Commit 4d0c5c5c authored by ultimanet's avatar ultimanet
Browse files

Merge remote-tracking branch 'upstream/master' into mpi

parents 9cf2d155 d66cbd72
......@@ -87,36 +87,58 @@ Requirements
(standard library)
* `GFFT <https://github.com/mrbell/gfft>`_ (v0.1.0) - Generalized Fast
Fourier Transformations for Python
Fourier Transformations for Python - **optional**
* `HEALPy <https://github.com/healpy/healpy>`_ (v1.4 without openmp) - A
Python wrapper for `HEALPix <http://sourceforge.net/projects/healpix/>`_
Python wrapper for `HEALPix <http://sourceforge.net/projects/healpix/>`_ -
**optional**
* `libsharp-wrapper <https://github.com/mselig/libsharp-wrapper>`_ (v0.1.2
without openmp) - A Python wrapper for the
`libsharp <http://sourceforge.net/projects/libsharp/>`_ library
`libsharp <http://sourceforge.net/projects/libsharp/>`_ library -
**optional**
Download
........
The latest release is tagged **v0.9.0** and is available as a source package
at `<https://github.com/mselig/nifty/tags>`_. The current version can be
obtained by cloning the repository::
The latest release is tagged **v1.0.6** and is available as a source package
at `<https://github.com/information-field-theory/nifty/tags>`_. The current
version can be obtained by cloning the repository::
git clone git://github.com/mselig/nifty.git
cd nifty
git clone git://github.com/information-field-theory/nifty.git
Installation
............
NIFTY is installed using Distutils by running the following command::
* NIFTY can be installed using `PyPI <https://pypi.python.org/pypi>`_ and
**pip** by running the following command::
python setup.py install
pip install ift_nifty
Alternatively, a private or user specific installation can be done by::
Alternatively, a private or user specific installation can be done by::
python setup.py install --user
python setup.py install --install-lib=/SOMEWHERE
pip install --user ift_nifty
* NIFTY can be installed using **Distutils** by running the following
command::
cd nifty
python setup.py install
Alternatively, a private or user specific installation can be done by::
python setup.py install --user
python setup.py install --install-lib=/SOMEWHERE
First Steps
...........
For a quickstart, you can browse through the
`informal introduction <http://www.mpa-garching.mpg.de/ift/nifty/start.html>`_
or dive into NIFTY by running one of the demonstrations, e.g.::
>>> run -m nifty.demos.demo_wf1
Acknowledgement
---------------
......
......@@ -457,10 +457,10 @@ class lm_space(space):
if(_gl_available): ## default
x = gl.synalm_f(arg[1],lmax=lmax,mmax=lmax)
else:
x = hp.synalm(arg[1].astype(np.complex128),lmax=lmax,mmax=lmax).astype(np.complex64)
x = hp.synalm(arg[1].astype(np.complex128),lmax=lmax,mmax=lmax).astype(np.complex64) ## FIXME: `verbose` kwarg
else:
if(_hp_available): ## default
x = hp.synalm(arg[1],lmax=lmax,mmax=lmax)
x = hp.synalm(arg[1],lmax=lmax,mmax=lmax) ## FIXME: `verbose` kwarg
else:
x = gl.synalm(arg[1],lmax=lmax,mmax=lmax)
......@@ -680,7 +680,7 @@ class lm_space(space):
elif(isinstance(codomain,hp_space)):
## transform
Tx = hp.alm2map(x.astype(np.complex128),codomain.para[0],lmax=self.para[0],mmax=self.para[1],pixwin=False,fwhm=0.0,sigma=None,invert=False,pol=True,inplace=False)
Tx = hp.alm2map(x.astype(np.complex128),codomain.para[0],lmax=self.para[0],mmax=self.para[1],pixwin=False,fwhm=0.0,sigma=None,invert=False,pol=True,inplace=False) ## FIXME: `verbose` kwarg
## weight if discrete
if(codomain.discrete):
Tx = codomain.calc_weight(Tx,power=0.5)
......@@ -1866,7 +1866,7 @@ class hp_space(space):
elif(arg[0]=="syn"):
lmax = 3*self.para[0]-1 ## 3*nside-1
x = hp.synfast(arg[1],self.para[0],lmax=lmax,mmax=lmax,alm=False,pol=True,pixwin=False,fwhm=0.0,sigma=None)
x = hp.synfast(arg[1],self.para[0],lmax=lmax,mmax=lmax,alm=False,pol=True,pixwin=False,fwhm=0.0,sigma=None) ## FIXME: `verbose` kwarg
## weight if discrete
if(self.discrete):
x = self.calc_weight(x,power=0.5)
......@@ -2007,7 +2007,7 @@ class hp_space(space):
if(self.discrete):
x = self.calc_weight(x,power=-0.5)
## transform
Tx = hp.map2alm(x.astype(np.float64),lmax=codomain.para[0],mmax=codomain.para[1],iter=kwargs.get("iter",self.niter),pol=True,use_weights=False,datapath=None)
Tx = hp.map2alm(x.astype(np.float64),lmax=codomain.para[0],mmax=codomain.para[1],iter=kwargs.get("iter",self.niter),pol=True,use_weights=False,regression=False,datapath=None)
else:
raise ValueError(about._errors.cstring("ERROR: unsupported transformation."))
......@@ -2081,7 +2081,7 @@ class hp_space(space):
if(self.discrete):
x = self.calc_weight(x,power=-0.5)
## power spectrum
return hp.anafast(x,map2=None,nspec=None,lmax=3*self.para[0]-1,mmax=3*self.para[0]-1,iter=kwargs.get("iter",self.niter),alm=False,pol=True,use_weights=False,datapath=None)
return hp.anafast(x,map2=None,nspec=None,lmax=3*self.para[0]-1,mmax=3*self.para[0]-1,iter=kwargs.get("iter",self.niter),alm=False,pol=True,use_weights=False,regression=False,datapath=None)
##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
......
......@@ -150,7 +150,7 @@ from multiprocessing import Value as mv
from multiprocessing import Array as ma
__version__ = "1.0.5"
__version__ = "1.0.6"
pi = 3.1415926535897932384626433832795028841971693993751058209749445923078164062862089986280348253421170679
......
......@@ -22,13 +22,16 @@
from distutils.core import setup
import os
setup(name="nifty",
version="0.9.0",
description="Numerical Information Field Theory",
setup(name="ift_nifty",
version="1.0.6",
author="Marco Selig",
author_email="mselig@mpa-garching.mpg.de",
maintainer="Theo Steininger",
maintainer_email="theos@mpa-garching.mpg.de",
description="Numerical Information Field Theory",
url="http://www.mpa-garching.mpg.de/ift/nifty/",
packages=["nifty", "nifty.demos", "nifty.rg", "nifty.lm"],
package_dir={"nifty": ""},
data_files=[(os.path.expanduser('~') + "/.nifty", ["nifty_config"])])
data_files=[(os.path.expanduser('~') + "/.nifty", ["nifty_config"])],
license="GPLv3")
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