返回 NumPy 中两个掩码数组的内积

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

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])。

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都不无效，要么是布尔数组，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

创建数组 1，一个使用 numpy.arange() 方法创建的包含整数元素的 3x3 数组 -

arr1 = np.arange(9).reshape((3,3))
print("Array1...
", arr1)
print("
Array type...
", arr1.dtype)

创建掩码数组 1 -

arr1 = ma.array(arr1)

掩码数组 1 -

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

显示掩码数组 1 -

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

创建数组 2，一个使用 numpy.arange() 方法创建的包含整数元素的 3x3 数组 -

arr2 = np.arange(9).reshape((3,3))
print("
Array2...
", arr2)
print("
Array type...
", arr2.dtype)

创建掩码数组 2 -

arr2 = ma.array(arr2)

掩码数组 2 -

arr2[2, 1] = ma.masked
arr2[2, 2] = ma.masked

显示掩码数组 2 -

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

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

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

示例

# Python ma.MaskedArray - Return the inner product of two masked arrays

import numpy as np
import numpy.ma as ma

# Array 1
# Creating a 3x3 array with int elements using the numpy.arange() method
arr1 = np.arange(9).reshape((3,3))
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, 1] = ma.masked
arr1[1, 1] = ma.masked

# Display Masked Array 1
print("
Masked Array1...
",arr1)

# Array 2
# Creating another 3x3 array with int elements using the numpy.arange() method
arr2 = np.arange(9).reshape((3,3))
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[2, 1] = ma.masked
arr2[2, 2] = 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))

输出

Array1...
[[0 1 2]
[3 4 5]
[6 7 8]]

Array type...
int64

Array Dimensions...
2

Our Array Shape...
(3, 3)

Elements in the Array...
9

Masked Array1...
[[0 -- 2]
[3 -- 5]
[6 7 8]]

Array2...
[[0 1 2]
[3 4 5]
[6 7 8]]

Array type...
int64

Array Dimensions...
2

Our Array Shape...
(3, 3)

Elements in the Array...
9

Masked Array2...
[[0 1 2]
[3 4 5]
[6 -- --]]

Result of inner product...
[[ 4 10 0]
[10 34 18]
[23 86 36]]

更新于: 2022年2月3日

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