使用 Numpy 中的 compress_rowcols() 沿特定轴仅抑制包含掩码值的行
要仅抑制沿特定轴包含掩码值的那些行,请在 Numpy 中使用 **np.ma.mask_compress_rowcols()** 方法。抑制行为由 axis 参数选择 -
- 如果 axis 为 None,则抑制行和列。
- 如果 axis 为 0,则仅抑制行。
- 如果 axis 为 1 或 -1,则仅抑制列。
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([[65, 68, 81], [93, 33, 76], [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的某些元素标记为无效 -
maskArr = ma.masked_array(arr, mask =[[1, 1, 0], [ 0, 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)
要仅抑制二维数组中沿特定轴包含掩码值的那些行,请使用 np.ma.mask_compress_rowcols() 方法。抑制行为由 axis 参数选择。如果 axis 为 None,则抑制行和列。如果 axis 为 0,则仅抑制行。如果 axis 为 1 或 -1,则仅抑制列 -
print("
Result...
",np.ma.compress_rowcols(maskArr, axis = 0))
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, 76], [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], [ 0, 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 suppress only rows of a 2-D array that contain masked values alomg specific axis, use the np.ma.mask_compress_rowcols() method in Numpy # The suppression behavior is selected with the axis parameter # If axis is None, both rows and columns are suppressed. # If axis is 0, only rows are suppressed. # If axis is 1 or -1, only columns are suppressed print("
Result...
",np.ma.compress_rowcols(maskArr, axis = 0))
输出
Array... [[65 68 81] [93 33 76] [73 88 51] [62 45 67]] Array type... int64 Array Dimensions... 2 Our Masked Array [[-- -- 81] [93 33 76] [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... [[93 33 76]]
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