From 42f62dade616f4f7a1b77d3ca18a6900a6e90a20 Mon Sep 17 00:00:00 2001
From: Felipe <fealho@gmail.com>
Date: Fri, 11 Aug 2023 12:19:04 -0700
Subject: [PATCH] Update test according to sdmetrics release

---
 setup.py                                      |  4 +-
 .../evaluation/test_multi_table.py            | 44 +++++++++++++++----
 2 files changed, 37 insertions(+), 11 deletions(-)

diff --git a/setup.py b/setup.py
index a89b20717..fad4b479d 100644
--- a/setup.py
+++ b/setup.py
@@ -24,8 +24,8 @@
     'copulas>=0.9.0,<0.10',
     'ctgan>=0.7.2,<0.8',
     'deepecho>=0.4.1,<0.5',
-    'rdt>=1.6.1.dev0',
-    'sdmetrics>=0.10.0,<0.11',
+    'rdt>=1.6.1',
+    'sdmetrics>=0.11.0,<0.12',
     'cloudpickle>=2.1.0,<3.0',
     'boto3>=1.15.0,<2',
     'botocore>=1.18,<2'
diff --git a/tests/integration/evaluation/test_multi_table.py b/tests/integration/evaluation/test_multi_table.py
index b2ef4d712..80087a768 100644
--- a/tests/integration/evaluation/test_multi_table.py
+++ b/tests/integration/evaluation/test_multi_table.py
@@ -3,23 +3,49 @@
 
 from sdv.evaluation.multi_table import evaluate_quality, run_diagnostic
 from sdv.metadata.multi_table import MultiTableMetadata
-from sdv.multi_table.hma import HMASynthesizer
 
 
 def test_evaluation():
     """Test ``evaluate_quality`` and ``run_diagnostic``."""
     # Setup
-    table = pd.DataFrame({'col': [1, 2, 3]})
-    data = {'table': table}
-    metadata = MultiTableMetadata()
-    metadata.detect_table_from_dataframe('table', table)
-    synthesizer = HMASynthesizer(metadata)
+    table = pd.DataFrame({'id': [0, 1, 2, 3], 'col': [1, 2, 3, 4]})
+    slightly_different_table = pd.DataFrame({'id': [0, 1, 2, 3], 'col': [1, 2, 3, 3.5]})
+    data = {
+        'table1': table,
+        'table2': table,
+    }
+    samples = {
+        'table1': table,
+        'table2': slightly_different_table,
+    }
+    metadata = MultiTableMetadata().load_from_dict({
+        'tables': {
+            'table1': {
+                'columns': {
+                    'id': {'sdtype': 'id'},
+                    'col': {'sdtype': 'numerical'},
+                },
+            },
+            'table2': {
+                'columns': {
+                    'id': {'sdtype': 'id'},
+                    'col': {'sdtype': 'numerical'},
+                },
+            }
+        },
+        'relationships': [
+            {
+                'parent_table_name': 'table1',
+                'parent_primary_key': 'id',
+                'child_table_name': 'table2',
+                'child_foreign_key': 'id'
+            }
+        ]
+    })
 
     # Run and Assert
-    synthesizer.fit(data)
-    samples = synthesizer.sample()
     score = evaluate_quality(data, samples, metadata).get_score()
-    assert score == 0.6666666666666667
+    assert score == .9375
 
     diagnostic = run_diagnostic(data, samples, metadata).get_results()
     assert diagnostic == {