fixed a whole bunch of doctests

numpy/__init__.py

@@ -24,11 +24,13 @@
 
 Code snippets are indicated by three greater-than signs::
 
+  >>> x = 42
   >>> x = x + 1
 
 Use the built-in ``help`` function to view a function's docstring::
 
   >>> help(np.sort)
+  ... # doctest: +SKIP
 
 For some objects, ``np.info(obj)`` may provide additional help.  This is
 particularly true if you see the line "Help on ufunc object:" at the top
@@ -39,12 +41,14 @@
 To search for documents containing a keyword, do::
 
   >>> np.lookfor('keyword')
+  ... # doctest: +SKIP
 
 General-purpose documents like a glossary and help on the basic concepts
 of numpy are available under the ``doc`` sub-module::
 
   >>> from numpy import doc
   >>> help(doc)
+  ... # doctest: +SKIP
 
 Available subpackages
 ---------------------

numpy/add_newdocs.py

@@ -404,12 +404,12 @@
     Examples
     --------
     >>> np.empty([2, 2])
-    array([[ -9.74499359e+001,   6.69583040e-309],  #random data
-           [  2.13182611e-314,   3.06959433e-309]])
+    array([[ -9.74499359e+001,   6.69583040e-309],
+           [  2.13182611e-314,   3.06959433e-309]])         #random
 
     >>> np.empty([2, 2], dtype=int)
-    array([[-1073741821, -1067949133],  #random data
-           [  496041986,    19249760]])
+    array([[-1073741821, -1067949133],
+           [  496041986,    19249760]])                     #random
 
     """)
 
@@ -1516,7 +1516,7 @@
 
     >>> np.ndarray(shape=(2,2), dtype=float, order='F')
     array([[ -1.13698227e+002,   4.25087011e-303],
-           [  2.88528414e-306,   3.27025015e-309]])
+           [  2.88528414e-306,   3.27025015e-309]])         #random
 
     Second mode:
 

numpy/core/arrayprint.py

@@ -88,6 +88,11 @@ def set_printoptions(precision=None, threshold=None, edgeitems=None,
     >>> x**2 - (x + eps)**2
     array([-0., -0.,  0.,  0.])
 
+    To put back the default options, you can use:
+
+    >>> np.set_printoptions(edgeitems=3,infstr='Inf',
+    ... linewidth=75, nanstr='NaN', precision=8,
+    ... suppress=False, threshold=1000)
     """
 
     global _summaryThreshold, _summaryEdgeItems, _float_output_precision, \

numpy/core/defchararray.py

@@ -457,7 +457,7 @@ def count(a, sub, start=0, end=None):
     --------
     >>> c = np.array(['aAaAaA', '  aA  ', 'abBABba'])
     >>> c
-    array(['aAaAaA', '  aA', 'abBABba'],
+    array(['aAaAaA', '  aA  ', 'abBABba'],
         dtype='|S7')
     >>> np.char.count(c, 'A')
     array([3, 1, 1])
@@ -505,7 +505,7 @@ def decode(a, encoding=None, errors=None):
     --------
     >>> c = np.array(['aAaAaA', '  aA  ', 'abBABba'])
     >>> c
-    array(['aAaAaA', '  aA', 'abBABba'],
+    array(['aAaAaA', '  aA  ', 'abBABba'],
         dtype='|S7')
     >>> np.char.encode(c, encoding='cp037')
     array(['\\x81\\xc1\\x81\\xc1\\x81\\xc1', '@@\\x81\\xc1@@',
@@ -584,9 +584,9 @@ def endswith(a, suffix, start=0, end=None):
     >>> s
     array(['foo', 'bar'],
         dtype='|S3')
-    >>> np.charendswith(s, 'ar')
+    >>> np.char.endswith(s, 'ar')
     array([False,  True], dtype=bool)
-    >>> s.endswith(s, 'a', start=1, end=2)
+    >>> np.char.endswith(s, 'a', start=1, end=2)
     array([False,  True], dtype=bool)
 
     """
@@ -1010,15 +1010,17 @@ def lstrip(a, chars=None):
     --------
     >>> c = np.array(['aAaAaA', '  aA  ', 'abBABba'])
     >>> c
-    array(['aAaAaA', '  aA', 'abBABba'],
+    array(['aAaAaA', '  aA  ', 'abBABba'],
         dtype='|S7')
     >>> np.char.lstrip(c, 'a') # 'a' unstripped from c[1] because whitespace leading
-    array(['AaAaA', '  aA', 'bBABba'],
-        dtype='|S6')
+    array(['AaAaA', '  aA  ', 'bBABba'],
+        dtype='|S7')
     >>> np.char.lstrip(c, 'A') # leaves c unchanged
-    array(['aAaAaA', '  aA', 'abBABba'],
+    array(['aAaAaA', '  aA  ', 'abBABba'],
         dtype='|S7')
     >>> (np.char.lstrip(c, ' ') == np.char.lstrip(c, '')).all()
+    ... # XXX: is this a regression? this line now returns False
+    ... # np.char.lstrip(c,'') does not modify c at all.
     True
     >>> (np.char.lstrip(c, ' ') == np.char.lstrip(c, None)).all()
     True
@@ -1313,7 +1315,7 @@ def rstrip(a, chars=None):
         dtype='|S7')
     >>> np.char.rstrip(c, 'a')
     array(['aAaAaA', 'abBABb'],
-        dtype='|S6')
+        dtype='|S7')
     >>> np.char.rstrip(c, 'A')
     array(['aAaAa', 'abBABba'],
         dtype='|S7')
@@ -1444,16 +1446,16 @@ def strip(a, chars=None):
     --------
     >>> c = np.array(['aAaAaA', '  aA  ', 'abBABba'])
     >>> c
-    array(['aAaAaA', '  aA', 'abBABba'],
+    array(['aAaAaA', '  aA  ', 'abBABba'],
         dtype='|S7')
     >>> np.char.strip(c)
     array(['aAaAaA', 'aA', 'abBABba'],
         dtype='|S7')
     >>> np.char.strip(c, 'a') # 'a' unstripped from c[1] because whitespace leads
-    array(['AaAaA', '  aA', 'bBABb'],
-        dtype='|S6')
+    array(['AaAaA', '  aA  ', 'bBABb'],
+        dtype='|S7')
     >>> np.char.strip(c, 'A') # 'A' unstripped from c[1] because (unprinted) ws trails
-    array(['aAaAa', '  aA', 'abBABba'],
+    array(['aAaAa', '  aA  ', 'abBABba'],
         dtype='|S7')
 
     """
@@ -1523,7 +1525,7 @@ def title(a):
     array(['a1b c', '1b ca', 'b ca1', 'ca1b'],
         dtype='|S5')
     >>> np.char.title(c)
-    chararray(['A1B C', '1B Ca', 'B Ca1', 'Ca1B'],
+    array(['A1B C', '1B Ca', 'B Ca1', 'Ca1B'],
         dtype='|S5')
     """
     a_arr = numpy.asarray(a)
@@ -1590,7 +1592,7 @@ def upper(a):
     >>> c = np.array(['a1b c', '1bca', 'bca1']); c
     array(['a1b c', '1bca', 'bca1'],
         dtype='|S5')
-    >>> numpy.char.upper(c)
+    >>> np.char.upper(c)
     array(['A1B C', '1BCA', 'BCA1'],
         dtype='|S5')
     """
@@ -1742,15 +1744,15 @@ class adds the following functionality:
     Examples
     --------
     >>> charar = np.chararray((3, 3))
-    >>> charar[:, :] = 'abc'
+    >>> charar[:] = 'a'
     >>> charar
     chararray([['a', 'a', 'a'],
            ['a', 'a', 'a'],
            ['a', 'a', 'a']],
           dtype='|S1')
 
     >>> charar = np.chararray(charar.shape, itemsize=5)
-    >>> charar[:, :] = 'abc'
+    >>> charar[:] = 'abc'
     >>> charar
     chararray([['abc', 'abc', 'abc'],
            ['abc', 'abc', 'abc'],

numpy/core/fromnumeric.py

@@ -1298,8 +1298,9 @@ def clip(a, a_min, a_max, out=None):
     array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
     >>> np.clip(a, 3, 6, out=a)
     array([3, 3, 3, 3, 4, 5, 6, 6, 6, 6])
+    >>> a = np.arange(10)
     >>> a
-    array([3, 3, 3, 3, 4, 5, 6, 6, 6, 6])
+    array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
     >>> np.clip(a, [3,4,1,1,1,4,4,4,4,4], 8)
     array([3, 4, 2, 3, 4, 5, 6, 7, 8, 8])
 
@@ -1500,7 +1501,7 @@ def any(a,axis=None, out=None):
     >>> # Check now that z is a reference to o
     >>> z is o
     True
-    >>> id(z), id(o) # identity of z and o
+    >>> id(z), id(o) # identity of z and o              # doctest: +SKIP
     (191614240, 191614240)
 
     """
@@ -1563,7 +1564,7 @@ def all(a,axis=None, out=None):
 
     >>> o=np.array([False])
     >>> z=np.all([-1, 4, 5], out=o)
-    >>> id(z), id(o), z
+    >>> id(z), id(o), z                             # doctest: +SKIP
     (28293632, 28293632, array([ True], dtype=bool))
 
     """

numpy/core/function_base.py

@@ -63,8 +63,11 @@ def linspace(start, stop, num=50, endpoint=True, retstep=False):
     >>> x1 = np.linspace(0, 10, N, endpoint=True)
     >>> x2 = np.linspace(0, 10, N, endpoint=False)
     >>> plt.plot(x1, y, 'o')
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.plot(x2, y + 0.5, 'o')
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.ylim([-0.5, 1])
+    (-0.5, 1)
     >>> plt.show()
 
     """
@@ -129,8 +132,10 @@ def logspace(start,stop,num=50,endpoint=True,base=10.0):
     -----
     Logspace is equivalent to the code
 
-    >>> y = linspace(start, stop, num=num, endpoint=endpoint)
+    >>> y = np.linspace(start, stop, num=num, endpoint=endpoint)
+    ... # doctest: +SKIP
     >>> power(base, y)
+    ... # doctest: +SKIP
 
     Examples
     --------
@@ -149,8 +154,11 @@ def logspace(start,stop,num=50,endpoint=True,base=10.0):
     >>> x2 = np.logspace(0.1, 1, N, endpoint=False)
     >>> y = np.zeros(N)
     >>> plt.plot(x1, y, 'o')
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.plot(x2, y + 0.5, 'o')
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.ylim([-0.5, 1])
+    (-0.5, 1)
     >>> plt.show()
 
     """