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PowerSpectra_3DLyA.py
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PowerSpectra_3DLyA.py
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import numpy as np
import astropy.units as u
import math as mh
import sys
import power_spectra as spe
import fourier_estimators as fou
import boxes
import bigfile
import subprocess
import os.path
def get3dps(snapshot_dir = '.', snapshot_num=14, grid_width=20, spectral_res=50*u.km/u.s, reload_snapshot=True, label=None, boxsize=20.,
spectra_savedir=None):
if reload_snapshot == False:
try:
print('trying to load 1D ps from ', spectra_savedir)
reload_snapshot=False
simulation_box_instance = boxes.SimulationBox(snapshot_num, snapshot_dir, grid_width, spectral_res,
reload_snapshot=reload_snapshot, spectra_savedir=spectra_savedir)
except OSError:
print('tried but failed to load 1d ps doesnt exist, now calculating')
reload_snapshot = True
simulation_box_instance = boxes.SimulationBox(snapshot_num, snapshot_dir, grid_width, spectral_res,
reload_snapshot=reload_snapshot, spectra_savedir=spectra_savedir)
#except KeyError:
# print('tried but failed to load 1d ps due to key error, now calculating')
# reload_snapshot = True
# spectra = boxes.SimulationBox(snapshot_num, snapshot_dir, grid_width, spectral_res,
# reload_snapshot=reload_snapshot, spectra_savedir=spectra_savedir)
else:
print('calculating 1d power')
simulation_box_instance = boxes.SimulationBox(snapshot_num, snapshot_dir, grid_width, spectral_res,
reload_snapshot=reload_snapshot, spectra_savedir=spectra_savedir)
simulation_box_instance.convert_fourier_units_to_distance = True
delta_flux_box = simulation_box_instance.skewers_realisation()
k_box = simulation_box_instance.k_box()
mu_box = simulation_box_instance.mu_box()
#Binning to match GenPK
n_k_bins = 6
n_mu_bins = 4
k_max = 20. / u.Mpc
k_min = np.min(k_box[k_box > 0. / u.Mpc])
k_bin_max = mh.exp(mh.log(k_max.value) + ((mh.log(k_max.value) - mh.log(k_min.value)) / (n_k_bins - 1))) / u.Mpc
k_bin_edges = np.exp(np.linspace(mh.log(k_min.value), mh.log(k_bin_max.value), n_k_bins + 1)) / u.Mpc
#k_bin_edges[-2] = k_max #HACK TO FIX BINNING OF NYQUIST FREQUENCY
mu_bin_edges = np.linspace(0., 1., n_mu_bins + 1)
print(len(k_box), len(mu_box), len(k_bin_edges), len(mu_bin_edges))
fourier_estimator_instance = fou.FourierEstimator3D(delta_flux_box)
#power_binned_k_mu, k_binned_2D = fourier_instance.get_flux_power_3D_two_coords_hist_binned(k_box, np.absolute(mu_box), k_bin_edges, mu_bin_edges, bin_coord2=False, count=False, std_err=False, norm=True)
#import pdb; pdb.set_trace()
power_binned, k_binned, mu_binned = fourier_estimator_instance.get_power_3D_two_coords_binned(k_box,np.absolute(mu_box),k_bin_edges,mu_bin_edges,bin_coord2=True)
return power_binned, k_binned, mu_binned, simulation_box_instance._redshift
if __name__ == "__main__":
import matplotlib as mpl
mpl.use('pdf')
import matplotlib.pyplot as plt
snap_nums = [1, 2]
boxsize = 40. #Mpc/h
grid_width = 400
spectral_res = 10*u.km/u.s
xlim1d = (0.3, 10)
xlim3d = (0.3, 100)
ylim_avg = (0.1, 10)
#spectra_dir_pre = '/home/landerson/lyalpha/'
#snapshot_dir_pre = '/home/fvillaescusa/data/Lya_ncv/'
snapshot_dir_pre = '/home/fvillaescusa/data/Lya_ncv/40Mpc_512/'
spectra_dir_pre = '/home/landerson/lyalpha/40Mpc_512/'
simulation_numbers = np.arange(0, 49.001, 1).astype(int)
savenpz_pre = ['T', 'NCV_0', 'NCV_1']
simulation_pre = ['', 'NCV_0_', 'NCV_1_']
#loop over redshift and the grid with associated with it
#I currently set the grid width to be the same at each redshift, though the resolution is different at different redshifts
#something to improve in the future
for snapshot_number in snap_nums:
fig, ax = plt.subplots(4, figsize=(6, 8)) #len(snap_nums))
for sim_pre, snpz in zip(simulation_pre, savenpz_pre):
specSaveFile = 'spec3d{0}_{1}_{2}.npz'.format(grid_width, snpz, snapshot_number)
try:
data = np.load(specSaveFile)
spectra = data['p3d']
mu = data['mu']
k = data['k3d']
z = data['z']
dataSaved = True
print('data loaded from npz for ', specSaveFile)
except IOError:
dataSaved = False
print('loading all data for ', specSaveFile)
spectra = []
mu = []
k = []
legend = []
z = []
for simulation_number in simulation_numbers:
if (sim_pre == 'NCV_1_') and (simulation_number > 24): continue
if (sim_pre == 'NCV_0_') and (simulation_number > 24): continue
snapshot_directory = snapshot_dir_pre + sim_pre + str(simulation_number)
save_directory = spectra_dir_pre + sim_pre + str(simulation_number)
spectra_directory = save_directory + '/SPECTRA_{0:03d}'.format(snapshot_number)
if not dataSaved:
ps, k_array, mu_array, redshift = get3dps(snapshot_num=snapshot_number, snapshot_dir = snapshot_directory,
reload_snapshot=False, grid_width=grid_width,
spectral_res=spectral_res, spectra_savedir=spectra_directory)
spectra.append(ps)
k.append(k_array)
z.append(redshift)
mu.append(mu_array)
if dataSaved:
k_array = k[simulation_number]
ps = spectra[simulation_number]
redshift = z[simulation_number]
mu_array = mu[simulation_number]
if not dataSaved: np.savez(specSaveFile, p3d=spectra, k3d=k, z=z, mu=mu)