从 numpy 数组创建稀疏矩阵 [英] Creating a sparse matrix from numpy array

问题描述

我需要使用 numpy 数组中的值创建一个矩阵.这些值应根据索引数组分布在矩阵线上.

像这样:

<预><代码>>>>价值观数组([ 0.73620381, 0.61843002, 0.33604769, 0.72344274, 0.48943796])>>>工业数组([0, 1, 2, 3, 2])>>>m = np.zeros((4, 5))>>>对于 enumerate(zip(inds, values)) 中的 i, (index, value):m[index, i] = 值>>>米数组([[ 0.73620381, 0. , 0. , 0. , 0. ],[ 0. , 0.61843002, 0. , 0. , 0. ],[ 0. , 0. , 0.33604769, 0. , 0.48943796],[ 0. , 0. , 0. , 0.72344274, 0. ]])

我想知道是否有一种矢量化的方式来做到这一点，即没有循环.有什么建议吗?

解决方案

这里是如何使用 花式索引:

<预><代码>>>>价值观数组([ 0.73620381, 0.61843002, 0.33604769, 0.72344274, 0.48943796])>>>工业数组([0, 1, 2, 3, 2])>>>mshape = (4,5)>>>m = np.zeros(mshape)>>>m[inds,np.arange(mshape[1])] = 值>>>米数组([[ 0.73620381, 0. , 0. , 0. , 0. ],[ 0. , 0.61843002, 0. , 0. , 0. ],[ 0. , 0. , 0.33604769, 0. , 0.48943796],[ 0. , 0. , 0. , 0.72344274, 0. ]])

I need to create a matrix with values from a numpy array. The values should be distributed over the matrix lines according to an array of indices.

Like this:

>>> values
array([ 0.73620381,  0.61843002,  0.33604769,  0.72344274,  0.48943796])
>>> inds
array([0, 1, 2, 3, 2])
>>> m = np.zeros((4, 5))
>>> for i, (index, value) in enumerate(zip(inds, values)):
        m[index, i] = value
>>> m
array([[ 0.73620381,  0.        ,  0.        ,  0.        ,  0.        ],
       [ 0.        ,  0.61843002,  0.        ,  0.        ,  0.        ],
       [ 0.        ,  0.        ,  0.33604769,  0.        ,  0.48943796],
       [ 0.        ,  0.        ,  0.        ,  0.72344274,  0.        ]])

I'd like to know if there is a vectorized way to do it, i.e., without a loop. Any suggestions?

解决方案

Here's how you could do it with fancy indexing:

>>> values
array([ 0.73620381,  0.61843002,  0.33604769,  0.72344274,  0.48943796])
>>> inds
array([0, 1, 2, 3, 2])
>>> mshape = (4,5)
>>> m = np.zeros(mshape)
>>> m[inds,np.arange(mshape[1])] = values
>>> m
array([[ 0.73620381,  0.        ,  0.        ,  0.        ,  0.        ],
       [ 0.        ,  0.61843002,  0.        ,  0.        ,  0.        ],
       [ 0.        ,  0.        ,  0.33604769,  0.        ,  0.48943796],
       [ 0.        ,  0.        ,  0.        ,  0.72344274,  0.        ]])

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