def test_outputs_xi_nfw_at_R():
#List vs. numpy.array
npt.assert_array_equal(xi.xi_nfw_at_R(Ra, Mass, conc, Omega_m), xi.xi_nfw_at_R(Ra.tolist(), Mass, conc, Omega_m))
#Single value vs numpy.array
arrout = xi.xi_nfw_at_R(Ra, Mass, conc, Omega_m)
for i in range(len(Ra)):
npt.assert_equal(xi.xi_nfw_at_R(Ra[i], Mass, conc, Omega_m), arrout[i])
def test_rho_vs_xi_nfw():
#Note: testing fractional precision to avoid numerical issues
arr1 = density.rho_nfw_at_R(R_arr, Mass, conc, Omega_m)
arr2 = xi.xi_nfw_at_R(R_arr, Mass, conc, Omega_m)
arr2 = rhom * (1 + arr2)
arr2 = arr2 / arr1
ones = np.ones_like(arr1)
npt.assert_array_equal(ones, arr2)
def test_combination():
xinfw = xi.xi_nfw_at_R(Ra, Mass, conc, Omega_m)
ximm = xi.xi_mm_at_R(Ra, knl, pnl)
from cluster_toolkit import bias
b = bias.bias_at_M(Mass, klin, plin, Omega_m)
xi2h = xi.xi_2halo(b, ximm)
xihm = xi.xi_hm(xinfw, xi2h)
xihm2 = xi.xi_hm(xinfw, xi2h, combination='max')
npt.assert_array_equal(xihm, xihm2)
xihm2 = xi.xi_hm(xinfw, xi2h, combination='sum')
npt.assert_raises(AssertionError, npt.assert_array_equal, xihm, xihm2)
with pytest.raises(Exception):
xi.xi_hm(xinfw, xi2h, combination='blah')
def test_nfw_mass_dependence():
masses = np.array([1e13, 1e14, 1e15])
for i in range(len(masses)-1):
xi1 = xi.xi_nfw_at_R(Ra, masses[i], conc, Omega_m)
xi2 = xi.xi_nfw_at_R(Ra, masses[i+1], conc, Omega_m)
npt.assert_array_less(xi1, xi2)
def test_exceptions_xi_nfw_at_R():
with pytest.raises(TypeError):
xi.xi_nfw_at_R() #No args
xi.xi_nfw_at_R(R, Mass, conc) #Too few args
xi.xi_nfw_at_R(R, Mass, conc, Omega_m, Omega_m) #Too many args
xi.xi_nfw_at_R("a string", Mass, conc, Omega_m, Omega_m) #Wrong type