some new features

.venv/lib/python3.12/site-packages/statsmodels/distributions/tests/test_ecdf.py

@@ -0,0 +1,56 @@
+import numpy as np
+import numpy.testing as npt
+from numpy.testing import assert_raises
+from statsmodels.distributions import StepFunction, monotone_fn_inverter
+from statsmodels.distributions import ECDFDiscrete
+
+
+class TestDistributions:
+
+    def test_StepFunction(self):
+        x = np.arange(20)
+        y = np.arange(20)
+        f = StepFunction(x, y)
+        vals = f(np.array([[3.2, 4.5], [24, -3.1], [3.0, 4.0]]))
+        npt.assert_almost_equal(vals, [[3, 4], [19, 0], [2, 3]])
+
+    def test_StepFunctionBadShape(self):
+        x = np.arange(20)
+        y = np.arange(21)
+        assert_raises(ValueError, StepFunction, x, y)
+        x = np.zeros((2, 2))
+        y = np.zeros((2, 2))
+        assert_raises(ValueError, StepFunction, x, y)
+
+    def test_StepFunctionValueSideRight(self):
+        x = np.arange(20)
+        y = np.arange(20)
+        f = StepFunction(x, y, side='right')
+        vals = f(np.array([[3.2, 4.5], [24, -3.1], [3.0, 4.0]]))
+        npt.assert_almost_equal(vals, [[3, 4], [19, 0], [3, 4]])
+
+    def test_StepFunctionRepeatedValues(self):
+        x = [1, 1, 2, 2, 2, 3, 3, 3, 4, 5]
+        y = [6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
+        f = StepFunction(x, y)
+        npt.assert_almost_equal(f([1, 2, 3, 4, 5]), [0, 7, 10, 13, 14])
+        f2 = StepFunction(x, y, side='right')
+        npt.assert_almost_equal(f2([1, 2, 3, 4, 5]), [7, 10, 13, 14, 15])
+
+    def test_monotone_fn_inverter(self):
+        x = [6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
+        fn = lambda x : 1./x  # noqa
+        y = fn(np.array(x))
+        f = monotone_fn_inverter(fn, x)
+        npt.assert_array_equal(f.y, x[::-1])
+        npt.assert_array_equal(f.x, y[::-1])
+
+    def test_ecdf_discrete(self):
+        x = [3, 3, 1, 4]
+        e = ECDFDiscrete(x)
+        npt.assert_array_equal(e.x, [-np.inf, 1, 3, 4])
+        npt.assert_array_equal(e.y, [0, 0.25, 0.75, 1])
+        e1 = ECDFDiscrete([3.5, 3.5, 1.5, 1, 4])
+        e2 = ECDFDiscrete([3.5, 1.5, 1, 4], freq_weights=[2, 1, 1, 1])
+        npt.assert_array_equal(e1.x, e2.x)
+        npt.assert_array_equal(e1.y, e2.y)