ran reindent in preparation for the 1.1 release

1 files changed, 30 insertions, 31 deletions

diff --git a/numpy/lib/io.py b/numpy/lib/io.py
index 9e61ab2f8..4c7180245 100644
--- a/numpy/lib/io.py
+++ b/numpy/lib/io.py
@@ -232,37 +232,37 @@ def loadtxt(fname, dtype=float, comments='#', delimiter=None, converters=None,
 
     Parameters
     ----------
-    fname : filename or a file handle.  
+    fname : filename or a file handle.
       Support for gzipped files is automatic, if the filename ends in .gz
 
-    dtype : data-type 
-      Data type of the resulting array.  If this is a record data-type, the 
-      resulting array will be 1-d and each row will be interpreted as an 
-      element of the array. The number of columns used must match the number 
+    dtype : data-type
+      Data type of the resulting array.  If this is a record data-type, the
+      resulting array will be 1-d and each row will be interpreted as an
+      element of the array. The number of columns used must match the number
       of fields in the data-type in this case.
 
-    comments : str 
+    comments : str
       The character used to indicate the start of a comment in the file.
 
     delimiter : str
-      A string-like character used to separate values in the file. If delimiter 
+      A string-like character used to separate values in the file. If delimiter
       is unspecified or none, any whitespace string is a separator.
 
     converters : {}
-      A dictionary mapping column number to a function that will convert that 
-      column to a float.  Eg, if column 0 is a date string: 
-      converters={0:datestr2num}. Converters can also be used to provide 
-      a default value for missing data: converters={3:lambda s: float(s or 0)}. 
-    
+      A dictionary mapping column number to a function that will convert that
+      column to a float.  Eg, if column 0 is a date string:
+      converters={0:datestr2num}. Converters can also be used to provide
+      a default value for missing data: converters={3:lambda s: float(s or 0)}.
+
     skiprows : int
       The number of rows from the top to skip.
 
     usecols : sequence
-      A sequence of integer column indexes to extract where 0 is the first 
+      A sequence of integer column indexes to extract where 0 is the first
       column, eg. usecols=(1,4,5) will extract the 2nd, 5th and 6th columns.
 
     unpack : bool
-      If True, will transpose the matrix allowing you to unpack into named 
+      If True, will transpose the matrix allowing you to unpack into named
       arguments on the left hand side.
 
     Examples
@@ -271,8 +271,8 @@ def loadtxt(fname, dtype=float, comments='#', delimiter=None, converters=None,
       >>> x,y,z = load('somefile.dat', usecols=(3,5,7), unpack=True)
       >>> r = np.loadtxt('record.dat', dtype={'names':('gender','age','weight'),
                 'formats': ('S1','i4', 'f4')})
-    
-    SeeAlso: scipy.io.loadmat to read and write matfiles.            
+
+    SeeAlso: scipy.io.loadmat to read and write matfiles.
     """
 
     if _string_like(fname):
@@ -332,23 +332,23 @@ def savetxt(fname, X, fmt='%.18e',delimiter=' '):
     Parameters
     ----------
     fname : filename or a file handle
-      If the filename ends in .gz, the file is automatically saved in 
-      compressed gzip format.  The load() command understands gzipped files 
+      If the filename ends in .gz, the file is automatically saved in
+      compressed gzip format.  The load() command understands gzipped files
       transparently.
     X : array or sequence
       Data to write to file.
-    fmt : string 
-      A format string %[flags][width][.precision]specifier. See notes below for 
+    fmt : string
+      A format string %[flags][width][.precision]specifier. See notes below for
       a description of some common flags and specifiers.
     delimiter : str
       Character separating columns.
-  
+
     Examples
     --------
       >>> savetxt('test.out', x, delimiter=',')         # X is an array
       >>> savetxt('test.out', (x,y,z))     # x,y,z equal sized 1D arrays
-      >>> savetxt('test.out', x, fmt='%1.4e')  # use exponential notation      
-    
+      >>> savetxt('test.out', x, fmt='%1.4e')  # use exponential notation
+
     Notes on fmt
     ------------
     flags:
@@ -362,19 +362,19 @@ def savetxt(fname, X, fmt='%.18e',delimiter=' '):
       For e, E and f specifiers, the number of digits to print after the decimal
       point.
       For g and G, the maximum number of significant digits.
-      For s, the maximum number of characters. 
+      For s, the maximum number of characters.
     specifiers:
       c : character
       d or i : signed decimal integer
-      e or E : scientific notation with e or E. 
+      e or E : scientific notation with e or E.
       f : decimal floating point
       g,G : use the shorter of e,E or f
       o : signed octal
       s : string of characters
       u : unsigned decimal integer
       x,X : unsigned hexadecimal integer
-      
-    This is not an exhaustive specification. 
+
+    This is not an exhaustive specification.
     """
 
     if _string_like(fname):
@@ -403,7 +403,7 @@ def savetxt(fname, X, fmt='%.18e',delimiter=' '):
 import re
 def fromregex(file, regexp, dtype):
     """Construct a record array from a text file, using regular-expressions parsing.
-    
+
     Array is constructed from all matches of the regular expression
     in the file. Groups in the regular expression are converted to fields.
 
@@ -423,7 +423,7 @@ def fromregex(file, regexp, dtype):
     >>> f.write("1312 foo\n1534  bar\n 444   qux")
     >>> f.close()
     >>> np.fromregex('test.dat', r"(\d+)\s+(...)", [('num', np.int64), ('key', 'S3')])
-    array([(1312L, 'foo'), (1534L, 'bar'), (444L, 'qux')], 
+    array([(1312L, 'foo'), (1534L, 'bar'), (444L, 'qux')],
           dtype=[('num', '<i8'), ('key', '|S3')])
 
     """
@@ -433,7 +433,7 @@ def fromregex(file, regexp, dtype):
         regexp = re.compile(regexp)
     if not isinstance(dtype, np.dtype):
         dtype = np.dtype(dtype)
-    
+
     seq = regexp.findall(file.read())
     if seq and not isinstance(seq[0], tuple):
         # make sure np.array doesn't interpret strings as binary data
@@ -441,4 +441,3 @@ def fromregex(file, regexp, dtype):
         seq = [(x,) for x in seq]
     output = np.array(seq, dtype=dtype)
     return output
-