使用NumPy将所有非掩码数据作为一维数组返回
要将所有非掩码数据作为一维数组返回,请使用NumPy中的 **ma.MaskedArray.compressed()** 方法。掩码要么是nomask,表示关联数组的任何值均无效,要么是一个布尔型数组,用于确定关联数组的每个元素的值是否有效。
numpy.ma.MaskedArray是ndarray的子类,用于处理包含缺失数据的数值数组。MaskedArray的实例可以被认为是几个元素的组合。
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([[35, 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,并将其中一些元素标记为无效:
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)
要将所有非掩码数据作为一维数组返回,请使用NumPy中的ma.MaskedArray.compressed()方法:
print("
Return Value...
",maskArr.compressed())
示例
# Python ma.MaskedArray - Return all the non-masked data as a 1-D array import numpy as np import numpy.ma as ma # Create an array with int elements using the numpy.array() method arr = np.array([[35, 85, 45], [67, 33, 59]]) 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, 0, 1], [ 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 all the non-masked data as a 1-D array, use the ma.MaskedArray.compressed() method in Numpy print("
Return Value...
",maskArr.compressed())
输出
Array... [[35 85 45] [67 33 59]] Array type... int64 Array Dimensions... 2 Our Masked Array [[35 85 --] [67 -- 59]] Our Masked Array type... int64 Our Masked Array Dimensions... 2 Our Masked Array Shape... (2, 3) Elements in the Masked Array... 6 Return Value... [35 85 67 59]
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