/* 

  Negative Binomial distribution in Picat.

  See ppl_distributions.pi for details, and
  ppl_distributions_test.pi for some more tests.

  Cf my Gamble model gamble_negative_binomial_dist.rkt

  This program was created by Hakan Kjellerstrand, hakank@gmail.com
  See also my Picat page: http://www.hakank.org/picat/

*/

import ppl_distributions, ppl_utils.
import util.

main => go.

/*

  var : p
  Probabilities:
  false: 0.9292000000000000
  true: 0.0708000000000000
  mean = [false = 0.9292,true = 0.0708]

  var : v
  Probabilities:
  0: 0.3554000000000000
  1: 0.3059000000000000
  2: 0.1788000000000000
  3: 0.0891000000000000
  4: 0.0425000000000000
  5: 0.0173000000000000
  6: 0.0067000000000000
  7: 0.0026000000000000
  8: 0.0012000000000000
  9: 0.0004000000000000
  10: 0.0001000000000000
  mean = 1.2599


*/
go ?=>
  reset_store,
  run_model(10_000,$model,[show_probs,mean]),
  nl,
  % show_store_lengths,
  % fail,
  nl.
go => true.
  
  
model() =>
  V = negative_binomial_dist(3,0.7),
  P = check(V >= 4),  
  add("v",V),
  add("p",P).


/*
  var : p
  Probabilities:
  false: 0.9876106194690265
  true: 0.0123893805309735
  mean = [false = 0.987611,true = 0.0123894]

  var : v
  Probabilities:
  6: 0.6088495575221239
  7: 0.2389380530973451
  8: 0.0902654867256637
  9: 0.0495575221238938
  10: 0.0088495575221239
  11: 0.0035398230088496
  mean = 6.62124


*/
go2 ?=>
  reset_store,
  run_model(50_000,$model2,[show_probs,mean]),
  nl,
  % show_store_lengths,
  % fail,
  nl.
go2 => true.
  
  
model2() =>
  V = negative_binomial_dist(3,0.7),
  observe(V > 5),
  P = check(V >= 10),
  if observed_ok then
    add("v",V),
    add("p",P)
  end.