Enable tests to work on fresh chroots

Author: firefly-cpp

niaarm/tests/test_coverage.py

@@ -1,14 +1,14 @@
 from unittest import TestCase
 from niaarm.association_rule import AssociationRule
 from niaarm.dataset import Dataset
-
+import os
 
 class TestCoverage(TestCase):
     # let's borrow a test case from wikipedia:
     # https://en.wikipedia.org/wiki/Lift_(data_mining)
 
     def setUp(self):
-        data = Dataset("datasets/wiki_test_case.csv")
+        data = Dataset(os.path.join(os.path.dirname(__file__), 'test_data', 'wiki_test_case.csv'))
         self.features = data.features
 
     def test_a(self):

niaarm/tests/test_cut_point.py

@@ -1,13 +1,13 @@
 from unittest import TestCase
 from niaarm.association_rule import AssociationRule, _cut_point
 from niaarm.dataset import Dataset
-
+import os
 
 class TestCutPoint(TestCase):
     # let's borrow a test case from Wikipedia:
     # https://en.wikipedia.org/wiki/Lift_(data_mining)
     def setUp(self):
-        data = Dataset("datasets/wiki_test_case.csv")
+        data = Dataset(os.path.join(os.path.dirname(__file__), 'test_data', 'wiki_test_case.csv'))
         self.features = data.features
         self.oper = AssociationRule(self.features)
 
@@ -37,7 +37,7 @@ def test_cut_pointA(self):
 
 class TestCutPointB(TestCase):
     def setUp(self):
-        data = Dataset("datasets/Abalone.csv")
+        data = Dataset(os.path.join(os.path.dirname(__file__), 'test_data', 'Abalone.csv'))
         self.features = data.features
         self.oper = AssociationRule(self.features)
 

niaarm/tests/test_data/Abalone.csv

@@ -0,0 +1,8 @@
+Feat1,Feat2
+A,0
+A,0
+A,1
+A,0
+B,1
+B,0
+B,1

niaarm/tests/test_data/wiki_test_case.csv

@@ -1,6 +1,6 @@
 from unittest import TestCase
 from niaarm.dataset import Dataset
-
+import os
 
 class TestReadCSVAbalone(TestCase):
     def test_read_features(self):
@@ -27,8 +27,8 @@ def test_read_features(self):
             'float',
             'float',
             'int']
-
-        data = Dataset("datasets/Abalone.csv")
+        
+        data = Dataset(os.path.join(os.path.dirname(__file__), 'test_data', 'Abalone.csv'))
 
         features = data.features
 
@@ -59,8 +59,8 @@ def test_read_features(self):
         minval = [None, 0]
         maxval = [None, 1]
         dtypes_a = ['cat', 'int']
-
-        data = Dataset("datasets/wiki_test_case.csv")
+        
+        data = Dataset(os.path.join(os.path.dirname(__file__), 'test_data', 'wiki_test_case.csv'))
 
         features = data.features
 

niaarm/tests/test_read_csv.py

@@ -1,13 +1,13 @@
 from unittest import TestCase
 from niaarm.association_rule import AssociationRule, _rule_feasible, _get_permutation
 from niaarm.dataset import Dataset
-
+import os
 
 class TestBuildRuleA(TestCase):
     # let's borrow a test case from Wikipedia:
     # https://en.wikipedia.org/wiki/Lift_(data_mining)
     def setUp(self):
-        data = Dataset("datasets/wiki_test_case.csv")
+        data = Dataset(os.path.join(os.path.dirname(__file__), 'test_data', 'wiki_test_case.csv'))
         self.features = data.features
         self.oper = AssociationRule(self.features)
 
@@ -139,7 +139,7 @@ def test_build_rule(self):
 class TestBuildRuleB(TestCase):
     # Abalone test case
     def setUp(self):
-        data = Dataset("datasets/Abalone.csv")
+        data = Dataset(os.path.join(os.path.dirname(__file__), 'test_data', 'Abalone.csv'))
         self.features = data.features
         self.oper = AssociationRule(self.features)
 

niaarm/tests/test_rule_building.py

@@ -1,11 +1,11 @@
 from unittest import TestCase
 from niaarm.association_rule import AssociationRule, _normalize, _cut_point
 from niaarm.dataset import Dataset
-
+import os
 
 class TestShrinkageA(TestCase):
     def setUp(self):
-        data = Dataset("datasets/wiki_test_case.csv")
+        data = Dataset(os.path.join(os.path.dirname(__file__), 'test_data', 'wiki_test_case.csv'))
         self.features = data.features
         self.oper = AssociationRule(self.features)
 
@@ -77,7 +77,7 @@ class TestShrinkageB(TestCase):
     # val = n1f + n2f + n3f = 0.38110243 + 0.41193212 + 0.32021534 =  1.11324989
 
     def setUp(self):
-        data = Dataset("datasets/Abalone.csv")
+        data = Dataset(os.path.join(os.path.dirname(__file__), 'test_data', 'Abalone.csv'))
         self.features = data.features
         self.oper = AssociationRule(self.features)
 

niaarm/tests/test_shrinkage.py

@@ -1,14 +1,14 @@
 from unittest import TestCase
 from niaarm.association_rule import AssociationRule, _cut_point
 from niaarm.dataset import Dataset
-
+import os
 
 class TestSupportConfidence(TestCase):
     # let's borrow test case from wikipedia:
     # https://en.wikipedia.org/wiki/Lift_(data_mining)
 
     def setUp(self):
-        data = Dataset("datasets/wiki_test_case.csv")
+        data = Dataset(os.path.join(os.path.dirname(__file__), 'test_data', 'wiki_test_case.csv'))
         self.features = data.features
         self.transactions = data.transactions
 

niaarm/tests/test_support_confidence.py

@@ -0,0 +1,4 @@
+from niaarm.tests.conftest import pytest_configure
+
+__all__ = ["pytest_configure"]
+