Join a sequence of masked arrays in Numpy



To join a sequence of masked arrays, use the ma.stack()  method in Python Numpy. The axis parameter specifies the index of the new axis in the dimensions of the result. For example, if axis=0 it will be the first dimension and if axis=-1 it will be the last dimension.

The out parameter, if provided, is the destination to place the result. The shape must be correct, matching that of what stack would have returned if no out argument were specified.

The function returns the stacked array has one more dimension than the input arrays. It is applied to both the _data and the _mask, if any.

Steps

At first, import the required library −

import numpy as np
import numpy.ma as ma

Create Array 1, a 3x3 array with int elements using the numpy.arange() method −

arr1 = np.arange(9).reshape((3,3))
print("Array1...
", arr1) print("
Array type...
", arr1.dtype)

Create a masked array 1 −

arr1 = ma.array(arr1)

Mask Array1 −

arr1[0, 1] = ma.masked
arr1[1, 1] = ma.masked

Display Masked Array 1 −

print("
Masked Array1...
",arr1)

Create Array 2, another 3x3 array with int elements using the numpy.arange() method −

arr2 = np.arange(9).reshape((3,3))
print("
Array2...
", arr2) print("
Array type...
", arr2.dtype)

Create masked array2 −

arr2 = ma.array(arr2)

Mask Array2 −

arr2[2, 1] = ma.masked
arr2[2, 2] = ma.masked

Display Masked Array 2 −

print("
Masked Array2...
",arr2)

To join a sequence of masked arrays, use the ma.stack() method in Python Numpy −

print("
Result of joining arrays...
",ma.stack((arr1, arr2)))

Example

# Python ma.MaskedArray - Join a sequence of masked arrays

import numpy as np
import numpy.ma as ma

# Array 1
# Creating a 3x3 array with int elements using the numpy.arange() method
arr1 = np.arange(9).reshape((3,3))
print("Array1...
", arr1) print("
Array type...
", arr1.dtype) # Get the dimensions of the Array print("
Array Dimensions...
",arr1.ndim) # Get the shape of the Array print("
Our Array Shape...
",arr1.shape) # Get the number of elements of the Array print("
Elements in the Array...
",arr1.size) # Create a masked array arr1 = ma.array(arr1) # Mask Array1 arr1[0, 1] = ma.masked arr1[1, 1] = ma.masked # Display Masked Array 1 print("
Masked Array1...
",arr1) # Array 2 # Creating another 3x3 array with int elements using the numpy.arange() method arr2 = np.arange(9).reshape((3,3)) print("
Array2...
", arr2) print("
Array type...
", arr2.dtype) # Get the dimensions of the Array print("
Array Dimensions...
",arr2.ndim) # Get the shape of the Array print("
Our Array Shape...
",arr2.shape) # Get the number of elements of the Array print("
Elements in the Array...
",arr2.size) # Create a masked array arr2 = ma.array(arr2) # Mask Array2 arr2[2, 1] = ma.masked arr2[2, 2] = ma.masked # Display Masked Array 2 print("
Masked Array2...
",arr2) # To join a sequence of masked arrays, use the ma.stack() method in Python Numpy print("
Result of joining arrays...
",ma.stack((arr1, arr2)))

Output

Array1...
[[0 1 2]
[3 4 5]
[6 7 8]]

Array type...
int64

Array Dimensions...
2

Our Array Shape...
(3, 3)

Elements in the Array...
9

Masked Array1...
[[0 -- 2]
[3 -- 5]
[6 7 8]]

Array2...
[[0 1 2]
[3 4 5]
[6 7 8]]

Array type...
int64

Array Dimensions...
2

Our Array Shape...
(3, 3)

Elements in the Array...
9

Masked Array2...
[[0 1 2]
[3 4 5]
[6 -- --]]

Result of joining arrays...
[[[0 -- 2]
[3 -- 5]
[6 7 8]]
[[0 1 2]
[3 4 5]
[6 -- --]]]

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