[Scipy-svn] r5307 - in trunk/scipy: io/matlab ndimage ndimage/tests signal/tests stats stats/tests

scipy-svn@scip... scipy-svn@scip...
Wed Dec 31 01:13:07 CST 2008


Author: jarrod.millman
Date: 2008-12-31 01:13:05 -0600 (Wed, 31 Dec 2008)
New Revision: 5307

Modified:
   trunk/scipy/io/matlab/gzipstreams.py
   trunk/scipy/io/matlab/mio5.py
   trunk/scipy/ndimage/doccer.py
   trunk/scipy/ndimage/filters.py
   trunk/scipy/ndimage/tests/test_doccer.py
   trunk/scipy/signal/tests/test_signaltools.py
   trunk/scipy/stats/stats.py
   trunk/scipy/stats/tests/test_stats.py
Log:
ran reindent


Modified: trunk/scipy/io/matlab/gzipstreams.py
===================================================================
--- trunk/scipy/io/matlab/gzipstreams.py	2008-12-31 07:02:20 UTC (rev 5306)
+++ trunk/scipy/io/matlab/gzipstreams.py	2008-12-31 07:13:05 UTC (rev 5307)
@@ -61,9 +61,9 @@
     ''
     >>> ZF.tell()
     6
-    >>> 
+    >>>
     '''
-    
+
     blocksize = 16384 # 16K
     def __init__(self, fileobj, length=None):
         ''' Initialize GzipInputStream
@@ -164,7 +164,7 @@
         -------
         data : string
             string containing read data
-            
+
         '''
         self.__fill(bytes)
         if bytes == -1:
@@ -217,4 +217,3 @@
                 break
             lines.append(s)
         return lines
-

Modified: trunk/scipy/io/matlab/mio5.py
===================================================================
--- trunk/scipy/io/matlab/mio5.py	2008-12-31 07:02:20 UTC (rev 5306)
+++ trunk/scipy/io/matlab/mio5.py	2008-12-31 07:13:05 UTC (rev 5307)
@@ -799,7 +799,7 @@
     def write(self):
         self.write_header()
         self._write_items()
-        
+
     def _write_items(self):
         # loop over data, column major
         A = np.atleast_2d(self.arr).flatten('F')
@@ -893,11 +893,11 @@
             # No interesting conversion possible
             raise TypeError('Could not convert %s (type %s) to array'
                             % (arr, type(arr)))
-        args = (self.stream, 
-                narr, 
-                name, 
-                is_global, 
-                self.unicode_strings, 
+        args = (self.stream,
+                narr,
+                name,
+                is_global,
+                self.unicode_strings,
                 self.long_field_names)
         if isinstance(narr, MatlabFunction):
             return Mat5FunctionWriter(*args)

Modified: trunk/scipy/ndimage/doccer.py
===================================================================
--- trunk/scipy/ndimage/doccer.py	2008-12-31 07:02:20 UTC (rev 5306)
+++ trunk/scipy/ndimage/doccer.py	2008-12-31 07:13:05 UTC (rev 5307)
@@ -94,7 +94,7 @@
     unindent_params : {False, True}, boolean, optional
         If True, strip common indentation from all parameters in
         docdict
-    
+
     Returns
     -------
     decfunc : function

Modified: trunk/scipy/ndimage/filters.py
===================================================================
--- trunk/scipy/ndimage/filters.py	2008-12-31 07:02:20 UTC (rev 5306)
+++ trunk/scipy/ndimage/filters.py	2008-12-31 07:13:05 UTC (rev 5307)
@@ -89,7 +89,7 @@
     'extra_arguments':_extra_arguments_doc,
     'extra_keywords':_extra_keywords_doc,
     }
-    
+
 docfiller = doccer.filldoc(docdict)
 
 @docfiller
@@ -99,7 +99,7 @@
 
     The lines of the array along the given axis are correlated with the
     given weights.
-    
+
     Parameters
     ----------
     %(input)s
@@ -921,7 +921,7 @@
     %(cval)s
     %(origin)s
     %(extra_arguments)s
-    %(extra_keywords)s    
+    %(extra_keywords)s
     """
     if extra_keywords is None:
         extra_keywords = {}
@@ -962,7 +962,7 @@
     %(cval)s
     %(origin)s
     %(extra_arguments)s
-    %(extra_keywords)s    
+    %(extra_keywords)s
     """
     if extra_keywords is None:
         extra_keywords = {}

Modified: trunk/scipy/ndimage/tests/test_doccer.py
===================================================================
--- trunk/scipy/ndimage/tests/test_doccer.py	2008-12-31 07:02:20 UTC (rev 5306)
+++ trunk/scipy/ndimage/tests/test_doccer.py	2008-12-31 07:13:05 UTC (rev 5307)
@@ -62,8 +62,8 @@
     # affect subsequent indent of inserted parameter
     yield assert_equal, formatted, """Single line doc Another test
    with some indent"""
-    
 
+
 def test_decorator():
     # with unindentation of parameters
     decorator = sndd.filldoc(doc_dict, True)

Modified: trunk/scipy/signal/tests/test_signaltools.py
===================================================================
--- trunk/scipy/signal/tests/test_signaltools.py	2008-12-31 07:02:20 UTC (rev 5306)
+++ trunk/scipy/signal/tests/test_signaltools.py	2008-12-31 07:13:05 UTC (rev 5307)
@@ -38,7 +38,7 @@
              [ 3, 33, 53, 67,  1, 78, 74, 55, 12, 83],
              [ 7, 11, 46, 70, 60, 47, 24, 43, 61, 26],
              [32, 61, 88,  7, 39,  4, 92, 64, 45, 61]]
-        
+
         d = signal.medfilt(f, [7, 3])
         e = signal.medfilt2d(np.array(f, np.float), [7, 3])
         assert_array_equal(d, [[ 0, 50, 50, 50, 42, 15, 15, 18, 27,  0],

Modified: trunk/scipy/stats/stats.py
===================================================================
--- trunk/scipy/stats/stats.py	2008-12-31 07:02:20 UTC (rev 5306)
+++ trunk/scipy/stats/stats.py	2008-12-31 07:13:05 UTC (rev 5307)
@@ -1904,7 +1904,7 @@
 
     >>> from scipy import stats
     >>> import numpy as np
-    
+
     >>> #fix seed to get the same result
     >>> np.random.seed(7654567)
     >>> rvs = stats.norm.rvs(loc=5,scale=10,size=(50,2))
@@ -1938,14 +1938,14 @@
 
     d = np.mean(a,axis) - popmean
     v = np.var(a, axis, ddof=1)
-    
+
     t = d / np.sqrt(v/float(n))
     t = np.where((d==0)*(v==0), 1.0, t) #define t=0/0 = 1, identical mean, var
     prob = distributions.t.sf(np.abs(t),df)*2  #use np.abs to get upper tail
     #distributions.t.sf currently does not propagate nans
     #this can be dropped, if distributions.t.sf propagates nans
     #if this is removed, then prob = prob[()] needs to be removed
-    prob = np.where(np.isnan(t), np.nan, prob)  
+    prob = np.where(np.isnan(t), np.nan, prob)
 
     if t.ndim == 0:
         t = t[()]
@@ -2004,7 +2004,7 @@
     >>> np.random.seed(12345678)
 
     test with sample with identical means
-    
+
     >>> rvs1 = stats.norm.rvs(loc=5,scale=10,size=500)
     >>> rvs2 = stats.norm.rvs(loc=5,scale=10,size=500)
     >>> stats.ttest_ind(rvs1,rvs2)
@@ -2012,7 +2012,7 @@
 
 
     test with sample with different means
-    
+
     >>> rvs3 = stats.norm.rvs(loc=8,scale=10,size=500)
     >>> stats.ttest_ind(rvs1,rvs3)
     (-5.0434013458585092, 5.4302979468623391e-007)
@@ -2032,7 +2032,7 @@
     t = d/np.sqrt(svar*(1.0/n1 + 1.0/n2))
     t = np.where((d==0)*(svar==0), 1.0, t) #define t=0/0 = 0, identical means
     prob = distributions.t.sf(np.abs(t),df)*2#use np.abs to get upper tail
-    
+
     #distributions.t.sf currently does not propagate nans
     #this can be dropped, if distributions.t.sf propagates nans
     #if this is removed, then prob = prob[()] needs to be removed
@@ -2041,7 +2041,7 @@
     if t.ndim == 0:
         t = t[()]
         prob = prob[()]
-        
+
     return t, prob
 
 
@@ -2113,15 +2113,15 @@
     d = (a-b).astype('d')
     v = np.var(d,axis,ddof=1)
     dm = np.mean(d, axis)
-    
+
     t = dm / np.sqrt(v/float(n))
-    t = np.where((dm==0)*(v==0), 1.0, t) #define t=0/0 = 1, zero mean and var 
+    t = np.where((dm==0)*(v==0), 1.0, t) #define t=0/0 = 1, zero mean and var
     prob = distributions.t.sf(np.abs(t),df)*2 #use np.abs to get upper tail
     #distributions.t.sf currently does not propagate nans
     #this can be dropped, if distributions.t.sf propagates nans
     #if this is removed, then prob = prob[()] needs to be removed
     prob = np.where(np.isnan(t), np.nan, prob)
-    
+
 ##    if not np.isscalar(t):
 ##        probs = np.reshape(probs, t.shape) # this should be redundant
 ##    if not np.isscalar(prob) and len(prob) == 1:

Modified: trunk/scipy/stats/tests/test_stats.py
===================================================================
--- trunk/scipy/stats/tests/test_stats.py	2008-12-31 07:02:20 UTC (rev 5306)
+++ trunk/scipy/stats/tests/test_stats.py	2008-12-31 07:13:05 UTC (rev 5307)
@@ -1088,18 +1088,18 @@
     t,p = stats.ttest_rel([0,0,0],[1,1,1])
     assert_equal((np.abs(t),p), (np.inf, 0))
     assert_equal(stats.ttest_rel([0,0,0], [0,0,0]), (1.0, 0.42264973081037427))
-    
+
     #check that nan in input array result in nan output
     anan = np.array([[1,np.nan],[-1,1]])
     assert_equal(stats.ttest_ind(anan, np.zeros((2,2))),([0, np.nan], [1,np.nan]))
-    
-    
+
+
 def test_ttest_ind():
     #regression test
     tr = 1.0912746897927283
     pr = 0.27647818616351882
     tpr = ([tr,-tr],[pr,pr])
-    
+
     rvs2 = np.linspace(1,100,100)
     rvs1 = np.linspace(5,105,100)
     rvs1_2D = np.array([rvs1, rvs2])
@@ -1133,15 +1133,15 @@
     #check that nan in input array result in nan output
     anan = np.array([[1,np.nan],[-1,1]])
     assert_equal(stats.ttest_ind(anan, np.zeros((2,2))),([0, np.nan], [1,np.nan]))
-    
 
-   
 
+
+
 def test_ttest_1samp_new():
     n1, n2, n3 = (10,15,20)
     rvn1 = stats.norm.rvs(loc=5,scale=10,size=(n1,n2,n3))
     rvn2 = stats.norm.rvs(loc=5,scale=10,size=(n1,n2,n3))
-    
+
     #check multidimensional array and correct axis handling
     #deterministic rvn1 and rvn2 would be better as in test_ttest_rel
     t1,p1 = stats.ttest_1samp(rvn1[:,:,:], np.ones((n2,n3)),axis=0)



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