def test_box_power_spectrum():
"""Check that the theoretical and box power spectra can be calculated."""
# Realise Gaussian box
np.random.seed(14)
box = CosmoBox(cosmo=default_cosmo,
box_scale=(1e3, 1e3, 1e3),
nsamp=64,
realise_now=False)
box.realise_density()
# Calculate binned power spectrum and theoretical power spectrum
re_k, re_pk, re_stddev = box.binned_power_spectrum()
th_k, th_pk = box.theoretical_power_spectrum()
# Check that sigma(R) and sigma_8 can be calculated
sigR = box.sigmaR(R=8.) # R in units of Mpc/h
sig8 = box.sigma8()
assert np.isclose(sigR, sig8)
# Run built-in test to print a report on sampling accuracy
box.test_sampling_error()
# Check that sigma_8 calculated from box is close to input cosmo sigma_8
# (this depends on box size/resolution)
assert np.abs(sig8 - box.cosmo['sigma8']) < 0.09 # 0.09 is empirical
def test_gaussian_box():
"""Generate Gaussian density field in box."""
# Realise Gaussian box
np.random.seed(11)
box = CosmoBox(cosmo=default_cosmo,
box_scale=(1e2, 1e2, 1e2),
nsamp=16,
realise_now=False)
box.realise_density()
# Check that density field is valid
assert box.delta_x.shape == (16, 16, 16)
assert box.delta_x.dtype == np.float64
assert np.all(~np.isnan(box.delta_x))
# Realise density field with same random seed and realise_now=True, and
# manually setting the redshift and a single box_scale
np.random.seed(11)
box2 = CosmoBox(cosmo=default_cosmo,
box_scale=1e2,
nsamp=16,
redshift=0.,
realise_now=True)
assert np.allclose(box.delta_x, box2.delta_x)
# Check that pixel resolution etc. is correct
assert box.Lx == box.Ly == box.Lz == 1e2
assert box.x.size == box.y.size == box.z.size == 16
assert np.isclose(np.max(box.x) - np.min(box.x), 1e2)
# Check that cuboidal boxes work
box3 = CosmoBox(cosmo=default_cosmo,
box_scale=(1e2, 2e2, 1e3),
nsamp=16,
redshift=1.,
realise_now=True)
assert box3.delta_x.shape == (16, 16, 16)
assert box3.delta_x.dtype == np.float64
assert np.all(~np.isnan(box3.delta_x))
def test_box_redshift_space_density():
"""Check that a redshift-space density field can be generated."""
# Realise Gaussian box and velocity field
np.random.seed(11)
box = CosmoBox(cosmo=default_cosmo,
box_scale=(1e2, 1e2, 1e2),
nsamp=16,
realise_now=False)
box.realise_density()
box.realise_velocity()
# Get redshift-space density field
vel_z = np.fft.ifftn(box.velocity_k[2]).real
delta_s = box.redshift_space_density(delta_x=box.delta_x,
velocity_z=vel_z,
sigma_nl=200.,
method='linear')
# Check that redshift-space density field is valid
assert delta_s.shape == (16, 16, 16)
# assert delta_s.dtype == np.float64
assert np.all(~np.isnan(delta_s))
#!/usr/bin/env python
import numpy as np
import pylab as plt
from fastbox.box import CosmoBox, default_cosmo
from numpy import fft
# Gaussian box
np.random.seed(10)
box = CosmoBox(cosmo=default_cosmo,
box_scale=(1e2, 1e2, 1e2),
nsamp=128,
realise_now=False)
box.realise_density()
box.realise_velocity()
# Plot real-space density field
plt.matshow(box.delta_x[0], vmin=-1., vmax=20., cmap='cividis')
plt.title("Real-space")
plt.colorbar()
# Get redshift-space density field
vel_z = fft.ifftn(box.velocity_k[2]).real
delta_s = box.redshift_space_density(delta_x=box.delta_x,
velocity_z=vel_z,
sigma_nl=200.,
method='linear')
plt.matshow(delta_s[0], vmin=-1., vmax=20., cmap='cividis')
plt.title("Redshift-space")