On Sunday, April 15, 2018, Peter Norvig <pe...@norvig.com> wrote: > If you think of a Counter as a multiset, then it should support __or__, > not __add__, right? > > I do think it would have been fine if Counter did not support "+" at all > (and/or if Counter was limited to integer values). But given where we are > now, it feels like we should preserve `c + c == 2 * c`. > > As to the "doesn't really add any new capabilities" argument, that's > true, but it is also true for Counter as a whole: it doesn't add much over > defaultdict(int), but it is certainly convenient to have a standard way to > do what it does. > > I agree with your intuition that low level is better. `total` would be > useful. If you have total and mul, then as you and others have pointed out, > normalize is just c *= 1/c.total. > > I can also see the argument for a new FrequencyTable class in the > statistics module. (By the way, I refactored my https://github.com/norvig/ > pytudes/blob/master/ipynb/Probability.ipynb a bit, and now I no longer > need a `normalize` function.) >

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nltk.probability.FreqDist(collections.Counter) doesn't have a __mul__ either http://www.nltk.org/api/nltk.html#nltk.probability.FreqDist numpy.unique(, return_counts=True).unique_counts returns an array sorted by value with a __mul__. https://docs.scipy.org/doc/numpy/reference/generated/numpy.unique.html scipy.stats.itemfreq returns an array sorted by value with a __mul__ and the items in the first column. https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.itemfreq.html pandas.Series.value_counts(, normalize=False) returns a Series sorted by descending frequency. https://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.value_counts.html > On Sun, Apr 15, 2018 at 5:06 PM Raymond Hettinger < > raymond.hettin...@gmail.com> wrote: > >> >> >> > On Apr 15, 2018, at 2:05 PM, Peter Norvig <pe...@norvig.com> wrote: >> > >> > For most types that implement __add__, `x + x` is equal to `2 * x`. >> > >> > ... >> > >> > >> > That is true for all numbers, list, tuple, str, timedelta, etc. -- but >> not for collections.Counter. I can add two Counters, but I can't multiply >> one by a scalar. That seems like an oversight. >> >> If you view the Counter as a sparse associative array of numeric values, >> it does seem like an oversight. If you view the Counter as a Multiset or >> Bag, it doesn't make sense at all ;-) >> >> From an implementation point of view, Counter is just a kind of dict that >> has a __missing__() method that returns zero. That makes it trivially easy >> to subclass Counter to add new functionality or just use dictionary >> comprehensions for bulk updates. >> >> > >> > >> > It would be worthwhile to implement multiplication because, among other >> reasons, Counters are a nice representation for discrete probability >> distributions, for which multiplication is an even more fundamental >> operation than addition. >> >> There is an open issue on this topic. See: https://bugs.python.org/ >> issue25478 >> >> One stumbling point is that a number of commenters are fiercely opposed >> to non-integer uses of Counter. Also, some of the use cases (such as those >> found in Allen Downey's "Think Stats" and "Think Bayes" books) also need >> division and rescaling to a total (i.e. normalizing the total to 1.0) for a >> probability mass function. >> >> If the idea were to go forward, it still isn't clear whether the correct >> API should be low level (__mul__ and __div__ and a "total" property) or >> higher level (such as a normalize() or rescale() method that produces a new >> Counter instance). The low level approach has the advantage that it is >> simple to understand and that it feels like a logical extension of the >> __add__ and __sub__ methods. The downside is that doesn't really add any >> new capabilities (being just short-cuts for a simple dict comprehension or >> call to c.values()). And, it starts to feature creep the Counter class >> further away from its core mission of counting and ventures into the realm >> of generic sparse arrays with numeric values. There is also a >> learnability/intelligibility issue in __add__ and __sub__ correspond to >> "elementwise" operations while __mul__ and __div__ would be "scalar >> broadcast" operations. >> >> Peter, I'm really glad you chimed in. My advocacy lacked sufficient >> weight to move this idea forward. >> >> >> Raymond >> >> >> >>

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