NumPy中掩盖小于等于给定值的数组
要掩盖小于等于给定值的数组,请在Python NumPy中使用**numpy.ma.masked_less_equal()**方法。此函数是masked_where的快捷方式,其中condition = (x <= value)。
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均有效),要么是一个布尔型数组,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数元素的数组:
arr = np.array([[83, 55, 73], [90, 49, 39], [73, 87, 51], [82, 45, 67]])
print("Array...
", arr)获取数组的类型:
print("
Array type...
", arr.dtype)获取数组的维度:
print("
Array Dimensions...
",arr.ndim)获取数组的形状:
print("
Our Array Shape...
",arr.shape)
获取数组的元素个数:
print("
Number of Elements in the Array...
",arr.size)要掩盖小于等于给定值的数组,请使用numpy.ma.masked_less_equal()方法。这里,我们将掩盖小于等于值73的数组:
print("
Result...
",np.ma.masked_less_equal(arr, 73))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([[83, 55, 73], [90, 49, 39], [73, 87, 51], [82, 45, 67]])
print("Array...
", arr)
# Get the type pf array
print("
Array type...
", arr.dtype)
# Get the dimensions of the Array
print("
Array Dimensions...
",arr.ndim)
# Get the shape of the Array
print("
Our Array Shape...
",arr.shape)
# Get the number of elements of the Array
print("
Number of Elements in the Array...
",arr.size)
# To mask an array where less than equal to a given value, use the numpy.ma.masked_less_equal() method in Python Numpy
# Here, we will the array less than equal to value 73
print("
Result...
",np.ma.masked_less_equal(arr, 73))输出
Array... [[83 55 73] [90 49 39] [73 87 51] [82 45 67]] Array type... int64 Array Dimensions... 2 Our Array Shape... (4, 3) Number of Elements in the Array... 12 Result... [[83 -- --] [90 -- --] [-- 87 --] [82 -- --]]
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