# Numpy MaskedArray.atleast_3d () Function | python

`numpy.MaskedArray.atleast_3d()` is used to transform input data into masked arrays with at least three dimensions. `numpy.MaskedArray.atleast_3d()` , 1D and 2D arrays are converted to 3D arrays, while larger input data is 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 & gt; = 3 `

Code # 1:

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 ` ` `  ` # import numy as geek ` ` # and numpy.ma module as ma ` ` import ` numpy as geek  ` import ` ` numpy.ma as ma `   ` # create 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 create a mask an arrayed array. ` ` # invalidating the entry. ` ` 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 the masked array ` ` out_arr ` ` = ` ` ma.atleast_2d (mask_arr1, mask_arr2, mask_arr3) ` ` print ` ` (` ` "Output masked array:" ` `, out_arr) `
 ` # Python program explaining ` ` # numpy.MaskedArray.atleast_3d () method ` ` `  ` # import numy like a geek ` ` # and the numpy.ma module like ma ` ` import ` ` numpy as geek ` ` import ` ` numpy.ma as ma `   ` # create input array ` ` in_arr ` ` = ` ` geek.array ([[[` ` 2e8 ` `, ` ` 3e ` ` - ` ` 5 ` `]], [[` ` - ` ` 45.0 ` `, ` ` 2e5 ` `]]]) ` ` print ` ` (` `" Input array: "` `, in_arr) `   ` # Now we create a masked array. ` ` # making one entry 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 the 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 ]]] `