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Return a random matrix with data from the "standard normal" distribution.

`randn` generates a matrix filled with random floats sampled from a
univariate "normal" (Gaussian) distribution of mean 0 and variance 1.

Parameters
----------
\*args : Arguments
    Shape of the output.
    If given as N integers, each integer specifies the size of one(more...)

        def randn(*args):
    """
    Return a random matrix with data from the "standard normal" distribution.

    `randn` generates a matrix filled with random floats sampled from a
    univariate "normal" (Gaussian) distribution of mean 0 and variance 1.

    Parameters
    ----------
    \\*args : Arguments
        Shape of the output.
        If given as N integers, each integer specifies the size of one
        dimension. If given as a tuple, this tuple gives the complete shape.

    Returns
    -------
    Z : matrix of floats
        A matrix of floating-point samples drawn from the standard normal
        distribution.

    See Also
    --------
    rand, random.randn

    Notes
    -----
    For random samples from :math:`N(\\mu, \\sigma^2)`, use:

    ``sigma * np.matlib.randn(...) + mu``

    Examples
    --------
    >>> import numpy.matlib
    >>> np.matlib.randn(1)
    matrix([[-0.09542833]])                                 #random
    >>> np.matlib.randn(1, 2, 3)
    matrix([[ 0.16198284,  0.0194571 ,  0.18312985],
            [-0.7509172 ,  1.61055   ,  0.45298599]])       #random

    Two-by-four matrix of samples from :math:`N(3, 6.25)`:

    >>> 2.5 * np.matlib.randn((2, 4)) + 3
    matrix([[ 4.74085004,  8.89381862,  4.09042411,  4.83721922],
            [ 7.52373709,  5.07933944, -2.64043543,  0.45610557]])  #random

    """
    if isinstance(args[0], tuple):
        args = args[0]
    return asmatrix(np.random.randn(*args))
        


src/n/u/nupic-linux64-HEAD/lib64/python2.6/site-packages/numpy/tests/test_matlib.py   nupic-linux64(Download)
def test_randn():
    x = np.matlib.randn(3)
    # check matrix type, array would have shape (3,)
    assert_(x.ndim == 2)
 

src/m/i/MissionPlanner-HEAD/Lib/site-packages/numpy/tests/test_matlib.py   MissionPlanner(Download)
def test_randn():
    x = np.matlib.randn(3)
    # check matrix type, array would have shape (3,)
    assert_(x.ndim == 2)
 

src/n/u/numpy-1.8.1/numpy/tests/test_matlib.py   numpy(Download)
def test_randn():
    x = np.matlib.randn(3)
    # check matrix type, array would have shape (3,)
    assert_(x.ndim == 2)