From: W. Trevor King <wking@drexel.edu>
Date: Thu, 4 Nov 2010 12:41:49 +0000 (-0400)
Subject: Fix 'Creating an HDF5 file' headline and convert tabs to spaces in HDF5 post.
X-Git-Url: http://git.tremily.us/?a=commitdiff_plain;h=3db1c0330e4e69e8d584305310fc890ac396ef6f;p=mw2txt.git

Fix 'Creating an HDF5 file' headline and convert tabs to spaces in HDF5 post.
---

diff --git a/posts/HDF5.mdwn b/posts/HDF5.mdwn
index 068394a..8ee60fa 100644
--- a/posts/HDF5.mdwn
+++ b/posts/HDF5.mdwn
@@ -27,7 +27,7 @@ filesystem concept map:
 
 
 Creating an HDF5 file
----------------------"
+---------------------
 
     >>> import h5py
     >>> f = h5py.File('file.h5', 'w')
@@ -171,7 +171,7 @@ Creating groups using absolute and relative names
     >>> f = h5py.File('groups.h5', 'w')
     >>> g1 = f.create_group('/MyGroup')
     >>> g2 = f.create_group('/MyGroup/Group_A')
-		>>> g3 = g1.create_group('Group_B')
+    >>> g3 = g1.create_group('Group_B')
     >>> f.keys()
     ['MyGroup']
     >>> f['MyGroup'].keys()
@@ -241,8 +241,8 @@ Just use the [Numpy slice indexing][slice] you're used to.
     >>> import numpy
     >>> f = h5py.File('hype.h5', 'w')
     >>> f['IntArray'] = numpy.ones((8, 10))
-		>>> dset = f['IntArray']
-		>>> dset.value
+    >>> dset = f['IntArray']
+    >>> dset.value
     array([[ 1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.],
            [ 1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.],
            [ 1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.],
@@ -251,7 +251,7 @@ Just use the [Numpy slice indexing][slice] you're used to.
            [ 1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.],
            [ 1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.],
            [ 1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.]])
-	  >>> f['IntArray'][:,5:] = 2
+    >>> f['IntArray'][:,5:] = 2
     >>> dset.value
     array([[ 1.,  1.,  1.,  1.,  1.,  2.,  2.,  2.,  2.,  2.],
            [ 1.,  1.,  1.,  1.,  1.,  2.,  2.,  2.,  2.,  2.],
@@ -262,8 +262,8 @@ Just use the [Numpy slice indexing][slice] you're used to.
            [ 1.,  1.,  1.,  1.,  1.,  2.,  2.,  2.,  2.,  2.],
            [ 1.,  1.,  1.,  1.,  1.,  2.,  2.,  2.,  2.,  2.]])
     >>> dset[1:4,2:6] = 5
-		>>> f['IntArray'].value
-		array([[ 1.,  1.,  1.,  1.,  1.,  2.,  2.,  2.,  2.,  2.],
+    >>> f['IntArray'].value
+    array([[ 1.,  1.,  1.,  1.,  1.,  2.,  2.,  2.,  2.,  2.],
            [ 1.,  1.,  5.,  5.,  5.,  5.,  2.,  2.,  2.,  2.],
            [ 1.,  1.,  5.,  5.,  5.,  5.,  2.,  2.,  2.,  2.],
            [ 1.,  1.,  5.,  5.,  5.,  5.,  2.,  2.,  2.,  2.],
@@ -283,16 +283,16 @@ Your array's `numpy.dtype` will be preserved.
     >>> import h5py
     >>> f = h5py.File('dtype.h5', 'w')
     >>> f['complex'] = 2 + 3j
-		>>> f['complex'].dtype
+    >>> f['complex'].dtype
     dtype('complex128')
-		>>> type(f['complex'].value)
+    >>> type(f['complex'].value)
     <type 'complex'>
-		>>> f['complex array'] = [1 + 2j, 3 + 4j]
-		>>> f['complex array'].dtype
+    >>> f['complex array'] = [1 + 2j, 3 + 4j]
+    >>> f['complex array'].dtype
     dtype('complex128')
-		>>> type(f['complex array'].value)
+    >>> type(f['complex array'].value)
     <type 'numpy.ndarray'>
-		>>> f.close()
+    >>> f.close()
 
 Which creates
 
@@ -343,20 +343,20 @@ Chunking and extendible datasets
 Extendible datasets must be chunked.
 
     >>> import h5py
-		>>> import numpy
+    >>> import numpy
     >>> f = h5py.File('ext.h5', 'w')
     >>> f['simple'] = [1, 2, 3]  # not chunked
-		>>> s = f['simple']
-		>>> s.chunks == None
-		True
-		>>> s.resize((6,))
+    >>> s = f['simple']
+    >>> s.chunks == None
+    True
+    >>> s.resize((6,))
     Traceback (most recent call last):
       ...
     TypeError: Only chunked datasets can be resized
-		>>> c = f.create_dataset('chunked', (3,), numpy.int32, chunks=(2,))
-		>>> c.chunks
+    >>> c = f.create_dataset('chunked', (3,), numpy.int32, chunks=(2,))
+    >>> c.chunks
     (2,)
-		>>> c[:] = [9, 8, 7]
+    >>> c[:] = [9, 8, 7]
     >>> c.resize((6,))
     >>> c.value
     array([1, 2, 3, 0, 0, 0])
@@ -364,7 +364,7 @@ Extendible datasets must be chunked.
     Traceback (most recent call last):
       ...
     TypeError: New shape length (2) must match dataset rank (1)
-		>>> f.close()
+    >>> f.close()
 
 The "chunkiness" of data is not listed by `h5dump`,