CODEWITHSUNDEEP
python
user1344873
user1344873

Reputation:

Getting index of numpy.ndarray

I have a one-dimensional array of the type numpy.ndarray and I want to know the index of it's max entry. After finding the max, I used

peakIndex = numpy.where(myArray==max)

to find the peak's index. But instead of the index, my script spits out

peakIndex = (array([1293]),)

I want my code to spit out just the integer 1293. How can I clean up the output?

Upvotes: 7

Views: 19029

Answers (2)

abought
abought

Reputation: 2680

To find the max value of an array, you can use the array.max() method. This will probably be more efficient than the for loop described in another answer, which- in addition to not being pythonic- isn't actually written in python. (if you wanted to take items out of the array one by one to compare, you could use ndenumerate, but you'd be sacrificing some of the performance benefits of arrays)

The reason that numpy.where() yields results as tuples is that more than one position could be equal to the max... and it's that edge case that would make something simple (like taking array[0]) prone to bugs. Per Is there a Numpy function to return the first index of something in an array?,

"The result is a tuple with first all the row indices, then all the column indices".

Your example uses a 1-D array, so you'd get the results you want directly from the array provided. It's a tuple with one element (one array of indices), and although you can iterate over ind_1d[0] directly, I converted it to a list solely for readability.

>>> peakIndex_1d
array([ 1. ,  1.1,  1.6,  1. ,  1.6,  0.8])
>>> ind_1d = numpy.where( peakIndex_1d == peakIndex_1d.max() )
(array([2, 4]),)
>>> list( ind_1d[0] )
[2, 4]

For a 2-D array with 3 values equal to the max, you could use:

>>> peakIndex
array([[ 0. ,  1.1,  1.5],
       [ 1.1,  1.5,  0.7],
       [ 0.2,  1.2,  1.5]])
>>> indices = numpy.where( peakIndex == peakIndex.max() )
>>> ind2d = zip(indices[0], indices[1])
[(0, 2), (1, 1), (2, 2)]

Upvotes: 3

ecatmur
ecatmur

Reputation: 157374

Rather than using numpy.where, you can use numpy.argmax.

peakIndex = numpy.argmax(myArray)

numpy.argmax returns a single number, the flattened index of the first occurrence of the maximum value. If myArray is multidimensional you might want to convert the flattened index to an index tuple:

peakIndexTuple = numpy.unravel_index(numpy.argmax(myArray), myArray.shape)

Upvotes: 8

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