1. Python
  2. Numpy MaskedArray.astype () Function | python

Numpy MaskedArray.astype () Function | python

numpy.MaskedArray.astype() returns a copy of the MaskedArray cast to this new type.

Syntax: numpy.MaskedArray.astype(newtype)

Parameters:
newtype: Type in which we want to convert the masked array.

Return: [MaskedArray] A copy of self cast to input newtype. The returned record shape matches self.shape.

Code # 1:

# Python program explaining
# numpy.MaskedArray.astype () method

 
# import numy as geek
# and numpy.ma module as ma

import numpy as geek

import numpy.ma as ma

 
# create input array

in_arr = geek.array ([ 1 , 2 ,  3 , - 1 , 5 ])

print ( "Input array:" , in_arr)

 
# Now we create a masked int32 array
# and invalidate the third entry.

mask_arr = ma.masked_array (in_arr, mask = [ 0 , 0 , 1 , 0 , 0 ])

print ( "Masked array:" , mask_arr)

  
# print disguised aaray data

print (mask_arr.dtype) 

 
# applying MaskedArray.astype methods to mask the array
# and convert it to float64

out_arr = mask_arr.astype ( `float64` )

print ( " Output typecasted array: " , out_arr)

  
# print data type Typecasted Masque Aaray

print (out_arr.dtype) 

Output: 

 Input array: [1 2 3 -1 5] Masked array: [1 2 - -1 5] int32 Output typecasted array: [1.0 2.0 - -1.0 5.0] float64  
 
  Code # 2:  
 
 
 
  
  
  
  # Python program explaining  
  # numpy.MaskedArray.astype () method  
 
  
  # import numy as geek  
  # and numpy.ma module as ma  
 
  import   numpy as geek 
 
  import   numpy.ma as ma  
   
  # create input array  
 
  in_arr   =   geek.array ([  10.1  ,   20.2  ,   30.3  ,   40.4  ,   50.5  ], dtype   =   `float64`  ) 
 
  print   ( " Input array: " , in_arr) 
 
   
  # Now we create a masked array, making  
  # the first and third entries are invalid.  
 
  mask_arr   =   ma.masked_array (in_arr, mask   =   [  1  ,   0  ,   1  ,   0  ,   0  ])  
 
  print   (  "Masked array:"  , mask_arr) 
 
  
  # print data like a disguised aaray  
 
  print   (mask_arr.dtype)  
 
  
  # using MaskedArray.astype methods to mask the array  
  # and convert it to int32  
 
  out_arr   =   mask_arr.astype (  `int32`  ) 
 
  print   (  "Output typecasted array:"  , out_arr) 
 
  
  # print data type Typecasted Masque Aaray   
  print   (out_arr.dtype) 
 
  
 
   Output :
 
 Input array: [10.1 20.2 30.3 40.4 50.5] Masked array: [- 20.2 - 40.4 50.5 ] float64 Output typecasted array: [- 20 - 40 50] int32