NumPy中滿足條件的陣列掩碼


要掩蓋滿足條件的陣列,請在Python NumPy中使用**numpy.ma.masked_where()**方法。將要掩蓋的陣列返回為在condition為True時被掩蓋的陣列。a或condition的任何掩蓋值在輸出中也會被掩蓋。

condition引數設定掩碼條件。當condition測試浮點值的相等性時,請考慮使用masked_values代替。copy引數,如果為True(預設值),則在結果中複製a。如果為False,則就地修改a並返回檢視。

步驟

首先,匯入所需的庫:

import numpy as np
import numpy.ma as ma

使用numpy.array()方法建立一個包含整數元素的陣列:

arr = np.array([[71, 55, 91], [82, 33, 39], [73, 82, 51], [90, 45, 82]])
print("Array...
", arr)

獲取陣列的型別:

print("
Array type...
", arr.dtype)

獲取陣列的維度:

print("
Array Dimensions...
",arr.ndim)

獲取陣列的形狀:

print("
Our Array Shape...
",arr.shape)

獲取陣列的元素個數:

print("
Number of Elements in the Array...
",arr.size)

要掩蓋滿足條件的陣列,請在Python NumPy中使用numpy.ma.masked_where()方法。這裡,所有大於60的元素都將被掩蓋:

print("
Result...
",np.ma.masked_where(arr > 60, arr))

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([[71, 55, 91], [82, 33, 39], [73, 82, 51], [90, 45, 82]])
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 a condition is met, use the numpy.ma.masked_where() method in Python Numpy # Here, all the elements above 60 will get masked print("
Result...
",np.ma.masked_where(arr > 60, arr))

輸出

Array...
[[71 55 91]
[82 33 39]
[73 82 51]
[90 45 82]]

Array type...
int64

Array Dimensions...
2

Our Array Shape...
(4, 3)

Number of Elements in the Array...
12

Result...
[[-- 55 --]
[-- 33 39]
[-- -- 51]
[-- 45 --]]

更新於:2022年2月4日

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