返回 NumPy 中兩個掩碼的三維陣列的內積

要返回兩個掩碼陣列的內積，請在 Python NumPy 中使用 **ma.inner()** 方法。out 引數建議，如果兩個陣列都是標量或都是一維陣列，則返回標量；否則返回陣列。out.shape = (*a.shape[:-1], *b.shape[:-1])。

掩碼陣列是標準 numpy.ndarray 和掩碼的組合。掩碼要麼是 nomask，表示關聯陣列的任何值均無效，要麼是布林值陣列，用於確定關聯陣列的每個元素的值是否有效。

步驟

首先，匯入所需的庫 -

import numpy as np
import numpy.ma as ma

使用 numpy.arange() 方法建立陣列 1，其中包含 int 元素 -

arr1 = np.arange(24).reshape((2,3,4))
print("Array1...
", arr1)
print("
Array type...
", arr1.dtype)

掩碼陣列 1 -

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

顯示掩碼陣列 1 -

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

使用 numpy.arange() 方法建立陣列 2，其中包含 int 元素 -

arr2 = np.arange(24).reshape((2,3,4))
print("
Array2...
", arr2)
print("
Array type...
", arr2.dtype)

建立另一個掩碼陣列 2 -

arr2 = ma.array(arr2)

掩碼陣列 2 -

arr2[0, 1, 2] = ma.masked
arr2[1, 2, 2] = ma.masked

顯示掩碼陣列 2 -

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

要返回兩個掩碼陣列的內積，請在 Python NumPy 中使用 ma.inner() 方法 -

print("
Result of inner product (3D arrays)...
",np.ma.inner(arr1, arr2))

示例

import numpy as np
import numpy.ma as ma

# Array 1
# Creating a 3D array with int elements using the numpy.arange() method
arr1 = np.arange(24).reshape((2,3,4))
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, 0, 1] = ma.masked

# Display Masked Array 1
print("
Masked Array1...
",arr1)
# Array 2
# Creating another 3D array with int elements using the numpy.arange() method
arr2 = np.arange(24).reshape((2,3,4))
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[0, 1, 2] = ma.masked
arr2[1, 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
print("
Result of inner product (3D arrays)...
",np.ma.inner(arr1,
arr2))

輸出

Array1...
[[[ 0 1 2 3]
[ 4 5 6 7]
[ 8 9 10 11]]

[[12 13 14 15]
[16 17 18 19]
[20 21 22 23]]]

Array type...
int64

Array Dimensions...
3

Our Array Shape...
(2, 3, 4)

Elements in the Array...
24

Masked Array1...
[[[0 -- 2 3]
[4 5 6 7]
[8 9 10 11]]

[[12 13 14 15]
[16 17 18 19]
[20 21 22 23]]]

Array2...
[[[ 0 1 2 3]
[ 4 5 6 7]
[ 8 9 10 11]]

[[12 13 14 15]
[16 17 18 19]
[20 21 22 23]]]

Array type...
int64

Array Dimensions...
3

Our Array Shape...
(2, 3, 4)

Elements in the Array...
24

Masked Array2...
[[[0 1 2 3]
[4 5 -- 7]
[8 9 10 11]]

[[12 13 14 15]
[16 17 18 19]
[20 21 -- 23]]]

Result of inner product (3D arrays)...
[[[[ 13 21 53]
[ 73 93 69]]

[[ 38 90 214]
[ 302 390 346]]

[[ 62 154 366]
[ 518 670 602]]]


[[[ 86 218 518]
[ 734 950 858]]

[[ 110 282 670]
[ 950 1230 1114]]

[[ 134 346 822]
[1166 1510 1370]]]]

AmitDiwan

更新於: 2022 年 2 月 5 日

121 次檢視

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