Python scipy.repeat() Examples

The following are 3 code examples of scipy.repeat(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module scipy , or try the search function .
Example #1
Source File: distance.py    From hdidx with MIT License 6 votes vote down vote up 
def Euclidean(feat, query=None,
              is_sparse=False, is_trans=False):
    """ Euclidean distance.
    """
    if query is None:
        (N, D) = feat.shape
        dotprod = feat.dot(feat.T)
        featl2norm = sp.repeat(dotprod.diagonal().reshape(1, -1), N, 0)
        qryl2norm = featl2norm.T
    else:
        (nQ, D) = query.shape
        (N, D) = feat.shape
        dotprod = query.dot(feat.T)
        qryl2norm = \
            sp.repeat(np.multiply(query, query).sum(1).reshape(-1, 1), N,  1)
        featl2norm = \
            sp.repeat(np.multiply(feat, feat).sum(1).reshape(1, -1), nQ, 0)

    return qryl2norm + featl2norm - 2 * dotprod
Example #2
Source File: distance.py    From hdidx with MIT License 5 votes vote down vote up 
def Euclidean_DML(feat, M, query=None,
                  is_sparse=False, is_trans=False):
    """ Euclidean distance with DML.
    """
    (N, D) = feat.shape
    dotprod = feat.dot(M).dot(feat.T)
    l2norm = sp.repeat(dotprod.diagonal().reshape(1, -1), N, 0)
    return l2norm + l2norm.T - 2 * dotprod
Example #3
Source File: histogram.py    From brats_segmentation-pytorch with MIT License 5 votes vote down vote up 
def __quadratic_forms_matrix_euclidean(h1, h2):
    r"""
    Compute the bin-similarity matrix for the quadratic form distance measure.
    The matric :math:`A` for two histograms :math:`H` and :math:`H'` of size :math:`m` and
    :math:`n` respectively is defined as
    
    .. math::
    
        A_{m,n} = 1 - \frac{d_2(H_m, {H'}_n)}{d_{max}}
    
    with
    
    .. math::
    
       d_{max} = \max_{m,n}d_2(H_m, {H'}_n)
    
    See also
    --------
    quadratic_forms
    """
    A = scipy.repeat(h2[:,scipy.newaxis], h1.size, 1) # repeat second array to form a matrix
    A = scipy.absolute(A - h1) # euclidean distances
    return 1 - (A / float(A.max()))


# //////////////// #
# Helper functions #
# //////////////// #