def testGenerate(self):
generate = SvcFGs.generate()
self.X[:, 15:25] = self.X[:, 15:25]*100
svc = generate()
svc.setWaveletInds(numpy.arange(100))
svc.learnModel(self.X, self.y)
self.assertEquals(numpy.intersect1d(numpy.arange(15,25), svc.getFeatureInds()).shape[0], 10)
predY = svc.predict(self.X)
#Now test when all features are wavelets
svc = generate()
svc.learnModel(self.X, self.y)
self.assertEquals(numpy.intersect1d(numpy.arange(15,25), svc.getFeatureInds()).shape[0], 10)
predY = svc.predict(self.X)
def testSetWeight(self):
learner = SvcFGs()
learner.setWeight(0.8)