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
#plt.title("FG-subtracted (4 modes, high-pass)")
#plt.colorbar()
#plt.matshow(cleaned_cube8[0,:,:], vmin=-1., vmax=2.)
#plt.title("FG-subtracted (8 modes)")
#plt.colorbar()
# Power spectra
sig_k, sig_pk, sig_stddev = box.binned_power_spectrum(delta_x=signal_cube)
proc4_k, proc4_pk, proc4_stddev = box.binned_power_spectrum(
delta_x=cleaned_cube4)
proc8_k, proc8_pk, proc8_stddev = box.binned_power_spectrum(
delta_x=cleaned_cube8)
proc4hp_k, proc4hp_pk, proc4hp_stddev = box.binned_power_spectrum(
delta_x=cleaned_cube4_hp)
th_k, th_pk = box.theoretical_power_spectrum()
amp_fac = (tracer.signal_amplitude() * tracer.bias_HI())**2.
plt.figure()
plt.subplot(111)
plt.plot(th_k, th_pk * amp_fac, 'k-')
plt.errorbar(sig_k, sig_pk, yerr=sig_stddev, color='r', marker='.')
plt.errorbar(proc4_k, proc4_pk, yerr=proc4_stddev, color='b', marker='x')
plt.errorbar(proc4hp_k, proc4hp_pk, yerr=proc4hp_stddev, color='y', marker='s')
plt.errorbar(proc8_k, proc8_pk, yerr=proc8_stddev, color='g', marker='+')
plt.xscale('log')
plt.yscale('log')
#plt.show()