def test_centered_profiles():
def _check_sigma(i):
assert_allclose(sigma_py.value, toy_data_sigma[i], rtol=1e-04)
def _check_deltasigma(i):
assert_allclose(deltasigma_py.value,
toy_data_deltasigma[i],
rtol=1e-04)
# note: default tolerance is (rtol=1e-07, atol=0)
zipped_inputs = zip(toy_data_rs, toy_data_dc, toy_data_rhoc)
# check all 4 sets of toy_data:
for i, (r_s, delta_c, rho_c) in enumerate(zipped_inputs):
smd = SurfaceMassDensity(r_s, delta_c, rho_c, rbins=toy_data_rbins)
sigma_py = smd.sigma_nfw()
_check_sigma(i)
deltasigma_py = smd.deltasigma_nfw()
_check_deltasigma(i)
def test_centered_profiles():
def _check_sigma(i):
assert_allclose(sigma_py.value, toy_data_sigma[i],
rtol=1e-04)
def _check_deltasigma(i):
assert_allclose(deltasigma_py.value, toy_data_deltasigma[i],
rtol=1e-04)
# note: default tolerance is (rtol=1e-07, atol=0)
zipped_inputs = zip(toy_data_rs, toy_data_dc, toy_data_rhoc)
# check all 4 sets of toy_data:
for i, (r_s, delta_c, rho_c) in enumerate(zipped_inputs):
smd = SurfaceMassDensity(r_s, delta_c, rho_c, rbins=toy_data_rbins)
sigma_py = smd.sigma_nfw()
_check_sigma(i)
deltasigma_py = smd.deltasigma_nfw()
_check_deltasigma(i)
def test_miscentered_profiles():
def _check_sigma(i):
assert_allclose(sigma_py_off.value, toy_data_sigma_off[i],
rtol=1e-04)
def _check_deltasigma(i):
assert_allclose(deltasigma_py_off.value, toy_data_deltasigma_off[i],
rtol=1e-04)
zipped_inputs = zip(toy_data_rs, toy_data_dc, toy_data_rhoc)
# check all 4 sets of toy_data:
for i, (r_s, delta_c, rho_c) in enumerate(zipped_inputs):
smd = SurfaceMassDensity(r_s, delta_c, rho_c,
offsets=toy_data_offset,
rbins=toy_data_rbins)
sigma_py_off = smd.sigma_nfw()
_check_sigma(i)
deltasigma_py_off = smd.deltasigma_nfw()
_check_deltasigma(i)
def test_miscentered_profiles():
def _check_sigma(i):
assert_allclose(sigma_py_off.value, toy_data_sigma_off[i], rtol=1e-04)
def _check_deltasigma(i):
assert_allclose(deltasigma_py_off.value,
toy_data_deltasigma_off[i],
rtol=1e-04)
zipped_inputs = zip(toy_data_rs, toy_data_dc, toy_data_rhoc)
# check all 4 sets of toy_data:
for i, (r_s, delta_c, rho_c) in enumerate(zipped_inputs):
smd = SurfaceMassDensity(r_s,
delta_c,
rho_c,
offsets=toy_data_offset,
rbins=toy_data_rbins)
sigma_py_off = smd.sigma_nfw()
_check_sigma(i)
deltasigma_py_off = smd.deltasigma_nfw()
_check_deltasigma(i)
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 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()