def generate_kweight(self, regen = False):
r"""Pregenerate the k weights array.
Parameters
==========
regen : boolean, optional
If True, force regeneration of the weights, to be used if
parameters have been changed,
"""
# Perform some sanity checks
self._check_input()
# If already generated return array now.
if(self._kweightgen == True and not regen):
return
spacing = self._w / self._n
kvec = fftutil.rfftfreqn(self._n, spacing / (2*math.pi))
self._kweight = self.powerspectrum(kvec)**0.5 * self._n.prod() / (2.0 * self._w.prod() )**0.5
if not np.isfinite(self._kweight.flat[0]):
self._kweight.flat[0] = 0.0
self._kweightgen = True
def generate_kweight(self, regen=False):
r"""Pregenerate the k weights array.
Parameters
==========
regen : boolean, optional
If True, force regeneration of the weights, to be used if
parameters have been changed,
"""
# Perform some sanity checks
self._check_input()
# If already generated return array now.
if (self._kweightgen == True and not regen):
return
spacing = self._w / self._n
kvec = fftutil.rfftfreqn(self._n, spacing / (2 * math.pi))
self._kweight = self.powerspectrum(kvec)**0.5 * self._n.prod() / (
2.0 * self._w.prod())**0.5
if not np.isfinite(self._kweight.flat[0]):
self._kweight.flat[0] = 0.0
self._kweightgen = True
def _realisation_dv(self, d, n):
"""Generate the density and line of sight velocity fields in a
3d cube.
"""
if not self._vv_only:
raise Exception("Doesn't work for independent fields, I need to think a bit more first.")
def psv(karray):
"""Assume k0 is line of sight"""
k = (karray ** 2).sum(axis=3) ** 0.5
return self.ps_vv(k) * self.velocity_damping(karray[..., 0])
# Generate an underlying random field realisation of the
# matter distribution.
rfv = RandomField(npix=n, wsize=d)
rfv.powerspectrum = psv
vf0 = rfv.getfield()
# Construct an array of \mu^2 for each Fourier mode.
spacing = rfv._w / rfv._n
kvec = fftutil.rfftfreqn(rfv._n, spacing / (2 * math.pi))
mu2arr = kvec[..., 0] ** 2 / (kvec ** 2).sum(axis=3)
mu2arr.flat[0] = 0.0
del kvec
df = vf0
# Construct the line of sight velocity field.
# TODO: is the s=rfv._n the correct thing here?
vf = np.fft.irfftn(mu2arr * np.fft.rfftn(vf0), s=rfv._n)
# return (df, vf, rfv, kvec)
return (df, vf) # , rfv)
def _realisation_dv(self, d, n):
"""Generate the density and line of sight velocity fields in a
3d cube.
"""
if not self._vv_only:
raise Exception(
"Doesn't work for independent fields, I need to think a bit more first."
)
def psv(karray):
"""Assume k0 is line of sight"""
k = (karray**2).sum(axis=3)**0.5
return self.ps_vv(k) * self.velocity_damping(karray[..., 0])
# Generate an underlying random field realisation of the
# matter distribution.
rfv = RandomField(npix=n, wsize=d)
rfv.powerspectrum = psv
vf0 = rfv.getfield()
# Construct an array of \mu^2 for each Fourier mode.
spacing = rfv._w / rfv._n
kvec = fftutil.rfftfreqn(rfv._n, spacing / (2 * math.pi))
mu2arr = kvec[..., 0]**2 / (kvec**2).sum(axis=3)
mu2arr.flat[0] = 0.0
del kvec
df = vf0
# Construct the line of sight velocity field.
# TODO: is the s=rfv._n the correct thing here?
vf = np.fft.irfftn(mu2arr * np.fft.rfftn(vf0), s=rfv._n)
#return (df, vf, rfv, kvec)
return (df, vf) #, rfv)