1,
     # LOSS_CB1_0,
     LOSS_CB1_1,
     LOSS_CB2_0,
     LOSS_CB2_1,
     ]

# params = ["l", "b", "Vmag", "beta"]
params = None

g = plots.get_subplot_plotter()
g.settings.figure_legend_frame = False
g.settings.alpha_filled_add = 0.75
# g.settings.title_limit_fontsize = 14
g.triangle_plot(X, params=params, filled=True, legend_loc='upper right', )
g.export(f"../plots/LOSS_comparison.png", dpi=500,)

$\texttt{Foundation}$ comparison

In [ ]:
FOUNDATION_Carrick_0 = read_samples("Foundation", "Carrick2015", 0, return_MCsamples=True)
FOUNDATION_Carrick_1 = read_samples("Foundation", "Carrick2015", 1, return_MCsamples=True)

FOUNDATION_CB1_0 = read_samples("Foundation", "csiborg1", 0, return_MCsamples=True)
FOUNDATION_CB1_1 = read_samples("Foundation", "csiborg1", 1, return_MCsamples=True)

FOUNDATION_CB2_0 = read_samples("Foundation", "csiborg2_main", 0, return_MCsamples=True)
FOUNDATION_CB2_1 = read_samples("Foundation", "csiborg2_main", 1, return_MCsamples=True)
In [ ]:
X = [
    FOUNDATION_Carrick_0,
    # FOUNDATION_Carrick_1,
    # FOUNDATION_CB1_0,
    FOUNDATION_CB1_1,
    FOUNDATION_CB2_0,
    FOUNDATION_CB2_1,
    ]

g = plots.get_subplot_plotter()
g.settings.figure_legend_frame = False
g.settings.alpha_filled_add = 0.75
# g.settings.title_limit_fontsize = 14
g.triangle_plot(X, filled=True, legend_loc='upper right')
g.export(f"../plots/FOUNDATION_comparison.png", dpi=500,)

$\texttt{Pantheon+}$ comparison

In [4]:
PANTHEONP_Carrick_0 = read_samples("Pantheon+", "Carrick2015", 0, return_MCsamples=True)
PANTHEONP_Carrick_1 = read_samples("Pantheon+", "Carrick2015", 1, return_MCsamples=True)

# PANTHEONP_CB1_0 = read_samples("Pantheon+", "csiborg1", 0, return_MCsamples=True)
# PANTHEONP_CB1_1 = read_samples("Pantheon+", "csiborg1", 1, return_MCsamples=True)

PANTHEONP_CB2_0 = read_samples("Pantheon+", "csiborg2_main", 0, return_MCsamples=True)
PANTHEONP_CB2_1 = read_samples("Pantheon+", "csiborg2_main", 1, return_MCsamples=True)
Reading Pantheon+ fitted to Carrick2015 with ksmooth = 0.
BIC  = 9952.745117 +- 0.000000
AIC  = 9907.553711 +- 0.000000
logZ = -4945.429688 +- 0.000000
chi2 = 1.147044 +- 0.069862
Removed no burn in

Reading Pantheon+ fitted to Carrick2015 with ksmooth = 1.
BIC  = 9995.297852 +- 0.000000
AIC  = 9950.106445 +- 0.000000
logZ = -4966.300293 +- 0.000000
chi2 = 1.139592 +- 0.069120
Removed no burn in

Reading Pantheon+ fitted to csiborg2_main with ksmooth = 0.
BIC  = 10055.604150 +- 27.237237
AIC  = 10010.412744 +- 27.237237
logZ = -5000.136133 +- 23.062465
chi2 = 0.985968 +- 0.117400
Removed no burn in

Reading Pantheon+ fitted to csiborg2_main with ksmooth = 1.
BIC  = 10023.778857 +- 13.951634
AIC  = 9978.587451 +- 13.951634
logZ = -4979.896411 +- 6.903517
chi2 = 1.115029 +- 0.091582
Removed no burn in
In [7]:
X = [
    PANTHEONP_Carrick_0,
    # PANTHEONP_Carrick_1,
    # PANTHEONP_CB1_0,
    # PANTHEONP_CB1_1,
    PANTHEONP_CB2_0,
    PANTHEONP_CB2_1,
    ]

g = plots.get_subplot_plotter()
g.settings.figure_legend_frame = False
g.settings.alpha_filled_add = 0.75
# g.settings.title_limit_fontsize = 14
g.triangle_plot(X, filled=True, legend_loc='upper right')
# g.export(f"../plots/PANTHEONP_comparison.png", dpi=500,)
No description has been provided for this image

$\texttt{Pantheon+}$ groups

In [8]:
LG = -1

PANTHEONP_Carrick = read_samples("Pantheon+", "Carrick2015", 0, return_MCsamples=True, subtract_LG_velocity=LG, )
PANTHEONP_Carrick_Groups = read_samples("Pantheon+_groups", "Carrick2015", 0, return_MCsamples=True, subtract_LG_velocity=LG)
PANTHEONP_Carrick_Groups_zSN = read_samples("Pantheon+_groups_zSN", "Carrick2015", 0, return_MCsamples=True, subtract_LG_velocity=LG)
PANTHEONP_Carrick_zSN = read_samples("Pantheon+_zSN", "Carrick2015", 0, return_MCsamples=True, subtract_LG_velocity=LG)

# ksmooth = 1
# PANTHEONP_CB2 = read_samples("Pantheon+", "csiborg2_main", ksmooth, return_MCsamples=True, subtract_LG_velocity=LG)
# PANTHEONP_CB2_Groups = read_samples("Pantheon+_groups", "csiborg2_main", ksmooth, return_MCsamples=True, subtract_LG_velocity=LG)
# PANTHEONP_CB2_Groups_zSN = read_samples("Pantheon+_groups_zSN", "csiborg2_main", ksmooth, return_MCsamples=True, subtract_LG_velocity=LG)
Reading Pantheon+ fitted to Carrick2015 with ksmooth = 0.
BIC  = 9952.745117 +- 0.000000
AIC  = 9907.553711 +- 0.000000
logZ = -4945.429688 +- 0.000000
chi2 = 1.147044 +- 0.069862
Removed no burn in

Reading Pantheon+_groups fitted to Carrick2015 with ksmooth = 0.
BIC  = 2578.150635 +- 0.000000
AIC  = 2545.786133 +- 0.000000
logZ = -1259.616211 +- 0.000000
chi2 = 1.185719 +- 0.318355
Removed no burn in

Reading Pantheon+_groups_zSN fitted to Carrick2015 with ksmooth = 0.
BIC  = 2796.622070 +- 0.000000
AIC  = 2764.257568 +- 0.000000
logZ = -1364.911255 +- 0.000000
chi2 = 1.072540 +- 0.119186
Removed no burn in

Reading Pantheon+_zSN fitted to Carrick2015 with ksmooth = 0.
BIC  = 10115.830078 +- 0.000000
AIC  = 10070.638672 +- 0.000000
logZ = -5025.696777 +- 0.000000
chi2 = 1.106855 +- 0.064999
Removed no burn in
In [10]:
params = ["Vmag", "l", "b"]
CMB = MCSamples(samples=multivariate_normal([627, 276, 30], [22, 3, 3]).rvs(size=20000),
                names=params, labels=names_to_latex(params, True), label="CMB")


X = [
    PANTHEONP_Carrick,
    # PANTHEONP_Carrick_Groups,
    # PANTHEONP_Carrick_Groups_zSN,
    PANTHEONP_Carrick_zSN,
    # PANTHEONP_CB2,
    # PANTHEONP_CB2_Groups,
    # PANTHEONP_CB2_Groups_zSN,
    # CMB,
    ]

g = plots.get_subplot_plotter()
g.settings.figure_legend_frame = False
g.settings.alpha_filled_add = 0.75
# g.settings.title_limit_fontsize = 14
g.triangle_plot(X, filled=True, legend_loc='upper right')
g.export(f"../../plots/PANTHEON_GROUPS_Carrick_comparison_LG.png", dpi=500,)
Removed no burn in
No description has been provided for this image

$\texttt{2MTF}$ comparison

In [ ]:
TWOMTF_Carrick_0 = read_samples("2MTF", "Carrick2015", 0, return_MCsamples=True)
TWOMTF_Carrick_1 = read_samples("2MTF", "Carrick2015", 1, return_MCsamples=True)

TWOMTF_CB1_0 = read_samples("2MTF", "csiborg1", 0, return_MCsamples=True)
TWOMTF_CB1_1 = read_samples("2MTF", "csiborg1", 1, return_MCsamples=True)

TWOMTF_CB2_0 = read_samples("2MTF", "csiborg2_main", 0, return_MCsamples=True)
TWOMTF_CB2_1 = read_samples("2MTF", "csiborg2_main", 1, return_MCsamples=True)
In [ ]:
X = [
    TWOMTF_Carrick_0,
    # TWOMTF_Carrick_1,
    # TWOMTF_CB1_0,
    TWOMTF_CB1_1,
    TWOMTF_CB2_0,
    TWOMTF_CB2_1,
    ]

g = plots.get_subplot_plotter()
g.settings.figure_legend_frame = False
g.settings.alpha_filled_add = 0.75
# g.settings.title_limit_fontsize = 14
g.triangle_plot(X, filled=True, legend_loc='upper right')
g.export(f"../plots/2MTF_comparison.png", dpi=500,)

$\texttt{SFI++ galaxies}$ comparison

In [ ]:
SFIGAL_Carrick_0 = read_samples("SFI_gals", "Carrick2015", 0, return_MCsamples=True)
SFIGAL_Carrick_1 = read_samples("SFI_gals", "Carrick2015", 1, return_MCsamples=True)

# SFIGAL_CB1_0 = read_samples("SFI_gals", "csiborg1", 0, return_MCsamples=True)
# SFIGAL_CB1_1 = read_samples("SFI_gals", "csiborg1", 1, return_MCsamples=True)

SFIGAL_CB2_0 = read_samples("SFI_gals", "csiborg2_main", 0, return_MCsamples=True)
SFIGAL_CB2_1 = read_samples("SFI_gals", "csiborg2_main", 1, return_MCsamples=True)
In [ ]:
X = [
    SFIGAL_Carrick_0,
    # SFIGAL_Carrick_1,
    # SFIGAL_CB1_0,
    # SFIGAL_CB1_1,
    # SFIGAL_CB2_0,
    SFIGAL_CB2_1,
    ]

g = plots.get_subplot_plotter()
g.settings.figure_legend_frame = False
g.settings.alpha_filled_add = 0.75
# g.settings.title_limit_fontsize = 14
g.triangle_plot(X, filled=True, legend_loc='upper right')
g.export(f"../plots/SFI_gals_comparison.png", dpi=500,)

$\texttt{SFI++ groups}$ comparison

In [ ]:
SFIGROUP_Carrick_0 = read_samples("SFI_groups", "Carrick2015", 0, return_MCsamples=True)
SFIGROUP_Carrick_1 = read_samples("SFI_groups", "Carrick2015", 1, return_MCsamples=True)

SFIGROUP_CB2_0 = read_samples("SFI_groups", "csiborg2_main", 0, return_MCsamples=True)
SFIGROUP_CB2_1 = read_samples("SFI_groups", "csiborg2_main", 1, return_MCsamples=True)
In [ ]:
X = [
    SFIGROUP_Carrick_0,
    SFIGAL_Carrick_0,
    # SFIGROUP_Carrick_1,
    # SFIGROUP_CB2_0,
    # SFIGROUP_CB2_1,
    ]

g = plots.get_subplot_plotter()
g.settings.figure_legend_frame = False
g.settings.alpha_filled_add = 0.75
# g.settings.title_limit_fontsize = 14
g.triangle_plot(X, filled=True, legend_loc='upper right')
g.export(f"../plots/SFI_gals_vs_groups_comparison.png", dpi=500,)

SN to TF comparison

In [ ]:
LG = 0

# PANTHEONP_Carrick = read_samples("Pantheon+", "Carrick2015", 0, return_MCsamples=True, subtract_LG_velocity=LG, )
# PANTHEONP_Groups_Carrick = read_samples("Pantheon+_groups", "Carrick2015", 0, return_MCsamples=True, subtract_LG_velocity=LG, )
# TWOMTF_Carrick = read_samples("2MTF", "Carrick2015", 0, return_MCsamples=True, subtract_LG_velocity=LG)
# SFIGAL_Carrick = read_samples("SFI_gals", "Carrick2015", 0, return_MCsamples=True, subtract_LG_velocity=LG)

k = 1
PANTHEONP_CB2 = read_samples("Pantheon+", "csiborg2_main", k, return_MCsamples=True, subtract_LG_velocity=LG, )
PANTHEONP_Groups_CB2 = read_samples("Pantheon+_groups", "csiborg2_main", k, return_MCsamples=True, subtract_LG_velocity=LG, )
TWOMTF_CB2 = read_samples("2MTF", "csiborg2_main", k, return_MCsamples=True, subtract_LG_velocity=LG)
SFIGAL_CB2 = read_samples("SFI_gals", "csiborg2_main", k, return_MCsamples=True, subtract_LG_velocity=LG)
In [ ]:
params = ["Vmag", "l", "b"]
CMB = MCSamples(samples=multivariate_normal([627, 276, 30], [22, 3, 3]).rvs(size=20000),
                names=params, labels=names_to_latex(params, True), label="CMB")


X = [
    # PANTHEONP_Carrick,
    # PANTHEONP_Groups_Carrick,
    # TWOMTF_Carrick,
    # SFIGAL_Carrick,
    PANTHEONP_CB2,
    PANTHEONP_Groups_CB2,
    TWOMTF_CB2,
    SFIGAL_CB2,
    CMB,
    ]

g = plots.get_subplot_plotter()
g.settings.figure_legend_frame = False
g.settings.alpha_filled_add = 0.75
# g.settings.title_limit_fontsize = 14
g.triangle_plot(X, filled=True, legend_loc='upper right')
# g.export(f"../../plots/SN_TF_CB2_consistency.png", dpi=500,)

Mock $\texttt{CB2}$ comparison

In [ ]:
SMALLMOCK_CB2_0 = read_samples("CB2_small", "csiborg2_main", 0, return_MCsamples=True)
SMALLMOCK_CB2_1 = read_samples("CB2_small", "csiborg2_main", 1, return_MCsamples=True)

LARGEMOCK_CB2_0 = read_samples("CB2_large", "csiborg2_main", 0, return_MCsamples=True)
LARGEMOCK_CB2_1 = read_samples("CB2_large", "csiborg2_main", 1, return_MCsamples=True)
In [ ]:
X = [
    # SMALLMOCK_CB2_0,
    # SMALLMOCK_CB2_1,
    LARGEMOCK_CB2_0,
    LARGEMOCK_CB2_1,
    ]

g = plots.get_subplot_plotter()
g.settings.figure_legend_frame = False
g.settings.alpha_filled_add = 0.75
# g.settings.title_limit_fontsize = 14
g.triangle_plot(X, filled=True, legend_loc='upper right')
g.export(f"../plots/CB2_mocks_large.png", dpi=500,)

External flow consistency

Carrick2015

In [ ]:
X = [
    # LOSS_Carrick_0,
    # FOUNDATION_Carrick_0,
    PANTHEONP_Carrick_0,
    TWOMTF_Carrick_0,
    SFIGAL_Carrick_0,
    ]

params = ["Vmag", "l", "b", "beta"]
g = plots.get_subplot_plotter()
g.settings.figure_legend_frame = False
g.settings.alpha_filled_add = 0.75
# g.settings.title_limit_fontsize = 14
g.triangle_plot(X, params=params, filled=True, legend_loc='upper right',)
g.export(f"../plots/Carrick2015_external_flow.png", dpi=500,)

CSiBORG1

In [ ]:
X = [
    # LOSS_CB1_1,
    # FOUNDATION_CB1_1,
    PANTHEONP_CB1_1,
    TWOMTF_CB1_1,
    # SFIGAL_CB1_1,
    ]

params = ["Vmag", "l", "b", "beta"]
g = plots.get_subplot_plotter()
g.settings.figure_legend_frame = False
g.settings.alpha_filled_add = 0.75
# g.settings.title_limit_fontsize = 14
g.triangle_plot(X, params=params, filled=True, legend_loc='upper right',)
g.export(f"../plots/CB1_external_flow.png", dpi=500,)

CSiBORG2

In [ ]:
X = [
    # LOSS_CB2_1,
    # FOUNDATION_CB2_1,
    PANTHEONP_CB2_1,
    TWOMTF_CB2_1,
    SFIGAL_CB2_1,
    ]

params = ["Vmag", "l", "b", "beta"]
g = plots.get_subplot_plotter()
g.settings.figure_legend_frame = False
g.settings.alpha_filled_add = 0.75
# g.settings.title_limit_fontsize = 14
g.triangle_plot(X, params=params, filled=True, legend_loc='upper right',)
g.export(f"../plots/CB2_external_flow.png", dpi=500,)
In [ ]:
k = 1
LG = 0

# Carrick
# LOSS_Carrick_LG = read_samples("LOSS", "Carrick2015", k, return_MCsamples=True, subtract_LG_velocity=LG)
# FOUNDATION_Carrick_LG = read_samples("Foundation", "Carrick2015", k, return_MCsamples=True, subtract_LG_velocity=LG)
# PANTHEON_Carrick_LG = read_samples("Pantheon+", "Carrick2015", k, return_MCsamples=True, subtract_LG_velocity=LG)
# TWOMTF_Carrick_LG = read_samples("2MTF", "Carrick2015", k, return_MCsamples=True, subtract_LG_velocity=LG)
SFIGAL_Carrick_LG = read_samples("SFI_gals", "Carrick2015", k, return_MCsamples=True, subtract_LG_velocity=LG)
SFIGROUPS_Carrick_LG = read_samples("SFI_groups", "Carrick2015", k, return_MCsamples=True, subtract_LG_velocity=LG)


# # CSiBORG2
# LOSS_CB2_LG = read_samples("LOSS", "csiborg2_main", k, return_MCsamples=True,subtract_LG_velocity=LG)
# FOUNDATION_CB2_LG = read_samples("Foundation", "csiborg2_main", k, return_MCsamples=True, subtract_LG_velocity=LG)
# PANTHEON_CB2_LG = read_samples("Pantheon+", "csiborg2_main", k, return_MCsamples=True, subtract_LG_velocity=LG)
# TWOMTF_CB2_LG = read_samples("2MTF", "csiborg2_main", k, return_MCsamples=True, subtract_LG_velocity=LG)
SFIGAL_CB2_LG = read_samples("SFI_gals", "csiborg2_main", k, return_MCsamples=True, subtract_LG_velocity=LG)
SFIGROUP_CB2_LG = read_samples("SFI_groups", "csiborg2_main", k, return_MCsamples=True, subtract_LG_velocity=LG)

# # CSiBORG1
# LOSS_CB1_LG = read_samples("LOSS", "csiborg1", k, return_MCsamples=True, subtract_LG_velocity=LG)
# FOUNDATION_CB1_LG = read_samples("Foundation", "csiborg1", k, return_MCsamples=True, subtract_LG_velocity=LG)
# PANTHEON_CB1_LG = read_samples("Pantheon+", "csiborg1", k, return_MCsamples=True, subtract_LG_velocity=LG)
# TWOMTF_CB1_LG = read_samples("2MTF", "csiborg1", k, return_MCsamples=True, subtract_LG_velocity=LG)
# SFIGAL_CB1_LG = read_samples("SFI_gals", "csiborg1", k, return_MCsamples=True, subtract_LG_velocity=LG)
In [ ]:
params = ["Vmag", "l", "b"]
CMB = MCSamples(samples=multivariate_normal([627, 276, 30], [22, 3, 3]).rvs(size=20000),
                names=params, labels=names_to_latex(params, True), label="CMB")

X = [
    # LOSS_Carrick_LG,
    # FOUNDATION_Carrick_LG,
    # PANTHEON_Carrick_LG,
    # TWOMTF_Carrick_LG,
    # SFIGAL_Carrick_LG,
    # SFIGROUPS_Carrick_LG,
    # LOSS_CB1_LG,
    # FOUNDATION_CB1_LG,
    # PANTHEON_CB1_LG,
    # TWOMTF_CB1_LG,
    # SFIGAL_CB1_LG,
    # LOSS_CB2_LG,
    # FOUNDATION_CB2_LG,
    # PANTHEON_CB2_LG,
    # TWOMTF_CB2_LG,
    SFIGAL_CB2_LG,
    SFIGROUP_CB2_LG,
    CMB,
    ]

g = plots.get_subplot_plotter()
g.settings.figure_legend_frame = False
g.settings.alpha_filled_add = 0.75
# g.settings.title_limit_fontsize = 14
g.triangle_plot(X, params=params, filled=True, legend_loc='upper right', )
# g.export(f"../plots/ALL_dipole.png", dpi=500,)
In [ ]: