Switched to using assert_frame_equal to avoid rounding errors

Author: jmafoster1

tests/main_tests/test_ctf.py

@@ -207,5 +207,4 @@ def test_ctf_evaluate_dag_inestimable(self):
                 "PASS_ci_low": 0,
             }
         ).sort_index()
-        print(results)
         pd.testing.assert_series_equal(results, expected)

tests/testing_tests/test_causal_test_adequacy.py

@@ -138,76 +138,78 @@ def test_to_dict(self):
         )
         adequacy_metric = causal_test_case.measure_adequacy(self.df, bootstrap_size=10)
 
-        self.assertEqual(
-            adequacy_metric.to_dict(include_results=True),
-            {
-                "kurtosis": {"test_input": 0.0},
-                "passing": 10,
-                "successful": 10,
-                "results": {
-                    "effect_estimate": {
-                        0: -2.220446049250313e-16,
-                        1: -1.1102230246251565e-16,
-                        2: 7.632783294297951e-17,
-                        3: 5.551115123125783e-17,
-                        4: 6.938893903907228e-17,
-                        5: 5.551115123125783e-17,
-                        6: 4.163336342344337e-17,
-                        7: -1.6653345369377348e-16,
-                        8: 3.469446951953614e-17,
-                        9: -1.3877787807814457e-16,
-                    },
-                    "ci_low": {
-                        0: -7.771553129157294e-16,
-                        1: -2.279269223868238e-16,
-                        2: -1.8906584687236155e-16,
-                        3: -1.57411847966069e-16,
-                        4: -3.27696708597398e-17,
-                        5: 2.3327440223904727e-17,
-                        6: -6.643195454332691e-19,
-                        7: -3.158788196765981e-16,
-                        8: -1.878128765814627e-16,
-                        9: -3.348328858540416e-16,
-                    },
-                    "ci_high": {
-                        0: 3.3306610306566683e-16,
-                        1: 5.8823174617924694e-18,
-                        2: 3.4172151275832057e-16,
-                        3: 2.6843415042858463e-16,
-                        4: 1.7154754893788438e-16,
-                        5: 8.769486223861093e-17,
-                        6: 8.393104639232001e-17,
-                        7: -1.718808771094884e-17,
-                        8: 2.57201815620535e-16,
-                        9: 5.727712969775247e-17,
-                    },
-                    "test_index": {0: 0, 1: 1, 2: 2, 3: 3, 4: 4, 5: 5, 6: 6, 7: 7, 8: 8, 9: 9},
-                    "passed": {
-                        0: True,
-                        1: True,
-                        2: True,
-                        3: True,
-                        4: True,
-                        5: True,
-                        6: True,
-                        7: True,
-                        8: True,
-                        9: True,
-                    },
-                    "var": {
-                        0: "test_input",
-                        1: "test_input",
-                        2: "test_input",
-                        3: "test_input",
-                        4: "test_input",
-                        5: "test_input",
-                        6: "test_input",
-                        7: "test_input",
-                        8: "test_input",
-                        9: "test_input",
-                    },
+        expected_dict = {
+            "kurtosis": {"test_input": 0.0},
+            "passing": 10,
+            "successful": 10,
+            "results": {
+                "effect_estimate": {
+                    0: -2.220446049250313e-16,
+                    1: -1.1102230246251565e-16,
+                    2: 7.632783294297951e-17,
+                    3: 5.551115123125783e-17,
+                    4: 6.938893903907228e-17,
+                    5: 5.551115123125783e-17,
+                    6: 4.163336342344337e-17,
+                    7: -1.6653345369377348e-16,
+                    8: 3.469446951953614e-17,
+                    9: -1.3877787807814457e-16,
+                },
+                "ci_low": {
+                    0: -7.771553129157294e-16,
+                    1: -2.279269223868238e-16,
+                    2: -1.8906584687236155e-16,
+                    3: -1.57411847966069e-16,
+                    4: -3.27696708597398e-17,
+                    5: 2.3327440223904727e-17,
+                    6: -6.643195454332691e-19,
+                    7: -3.158788196765981e-16,
+                    8: -1.878128765814627e-16,
+                    9: -3.348328858540416e-16,
+                },
+                "ci_high": {
+                    0: 3.3306610306566683e-16,
+                    1: 5.8823174617924694e-18,
+                    2: 3.4172151275832057e-16,
+                    3: 2.6843415042858463e-16,
+                    4: 1.7154754893788438e-16,
+                    5: 8.769486223861093e-17,
+                    6: 8.393104639232001e-17,
+                    7: -1.718808771094884e-17,
+                    8: 2.57201815620535e-16,
+                    9: 5.727712969775247e-17,
+                },
+                "test_index": {0: 0, 1: 1, 2: 2, 3: 3, 4: 4, 5: 5, 6: 6, 7: 7, 8: 8, 9: 9},
+                "passed": {
+                    0: True,
+                    1: True,
+                    2: True,
+                    3: True,
+                    4: True,
+                    5: True,
+                    6: True,
+                    7: True,
+                    8: True,
+                    9: True,
+                },
+                "var": {
+                    0: "test_input",
+                    1: "test_input",
+                    2: "test_input",
+                    3: "test_input",
+                    4: "test_input",
+                    5: "test_input",
+                    6: "test_input",
+                    7: "test_input",
+                    8: "test_input",
+                    9: "test_input",
                 },
             },
+        }
+        # Use json_normalize to avoid rounding errors
+        pd.testing.assert_frame_equal(
+            pd.json_normalize(expected_dict).round(2),
+            pd.json_normalize(adequacy_metric.to_dict(include_results=True)).round(2),
         )
 
     def test_dag_adequacy_dependent(self):