Python Numpy MaskedArray.maximum_fill_value()函数

Python Numpy MaskedArray.maximum_fill_value()函数

numpy.MaskedArray.maximum_fill_value()函数用于返回一个对象的dtype所能代表的最小值。

语法: numpy.ma.maximum_fill_value(obj)

参数:
obj : [ ndarray, dtype or scalar ] 返回最小填充值的阵列数据类型或标量。

返回 : [ 标量 ] 最小填充值。

代码#1:

# Python program explaining
# numpy.MaskedArray.maximum_fill_value() method 
    
# importing numpy as geek  
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma 
    
# creating input array  
in_arr = geek.array([1,  3,  5, -3], dtype ='float')
print ("Input array : ", in_arr) 
    
# Now we are creating a masked array. 
# by making  entry as invalid.  
mask_arr = ma.masked_array(in_arr, mask =[1, 0, 0, 0]) 
print ("Masked array : ", mask_arr) 
    
# applying MaskedArray.maximum_fill_value    
# methods to masked array
out_val = ma.maximum_fill_value(mask_arr) 
print ("Minimum filled value : ", out_val) 

输出:

Input array :  [ 1.  3.  5. -3.]
Masked array :  [-- 3.0 5.0 -3.0]
Minimum filled value :  -inf

代码#2:

# Python program explaining
# numpy.MaskedArray.maximum_fill_value() method 
    
# importing numpy as geek  
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma 
    
# creating input array  
in_arr = geek.array([[1, 2], [ 3, -1], [ 5, -3]])
print ("Input array : ", in_arr) 
    
# Now we are creating a masked array. 
# by making  entry as invalid.  
mask_arr = ma.masked_array(in_arr, mask =[[1, 0], [ 1, 0], [ 0, 0]]) 
print ("Masked array : ", mask_arr) 
    
# applying MaskedArray.maximum_fill_value    
# methods to masked array
out_val = ma.maximum_fill_value(mask_arr) 
print ("Minimum filled value : ", out_val)  

输出:

Input array :  [[ 1  2]
 [ 3 -1]
 [ 5 -3]]
Masked array :  [[-- 2]
 [-- -1]
 [5 -3]]
Minimum filled value :  -2147483648

Python教程

Java教程

Web教程

数据库教程

图形图像教程

大数据教程

开发工具教程

计算机教程

Numpy 数组操作