Added some unittests in test_learning.py

TheSPARTA · agarwl · commit 1c6de72b6434 · 2017-03-08T21:29:05.000+05:30
diff --git a/tests/test_learning.py b/tests/test_learning.py
@@ -1,7 +1,11 @@
 import pytest
-from learning import parse_csv, weighted_mode, weighted_replicate, DataSet, \
-                     PluralityLearner, NaiveBayesLearner, NearestNeighborLearner
+import math
 from utils import DataFile
+from learning import (
+    parse_csv, weighted_mode, weighted_replicate, DataSet,
+    PluralityLearner, NaiveBayesLearner, NearestNeighborLearner,
+    rms_error, manhattan_distance, mean_boolean_error, mean_error
+)
 
 
 def test_parse_csv():
@@ -33,3 +37,31 @@ def test_k_nearest_neighbors():
 
     kNN = NearestNeighborLearner(iris,k=3)
     assert kNN([5,3,1,0.1]) == "setosa"
+
+def test_rms_error():
+    assert rms_error([2,2], [2,2]) == 0
+    assert rms_error((0,0), (0,1)) == math.sqrt(0.5)
+    assert rms_error((1,0), (0,1)) ==  1
+    assert rms_error((0,0), (0,-1)) ==  math.sqrt(0.5)
+    assert rms_error((0,0.5), (0,-0.5)) ==  math.sqrt(0.5)
+
+def test_manhattan_distance():
+    assert manhattan_distance([2,2], [2,2]) == 0
+    assert manhattan_distance([0,0], [0,1]) == 1
+    assert manhattan_distance([1,0], [0,1]) ==  2
+    assert manhattan_distance([0,0], [0,-1]) ==  1
+    assert manhattan_distance([0,0.5], [0,-0.5]) == 1
+
+def test_mean_boolean_error():
+    assert mean_boolean_error([1,1], [0,0]) == 1
+    assert mean_boolean_error([0,1], [1,0]) == 1
+    assert mean_boolean_error([1,1], [0,1]) == 0.5
+    assert mean_boolean_error([0,0], [0,0]) == 0
+    assert mean_boolean_error([1,1], [1,1]) == 0
+
+def test_mean_error():
+    assert mean_error([2,2], [2,2]) == 0
+    assert mean_error([0,0], [0,1]) == 0.5
+    assert mean_error([1,0], [0,1]) ==  1
+    assert mean_error([0,0], [0,-1]) ==  0.5
+    assert mean_error([0,0.5], [0,-0.5]) == 0.5
