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>
344 KiB
344 KiB
In [1]:
import numpy as np
%matplotlib notebook
import matplotlib.pyplot as plt
try:
import csiborgtools
except ModuleNotFoundError:
import sys
sys.path.append("../")
import csiborgtools
import utils
%load_ext autoreload
%autoreload 2
import joblib
from os.path import join
from glob import glob
In [2]:
Nsim = 9844
simpath = csiborgtools.io.get_sim_path(Nsim)
Nsnap = 1016
outfname = join(utils.dumpdir, "ramses_out_{}_{}.npy".format(str(Nsim).zfill(5), str(Nsnap).zfill(5)))
mmain = csiborgtools.io.read_mmain(Nsim, "/mnt/zfsusers/hdesmond/Mmain")
data = np.load(outfname)
data = csiborgtools.io.merge_mmain_to_clumps(data, mmain)
data = data[(data["npart"] > 100) & np.isfinite(data["m200"])]
boxunits = csiborgtools.units.BoxUnits(Nsnap, simpath)
In [22]:
R = np.sqrt((data["peak_x"] - 0.5)**2 + (data["peak_y"] - 0.5)**2 + (data["peak_z"] - 0.5)**2)
In [29]:
boxunits.box2kpc(0.21) * 1e-3
Out[29]:
In [30]:
plt.figure()
plt.hist(R, bins="auto")
plt.axvline(0.22, c="red")
plt.show()
In [34]:
mass = boxunits.box2solarmass(data["m200"])
Out[34]:
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In [3]:
# Nsplit = 0
# loaddir = join(utils.dumpdir, "temp")
# parts, part_clumps, clumps = csiborgtools.fits.load_split_particles(
# Nsplit, loaddir, Nsim, Nsnap, remove_split=False)
In [43]:
# n = 584
# xs = csiborgtools.fits.pick_single_clump(n, parts, part_clumps, clumps)
# halo = csiborgtools.fits.Clump.from_arrays(*xs, rhoc=boxunits.box_rhoc)
# print(halo.Npart)
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