在NumPy中返回具有转置轴的掩码数组视图
要返回具有转置轴的数组视图,请在NumPy中使用**ma.MaskedArray.transpose()**方法。对于一维数组,这没有效果,因为转置向量只是相同的向量。要将一维数组转换为二维列向量,必须添加一个额外的维度。np.atleast2d(a).T可以实现此目的,a[:, np.newaxis]也可以。对于二维数组,这是标准的矩阵转置。
轴可以是:
None或无参数 - 反转轴的顺序。
整数元组 - 元组中第j个位置的i表示a的第i个轴成为a.transpose()的第j个轴。
n个整数 - 与n个相同整数的元组相同
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)
返回具有转置轴的数组视图,在NumPy中使用ma.MaskedArray.transpose()方法:
print("
Result...
",maskArr.transpose())
示例
# Python ma.MaskedArray - Return a view of the array with axes transposed 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 maskArr = ma.masked_array(arr, mask =[[0, 1, 0], [ 0, 0, 0]]) 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 view of the array with axes transposed, use the ma.MaskedArray.transpose() method in Numpy print("
Result...
",maskArr.transpose())
输出
Array... [[78 85 51] [56 33 97]] Array type... int64 Array Dimensions... 2 Our Masked Array [[78 -- 51] [56 33 97]] Our Masked Array type... int64 Our Masked Array Dimensions... 2 Our Masked Array Shape... (2, 3) Elements in the Masked Array... 6 Result... [[78 56] [-- 33] [51 97]]
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