Updated the option weight setter to match the expected calculator one. Should...

Updated the option weight setter to match the expected calculator one. Should be more realistic now. Tests updated and all passed.

setup.py

@@ -63,7 +63,7 @@ class CMakeBuild(build_ext):
 
 
 setup(name='noComparisonSimulation',
-      version='1.0.0',
+      version='1.0.1',
       author='Chanelle Lee',
       description='A module which calculates simple aggregation for a population',
       long_description='',

src/noComparisonSimulation/parameters.py

@@ -77,14 +77,22 @@ def retOptionWeights(n, case):
         arr[0] = 1
         return arr
 
+    def _ret_expo_weights(a, n):
+        """
+        Returns weights exponentially distributed using:
+
+            w_i = ({1-a} / {1-a^{n}} * a^{i-1}
+        """
+        return np.array([(((1 - a) / (1 - (a ** n))) * (a ** (i - 1)))
+                         for i in range(1, n + 1)])
+
     def _ret_decreasing_weights(n):
         """
         Returns weights that decrease as they get worse
         i.e.
             w1 >~ w2 >~ ... >~wn
         """
-        return (np.linspace(1, 0, n + 2)[1: -1] /
-                sum(np.linspace(0, 1, n + 2)[1: -1]))
+        return _ret_expo_weights(0.2, n)
 
     def _ret_outlier_weights(n):
         """
@@ -93,8 +101,10 @@ def retOptionWeights(n, case):
         i.e.
             w1 >> w2 = ... = wn
         """
-        return np.append(np.array([2 * (1 / n)]),
-                         (1 - 2 * (1 / n)) / (n - 1) * np.ones(n - 1))
+        w1 = _ret_expo_weights(0.2, n)[0]
+        wn = (1 - w1) / (n - 1)
+
+        return np.array((w1, ) + (n - 1) * (wn, ))
 
     if n < 1:
         raise ValueError("n must be positive")

tests/test_parameters.py

@@ -59,11 +59,13 @@ def test_params_invalid_type(num_options, pool_size, pop_size, total_its):
 @pytest.mark.parametrize("n, case, expected", [
     (3, "equal", np.array([1 / 3, 1 / 3, 1 / 3])),
     (3, "noiseless", np.array([1, 0, 0])),
-    (3, "decreasing", np.array([0.5, 1 / 3, 1 / 6])),
-    (3, "outlier", np.array([2 / 3, 1 / 6, 1 / 6]))
+    (3, "decreasing", np.array([0.8065, 0.1613, 0.0323])),
+    (3, "outlier", np.array([0.8065, 0.0968, 0.0968]))
 ])
 def test_retOptionWeights_valid(n, case, expected):
-    numpy.testing.assert_allclose(retOptionWeights(n, case), expected)
+    numpy.testing.assert_almost_equal(retOptionWeights(n, case),
+                                      expected,
+                                      decimal=4)
 
 
 def test_retOptionWeights_invalid_case():