def massrich_norm(self, norm):
self._massrich_norm = utils.check_units_and_type(norm,
units.Msun,
is_scalar=True)
# behavior is to convert current n200 -> new m200
if hasattr(self, 'n200'):
self._richness_to_mass()
def m200(self, mass):
# Creates/updates values of cluster M200s & dependant variables.
self._m200 = utils.check_units_and_type(mass,
units.Msun,
num=self.number)
self._df['m200'] = pd.Series(self._m200, index=self._df.index)
self._mass_to_richness()
def n200(self, richness):
# Creates/updates values of cluster N200s & dependant variables.
self._n200 = utils.check_units_and_type(richness,
None,
num=self.number)
self._df['n200'] = pd.Series(self._n200, index=self._df.index)
self._richness_to_mass()
def z(self, redshifts):
# Changes the values of the cluster z's and z-dependant variables.
self._z = utils.check_units_and_type(redshifts, None, num=self.number)
self._Dang_l = self._cosmo.angular_diameter_distance(self._z)
self._df['z'] = pd.Series(self._z, index=self._df.index)
self._rho_crit = self._cosmo.critical_density(self._z)
if self._n200 is not None:
self._update_dependant_variables()
def z(self, redshifts):
# Changes the values of the cluster z's and z-dependant variables.
self._z = utils.check_units_and_type(redshifts, None, num=self.number)
self._Dang_l = self._cosmo.angular_diameter_distance(self._z)
self._df['z'] = pd.Series(self._z, index=self._df.index)
self._rho_crit = self._cosmo.critical_density(self._z)
if self._n200 is not None:
self._update_dependant_variables()
def __init__(self, rs, delta_c, rho_crit, offsets=None, rbins=None,
numTh=200, numRoff=200, numRinner=20, factorRouter=3):
if rbins is None:
rmin, rmax = 0.1, 5.
rbins = np.logspace(np.log10(rmin), np.log10(rmax), num=50)
self._rbins = rbins * units.Mpc
else:
# check rbins input units & type
self._rbins = utils.check_units_and_type(rbins, units.Mpc)
# check input units & types
self._rs = utils.check_units_and_type(rs, units.Mpc)
self._delta_c = utils.check_units_and_type(delta_c, None)
self._rho_crit = utils.check_units_and_type(rho_crit, units.Msun /
units.Mpc / (units.pc**2))
self._numRoff = utils.check_units_and_type(numRoff, None,
is_scalar=True)
self._numTh = utils.check_units_and_type(numTh, None, is_scalar=True)
self._numRinner = utils.check_units_and_type(numRinner, None,
is_scalar=True)
self._factorRouter = utils.check_units_and_type(factorRouter, None,
is_scalar=True)
# check numbers of bins are all positive
if (numRoff <= 0) or (numTh <= 0) or (numRinner <= 0) or \
(factorRouter <= 0):
raise ValueError('Require numbers of bins > 0')
self._nbins = self._rbins.shape[0]
self._nlens = self._rs.shape[0]
if offsets is not None:
self._sigmaoffset = utils.check_units_and_type(offsets, units.Mpc)
utils.check_input_size(self._sigmaoffset, self._nlens)
else:
self._sigmaoffset = offsets
# check array sizes are compatible
utils.check_input_size(self._rs, self._nlens)
utils.check_input_size(self._delta_c, self._nlens)
utils.check_input_size(self._rho_crit, self._nlens)
utils.check_input_size(self._rbins, self._nbins)
rs_dc_rcrit = self._rs * self._delta_c * self._rho_crit
self._rs_dc_rcrit = rs_dc_rcrit.reshape(self._nlens,
1).repeat(self._nbins, 1)
# set self._x, self._x_big, self._x_small, self._x_one
_set_dimensionless_radius(self)
def calc_nfw(self, rbins, offsets=None, numTh=200, numRoff=200,
numRinner=20, factorRouter=3):
"""Calculates Sigma and DeltaSigma profiles.
Generates the surface mass density (sigma_nfw attribute of parent
object) and differential surface mass density (deltasigma_nfw
attribute of parent object) profiles of each cluster, assuming a
spherical NFW model. Optionally includes the effect of cluster
miscentering offsets.
Parameters
----------
rbins : array_like
Radial bins (in Mpc) for calculating cluster profiles. Should
be 1D, optionally with astropy.units of Mpc.
offsets : array_like, optional
Parameter describing the width (in Mpc) of the Gaussian
distribution of miscentering offsets. Should be 1D, optionally
with astropy.units of Mpc.
Other Parameters
-------------------
numTh : int, optional
Parameter to pass to SurfaceMassDensity(). Number of bins to
use for integration over theta, for calculating offset profiles
(no effect for offsets=None). Default 200.
numRoff : int, optional
Parameter to pass to SurfaceMassDensity(). Number of bins to
use for integration over R_off, for calculating offset profiles
(no effect for offsets=None). Default 200.
numRinner : int, optional
Parameter to pass to SurfaceMassDensity(). Number of bins at
r < min(rbins) to use for integration over Sigma(<r), for
calculating DeltaSigma (no effect for Sigma ever, and no effect
for DeltaSigma if offsets=None). Default 20.
factorRouter : int, optional
Parameter to pass to SurfaceMassDensity(). Factor increase over
number of rbins, at min(r) < r < max(r), of bins that will be
used at for integration over Sigma(<r), for calculating
DeltaSigma (no effect for Sigma, and no effect for DeltaSigma
if offsets=None). Default 3.
"""
if offsets is None:
self._sigoffset = np.zeros(self.number) * units.Mpc
else:
self._sigoffset = utils.check_units_and_type(offsets, units.Mpc,
num=self.number)
self.rbins = utils.check_units_and_type(rbins, units.Mpc)
rhoc = self._rho_crit.to(units.Msun / units.pc**2 / units.Mpc)
smd = SurfaceMassDensity(self.rs, self.delta_c, rhoc,
offsets=self._sigoffset,
rbins=self.rbins,
numTh=numTh,
numRoff=numRoff,
numRinner=numRinner,
factorRouter=factorRouter)
self.sigma_nfw = smd.sigma_nfw()
self.deltasigma_nfw = smd.deltasigma_nfw()
def massrich_norm(self, norm):
self._massrich_norm = utils.check_units_and_type(norm, units.Msun,
is_scalar=True)
# behavior is to convert current n200 -> new m200
if hasattr(self, 'n200'):
self._richness_to_mass()
def m200(self, mass):
# Creates/updates values of cluster M200s & dependant variables.
self._m200 = utils.check_units_and_type(mass, units.Msun,
num=self.number)
self._df['m200'] = pd.Series(self._m200, index=self._df.index)
self._mass_to_richness()
def n200(self, richness):
# Creates/updates values of cluster N200s & dependant variables.
self._n200 = utils.check_units_and_type(richness, None,
num=self.number)
self._df['n200'] = pd.Series(self._n200, index=self._df.index)
self._richness_to_mass()
def calc_nfw(self,
rbins,
offsets=None,
numTh=200,
numRoff=200,
numRinner=20,
factorRouter=3):
"""Calculates Sigma and DeltaSigma profiles.
Generates the surface mass density (sigma_nfw attribute of parent
object) and differential surface mass density (deltasigma_nfw
attribute of parent object) profiles of each cluster, assuming a
spherical NFW model. Optionally includes the effect of cluster
miscentering offsets.
Parameters
----------
rbins : array_like
Radial bins (in Mpc) for calculating cluster profiles. Should
be 1D, optionally with astropy.units of Mpc.
offsets : array_like, optional
Parameter describing the width (in Mpc) of the Gaussian
distribution of miscentering offsets. Should be 1D, optionally
with astropy.units of Mpc.
Other Parameters
-------------------
numTh : int, optional
Parameter to pass to SurfaceMassDensity(). Number of bins to
use for integration over theta, for calculating offset profiles
(no effect for offsets=None). Default 200.
numRoff : int, optional
Parameter to pass to SurfaceMassDensity(). Number of bins to
use for integration over R_off, for calculating offset profiles
(no effect for offsets=None). Default 200.
numRinner : int, optional
Parameter to pass to SurfaceMassDensity(). Number of bins at
r < min(rbins) to use for integration over Sigma(<r), for
calculating DeltaSigma (no effect for Sigma ever, and no effect
for DeltaSigma if offsets=None). Default 20.
factorRouter : int, optional
Parameter to pass to SurfaceMassDensity(). Factor increase over
number of rbins, at min(r) < r < max(r), of bins that will be
used at for integration over Sigma(<r), for calculating
DeltaSigma (no effect for Sigma, and no effect for DeltaSigma
if offsets=None). Default 3.
"""
if offsets is None:
self._sigoffset = np.zeros(self.number) * units.Mpc
else:
self._sigoffset = utils.check_units_and_type(offsets,
units.Mpc,
num=self.number)
self.rbins = utils.check_units_and_type(rbins, units.Mpc)
rhoc = self._rho_crit.to(units.Msun / units.pc**2 / units.Mpc)
smd = SurfaceMassDensity(self.rs,
self.delta_c,
rhoc,
offsets=self._sigoffset,
rbins=self.rbins,
numTh=numTh,
numRoff=numRoff,
numRinner=numRinner,
factorRouter=factorRouter)
self.sigma_nfw = smd.sigma_nfw()
self.deltasigma_nfw = smd.deltasigma_nfw()
