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