csiborgtools/notebooks/flow/selection.ipynb
Richard Stiskalek 2b938c112c
More flow preparation & Olympics (#143)
* Add more comments

* Add flow paths

* Simplify paths

* Update default arguemnts

* Update paths

* Update param names

* Update some of scipts for reading files

* Add the Mike method option

* Update plotting

* Update fnames

* Simplify things

* Make more default options

* Add print

* Update

* Downsample CF4

* Update numpyro selection

* Add selection fitting nb

* Add coeffs

* Update script

* Add nb

* Add label

* Increase number of steps

* Update default params

* Add more labels

* Improve file name

* Update nb

* Fix little bug

* Remove import

* Update scales

* Update labels

* Add script

* Update script

* Add more

* Add more labels

* Add script

* Add submit

* Update spacing

* Update submit scrips

* Update script

* Update defaults

* Update defaults

* Update nb

* Update test

* Update imports

* Add script

* Add support for Indranil void

* Add a dipole

* Update nb

* Update submit

* Update Om0

* Add final

* Update default params

* Fix bug

* Add option to fix to LG frame

* Add Vext label

* Add Vext label

* Update script

* Rm fixed LG

* rm LG stuff

* Update script

* Update bulk flow plotting

* Update nb

* Add no field option

* Update defaults

* Update nb

* Update script

* Update nb

* Update nb

* Add names to plots

* Update nb

* Update plot

* Add more latex names

* Update default

* Update nb

* Update np

* Add plane slicing

* Add nb with slices

* Update nb

* Update script

* Upddate nb

* Update nb
2024-09-11 08:45:42 +02:00

14 KiB

Density & velocity fields alond a LOS

In [128]:
# 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 jax import numpy as jnp
from numpyro.infer import MCMC, NUTS, init_to_median

import csiborgtools


%load_ext autoreload
%autoreload 2
%matplotlib inline

paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
The autoreload extension is already loaded. To reload it, use:
  %reload_ext autoreload

LOS density & radial velocity plots

In [129]:
fpath = "/mnt/extraspace/rstiskalek/catalogs/PV_compilation.hdf5"

loader_carrick = csiborgtools.flow.DataLoader("Carrick2015", [0], "Pantheon+", fpath, paths, ksmooth=0, )
# loaders_csiborg2X = [csiborgtools.flow.DataLoader("csiborg2X", i, "LOSS", fpath, paths, ksmooth=1, verbose=False) for i in range(20)]
# loaders_csiborg2 = [csiborgtools.flow.DataLoader("csiborg2_main", i, "LOSS", fpath, paths, ksmooth=1, verbose=False) for i in range(20)]

# loader_CF4 = csiborgtools.flow.DataLoader("CF4gp", [0], "LOSS", fpath, paths, ksmooth=0, )
# loader_lilow = csiborgtools.flow.DataLoader("Lilow2024", [0], "LOSS", fpath, paths, ksmooth=0, )
2024-07-17 10:04:21.726937:   reading the catalogue,
2024-07-17 10:04:21.744932:   reading the interpolated field,
2024-07-17 10:04:21.770393:   calculating the radial velocity.
/mnt/users/rstiskalek/csiborgtools/csiborgtools/flow/flow_model.py:91: UserWarning: The number of radial steps is even. Skipping the first step at 0.0 because Simpson's rule requires an odd number of steps.
  warn(f"The number of radial steps is even. Skipping the first "
In [130]:
# ks = [i for i in range(50)]
# ks = [30, 50,]
ks = np.random.choice(50, 2, replace=False)

for k in ks:
    fig, axs = plt.subplots(2, 1, figsize=(7, 7), sharex=True)
    fig.subplots_adjust(wspace=0)
    cols = plt.rcParams['axes.prop_cycle'].by_key()['color']

    # # CSiBORG2
    # x = loaders_csiborg2X[0].rdist
    # y = np.asarray([loaders_csiborg2[i].los_density[k, :] for i in range(len(loaders_csiborg2X))])
    # ylow, ymed, yhigh = np.percentile(y, [16, 50, 84], axis=0)
    # axs[0].fill_between(x, ylow, yhigh, color=cols[0], alpha=0.25)
    # axs[0].plot(x, ymed, color=cols[0], label="CSiBORG2")

    # y = np.asarray([loaders_csiborg2[i].los_radial_velocity[k, :] for i in range(len(loaders_csiborg2X))])
    # ylow, ymed, yhigh = np.percentile(y, [16, 50, 84], axis=0)
    # axs[1].fill_between(x, ylow, yhigh, color=cols[0], alpha=0.25)
    # axs[1].plot(x, ymed, color=cols[0], label="CSiBORG2")

    # # CSiBORG2X
    # x = loaders_csiborg2X[0].rdist
    # y = np.asarray([loaders_csiborg2X[i].los_density[k, :] for i in range(len(loaders_csiborg2X))])
    # ylow, ymed, yhigh = np.percentile(y, [16, 50, 84], axis=0)
    # axs[0].fill_between(x, ylow, yhigh, color=cols[1], alpha=0.25)
    # axs[0].plot(x, ymed, color=cols[1], label="CSiBORG2X")

    # y = np.asarray([loaders_csiborg2X[i].los_radial_velocity[k, :] for i in range(len(loaders_csiborg2X))])
    # ylow, ymed, yhigh = np.percentile(y, [16, 50, 84], axis=0)
    # axs[1].fill_between(x, ylow, yhigh, color=cols[1], alpha=0.25)
    # axs[1].plot(x, ymed, color=cols[1], label="CSiBORG2X")

    # Plot Carrick+2015
    axs[0].plot(loader_carrick.rdist, loader_carrick.los_density[0, k, :], color="red", label="Carrick+2015")
    axs[1].plot(loader_carrick.rdist, loader_carrick.los_radial_velocity[0, k, :] * 0.43, color="red")
    axs[1].axvline(loader_carrick._rmax[0, k], c="black", linestyle="--")

    # # Plot CF4
    # c = cols[4]
    # axs[0].plot(loader_CF4.rdist, loader_CF4.los_density[0, k, :], color=c, label="CF4")
    # axs[1].plot(loader_CF4.rdist, loader_CF4.los_radial_velocity[0, k, :], color=c)

    # # Plot Lilow2024
    # c = cols[5]
    # axs[0].plot(loader_lilow.rdist, loader_lilow.los_density[0, k, :], color=c, label="Lilow+2024")
    # axs[1].plot(loader_lilow.rdist, loader_lilow.los_radial_velocity[0, k, :], color=c)
    axs[1].axhline(0, color="black", linestyle="--")


    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()
No description has been provided for this image
No description has been provided for this image

Test running a model

In [84]:
fpath_data = "/mnt/extraspace/rstiskalek/catalogs/PV_compilation.hdf5"

simname = "Carrick2015"
catalogue = "LOSS"
loader = csiborgtools.flow.DataLoader(simname, [0, 0], catalogue, fpath_data, paths, ksmooth=0, )

SN_hyperparams = {"e_mu_mean": 0.1, "e_mu_std": 0.05,
                  "mag_cal_mean": -18.25, "mag_cal_std": 0.5,
                  "alpha_cal_mean": 0.148, "alpha_cal_std": 0.05,
                  "beta_cal_mean": 3.112, "beta_cal_std": 1.0,
                  }
calibration_hyperparams = {"Vext_std": 250,
                           "alpha_mean": 1.0, "alpha_std": 0.5,
                           "beta_mean": 1.0, "beta_std": 0.5,
                           "sigma_v_mean": 150., "sigma_v_std": 100.,
                           "sample_alpha": True, "sample_beta": True,
                           }
get_model_kwargs = {"zcmb_max": 0.05}
2024-06-29 19:40:25.229961:   reading the catalogue,
2024-06-29 19:40:25.243502:   reading the interpolated field,
2024-06-29 19:40:25.261423:   calculating the radial velocity.
/mnt/users/rstiskalek/csiborgtools/csiborgtools/flow/flow_model.py:91: UserWarning: The number of radial steps is even. Skipping the first step at 0.0 because Simpson's rule requires an odd number of steps.
  warn(f"The number of radial steps is even. Skipping the first "

Running HMC

In [85]:
model = csiborgtools.flow.get_model(loader, **get_model_kwargs)
model_kwargs = {"distmod_hyperparams": SN_hyperparams, "calibration_hyperparams": calibration_hyperparams,}
Selected 50/50 galaxies.
In [86]:
kernel = NUTS(model, init_strategy=init_to_median(num_samples=100))
mcmc = MCMC(kernel, num_warmup=500, num_samples=500)

rng_key = jax.random.PRNGKey(5)
mcmc.run(rng_key, extra_fields=("potential_energy",), **model_kwargs)
mcmc.print_summary()
samples = mcmc.get_samples()
sample: 100%|██████████| 1000/1000 [02:10<00:00,  7.68it/s, 7 steps of size 4.49e-01. acc. prob=0.90]  
                 mean       std    median      5.0%     95.0%     n_eff     r_hat
    Vext[0]     -3.71     69.92     -3.04   -123.73    103.87    469.72      1.00
    Vext[1]    -27.47     95.52    -30.48   -151.20    172.63    308.02      1.00
    Vext[2]    -59.27    131.26    -57.79   -273.64    137.55    456.29      1.00
      alpha      1.09      0.38      1.10      0.50      1.69    400.05      1.00
  alpha_cal      0.13      0.03      0.13      0.09      0.17    558.81      1.00
       beta      0.43      0.11      0.44      0.27      0.61    341.86      1.00
   beta_cal      3.54      0.18      3.54      3.23      3.81    606.77      1.00
       e_mu      0.08      0.03      0.08      0.04      0.12    330.71      1.00
    mag_cal    -18.19      0.04    -18.19    -18.25    -18.13    389.94      1.00
    sigma_v    176.93     52.05    169.93    102.74    267.56    315.30      1.00

Number of divergences: 0
In [ ]: