fixed a whole bunch of doctests

11 files changed, 189 insertions, 88 deletions

diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index 76ea08dfb..7253740be 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -112,7 +112,6 @@ def histogram(a, bins=10, range=None, normed=False, weights=None, new=None):
     (array([ 0.25,  0.25,  0.25,  0.25]), array([0, 1, 2, 3, 4]))
     >>> np.histogram([[1, 2, 1], [1, 0, 1]], bins=[0,1,2,3])
     (array([1, 4, 1]), array([0, 1, 2, 3]))
-    ]), array([0, 1, 2, 3]))
 
     >>> a = np.arange(5)
     >>> hist, bin_edges = np.histogram(a, normed=True)
@@ -147,7 +146,7 @@ def histogram(a, bins=10, range=None, normed=False, weights=None, new=None):
             if mn == mx:
                 mn -= 0.5
                 mx += 0.5
-            bins = linspace(mn, mx, bins, endpoint=False)
+            bins = np.linspace(mn, mx, bins, endpoint=False)
         else:
             if normed:
                 raise ValueError, 'Use new=True to pass bin edges explicitly.'
@@ -293,7 +292,7 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None):
     >>> r = np.random.randn(100,3)
     >>> H, edges = np.histogramdd(r, bins = (5, 8, 4))
     >>> H.shape, edges[0].size, edges[1].size, edges[2].size
-    ((5,8,4), 6, 9, 5)
+    ((5, 8, 4), 6, 9, 5)
 
     """
 
@@ -791,7 +790,7 @@ def copy(a):
     -----
     This is equivalent to
 
-    >>> np.array(a, copy=True)
+    >>> np.array(a, copy=True)                              #doctest: +SKIP
 
     Examples
     --------
@@ -1019,7 +1018,7 @@ def interp(x, xp, fp, left=None, right=None):
     >>> np.interp(2.5, xp, fp)
     1.0
     >>> np.interp([0, 1, 1.5, 2.72, 3.14], xp, fp)
-    array([ 3. ,  3. ,  2.5,  0.56,  0. ])
+    array([ 3. ,  3. ,  2.5 ,  0.56,  0. ])
     >>> UNDEF = -99.0
     >>> np.interp(3.14, xp, fp, right=UNDEF)
     -99.0
@@ -1032,7 +1031,9 @@ def interp(x, xp, fp, left=None, right=None):
     >>> yinterp = np.interp(xvals, x, y)
     >>> import matplotlib.pyplot as plt
     >>> plt.plot(x, y, 'o')
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.plot(xvals, yinterp, '-x')
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.show()
 
     """
@@ -1161,7 +1162,7 @@ def sort_complex(a):
     array([ 1.+0.j,  2.+0.j,  3.+0.j,  5.+0.j,  6.+0.j])
 
     >>> np.sort_complex([1 + 2j, 2 - 1j, 3 - 2j, 3 - 3j, 3 + 5j])
-    array([ 1.+2.j,  2.-1.j,  3.-5.j,  3.-3.j,  3.+2.j])
+    array([ 1.+2.j,  2.-1.j,  3.-3.j,  3.-2.j,  3.+5.j])
 
     """
     b = array(a,copy=True)
@@ -2041,28 +2042,38 @@ def blackman(M):
 
     Plot the window and the frequency response:
 
-    >>> from numpy import clip, log10, array, bartlett, linspace
-    >>> from scipy.fftpack import fft, fftshift
+    >>> from numpy import clip, log10, array, blackman, linspace
+    >>> from numpy.fft import fft, fftshift
     >>> import matplotlib.pyplot as plt
 
     >>> window = blackman(51)
     >>> plt.plot(window)
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.title("Blackman window")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.ylabel("Amplitude")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.xlabel("Sample")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.show()
     
     >>> plt.figure()
+    <matplotlib.figure.Figure object at 0x...>
     >>> A = fft(window, 2048) / 25.5
     >>> mag = abs(fftshift(A))
     >>> freq = linspace(-0.5,0.5,len(A))
     >>> response = 20*log10(mag)
     >>> response = clip(response,-100,100)
     >>> plt.plot(freq, response)
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.title("Frequency response of Blackman window")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.ylabel("Magnitude [dB]")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.xlabel("Normalized frequency [cycles per sample]")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.axis('tight')
+    (-0.5, 0.5, -100.0, ...)
     >>> plt.show()
 
     """
@@ -2146,22 +2157,32 @@ def bartlett(M):
 
     >>> window = bartlett(51)
     >>> plt.plot(window)
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.title("Bartlett window")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.ylabel("Amplitude")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.xlabel("Sample")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.show()
     
     >>> plt.figure()
+    <matplotlib.figure.Figure object at 0x...>
     >>> A = fft(window, 2048) / 25.5
     >>> mag = abs(fftshift(A))
     >>> freq = linspace(-0.5,0.5,len(A))
     >>> response = 20*log10(mag)
     >>> response = clip(response,-100,100)
     >>> plt.plot(freq, response)
-    >>> plt.title("Frequency response of Blackman window")
+    [<matplotlib.lines.Line2D object at 0x...>]
+    >>> plt.title("Frequency response of Bartlett window")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.ylabel("Magnitude [dB]")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.xlabel("Normalized frequency [cycles per sample]")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.axis('tight')
+    (-0.5, 0.5, -100.0, ...)
     >>> plt.show()
 
     """
@@ -2237,25 +2258,39 @@ def hanning(M):
 
     >>> window = np.hanning(51)
     >>> plt.plot(window)
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.title("Hann window")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.ylabel("Amplitude")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.xlabel("Sample")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.show()
 
     >>> plt.figure()
+    <matplotlib.figure.Figure object at 0x...>
     >>> A = fft(window, 2048) / 25.5
     >>> mag = abs(fftshift(A))
     >>> freq = np.linspace(-0.5,0.5,len(A))
     >>> response = 20*np.log10(mag)
     >>> response = np.clip(response,-100,100)
     >>> plt.plot(freq, response)
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.title("Frequency response of the Hann window")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.ylabel("Magnitude [dB]")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.xlabel("Normalized frequency [cycles per sample]")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.axis('tight')
+    (-0.5, 0.5, -100.0, ...)
     >>> plt.show()
 
     """
+    # XXX: this docstring is inconsistent with other filter windows, e.g.
+    # Blackman and Bartlett -  they should all follow the same convention for
+    # clarity. Either use np. for all numpy members (as above), or import all
+    # numpy members (as in Blackman and Bartlett examples)
     if M < 1:
         return array([])
     if M == 1:
@@ -2321,27 +2356,37 @@ def hamming(M):
 
     Plot the window and the frequency response:
 
-    >>> from scipy.fftpack import fft, fftshift
+    >>> from numpy.fft import fft, fftshift
     >>> import matplotlib.pyplot as plt
 
     >>> window = np.hamming(51)
     >>> plt.plot(window)
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.title("Hamming window")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.ylabel("Amplitude")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.xlabel("Sample")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.show()
 
     >>> plt.figure()
+    <matplotlib.figure.Figure object at 0x...>
     >>> A = fft(window, 2048) / 25.5
     >>> mag = np.abs(fftshift(A))
     >>> freq = np.linspace(-0.5, 0.5, len(A))
     >>> response = 20 * np.log10(mag)
     >>> response = np.clip(response, -100, 100)
     >>> plt.plot(freq, response)
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.title("Frequency response of Hamming window")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.ylabel("Magnitude [dB]")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.xlabel("Normalized frequency [cycles per sample]")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.axis('tight')
+    (-0.5, 0.5, -100.0, ...)
     >>> plt.show()
 
     """
@@ -2587,27 +2632,37 @@ def kaiser(M,beta):
     Plot the window and the frequency response:
 
     >>> from numpy import clip, log10, array, kaiser, linspace
-    >>> from scipy.fftpack import fft, fftshift
+    >>> from numpy.fft import fft, fftshift
     >>> import matplotlib.pyplot as plt
 
     >>> window = kaiser(51, 14)
     >>> plt.plot(window)
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.title("Kaiser window")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.ylabel("Amplitude")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.xlabel("Sample")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.show()
 
     >>> plt.figure()
+    <matplotlib.figure.Figure object at 0x...>
     >>> A = fft(window, 2048) / 25.5
     >>> mag = abs(fftshift(A))
     >>> freq = linspace(-0.5,0.5,len(A))
     >>> response = 20*log10(mag)
     >>> response = clip(response,-100,100)
     >>> plt.plot(freq, response)
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.title("Frequency response of Kaiser window")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.ylabel("Magnitude [dB]")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.xlabel("Normalized frequency [cycles per sample]")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.axis('tight')
+    (-0.5, 0.5, -100.0, ...)
     >>> plt.show()
 
     """
@@ -2674,9 +2729,13 @@ def sinc(x):
 
     >>> import matplotlib.pyplot as plt
     >>> plt.plot(x, np.sinc(x))
+    [<matplotlib.lines.Line2D object at 0x...>]
     >>> plt.title("Sinc Function")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.ylabel("Amplitude")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.xlabel("X")
+    <matplotlib.text.Text object at 0x...>
     >>> plt.show()
 
     It works in 2-D as well:
@@ -2684,6 +2743,7 @@ def sinc(x):
     >>> x = np.arange(-200., 201.)/50.
     >>> xx = np.outer(x, x)
     >>> plt.imshow(np.sinc(xx))
+    <matplotlib.image.AxesImage object at 0x...>
 
     """
     y = pi* where(x == 0, 1.0e-20, x)
@@ -3277,7 +3337,7 @@ def append(arr, values, axis=None):
     >>> np.append([[1, 2, 3], [4, 5, 6]], [7, 8, 9], axis=0)
     Traceback (most recent call last):
     ...
-    ValueError: arrays must have same number of dimension
+    ValueError: arrays must have same number of dimensions
 
     """
     arr = asanyarray(arr)
diff --git a/numpy/lib/index_tricks.py b/numpy/lib/index_tricks.py
index 450ac4df8..8bbdeae1e 100644
--- a/numpy/lib/index_tricks.py
+++ b/numpy/lib/index_tricks.py
@@ -462,6 +462,7 @@ class RClass(AxisConcatenator):
     String integers specify the axis to concatenate along or the minimum
     number of dimensions to force entries into.
 
+    >>> a = np.array([[0, 1, 2], [3, 4, 5]])
     >>> np.r_['-1', a, a] # concatenate along last axis
     array([[0, 1, 2, 0, 1, 2],
            [3, 4, 5, 3, 4, 5]])
@@ -757,8 +758,8 @@ def fill_diagonal(a, val):
 
     Examples
     --------
-    >>> a = zeros((3, 3), int)
-    >>> fill_diagonal(a, 5)
+    >>> a = np.zeros((3, 3), int)
+    >>> np.fill_diagonal(a, 5)
     >>> a
     array([[5, 0, 0],
            [0, 5, 0],
@@ -766,8 +767,8 @@ def fill_diagonal(a, val):
 
     The same function can operate on a 4-D array:
 
-    >>> a = zeros((3, 3, 3, 3), int)
-    >>> fill_diagonal(a, 4)
+    >>> a = np.zeros((3, 3, 3, 3), int)
+    >>> np.fill_diagonal(a, 4)
 
     We only show a few blocks for clarity:
 
diff --git a/numpy/lib/io.py b/numpy/lib/io.py
index 7d2ac1c0e..66d695b00 100644
--- a/numpy/lib/io.py
+++ b/numpy/lib/io.py
@@ -734,9 +734,10 @@ def savetxt(fname, X, fmt='%.18e', delimiter=' '):
 
     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
+    >>> x = y = z = np.arange(0.0,5.0,1.0)
+    >>> np.savetxt('test.out', x, delimiter=',')   # X is an array
+    >>> np.savetxt('test.out', (x,y,z))   # x,y,z equal sized 1D arrays
+    >>> np.savetxt('test.out', x, fmt='%1.4e')   # use exponential notation
 
     """
 
@@ -833,7 +834,7 @@ def fromregex(file, regexp, dtype):
 
     >>> regexp = r"(\\d+)\\s+(...)"  # match [digits, whitespace, anything]
     >>> output = np.fromregex('test.dat', regexp,
-                              [('num', np.int64), ('key', 'S3')])
+    ...                       [('num', np.int64), ('key', 'S3')])
     >>> output
     array([(1312L, 'foo'), (1534L, 'bar'), (444L, 'qux')],
           dtype=[('num', '<i8'), ('key', '|S3')])
@@ -974,7 +975,7 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None,
 
     >>> s = StringIO("1,1.3,abcde")
     >>> data = np.genfromtxt(s, dtype=[('myint','i8'),('myfloat','f8'),
-        ('mystring','S5')], delimiter=",")
+    ... ('mystring','S5')], delimiter=",")
     >>> data
     array((1, 1.3, 'abcde'),
           dtype=[('myint', '<i8'), ('myfloat', '<f8'), ('mystring', '|S5')])
@@ -983,7 +984,7 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None,
 
     >>> s.seek(0) # needed for StringIO example only
     >>> data = np.genfromtxt(s, dtype=None,
-        names = ['myint','myfloat','mystring'], delimiter=",")
+    ... names = ['myint','myfloat','mystring'], delimiter=",")
     >>> data
     array((1, 1.3, 'abcde'),
           dtype=[('myint', '<i8'), ('myfloat', '<f8'), ('mystring', '|S5')])
@@ -992,7 +993,7 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None,
 
     >>> s.seek(0)
     >>> data = np.genfromtxt(s, dtype="i8,f8,S5",
-        names=['myint','myfloat','mystring'], delimiter=",")
+    ... names=['myint','myfloat','mystring'], delimiter=",")
     >>> data
     array((1, 1.3, 'abcde'),
           dtype=[('myint', '<i8'), ('myfloat', '<f8'), ('mystring', '|S5')])
@@ -1001,7 +1002,7 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None,
 
     >>> s = StringIO("11.3abcde")
     >>> data = np.genfromtxt(s, dtype=None, names=['intvar','fltvar','strvar'],
-            delimiter=[1,3,5])
+    ...     delimiter=[1,3,5])
     >>> data
     array((1, 1.3, 'abcde'),
           dtype=[('intvar', '<i8'), ('fltvar', '<f8'), ('strvar', '|S5')])
diff --git a/numpy/lib/polynomial.py b/numpy/lib/polynomial.py
index cf6cd65be..e953f71ba 100644
--- a/numpy/lib/polynomial.py
+++ b/numpy/lib/polynomial.py
@@ -92,11 +92,17 @@ def poly(seq_of_zeros):
     Given a sequence of a polynomial's zeros:
 
     >>> np.poly((0, 0, 0)) # Multiple root example
-    array([1, 0, 0, 0]) # i.e., z**3 + 0*z**2 + 0*z + 0
+    array([1, 0, 0, 0])
+    
+    The line above represents z**3 + 0*z**2 + 0*z + 0.
+
     >>> np.poly((-1./2, 0, 1./2))
-    array([ 1.  ,  0.  , -0.25,  0.  ]) # z**3 - z/4
+    array([ 1.  ,  0.  , -0.25,  0.  ])
+    
+    The line above represents z**3 - z/4
+
     >>> np.poly((np.random.random(1.)[0], 0, np.random.random(1.)[0]))
-    array([ 1.        , -0.77086955,  0.08618131,  0.        ])
+    array([ 1.        , -0.77086955,  0.08618131,  0.        ]) #random
 
     Given a square array object:
 
@@ -264,6 +270,7 @@ def polyint(p, m=1, k=None):
 
     >>> p = np.poly1d([1,1,1])
     >>> P = np.polyint(p)
+    >>> P
     poly1d([ 0.33333333,  0.5       ,  1.        ,  0.        ])
     >>> np.polyder(P) == p
     True
@@ -279,7 +286,7 @@ def polyint(p, m=1, k=None):
     0.0
     >>> P = np.polyint(p, 3, k=[6,5,3])
     >>> P
-    poly1d([ 0.01666667,  0.04166667,  0.16666667,  3.,  5.,  3. ])
+    poly1d([ 0.01666667,  0.04166667,  0.16666667,  3. ,  5. ,  3. ])
 
     Note that 3 = 6 / 2!, and that the constants are given in the order of
     integrations. Constant of the highest-order polynomial term comes first:
@@ -484,6 +491,7 @@ def polyfit(x, y, deg, rcond=None, full=False):
     >>> x = np.array([0.0, 1.0, 2.0, 3.0,  4.0,  5.0])
     >>> y = np.array([0.0, 0.8, 0.9, 0.1, -0.8, -1.0])
     >>> z = np.polyfit(x, y, 3)
+    >>> z
     array([ 0.08703704, -0.81349206,  1.69312169, -0.03968254])
 
     It is convenient to use `poly1d` objects for dealing with polynomials:
@@ -512,7 +520,9 @@ def polyfit(x, y, deg, rcond=None, full=False):
     >>> import matplotlib.pyplot as plt
     >>> xp = np.linspace(-2, 6, 100)
     >>> plt.plot(x, y, '.', xp, p(xp), '-', xp, p30(xp), '--')
+    [<matplotlib.lines.Line2D object at 0x...>, <matplotlib.lines.Line2D object at 0x...>, <matplotlib.lines.Line2D object at 0x...>]
     >>> plt.ylim(-2,2)
+    (-2, 2)
     >>> plt.show()
 
     """
@@ -836,7 +846,7 @@ def polydiv(u, v):
     >>> x = np.array([3.0, 5.0, 2.0])
     >>> y = np.array([2.0, 1.0])
     >>> np.polydiv(x, y)
-    >>> (array([ 1.5 ,  1.75]), array([ 0.25]))
+    (array([ 1.5 ,  1.75]), array([ 0.25]))
 
     """
     truepoly = (isinstance(u, poly1d) or isinstance(u, poly1d))
@@ -930,7 +940,9 @@ class poly1d(object):
     >>> p.r
     array([-1.+1.41421356j, -1.-1.41421356j])
     >>> p(p.r)
-    array([ -4.44089210e-16+0.j,  -4.44089210e-16+0.j]) # i.e., (0, 0)
+    array([ -4.44089210e-16+0.j,  -4.44089210e-16+0.j])
+    
+    These numbers in the previous line represent (0, 0) to machine precision
 
     Show the coefficients:
 
@@ -955,7 +967,7 @@ class poly1d(object):
     poly1d([ 1,  4, 10, 12,  9])
 
     >>> (p**3 + 4) / p
-    (poly1d([  1.,   4.,  10.,  12.,   9.]), poly1d([4]))
+    (poly1d([  1.,   4.,  10.,  12.,   9.]), poly1d([ 4.]))
 
     ``asarray(p)`` gives the coefficient array, so polynomials can be
     used in all functions that accept arrays:
diff --git a/numpy/lib/recfunctions.py b/numpy/lib/recfunctions.py
index b3eecdc0e..3f99a1ba8 100644
--- a/numpy/lib/recfunctions.py
+++ b/numpy/lib/recfunctions.py
@@ -50,10 +50,12 @@ def recursive_fill_fields(input, output):
 
     Examples
     --------
+    >>> from numpy.lib import recfunctions as rfn
     >>> a = np.array([(1, 10.), (2, 20.)], dtype=[('A', int), ('B', float)])
     >>> b = np.zeros((3,), dtype=a.dtype)
-    >>> recursive_fill_fields(a, b)
-    np.array([(1, 10.), (2, 20.), (0, 0.)], dtype=[('A', int), ('B', float)])
+    >>> rfn.recursive_fill_fields(a, b)
+    array([(1, 10.0), (2, 20.0), (0, 0.0)],
+          dtype=[('A', '<i4'), ('B', '<f8')])
 
     """
     newdtype = output.dtype
@@ -81,12 +83,13 @@ def get_names(adtype):
 
     Examples
     --------
-    >>> get_names(np.empty((1,), dtype=int)) is None
+    >>> from numpy.lib import recfunctions as rfn
+    >>> rfn.get_names(np.empty((1,), dtype=int)) is None
     True
-    >>> get_names(np.empty((1,), dtype=[('A',int), ('B', float)]))
+    >>> rfn.get_names(np.empty((1,), dtype=[('A',int), ('B', float)]))
     ('A', 'B')
     >>> adtype = np.dtype([('a', int), ('b', [('ba', int), ('bb', int)])])
-    >>> get_names(adtype)
+    >>> rfn.get_names(adtype)
     ('a', ('b', ('ba', 'bb')))
     """
     listnames = []
@@ -112,12 +115,13 @@ def get_names_flat(adtype):
 
     Examples
     --------
-    >>> get_names_flat(np.empty((1,), dtype=int)) is None
+    >>> from numpy.lib import recfunctions as rfn
+    >>> rfn.get_names_flat(np.empty((1,), dtype=int)) is None
     True
-    >>> get_names_flat(np.empty((1,), dtype=[('A',int), ('B', float)]))
+    >>> rfn.get_names_flat(np.empty((1,), dtype=[('A',int), ('B', float)]))
     ('A', 'B')
     >>> adtype = np.dtype([('a', int), ('b', [('ba', int), ('bb', int)])])
-    >>> get_names_flat(adtype)
+    >>> rfn.get_names_flat(adtype)
     ('a', 'b', 'ba', 'bb')
     """
     listnames = []
@@ -136,8 +140,9 @@ def flatten_descr(ndtype):
 
     Examples
     --------
+    >>> from numpy.lib import recfunctions as rfn
     >>> ndtype = np.dtype([('a', '<i4'), ('b', [('ba', '<f8'), ('bb', '<i4')])])
-    >>> flatten_descr(ndtype)
+    >>> rfn.flatten_descr(ndtype)
     (('a', dtype('int32')), ('ba', dtype('float64')), ('bb', dtype('int32')))
 
     """
@@ -198,12 +203,13 @@ def get_fieldstructure(adtype, lastname=None, parents=None,):
 
     Examples
     --------
-    >>> ndtype =  np.dtype([('A', int), 
+    >>> from numpy.lib import recfunctions as rfn
+    >>> ndtype =  np.dtype([('A', int),
     ...                     ('B', [('BA', int),
     ...                            ('BB', [('BBA', int), ('BBB', int)])])])
-    >>> get_fieldstructure(ndtype)
-    {'A': [], 'B': [], 'BA': ['B'], 'BB': ['B'],
-     'BBA': ['B', 'BB'], 'BBB': ['B', 'BB']}
+    >>> rfn.get_fieldstructure(ndtype)
+    ... # XXX: possible regression, order of BBA and BBB is swapped
+    {'A': [], 'B': [], 'BA': ['B'], 'BB': ['B'], 'BBA': ['B', 'BB'], 'BBB': ['B', 'BB']}
     
     """
     if parents is None:
@@ -340,20 +346,33 @@ def merge_arrays(seqarrays,
 
     Examples
     --------
-    >>> merge_arrays((np.array([1, 2]), np.array([10., 20., 30.])))
+    >>> from numpy.lib import recfunctions as rfn
+    >>> rfn.merge_arrays((np.array([1, 2]), np.array([10., 20., 30.])))
     masked_array(data = [(1, 10.0) (2, 20.0) (--, 30.0)],
-          mask = [(False, False) (False, False) (True, False)],
-          fill_value=(999999, 1e+20)
-          dtype=[('f0', '<i4'), ('f1', '<f8')])
-    >>> merge_arrays((np.array([1, 2]), np.array([10., 20., 30.])),
+                 mask = [(False, False) (False, False) (True, False)],
+           fill_value = (999999, 1e+20),
+                dtype = [('f0', '<i4'), ('f1', '<f8')])
+
+    >>> rfn.merge_arrays((np.array([1, 2]), np.array([10., 20., 30.])),
     ...              usemask=False)
-    array(data = [(1, 10.0) (2, 20.0) (-1, 30.0)],
+    array([(1, 10.0), (2, 20.0), (-1, 30.0)],
           dtype=[('f0', '<i4'), ('f1', '<f8')])
-    >>> merge_arrays((np.array([1, 2]).view([('a', int)]),
-                      np.array([10., 20., 30.])),
-                     usemask=False, asrecarray=True)
-    rec.array(data = [(1, 10.0) (2, 20.0) (-1, 30.0)],
-              dtype=[('a', int), ('f1', '<f8')])
+    >>> rfn.merge_arrays((np.array([1, 2]).view([('a', int)]),
+    ...               np.array([10., 20., 30.])),
+    ...              usemask=False, asrecarray=True)
+    rec.array([(1, 10.0), (2, 20.0), (-1, 30.0)],
+              dtype=[('a', '<i4'), ('f1', '<f8')])
+
+    Notes
+    -----
+    * Without a mask, the missing value will be filled with something,
+    * depending on what its corresponding type:
+            -1      for integers
+            -1.0    for floating point numbers
+            '-'     for characters
+            '-1'    for strings
+            True    for boolean values
+    * XXX: I just obtained these values empirically
     """
     if (len(seqarrays) == 1):
         seqarrays = seqarrays[0]
@@ -436,15 +455,16 @@ def drop_fields(base, drop_names, usemask=True, asrecarray=False):
 
     Examples
     --------
+    >>> from numpy.lib import recfunctions as rfn
     >>> a = np.array([(1, (2, 3.0)), (4, (5, 6.0))],
-                     dtype=[('a', int), ('b', [('ba', float), ('bb', int)])])
-    >>> drop_fields(a, 'a')
+    ...   dtype=[('a', int), ('b', [('ba', float), ('bb', int)])])
+    >>> rfn.drop_fields(a, 'a')
     array([((2.0, 3),), ((5.0, 6),)], 
           dtype=[('b', [('ba', '<f8'), ('bb', '<i4')])])
-    >>> drop_fields(a, 'ba')
+    >>> rfn.drop_fields(a, 'ba')
     array([(1, (3,)), (4, (6,))], 
           dtype=[('a', '<i4'), ('b', [('bb', '<i4')])])
-    >>> drop_fields(a, ['ba', 'bb'])
+    >>> rfn.drop_fields(a, ['ba', 'bb'])
     array([(1,), (4,)], 
           dtype=[('a', '<i4')])
     """
@@ -500,12 +520,12 @@ def rename_fields(base, namemapper):
 
     Examples
     --------
+    >>> from numpy.lib import recfunctions as rfn
     >>> a = np.array([(1, (2, [3.0, 30.])), (4, (5, [6.0, 60.]))],
-                      dtype=[('a', int),
-                             ('b', [('ba', float), ('bb', (float, 2))])])
-    >>> rename_fields(a, {'a':'A', 'bb':'BB'})
-    array([(1, (2.0, 3)), (4, (5.0, 6))], 
-          dtype=[('A', '<i4'), ('b', [('ba', '<f8'), ('BB', '<i4')])])
+    ...   dtype=[('a', int),('b', [('ba', float), ('bb', (float, 2))])])
+    >>> rfn.rename_fields(a, {'a':'A', 'bb':'BB'})
+    array([(1, (2.0, [3.0, 30.0])), (4, (5.0, [6.0, 60.0]))], 
+          dtype=[('A', '<i4'), ('b', [('ba', '<f8'), ('BB', '<f8', 2)])])
 
     """
     def _recursive_rename_fields(ndtype, namemapper):
@@ -650,19 +670,21 @@ def stack_arrays(arrays, defaults=None, usemask=True, asrecarray=False,
 
     Examples
     --------
+    >>> from numpy.lib import recfunctions as rfn
     >>> x = np.array([1, 2,])
-    >>> stack_arrays(x) is x
+    >>> rfn.stack_arrays(x) is x
     True
     >>> z = np.array([('A', 1), ('B', 2)], dtype=[('A', '|S3'), ('B', float)])
     >>> zz = np.array([('a', 10., 100.), ('b', 20., 200.), ('c', 30., 300.)],
-                      dtype=[('A', '|S3'), ('B', float), ('C', float)])
-    >>> test = stack_arrays((z,zz))
-    >>> masked_array(data = [('A', 1.0, --) ('B', 2.0, --) ('a', 10.0, 100.0)
-    ... ('b', 20.0, 200.0) ('c', 30.0, 300.0)],
-    ...       mask = [(False, False, True) (False, False, True) (False, False, False)
-    ... (False, False, False) (False, False, False)],
-    ...       fill_value=('N/A', 1e+20, 1e+20)
-    ...       dtype=[('A', '|S3'), ('B', '<f8'), ('C', '<f8')])
+    ...   dtype=[('A', '|S3'), ('B', float), ('C', float)])
+    >>> test = rfn.stack_arrays((z,zz))
+    >>> test
+    masked_array(data = [('A', 1.0, --) ('B', 2.0, --) ('a', 10.0, 100.0) ('b', 20.0, 200.0)
+     ('c', 30.0, 300.0)],
+                 mask = [(False, False, True) (False, False, True) (False, False, False)
+     (False, False, False) (False, False, False)],
+           fill_value = ('N/A', 1e+20, 1e+20),
+                dtype = [('A', '|S3'), ('B', '<f8'), ('C', '<f8')])
 
     """
     if isinstance(arrays, ndarray):
@@ -735,10 +757,12 @@ def find_duplicates(a, key=None, ignoremask=True, return_index=False):
 
     Examples
     --------
+    >>> from numpy.lib import recfunctions as rfn
     >>> ndtype = [('a', int)]
-    >>> a = ma.array([1, 1, 1, 2, 2, 3, 3], 
+    >>> a = np.ma.array([1, 1, 1, 2, 2, 3, 3], 
     ...         mask=[0, 0, 1, 0, 0, 0, 1]).view(ndtype)
-    >>> find_duplicates(a, ignoremask=True, return_index=True)
+    >>> rfn.find_duplicates(a, ignoremask=True, return_index=True)
+    ... # XXX: judging by the output, the ignoremask flag has no effect
     """
     a = np.asanyarray(a).ravel()
     # Get a dictionary of fields
diff --git a/numpy/lib/shape_base.py b/numpy/lib/shape_base.py
index f21786805..69fe98314 100644
--- a/numpy/lib/shape_base.py
+++ b/numpy/lib/shape_base.py
@@ -46,9 +46,9 @@ def apply_along_axis(func1d,axis,arr,*args):
     ...     return (a[0] + a[-1]) * 0.5
     >>> b = np.array([[1,2,3], [4,5,6], [7,8,9]])
     >>> np.apply_along_axis(my_func, 0, b)
-    array([4., 5., 6.])
+    array([ 4.,  5.,  6.])
     >>> np.apply_along_axis(my_func, 1, b)
-    array([2., 5., 8.])
+    array([ 2.,  5.,  8.])
 
     For a function that doesn't return a scalar, the number of dimensions in
     `outarr` is the same as `arr`.
@@ -729,7 +729,7 @@ def kron(a,b):
     >>> J1 = (0,) + J             # extend to ndim=4
     >>> S1 = (1,) + b.shape
     >>> K = tuple(np.array(I) * np.array(S1) + np.array(J1))
-    >>> C[K] == A[I]*B[J]
+    >>> c[K] == a[I]*b[J]
     True
 
     """
diff --git a/numpy/lib/tests/test_format.py b/numpy/lib/tests/test_format.py
index 35558400f..ec035ca28 100644
--- a/numpy/lib/tests/test_format.py
+++ b/numpy/lib/tests/test_format.py
@@ -108,7 +108,7 @@ Test the header writing.
 
     >>> for arr in basic_arrays + record_arrays:
     ...     f = StringIO()
-    ...     format.write_array_header_1_0(f, arr)
+    ...     format.write_array_header_1_0(f, arr)   # XXX: arr is not a dict, items gets called on it
     ...     print repr(f.getvalue())
     ...
     "F\x00{'descr': '|u1', 'fortran_order': False, 'shape': (0,)}              \n"
diff --git a/numpy/lib/twodim_base.py b/numpy/lib/twodim_base.py
index 0d53bbb68..40a5aec33 100644
--- a/numpy/lib/twodim_base.py
+++ b/numpy/lib/twodim_base.py
@@ -52,7 +52,7 @@ def fliplr(m):
            [ 3.,  0.,  0.]])
 
     >>> A = np.random.randn(2,3,5)
-    >>> np.all(numpy.fliplr(A)==A[:,::-1,...])
+    >>> np.all(np.fliplr(A)==A[:,::-1,...])
     True
 
     """
@@ -582,7 +582,7 @@ def histogram2d(x,y, bins=10, range=None, normed=False, weights=None):
     >>> x, y = np.random.randn(2, 100)
     >>> H, xedges, yedges = np.histogram2d(x, y, bins=(5, 8))
     >>> H.shape, xedges.shape, yedges.shape
-    ((5,8), (6,), (9,))
+    ((5, 8), (6,), (9,))
 
     We can now use the Matplotlib to visualize this 2-dimensional histogram:
 
diff --git a/numpy/lib/type_check.py b/numpy/lib/type_check.py
index f11672609..c0a5760a4 100644
--- a/numpy/lib/type_check.py
+++ b/numpy/lib/type_check.py
@@ -260,7 +260,7 @@ def iscomplexobj(x):
     False
     >>> np.iscomplexobj(1+0j)
     True
-    np.iscomplexobj([3, 1+0j, True])
+    >>> np.iscomplexobj([3, 1+0j, True])
     True
 
     """
@@ -345,6 +345,7 @@ def nan_to_num(x):
 
     Examples
     --------
+    >>> np.set_printoptions(precision=8)
     >>> x = np.array([np.inf, -np.inf, np.nan, -128, 128])
     >>> np.nan_to_num(x)
     array([  1.79769313e+308,  -1.79769313e+308,   0.00000000e+000,
diff --git a/numpy/lib/ufunclike.py b/numpy/lib/ufunclike.py
index 5e89b0930..bb8ee7808 100644
--- a/numpy/lib/ufunclike.py
+++ b/numpy/lib/ufunclike.py
@@ -99,9 +99,9 @@ def isposinf(x, y=None):
     >>> x = np.array([-np.inf, 0., np.inf])
     >>> y = np.array([2, 2, 2])
     >>> np.isposinf(x, y)
-    array([1, 0, 0])
+    array([0, 0, 1])
     >>> y
-    array([1, 0, 0])
+    array([0, 0, 1])
 
     """
     if y is None:
diff --git a/numpy/lib/utils.py b/numpy/lib/utils.py
index 43d6ede1f..3e73c2a0f 100644
--- a/numpy/lib/utils.py
+++ b/numpy/lib/utils.py
@@ -344,7 +344,7 @@ def who(vardict=None):
 
     >>> d = {'x': np.arange(2.0), 'y': np.arange(3.0), 'txt': 'Some str',
     ... 'idx':5}
-    >>> np.whos(d)
+    >>> np.who(d)
     Name            Shape            Bytes            Type
     ===========================================================
     y               3                24               float64
@@ -666,7 +666,7 @@ def source(object, output=sys.stdout):
 
     Examples
     --------
-    >>> np.source(np.interp)
+    >>> np.source(np.interp)                        #doctest: +SKIP
     In file: /usr/lib/python2.6/dist-packages/numpy/lib/function_base.py
     def interp(x, xp, fp, left=None, right=None):
         \"\"\".... (full docstring printed)\"\"\"
@@ -677,7 +677,7 @@ def source(object, output=sys.stdout):
 
     The source code is only returned for objects written in Python.
 
-    >>> np.source(np.array)
+    >>> np.source(np.array)                         #doctest: +SKIP
     Not available for this object.
 
     """
@@ -737,6 +737,8 @@ def lookfor(what, module=None, import_modules=True, regenerate=False,
     ------------------------------------------
     numpy.binary_repr
         Return the binary representation of the input number as a string.
+    numpy.core.setup_common.long_double_representation
+        Given a binary dump as given by GNU od -b, look for long double
     numpy.base_repr
         Return a string representation of a number in the given base system.
     ...
@@ -1066,7 +1068,7 @@ def safe_eval(source):
       ...
     SyntaxError: invalid syntax
 
-    >>> safe_eval('open("/home/user/.ssh/id_dsa").read()')
+    >>> np.safe_eval('open("/home/user/.ssh/id_dsa").read()')
     Traceback (most recent call last):
       ...
     SyntaxError: Unsupported source construct: compiler.ast.CallFunc