返回 NumPy 中两个带掩码的一维数组的内积


要返回两个带掩码数组的内积,请在 Python NumPy 中使用 **ma.inner()** 方法。对于一维数组,这是向量的普通内积(不进行复共轭);在更高维度上,这是对最后一个轴的求和积。

out 参数表明,如果两个数组都是标量或都是一维数组,则返回标量;否则返回数组。out.shape = (*a.shape[:-1], *b.shape[:-1])。

带掩码数组是标准 numpy.ndarray 和掩码的组合。掩码要么是 nomask(表示关联数组的任何值均有效),要么是布尔值数组,用于确定关联数组的每个元素的值是否有效。

步骤

首先,导入所需的库:

import numpy as np import numpy.ma as ma

使用 numpy.array() 方法创建数组 1,其中包含整数元素:

arr1 = np.array([5, 10, 15, 20, 25]) print("Array1...", arr1) print("Array type...", arr1.dtype)

创建带掩码的数组 1:

arr1 = ma.array(arr1)

掩码数组 1:

arr1[0] = ma.masked arr1[1] = ma.masked

显示带掩码的数组 1:

print("Masked Array1...",arr1)

使用 numpy.array() 方法创建另一个数组 2,其中包含整数元素:

arr2 = np.array([7, 14, 21, 28, 35]) print("Array2...", arr2) print("Array type...", arr2.dtype)

创建一个带掩码的数组 2:

arr2 = ma.array(arr2)

掩码数组 2:

arr2[3] = ma.masked arr2[4] = ma.masked

显示带掩码的数组 2:

print("Masked Array2...",arr2)

要返回两个带掩码数组的内积,请在 Python NumPy 中使用 ma.inner() 方法。对于一维数组,这是向量的普通内积(不进行复共轭);在更高维度上,这是对最后一个轴的求和积:

print("Result of inner product...",np.ma.inner(arr1, arr2))

示例

Open Compiler
# Python ma.MaskedArray - Return the inner product of two masked One- Dimensional arrays import numpy as np import numpy.ma as ma # Array 1 # Creating a 1D array with int elements using the numpy.array() method arr1 = np.array([5, 10, 15, 20, 25]) print("Array1...", arr1) print("Array type...", arr1.dtype) # Get the dimensions of the Array print("Array Dimensions...",arr1.ndim) # Get the shape of the Array print("Our Array Shape...",arr1.shape) # Get the number of elements of the Array print("Elements in the Array...",arr1.size) # Create a masked array arr1 = ma.array(arr1) # Mask Array1 arr1[0] = ma.masked arr1[1] = ma.masked # Display Masked Array 1 print("Masked Array1...",arr1) # Array 2 # Creating another 1D array with int elements using the numpy.array() method arr2 = np.array([7, 14, 21, 28, 35]) print("Array2...", arr2) print("Array type...", arr2.dtype) # Get the dimensions of the Array print("Array Dimensions...",arr2.ndim) # Get the shape of the Array print("Our Array Shape...",arr2.shape) # Get the number of elements of the Array print("Elements in the Array...",arr2.size) # Create a masked array arr2 = ma.array(arr2) # Mask Array2 arr2[3] = ma.masked arr2[4] = ma.masked # Display Masked Array 2 print("Masked Array2...",arr2) # To return the inner product of two masked arrays, use the ma.inner() method in Python Numpy # Ordinary inner product of vectors for 1-D arrays (without complex conjugation), in higher dimensions a sum product over the last axes. print("Result of inner product...",np.ma.inner(arr1, arr2))

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输出

Array1...
[ 5 10 15 20 25]

Array type...
int64

Array Dimensions...
1

Our Array Shape...
(5,)

Elements in the Array...
5

Masked Array1...
[-- -- 15 20 25]

Array2...
[ 7 14 21 28 35]

Array type...
int64

Array Dimensions...
1

Our Array Shape...
(5,)

Elements in the Array...
5

Masked Array2...
[7 14 21 -- --]

Result of inner product...
315

更新于:2022年2月3日

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