返回 NumPy 中降维为一维的掩码数组的副本
要返回降维为一维的数组的副本,请在 NumPy 中使用 **ma.MaskedArray.flatten()** 方法。
顺序“C”表示以行优先(C 样式)顺序展平。“F”表示以列优先(Fortran 样式)顺序展平。“A”表示如果 a 在内存中是 Fortran 连续的,则以列优先顺序展平,否则以行优先顺序展平。“K”表示按元素在内存中出现的顺序展平 a。默认为“C”。
掩码数组是标准 numpy.ndarray 和掩码的组合。掩码要么是 nomask,表示关联数组的没有任何值无效,要么是一个布尔数组,它决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() 方法创建一个包含整型元素的数组:
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)
返回降维为一维的数组的副本,在 NumPy 中使用 ma.MaskedArray.flatten() 方法:
print("
Result...
",maskArr.flatten())
示例
# Python ma.MaskedArray - Return a copy of the array collapsed into one dimension 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, 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 a copy of the array collapsed into one dimension, use the ma.MaskedArray.flatten() method in Numpy print("Result...",maskArr.flatten())
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输出
Array... [[78 85 51] [56 33 97]] Array type... int64 Array Dimensions... 2 Our Masked Array [[78 -- 51] [56 -- 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 -- 51 56 -- 97]
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