accelerated discrete sampling by ~3-5x times

[jrzkaminski]

Accelerated discrete sampling using cumulative distribution and numpy function. It could be further used to make vector predictions instead of iterating over samples.

[jrzkaminski]

I've also made an itertools version of the same algorithm, it is even faster, but does not accept vectors or matrices.

def choose(self, node_info: Dict[str, Union[float, str]], pvals: List[str]) -> str:
        vals = node_info["vals"]
        dist = self.get_dist(node_info, pvals)

        cumulative_dist = list(accumulate(dist))

        rand = random.random()
        rindex = next((i for i, ubound in enumerate(cumulative_dist) if rand < ubound), len(vals) - 1)

        return vals[rindex]

[codecov-commenter]

Codecov Report

Merging #90 (0f9c34c) into master (f234a9f) will decrease coverage by 0.09%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master      #90      +/-   ##
==========================================
- Coverage   65.03%   64.95%   -0.09%     
==========================================
  Files          43       43              
  Lines        2903     2896       -7     
==========================================
- Hits         1888     1881       -7     
  Misses       1015     1015              

Files	Coverage Δ
bamt/nodes/discrete_node.py	96.29% <100.00%> (-0.43%)	⬇️