Numpy MaskedArray.atleast_3d() function

Numpy MaskedArray.atleast_3d() function | Python

Last Updated : 13 Oct, 2019

numpy.MaskedArray.atleast_3d() function is used to convert inputs to masked arrays with at least three dimension.Scalar, 1-dimensional and 2-dimensional arrays are converted to 3-dimensional arrays, whilst higher-dimensional inputs are preserved.

Syntax : numpy.ma.atleast_3d(*arys)

Parameters:
arys:[ array_like] One or more input arrays.

Return : [ ndarray] An array, or list of arrays, each with arr.ndim >= 3

Code #1 :

# Python program explaining 
# numpy.MaskedArray.atleast_3d() method  
    
# importing numpy as geek   
# and numpy.ma module as ma  
import numpy as geek  
import numpy.ma as ma  
    
# creating input arrays   
in_arr1 = geek.array([ 3, -1, 5, -3]) 
print ("1st Input array : ", in_arr1) 
  
in_arr2 = geek.array(2) 
print ("2nd Input array : ", in_arr2) 
  
in_arr3 = geek.array([[1, 2], [ 3, -1], [ 5, -3]]) 
print ("3rd Input array : ", in_arr3)  
    
# Now we are creating  masked array.  
# by making  entry as invalid.   
mask_arr1 = ma.masked_array(in_arr1, mask =[ 1, 0, 1, 0])  
print ("1st Masked array : ", mask_arr1) 
  
mask_arr2 = ma.masked_array(in_arr2, mask = 0)  
print ("2nd Masked array : ", mask_arr2) 
  
mask_arr3 = ma.masked_array(in_arr3, mask =[[ 1, 0], [ 0, 1], [ 0, 0]])  
print ("3rd Masked array : ", mask_arr3) 
    
# applying MaskedArray.atleast_3d methods  
# to masked array  
out_arr = ma.atleast_2d(mask_arr1, mask_arr2, mask_arr3)  
print ("Output masked array : ", out_arr)  

Output:

1st Input array :  [ 3 -1  5 -3]
2nd Input array :  2
3rd Input array :  [[ 1  2]
 [ 3 -1]
 [ 5 -3]]
1st Masked array :  [-- -1 -- -3]
2nd Masked array :  2
3rd Masked array :  [[-- 2]
 [3 --]
 [5 -3]]
Output masked array :  [masked_array(data=[[--, -1, --, -3]],
             mask=[[ True, False,  True, False]],
       fill_value=999999), masked_array(data=[[2]],
             mask=[[False]],
       fill_value=999999), masked_array(
  data=[[--, 2],
        [3, --],
        [5, -3]],
  mask=[[ True, False],
        [False,  True],
        [False, False]],
  fill_value=999999)]

Code #2 :

# Python program explaining 
# numpy.MaskedArray.atleast_3d() 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([[[ 2e8, 3e-5]], [[ -45.0, 2e5]]]) 
print ("Input array : ", in_arr) 
      
# Now we are creating a masked array.  
# by making one entry as invalid.   
mask_arr = ma.masked_array(in_arr, mask =[[[ 1, 0]], [[ 0, 0]]])  
print ("3D Masked array : ", mask_arr)  
     
# applying MaskedArray.atleast_3d methods  
# to masked array 
out_arr = ma.atleast_3d(mask_arr)  
print ("Output masked array : ", out_arr) 

Output:

Input array :  [[[ 2.0e+08  3.0e-05]]

 [[-4.5e+01  2.0e+05]]]
3D Masked array :  [[[-- 3e-05]]

 [[-45.0 200000.0]]]
Output masked array :  [[[-- 3e-05]]

 [[-45.0 200000.0]]]

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