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https://github.com/Richard-Sti/csiborgtools.git
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ee222cd010
* Update nb * Update script * Update script * Rename * Update script * Update script * Remove warning * Ignore minors when extracting MAH * Fix paths bug * Move notebooks * Move files * Rename and delete things * Rename file * Move file * Rename things * Remove old print statement * Add basic MAH plot * Add random MAH path * Output snapshot numbers * Add MAH random extraction * Fix redshift bug * Edit script * Add extracting random MAH * Little updates * Add CB2 redshift * Add some caching * Add diagnostic plots * Add caching * Minor updates * Update nb * Update notebook * Update script * Add Sorce randoms * Add CB2 varysmall * Update nb * Update nb * Update nb * Use catalogue HMF * Move definition of radec2galactic * Update nb * Update import * Update import * Add galatic coords to catalogues * Update nb
198 KiB
198 KiB
In [1]:
import numpy as np
%matplotlib notebook
import matplotlib.pyplot as plt
import sys
sys.path.append("../")
import galomatch
import utils
%load_ext autoreload
%autoreload 2
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mmains = utils.load_mmains(1)
mmains = galomatch.utils.list_to_ndarray(mmains, ["ra", "dec", "mass_cl"])
sim = mmains[0, ...]
sim = sim[sim[:, 2] > 1e13, :]
Nsim = sim.shape[0]
obs = utils.load_2mpp()
Nobs = obs.size
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RA1 = obs["RA"]
DEC1 = obs["DEC"]
RA2 = sim[:, 0]
DEC2 = sim[:, 1]
bins = np.logspace(np.log10(0.005), np.log10(10.0), 15)
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# galomatch.match.angular_tpcf(bins, RA1, DEC1, RA2, DEC2)
x2 = galomatch.match.angular_tpcf(bins, RA1, DEC1, RA2, DEC2, nthreads=4)
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x1
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x2
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plt.figure()
plt.scatter(RA1, DEC1, s=0.001)
plt.scatter(RA2, DEC2, s=0.1)
plt.show()
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randNsim = Nsim * 5
randNobs = Nobs * 5
randRAsim, randDECsim = galomatch.match.get_randoms_sphere(randNsim, seed=42)
randRAobs, randDECobs = galomatch.match.get_randoms_sphere(randNobs, seed=21)
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from Corrfunc.mocks import DDtheta_mocks
from Corrfunc.utils import convert_3d_counts_to_cf
nthreads = 1
RA1 = obs["RA"]
DEC1 = obs["DEC"]
RA2 = RA1
DEC2 = DEC1
# RA2 = sim[:, 0]
# DEC2 = sim[:, 1]
D1D2 = DDtheta_mocks(0, nthreads, bins, RA1, DEC1, RA2=RA2, DEC2=DEC2)
D1R2 = DDtheta_mocks(0, nthreads, bins, RA1, DEC1, RA2=randRAsim, DEC2=randDECsim)
D2R1 = DDtheta_mocks(0, nthreads, bins, RA2, DEC2, RA2=randRAobs, DEC2=randDECobs)
R1R2 = DDtheta_mocks(0, nthreads, bins, randRAobs, randDECobs, RA2=randRAsim, DEC2=randDECsim)
cf = convert_3d_counts_to_cf(Nobs, Nsim, randNobs, randNsim, D1D2, D1R2, D2R1, R1R2)
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convert_3d_counts_to_cf()
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x = [0.5 * (bins[i + 1] + bins[i]) for i in range(bins.size - 1)]
plt.figure()
plt.plot(x, cf)
# plt.yscale("log")
plt.xscale("log")
plt.show()
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plt.figure()
plt.plot(DR["thetaavg"], DR["npairs"])
plt.yscale("log")
plt.xscale("log")
plt.show()
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cf = convert_3d_counts_to_cf(Ngals, Ngals, randN, randN, DD, DR, DR, RR)
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fpath = "/mnt/zfsusers/rstiskalek/galomatch/data/HFI_PCCS_SZ-union_R2.08.fits"
obs = galomatch.io.read_planck2015(fpath, cosmo, 214)
c1 = SkyCoord(ra=obs["RA"]*u.degree, dec=obs["DEC"]*u.degree, distance=obs["COMDIST"]*u.Mpc)
c2 = SkyCoord(ra=sim["ra"]*u.degree, dec=sim["dec"]*u.degree, distance=sim["dist"]*u.Mpc)
sep, indxs = galomatch.match.brute_spatial_separation(c1, c2, N=100, angular=False, verbose=True, )
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