在NumPy中抑制包含掩码值的二维数组的整行
要抑制包含掩码值的二维数组的整行,请在NumPy中使用 **np.ma.mask_compress_rows()** 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都不无效,要么是布尔值的数组,用于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数量 -
print("
Elements in the Masked Array...
",maskArr.size)
要抑制包含掩码值的二维数组的整行,请使用 np.ma.mask_compress_rows() 方法 -
print("
Result...
",np.ma.compress_rows(maskArr))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], [ 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 whole rows of a 2-D array that contain masked values, use the np.ma.mask_compress_rows() method in Numpy
print("
Result...
",np.ma.compress_rows(maskArr))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] [93 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... [[93 33 39]]
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