返回一个掩码数组，包含相同的数据，但形状在NumPy中被视为行主序

要返回一个包含相同数据但具有新形状的掩码数组，请在NumPy中使用**ma.MaskedArray.reshape()**方法。赋予数组一个新形状而不改变其数据。“**order**”参数设置顺序。“C”顺序决定数组数据是否应按C语言(行主序)的方式查看。

新形状应该与原始形状兼容。如果提供一个整数，则结果将是一个具有该长度的一维数组。

order参数决定数组数据是按C语言(行主序)还是FORTRAN(列主序)顺序查看。返回一个包含相同数据但具有新形状的掩码数组。结果是对原始数组的视图；如果无法实现，则会引发ValueError。

步骤

首先，导入所需的库：

import numpy as np
import numpy.ma as ma

使用numpy.array()方法创建一个包含整数元素的数组：

arr = np.array([[49, 85, 45], [67, 33, 59]])
print("Array...
", arr)
print("
Array type...
", arr.dtype)

获取数组的维度：

print("Array Dimensions...
",arr.ndim)

创建一个掩码数组，并将其中一些标记为无效：

maskArr = ma.masked_array(arr, mask =[[0, 0, 1], [ 0, 1, 0]])
print("
Our Masked Array
", maskArr)
print("
Our Masked Array type...
", maskArr.dtype)

获取掩码数组的维度：

print("
Our Masked Array Dimensions...
",maskArr.ndim)

获取掩码数组的形状：

print("
Our Masked Array Shape...
",maskArr.shape)

获取掩码数组的元素个数：

print("
Elements in the Masked Array...
",maskArr.size)

要返回一个包含相同数据但具有新形状的掩码数组，请使用ma.MaskedArray.reshape()。顺序由“order”参数设置。“C”顺序决定数组数据是否应按C语言(行主序)的方式查看：

print("
Result...
",maskArr.reshape((6,1),order='C'))

示例

# Python ma.MaskedArray - Return a masked array containing the same data but with a new shape
# viewed as row-major order

import numpy as np
import numpy.ma as ma

# Create an array with int elements using the numpy.array() method
arr = np.array([[78, 85, 51], [56, 33, 97]])
print("Array...
", arr)
print("
Array type...
", arr.dtype)

# Get the dimensions of the Array
print("
Array Dimensions...
",arr.ndim)

# Create a masked array and mask some of them as invalid

# The masked array is 1x6
maskArr = ma.masked_array(arr, mask =[[0, 1, 0, 0, 0, 1]])
print("
Our Masked Array
", maskArr)
print("
Our Masked Array type...
", maskArr.dtype)

# Get the dimensions of the Masked Array
print("
Our Masked Array Dimensions...
",maskArr.ndim)

# Get the shape of the Masked Array
print("
Our Masked Array Shape...
",maskArr.shape)

# Get the number of elements of the Masked Array
print("
Elements in the Masked Array...
",maskArr.size)

# To return a masked array containing the same data, but with a new shape, use the ma.MaskedArray.reshape() method in Numpy
# Give a new shape to the array without changing its data
# The new shape of the masked array is set to 6x1 as a parameter
# The new shape should be compatible with the original shape.
# If an integer is supplied, then the result will be a 1-D array of that length
# The order is set using the "order" parameter
# The 'C' order determines whether the array data should be viewed as in C (row-major)
print("
Result...
",maskArr.reshape((6,1),order='C'))

输出

Array...
[[78 85 51]
[56 33 97]]

Array type...
int64

Array Dimensions...
2

Our Masked Array
[[78 -- 51]
[56 33 --]]

Our Masked Array type...
int64

Our Masked Array Dimensions...
2

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

Elements in the Masked Array...
6

Result...
[[78]
[--]
[51]
[56]
[33]
[--]]

更新于：2022年2月4日

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