Return the indices of unmasked elements that are not zero in NumPy

NumpyServer Side ProgrammingProgramming

To return the indices of unmasked elements that are not zero, use the ma.MaskedArray.nonzero()

Returns a tuple of arrays, one for each dimension, containing the indices of the non-zero elements in that dimension. The corresponding non-zero values can be obtained with −

a[a.nonzero()]

To group the indices by element, rather than dimension, use instead −

np.transpose(a.nonzero())

The result of this is always a 2d array, with a row for each non-zero element.

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 return the indices of unmasked elements that are not zero, use the ma.MaskedArray.nonzero() method in Numpy. Returns a tuple of arrays, one for each dimension, containing the indices of the non-zero elements in that dimension −

print("
Result...
",maskArr.nonzero())

Example

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 return the indices of unmasked elements that are not zero, use the ma.MaskedArray.nonzero() method in Numpy # Returns a tuple of arrays, one for each dimension, containing the indices of the non-zero elements in that dimension. print("
Result...
",maskArr.nonzero())

Output

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

Array type...
int64

Array Dimensions...
2

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

Our Masked Array type...
int64

Our Masked Array Dimensions...
2

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

Elements in the Masked Array...
16

Result...
(array([0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3]), array([2, 3, 0, 1, 3, 0, 1, 2, 0, 2, 3]))
raja
Updated on 05-Feb-2022 07:29:12

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