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-------
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out : ndarray
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The drawn samples, arranged according to `shape`. If the
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- shape given is (m,n,...), then the shape of `out` is is
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+ shape given is (m,n,...), then the shape of `out` is
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(m,n,...,N).
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In other words, each entry ``out[i,j,...,:]`` is an N-dimensional
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value drawn from the distribution.
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list of str
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This is not a real return value. It exists to test
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anonymous return values.
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+ no_description
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Other Parameters
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----------------
@@ -184,7 +185,7 @@ def test_other_parameters():
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def test_returns ():
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- assert_equal (len (doc ['Returns' ]), 2 )
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+ assert_equal (len (doc ['Returns' ]), 3 )
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arg , arg_type , desc = doc ['Returns' ][0 ]
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assert_equal (arg , 'out' )
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assert_equal (arg_type , 'ndarray' )
@@ -197,6 +198,11 @@ def test_returns():
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assert desc [0 ].startswith ('This is not a real' )
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assert desc [- 1 ].endswith ('anonymous return values.' )
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+ arg , arg_type , desc = doc ['Returns' ][2 ]
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+ assert_equal (arg , 'no_description' )
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+ assert_equal (arg_type , '' )
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+ assert not '' .join (desc ).strip ()
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+
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def test_yields ():
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section = doc_yields ['Yields' ]
@@ -365,14 +371,15 @@ def test_str():
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-------
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out : ndarray
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The drawn samples, arranged according to `shape`. If the
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- shape given is (m,n,...), then the shape of `out` is is
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+ shape given is (m,n,...), then the shape of `out` is
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(m,n,...,N).
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In other words, each entry ``out[i,j,...,:]`` is an N-dimensional
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value drawn from the distribution.
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list of str
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This is not a real return value. It exists to test
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anonymous return values.
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+ no_description
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Other Parameters
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----------------
@@ -496,7 +503,7 @@ def test_sphinx_str():
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**out** : ndarray
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The drawn samples, arranged according to `shape`. If the
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- shape given is (m,n,...), then the shape of `out` is is
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+ shape given is (m,n,...), then the shape of `out` is
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(m,n,...,N).
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In other words, each entry ``out[i,j,...,:]`` is an N-dimensional
@@ -506,6 +513,9 @@ def test_sphinx_str():
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This is not a real return value. It exists to test
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anonymous return values.
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+ no_description
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+ ..
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+
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:Other Parameters:
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**spam** : parrot
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