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Commit 18d2fafe authored by Marco Selig's avatar Marco Selig
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docu adjustments; changed to pre-release version 0.3.9; TODO: nifty reference.

parent 9ba55278
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demos/demo_excaliwir.py
View file @ 18d2fafe
......@@ -52,7 +52,7 @@ g = gl_space(48)
z = s_space = k = k_space = p = d_space = None
## power spectrum (and more)
power = powerindex = powerundex = kindex = rho = None
power = kindex = rho = powerindex = powerundex = None
## operators
S = Sk = R = N = Nj = D = None
......@@ -111,7 +111,7 @@ def setup(space,s2n=3,nvar=None):
the noise variance, `nvar` will be calculated according to
`s2n` if not specified (default: None)
"""
global z,s_space,k,k_space,p,d_space,power,powerindex,powerundex,kindex,rho,S,Sk,R,N,Nj,D,s,n,d,j,m
global z,s_space,k,k_space,p,d_space,power,kindex,rho,powerindex,powerundex,S,Sk,R,N,Nj,D,s,n,d,j,m
## signal space
z = s_space = space
......@@ -119,17 +119,15 @@ def setup(space,s2n=3,nvar=None):
## conjugate space
k = k_space = s_space.get_codomain()
## the power indices are calculated once and saved
powerindex = k_space.get_power_index()
powerundex = k_space.get_power_undex()
kindex,rho = k_space.get_power_index(irreducible=True)
kindex,rho,powerindex,powerundex = k_space.get_power_indices()
## power spectrum
power = [42/(kk+1)**3 for kk in kindex]
power = (lambda kk: 42/(kk+1)**3)
## prior signal covariance operator (power operator)
S = power_operator(k_space,spec=power,pindex=powerindex)
S = power_operator(k_space,spec=power)
## projection operator to the spectral bands
Sk = S.get_projection_operator(pindex=powerindex)
Sk = S.get_projection_operator()
## the Gaussian random field generated from its power operator S
s = S.get_random_field(domain=s_space,target=k_space)
......@@ -169,7 +167,7 @@ def run(space=r1,s2n=3,nvar=None,**kwargs):
the noise variance, `nvar` will be calculated according to
`s2n` if not specified (default: None)
"""
global z,s_space,k,k_space,p,d_space,power,powerindex,powerundex,kindex,rho,S,Sk,R,N,Nj,D,s,n,d,j,m
global s_space,k_space,d_space,power,S,Sk,R,N,Nj,D,s,n,d,j,m
## setting up signal, noise, data and the operators S, N and R
setup(space,s2n=s2n,nvar=nvar)
......@@ -196,7 +194,7 @@ def run(space=r1,s2n=3,nvar=None,**kwargs):
m.plot(title="reconstructed map",vmin=np.min(s.val),vmax=np.max(s.val),**kwargs)
## power spectrum
# s.plot(title="power spectra",power=True,other=(m,power),mono=False,kindex=kindex)
# s.plot(title="power spectra",power=True,other=(m,power),mono=False)
## uncertainty
# uncertainty = D.hat(bare=True,nrun=D.domain.dim()//4,target=k_space)
......@@ -234,7 +232,7 @@ def run_critical(space=r2,s2n=3,nvar=None,q=1E-12,alpha=1,perception=[1,0],**kwa
infer_power
"""
global z,s_space,k,k_space,p,d_space,power,powerindex,powerundex,kindex,rho,S,Sk,R,N,Nj,D,s,n,d,j,m
global s_space,k_space,d_space,power,rho,S,Sk,R,N,Nj,D,s,n,d,j,m
## setting up signal, noise, data and the operators S, N and R
setup(space,s2n=s2n,nvar=nvar)
......@@ -245,7 +243,7 @@ def run_critical(space=r2,s2n=3,nvar=None,q=1E-12,alpha=1,perception=[1,0],**kwa
j = R.adjoint_times(N.inverse_times(d))
## unknown power spectrum, the power operator is given an initial value
S.set_power(42,bare=True,pindex=powerindex) ## The answer is 42. I double checked.
S.set_power(42,bare=True) ## The answer is 42. I double checked.
## the power spectrum is drawn from the first guess power operator
pk = S.get_power(bare=False) ## non-bare(!)
......@@ -266,14 +264,14 @@ def run_critical(space=r2,s2n=3,nvar=None,q=1E-12,alpha=1,perception=[1,0],**kwa
b1 = Sk.pseudo_tr(m) ## == Sk(m).pseudo_dot(m), but faster
b2 = Sk.pseudo_tr(D,nrun=np.sqrt(Sk.domain.dim())//4) ## probing of the partial traces of D
pk_new = (2*q+b1+perception[0]*b2)/(rho+2*(alpha-1+perception[1])) ## non-bare(!)
pk_new = smooth_power(pk_new,kindex,mode="2s",exclude=min(8,len(power))) ## smoothing
pk_new = smooth_power(pk_new,domain=k_space,mode="2s",exclude=min(8,len(rho))) ## smoothing
## the power operator is given the new spectrum
S.set_power(pk_new,bare=False,pindex=powerindex) ## auto-updates D
S.set_power(pk_new,bare=False) ## auto-updates D
## check convergence
log_change = np.max(np.abs(log(pk_new/pk)))
if(log_change<=0.01):
note.cprint("NOTE: accuracy reached in iteration %u."%(iteration))
note.cprint("NOTE: desired accuracy reached in iteration %u."%(iteration))
break
else:
note.cprint("NOTE: log-change == %4.3f ( > 1%% ) in iteration %u."%(log_change,iteration))
......@@ -290,7 +288,7 @@ def run_critical(space=r2,s2n=3,nvar=None,q=1E-12,alpha=1,perception=[1,0],**kwa
m.plot(title="reconstructed map",vmin=np.min(s.val),vmax=np.max(s.val),**kwargs)
## power spectrum
s.plot(title="power spectra",power=True,other=(S.get_power(pundex=powerundex),power),mono=False,kindex=kindex)
s.plot(title="power spectra",power=True,other=(S.get_power(),power),mono=False)
## uncertainty
# uncertainty = D.hat(bare=True,nrun=D.domain.dim()//4,target=k_space)
......
demos/demo_faraday.py
View file @ 18d2fafe
......@@ -91,8 +91,7 @@ def run(projection=False, power=False):
m1 = m0.transform(l)
if(projection):
## define projection operator
powerindex = l.get_power_index()
Sk = projection_operator(l, assign=powerindex)
Sk = projection_operator(l)
## project quadrupole
m2 = Sk(m0, band=2)
......@@ -116,7 +115,7 @@ def run(projection=False, power=False):
m3.plot(title=r"$m$ on a spherical Gauss-Legendre grid", vmin=-4, vmax=4, cmap=ncmap.fm())
m4.plot(title=r"$m$ on a regular 2D grid", vmin=-4, vmax=4, cmap=ncmap.fm())
if(power):
m5.plot(title=r"(restricted) Fourier power spectrum of $m$", vmin=1E-3, vmax=1E+0, mono=False)
m5.plot(title=r"(restricted, binned) Fourier power spectrum of $m$", vmin=1E-3, vmax=1E+0, mono=False, log=True)
##=============================================================================
nifty_core.py
View file @ 18d2fafe
......@@ -483,7 +483,7 @@ class _about(object): ## nifty support class for global settings
"""
## version
self._version = "0.3.1"
self._version = "0.3.9" ## FIXME: release veriosn 0.4.0 << REFERENCE + README
## switches and notifications
self._errors = notification(default=True,ccode=notification._code)
......@@ -1071,7 +1071,7 @@ class space(object):
def get_power_index(self,irreducible=False): ## TODO: remove in future version
"""
Provides the indexing array of the power spectrum.
**DEPRECATED** Provides the indexing array of the power spectrum.
Provides either an array giving for each component of a field the
corresponding index of a power spectrum (if ``irreducible==False``)
......@@ -1105,9 +1105,9 @@ class space(object):
about.warnings.cprint("WARNING: 'get_power_index' is deprecated.")
raise NotImplementedError(about._errors.cstring("ERROR: no generic instance method 'get_power_index'."))
def get_power_undex(self,pindex=None):
def get_power_undex(self,pindex=None): ## TODO: remove in future version
"""
Provides the unindexing list for an indexed power spectrum.
**DEPRECATED** Provides the unindexing list for an indexed power spectrum.
Parameters
----------
......@@ -1948,8 +1948,8 @@ class point_space(space):
def get_power_index(self,irreducible=False): ## TODO: remove in future version
"""
Raises an error since the power spectrum is ill-defined for point
spaces.
**DEPRECATED** Raises an error since the power spectrum is
ill-defined for point spaces.
"""
about.warnings.cprint("WARNING: 'get_power_index' is deprecated.")
raise AttributeError(about._errors.cstring("ERROR: power spectra ill-defined for (unstructured) point spaces."))
......@@ -2454,7 +2454,7 @@ class rg_space(space):
def get_power_index(self,irreducible=False): ## TODO: remove in future version
"""
Provides the indexing array of the power spectrum.
**DEPRECATED** Provides the indexing array of the power spectrum.
Provides either an array giving for each component of a field the
corresponding index of a power spectrum (if ``irreducible==False``)
......@@ -3542,7 +3542,7 @@ class lm_space(space):
def get_power_index(self,irreducible=False): ## TODO: remove in future version
"""
Provides the indexing array of the power spectrum.
**DEPRECATED** Provides the indexing array of the power spectrum.
Provides either an array giving for each component of a field the
corresponding index of a power spectrum (if ``irreducible==False``)
......@@ -4367,7 +4367,7 @@ class gl_space(space):
def get_power_index(self,irreducible=False): ## TODO: remove in future version
"""
Raises an error since the power spectrum for a field on the sphere
**DEPRECATED** Raises an error since the power spectrum for a field on the sphere
is defined via the spherical harmonics components and not its
position-space representation.
"""
......@@ -5000,7 +5000,7 @@ class hp_space(space):
def get_power_index(self,irreducible=False): ## TODO: remove in future version
"""
Raises an error since the power spectrum for a field on the sphere
**DEPRECATED** Raises an error since the power spectrum for a field on the sphere
is defined via the spherical harmonics components and not its
position-space representation.
"""
......@@ -5528,8 +5528,8 @@ class nested_space(space):
def get_power_index(self,irreducible=False): ## TODO: remove in future version
"""
Raises an error since there is no canonical definition for the
power spectrum on a generic product space.
**DEPRECATED** Raises an error since there is no canonical
definition for the power spectrum on a generic product space.
"""
about.warnings.cprint("WARNING: 'get_power_index' is deprecated.")
raise AttributeError(about._errors.cstring("ERROR: power spectra indexing ill-defined."))
......
nifty_power.py
View file @ 18d2fafe
......@@ -41,9 +41,9 @@
"""
from __future__ import division
from scipy.interpolate import interp1d as ip
from scipy.interpolate import interp1d as ip ##
#import numpy as np
from nifty_core import *
from nifty.nifty_core import *
import smoothing as gs
......
setup.py
View file @ 18d2fafe
......@@ -23,7 +23,7 @@ from distutils.core import setup
import os
setup(name="nifty",
version="0.3.1",
version="0.4.0",
description="Numerical Information Field Theory",
author="Marco Selig",
author_email="mselig@mpa-garching.mpg.de",
......
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