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authorPauli Virtanen <pav@iki.fi>2009-05-20 21:50:09 +0000
committerPauli Virtanen <pav@iki.fi>2009-05-20 21:50:09 +0000
commitd3133f1ed2d3c2e56853d14a5b3e5e1f2cff11e2 (patch)
tree7590c4f73a0a4e2009a8de860f49699e05bd5a94 /numpy/random/mtrand
parent260728f7a0010f717a246be1b199b93ea89c02fc (diff)
downloadnumpy-d3133f1ed2d3c2e56853d14a5b3e5e1f2cff11e2.tar.gz
Docstring fixes: make some examples to work properly
Diffstat (limited to 'numpy/random/mtrand')
-rw-r--r--numpy/random/mtrand/mtrand.pyx11
1 files changed, 6 insertions, 5 deletions
diff --git a/numpy/random/mtrand/mtrand.pyx b/numpy/random/mtrand/mtrand.pyx
index b3b676b9c..2bc2652fe 100644
--- a/numpy/random/mtrand/mtrand.pyx
+++ b/numpy/random/mtrand/mtrand.pyx
@@ -1279,8 +1279,8 @@ cdef class RandomState:
>>> import matplotlib.pyplot as plt
>>> import scipy.special as sps
>>> count, bins, ignored = plt.hist(s, 50, normed=True)
- >>> y = bins**(shape-1)*((exp(-bins/scale))/\\
- (sps.gamma(shape)*scale**shape))
+ >>> y = bins**(shape-1)*(exp(-bins/scale) /
+ ... (sps.gamma(shape)*scale**shape))
>>> plt.plot(bins, y, linewidth=2, color='r')
>>> plt.show()
@@ -1672,8 +1672,8 @@ cdef class RandomState:
>>> import matplotlib.pyplot as plt
>>> import scipy.special as sps
>>> count, bins, ignored = plt.hist(s, 50, normed=True)
- >>> x = arange(-pi, pi, 2*pi/50.)
- >>> y = -np.exp(kappa*np.cos(x-mu))/(2*pi*sps.jn(0,kappa))
+ >>> x = np.arange(-np.pi, np.pi, 2*np.pi/50.)
+ >>> y = -np.exp(kappa*np.cos(x-mu))/(2*np.pi*sps.jn(0,kappa))
>>> plt.plot(x, y/max(y), linewidth=2, color='r')
>>> plt.show()
@@ -1858,6 +1858,7 @@ cdef class RandomState:
the probability density function:
>>> import matplotlib.pyplot as plt
+ >>> x = np.arange(1,100.)/50.
>>> def weib(x,n,a):
... return (a / n) * (x / n)**(a - 1) * np.exp(-(x / n)**a)
@@ -2619,7 +2620,7 @@ cdef class RandomState:
>>> import scipy.special as sps
Truncate s values at 50 so plot is interesting
>>> count, bins, ignored = plt.hist(s[s<50], 50, normed=True)
- >>> x = arange(1., 50.)
+ >>> x = np.arange(1., 50.)
>>> y = x**(-a)/sps.zetac(a)
>>> plt.plot(x, y/max(y), linewidth=2, color='r')
>>> plt.show()