I have a dictionary associating a probability to a char
d = {'a': 0.2, 'b': 0.3, 'c': 0.4, 'd':0.1}
And I am searching a way to associate to each char the lowest value of his frequency distribution. So every char must be associated to the sum of the previous ones. I know dictionary are not ordered but it should return something like
ddist = {'a': 0, 'b': 0.2, 'c': 0.5, 'd': 0.9}
I tried with a loop but I did not find a way to get the previous values...
Any ideas ?
You can simply iterate over a sorted version of the keys:
d = {'a': 0.2, 'b': 0.3, 'c': 0.4, 'd':0.1}
ddist = {}
t = 0
for key in sorted(d):
ddist[key] = t
t += d[key]
As dicts are unordered, so you need to define the key order yourself, or use collections.OrderedDict from the start.
>>> def accumulate(seq):
total = 0
for item in seq:
yield total
total += item
...
>>> keys = ['a', 'b', 'c', 'd'] #For your dict, this is sorted(d)
>>> dict(zip(keys, accumulate(d[k] for k in keys)))
{'a': 0, 'c': 0.5, 'b': 0.2, 'd': 0.9}
#or
>>> from collections import OrderedDict
>>> OrderedDict(zip(keys, accumulate(d[k] for k in keys)))
OrderedDict([('a', 0), ('b', 0.2), ('c', 0.5), ('d', 0.9)])
