def xi_C_at_r(radii, r_A, r_B, beta_ex, xi_2h):
"""Halo-matter correlation function with halo exclusion incorporated.
Args:
radii (float or array-like): Radii of the profile in Mpc/h
r_A (float): radius of first correction term in Mpc/h
r_B (float): radius of second correction term in Mpc/h
beta_ex (float): width parameter for exclusion terms
xi_2h (float or array-like): 2-halo term of the exclusion profile
Returns:
float or array-like: correction term for the exclusion profile
"""
radii = np.asarray(radii)
xi_2h = np.asarray(xi_2h)
scalar_input = False
if radii.ndim == 0:
radii = radii[None] #makes r 1D
scalar_input = True
if radii.ndim > 1:
raise Exception("radii cannot be a >1D array.")
if len(radii) != len(xi_2h):
raise Exception("len(r) must equal len(xi_2h)")
lib = cluster_toolkit._lib
xi_C = np.zeros_like(radii)
lib.xi_C_at_r_arr(dc(radii), len(radii), r_A, r_B, beta_ex, dc(xi_2h),
dc(xi_C))
if scalar_input:
return np.squeeze(xi_C)
return xi_C
def theta_at_r(radii, rt, beta):
"""Truncation function.
Args:
radii (float or array-like): Radii of the profile in Mpc/h
rt (float): truncation radius in Mpc/h
beta (float): width of the truncation distribution (erfc) in Mpc/h
Returns:
float or array-like: Truncation function
"""
radii = np.asarray(radii)
scalar_input = False
if radii.ndim == 0:
radii = radii[None] #makes r 1D
scalar_input = True
if radii.ndim > 1:
raise Exception("radii cannot be a >1D array.")
theta = np.zeros_like(radii)
cluster_toolkit._lib.theta_erfc_at_r_arr(dc(radii), len(radii), rt, beta,
dc(theta))
if scalar_input:
return np.squeeze(theta)
return theta
def xi_2h_exclusion_at_r(radii, r_eff, beta_eff, bias, xi_mm):
"""2-halo term in the halo-matter correlation function
using halo exclusion theory.
Args:
radii (float or array-like): Radii of the profile in Mpc/h
r_eff (float): effective radius for 2-halo subtraction in Mpc/h
beta_eff (float): width for effective radius truncation
bias (float): halo bias at large scales
xi_mm (float or array-like): matter correlation function.
Must have same shape as the radii.
Returns:
float or array-like: 2-halo of the exclusion profile at each radii
"""
radii = np.asarray(radii)
xi_mm = np.asarray(xi_mm)
scalar_input = False
if radii.ndim == 0:
radii = radii[None] #makes r 1D
scalar_input = True
if radii.ndim > 1:
raise Exception("radii cannot be a >1D array.")
if len(radii) != len(xi_mm):
raise Exception("len(r) must equal len(xi_mm)")
lib = cluster_toolkit._lib
xi_2h = np.zeros_like(radii)
lib.xi_2h_at_r_arr(dc(radii), len(radii), r_eff, beta_eff, bias, dc(xi_mm),
dc(xi_2h))
if scalar_input:
return np.squeeze(xi_2h)
return xi_2h
def xi_hm_exclusion_at_r(radii,
Mass,
conc,
alpha,
rt,
beta,
r_eff,
beta_eff,
r_A,
r_B,
beta_ex,
bias,
xi_mm,
Omega_m,
delta=200):
"""Halo-matter correlation function with halo exclusion incorporated.
Args:
radii (float or array-like): Radii of the profile in Mpc/h
Mass (float): Mass in Msun/h
conc (float): concentration of the 1-halo profile
alpha (float): Einasto parameter
rt (float): truncation radius in Mpc/h
beta (float): width of the truncation distribution (erfc) in Mpc/h
r_eff (float): effective radius for 2-halo subtraction in Mpc/h
beta_eff (float): width for effective radius truncation
r_A (float): radius of first correction term in Mpc/h
r_B (float): radius of second correction term in Mpc/h
beta_ex (float): width parameter for exclusion terms
bias (float): linear halo bias
xi_mm (float or array-like): matter correlation function.
same shape as radii
Omega_m (float): matter density fraction
delta (int): halo overdensity. Default is 200
Returns:
float or array-like: exclusion profile at each radii
"""
radii = np.asarray(radii)
xi_mm = np.asarray(xi_mm)
scalar_input = False
if radii.ndim == 0:
radii = radii[None] #makes r 1D
scalar_input = True
if radii.ndim > 1:
raise Exception("radii cannot be a >1D array.")
if len(radii) != len(xi_mm):
raise Exception("len(r) must equal len(xi_mm)")
lib = cluster_toolkit._lib
xi_hm = np.zeros_like(radii)
lib.xi_hm_exclusion_at_r_arr(dc(radii), len(radii), Mass, conc, alpha, rt,
beta, r_eff, beta_eff, r_A, r_B, beta_ex,
bias, dc(xi_mm), delta, Omega_m, dc(xi_hm))
if scalar_input:
return np.squeeze(xi_hm)
return xi_hm
def xi_1h_exclusion_at_r(radii,
Mass,
conc,
alpha,
rt,
beta,
Omega_m,
delta=200):
"""Halo-matter correlation function with halo exclusion incorporated,
but just the 1-halo term.
Args:
radii (float or array-like): Radii of the profile in Mpc/h
Mass (float): Mass in Msun/h
conc (float): concentration of the 1-halo profile
alpha (float): Einasto parameter
rt (float): truncation radius in Mpc/h
beta (float): width of the truncation distribution (erfc) in Mpc/h
Omega_m (float): Matter density fraction
delta (float): halo overdensity; default is 200
Returns:
float or array-like: 1-halo of the exclusion profile at each radii
"""
radii = np.asarray(radii)
scalar_input = False
if radii.ndim == 0:
radii = radii[None] #makes r 1D
scalar_input = True
if radii.ndim > 1:
raise Exception("radii cannot be a >1D array.")
lib = cluster_toolkit._lib
xi_1h = np.zeros_like(radii)
lib.xi_1h_at_r_arr(dc(radii), len(radii), Mass, conc, alpha, rt, beta,
delta, Omega_m, dc(xi_1h))
if scalar_input:
return np.squeeze(xi_1h)
return xi_1h