From e3bc384b54226c4fe74dc8c7969eed40287b0fb2 Mon Sep 17 00:00:00 2001
From: davidlevinwork <david.levin2@live.biu.ac.il>
Date: Mon, 13 May 2024 08:19:16 +0300
Subject: [PATCH] feat(tests): customize tests to the new flow

---
 tests/dataset.csv            |  3 ---
 tests/test_algo.py           | 20 +++++++++++++++++---
 tests/test_data_processor.py |  3 ++-
 3 files changed, 19 insertions(+), 7 deletions(-)
 delete mode 100644 tests/dataset.csv

diff --git a/tests/dataset.csv b/tests/dataset.csv
deleted file mode 100644
index 7f37f02..0000000
--- a/tests/dataset.csv
+++ /dev/null
@@ -1,3 +0,0 @@
-feature_0,feature_1,feature_2,class
-1,2,3,0
-4,5,6,1
diff --git a/tests/test_algo.py b/tests/test_algo.py
index 40681aa..6ae92e0 100644
--- a/tests/test_algo.py
+++ b/tests/test_algo.py
@@ -1,18 +1,32 @@
+from typing import Optional
 from unittest.mock import patch
-
 from gbfs.algorithms.base import FeatureSelectorBase
+import pandas as pd
+
+
+class ConcreteFeatureSelector(FeatureSelectorBase):
+    def select_features(self) -> Optional[list]:
+        return []
 
 
 @patch('gbfs.models.dim_reducer.DimReducerProtocol')
-def test_initialization(mock_dim_reducer_protocol):
+@patch('pandas.read_csv')
+def test_initialization(mock_read_csv, mock_dim_reducer_protocol):
     """
     Test initialization of FeatureSelectorBase with mocked dependencies.
     """
+    # Mock read_csv to return a DataFrame
+    mock_read_csv.return_value = pd.DataFrame({
+        'feature1': [1, 2, 3],
+        'feature2': [4, 5, 6],
+        'class': [0, 1, 0]
+    })
+
     dataset_path = 'tests/dataset.csv'
     separability_metric = 'jm'
     label_column = 'class'
 
-    fs_base = FeatureSelectorBase(
+    fs_base = ConcreteFeatureSelector(
         dataset_path,
         separability_metric,
         mock_dim_reducer_protocol,
diff --git a/tests/test_data_processor.py b/tests/test_data_processor.py
index 19ff889..b107dc0 100644
--- a/tests/test_data_processor.py
+++ b/tests/test_data_processor.py
@@ -59,10 +59,11 @@ def test_compute_data_properties():
             }
         ),
     )
+    feature_costs = {'feature1': 1.0, 'feature2': 1.0}
 
     data_processor = DataProcessor('tests/dataset.csv')
 
-    data_props = data_processor._compute_data_properties(mock_data_collection)
+    data_props = data_processor._compute_data_properties(mock_data_collection, feature_costs)
 
     assert isinstance(data_props, DataProps), 'Should return a DataProps instance.'
     assert data_props.n_features == 2, 'There should be two features.'