def get_test_error(self):
data, filenames = self.get_test_patches_and_filenames()
if self.test_on_images:
print 'testing on images'
probabilities, test_results = self.get_predictions(data)
fileProbs, fileLabels, fileIDs = ModelEvaluation.GetUnormalizedJointLogProbability(probabilities, data[1].reshape(-1), filenames)
filePredictions = ModelEvaluation.GetPredictions(fileProbs)
fileAccuracy, misclassifiedFiles = ModelEvaluation.CalculateAccuracy(filePredictions, fileLabels)
nExamples = test_results[1]
results = ({'logprob' : [test_results[0]['logprob'][0], (1-fileAccuracy) * test_results[1]]}, test_results[1])
if self.test_only: # Print the individual batch results for safety
print str(results)
else:
print 'not testing on images'
self.libmodel.startBatch(data, True)
results = self.finish_batch()
self.regular_test_outputs += [IGPUModel.get_test_error(self)]
return results
