""" Unit tests for the StatsAnalysis class in fdj_slayer.stats module """ import unittest from unittest.mock import patch import math from fdj_slayer.stats import StatsAnalysis class TestStatsAnalysis(unittest.TestCase): """Tests for the StatsAnalysis class""" def setUp(self): """Set up test fixtures before each test method""" self.stats_analyzer = StatsAnalysis( max_number=50, max_star=12, number_of_numbers=5, number_of_stars=2) self.sample_draws = [ {'numbers': [1, 10, 20, 30, 40], 'stars': [1, 10]}, {'numbers': [5, 15, 25, 35, 45], 'stars': [5, 12]}, {'numbers': [2, 12, 22, 32, 42], 'stars': [2, 11]}, {'numbers': [3, 13, 23, 33, 43], 'stars': [3, 8]}, {'numbers': [4, 14, 24, 34, 44], 'stars': [4, 9]} ] def test_init(self): """Test initialization with correct parameters""" self.assertEqual(self.stats_analyzer.max_number, 50) self.assertEqual(self.stats_analyzer.max_star, 12) self.assertEqual(self.stats_analyzer.number_of_numbers, 5) self.assertEqual(self.stats_analyzer.number_of_stars, 2) def test_extract_numbers_and_stars(self): """Test extraction of numbers and stars from draws""" all_numbers, all_stars = self.stats_analyzer._extract_numbers_and_stars( self.sample_draws) expected_numbers = [1, 10, 20, 30, 40, 5, 15, 25, 35, 45, 2, 12, 22, 32, 42, 3, 13, 23, 33, 43, 4, 14, 24, 34, 44] expected_stars = [1, 10, 5, 12, 2, 11, 3, 8, 4, 9] self.assertEqual(sorted(all_numbers), sorted(expected_numbers)) self.assertEqual(sorted(all_stars), sorted(expected_stars)) def test_calculate_frequencies(self): """Test frequency calculation""" values = [1, 2, 2, 3, 3, 3, 4, 4, 4, 4] max_value = 5 frequencies = self.stats_analyzer._calculate_frequencies( values, max_value) self.assertEqual(frequencies, {1: 1, 2: 2, 3: 3, 4: 4, 5: 0}) self.assertEqual(sum(frequencies.values()), len(values)) def test_find_min_max_frequencies(self): """Test finding minimum and maximum frequencies""" counts = {1: 5, 2: 3, 3: 3, 4: 10, 5: 0} min_max = self.stats_analyzer._find_min_max_frequencies(counts) self.assertEqual(min_max["min"], ([5], 0)) self.assertEqual(min_max["max"], ([4], 10)) counts = {1: 5, 2: 5, 3: 0, 4: 0, 5: 10, 6: 10} min_max = self.stats_analyzer._find_min_max_frequencies(counts) self.assertEqual(sorted(min_max["min"][0]), [3, 4]) self.assertEqual(min_max["min"][1], 0) self.assertEqual(sorted(min_max["max"][0]), [5, 6]) self.assertEqual(min_max["max"][1], 10) def test_calculate_statistics(self): """Test statistics calculation""" counts = {1: 5, 2: 10, 3: 15} expected_freq = 10 min_max = {"min": ([1], 5), "max": ([3], 15)} stats_data = self.stats_analyzer._calculate_statistics( counts, expected_freq, min_max) expected_std_dev = math.sqrt( sum((count - expected_freq)**2 for count in [5, 10, 15]) / 3) expected_variation_pct = (15 - 5) / expected_freq * 100 self.assertAlmostEqual(stats_data["std_dev"], expected_std_dev) self.assertAlmostEqual( stats_data["variation_pct"], expected_variation_pct) def test_assess_randomness(self): """Test randomness assessment based on p-value""" self.assertEqual( self.stats_analyzer._assess_randomness(0.06), "likely random") self.assertEqual(self.stats_analyzer._assess_randomness( 0.05), "possibly biased") self.assertEqual(self.stats_analyzer._assess_randomness( 0.04), "possibly biased") self.assertEqual( self.stats_analyzer._assess_randomness(0.8), "likely random") self.assertEqual(self.stats_analyzer._assess_randomness( 0.01), "possibly biased") @patch('scipy.stats.chisquare') def test_perform_chi_square_test(self, mock_chisquare): """Test chi-square test with mocked scipy function""" mock_chisquare.return_value = (1.234, 0.567) counts = {1: 5, 2: 7, 3: 9} expected_freq = 7 max_value = 3 result = self.stats_analyzer._perform_chi_square_test( counts, expected_freq, max_value) mock_chisquare.assert_called_once_with([5, 7, 9], [7, 7, 7]) self.assertEqual(result, {"chi2": 1.234, "p_value": 0.567}) def test_analyze_dataset(self): """Test dataset analysis with mocked internal methods""" values = [1, 1, 2, 2, 2, 3, 3, 4] value_type = "number" max_value = 5 with patch.object(self.stats_analyzer, '_calculate_frequencies') as mock_calc_freq, \ patch.object(self.stats_analyzer, '_perform_chi_square_test') as mock_chi2, \ patch.object(self.stats_analyzer, '_find_min_max_frequencies') as mock_min_max, \ patch.object(self.stats_analyzer, '_calculate_statistics') as mock_stats, \ patch.object(self.stats_analyzer, '_assess_randomness') as mock_assess: mock_calc_freq.return_value = {1: 2, 2: 3, 3: 2, 4: 1, 5: 0} mock_chi2.return_value = {"chi2": 2.5, "p_value": 0.6} mock_min_max.return_value = {"min": ([5], 0), "max": ([2], 3)} mock_stats.return_value = {"std_dev": 1.2, "variation_pct": 30.0} mock_assess.return_value = "likely random" results = self.stats_analyzer._analyze_dataset( values, value_type, max_value) self.assertEqual(results["number_frequencies"], { 1: 2, 2: 3, 3: 2, 4: 1, 5: 0}) self.assertEqual( results["expected_number_freq"], len(values) / max_value) self.assertEqual(results["number_chi2"], 2.5) self.assertEqual(results["p_value_numbers"], 0.6) self.assertEqual(results["min_number"], ([5], 0)) self.assertEqual(results["max_number"], ([2], 3)) self.assertEqual(results["number_std_dev"], 1.2) self.assertEqual(results["number_variation_pct"], 30.0) self.assertEqual(results["number_assessment"], "likely random") @patch.object(StatsAnalysis, '_analyze_dataset') @patch.object(StatsAnalysis, '_extract_numbers_and_stars') def test_analyze_randomness(self, mock_extract, mock_analyze): """Test analyze_randomness with mocked methods to verify method interactions""" mock_extract.return_value = ([1, 2, 3], [4, 5]) mock_analyze.side_effect = [ {"number_key": "number_value"}, {"star_key": "star_value"} ] results = self.stats_analyzer.analyze_randomness(self.sample_draws) mock_extract.assert_called_once_with(self.sample_draws) self.assertEqual(mock_analyze.call_count, 2) mock_analyze.assert_any_call([1, 2, 3], "number", 50) mock_analyze.assert_any_call([4, 5], "star", 12) self.assertEqual(results, { "sample_size": len(self.sample_draws), "number_key": "number_value", "star_key": "star_value" }) @patch('scipy.stats.chisquare') def test_analyze_randomness_integration(self, mock_chisquare): """Integration test for analyze_randomness with real data""" mock_chisquare.return_value = (2.0, 0.8) results = self.stats_analyzer.analyze_randomness(self.sample_draws) self.assertEqual(results["sample_size"], len(self.sample_draws)) self.assertIn("number_frequencies", results) self.assertIn("star_frequencies", results) self.assertEqual( len(results["number_frequencies"]), self.stats_analyzer.max_number) self.assertEqual( len(results["star_frequencies"]), self.stats_analyzer.max_star) self.assertEqual(results["number_assessment"], "likely random") self.assertEqual(results["star_assessment"], "likely random") def test_analyze_randomness_empty_draws(self): """Test behavior with empty draws list""" with self.assertRaises(ValueError): self.stats_analyzer.analyze_randomness([]) if __name__ == '__main__': unittest.main()