diff options
Diffstat (limited to 'numpy/random/mtrand/mtrand.pyx')
| -rw-r--r-- | numpy/random/mtrand/mtrand.pyx | 7 |
1 files changed, 0 insertions, 7 deletions
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') |