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Concatenate a sequence of masked arrays along specific axis in Numpy
To concatenate a sequence of masked arrays, use the ma.concatenate() method in Python Numpy. The axis is set using the "axis" parameter.
The parameters are the arrays that must have the same shape, except in the dimension corresponding to axis (the first, by default). The axis is the axis along which the arrays will be joined. Default is 0. The function returns the concatenated array with any masked entries preserved.
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, a 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 a masked array 2 −
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 concatenate a sequence of masked arrays, use the ma.concatenate() method in Python Numpy. The axis is set using the "axis" parameter:
print("
Result of concatenation...
",ma.concatenate([arr1, arr2], axis = 1))Example
# Python ma.MaskedArray - Concatenate a sequence of masked arrays along specific axis
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 concatenate a sequence of arrays, use the ma.concatenate() method in Python Numpy
print("
Result of concatenation...
",ma.concatenate([arr1, arr2], axis = 1))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 concatenation... [[0 -- 2 0 1 2] [3 -- 5 3 4 5] [6 7 8 6 -- --]]
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