返回 NumPy 中非零且未掩码元素的索引
要返回非零且未掩码元素的索引,请使用 **ma.MaskedArray.nonzero()**
返回一个元组数组,每个维度一个,包含该维度中非零元素的索引。可以使用 - 获取相应的非零值。
a[a.nonzero()]
要按元素而不是维度对索引进行分组,请改用 -
np.transpose(a.nonzero())
其结果始终是一个二维数组,每行对应一个非零元素。
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 int 元素的数组 -
arr = np.array([[55, 85, 59, 77], [67, 33, 39, 57], [29, 88, 51, 37], [56, 45, 99, 85]])
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掩盖其中一些无效元素 -
maskArr = ma.masked_array(arr, mask =[[1, 1, 0, 0], [ 0, 0, 1, 0], [0, 0, 0, 1], [0, 1, 0, 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)
要返回非零且未掩码元素的索引,请在 NumPy 中使用 ma.MaskedArray.nonzero() 方法。返回一个元组数组,每个维度一个,包含该维度中非零元素的索引 -
print("
Result...
",maskArr.nonzero())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([[55, 85, 59, 77], [67, 33, 39, 57], [29, 88, 51, 37], [56, 45, 99, 85]])
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, 1, 0], [0, 0, 0, 1], [0, 1, 0, 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 the indices of unmasked elements that are not zero, use the ma.MaskedArray.nonzero() method in Numpy
# Returns a tuple of arrays, one for each dimension, containing the indices of the non-zero elements in that dimension.
print("
Result...
",maskArr.nonzero())输出
Array... [[55 85 59 77] [67 33 39 57] [29 88 51 37] [56 45 99 85]] Array type... int64 Array Dimensions... 2 Our Masked Array [[-- -- 59 77] [67 33 -- 57] [29 88 51 --] [56 -- 99 85]] Our Masked Array type... int64 Our Masked Array Dimensions... 2 Our Masked Array Shape... (4, 4) Elements in the Masked Array... 16 Result... (array([0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3]), array([2, 3, 0, 1, 3, 0, 1, 2, 0, 2, 3]))
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