Repeat elements of a masked array in Numpy

To repeat elements of a masked array, use the ma.MaskedArray.repeat() method in Numpy. The "repeats" parameter sets the number of repetitions for each element. Here, repeats is broadcasted to fit the shape of the given axis. It returns the output array which has the same shape as a, except along the given axis.

The axis is the axis along which to repeat values. By default, use the flattened input array, and return a flat output array.

Steps

At first, import the required library −

import numpy as np
import numpy.ma as ma

Create an array with int elements using the numpy.array() method −

arr = np.array([[55, 85, 59, 77], [67, 33, 39, 57], [29, 88, 51, 37], [56, 45, 99, 85]])
print("Array...
", arr)
print("
Array type...
", arr.dtype)

Get the dimensions of the Array −

print("
Array Dimensions...
",arr.ndim)

Create a masked array and mask some of them as invalid −

maskArr = ma.masked_array(arr, mask =[[1, 1, 0, 0], [ 0, 0, 1, 0], [0, 0, 0, 1], [0, 1, 0, 0]])
print("
Our Masked Array
", maskArr)
print("
Our Masked Array type...
", maskArr.dtype)

Get the dimensions of the Masked Array −

print("
Our Masked Array Dimensions...
",maskArr.ndim)

Get the shape of the Masked Array −

print("
Our Masked Array Shape...
",maskArr.shape)

Get the number of elements of the Masked Array −

print("
Elements in the Masked Array...
",maskArr.size)

To repeat elements of a masked array, use the ma.MaskedArray.repeat() method in Numpy. The "repeats" parameter sets the number of repetitions for each element. The repeats is broadcasted to fit the shape −

print("
Result...
",maskArr.repeat(3))

Example

# Python ma.MaskedArray - Repeat elements of a masked array

import numpy as np
import numpy.ma as ma

# Create an array with int elements using the numpy.array() method
arr = np.array([[55, 85, 59, 77], [67, 33, 39, 57], [29, 88, 51, 37], [56, 45, 99, 85]])
print("Array...
", arr)
print("
Array type...
", arr.dtype)

# Get the dimensions of the Array
print("
Array Dimensions...
",arr.ndim)

# Create a masked array and mask some of them as invalid
maskArr = ma.masked_array(arr, mask =[[1, 1, 0, 0], [ 0, 0, 1, 0], [0, 0, 0, 1], [0, 1, 0, 0]])
print("
Our Masked Array
", maskArr)
print("
Our Masked Array type...
", maskArr.dtype)

# Get the dimensions of the Masked Array
print("
Our Masked Array Dimensions...
",maskArr.ndim)

# Get the shape of the Masked Array
print("
Our Masked Array Shape...
",maskArr.shape)

# Get the number of elements of the Masked Array
print("
Elements in the Masked Array...
",maskArr.size)

# To repeat elements of a masked array, use the ma.MaskedArray.repeat() method in Numpy
# The "repeats" parameter sets the number of repetitions for each element.
# The repeats is broadcasted to fit the shape.
print("
Result...
",maskArr.repeat(3))

Output

Array...
[[55 85 59 77]
[67 33 39 57]
[29 88 51 37]
[56 45 99 85]]

Array type...
int32

Array Dimensions...
2

Our Masked Array
[[-- -- 59 77]
[67 33 -- 57]
[29 88 51 --]
[56 -- 99 85]]

Our Masked Array type...
int32

Our Masked Array Dimensions...
2

Our Masked Array Shape...
(4, 4)

Elements in the Masked Array...
16

Result...
[-- -- -- -- -- -- 59 59 59 77 77 77 67 67 67 33 33 33 -- -- -- 57 57 57
29 29 29 88 88 88 51 51 51 -- -- -- 56 56 56 -- -- -- 99 99 99 85 85 85]