Merge pull request #59 from UBC-MDS/increase_coverage

Increase coverage
UBC-MDS · Mar 10, 2018 · f9f9e83 · f9f9e83
2 parents d9239a5 + a803cb9
commit f9f9e83
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Showing 2 changed files with 28 additions and 10 deletions.
diff --git a/README.md b/README.md
@@ -73,28 +73,25 @@ python -m pytest tests/test_forward_selection.py
 
 $ py.test --cov=pypunisher tests/
 
-============================================================================ test session starts =============================================================================
 platform darwin -- Python 3.6.3, pytest-3.4.1, py-1.5.2, pluggy-0.6.0
+...
 plugins: cov-2.5.1
-collected 12 items                                                                                                                                                           
+collected 13 items                                                                                                                                                           
 
-tests/test_backward_selection.py .                                                                                                                                     [  8%]
-tests/test_criterion.py ....                                                                                                                                           [ 41%]
-tests/test_forward_selection.py .                                                                                                                                      [ 50%]
-tests/test_selection.py ......                                                                                                                                         [100%]
+...
 
 ---------- coverage: platform darwin, python 3.6.3-final-0 -----------
 Name                                        Stmts   Miss  Cover
 ---------------------------------------------------------------
-pypunisher/__init__.py                          2      0   100%
+pypunisher/__init__.py                          4      0   100%
 pypunisher/_checks.py                          19      1    95%
 pypunisher/metrics/__init__.py                  1      0   100%
 pypunisher/metrics/criterion.py                28      3    89%
 pypunisher/selection_engines/__init__.py        2      0   100%
-pypunisher/selection_engines/_utils.py         20      4    80%
-pypunisher/selection_engines/selection.py      90     15    83%
+pypunisher/selection_engines/_utils.py         20      2    90%
+pypunisher/selection_engines/selection.py      90     11    88%
 ---------------------------------------------------------------
-TOTAL                                         162     23    86%
+TOTAL                                         164     17    90%
 ```
 
 ## Contributors: 

diff --git a/tests/test_selection.py b/tests/test_selection.py
@@ -69,12 +69,18 @@ class Model(object):
 
 forward_output = forward()
 
+# Run using the other parameter option
+forward_output += forward(n_features=1, min_change=None)
+
 # Force the backward selection algorithm to
 # select the single feature it thinks is most predictive.
 # If implemented correctly, `backward()` should be able to
 # identify `TRUE_BEST_FEATURE` as predictive.
 backward_output = backward(n_features=1)
 
+# Run using the other parameter option
+backward_output += backward(min_change=0.0001, n_features=None)
+
 
 # -----------------------------------------------------------------------------
 # Test outputs: Type
@@ -97,6 +103,21 @@ def test_bsel_output_type():
     output_type(backward_output)
 
 
+# -----------------------------------------------------------------------------
+# Test `n_features`
+# -----------------------------------------------------------------------------
+
+
+def test_n_features():
+    """
+    Test various version of n_features
+    """
+    for n_features in (10000, -1.0):
+        with pytest.raises(ValueError):  # should raise
+            backward(n_features=n_features)
+    backward(n_features=0.5)  # this should not raise
+
+
 # -----------------------------------------------------------------------------
 # Test outputs: Selection of the Predictive Feature
 # -----------------------------------------------------------------------------