drwho.epls: Remove dummy episodes from incomplete extras data.

[epls] / clusters

#! /usr/bin/python3

import math as M
import sys as SYS

data = []
for line in SYS.stdin: data.append(float(line))
data.sort()
data = [data]

def cover(lo, hi):
  mid = (lo + hi)/2
  return mid, 1.0 - lo/mid

def metric(vv):
  print(";; measuring...")
  tot = 0
  for v in vv:
    spread = M.pow(v[-1] - v[0], 0.5)
    print(";;\t%g .. %g -> %g" % (v[0], v[-1], spread))
    tot += spread
  return tot

def largest_gap(vv):
  #print(";; finding gap...")
  best, bestwd = None, None
  for i, v in enumerate(vv):
    lo = v[0]
    for j in range(1, len(v)):
      hi = v[j]
      _, spread = cover(lo, hi)
      #print(";;\t%d/%d: %g .. %g -> %g" % (i, j, lo, hi, spread))
      if bestwd is None or spread > bestwd:
        best, bestwd = (i, j), spread
      lo = hi
  #if best is None: print(";; already atomized")
  #else: print(";; best gap %d/%d; %g" % (best[0], best[1], bestwd))
  return best

lastmetric = metric(data)
while True:
  best = largest_gap(data)
  if best is None: break
  i, j = best
  newdata = data[:i] + [data[i][:j], data[i][j:]] + data[i + 1:]
  newmetric = metric(newdata)
  if newmetric > lastmetric: break
  lastmetric, data = newmetric, newdata

def format_duration(t):
  f, t = M.modf(t)
  frac = ("%g" % f)[1:]
  if t >= 3600: return "%d:%02d:%02d%s" % (t//3600, (t//60)%60, t%60, frac)
  elif t >= 60: return "%d:%02d%s" % (t//60, t%60, frac)
  else: return "%d%s s" % (t, frac)

for v in data:
  mid, spread = cover(v[0], v[-1])
  print("%s ± %g%%" % (format_duration(mid), 100.0*spread))