How to run CorrHOD_cubic#
import numpy as np
import matplotlib.pyplot as plt
from pathlib import Path
from pycorr import project_to_multipoles
from CorrHOD import CorrHOD_cubic
# Get the number of threads available
import multiprocessing
nthread = multiprocessing.cpu_count()
print(f'Number of threads available: {nthread}')
Number of threads available: 256
# Logging
import sys
from CorrHOD import create_logger
from mockfactory import setup_logging
# Get a logger object
setup_logging() # Initialize the logging for all the loggers that will not have a handler
logger = create_logger('CorrHOD', level='debug', stream=sys.stdout)
# Define the parameters we will use
path2config = Path('config.yaml')
# let's define some parameters to pass to the HOD model
HOD_params = {
'logM_cut': 12,
'logM1': 13,
'sigma': 0.32,
'alpha': 1.11,
'kappa': 10**(-1.43),
'alpha_c': 0.0,
'alpha_s': 0.0,
'Bcent': 0.0,
'Bsat': 0.0
}
# The parameters we did not define will take the default values from the config file
# DensitySplit parameters
nquantiles = 10 # Number of quantiles to split the sample
# Correlation functions parameters
sbins = np.linspace(0.1, 30, 50) # Bins in s for the CFs (default ones)
edges = [sbins, np.linspace(-1, 1, 60)]
# Initialize the CorrHOD object
Object = CorrHOD_cubic(path2config, HOD_params, los='z')
Object.initialize_halo() # Load the halo catalog
Object.populate_halos() # Populate the halos with galaxies
print('Tracer used: ', Object.tracer)
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gen mocks 26.767639636993408
Number density of the populated halos : 9.89e-04 h^3/Mpc^3
Tracer used: LRG
data_positions = Object.get_tracer_positions() # Get the positions of the galaxies
# Compute the DensitySplit
quantiles, density = Object.compute_DensitySplit(nquantiles=nquantiles, nthread=nthread)
[000133.50] [0/1] 07-13 13:33 FFTWEngine INFO Loading wisdom from wisdom.shape-400-400-400.type-float64.nthreads-256.npy.
[000133.55] [0/1] 07-13 13:33 FFTWEngine INFO Saving wisdom to wisdom.shape-400-400-400.type-float64.nthreads-256.npy.
fig, ax = plt.subplots(1, 2, figsize=(12, 4))
# Plot the quantiles density
from pandas import qcut
density_quantiles = []
q_cut = qcut(density, nquantiles, labels=False)
for i in range(nquantiles):
density_quantiles.append(density[q_cut == i])
ax[1].hist(density_quantiles[i], bins=100, density=True, alpha=0.8, label=f'Q{i}')
ax[0].hist(density, bins=500, density=True, alpha=0.7, color='k')
ax[0].set_xlabel(r'$\Delta(R_s)$', fontsize=15)
ax[1].set_xlabel(r'$\Delta(R_s)$', fontsize=15)
ax[0].set_ylabel('PDF', fontsize=15)
fig.suptitle(f'Density PDFs for {nquantiles} quantiles', fontsize=15);
# Plot the positions in the sky
fig, ax = plt.subplots(1, 2, figsize=(12, 5))
boxsize = Object.boxsize
cut = data_positions[:, 2] < 50
ax[0].scatter(data_positions[cut, 0], data_positions[cut, 1], s=0.1, color='grey', label='Galaxies')
ax[1].scatter(data_positions[cut, 0], data_positions[cut, 1], s=0.1, color='grey', label='Galaxies')
for i, ids in enumerate([0, nquantiles-1]):
cut = quantiles[ids][:, 2] < 50
ax[i].scatter(quantiles[ids][cut, 0], quantiles[ids][cut, 1], s=0.1, color='crimson', label='Density split')
ax[i].set_title(f'DS{ids}', fontsize=12)
ax[i].set_xlabel('x [Mpc/h]', fontsize=12)
ax[i].set_ylabel('x [Mpc/h]', fontsize=12)
# ax[i].set_xlim(0, boxsize)
# ax[i].set_ylim(0, boxsize)
ax[0].legend(fontsize=12, markerscale=5, loc='upper left')
plt.show();
# Downsample galaxies and quantiles to speed up the computing time
new_n = 5e-4 # New number density
Object.downsample_data(new_n=new_n);
Downsampling the data to a number density of 5.00e-04 h^3/Mpc^3: 4000000 galaxies remaining from 7911150 galaxies
# Compute the 2PCF
xi = Object.compute_2pcf(edges=edges, nthread=nthread)
xi.plot(mode='poles'); # Quick way to plot the CFs from pycorr
[000468.74] [0/1] 07-13 13:39 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000468.74] [0/1] 07-13 13:39 TwoPointCorrelationFunction INFO Running auto-correlation.
[000468.74] [0/1] 07-13 13:39 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000485.09] [0/1] 07-13 13:39 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
# Compute the Cross-Correlation for DS0 and DS9
xi_0 = Object.compute_cross_corr(0, edges=edges, nthread=nthread)
xi_9 = Object.compute_cross_corr(9, edges=edges, nthread=nthread)
The run_all() method#
The following code will run the full analysis for the cubic HOD model.
import numpy as np
import matplotlib.pyplot as plt
from pathlib import Path
from CorrHOD import CorrHOD_cubic
# Get the number of threads available
import multiprocessing
nthread = multiprocessing.cpu_count()
print(f'Number of threads available: {nthread}')
# Get the loggers
import sys
from CorrHOD import create_logger
from mockfactory import setup_logging
setup_logging() # Initialize the logging for all the loggers that will not have a handler
logger = create_logger('CorrHOD', level='debug', stream=sys.stdout)
path2config = Path('config.yaml')
HOD_params = {
'logM_cut': 12,
'logM1': 13,
'sigma': 0.32,
'alpha': 1.11,
'kappa': 10**(-1.43),
'alpha_c': 0.0,
'alpha_s': 0.0,
'Bcent': 0.0,
'Bsat': 0.0
}
# DensitySplit parameters
nquantiles = 10 # Number of quantiles to split the sample
Object = CorrHOD_cubic(path2config, HOD_params)
# We artificially reduce the number density to speed up the computation time
new_n = 1e-4 # Density to downsample to after the DensitySplit
Object.run_all(downsample_to=new_n, nquantiles=nquantiles, nthread=nthread)
Number of threads available: 256
Running CorrHOD with the following parameters (0) :
Simulation : AbacusSummit_base_c000_ph000
logM_cut : 12
logM1 : 13
sigma : 0.32
alpha : 1.11
kappa : 0.03715352290971726
alpha_c : 0.0
alpha_s : 0.0
Bcent : 0.0
Bsat : 0.0
Number density : 1.00e-03 h^3/Mpc^3
Initializing and populating the halos ...
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Initialized the halos in 59.05 s
gen mocks 28.902310609817505
Number density of the populated halos : 9.89e-04 h^3/Mpc^3
Computing along the x line of sight ...
Computing the DensitySplit ...
[000091.32] [0/1] 07-13 13:42 FFTWEngine INFO Loading wisdom from wisdom.shape-400-400-400.type-float64.nthreads-256.npy.
[000091.36] [0/1] 07-13 13:42 FFTWEngine INFO Saving wisdom to wisdom.shape-400-400-400.type-float64.nthreads-256.npy.
Computed the DensitySplit in 28.80 s
Downsampling the data to a number density of 1.00e-04 h^3/Mpc^3: 800000 galaxies remaining from 7911150 galaxies
Downsampled the galaxies to 1.00e-04 h^3/Mpc^3
Computing the 2PCF ...
[000120.57] [0/1] 07-13 13:43 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000120.57] [0/1] 07-13 13:43 TwoPointCorrelationFunction INFO Running auto-correlation.
[000120.57] [0/1] 07-13 13:43 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000137.96] [0/1] 07-13 13:43 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the 2PCF in 17.40 s
Computing the auto-correlation and cross-correlation of quantile 0 ...
[000137.97] [0/1] 07-13 13:43 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000137.97] [0/1] 07-13 13:43 TwoPointCorrelationFunction INFO Running auto-correlation.
[000137.97] [0/1] 07-13 13:43 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000152.72] [0/1] 07-13 13:43 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 0 in 14.76 s
[000152.73] [0/1] 07-13 13:43 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000152.73] [0/1] 07-13 13:43 TwoPointCorrelationFunction INFO Running cross-correlation.
[000152.73] [0/1] 07-13 13:43 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000181.82] [0/1] 07-13 13:44 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 0 in 29.09 s
Computing the auto-correlation and cross-correlation of quantile 1 ...
[000181.82] [0/1] 07-13 13:44 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000181.82] [0/1] 07-13 13:44 TwoPointCorrelationFunction INFO Running auto-correlation.
[000181.82] [0/1] 07-13 13:44 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000196.89] [0/1] 07-13 13:44 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 1 in 15.07 s
[000196.89] [0/1] 07-13 13:44 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000196.89] [0/1] 07-13 13:44 TwoPointCorrelationFunction INFO Running cross-correlation.
[000196.89] [0/1] 07-13 13:44 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000224.87] [0/1] 07-13 13:45 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 1 in 27.98 s
Computing the auto-correlation and cross-correlation of quantile 2 ...
[000224.87] [0/1] 07-13 13:45 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000224.87] [0/1] 07-13 13:45 TwoPointCorrelationFunction INFO Running auto-correlation.
[000224.87] [0/1] 07-13 13:45 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000239.84] [0/1] 07-13 13:45 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 2 in 14.97 s
[000239.84] [0/1] 07-13 13:45 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000239.84] [0/1] 07-13 13:45 TwoPointCorrelationFunction INFO Running cross-correlation.
[000239.84] [0/1] 07-13 13:45 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000269.96] [0/1] 07-13 13:45 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 2 in 30.12 s
Computing the auto-correlation and cross-correlation of quantile 3 ...
[000269.96] [0/1] 07-13 13:45 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000269.96] [0/1] 07-13 13:45 TwoPointCorrelationFunction INFO Running auto-correlation.
[000269.96] [0/1] 07-13 13:45 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000288.69] [0/1] 07-13 13:46 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 3 in 18.73 s
[000288.69] [0/1] 07-13 13:46 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000288.69] [0/1] 07-13 13:46 TwoPointCorrelationFunction INFO Running cross-correlation.
[000288.69] [0/1] 07-13 13:46 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000318.63] [0/1] 07-13 13:46 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 3 in 29.94 s
Computing the auto-correlation and cross-correlation of quantile 4 ...
[000318.64] [0/1] 07-13 13:46 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000318.64] [0/1] 07-13 13:46 TwoPointCorrelationFunction INFO Running auto-correlation.
[000318.64] [0/1] 07-13 13:46 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000334.95] [0/1] 07-13 13:46 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 4 in 16.31 s
[000334.95] [0/1] 07-13 13:46 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000334.95] [0/1] 07-13 13:46 TwoPointCorrelationFunction INFO Running cross-correlation.
[000334.95] [0/1] 07-13 13:46 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000362.38] [0/1] 07-13 13:47 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 4 in 27.43 s
Computing the auto-correlation and cross-correlation of quantile 5 ...
[000362.38] [0/1] 07-13 13:47 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000362.38] [0/1] 07-13 13:47 TwoPointCorrelationFunction INFO Running auto-correlation.
[000362.38] [0/1] 07-13 13:47 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000380.17] [0/1] 07-13 13:47 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 5 in 17.79 s
[000380.17] [0/1] 07-13 13:47 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000380.17] [0/1] 07-13 13:47 TwoPointCorrelationFunction INFO Running cross-correlation.
[000380.17] [0/1] 07-13 13:47 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000408.83] [0/1] 07-13 13:48 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 5 in 28.66 s
Computing the auto-correlation and cross-correlation of quantile 6 ...
[000408.84] [0/1] 07-13 13:48 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000408.84] [0/1] 07-13 13:48 TwoPointCorrelationFunction INFO Running auto-correlation.
[000408.84] [0/1] 07-13 13:48 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000426.93] [0/1] 07-13 13:48 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 6 in 18.09 s
[000426.93] [0/1] 07-13 13:48 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000426.93] [0/1] 07-13 13:48 TwoPointCorrelationFunction INFO Running cross-correlation.
[000426.93] [0/1] 07-13 13:48 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000455.50] [0/1] 07-13 13:48 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 6 in 28.58 s
Computing the auto-correlation and cross-correlation of quantile 7 ...
[000455.51] [0/1] 07-13 13:48 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000455.51] [0/1] 07-13 13:48 TwoPointCorrelationFunction INFO Running auto-correlation.
[000455.51] [0/1] 07-13 13:48 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000472.28] [0/1] 07-13 13:49 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 7 in 16.78 s
[000472.29] [0/1] 07-13 13:49 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000472.29] [0/1] 07-13 13:49 TwoPointCorrelationFunction INFO Running cross-correlation.
[000472.29] [0/1] 07-13 13:49 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000500.90] [0/1] 07-13 13:49 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 7 in 28.62 s
Computing the auto-correlation and cross-correlation of quantile 8 ...
[000500.91] [0/1] 07-13 13:49 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000500.91] [0/1] 07-13 13:49 TwoPointCorrelationFunction INFO Running auto-correlation.
[000500.91] [0/1] 07-13 13:49 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000518.14] [0/1] 07-13 13:49 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 8 in 17.23 s
[000518.14] [0/1] 07-13 13:49 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000518.14] [0/1] 07-13 13:49 TwoPointCorrelationFunction INFO Running cross-correlation.
[000518.14] [0/1] 07-13 13:49 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000545.67] [0/1] 07-13 13:50 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 8 in 27.53 s
Computing the auto-correlation and cross-correlation of quantile 9 ...
[000545.67] [0/1] 07-13 13:50 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000545.67] [0/1] 07-13 13:50 TwoPointCorrelationFunction INFO Running auto-correlation.
[000545.67] [0/1] 07-13 13:50 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000561.11] [0/1] 07-13 13:50 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 9 in 15.45 s
[000561.12] [0/1] 07-13 13:50 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000561.12] [0/1] 07-13 13:50 TwoPointCorrelationFunction INFO Running cross-correlation.
[000561.12] [0/1] 07-13 13:50 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000588.69] [0/1] 07-13 13:51 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 9 in 27.57 s
Ran los 'x' in 500.67 s
Computing along the y line of sight ...
Computing the DensitySplit ...
[000592.06] [0/1] 07-13 13:51 FFTWEngine INFO Loading wisdom from wisdom.shape-400-400-400.type-float64.nthreads-256.npy.
[000592.11] [0/1] 07-13 13:51 FFTWEngine INFO Saving wisdom to wisdom.shape-400-400-400.type-float64.nthreads-256.npy.
Computed the DensitySplit in 26.47 s
Downsampling the data to a number density of 1.00e-04 h^3/Mpc^3: 800000 galaxies remaining from 7911150 galaxies
Downsampled the galaxies to 1.00e-04 h^3/Mpc^3
Computing the 2PCF ...
[000618.84] [0/1] 07-13 13:51 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000618.84] [0/1] 07-13 13:51 TwoPointCorrelationFunction INFO Running auto-correlation.
[000618.84] [0/1] 07-13 13:51 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000636.07] [0/1] 07-13 13:51 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the 2PCF in 17.23 s
Computing the auto-correlation and cross-correlation of quantile 0 ...
[000636.07] [0/1] 07-13 13:51 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000636.07] [0/1] 07-13 13:51 TwoPointCorrelationFunction INFO Running auto-correlation.
[000636.07] [0/1] 07-13 13:51 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000650.51] [0/1] 07-13 13:52 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 0 in 14.44 s
[000650.51] [0/1] 07-13 13:52 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000650.51] [0/1] 07-13 13:52 TwoPointCorrelationFunction INFO Running cross-correlation.
[000650.51] [0/1] 07-13 13:52 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000680.30] [0/1] 07-13 13:52 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 0 in 29.79 s
Computing the auto-correlation and cross-correlation of quantile 1 ...
[000680.31] [0/1] 07-13 13:52 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000680.31] [0/1] 07-13 13:52 TwoPointCorrelationFunction INFO Running auto-correlation.
[000680.31] [0/1] 07-13 13:52 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000697.02] [0/1] 07-13 13:52 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 1 in 16.71 s
[000697.02] [0/1] 07-13 13:52 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000697.02] [0/1] 07-13 13:52 TwoPointCorrelationFunction INFO Running cross-correlation.
[000697.02] [0/1] 07-13 13:52 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000725.90] [0/1] 07-13 13:53 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 1 in 28.88 s
Computing the auto-correlation and cross-correlation of quantile 2 ...
[000725.90] [0/1] 07-13 13:53 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000725.90] [0/1] 07-13 13:53 TwoPointCorrelationFunction INFO Running auto-correlation.
[000725.90] [0/1] 07-13 13:53 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000742.42] [0/1] 07-13 13:53 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 2 in 16.52 s
[000742.42] [0/1] 07-13 13:53 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000742.42] [0/1] 07-13 13:53 TwoPointCorrelationFunction INFO Running cross-correlation.
[000742.42] [0/1] 07-13 13:53 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000772.34] [0/1] 07-13 13:54 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 2 in 29.92 s
Computing the auto-correlation and cross-correlation of quantile 3 ...
[000772.34] [0/1] 07-13 13:54 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000772.34] [0/1] 07-13 13:54 TwoPointCorrelationFunction INFO Running auto-correlation.
[000772.34] [0/1] 07-13 13:54 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000788.47] [0/1] 07-13 13:54 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 3 in 16.14 s
[000788.48] [0/1] 07-13 13:54 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000788.48] [0/1] 07-13 13:54 TwoPointCorrelationFunction INFO Running cross-correlation.
[000788.48] [0/1] 07-13 13:54 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000816.69] [0/1] 07-13 13:54 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 3 in 28.21 s
Computing the auto-correlation and cross-correlation of quantile 4 ...
[000816.69] [0/1] 07-13 13:54 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000816.69] [0/1] 07-13 13:54 TwoPointCorrelationFunction INFO Running auto-correlation.
[000816.69] [0/1] 07-13 13:54 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000835.74] [0/1] 07-13 13:55 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 4 in 19.05 s
[000835.74] [0/1] 07-13 13:55 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000835.74] [0/1] 07-13 13:55 TwoPointCorrelationFunction INFO Running cross-correlation.
[000835.74] [0/1] 07-13 13:55 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000863.57] [0/1] 07-13 13:55 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 4 in 27.83 s
Computing the auto-correlation and cross-correlation of quantile 5 ...
[000863.57] [0/1] 07-13 13:55 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000863.57] [0/1] 07-13 13:55 TwoPointCorrelationFunction INFO Running auto-correlation.
[000863.57] [0/1] 07-13 13:55 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000879.13] [0/1] 07-13 13:55 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 5 in 15.56 s
[000879.14] [0/1] 07-13 13:55 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000879.14] [0/1] 07-13 13:55 TwoPointCorrelationFunction INFO Running cross-correlation.
[000879.14] [0/1] 07-13 13:55 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000907.94] [0/1] 07-13 13:56 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 5 in 28.81 s
Computing the auto-correlation and cross-correlation of quantile 6 ...
[000907.94] [0/1] 07-13 13:56 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000907.94] [0/1] 07-13 13:56 TwoPointCorrelationFunction INFO Running auto-correlation.
[000907.94] [0/1] 07-13 13:56 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000923.42] [0/1] 07-13 13:56 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 6 in 15.48 s
[000923.42] [0/1] 07-13 13:56 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000923.42] [0/1] 07-13 13:56 TwoPointCorrelationFunction INFO Running cross-correlation.
[000923.43] [0/1] 07-13 13:56 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000952.93] [0/1] 07-13 13:57 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 6 in 29.51 s
Computing the auto-correlation and cross-correlation of quantile 7 ...
[000952.93] [0/1] 07-13 13:57 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000952.93] [0/1] 07-13 13:57 TwoPointCorrelationFunction INFO Running auto-correlation.
[000952.93] [0/1] 07-13 13:57 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000969.57] [0/1] 07-13 13:57 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 7 in 16.64 s
[000969.57] [0/1] 07-13 13:57 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000969.57] [0/1] 07-13 13:57 TwoPointCorrelationFunction INFO Running cross-correlation.
[000969.57] [0/1] 07-13 13:57 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[000998.86] [0/1] 07-13 13:57 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 7 in 29.29 s
Computing the auto-correlation and cross-correlation of quantile 8 ...
[000998.86] [0/1] 07-13 13:57 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[000998.86] [0/1] 07-13 13:57 TwoPointCorrelationFunction INFO Running auto-correlation.
[000998.86] [0/1] 07-13 13:57 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001014.46] [0/1] 07-13 13:58 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 8 in 15.60 s
[001014.46] [0/1] 07-13 13:58 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001014.46] [0/1] 07-13 13:58 TwoPointCorrelationFunction INFO Running cross-correlation.
[001014.46] [0/1] 07-13 13:58 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001042.25] [0/1] 07-13 13:58 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 8 in 27.79 s
Computing the auto-correlation and cross-correlation of quantile 9 ...
[001042.25] [0/1] 07-13 13:58 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001042.25] [0/1] 07-13 13:58 TwoPointCorrelationFunction INFO Running auto-correlation.
[001042.25] [0/1] 07-13 13:58 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001056.30] [0/1] 07-13 13:58 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 9 in 14.04 s
[001056.30] [0/1] 07-13 13:58 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001056.30] [0/1] 07-13 13:58 TwoPointCorrelationFunction INFO Running cross-correlation.
[001056.30] [0/1] 07-13 13:58 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001084.05] [0/1] 07-13 13:59 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 9 in 27.75 s
Ran los 'y' in 495.36 s
Computing along the z line of sight ...
Computing the DensitySplit ...
[001087.41] [0/1] 07-13 13:59 FFTWEngine INFO Loading wisdom from wisdom.shape-400-400-400.type-float64.nthreads-256.npy.
[001087.45] [0/1] 07-13 13:59 FFTWEngine INFO Saving wisdom to wisdom.shape-400-400-400.type-float64.nthreads-256.npy.
Computed the DensitySplit in 25.63 s
Downsampling the data to a number density of 1.00e-04 h^3/Mpc^3: 800000 galaxies remaining from 7911150 galaxies
Downsampled the galaxies to 1.00e-04 h^3/Mpc^3
Computing the 2PCF ...
[001113.05] [0/1] 07-13 13:59 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001113.05] [0/1] 07-13 13:59 TwoPointCorrelationFunction INFO Running auto-correlation.
[001113.05] [0/1] 07-13 13:59 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001128.82] [0/1] 07-13 14:00 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the 2PCF in 15.77 s
Computing the auto-correlation and cross-correlation of quantile 0 ...
[001128.82] [0/1] 07-13 14:00 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001128.82] [0/1] 07-13 14:00 TwoPointCorrelationFunction INFO Running auto-correlation.
[001128.82] [0/1] 07-13 14:00 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001142.55] [0/1] 07-13 14:00 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 0 in 13.73 s
[001142.55] [0/1] 07-13 14:00 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001142.55] [0/1] 07-13 14:00 TwoPointCorrelationFunction INFO Running cross-correlation.
[001142.56] [0/1] 07-13 14:00 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001168.90] [0/1] 07-13 14:00 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 0 in 26.34 s
Computing the auto-correlation and cross-correlation of quantile 1 ...
[001168.90] [0/1] 07-13 14:00 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001168.90] [0/1] 07-13 14:00 TwoPointCorrelationFunction INFO Running auto-correlation.
[001168.90] [0/1] 07-13 14:00 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001185.22] [0/1] 07-13 14:01 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 1 in 16.32 s
[001185.22] [0/1] 07-13 14:01 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001185.22] [0/1] 07-13 14:01 TwoPointCorrelationFunction INFO Running cross-correlation.
[001185.23] [0/1] 07-13 14:01 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001211.90] [0/1] 07-13 14:01 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 1 in 26.67 s
Computing the auto-correlation and cross-correlation of quantile 2 ...
[001211.90] [0/1] 07-13 14:01 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001211.90] [0/1] 07-13 14:01 TwoPointCorrelationFunction INFO Running auto-correlation.
[001211.90] [0/1] 07-13 14:01 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001231.07] [0/1] 07-13 14:01 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 2 in 19.18 s
[001231.08] [0/1] 07-13 14:01 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001231.08] [0/1] 07-13 14:01 TwoPointCorrelationFunction INFO Running cross-correlation.
[001231.08] [0/1] 07-13 14:01 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001258.71] [0/1] 07-13 14:02 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 2 in 27.64 s
Computing the auto-correlation and cross-correlation of quantile 3 ...
[001258.71] [0/1] 07-13 14:02 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001258.72] [0/1] 07-13 14:02 TwoPointCorrelationFunction INFO Running auto-correlation.
[001258.72] [0/1] 07-13 14:02 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001274.21] [0/1] 07-13 14:02 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 3 in 15.50 s
[001274.21] [0/1] 07-13 14:02 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001274.22] [0/1] 07-13 14:02 TwoPointCorrelationFunction INFO Running cross-correlation.
[001274.22] [0/1] 07-13 14:02 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001301.29] [0/1] 07-13 14:02 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 3 in 27.08 s
Computing the auto-correlation and cross-correlation of quantile 4 ...
[001301.30] [0/1] 07-13 14:02 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001301.30] [0/1] 07-13 14:02 TwoPointCorrelationFunction INFO Running auto-correlation.
[001301.30] [0/1] 07-13 14:02 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001316.41] [0/1] 07-13 14:03 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 4 in 15.11 s
[001316.41] [0/1] 07-13 14:03 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001316.41] [0/1] 07-13 14:03 TwoPointCorrelationFunction INFO Running cross-correlation.
[001316.41] [0/1] 07-13 14:03 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001342.85] [0/1] 07-13 14:03 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 4 in 26.44 s
Computing the auto-correlation and cross-correlation of quantile 5 ...
[001342.85] [0/1] 07-13 14:03 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001342.85] [0/1] 07-13 14:03 TwoPointCorrelationFunction INFO Running auto-correlation.
[001342.85] [0/1] 07-13 14:03 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001360.05] [0/1] 07-13 14:03 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 5 in 17.21 s
[001360.06] [0/1] 07-13 14:03 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001360.06] [0/1] 07-13 14:03 TwoPointCorrelationFunction INFO Running cross-correlation.
[001360.06] [0/1] 07-13 14:03 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001387.60] [0/1] 07-13 14:04 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 5 in 27.54 s
Computing the auto-correlation and cross-correlation of quantile 6 ...
[001387.60] [0/1] 07-13 14:04 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001387.60] [0/1] 07-13 14:04 TwoPointCorrelationFunction INFO Running auto-correlation.
[001387.60] [0/1] 07-13 14:04 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001402.59] [0/1] 07-13 14:04 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 6 in 14.99 s
[001402.59] [0/1] 07-13 14:04 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001402.59] [0/1] 07-13 14:04 TwoPointCorrelationFunction INFO Running cross-correlation.
[001402.59] [0/1] 07-13 14:04 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001429.81] [0/1] 07-13 14:05 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 6 in 27.22 s
Computing the auto-correlation and cross-correlation of quantile 7 ...
[001429.82] [0/1] 07-13 14:05 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001429.82] [0/1] 07-13 14:05 TwoPointCorrelationFunction INFO Running auto-correlation.
[001429.82] [0/1] 07-13 14:05 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001444.88] [0/1] 07-13 14:05 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 7 in 15.07 s
[001444.88] [0/1] 07-13 14:05 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001444.88] [0/1] 07-13 14:05 TwoPointCorrelationFunction INFO Running cross-correlation.
[001444.88] [0/1] 07-13 14:05 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001472.80] [0/1] 07-13 14:05 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 7 in 27.92 s
Computing the auto-correlation and cross-correlation of quantile 8 ...
[001472.81] [0/1] 07-13 14:05 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001472.81] [0/1] 07-13 14:05 TwoPointCorrelationFunction INFO Running auto-correlation.
[001472.81] [0/1] 07-13 14:05 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001488.37] [0/1] 07-13 14:06 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 8 in 15.56 s
[001488.37] [0/1] 07-13 14:06 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001488.37] [0/1] 07-13 14:06 TwoPointCorrelationFunction INFO Running cross-correlation.
[001488.37] [0/1] 07-13 14:06 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001517.50] [0/1] 07-13 14:06 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 8 in 29.13 s
Computing the auto-correlation and cross-correlation of quantile 9 ...
[001517.51] [0/1] 07-13 14:06 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001517.51] [0/1] 07-13 14:06 TwoPointCorrelationFunction INFO Running auto-correlation.
[001517.51] [0/1] 07-13 14:06 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001534.08] [0/1] 07-13 14:06 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the auto-correlation of quantile 9 in 16.58 s
[001534.08] [0/1] 07-13 14:06 TwoPointCorrelationFunction INFO Using estimator <class 'pycorr.twopoint_estimator.NaturalTwoPointEstimator'>.
[001534.08] [0/1] 07-13 14:06 TwoPointCorrelationFunction INFO Running cross-correlation.
[001534.08] [0/1] 07-13 14:06 TwoPointCorrelationFunction INFO Computing two-point counts D1D2.
[001562.70] [0/1] 07-13 14:07 TwoPointCorrelationFunction INFO Analytically computing two-point counts R1R2.
Computed the cross-correlation of quantile 9 in 28.62 s
Ran los 'z' in 478.65 s
Run_all in 1562.64 s
# Plot the CFs
fig, ax = plt.subplots(2, 3, sharex=True, figsize=(16, 7))
colors = [f'C{i}' for i in range(nquantiles)]
s = Object.CF['average']['s'] # Get the separation s (identical for all CFs)
for i in range(nquantiles):
color = colors[i]
alpha = 0.6
# Plot the multipoles of the auto correlation
poles1 = Object.CF['average']['Auto'][f'DS{i}']
ax[0,0].plot(s, poles1[0]*s**2, alpha=alpha, color=color, label = f'DS{i}')
ax[0,1].plot(s, poles1[1]*s**2, alpha=alpha, color=color)
ax[0,2].plot(s, poles1[2]*s**2, alpha=alpha, color=color)
# Plot the multipoles of the cross correlation
poles2 = Object.CF['average']['Cross'][f'DS{i}']
ax[1,0].plot(s, poles2[0]*s**2, alpha=alpha, color=color)
ax[1,1].plot(s, poles2[1]*s**2, alpha=alpha, color=color)
ax[1,2].plot(s, poles2[2]*s**2, alpha=alpha, color=color)
#Add the 2PCF on both plots
poles = Object.CF['average']['2PCF']
for i in [0, 1]:
ax[i,0].plot(s, poles[0]*s**2, alpha=alpha, color='k', ls='--', label='2PCF')
ax[i,1].plot(s, poles[1]*s**2, alpha=alpha, color='k', ls='--')
ax[i,2].plot(s, poles[2]*s**2, alpha=alpha, color='k', ls='--')
ax[0,0].legend()
ax[1,0].set_xlabel(r'$s$')
ax[1,0].set_ylabel(r'$s^2\xi_l(s)$')
ax[0,0].set_ylabel(r'$s^2\xi_l(s)$')
ax[0,0].set_title('Monopole', fontsize=11)
ax[0,1].set_title('Quadrupole', fontsize=11)
ax[0,2].set_title('Hexadecapole', fontsize=11)
fig.suptitle('Auto (top) and Cross (bottom) Correlation for c000', fontsize=15, y=1);
# Access the times
# The times are stored in a dictionary
times_dict = Object.times_dict
# Let's compute some interesting times to look at
total_time = times_dict['run_all']
mean_los_time = np.mean([times_dict[los]['run_los'] for los in ['x', 'y', 'z']], axis=0)
mean_2PCF_time = np.mean([times_dict[los]['compute_2pcf'] for los in ['x', 'y', 'z']], axis=0)
mean_auto_time = np.mean([times_dict[los]['compute_auto_corr'][f'DS{i}'] for los in ['x', 'y', 'z'] for i in range(nquantiles)], axis=0)
mean_cross_time = np.mean([times_dict[los]['compute_cross_corr'][f'DS{i}'] for los in ['x', 'y', 'z'] for i in range(nquantiles)], axis=0)
total_auto_time = np.mean([np.sum([times_dict[los]['compute_auto_corr'][f'DS{i}'] for i in range(nquantiles)], axis=0) for los in ['x', 'y', 'z']], axis=0)
total_cross_time = np.mean([np.sum([times_dict[los]['compute_cross_corr'][f'DS{i}'] for i in range(nquantiles)], axis=0) for los in ['x', 'y', 'z']], axis=0)
#Display the times
print(f'Total time: {total_time:.2f} s')
print(f'Mean time for computing a LOS: {mean_los_time:.2f} s')
print(f'Mean time for computing the 2PCF: {mean_2PCF_time:.2f} s')
print(f'Mean time for computing an auto correlation: {mean_auto_time:.2f} s')
print(f'Mean time for computing a cross correlation: {mean_cross_time:.2f} s')
print(f'Mean time for computing all auto correlations: {total_auto_time:.2f} s')
print(f'Mean time for computing all cross correlations: {total_cross_time:.2f} s')
Total time: 1562.64 s
Mean time for computing a LOS: 491.56 s
Mean time for computing the 2PCF: 16.80 s
Mean time for computing an auto correlation: 16.15 s
Mean time for computing a cross correlation: 28.26 s
Mean time for computing all auto correlations: 161.54 s
Mean time for computing all cross correlations: 282.64 s
Load a catalog in the class#
It is also possible to run the analysis on a catalog that is not generated by the class. The catalog must be a pandas array.
# Import the data
import pandas as pd
from CorrHOD.catalogs import read_fits
path = '/global/cfs/cdirs/desi/cosmosim/FirstGenMocks/AbacusSummit/CubicBox/BGS_v2/z0.200/AbacusSummit_base_c000_ph000/BGS_box_ph000.fits'
data_cubic = read_fits(path, check_cubic_format=True, print_column_names=True)
# Apply some cuts to the data
mask = (data_cubic['R_MAG_ABS'] < -21.5).to_numpy() # Create a mask to select the galaxies that are brighter than the magnitude cut
data_cubic = pd.DataFrame(data_cubic.values[mask], columns=data_cubic.columns) # Apply the mask to the data
# Create a CorrHOD object to make computation easier
path2config = Path('config.yaml') # Useless here, but we need it to create the object
Object = CorrHOD_cubic(path2config)
Object.cubic_dict = data_cubic
# And then, run the analysis as usual
Object.get_tracer_positions(); # Get the positions of the tracers and get the coordinates in the right shift
...