使用 NumPy 减少多维数组并在特定轴上乘以元素
要减少多维数组,请在 Python NumPy 中使用 **np.ufunc.reduce()** 方法。在这里,我们使用 **multiply.reduce()** 将其简化为元素的乘积。轴是使用“axis”参数设置的。执行缩减的轴或轴。
**numpy.ufunc** 具有在整个数组上逐元素操作的函数。ufunc是用 C(为了速度)编写的,并通过 NumPy 的 ufunc 功能链接到 Python。通用函数(或简称 ufunc)是在 ndarrays 上以逐元素方式操作的函数,支持数组广播、类型转换和几个其他标准功能。也就是说,ufunc 是一个“矢量化”的函数包装器,该函数采用固定数量的特定输入并产生固定数量的特定输出。
步骤
首先,导入所需的库 -
import numpy as np
创建一个多维数组 -
arr = np.arange(27).reshape((3,3,3))
显示数组 -
print("Array...", arr)
获取数组的类型 -
print("Our Array type...", arr.dtype)
获取数组的维度 -
print("Our Array Dimensions...",arr.ndim)
要减少多维数组,请在 Python NumPy 中使用 np.ufunc.reduce() 方法。在这里,我们使用 multiply.reduce() 将其简化为元素的乘积。轴是使用“axis”参数设置的。执行缩减的轴或轴 -
print("Result along specific axis (multiplication)...",np.multiply.reduce(arr, axis = 1))
示例
import numpy as np # The numpy.ufunc has functions that operate element by element on whole arrays. # ufuncs are written in C (for speed) and linked into Python with NumPy’s ufunc facility # Create a multi-dimensional array arr = np.arange(27).reshape((3,3,3)) # Display the array print("Array...", arr) # Get the type of the array print("Our Array type...", arr.dtype) # Get the dimensions of the Array print("Our Array Dimensions...",arr.ndim) # To reduce a multi-dimensional array, use the np.ufunc.reduce() method in Python Numpy # Here, we have used multiply.reduce() to reduce it to the multiplication of elements # The axis is set using the "axis" parameter # Axis or axes along which a reduction is performed print("Result along specific axis (multiplication)...",np.multiply.reduce(arr, axis = 1))
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输出
Array... [[[ 0 1 2] [ 3 4 5] [ 6 7 8]] [[ 9 10 11] [12 13 14] [15 16 17]] [[18 19 20] [21 22 23] [24 25 26]]] Our Array type... int64 Our Array Dimensions... 3 Result along specific axis (multiplication)... [[ 0 28 80] [ 1620 2080 2618] [ 9072 10450 11960]]
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