def read_density(self, dens_file, contrast=False):
if self.dens_file_reader is not None: dens = self.dens_file_reader(dens_file)
else:
t2c.set_sim_constants(int(self.Lbox*0.7))
dens = t2c.DensityFile(dens_file).raw_density#cgs_density*u.g/u.cm**3
self.nGrid = dens.shape[0]
if contrast: dens = dens/dens.mean() - 1.
return dens
# Get data from dawn-1
xf_dir = '/disk/dawn-1/garrelt/Reionization/C2Ray_WMAP7/500Mpc/500Mpc_z50_0_300/results/' #'/disk/dawn-1/garrelt/Reionization/C2Ray_WMAP7/500Mpc/500Mpc_f2_0_300/retrieved_from_khagolaz/results/'
dn_dir = '/disk/dawn-1/garrelt/Reionization/C2Ray_WMAP7/500Mpc/coarser_densities/nc300/'
xf_files = glob(xf_dir+'xfrac3d_*')
dn_files = glob(dn_dir+'*n_all.dat')
xf_zs = np.array([ff.split('xfrac3d_')[-1].split('.bin')[0] for ff in xf_files]).astype(float)
dn_zs = np.array([ff.split('/')[-1].split('n_all')[0] for ff in dn_files]).astype(float)
zs = np.intersect1d(xf_zs,dn_zs)
filename = './slices_dataset_500Mpc_z50_0_300.pkl' #'./slices_dataset_500Mpc_f2_0_300.pkl'
dataset = pickle.load(open(filename, 'rb')) if glob(filename) else {}
if len(dataset.keys())==0:
for zz in tqdm(zs):
xx = t2c.XfracFile(xf_dir+'xfrac3d_{:.3f}.bin'.format(zz)).xi
dd = t2c.DensityFile(dn_dir+'{:.3f}n_all.dat'.format(zz)).cgs_density
dt = t2c.calc_dt(xx, dd, zz)
dataset['{:.3f}'.format(zz)] = {'xf': xx[:,:,100], 'dt': dt[:,:,100]}
pickle.dump(dataset,open(filename, 'wb'))
dataset_zs = np.array([ii for ii in dataset.keys()]).astype(float)
dataset_xs = np.array([dataset['{:.3f}'.format(zz)]['xf'].mean() for zz in dataset_zs])
dataset_zs = dataset_zs[np.argsort(-dataset_zs)][12:-12]
dataset_range = np.array([[dataset['{:.3f}'.format(zz)]['dt'].min(),dataset['{:.3f}'.format(zz)]['dt'].max()] for zz in dataset_zs])
class AnimatedGif:
def __init__(self, size=(640, 480), figsize=None, fps=1, cmap='jet', text_color='red'):
self.fig = plt.figure(figsize=figsize)
if figsize is None: self.fig.set_size_inches(size[0] / 100, size[1] / 100)
ax = self.fig.add_axes([0, 0, 1, 1], frameon=False, aspect=1)
ax.set_xticks([])
# interpolate redshift list
redshift_xi = t2c.get_xfrac_redshifts(path_xi)
redshift_dens = t2c.get_dens_redshifts(path_dens)
redshift = SameValuesInArray(redshift_xi, redshift_dens)
print('tot redshift:', redshift.size)
#### Code below this is important
t2c.set_sim_constants(sim)
min_arr = []
max_arr = []
for i in tqdm(range(len(redshift))):
z = redshift[i]
xf = t2c.XfracFile('%sxfrac3d_%.3f.bin' %(path_xi, z)).xi
dn = t2c.DensityFile('%s%.3fn_all.dat' %(path_dens, z)).cgs_density
dt = t2c.calc_dt(xf, dn, z)
ps_dt = t2c.power_spectrum_nd(dt)
if(smt): ps_dt = ndimage.gaussian_filter(ps_dt, 5, mode='wrap')
for ax in ['x', 'y', 'z']:
if(ax=='x'):
rs_dt = np.log10(ps_dt[:, int(mesh/2):int(mesh/2)+out_res, int(mesh/2):int(mesh/2)+out_res])
elif(ax=='y'):
rs_dt = np.log10(ps_dt[int(mesh/2):int(mesh/2)+out_res, :, int(mesh/2):int(mesh/2)+out_res])
else:
rs_dt = np.log10(ps_dt[int(mesh/2):int(mesh/2)+out_res, int(mesh/2):int(mesh/2)+out_res, :])
for j in range(len(rs_dt)):
if(ax=='x'):
pp = rs_dt[j, :, :]
Setup script
'''
import numpy as np
import matplotlib.pyplot as plt
from sim21cm import extreme_model
import tools21cm as t2c
t2c.set_sim_constants(500)
# Instantaneous simulation
### In this mode, we take one density field and ionize it based on a
### given average ionization fraction
dens_file = '/disk/dawn-1/garrelt/Reionization/C2Ray_WMAP7/500Mpc/coarser_densities/nc300/8.064n_all.dat'
dens = t2c.DensityFile(dens_file).raw_density
xi = [0.3, 0.7]
simoi = extreme_model.OutsideIn()
xhii0 = simoi.run_instant(dens,
xi[0],
volume_averaged=True,
mass_averaged=True,
write=False)
xhii1 = simoi.run_instant(dens,
xi[1],
volume_averaged=True,
mass_averaged=True,
write=False)
plt.figure()
kwargs['histtype'] = 'step'
if not 'color' in kwargs.keys():
kwargs['color'] = 'k'
pl.hist(plot_data.flatten(), log=logscale, **kwargs)
#Labels
if datatype == 'xfrac':
pl.xlabel('$x_i$')
elif datatype == 'density':
pl.xlabel('$\\rho \; \mathrm{[g \; cm^{-3}]}$')
if __name__ == '__main__':
import tools21cm as t2c
import pylab as pl
t2c.set_verbose(True)
pl.figure()
dfilename = '/disk/sn-12/garrelt/Science/Simulations/Reionization/C2Ray_WMAP5/114Mpc_WMAP5/coarser_densities/nc256_halos_removed/6.905n_all.dat'
xfilename = '/disk/sn-12/garrelt/Science/Simulations/Reionization/C2Ray_WMAP5/114Mpc_WMAP5/114Mpc_f2_10S_256/results_ranger/xfrac3d_8.958.bin'
dfile = t2c.DensityFile(dfilename)
# plot_slice(dfile, los_axis=1, logscale=True, cmap=pl.cm.hot)
# ax2 = pl.subplot(1,2,2)
# plot_slice(xfilename)
plot_slice(t2c.XfracFile(xfilename))
pl.show()