Looks up redshift corresponds to comoving distance d. A spline interpolation is setup up to redshift $z_\mathrm{max}$.
distance = Distance(z_max)
| Operation | Result |
|---|---|
| distance.z_max | z_max given in the initialisation |
| distance.d_max | maximum d usable for distance.redshift(d) |
| distance.redshift(d) | redshift coresponds to comoving distance $d$ |
In [1]:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import mockgallib as mock
mock.cosmology.set(0.31) # set omega_m
z_max = 1.5
mock.distance.init(z_max)
In [3]:
d_max = mock.cosmology.compute_comoving_distance(1/(1 + z_max))
d = np.arange(0, d_max, 10)
z = [mock.distance.redshift(dd) for dd in d]
plt.xlabel('$d$')
plt.ylabel('$z$')
plt.plot(d, z, 'r-')
z = np.arange(0, z_max, 0.1)
a = 1/(1 + z)
d = [ mock.cosmology.compute_comoving_distance(aa) for aa in a ]
plt.plot(d, z, 'x')
plt.show();
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In [1]:
%%html
<style>table {float:left}</style>