+ " gradientNorm =" + gradientNorm); assertTrue("Value should be 35770 but is" + optimizableValue, Math .abs(optimizableValue + 35770) < 0.001); assertTrue(Math.abs(gradientNorm - 520) < 0.001);
+ " gradientNorm =" + gradientNorm); assertTrue("Value should be 35770 but is" + optimizableValue, Math .abs(optimizableValue + 35770) < 0.001); assertTrue(Math.abs(gradientNorm - 520) < 0.001);
assertTrue(notstartFound); assertTrue(!notstartFound);
assertTrue(notstartFound); assertTrue(!notstartFound);
assertTrue("Final zero-order likelihood <" + lik1 + "> greater than first-order <" + lik2 + ">", lik1 < lik2); assertTrue("Final defaults-only likelihood <" + lik2 + "> greater than full first-order <" + lik3 + ">", lik2 < lik3);
assertTrue("Final zero-order likelihood <" + lik1 + "> greater than first-order <" + lik2 + ">", lik1 < lik2); assertTrue("Final defaults-only likelihood <" + lik2 + "> greater than full first-order <" + lik3 + ">", lik2 < lik3);
assertTrue(lattice.getGammaProbability(0, crf.getState(0)) == 1.0); assertTrue(lattice.getGammaProbability(0, crf.getState(1)) == 0.0); assertTrue(lattice.getGammaProbability(1, crf.getState(0)) == 0.0); assertTrue(lattice.getGammaProbability(1, crf.getState(1)) == 1.0); assertTrue(lattice .getXiProbability(1, crf.getState(1), crf.getState(1)) == 1.0); assertTrue(lattice .getXiProbability(1, crf.getState(1), crf.getState(0)) == 0.0); assertTrue("Lattice weight = " + lattice.getTotalWeight(), lattice .getTotalWeight() == 4.0);
assertTrue(lattice.getGammaProbability(0, crf.getState(0)) == 1.0); assertTrue(lattice.getGammaProbability(0, crf.getState(1)) == 0.0); assertTrue(lattice.getGammaProbability(1, crf.getState(0)) == 0.0); assertTrue(lattice.getGammaProbability(1, crf.getState(1)) == 1.0); assertTrue(lattice .getXiProbability(1, crf.getState(1), crf.getState(1)) == 1.0); assertTrue(lattice .getXiProbability(1, crf.getState(1), crf.getState(0)) == 0.0); assertTrue("Lattice weight = " + lattice.getTotalWeight(), lattice .getTotalWeight() == 4.0);
Sequence<Transducer.State> viterbiPath = lattice.bestStateSequence(); assertTrue(viterbiPath.get(0) == crf.getState(0)); assertTrue(viterbiPath.get(1) == crf.getState(1)); assertTrue(viterbiPath.get(2) == crf.getState(1));
Sequence<Transducer.State> viterbiPath = lattice.bestStateSequence(); assertTrue(viterbiPath.get(0) == crf.getState(0)); assertTrue(viterbiPath.get(1) == crf.getState(1)); assertTrue(viterbiPath.get(2) == crf.getState(1));
double val1 = optable1.getValue(); double val2 = optable2.getValue(); assertTrue( "Error: Freezing weights does not harm log-likelihood! Full " + val1 + ", Frozen " + val2, val1 > val2);
double val1 = optable1.getValue(); double val2 = optable2.getValue(); assertTrue( "Error: Freezing weights does not harm log-likelihood! Full " + val1 + ", Frozen " + val2, val1 > val2);