def getfield(self):
r"""Generate a new realisation of the 3d field.
Returns
-------
field : ndarray
A realisation of the power spectrum. Shape is self._n.
"""
self.generate_kweight()
s = self._kweight.shape
# Fill array
f = np.random.standard_normal(s) + 1.0J * np.random.standard_normal(s)
f *= self._kweight
# TODO: is self._n argument here correct?
r = fftutil.irfftn(f)
return r
def getfield(self):
r"""Generate a new realisation of the 3d field.
Returns
-------
field : ndarray
A realisation of the power spectrum. Shape is self._n.
"""
self.generate_kweight()
s = self._kweight.shape
# Fill array
f = np.random.standard_normal(s) + 1.0J * np.random.standard_normal(s)
f *= self._kweight
# TODO: is self._n argument here correct?
r = fftutil.irfftn(f)
return r
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.
print("Gen field.")
rfv = gaussianfield.RandomField(npix=n, wsize=d)
rfv.powerspectrum = psv
vf0 = rfv.getfield()
# Construct an array of \mu^2 for each Fourier mode.
print("Construct kvec")
spacing = rfv._w / rfv._n
kvec = fftutil.rfftfreqn(rfv._n, spacing / (2 * math.pi))
print("Construct mu2")
mu2arr = kvec[..., 0] ** 2 / (kvec ** 2).sum(axis=3)
mu2arr.flat[0] = 0.0
del kvec
df = vf0
print("FFT vel")
# Construct the line of sight velocity field.
# TODO: is the s=rfv._n the correct thing here?
vf = fftutil.irfftn(mu2arr * fftutil.rfftn(vf0))
# 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.
print "Gen field."
rfv = gaussianfield.RandomField(npix = n, wsize = d)
rfv.powerspectrum = psv
vf0 = rfv.getfield()
# Construct an array of \mu^2 for each Fourier mode.
print "Construct kvec"
spacing = rfv._w / rfv._n
kvec = fftutil.rfftfreqn(rfv._n, spacing / (2*math.pi))
print "Construct mu2"
mu2arr = kvec[...,0]**2 / (kvec**2).sum(axis=3)
mu2arr.flat[0] = 0.0
del kvec
df = vf0
print "FFT vel"
# Construct the line of sight velocity field.
# TODO: is the s=rfv._n the correct thing here?
vf = fftutil.irfftn(mu2arr * fftutil.rfftn(vf0))
#return (df, vf, rfv, kvec)
return (df, vf) #, rfv)
