返回NumPy中掩码数组的长度
要返回掩码数组的长度,请在 Python NumPy 中使用 **ma.MaskedArray.__len__()** 方法。掩码数组是标准 numpy.ndarray 和掩码的组合。掩码要么是 nomask,表示关联数组的任何值均无效,要么是布尔值数组,用于确定关联数组的每个元素的值是否有效。
NumPy 提供了全面的数学函数、随机数生成器、线性代数例程、傅里叶变换等。它支持各种硬件和计算平台,并且与分布式、GPU 和稀疏数组库配合良好。
步骤
首先,导入所需的库 -
import numpy as np import numpy.ma as ma
使用 numpy.array() 方法创建包含整数元素的数组 -
arr = np.array([[65, 68, 81], [93, 33, 39], [73, 88, 51], [62, 45, 67]]) 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 =[[1, 1, 0], [ 1, 0, 0], [0, 1, 0], [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)
要返回掩码数组的长度,请使用 ma.MaskedArray.__len__() 方法 -
print("
Result...
",maskArr.__len__())
示例
import numpy as np import numpy.ma as ma # Create an array with int elements using the numpy.array() method arr = np.array([[65, 68, 81], [93, 33, 39], [73, 88, 51], [62, 45, 67]]) 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], [ 1, 0, 0], [0, 1, 0], [0, 1, 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 the length of the masked array, use the ma.MaskedArray.__len__() method print("
Result...
",maskArr.__len__())
输出
Array... [[65 68 81] [93 33 39] [73 88 51] [62 45 67]] Array type... int64 Array Dimensions... 2 Our Masked Array [[-- -- 81] [-- 33 39] [73 -- 51] [62 -- 67]] Our Masked Array type... int64 Our Masked Array Dimensions... 2 Our Masked Array Shape... (4, 3) Elements in the Masked Array... 12 Result... 4
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