def test_example_3(self): example = """ NN EE — -10 5 0 5 10 Favours [Pedicle Screw] Favours [Hybrid Instrumentation] """ groups, mid_scale = SPSSForestPlot._decode_footer_scale_ocr(example) self.assertEqual(groups, ("Pedicle Screw", "Hybrid Instrumentation")) self.assertEqual(mid_scale, 0.0)
def test_example_4(self): example = 'Heterogeneity: Chi? = 15.08, df= 10 (P = 0.13);\n‘Test for overall effect: Z = 9.01 (P < 0.00001)\n\n\n\n' hetrogeneity, overall_effect = SPSSForestPlot._decode_footer_summary_ocr( example) self.assertEqual(dict(hetrogeneity), { "Chi": 15.08, "df": 10.0, "P": 0.13 }) self.assertEqual(overall_effect, {"Z": 9.01, "P": 0.00001})
def test_example_6(self): example = 'Heterogeneity: Chi? = 2.11, df = 5 (P = 0.83); 7 = 0%\nTest for overall effect: Z = 3.80 (P = 0.0001)\n\n' hetrogeneity, overall_effect = SPSSForestPlot._decode_footer_summary_ocr( example) self.assertEqual(dict(hetrogeneity), { "Chi": 2.11, "df": 5.0, "P": 0.83, "I": 0.0 }) self.assertEqual(overall_effect, {"Z": 3.8, "P": 0.0001})
def test_example_2(self): example = 'Heterogeneity: Chi? = 2.07, df= 10 (P= 1.00); /7= 0%\nTest for overall effect: Z= 1.13 (P = 0.26)\n\x0c' hetrogeneity, overall_effect = SPSSForestPlot._decode_footer_summary_ocr( example) self.assertEqual(dict(hetrogeneity), { "Chi": 2.07, "df": 10.0, "P": 1.00, "I": 0.0 }) self.assertEqual(overall_effect, {"Z": 1.13, "P": 0.26})
def test_example_1(self): example = 'Heterogeneity: Tau? = 0.00; Chi? = 2.98, df= 4 (P = 0.56), I= 0% |\nTest for overall effect: Z= 3.12' hetrogeneity, overall_effect = SPSSForestPlot._decode_footer_summary_ocr( example) self.assertEqual(dict(hetrogeneity), { "Tau": 0.00, "Chi": 2.98, "df": 4, "P": 0.56, "I": 0.0 }) self.assertEqual(overall_effect, {"Z": 3.12})
def test_lines_example_1(self): example = [ "Chua D (2010) 15 47 9 48 8.9% 1.70 (0.83, 3.50)", "Dou-Dou Li (2015) 9 18 § 18 7.4% 1.80 (0.75, 4.32)", "Fei Teng (2017) 22 26 6 26 9.0% 3.53 (1.72, 7.22]", ] titles, values = SPSSForestPlot._decode_table_lines_ocr(example) self.assertEqual( titles, ["Chua D (2010)", "Dou-Dou Li (2015)", "Fei Teng (2017)"]) self.assertEqual(values, [ (1.7, 0.83, 3.5), (1.8, 0.75, 4.32), (3.53, 1.72, 7.22), ])
def test_example_1(self): example = 'Odds Ratio\nM-H. Fixed. 95% Cl\n\x0c' values = SPSSForestPlot._decode_header_summary_ocr(example) self.assertEqual(values, ("M-H", "Fixed", "95"))
def test_example_4(self): example = "Mean Difference\nTV. Random. 95% CI\n" values = SPSSForestPlot._decode_header_summary_ocr(example) self.assertEqual(values, ("IV", "Random", "95"))
def test_example_3(self): example = 'Mean Difference\n1V. Fixed, 95% Cl\n' values = SPSSForestPlot._decode_header_summary_ocr(example) self.assertEqual(values, ("IV", "Fixed", "95"))
def test_example_2(self): example = 'Mean Difference\nIV. Random. 95% Cl\n\x0c' values = SPSSForestPlot._decode_header_summary_ocr(example) self.assertEqual(values, ("IV", "Random", "95"))