Return input with invalid data masked and replaced by a fill value in Numpy

To return input with invalid data masked and replaced by a fill value, use the numpy.ma.fix_invalid() method in Python Numpy. A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.

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([[65, 68, 81], [93, 33, 39], [73, 88, 51], [62, 45, 67]])
print("Array...
", arr)
print("\nArray type...
", arr.dtype)

Get the dimensions of the Array −

print("\nArray 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], [0, 1, 0], [0, 1, 0]])
print("\nOur Masked Array
", maskArr)
print("\nOur Masked Array type...
", maskArr.dtype)

Get the dimensions of the Array −

print("\nOur Masked Array Dimensions...
",arr.ndim)

Get the shape of the Array −

print("\nOur Masked Array Shape...
",arr.shape)

Get the number of elements of the Array −

print("\nElements in the Masked Array...
",arr.size)

To return input with invalid data masked and replaced by a fill value, use the numpy.ma.fix_invalid() method in Python Numpy:

print("\nResult...
",np.ma.fix_invalid(arr))

Example

import numpy as np
import numpy.ma as ma

# Create an array with int elements using the numpy.array() method
arr = np.array([[65, 68, 81], [93, 33, 39], [73, 88, 51], [62, 45, 67]])
print("Array...
", arr)
print("\nArray type...
", arr.dtype)

# Get the dimensions of the Array
print("\nArray 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], [0, 1, 0], [0, 1, 0]])
print("\nOur Masked Array
", maskArr)
print("\nOur Masked Array type...
", maskArr.dtype)

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

# Get the shape of the Array
print("\nOur Masked Array Shape...
",arr.shape)

# Get the number of elements of the Array
print("\nElements in the Masked Array...
",arr.size)

# To return input with invalid data masked and replaced by a fill value, use the numpy.ma.fix_invalid() method in Python Numpy
print("\nResult...
",np.ma.fix_invalid(arr))

Output

Array...
[[65 68 81]
[93 33 39]
[73 88 51]
[62 45 67]]

Array type...
int64

Array Dimensions...
2
Our Masked Array
[[-- -- 81]
[93 33 39]
[73 -- 51]
[62 -- 67]]

Our Masked Array type...
int64

Our Masked Array Dimensions...
2

Our Masked Array Shape...
(4, 3)

Elements in the Masked Array...
12

Result...
[[65 68 81]
[93 33 39]
[73 88 51]
[62 45 67]]