mirror of
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235 lines
8.5 KiB
Python
235 lines
8.5 KiB
Python
import os
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import unittest
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from io import StringIO
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from unittest.mock import patch
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from ..Results import Summary
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from ..Utils import Symbols
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class SummaryTest(unittest.TestCase):
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def __init__(self, *args, **kwargs):
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os.chdir(os.path.dirname(os.path.abspath(__file__)))
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super().__init__(*args, **kwargs)
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def test_summary_without_model(self):
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report = Summary()
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report.acquire()
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computed = report.best_results(score="accuracy")
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expected = [
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{
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"score": "accuracy",
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"model": "STree",
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"title": "With gridsearched hyperparameters",
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"platform": "iMac27",
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"date": "2021-09-30",
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"time": "11:42:07",
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"stratified": "0",
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"file": "results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json",
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"metric": 0.04544339345094904,
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"duration": 624.2505249977112,
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},
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{
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"score": "accuracy",
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"model": "ODTE",
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"title": "Gridsearched hyperparams v022.1b random_init",
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"platform": "Galgo",
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"date": "2022-04-20",
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"time": "10:52:20",
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"stratified": "0",
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"file": "results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json",
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"metric": 0.04340676203831255,
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"duration": 22591.471411943436,
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},
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{
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"score": "accuracy",
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"model": "STree",
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"title": "default A",
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"platform": "iMac27",
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"date": "2021-10-27",
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"time": "09:40:40",
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"stratified": "0",
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"file": "results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json",
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"metric": 0.04158163842230773,
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"duration": 3395.009148836136,
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},
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{
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"score": "accuracy",
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"model": "STree",
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"title": "default B",
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"platform": "macbook-pro",
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"date": "2021-11-01",
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"time": "19:17:07",
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"stratified": "0",
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"file": "results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json",
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"metric": 0.03789928437296904,
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"duration": 4115.042420864105,
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},
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{
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"score": "accuracy",
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"model": "RandomForest",
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"title": "Test default paramters with RandomForest",
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"platform": "iMac27",
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"date": "2022-01-14",
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"time": "12:39:30",
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"stratified": "0",
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"file": "results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json",
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"metric": 0.03627309062515771,
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"duration": 272.7363500595093,
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},
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]
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self.assertListEqual(computed, expected)
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def test_summary_with_model(self):
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report = Summary()
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report.acquire()
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computed = report.best_results(
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criterion="model", value="STree", score="accuracy"
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)
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expected = [
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{
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"score": "accuracy",
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"model": "STree",
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"title": "With gridsearched hyperparameters",
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"platform": "iMac27",
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"date": "2021-09-30",
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"time": "11:42:07",
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"stratified": "0",
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"file": "results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json",
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"metric": 0.04544339345094904,
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"duration": 624.2505249977112,
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},
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{
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"score": "accuracy",
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"model": "STree",
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"title": "default A",
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"platform": "iMac27",
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"date": "2021-10-27",
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"time": "09:40:40",
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"stratified": "0",
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"file": "results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json",
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"metric": 0.04158163842230773,
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"duration": 3395.009148836136,
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},
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{
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"score": "accuracy",
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"model": "STree",
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"title": "default B",
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"platform": "macbook-pro",
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"date": "2021-11-01",
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"time": "19:17:07",
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"stratified": "0",
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"file": "results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json",
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"metric": 0.03789928437296904,
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"duration": 4115.042420864105,
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},
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]
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self.assertListEqual(computed, expected)
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def test_summary_list_results_model(self):
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report = Summary()
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report.acquire()
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with patch("sys.stdout", new=StringIO()) as fake_out:
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report.list_results(model="STree")
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computed = fake_out.getvalue()
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with open(
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os.path.join("test_files", "summary_list_model.test"), "r"
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) as f:
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expected = f.read()
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self.assertEqual(computed, expected)
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def test_summary_list_results_score(self):
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report = Summary()
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report.acquire()
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with patch("sys.stdout", new=StringIO()) as fake_out:
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report.list_results(score="accuracy")
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computed = fake_out.getvalue()
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with open(
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os.path.join("test_files", "summary_list_score.test"), "r"
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) as f:
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expected = f.read()
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self.assertEqual(computed, expected)
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def test_summary_list_results_n(self):
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report = Summary()
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report.acquire()
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with patch("sys.stdout", new=StringIO()) as fake_out:
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report.list_results(score="accuracy", number=3)
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computed = fake_out.getvalue()
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with open(os.path.join("test_files", "summary_list_n.test"), "r") as f:
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expected = f.read()
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self.assertEqual(computed, expected)
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def test_summary_list_hiden(self):
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report = Summary(hidden=True)
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report.acquire()
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with patch("sys.stdout", new=StringIO()) as fake_out:
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report.list_results(score="accuracy")
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computed = fake_out.getvalue()
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with open(
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os.path.join("test_files", "summary_list_hidden.test"), "r"
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) as f:
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expected = f.read()
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self.assertEqual(computed, expected)
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def test_show_result_no_title(self):
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report = Summary()
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report.acquire()
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with patch("sys.stdout", new=StringIO()) as fake_out:
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title = ""
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best = report.best_result(
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criterion="model", value="STree", score="accuracy"
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)
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report.show_result(data=best, title=title)
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computed = fake_out.getvalue()
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with open(
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os.path.join("test_files", "summary_show_results.test"), "r"
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) as f:
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expected = f.read()
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self.assertEqual(computed, expected)
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def test_show_result_title(self):
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report = Summary()
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report.acquire()
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with patch("sys.stdout", new=StringIO()) as fake_out:
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title = "**Title**"
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best = report.best_result(
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criterion="model", value="STree", score="accuracy"
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)
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report.show_result(data=best, title=title)
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computed = fake_out.getvalue()
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with open(
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os.path.join("test_files", "summary_show_results_title.test"), "r"
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) as f:
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expected = f.read()
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self.assertEqual(computed, expected)
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def test_show_result_no_data(self):
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report = Summary()
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report.acquire()
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with patch("sys.stdout", new=StringIO()) as fake_out:
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title = "**Test**"
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report.show_result(data={}, title=title)
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computed = fake_out.getvalue()
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expected = f"** **Test** has No data **\n"
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self.assertEqual(computed, expected)
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def test_best_results_datasets(self):
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report = Summary()
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report.acquire()
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computed = report.best_results_datasets()
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expected = {
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"balance-scale": (
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0.83616,
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{},
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"results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json",
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"Test default paramters with RandomForest",
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),
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"balloons": (
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0.5566666666666668,
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{"max_features": "auto", "splitter": "mutual"},
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"results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json",
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"default B",
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),
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}
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self.assertSequenceEqual(computed, expected)
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