def to_window(self, **params):
window = WindowFunction1D(**params)
sedges = self.result.sedges
window.poles = self.result.ells
window.los = self.result.los
if hasattr(self.result, 's'):
window.s = self.result.s
empty = scipy.isnan(window.s)
window.s[empty] = edges_to_mid(sedges)[empty]
else:
window.s = edges_to_mid(sedges)
window.window = self.result.counts
if window.zero in window:
window.error = window.window[window.index(window.zero)]**(1. / 2.)
volume = (4. * constants.pi) * radial_volume(sedges)
for ill, ell in enumerate(window):
window.window[ill] *= (
2 * ell +
1) / volume #legendre normalization and radial volume
window.window /= self.weight_tot
if hasattr(window, 'error'): window.error /= volume * self.weight_tot
window.norm = 1.
window.pad_zero()
return window
def to_window(self, s, key='A', **params):
poles = self.result.poles
attrs = self.result.attrs
self.logger.info('k-range: {:.1f} - {:.1f}.'.format(
attrs['kfun'].max(), attrs['knyq'].min()))
window = WindowFunction1D(**params)
window.poles = attrs['poles']
window.los = ('endpoint', self.params['losn'])
window.s = scipy.asarray(s)
self.logger.info(
'Normalization is {:.7g} and shotnoise is {:.7g}.'.format(
self.normalization, self.shotnoise))
#mask = poles['k']<attrs['knyq'].min()/3.
mask = poles['k'] >= 0.
k = poles['k'][mask]
volume = attrs['kfun'].prod() * poles['modes'][mask]
if key == 'A':
def Wk(ell):
return poles['{}_{:d}'.format(key, ell)][mask] / scipy.sqrt(
self.normalization)
if key == 'power':
def Wk(ell):
if ell == 0:
return poles['{}_{:d}'.format(
key,
ell)].real[mask] / self.normalization - self.shotnoise
return poles['{}_{:d}'.format(
key, ell)].real[mask] / self.normalization
window.window = scipy.empty((len(window.poles), len(window.s)),
dtype=Wk(0).dtype)
kk, ks = scipy.meshgrid(k, window.s, sparse=False, indexing='ij')
ks = kk * ks
for ill, ell in enumerate(window):
self.logger.info('Hankel transforming {}_{:d}.'.format(key, ell))
integrand = Wk(ell)[:, None] * 1. / (2. * constants.pi)**3 * (
-1)**(ell // 2) * special.spherical_jn(ell, ks)
window.window[ill] = scipy.sum(volume[:, None] * integrand, axis=0)
window.norm = self.normref
window.pad_zero()
return window
def to_window(self, **params):
window = WindowFunction1D(**params)
window.poles = self.result.ells
window.los = self.result.los
window.s = self.result.x
window.window = self.result.y
for ill, ell in enumerate(window):
window.window[ill] *= (2 * ell + 1) #legendre normalization
window.window *= 1. / self.result.integral()
window.norm = 1.
window.pad_zero()
return window
def to_window(self, **params):
window = WindowFunction1D(**params)
sedges = self.result.sedges
window.poles = self.result.ells
window.los = self.result.los
if hasattr(self.result, 's'):
window.s = self.result.s
empty = scipy.isnan(window.s)
window.s[empty] = edges_to_mid(sedges)[empty]
else:
window.s = edges_to_mid(sedges)
window.window = self.result.counts
volume = -scipy.diff(s_to_cos(sedges))
window.window /= volume[None, ...]
window.pad_zero()
window.s = s_to_cos(window.s)[::-1]
window.window[0] = window.window[0][::-1]
return window