努比。在Python中将_应用于_轴（）-yiteyi-C++库

这个 努比。将_应用于_轴（） 在阵列中的多个轴上重复应用函数。

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语法：

numpy.apply_over_axes(func, array, axes)

参数：

1d_func  : the required function to perform over 1D array. It can only be applied in          1D slices of input array and that too along a particular axis. axis     : required axis along which we want input array to be slicedarray    : Input array to work on *args    : Additional arguments to 1D_function **kwargs : Additional arguments to 1D_function

返回：

The output array. Shape of the output array can be different depending on whether func changes the shape of its output with respect to its input.

代码1：

python

                         # Python Program illustrating                       
                         # apply_over_axis() in NumPy                       
           
                         import                                     numpy as geek                       
           
                         # Using a 3D array                       
                         geek_array                                     =                                     geek.arange(                                     16                                     ).reshape(                                     2                                     ,                                     2                                     ,                                     4                                     )                       
                         print                                     (                                     "geek array  :"                                     , geek_array)                       
           
                         # Applying pre-defined sum function over the axis of 3D array                       
                         print                                     (                                     "func sum :  "                                     , geek.apply_over_axes(geek.                                     sum                                     , geek_array, [                                     1                                     ,                                     1                                     ,                                     0                                     ]))                       
           
                         # Applying pre-defined min function over the axis of 3D array                       
                         print                                     (                                     "func min :  "                                     , geek.apply_over_axes(geek.                                     min                                     , geek_array, [                                     1                                     ,                                     1                                     ,                                     0                                     ]))                       

输出：

geek array  : [[[ 0  1  2  3]  [ 4  5  6  7]] [[ 8  9 10 11]  [12 13 14 15]]]func sum :   [[[24 28 32 36]]]func min :   [[[0 1 2 3]]]

代码2：

python

                         # Python Program illustrating                       
                         # apply_over_axis() in NumPy                       
           
                         import                                     numpy as geek                       
           
                         # Using a 2D array                       
                         geek_array                                     =                                     geek.arange(                                     16                                     ).reshape(                                     4                                     ,                                     4                                     )                       
                         print                                     (                                     "geek array  :"                                     , geek_array)                       
           
                         """                       
                                                 ->[[ 0  1  2  3]    min : 0     max : 3    sum =  0 + 1 + 2 + 3                       
                                                 -> [ 4  5  6  7]    min : 4     max : 7    sum =  4 + 5 + 6 + 7                       
                                                 -> [ 8  9 10 11]    min : 8     max : 11   sum =  8 + 9 + 10 + 11                       
                                                 -> [12 13 14 15]]   min : 12    max : 15   sum =  12 + 13 + 14 + 15                       
           
                         """                       
           
                         # Applying pre-defined min function over the axis of 2D array                       
                         print                                     (                                     "Applying func max :  "                                     , geek.apply_over_axes(geek.                                     max                                     , geek_array, [                                     1                                     ,                                     -                                     1                                     ]))                       
           
                         # Applying pre-defined min function over the axis of 2D array                       
                         print                                     (                                     "Applying func min :  "                                     , geek.apply_over_axes(geek.                                     min                                     , geek_array, [                                     1                                     ,                                     -                                     1                                     ]))                       
           
                         # Applying pre-defined sum function over the axis of 2D array                       
                         print                                     (                                     "Applying func sum :  "                                     , geek.apply_over_axes(geek.                                     sum                                     , geek_array, [                                     1                                     ,                                     -                                     1                                     ]))                       

输出：

geek array  : [[ 0  1  2  3] [ 4  5  6  7] [ 8  9 10 11] [12 13 14 15]]Applying func max :   [[ 3] [ 7] [11] [15]]Applying func min :   [[ 0] [ 4] [ 8] [12]]Applying func sum :   [[ 6] [22] [38] [54]]

代码3：相当于代码2，不使用numpy。将_应用于_轴（）

python

                         # Python Program illustrating                       
                         # equivalent to apply_over_axis()                       
           
                         import                                     numpy as geek                       
           
                         # Using a 3D array                       
                         geek_array                                     =                                     geek.arange(                                     16                                     ).reshape(                                     2                                     ,                                     2                                     ,                                     4                                     )                       
                         print                                     (                                     "geek array  :"                                     , geek_array)                       
           
                         # returning sum of all elements as per the axis                       
                         print                                     (                                     "func : "                                     , geek.                                     sum                                     (geek_array, axis                                     =                                     (                                     1                                     ,                                     0                                     ,                                     2                                     ), keepdims                                     =                                     True                                     ))                       

输出：

geek array  : [[[ 0  1  2  3]  [ 4  5  6  7]] [[ 8  9 10 11]  [12 13 14 15]]]func :  [[[120]]]

参考资料： https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.apply_over_axes.html

注：这些代码不会在online-ID上运行。请在您的系统上运行它们以探索工作环境。

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