在NumPy中掩盖包含掩码值的二维数组的行
要掩盖包含掩码值的二维数组的行,请在 NumPy 中使用 **np.ma.mask_rows()** 方法。掩码要么是 nomask,表示关联数组中没有无效值,要么是一个布尔数组,它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一些标记为无效:
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)
要掩盖包含掩码值的二维数组的行,请在 NumPy 中使用 np.ma.mask_rows() 方法:
print("Result...",np.ma.mask_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 mask rows of a 2D array that contain masked values, use the np.ma.mask_rows() method in Numpy print("Result...",np.ma.mask_rows(maskArr))
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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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