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-rw-r--r--numpy/doc/EXAMPLE_DOCSTRING.txt7
1 files changed, 4 insertions, 3 deletions
diff --git a/numpy/doc/EXAMPLE_DOCSTRING.txt b/numpy/doc/EXAMPLE_DOCSTRING.txt
index 2872de113..ee1326474 100644
--- a/numpy/doc/EXAMPLE_DOCSTRING.txt
+++ b/numpy/doc/EXAMPLE_DOCSTRING.txt
@@ -72,9 +72,10 @@ generated data-points:
>>> mean = [0,0]
>>> cov = [[1,0],[0,100]] # diagonal covariance, points lie on x or y-axis
+>>> x,y = np.random.multivariate_normal(mean,cov,5000).T
->>> x,y = numpy.multivariate_normal(mean,cov,5000).T
->>> pyplot.plot(x,y,'x'); pyplot.axis('equal'); pyplot.show()
+>>> import matplotlib.pyplot as plt
+>>> plt.plot(x,y,'x'); plt.axis('equal'); pyplot.show()
Note that the covariance matrix must be non-negative definite.
@@ -89,7 +90,7 @@ Examples
--------
>>> mean = (1,2)
>>> cov = [[1,0],[1,0]]
->>> x = multivariate_normal(mean,cov,(3,3))
+>>> x = np.random.multivariate_normal(mean,cov,(3,3))
>>> x.shape
(3, 3, 2)