I am trying to get a bincount of a numpy array which is of the float type:
w = np.array([0.1, 0.2, 0.1, 0.3, 0.5])
print np.bincount(w)
How can you use bincount() with float values and not int?
Count number of occurrences of each value in array of non-negative ints. The number of bins (of size 1) is one larger than the largest value in x. If minlength is specified, there will be at least this number of bins in the output array (though it will be longer if necessary, depending on the contents of x).
bincount returns the count of values in each bin from 0 to the largest value in the array i.e.
You need to use numpy.unique
before you use bincount
. Otherwise it's ambiguous what you're counting. unique
should be much faster than Counter for numpy arrays.
>>> w = np.array([0.1, 0.2, 0.1, 0.3, 0.5])
>>> uniqw, inverse = np.unique(w, return_inverse=True)
>>> uniqw
array([ 0.1, 0.2, 0.3, 0.5])
>>> np.bincount(inverse)
array([2, 1, 1, 1])
Since version 1.9.0, you can use np.unique
directly:
w = np.array([0.1, 0.2, 0.1, 0.3, 0.5])
values, counts = np.unique(w, return_counts=True)
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