def radial_mock(self, method="EEP", N=None, bins=100,
new_lumfunc=False, min_acceptable=1, eps=0.01,
max_iter=10, selbins=100):
"""
Creates a random catalogue of particles based on a defined selection function. Only radial co-ords.
Ouput: radii :: length N vector (default length of survey) of radii
"""
z_min = self.survey_data['redshift'].min()
z_max = self.survey_data['redshift'].max()
if N is None:
N = self.N
if method is None:
radii = sf.create_radial_selection_simple(z_min, z_max, N)
else:
M, phi = self.lum_func(Np=bins, method=method,
new=new_lumfunc, min_acceptable=min_acceptable,
eps=eps, max_iter=max_iter)
s_of_z = sf.selection_of_z(selbins, phi, M, self.survey_data["mag_r"],
self.survey_data["absmag"],
self.survey_data["redshift"])
radii = sf.create_mock(s_of_z, z_min, z_max, N)
#Plot it
plt.clf()
plt.hist(radii, bins=100, normed=True, label="Mock")
plt.hist(self.survey_data['redshift'], bins=100, normed=True, label="Data")
plt.legend()
plt.savefig(self._dirs['SelectionFunction'] +
'N(z)_' + method + '_L' + str(bins)
+ "_S" + str(selbins) + '.' + self.plottype)
return radii
