import * as Chai from 'chai';
import Svm from '../lib/core/engine/svm'

const should = Chai.should();

const circularDataset = {
  points: [
    [ 77.08537142627756, 60.7455136985482 ],
    [ 54.94324221651883, 63.78584077042318 ],
    [ 45.124087171506936, 80.97650097253724 ],
    [ 62.00480777917741, 49.642444449970675 ],
    [ 56.958382663885864, 81.27710664286386 ],
    [ 52.72767259658451, 66.03517399586579 ],
    [ 19.518515661340157, 35.12014495118882 ],
    [ 58.87894639269981, 59.27927960679746 ],
    [ 13.59822313333904, 61.66342807818599 ],
    [ 37.01348768362775, 54.679365456721584 ],
    [ 85.01654232561876, 46.57532675823407 ],
    [ 34.70627848361286, 44.84248665899513 ],
    [ 63.443893468418494, 74.07028656564599 ],
    [ 61.456705623249455, 41.09439124577563 ],
    [ 84.26782294646438, 26.269714017498337 ],
    [ 37.44407046741475, 50.98956479733988 ],
    [ 37.53801531593166, 79.73505569185346 ],
    [ 61.308207468398585, 44.41090753575729 ],
    [ 49.57073028314457, 5.715350047914129 ],
    [ 63.640430592148775, 39.56876863124383 ]
  ],
  labels: [
     1, -1,  1, -1,  1, -1,  1,
    -1,  1, -1,  1, -1,  1, -1,
     1, -1,  1, -1,  1, -1
  ]
}

const svm = new Svm(circularDataset, 5, 'RBF', 15 );

/**
 * Engine#SVM related tests
 */
describe('testing support vector machine', () => {
    
    it('should classify data correctly', () => {
      const positiveResult = svm.predict([0,0]);
      const negativeResult = svm.predict([50,50]);
      positiveResult.should.equal(1);
      negativeResult.should.equal(-1);
    });
});