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-rw-r--r--numpy/core/function_base.py8
-rw-r--r--numpy/fft/pocketfft.py4
-rw-r--r--numpy/lib/function_base.py11
-rw-r--r--numpy/lib/twodim_base.py7
-rw-r--r--numpy/random/mtrand/mtrand.pyx7
5 files changed, 2 insertions, 35 deletions
diff --git a/numpy/core/function_base.py b/numpy/core/function_base.py
index 762328173..f8800b83e 100644
--- a/numpy/core/function_base.py
+++ b/numpy/core/function_base.py
@@ -110,9 +110,6 @@ def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None,
Graphical illustration:
- >>> import matplotlib
- >>> import matplotlib.pyplot
- >>> matplotlib.pyplot.switch_backend('agg')
>>> import matplotlib.pyplot as plt
>>> N = 8
>>> y = np.zeros(N)
@@ -263,9 +260,6 @@ def logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None,
Graphical illustration:
- >>> import matplotlib
- >>> import matplotlib.pyplot
- >>> matplotlib.pyplot.switch_backend('agg')
>>> import matplotlib.pyplot as plt
>>> N = 10
>>> x1 = np.logspace(0.1, 1, N, endpoint=True)
@@ -379,8 +373,6 @@ def geomspace(start, stop, num=50, endpoint=True, dtype=None, axis=0):
Graphical illustration of ``endpoint`` parameter:
- >>> import matplotlib
- >>> matplotlib.use('agg')
>>> import matplotlib.pyplot as plt
>>> N = 10
>>> y = np.zeros(N)
diff --git a/numpy/fft/pocketfft.py b/numpy/fft/pocketfft.py
index 794d13937..45dc162f6 100644
--- a/numpy/fft/pocketfft.py
+++ b/numpy/fft/pocketfft.py
@@ -163,8 +163,6 @@ def fft(a, n=None, axis=-1, norm=None):
in the real part and anti-symmetric in the imaginary part, as described in
the `numpy.fft` documentation:
- >>> import matplotlib
- >>> matplotlib.use('Agg')
>>> import matplotlib.pyplot as plt
>>> t = np.arange(256)
>>> sp = np.fft.fft(np.sin(t))
@@ -258,8 +256,6 @@ def ifft(a, n=None, axis=-1, norm=None):
Create and plot a band-limited signal with random phases:
- >>> import matplotlib
- >>> matplotlib.use('agg')
>>> import matplotlib.pyplot as plt
>>> t = np.arange(400)
>>> n = np.zeros((400,), dtype=complex)
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index 274f957db..cee7b3a62 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -2593,8 +2593,6 @@ def blackman(M):
Examples
--------
- >>> import matplotlib
- >>> matplotlib.use('agg')
>>> import matplotlib.pyplot as plt
>>> np.blackman(12)
array([-1.38777878e-17, 3.26064346e-02, 1.59903635e-01, # may vary
@@ -2811,9 +2809,6 @@ def hanning(M):
Plot the window and its frequency response:
- >>> import matplotlib
- >>> import matplotlib.pyplot
- >>> matplotlib.pyplot.switch_backend('agg')
>>> import matplotlib.pyplot as plt
>>> from numpy.fft import fft, fftshift
>>> window = np.hanning(51)
@@ -2914,9 +2909,6 @@ def hamming(M):
Plot the window and the frequency response:
- >>> import matplotlib
- >>> import matplotlib.pyplot
- >>> matplotlib.pyplot.switch_backend('agg')
>>> import matplotlib.pyplot as plt
>>> from numpy.fft import fft, fftshift
>>> window = np.hamming(51)
@@ -3192,8 +3184,6 @@ def kaiser(M, beta):
Examples
--------
- >>> import matplotlib
- >>> matplotlib.use('agg')
>>> import matplotlib.pyplot as plt
>>> np.kaiser(12, 14)
array([7.72686684e-06, 3.46009194e-03, 4.65200189e-02, # may vary
@@ -3288,7 +3278,6 @@ def sinc(x):
Examples
--------
- >>> import matplotlib
>>> import matplotlib.pyplot as plt
>>> x = np.linspace(-4, 4, 41)
>>> np.sinc(x)
diff --git a/numpy/lib/twodim_base.py b/numpy/lib/twodim_base.py
index 54d0240ef..e165c9b02 100644
--- a/numpy/lib/twodim_base.py
+++ b/numpy/lib/twodim_base.py
@@ -644,10 +644,7 @@ def histogram2d(x, y, bins=10, range=None, normed=None, weights=None,
Examples
--------
- >>> import matplotlib
- >>> import matplotlib.pyplot
- >>> matplotlib.pyplot.switch_backend('agg')
- >>> import matplotlib as mpl
+ >>> from matplotlib.image import NonUniformImage
>>> import matplotlib.pyplot as plt
Construct a 2-D histogram with variable bin width. First define the bin
@@ -684,7 +681,7 @@ def histogram2d(x, y, bins=10, range=None, normed=None, weights=None,
>>> ax = fig.add_subplot(133, title='NonUniformImage: interpolated',
... aspect='equal', xlim=xedges[[0, -1]], ylim=yedges[[0, -1]])
- >>> im = mpl.image.NonUniformImage(ax, interpolation='bilinear')
+ >>> im = NonUniformImage(ax, interpolation='bilinear')
>>> xcenters = (xedges[:-1] + xedges[1:]) / 2
>>> ycenters = (yedges[:-1] + yedges[1:]) / 2
>>> im.set_data(xcenters, ycenters, H)
diff --git a/numpy/random/mtrand/mtrand.pyx b/numpy/random/mtrand/mtrand.pyx
index 2a6daa88c..134bc2e09 100644
--- a/numpy/random/mtrand/mtrand.pyx
+++ b/numpy/random/mtrand/mtrand.pyx
@@ -2168,7 +2168,6 @@ cdef class RandomState:
>>> NF = np.histogram(nc_vals, bins=50, density=True)
>>> c_vals = np.random.f(dfnum, dfden, 1000000)
>>> F = np.histogram(c_vals, bins=50, density=True)
- >>> import matplotlib
>>> import matplotlib.pyplot as plt
>>> plt.plot(F[1][1:], F[0])
>>> plt.plot(NF[1][1:], NF[0])
@@ -2447,7 +2446,6 @@ cdef class RandomState:
--------
Draw samples and plot the distribution:
- >>> import matplotlib
>>> import matplotlib.pyplot as plt
>>> s = np.random.standard_cauchy(1000000)
>>> s = s[(s>-25) & (s<25)] # truncate distribution so it plots well
@@ -3285,7 +3283,6 @@ cdef class RandomState:
>>> loc, scale = 10, 1
>>> s = np.random.logistic(loc, scale, 10000)
- >>> import matplotlib
>>> import matplotlib.pyplot as plt
>>> count, bins, ignored = plt.hist(s, bins=50)
@@ -3487,7 +3484,6 @@ cdef class RandomState:
--------
Draw values from the distribution and plot the histogram
- >>> import matplotlib
>>> from matplotlib.pyplot import hist
>>> values = hist(np.random.rayleigh(3, 100000), bins=200, density=True)
@@ -4243,7 +4239,6 @@ cdef class RandomState:
>>> ngood, nbad, nsamp = 100, 2, 10
# number of good, number of bad, and number of samples
>>> s = np.random.hypergeometric(ngood, nbad, nsamp, 1000)
- >>> import matplotlib
>>> from matplotlib.pyplot import hist
>>> hist(s)
# note that it is very unlikely to grab both bad items
@@ -4354,7 +4349,6 @@ cdef class RandomState:
>>> a = .6
>>> s = np.random.logseries(a, 10000)
- >>> import matplotlib
>>> import matplotlib.pyplot as plt
>>> count, bins, ignored = plt.hist(s)
@@ -4736,7 +4730,6 @@ cdef class RandomState:
>>> s = np.random.dirichlet((10, 5, 3), 20).transpose()
- >>> import matplotlib
>>> import matplotlib.pyplot as plt
>>> plt.barh(range(20), s[0])
>>> plt.barh(range(20), s[1], left=s[0], color='g')
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