/*

  Iris dataset

  * With TotalApprox = 4 (res should be 2)

    [program = 6.803754343094191 - 5.968800669521466 + PW,res = 2.234953673572725,count = 1]


  * TotalApprox = 5 (res should be 2)

    [program = PW + if_then_else(-6.048972614132321,5.661984475172117,6.803754343094191 + -6.048972614132321),res = 2.15478172896187,count = 72]
    [program = if_then_else(-6.048972614132321,5.661984475172117,6.803754343094191 + -6.048972614132321) + PW,res = 2.15478172896187,count = 70]
    [program = if_then_else(-6.048972614132321,5.661984475172117,6.803754343094191 + -6.048972614132321) + if_then_else(5.661984475172117,SW * SL,PW),res = 2.15478172896187,count = 60]
    [program = if_then_else(-6.048972614132321,5.661984475172117,6.803754343094191 + -6.048972614132321) + if_then_else(PL,PW,PW),res = 2.15478172896187,count = 39]
    [program = if_then_else(-6.048972614132321,5.661984475172117,6.803754343094191 + -6.048972614132321) + if_then_else(5.36459189623808,-2.112341463618139,PW),res = 2.15478172896187,count = 20]
    [program = if_then_else(5.661984475172117,SW * SL,PW) + if_then_else(-6.048972614132321,5.661984475172117,6.803754343094191 + -6.048972614132321),res = 2.15478172896187,count = 6]
    [program = if_then_else(PL,PW,PW) + if_then_else(-6.048972614132321,5.661984475172117,6.803754343094191 + -6.048972614132321),res = 2.15478172896187,count = 5]
    [program = if_then_else(-6.048972614132321,5.661984475172117,6.803754343094191 + -6.048972614132321) + if_then_else(PL + 8.232947158735687,5.661984475172117,PW),res = 2.15478172896187,count = 4]
    [program = if_then_else(-6.048972614132321 * (PW + -4.444505783936244 + 8.232947158735687),SW,PW) + if_then_else(-6.048972614132321,5.661984475172117,6.803754343094191 + -6.048972614132321),res = 2.15478172896187,count = 1]
    [program = if_then_else(5.36459189623808,-2.112341463618139,PW) + if_then_else(-6.048972614132321,5.661984475172117,6.803754343094191 + -6.048972614132321),res = 2.15478172896187,count = 1]

    resultMap = [2.15478172896187 = 10]

  * TotalApprox = 5 and if_less  (res should be 1)
    [program = PW + (-6.048972614132321 + 6.803754343094191),res = 0.95478172896187,count = 90]
    [program = -6.048972614132321 + 6.803754343094191 + PW,res = 0.95478172896187,count = 82]
    [program = -6.048972614132321 + 6.803754343094191 + 1.079399115908611 * PW,res = 0.970661552143592,count = 53]
    [program = 1.079399115908611 * PW + (-6.048972614132321 + 6.803754343094191),res = 0.970661552143592,count = 52]
    [program = -6.048972614132321 + 6.803754343094191 + if_less(PL - PL,5.36459189623808,PW,5.968800669521466),res = 0.95478172896187,count = 28]
    [program = -6.048972614132321 + 6.803754343094191 + if_less(PL,5.661984475172117 + SL,PW,5.968800669521466 + 8.232947158735687),res = 0.95478172896187,count = 10]
    [program = -6.048972614132321 + 6.803754343094191 + if_less(SW,-4.444505783936244,1.079399115908611,PW),res = 0.95478172896187,count = 2]
    [program = if_less(5.968800669521466,SW,PW,PW) + (-6.048972614132321 + 6.803754343094191),res = 0.95478172896187,count = 1]

    resultMap = [0.95478172896187 = 6,0.970661552143592 = 2]

     [program = -2.112341463618139 - -3.29554488570222 + PW + (5.36459189623808 - 5.661984475172117),res = 1.085810843150043,count = 58]
     [program = 5.36459189623808 - 5.661984475172117 + (-2.112341463618139 - -3.29554488570222 + PW),res = 1.085810843150043,count = 46]
     [program = PW * 1.079399115908611 - (5.36459189623808 + round(-6.048972614132321)),res = 0.851287926943642,count = 43]
     [program = 1.079399115908611 + PW + (5.36459189623808 - 5.661984475172117),res = 0.982006536974574,count = 11]
     [program = 5.36459189623808 - 5.661984475172117 + (1.079399115908611 + PW),res = 0.982006536974574,count = 1]

     resultMap = [1.085810843150043 = 2,0.982006536974574 = 2,0.851287926943642 = 1]


  Cf iris.conf

*/
import util.
data(iris,Data,Vars,Unknown,Ops,Constants,MaxSize,Params) :-
  Data =  [ [[A,B,C,D],E] : [A,B,C,D,E] in chunks_of([
5.1,3.5,1.4,0.2,1,
4.9,3.0,1.4,0.2,1,
4.7,3.2,1.3,0.2,1,
4.6,3.1,1.5,0.2,1,
5.0,3.6,1.4,0.2,1,
5.4,3.9,1.7,0.4,1,
4.6,3.4,1.4,0.3,1,
5.0,3.4,1.5,0.2,1,
4.4,2.9,1.4,0.2,1,
4.9,3.1,1.5,0.1,1,
5.4,3.7,1.5,0.2,1,
4.8,3.4,1.6,0.2,1,
4.8,3.0,1.4,0.1,1,
4.3,3.0,1.1,0.1,1,
5.8,4.0,1.2,0.2,1,
5.7,4.4,1.5,0.4,1,
5.4,3.9,1.3,0.4,1,
5.1,3.5,1.4,0.3,1,
5.7,3.8,1.7,0.3,1,
5.1,3.8,1.5,0.3,1,
5.4,3.4,1.7,0.2,1,
5.1,3.7,1.5,0.4,1,
4.6,3.6,1.0,0.2,1,
5.1,3.3,1.7,0.5,1,
4.8,3.4,1.9,0.2,1,
5.0,3.0,1.6,0.2,1,
5.0,3.4,1.6,0.4,1,
5.2,3.5,1.5,0.2,1,
5.2,3.4,1.4,0.2,1,
4.7,3.2,1.6,0.2,1,
4.8,3.1,1.6,0.2,1,
5.4,3.4,1.5,0.4,1,
5.2,4.1,1.5,0.1,1,
5.5,4.2,1.4,0.2,1,
4.9,3.1,1.5,0.1,1,
5.0,3.2,1.2,0.2,1,
5.5,3.5,1.3,0.2,1,
4.9,3.1,1.5,0.1,1,
4.4,3.0,1.3,0.2,1,
5.1,3.4,1.5,0.2,1,
5.0,3.5,1.3,0.3,1,
4.5,2.3,1.3,0.3,1,
4.4,3.2,1.3,0.2,1,
5.0,3.5,1.6,0.6,1,
5.1,3.8,1.9,0.4,1,
4.8,3.0,1.4,0.3,1,
5.1,3.8,1.6,0.2,1,
4.6,3.2,1.4,0.2,1,
5.3,3.7,1.5,0.2,1,
5.0,3.3,1.4,0.2,1,

7.0,3.2,4.7,1.4,2,
6.4,3.2,4.5,1.5,2,
6.9,3.1,4.9,1.5,2,
5.5,2.3,4.0,1.3,2,
6.5,2.8,4.6,1.5,2,
5.7,2.8,4.5,1.3,2,
6.3,3.3,4.7,1.6,2,
4.9,2.4,3.3,1.0,2,
6.6,2.9,4.6,1.3,2,
5.2,2.7,3.9,1.4,2,
5.0,2.0,3.5,1.0,2,
5.9,3.0,4.2,1.5,2,
6.0,2.2,4.0,1.0,2,
6.1,2.9,4.7,1.4,2,
5.6,2.9,3.6,1.3,2,
6.7,3.1,4.4,1.4,2,
5.6,3.0,4.5,1.5,2,
5.8,2.7,4.1,1.0,2,
6.2,2.2,4.5,1.5,2,
5.6,2.5,3.9,1.1,2,
5.9,3.2,4.8,1.8,2,
6.1,2.8,4.0,1.3,2,
6.3,2.5,4.9,1.5,2,
6.1,2.8,4.7,1.2,2,
6.4,2.9,4.3,1.3,2,
6.6,3.0,4.4,1.4,2,
6.8,2.8,4.8,1.4,2,
6.7,3.0,5.0,1.7,2,
6.0,2.9,4.5,1.5,2,
5.7,2.6,3.5,1.0,2,
5.5,2.4,3.8,1.1,2,
5.5,2.4,3.7,1.0,2,
5.8,2.7,3.9,1.2,2,
6.0,2.7,5.1,1.6,2,
5.4,3.0,4.5,1.5,2,
6.0,3.4,4.5,1.6,2,
6.7,3.1,4.7,1.5,2,
6.3,2.3,4.4,1.3,2,
5.6,3.0,4.1,1.3,2,
5.5,2.5,4.0,1.3,2,
5.5,2.6,4.4,1.2,2,
6.1,3.0,4.6,1.4,2,
5.8,2.6,4.0,1.2,2,
5.0,2.3,3.3,1.0,2,
5.6,2.7,4.2,1.3,2,
5.7,3.0,4.2,1.2,2,
5.7,2.9,4.2,1.3,2,
6.2,2.9,4.3,1.3,2,
5.1,2.5,3.0,1.1,2,
5.7,2.8,4.1,1.3,2,

6.3,3.3,6.0,2.5,3,
5.8,2.7,5.1,1.9,3,
7.1,3.0,5.9,2.1,3,
6.3,2.9,5.6,1.8,3,
6.5,3.0,5.8,2.2,3,
7.6,3.0,6.6,2.1,3,
4.9,2.5,4.5,1.7,3,
7.3,2.9,6.3,1.8,3,
6.7,2.5,5.8,1.8,3,
7.2,3.6,6.1,2.5,3,
6.5,3.2,5.1,2.0,3,
6.4,2.7,5.3,1.9,3,
6.8,3.0,5.5,2.1,3,
5.7,2.5,5.0,2.0,3,
5.8,2.8,5.1,2.4,3,
6.4,3.2,5.3,2.3,3,
6.5,3.0,5.5,1.8,3,
7.7,3.8,6.7,2.2,3,
7.7,2.6,6.9,2.3,3,
6.0,2.2,5.0,1.5,3,
6.9,3.2,5.7,2.3,3,
5.6,2.8,4.9,2.0,3,
7.7,2.8,6.7,2.0,3,
6.3,2.7,4.9,1.8,3,
6.7,3.3,5.7,2.1,3,
7.2,3.2,6.0,1.8,3,
6.2,2.8,4.8,1.8,3,
6.1,3.0,4.9,1.8,3,
6.4,2.8,5.6,2.1,3,
7.2,3.0,5.8,1.6,3,
7.4,2.8,6.1,1.9,3,
7.9,3.8,6.4,2.0,3,
6.4,2.8,5.6,2.2,3,
6.3,2.8,5.1,1.5,3,
6.1,2.6,5.6,1.4,3,
7.7,3.0,6.1,2.3,3,
6.3,3.4,5.6,2.4,3,
6.4,3.1,5.5,1.8,3,
6.0,3.0,4.8,1.8,3,
6.9,3.1,5.4,2.1,3,
6.7,3.1,5.6,2.4,3,
6.9,3.1,5.1,2.3,3,
5.8,2.7,5.1,1.9,3,
6.8,3.2,5.9,2.3,3,
6.7,3.3,5.7,2.5,3,
6.7,3.0,5.2,2.3,3,
6.3,2.5,5.0,1.9,3,
6.5,3.0,5.2,2.0,3,
6.2,3.4,5.4,2.3,3,
5.9,3.0,5.1,1.8,3
 
],5)],
  % Unknown = [7.0,3.2,4.7,1.4], % should be 2
  Unknown = [4.4,3.2,1.3,0.2], % should be 1
  Vars = ['SL','SW','PL','PW' ],
  Ops = [+,-,*,if_less_than,if_then_else,<=,round],
  % Ops = [+,-,*,if_less,round],    
  Constants = [frand(-10,10) : _ in 1..10],
  MaxSize = 31,
  Params = new_map([
                    approx=0.49, % it has a somewhat close solution for the instance
                    total_approx=5, % total sum of errors
                    show_best=3,
                    init_size=500,
                    num_gens=100,
                    show_only_improvements=true
                    % ,debug=true
                    % ,show_instances=true
                    % ,show_errors=true
                    % mutation_rate=0.5 % from iris.conf
                    % , stop_criteria=loop
                    ]).