mirror of
https://github.com/DifferentiableUniverseInitiative/JaxPM.git
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6693e5c725
* Use cosmo as arg for the ODE function * Update examples * format * notebook update * fix tests * add correct annotations for weights in painting and warning for cic_paint in distributed pm * update test_against_fpm * update distributed tests and add jacfwd jacrev and vmap tests * format * add Caveats to notebook readme * final touches * update Growth.py to allow using FastPM solver * fix 2D painting when input is (X , Y , 2) shape * update cic read halo size and notebooks examples * Allow env variable control of caching in growth * Format * update test jax version * update notebooks/03-MultiGPU_PM_Halo.ipynb * update numpy install in wf * update tolerance :) * reorganize install in test workflow * update tests * add mpi4py * update tests.yml * update tests * update wf * format * make normal_field signature consistent with jax.random.normal * update by default normal_field dtype to match JAX * format * debug test workflow * format * debug test workflow * updating tests * fix accuracy * fixed tolerance * adding caching * Update conftest.py * Update tolerance and precision settings in distributed PM tests * revererting back changes to growth.py --------- Co-authored-by: Francois Lanusse <fr.eiffel@gmail.com> Co-authored-by: Francois Lanusse <EiffL@users.noreply.github.com>
4.9 MiB
4.9 MiB
In [1]:
import numpy as np
%matplotlib notebook
import matplotlib.pyplot as plt
# Local imports
try:
import csiborgtools
except ModuleNotFoundError:
import sys
sys.path.append("../")
import csiborgtools
import utils
%load_ext autoreload
%autoreload 2
In [28]:
Nsim = 9844
Nsnap = 1016
sim = utils.load_processed(Nsim, Nsnap)
sim = sim[sim["dist"] < 200]
gals = utils.load_2mpp()
gals = gals[gals["CDIST_CMB"] < 200]
planck = utils.load_planck2015()
In [101]:
dx = 40
dmin = 100
dmax = dmin + dx
mask_obs = (dmin < gals["CDIST_CMB"]) & (gals["CDIST_CMB"] < dmax)
mask_sim = (dmin < sim["dist"]) & (sim["dist"] < dmax) & (sim["m200"] > 1e12)
mask_planck = (dmin < planck["COMDIST"]) & (planck["COMDIST"] < dmax)
print(mask_planck.sum())
plt.figure()
plt.scatter(sim["ra"][mask_sim], sim["dec"][mask_sim], s=1, label="CSiBORG")
plt.scatter(gals["RA"][mask_obs], gals["DEC"][mask_obs], s=1, label="2M++")
plt.scatter(planck["RA"][mask_planck], planck["DEC"][mask_planck], s=50, label="Planck", c="m")
plt.legend()
plt.title(r"$M_{{200c}} > 10^{{12}} M_\odot$ and ${}~\mathrm{{Mpc}} < D_{{c}} < {}~\mathrm{{Mpc}}$"
.format(dmin, dmax))
plt.xlabel(r"$\mathrm{RA}$")
plt.ylabel(r"$\delta$")
plt.savefig("../plots/sky_comparison.png", dpi=400)
plt.show()
In [75]:
planck = utils.load_planck2015(1500)
plt.figure()
plt.scatter(planck["COMDIST"], planck["MSZ"], s=3)
plt.axvline(200, c="red", zorder=0)
plt.title("Planck clusters")
plt.xlabel(r"$D_{c}~[\mathrm{Mpc}]$")
plt.ylabel(r"$M_{500c}$")
plt.yscale("log")
plt.tight_layout()
plt.savefig("../plots/planck_mass_dist.png", dpi=450)
plt.show()
In [77]:
planck = utils.load_planck2015(200)
In [103]:
mask_sim = sim["m500"] > 1e14
mask_planck = planck["MSZ"] > 1e14
plt.figure()
plt.scatter(planck["RA"], planck["DEC"], label="Planck", c=np.log10(planck["MSZ"]))
plt.colorbar()
plt.scatter(sim["ra"][mask_sim], sim["dec"][mask_sim], label="CSiBORG", c="red", s=3, zorder=1)
plt.legend(loc=2)
plt.title(r"Sky comparison of CSiBORG and Planck of $M_{500c} > 10^{14} M_\odot$")
plt.xlabel(r"$\mathrm{RA}$")
plt.ylabel(r"$\delta$")
plt.tight_layout()
plt.savefig("../plots/clusters_positions.png", dpi=450)
plt.show()
In [ ]: