在NumPy中沿轴1连接一系列掩码数组

要在特定轴上连接一系列掩码数组，请使用Python NumPy中的**ma.stack()**方法。“**axis**”参数用于设置轴。axis参数指定结果维度中新轴的索引。例如，如果axis=0，它将是第一维；如果axis=-1，它将是最后一维。

如果提供out参数，则将其作为目标位置放置结果。形状必须正确，与未指定out参数时stack返回的形状匹配。

该函数返回的堆叠数组比输入数组多一个维度。它同时应用于_data和_mask（如果有）。

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，另一个使用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)

要在特定轴上连接一系列掩码数组，请使用Python NumPy中的ma.stack()方法。“axis”参数用于设置轴：

print("
Result of joining arrays...
",ma.stack((arr1, arr2), axis = 1))

示例

# Python ma.MaskedArray - Join a sequence of masked arrays along axis 1

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 join a sequence of masked arrays along specific axis, use the ma.stack() method in Python Numpy
# The axis is set using the "axis" parameter
print("
Result of joining arrays...
",ma.stack((arr1, arr2), axis = 1))

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 joining arrays...
[[[0 -- 2]
[0 1 2]]
[[3 -- 5]
[3 4 5]]
[[6 7 8]
[6 -- --]]]

更新于：2022年2月3日

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