def assert_estimation(self, tp, tn, fp, fn, total, positives, negatives, fitness): assert_that(self.sut.true_positive, is_(equal_to(tp))) assert_that(self.sut.true_negative, is_(equal_to(tn))) assert_that(self.sut.false_positive, is_(equal_to(fp))) assert_that(self.sut.false_negative, is_(equal_to(fn))) assert_that(self.sut.total, is_(equal_to(total))) assert_that(self.sut.positives_that_has_occurred, is_(equal_to(positives))) assert_that(self.sut.negatives_that_has_occurred, is_(equal_to(negatives))) assert_nearly_equal_or_both_nan(self.sut.fitness, fitness)
def assert_estimation(self, n_success, n_evals, s, min_evals): assert_that(self.sut.n_success, is_(equal_to(n_success))) assert_nearly_equal_or_both_nan(self.sut.n_evals, n_evals) assert_nearly_equal_or_both_nan(self.sut.s, s) assert_nearly_equal_or_both_nan(self.sut.min_evals, min_evals)
def assert_estimation(self, step, fitness, miss_rate, fallout, sensitivity, specificity, accuracy, min_fitness, max_fitness, min_miss_rate, max_miss_rate, min_fallout, max_fallout, min_sensitivity, max_sensitivity, min_specificity, max_specificity, min_accuracy, max_accuracy, average_fitness, average_miss_rate, average_fallout, average_sensitivity, average_specificity, average_accuracy, global_min_fitness, global_min_miss_rate, global_min_fallout, global_min_sensitivity, global_min_specificity, global_min_accuracy, global_max_fitness, global_max_miss_rate, global_max_fallout, global_max_sensitivity, global_max_specificity, global_max_accuracy, estimator=None): fit = 'fitness' mis = 'missrate' fal = 'fallout' sen = 'sensitivity' spe = 'specificity' acc = 'accuracy' estimator = estimator if estimator is not None else self.sut assert_nearly_equal_or_both_nan(estimator[fit].get(step), fitness) assert_nearly_equal_or_both_nan(estimator[mis].get(step), miss_rate) assert_nearly_equal_or_both_nan(estimator[fal].get(step), fallout) assert_nearly_equal_or_both_nan(estimator[sen].get(step), sensitivity) assert_nearly_equal_or_both_nan(estimator[spe].get(step), specificity) assert_nearly_equal_or_both_nan(estimator[acc].get(step), accuracy) assert_nearly_equal_or_both_nan(estimator[fit].get_min(step), min_fitness) assert_nearly_equal_or_both_nan(estimator[fit].get_max(step), max_fitness) assert_nearly_equal_or_both_nan(estimator[mis].get_min(step), min_miss_rate) assert_nearly_equal_or_both_nan(estimator[mis].get_max(step), max_miss_rate) assert_nearly_equal_or_both_nan(estimator[fal].get_min(step), min_fallout) assert_nearly_equal_or_both_nan(estimator[fal].get_max(step), max_fallout) assert_nearly_equal_or_both_nan(estimator[sen].get_min(step), min_sensitivity) assert_nearly_equal_or_both_nan(estimator[sen].get_max(step), max_sensitivity) assert_nearly_equal_or_both_nan(estimator[spe].get_min(step), min_specificity) assert_nearly_equal_or_both_nan(estimator[spe].get_max(step), max_specificity) assert_nearly_equal_or_both_nan(estimator[acc].get_min(step), min_accuracy) assert_nearly_equal_or_both_nan(estimator[acc].get_max(step), max_accuracy) assert_nearly_equal_or_both_nan(estimator[fit].get_global_average(), average_fitness) assert_nearly_equal_or_both_nan(estimator[mis].get_global_average(), average_miss_rate) assert_nearly_equal_or_both_nan(estimator[fal].get_global_average(), average_fallout) assert_nearly_equal_or_both_nan(estimator[sen].get_global_average(), average_sensitivity) assert_nearly_equal_or_both_nan(estimator[spe].get_global_average(), average_specificity) assert_nearly_equal_or_both_nan(estimator[acc].get_global_average(), average_accuracy) assert_nearly_equal_or_both_nan(estimator[fit].get_global_min(), global_min_fitness) assert_nearly_equal_or_both_nan(estimator[mis].get_global_min(), global_min_miss_rate) assert_nearly_equal_or_both_nan(estimator[fal].get_global_min(), global_min_fallout) assert_nearly_equal_or_both_nan(estimator[sen].get_global_min(), global_min_sensitivity) assert_nearly_equal_or_both_nan(estimator[spe].get_global_min(), global_min_specificity) assert_nearly_equal_or_both_nan(estimator[acc].get_global_min(), global_min_accuracy) assert_nearly_equal_or_both_nan(estimator[fit].get_global_max(), global_max_fitness) assert_nearly_equal_or_both_nan(estimator[mis].get_global_max(), global_max_miss_rate) assert_nearly_equal_or_both_nan(estimator[fal].get_global_max(), global_max_fallout) assert_nearly_equal_or_both_nan(estimator[sen].get_global_max(), global_max_sensitivity) assert_nearly_equal_or_both_nan(estimator[spe].get_global_max(), global_max_specificity) assert_nearly_equal_or_both_nan(estimator[acc].get_global_max(), global_max_accuracy)