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Python scipy.repeat方法代码示例

本文整理汇总了Python中scipy.repeat方法的典型用法代码示例。如果您正苦于以下问题:Python scipy.repeat方法的具体用法?Python scipy.repeat怎么用?Python scipy.repeat使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在scipy的用法示例。


在下文中一共展示了scipy.repeat方法的3个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: Euclidean

# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import repeat [as 别名]
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 
开发者ID:hdidx,项目名称:hdidx,代码行数:21,代码来源:distance.py

示例2: Euclidean_DML

# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import repeat [as 别名]
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 
开发者ID:hdidx,项目名称:hdidx,代码行数:10,代码来源:distance.py

示例3: __quadratic_forms_matrix_euclidean

# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import repeat [as 别名]
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 #
# //////////////// # 
开发者ID:doublechenching,项目名称:brats_segmentation-pytorch,代码行数:30,代码来源:histogram.py


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