Numpy bincount() with floats
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)>>> uniqwarray([ 0.1, 0.2, 0.3, 0.5])>>> np.bincount(inverse)array([2, 1, 1, 1])
You want something like this?
>>> from collections import Counter>>> w = np.array([0.1, 0.2, 0.1, 0.3, 0.5])>>> c = Counter(w)Counter({0.10000000000000001: 2, 0.5: 1, 0.29999999999999999: 1, 0.20000000000000001: 1})or, more nicely output:
Counter({0.1: 2, 0.5: 1, 0.3: 1, 0.2: 1})You can then sort it and get your values:
>>> np.array([v for k,v in sorted(c.iteritems())])array([2, 1, 1, 1])The output of bincount wouldn't make sense with floats:
>>> np.bincount([10,11])array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1])as there is no defined sequence of floats.