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 --]]
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