[SCM] Core functionality for performing astronomy and astrophysics with Python branch, debian, updated. 118db66a494c64fef2e145137231793bbdaa4974

[Ole Streicher]

The following commit has been merged in the debian branch:
commit 118db66a494c64fef2e145137231793bbdaa4974
Author: Ole Streicher <debian at liska.ath.cx>
Date:   Wed Feb 13 13:34:57 2013 +0100

    Fix dh_sphinx problems

diff --git a/debian/patches/fix_sphinxbuild.patch b/debian/patches/fix_sphinxbuild.patch
new file mode 100644
index 0000000..98c8ce0
--- /dev/null
+++ b/debian/patches/fix_sphinxbuild.patch
@@ -0,0 +1,119 @@
+Author: Ole Streicher <debian at liska.ath.cx>
+Description: Fix some glitches of the documentation that may prevent
+ dh_pshinxdoc to succeed.
+--- /dev/null
++++ b/CHANGES.rst
+@@ -0,0 +1 @@
++(dummy)
+--- a/docs/io/registry.rst
++++ b/docs/io/registry.rst
+@@ -4,7 +4,9 @@
+ I/O Registry (`astropy.io.registry`)
+ ************************************
+ 
+-.. note:: The I/O registry is only meant to be used directly by users who want
++.. note::
++
++          The I/O registry is only meant to be used directly by users who want
+           to define their own custom readers/writers. Users who want to find
+           out more about what built-in formats are supported by
+           :class:`~astropy.table.table.Table` by default should see
+--- a/astropy/nddata/convolution/convolve.py
++++ b/astropy/nddata/convolution/convolve.py
+@@ -172,17 +172,19 @@
+     Convolve an ndarray with an nd-kernel.  Returns a convolved image with
+     shape = array.shape.  Assumes kernel is centered.
+ 
+-    convolve_fft differs from `scipy.signal.fftconvolve` in a few ways:
++    `convolve_fft` differs from `scipy.signal.fftconvolve` in a few ways:
+ 
+-    * can treat NaN's as zeros or interpolate over them
+-    * (optionally) pads to the nearest 2^n size to improve FFT speed
+-    * only operates in mode='same' (i.e., the same shape array is returned) mode
+-    * can use your own fft, e.g. pyFFTW or pyFFTW3, which can lead to
+-      performance improvements, depending on your system configuration.  fftw3
++    * It can treat NaN's as zeros or interpolate over them.
++    * (optionally) It pads to the nearest 2^n size to improve FFT speed.
++    * Its only valid `mode` is 'same' (i.e., the same shape array is returned)
++    * It lets you use your own fft, e.g.,
++      `pyFFTW <http://pypi.python.org/pypi/pyFFTW>`_ or
++      `pyFFTW3 <http://pypi.python.org/pypi/PyFFTW3/0.2.1>`_ , which can lead to
++      performance improvements, depending on your system configuration.  pyFFTW3
+       is threaded, and therefore may yield significant performance benefits on
+       multi-core machines at the cost of greater memory requirements.  Specify
+-      the :param:`fftn` and :param:`ifftn` keyword to override the default, which
+-      is numpy's fft
++      the `fftn` and `ifftn` keywords to override the default, which is
++      `numpy.fft.fft` and `numpy.fft.ifft`.
+ 
+     Parameters
+     ----------
+@@ -245,7 +247,7 @@
+         `fftn=scipy.fftpack.fftn`
+     complex_dtype : np.complex
+         Which complex dtype to use.  `numpy` has a range of options, from 64 to
+-        256.  
++        256.
+ 
+     See Also
+     --------
+@@ -261,36 +263,36 @@
+ 
+     Examples
+     --------
+-    >>> convolve_fft([1,0,3],[1,1,1])
++    >>> convolve_fft([1, 0, 3], [1, 1, 1])
+     array([ 1.,  4.,  3.])
+ 
+-    >>> convolve_fft([1,np.nan,3],[1,1,1])
++    >>> convolve_fft([1, np.nan, 3], [1, 1, 1])
+     array([ 1.,  4.,  3.])
+ 
+-    >>> convolve_fft([1,0,3],[0,1,0])
++    >>> convolve_fft([1, 0, 3], [0, 1, 0])
+     array([ 1.,  0.,  3.])
+ 
+-    >>> convolve_fft([1,2,3],[1])
++    >>> convolve_fft([1, 2, 3], [1])
+     array([ 1.,  2.,  3.])
+ 
+-    >>> convolve_fft([1,np.nan,3],[0,1,0], interpolate_nan=True)
++    >>> convolve_fft([1, np.nan, 3], [0, 1, 0], interpolate_nan=True)
+     array([ 1.,  0.,  3.])
+ 
+-    >>> convolve_fft([1,np.nan,3],[0,1,0], interpolate_nan=True, min_wt=1e-8)
++    >>> convolve_fft([1, np.nan, 3], [0, 1, 0], interpolate_nan=True,
++    ...              min_wt=1e-8)
+     array([ 1.,  nan,  3.])
+ 
+-    >>> convolve_fft([1,np.nan,3],[1,1,1], interpolate_nan=True)
++    >>> convolve_fft([1, np.nan, 3], [1, 1, 1], interpolate_nan=True)
+     array([ 1.,  4.,  3.])
+ 
+-    >>> convolve_fft([1,np.nan,3],[1,1,1], interpolate_nan=True, 
+-                     normalize_kernel=True, ignore_edge_zeros=True)
++    >>> convolve_fft([1, np.nan, 3], [1, 1, 1], interpolate_nan=True,
++    ...               normalize_kernel=True, ignore_edge_zeros=True)
+     array([ 1.,  2.,  3.])
+ 
+-    # optional - requires scipy
+-    >>> import scipy.fftpack
+-    >>> convolve_fft([1,np.nan,3],[1,1,1], interpolate_nan=True, 
+-                      normalize_kernel=True, ignore_edge_zeros=True,
+-                      fftn=scipy.fftpack.fft, ifftn=scipy.fftpack.ifft)
++    >>> import scipy.fftpack  # optional - requires scipy
++    >>> convolve_fft([1, np.nan, 3], [1, 1, 1], interpolate_nan=True,
++    ...               normalize_kernel=True, ignore_edge_zeros=True,
++    ...               fftn=scipy.fftpack.fft, ifftn=scipy.fftpack.ifft)
+     array([ 1.,  2.,  3.])
+ 
+     """
+@@ -347,7 +349,7 @@
+         else:
+             kernel_is_normalized = False
+             if (interpolate_nan or ignore_edge_zeros):
+-                WARNING = ("Kernel is not normalized, therefore ignore_edge_zeros"+ 
++                WARNING = ("Kernel is not normalized, therefore ignore_edge_zeros"+
+                     "and interpolate_nan will be ignored.")
+                 log.warn(WARNING)
+ 
diff --git a/debian/patches/series b/debian/patches/series
index 99a8d59..470ec3b 100644
--- a/debian/patches/series
+++ b/debian/patches/series
@@ -1 +1,2 @@
 install_on_py2.6.patch
+fix_sphinxbuild.patch

-- 
Core functionality for performing astronomy and astrophysics with Python