[Scipy-svn] r6760 - in trunk: scipy/stats scipy/stats/tests tools

scipy-svn@scip... scipy-svn@scip...
Sat Sep 11 20:00:29 CDT 2010


Author: ptvirtan
Date: 2010-09-11 20:00:29 -0500 (Sat, 11 Sep 2010)
New Revision: 6760

Modified:
   trunk/scipy/stats/_support.py
   trunk/scipy/stats/distributions.py
   trunk/scipy/stats/morestats.py
   trunk/scipy/stats/stats.py
   trunk/scipy/stats/tests/test_discrete_basic.py
   trunk/scipy/stats/tests/test_stats.py
   trunk/tools/py3tool.py
Log:
3K: stats: minimal changes to make scipy.stats to import

Modified: trunk/scipy/stats/_support.py
===================================================================
--- trunk/scipy/stats/_support.py	2010-09-12 01:00:08 UTC (rev 6759)
+++ trunk/scipy/stats/_support.py	2010-09-12 01:00:29 UTC (rev 6760)
@@ -1,9 +1,11 @@
 from numpy import asarray
-import stats
 import numpy as np
-from types import ListType, TupleType, StringType
 import copy
 
+ListType = list
+TupleType = tuple
+StringType = str
+
 def abut(source, *args):
     # comment: except for the repetition, this is equivalent to hstack.
     """\nLike the |Stat abut command.  It concatenates two arrays column-wise
@@ -236,7 +238,7 @@
                 item.append(cfcn(avgcol))
                 if stderr:
                     if len(avgcol)>1:
-                        item.append(stats.stderr(avgcol))
+                        item.append(compute_stderr(avgcol))
                     else:
                         item.append('N/A')
                 if ns:
@@ -248,7 +250,30 @@
             new_a = np.array(newlist,'O')
         return new_a
 
+def _chk_asarray(a, axis):
+    if axis is None:
+        a = np.ravel(a)
+        outaxis = 0
+    else:
+        a = np.asarray(a)
+        outaxis = axis
+    return a, outaxis
 
+def _chk2_asarray(a, b, axis):
+    if axis is None:
+        a = np.ravel(a)
+        b = np.ravel(b)
+        outaxis = 0
+    else:
+        a = np.asarray(a)
+        b = np.asarray(b)
+        outaxis = axis
+    return a, b, outaxis
+
+def compute_stderr(a, axis=0, ddof=1):
+    a, axis = _chk_asarray(a, axis)
+    return np.std(a,axis,ddof=1) / float(np.sqrt(a.shape[axis]))
+
 def makestr(item):
     if type(item) != StringType:
         item = str(item)

Modified: trunk/scipy/stats/distributions.py
===================================================================
--- trunk/scipy/stats/distributions.py	2010-09-12 01:00:08 UTC (rev 6759)
+++ trunk/scipy/stats/distributions.py	2010-09-12 01:00:29 UTC (rev 6760)
@@ -81,9 +81,15 @@
 from scipy.misc import doccer
 all = alltrue
 sgf = vectorize
-import new
 
+try:
+    from new import instancemethod
+except ImportError:
+    # Python 3
+    def instancemethod(func, obj, cls):
+        return types.MethodType(func, obj)
 
+
 # These are the docstring parts used for substitution in specific
 # distribution docstrings.
 
@@ -266,9 +272,15 @@
 # clean up all the separate docstring elements, we do not need them anymore
 for obj in [s for s in dir() if s.startswith('_doc_')]:
     exec('del ' + obj)
-del s, obj
+del obj
+try:
+    del s
+except NameError:
+    # in Python 3, loop variables are not visible after the loop
+    pass
 
 
+
 def _build_random_array(fun, args, size=None):
 # Build an array by applying function fun to
 # the arguments in args, creating an array with
@@ -542,7 +554,7 @@
 
         # self._size is total size of all output values
         self._size = product(size, axis=0)
-        if self._size > 1:
+        if self._size is not None and self._size > 1:
             size = numpy.array(size, ndmin=1)
 
         if np.all(scale == 0):
@@ -4764,17 +4776,17 @@
             self.qvals = numpy.cumsum(self.pk,axis=0)
             self.F = make_dict(self.xk, self.qvals)
             self.Finv = reverse_dict(self.F)
-            self._ppf = new.instancemethod(sgf(_drv_ppf,otypes='d'),
-                                           self, rv_discrete)
-            self._pmf = new.instancemethod(sgf(_drv_pmf,otypes='d'),
-                                           self, rv_discrete)
-            self._cdf = new.instancemethod(sgf(_drv_cdf,otypes='d'),
-                                           self, rv_discrete)
-            self._nonzero = new.instancemethod(_drv_nonzero, self, rv_discrete)
-            self.generic_moment = new.instancemethod(_drv_moment,
-                                                     self, rv_discrete)
-            self.moment_gen = new.instancemethod(_drv_moment_gen,
+            self._ppf = instancemethod(sgf(_drv_ppf,otypes='d'),
+                                       self, rv_discrete)
+            self._pmf = instancemethod(sgf(_drv_pmf,otypes='d'),
+                                       self, rv_discrete)
+            self._cdf = instancemethod(sgf(_drv_cdf,otypes='d'),
+                                       self, rv_discrete)
+            self._nonzero = instancemethod(_drv_nonzero, self, rv_discrete)
+            self.generic_moment = instancemethod(_drv_moment,
                                                  self, rv_discrete)
+            self.moment_gen = instancemethod(_drv_moment_gen,
+                                             self, rv_discrete)
             self.numargs=0
         else:
             cdf_signature = inspect.getargspec(self._cdf.im_func)
@@ -4787,14 +4799,14 @@
             #correct nin for generic moment vectorization
             self.vec_generic_moment = sgf(_drv2_moment, otypes='d')
             self.vec_generic_moment.nin = self.numargs + 2
-            self.generic_moment = new.instancemethod(self.vec_generic_moment,
-                                                     self, rv_discrete)
+            self.generic_moment = instancemethod(self.vec_generic_moment,
+                                                 self, rv_discrete)
 
             #correct nin for ppf vectorization
             _vppf = sgf(_drv2_ppfsingle,otypes='d')
             _vppf.nin = self.numargs + 2 # +1 is for self
-            self._vecppf = new.instancemethod(_vppf,
-                                              self, rv_discrete)
+            self._vecppf = instancemethod(_vppf,
+                                          self, rv_discrete)
 
         #now that self.numargs is defined, we can adjust nin
         self._cdfvec.nin = self.numargs + 1

Modified: trunk/scipy/stats/morestats.py
===================================================================
--- trunk/scipy/stats/morestats.py	2010-09-12 01:00:08 UTC (rev 6759)
+++ trunk/scipy/stats/morestats.py	2010-09-12 01:00:29 UTC (rev 6760)
@@ -6,6 +6,7 @@
 import math
 import statlib
 import stats
+from stats import find_repeats
 import distributions
 from numpy import isscalar, r_, log, sum, around, unique, asarray
 from numpy import zeros, arange, sort, amin, amax, any, where, \
@@ -29,13 +30,7 @@
            'circmean', 'circvar', 'circstd',
           ]
 
-def find_repeats(arr):
-    """Find repeats in arr and return (repeats, repeat_count)
-    """
-    v1,v2, n = futil.dfreps(arr)
-    return v1[:n],v2[:n]
 
-
 ##########################################################
 ###  Bayesian confidence intervals for mean, variance, std
 ##########################################################

Modified: trunk/scipy/stats/stats.py
===================================================================
--- trunk/scipy/stats/stats.py	2010-09-12 01:00:08 UTC (rev 6759)
+++ trunk/scipy/stats/stats.py	2010-09-12 01:00:29 UTC (rev 6760)
@@ -203,12 +203,12 @@
 import scipy.linalg as linalg
 import numpy as np
 
-#import scipy.stats  #is this a circular import ?
-from morestats import find_repeats #is only reference to scipy.stats
+import futil
 import distributions
 
 # Local imports.
 import _support
+from _support import _chk_asarray, _chk2_asarray
 
 __all__ = ['gmean', 'hmean', 'mean', 'cmedian', 'median', 'mode',
            'tmean', 'tvar', 'tmin', 'tmax', 'tstd', 'tsem',
@@ -233,26 +233,12 @@
           ]
 
 
-def _chk_asarray(a, axis):
-    if axis is None:
-        a = np.ravel(a)
-        outaxis = 0
-    else:
-        a = np.asarray(a)
-        outaxis = axis
-    return a, outaxis
+def find_repeats(arr):
+    """Find repeats in arr and return (repeats, repeat_count)
+    """
+    v1,v2, n = futil.dfreps(arr)
+    return v1[:n],v2[:n]
 
-def _chk2_asarray(a, b, axis):
-    if axis is None:
-        a = np.ravel(a)
-        b = np.ravel(b)
-        outaxis = 0
-    else:
-        a = np.asarray(a)
-        b = np.asarray(b)
-        outaxis = axis
-    return a, b, outaxis
-
 #######
 ### NAN friendly functions
 ########
@@ -1642,7 +1628,6 @@
     a, axis = _chk_asarray(a, axis)
     return np.std(a,axis,ddof=1) / float(np.sqrt(a.shape[axis]))
 
-
 def sem(a, axis=0, ddof=1):
     """
     Calculates the standard error of the mean (or standard error of

Modified: trunk/scipy/stats/tests/test_discrete_basic.py
===================================================================
--- trunk/scipy/stats/tests/test_discrete_basic.py	2010-09-12 01:00:08 UTC (rev 6759)
+++ trunk/scipy/stats/tests/test_discrete_basic.py	2010-09-12 01:00:29 UTC (rev 6760)
@@ -142,7 +142,7 @@
 
 def check_oth(distfn, arg, msg):
     #checking other methods of distfn
-    meanint = round(distfn.stats(*arg)[0]) # closest integer to mean
+    meanint = round(float(distfn.stats(*arg)[0])) # closest integer to mean
     npt.assert_almost_equal(distfn.sf(meanint, *arg), 1 - \
                             distfn.cdf(meanint, *arg), decimal=8)
     median_sf = distfn.isf(0.5, *arg)

Modified: trunk/scipy/stats/tests/test_stats.py
===================================================================
--- trunk/scipy/stats/tests/test_stats.py	2010-09-12 01:00:08 UTC (rev 6759)
+++ trunk/scipy/stats/tests/test_stats.py	2010-09-12 01:00:29 UTC (rev 6760)
@@ -1572,7 +1572,7 @@
     def do(self, a, b, axis=None, dtype=None):
         x = stats.hmean(a, axis=axis, dtype=dtype)
         assert_almost_equal(b, x)
-	assert_equal(x.dtype, dtype)
+        assert_equal(x.dtype, dtype)
 
 class GeoMeanTestCase:
     def test_1dlist(self):
@@ -1663,7 +1663,7 @@
         #Note this doesn't test when axis is not specified
         x = stats.gmean(a, axis=axis, dtype=dtype)
         assert_almost_equal(b, x)
-	assert_equal(x.dtype, dtype)
+        assert_equal(x.dtype, dtype)
 
 
 def test_binomtest():

Modified: trunk/tools/py3tool.py
===================================================================
--- trunk/tools/py3tool.py	2010-09-12 01:00:08 UTC (rev 6759)
+++ trunk/tools/py3tool.py	2010-09-12 01:00:29 UTC (rev 6760)
@@ -173,6 +173,7 @@
         os.path.join('optimize', 'nnls.py'),
         os.path.join('signal', '__init__.py'),
         os.path.join('signal', 'bsplines.py'),
+        os.path.join('signal', 'signaltools.py'),
         os.path.join('special', '__init__.py'),
         os.path.join('special', 'basic.py'),
         os.path.join('special', 'orthogonal.py'),
@@ -184,6 +185,11 @@
         os.path.join('sparse', 'linalg', 'eigen', 'arpack', 'arpack.py'),
         os.path.join('sparse', 'linalg', 'eigen', 'arpack', 'speigs.py'),
         os.path.join('sparse', 'linalg', 'iterative', 'isolve', 'iterative.py'),
+        os.path.join('stats', 'stats.py'),
+        os.path.join('stats', 'distributions.py'),
+        os.path.join('stats', 'morestats.py'),
+        os.path.join('stats', 'kde.py'),
+        os.path.join('stats', 'mstats_basic.py'),
     ]
 
     if any(filename.endswith(x) for x in import_mangling):



More information about the Scipy-svn mailing list