Commit aa67fcf6 authored by Marco Selig's avatar Marco Selig

version update.

parent 698d5799
......@@ -96,7 +96,7 @@ Requirements
Download
........
The latest release is tagged **v0.3.0** and is available as a source package
The latest release is tagged **v0.4.0** and is available as a source package
at `<https://github.com/mselig/nifty/tags>`_. The current version can be
obtained by cloning the repository::
......@@ -128,8 +128,9 @@ References
..........
.. [1] Selig et al., "NIFTY - Numerical Information Field Theory - a
versatile Python library for signal inference", submitted to A&A, 2013;
`arXiv:1301.4499 <http://www.arxiv.org/abs/1301.4499>`_
versatile Python library for signal inference",
`A&A, vol. 554, id. A26 <http://dx.doi.org/10.1051/0004-6361/201321236>`_,
2013; `arXiv:1301.4499 <http://www.arxiv.org/abs/1301.4499>`_
Release Notes
-------------
......
......@@ -107,7 +107,8 @@
References
----------
.. [#] Selig et al., "NIFTY -- Numerical Information Field Theory --
a versatile Python library for signal inference", submitted to A&A,
a versatile Python library for signal inference",
`A&A, vol. 554, id. A26 <http://dx.doi.org/10.1051/0004-6361/201321236>`_,
2013; `arXiv:1301.4499 <http://www.arxiv.org/abs/1301.4499>`_
"""
......@@ -483,7 +484,7 @@ class _about(object): ## nifty support class for global settings
"""
## version
self._version = "0.3.97" ## FIXME: release veriosn 0.4.0 << REFERENCE + README
self._version = "0.4.0"
## switches and notifications
self._errors = notification(default=True,ccode=notification._code)
......@@ -1107,7 +1108,7 @@ class space(object):
def get_power_undex(self,pindex=None): ## TODO: remove in future version
"""
**DEPRECATED** Provides the unindexing list for an indexed power spectrum.
**DEPRECATED** Provides the Unindexing array for an indexed power spectrum.
Parameters
----------
......@@ -1117,13 +1118,13 @@ class space(object):
Returns
-------
pundex : list
Unindexing list undoing power indexing.
pundex : numpy.ndarray
Unindexing array undoing power indexing.
Notes
-----
Indexing with the unindexing list undoes the indexing with the
indexing array; i.e., ``x == x[pindex][pundex]``.
Indexing with the unindexing array undoes the indexing with the
indexing array; i.e., ``power == power[pindex].flatten()[pundex]``.
See also
--------
......@@ -1174,7 +1175,7 @@ class space(object):
Provides one-dimensional arrays containing the scales of the
spectral bands and the numbers of modes per scale, and an array
giving for each component of a field the corresponding index of a
power spectrum as well as an unindexing list.
power spectrum as well as an Unindexing array.
Parameters
----------
......@@ -1201,16 +1202,16 @@ class space(object):
pindex : numpy.ndarray
Indexing array giving the power spectrum index for each
represented mode.
pundex : list
Unindexing list undoing power spectrum indexing.
pundex : numpy.ndarray
Unindexing array undoing power spectrum indexing.
Notes
-----
The ``kindex`` and ``rho`` are each one-dimensional arrays.
The indexing array is of the same shape as a field living in this
space and contains the indices of the associated bands.
Indexing with the unindexing list undoes the indexing with the
indexing array; i.e., ``power == power[pindex][pundex]``.
Indexing with the unindexing array undoes the indexing with the
indexing array; i.e., ``power == power[pindex].flatten()[pundex]``.
See also
--------
......
......@@ -64,8 +64,8 @@ def weight_power(domain,spec,power=1,pindex=None,pundex=None,**kwargs):
pindex : ndarray, *optional*
Indexing array giving the power spectrum index for each
represented mode.
pundex : list, *optional*
Unindexing list undoing power indexing.
pundex : ndarray, *optional*
Unindexing array undoing power indexing.
Returns
-------
......@@ -265,7 +265,7 @@ def _calc_laplace(kindex): ## > computes Laplace operator and integrand
klim = len(kindex)
L = np.zeros((klim,klim))
I = np.zeros(klim)
for jj in range(2,klim-1): ## leave out {0,1,kmax}
for jj in xrange(2,klim-1): ## leave out {0,1,kmax}
L[jj,jj-1] = 2/(dl2[jj-1]*dl1[jj-1])
L[jj,jj] = -2/dl2[jj-1]*(1/dl1[jj]+1/dl1[jj-1])
L[jj,jj+1] = 2/(dl2[jj-1]*dl1[jj])
......@@ -317,8 +317,8 @@ def infer_power(m,domain=None,Sk=None,D=None,pindex=None,pundex=None,kindex=None
pindex : numpy.ndarray, *optional*
Indexing array giving the power spectrum index for each
represented mode (default: None).
pundex : list, *optional*
Unindexing list undoing power indexing.
pundex : ndarray, *optional*
Unindexing array undoing power indexing.
kindex : numpy.ndarray, *optional*
Scale corresponding to each band in the power spectrum
(default: None).
......
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