从 NumPy 中的掩码数组中返回指定的对角线
要返回指定的对角线,在 Python Numpy 中使用 ma.MaskedArray.diagonal 方法。掩码数组是标准 numpy.ndarray 和一个掩码的组合。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,用来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
使用 numpy.array() 方法创建一个包含 int 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标记其中一些无效 −
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数量 −
print("
Elements in the Masked Array...
",maskArr.size)
返回指定的对角线,在 Numpy 中使用 ma.MaskedArray.diagonal() 方法 −
print("
Result...
",maskArr.diagonal())
范例
import numpy as np import numpy.ma as ma # Create an array with int elements using the numpy.array() method arr = np.array([[55, 85, 59, 77], [67, 33, 39, 57], [29, 88, 51, 37], [56, 45, 99, 85]]) 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 =[[1, 1, 0, 0], [ 0, 0, 1, 0], [0, 0, 0, 1], [0, 1, 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 specified diagonals, use the ma.MaskedArray.diagonal() method in Numpy print("
Result...
",maskArr.diagonal())
输出
Array... [[55 85 59 77] [67 33 39 57] [29 88 51 37] [56 45 99 85]] Array type... int64 Array Dimensions... 2 Our Masked Array [[-- -- 59 77] [67 33 -- 57] [29 88 51 --] [56 -- 99 85]] Our Masked Array type... int64 Our Masked Array Dimensions... 2 Our Masked Array Shape... (4, 4) Elements in the Masked Array... 16 Result... [-- 33 51 85]
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