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"))