Transform a masked array into a flexibletype array with torecords() in Numpy


To transform a masked array into a flexible-type array, use the ma.MaskedArray.torecords(). The flexible type array that is returned will have two fields

  • The _data field stores the _data part of the array.

  • The _mask field stores the _mask part of the array.method in Numpy.

Returns a new flexible-type ndarray with two fields − the first element containing a value, the second element containing the corresponding mask boolean. The returned record shape matches self.shape.

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([[49, 85, 45], [67, 33, 59]])
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 =[[0, 0, 1], [ 0, 1, 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)

Transform a masked array into a flexible-type array, use the ma.MaskedArray.torecords() method in Numpy. The flexible type array that is returned will have two fields: the _data field stores the _data part of the array −

print("
Result of the transformation...
",maskArr.torecords())

Example

# Python - Transform a masked array into a flexible-type array with MaskedArray.torecords()

import numpy as np
import numpy.ma as ma

# Create an array with int elements using the numpy.array() method
arr = np.array([[49, 85, 45], [67, 33, 59]])
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 =[[0, 0, 1], [ 0, 1, 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 transform a masked array into a flexible-type array, use the ma.MaskedArray.torecords() method in Numpy # The flexible type array that is returned will have two fields: the _data field stores the _data part of the array. #, the _mask field stores the _mask part of the array. print("
Result of the transformation...
",maskArr.torecords())

Output

Array...
[[49 85 45]
[67 33 59]]

Array type...
int64

Array Dimensions...
2

Our Masked Array
[[49 85 --]
[67 -- 59]]

Our Masked Array type...
int64

Our Masked Array Dimensions...
2

Our Masked Array Shape...
(2, 3)

Elements in the Masked Array...
6

Result of the transformation...
[[(49, False) (85, False) (45, True)]
[(67, False) (33, True) (59, False)]]

Updated on: 02-Feb-2022

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