Updated tests

rmj3197 · Mar 11, 2024 · ab59d49 · ab59d49
1 parent 86b7470
commit ab59d49
Show file tree

Hide file tree

Showing 13 changed files with 112 additions and 9 deletions.
diff --git a/.DS_Store b/.DS_Store
diff --git a/.gitignore b/.gitignore
@@ -158,4 +158,5 @@ cython_debug/
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
 .vscode/
-htmlcov/
+htmlcov/
+.DS_Store
diff --git a/QuadratiK/.DS_Store b/QuadratiK/.DS_Store
diff --git a/QuadratiK/datasets/.DS_Store b/QuadratiK/datasets/.DS_Store
diff --git a/QuadratiK/datasets/data/.DS_Store b/QuadratiK/datasets/data/.DS_Store
diff --git a/QuadratiK/kernel_test/_h_selection.py b/QuadratiK/kernel_test/_h_selection.py
@@ -545,7 +545,7 @@ def select_h(
         elif isinstance(y, pd.DataFrame):
             y = y.values
         else:
-            raise ValueError(
+            raise TypeError(
                 "y must be a list, numpy.ndarray, \
                     or a pandas DataFrame with one column (for k-sample case) or more"
             )
@@ -563,7 +563,7 @@ def select_h(
         elif alternative == "skewness":
             delta = np.array([0.2, 0.3, 0.6])
 
-    if alternative is None:
+    if (alternative is None) or (alternative not in ["location","scale","skewness"]):
         raise ValueError(
             "Please specify alternative from 'location', 'scale' or 'skewness'"
         )

diff --git a/QuadratiK/ui/.DS_Store b/QuadratiK/ui/.DS_Store
diff --git a/doc/.DS_Store b/doc/.DS_Store
diff --git a/doc/build/.DS_Store b/doc/build/.DS_Store
diff --git a/doc/source/.DS_Store b/doc/source/.DS_Store
diff --git a/tests/.DS_Store b/tests/.DS_Store
diff --git a/tests/test_select_h.py b/tests/test_select_h.py
@@ -1,5 +1,6 @@
 import unittest
 import numpy as np
+import pandas as pd
 from QuadratiK.kernel_test import select_h
 
 
@@ -11,6 +12,7 @@ def test_select_h_one_sample_skewness(self):
             x=x, alternative="skewness", random_state=42, power_plot=True
         )
         self.assertIsInstance(h_sel, (int, float))
+        self.assertIsInstance(all_powers, pd.DataFrame)
         self.assertIsNotNone(plot)
 
     def test_select_h_one_sample_location(self):
@@ -20,6 +22,7 @@ def test_select_h_one_sample_location(self):
             x=x, alternative="location", random_state=42, power_plot=True
         )
         self.assertIsInstance(h_sel, (int, float))
+        self.assertIsInstance(all_powers, pd.DataFrame)
         self.assertIsNotNone(plot)
 
     def test_select_h_one_sample_scale(self):
@@ -29,8 +32,9 @@ def test_select_h_one_sample_scale(self):
             x=x, alternative="scale", random_state=42, power_plot=True
         )
         self.assertIsInstance(h_sel, (int, float))
+        self.assertIsInstance(all_powers, pd.DataFrame)
         self.assertIsNotNone(plot)
-
+        
     def test_select_h_two_sample_skewness(self):
         np.random.seed(42)
         x = np.random.randn(200, 2)
@@ -40,6 +44,7 @@ def test_select_h_two_sample_skewness(self):
             x=x, y=y, alternative="skewness", random_state=42, power_plot=True
         )
         self.assertIsInstance(h_sel, (int, float))
+        self.assertIsInstance(all_powers, pd.DataFrame)
         self.assertIsNotNone(plot)
 
     def test_select_h_two_sample_location(self):
@@ -51,6 +56,7 @@ def test_select_h_two_sample_location(self):
             x=x, y=y, alternative="location", random_state=42, power_plot=True
         )
         self.assertIsInstance(h_sel, (int, float))
+        self.assertIsInstance(all_powers, pd.DataFrame)
         self.assertIsNotNone(plot)
 
     def test_select_h_two_sample_scale(self):
@@ -62,25 +68,113 @@ def test_select_h_two_sample_scale(self):
             x=x, y=y, alternative="scale", random_state=42, power_plot=True
         )
         self.assertIsInstance(h_sel, (int, float))
+        self.assertIsInstance(all_powers, pd.DataFrame)
         self.assertIsNotNone(plot)
 
     def test_select_h_k_sample_location(self):
         np.random.seed(42)
         x = np.random.randn(100 * 3, 2)
         y = np.repeat(np.arange(1, 4), repeats=100)
-        h_sel, all_powers = select_h(x=x, y=y, alternative="location", random_state=42)
+        h_sel, all_powers, plot = select_h(
+            x=x, y=y, alternative="location", random_state=42, power_plot=True
+        )
+        self.assertIsInstance(all_powers, pd.DataFrame)
         self.assertIsInstance(h_sel, (int, float))
+        self.assertIsNotNone(plot)
 
     def test_select_h_k_sample_skewness(self):
         np.random.seed(42)
         x = np.random.randn(100 * 3, 2)
         y = np.repeat(np.arange(1, 4), repeats=100)
-        h_sel, all_powers = select_h(x=x, y=y, alternative="skewness", random_state=42)
+        h_sel, all_powers, plot = select_h(
+            x=x, y=y, alternative="skewness", random_state=42, power_plot=True
+        )
+        self.assertIsInstance(all_powers, pd.DataFrame)
         self.assertIsInstance(h_sel, (int, float))
+        self.assertIsNotNone(plot)
 
     def test_select_h_k_sample_scale(self):
         np.random.seed(42)
-        x = np.random.randn(100 * 3, 2)
+        x = np.random.randn(100 * 3, 3)
         y = np.repeat(np.arange(1, 4), repeats=100)
-        h_sel, all_powers = select_h(x=x, y=y, alternative="scale", random_state=42)
+        h_sel, all_powers, plot = select_h(
+            x=x, y=y, alternative="scale", random_state=42, power_plot=True
+        )
+        self.assertIsInstance(all_powers, pd.DataFrame)
         self.assertIsInstance(h_sel, (int, float))
+        self.assertIsNotNone(plot)
+
+    def test_select_h_inputs(self):
+        x = pd.DataFrame(np.random.randn(100 * 3, 1))
+        y = pd.DataFrame(np.repeat(np.arange(1, 4), repeats=100))
+
+        with self.assertRaises(ValueError):
+            select_h(x=x, y=y, alternative="scale", random_state=[42], power_plot=True)
+
+        with self.assertRaises(TypeError):
+            x_list = [1, 2, 3, 4]
+            y_list = [1,1,2,2]
+            select_h(
+                x=x_list,
+                y=y_list,
+                alternative="scale",
+                random_state=42,
+                power_plot=True,
+            )
+
+        with self.assertRaises(TypeError):
+            x_df = pd.DataFrame(np.random.randn(100,2))
+            y_int = -1
+            select_h(
+                x=x_df,
+                y=y_int,
+                alternative="scale",
+                random_state=42,
+                power_plot=True,
+            )
+
+        with self.assertRaises(ValueError):
+            select_h(x=x, y=y, alternative="some", random_state=42, power_plot=True)
+
+        with self.assertRaises(ValueError):
+            select_h(
+                x=x,
+                y=y,
+                alternative="scale",
+                random_state=42,
+                power_plot=True,
+                delta_dim=[1, 1],
+            )
+
+        with self.assertRaises(ValueError):
+            x = (np.random.randn(100 * 3, 1))
+            select_h(
+                x=x,
+                y=None,
+                alternative="scale",
+                random_state=42,
+                power_plot=True,
+                delta_dim=[1, 1],
+            )
+
+        with self.assertRaises(ValueError):
+            x_two_sample = pd.DataFrame(np.random.randn(100 * 3, 5))
+            y_two_sample = pd.DataFrame(np.random.randn(100 * 3, 3))
+            select_h(
+                x=x_two_sample,
+                y=y_two_sample,
+                alternative="scale",
+                random_state=42,
+                power_plot=True,
+            )
+        with self.assertRaises(ValueError):
+            x_two_sample = pd.DataFrame(np.random.randn(100 * 3, 3))
+            y_two_sample = pd.DataFrame(np.random.randn(100 * 3, 3))
+            select_h(
+                x=x_two_sample,
+                y=y_two_sample,
+                alternative="scale",
+                random_state=42,
+                power_plot=True,
+                delta_dim=[1,1]
+            )
diff --git a/tests/test_uniformity_test.py b/tests/test_uniformity_test.py
@@ -16,7 +16,10 @@ def test_uniformity_test(self):
         x_sp = dat / np.linalg.norm(dat)
         uniformity_test = PoissonKernelTest(rho=0.8, random_state=42).test(x_sp)
         self.assertIsInstance(uniformity_test.u_statistic_un_, (int, float))
+        self.assertIsInstance(uniformity_test.u_statistic_cv_ ,(int, float))
+        self.assertIsInstance(uniformity_test.u_statistic_h0_, np.bool_)
         self.assertIsInstance(uniformity_test.v_statistic_vn_, (int, float))
+
         self.assertIsInstance(uniformity_test.stats(), pd.DataFrame)
         self.assertIsInstance(uniformity_test.summary(print_fmt="html"), str)
         self.assertIsInstance(uniformity_test.summary(), str)
@@ -34,8 +37,13 @@ def test_uniformity_test(self):
             x = [1, 2, 3, 4, 5]
             PoissonKernelTest(rho=0.8, random_state=42).test(x)
 
+
     def test_uniformity_no_rndm_state_dataframe(self):
         x_sp = pd.DataFrame(sample_hypersphere(npoints=100, ndim=3))
-        uniformity_test = PoissonKernelTest(rho=0.8, random_state=None).test(x_sp)
+        uniformity_test = PoissonKernelTest(
+            rho=0.8, random_state=None, num_iter=10, n_jobs=4
+        ).test(x_sp)
         self.assertIsInstance(uniformity_test.u_statistic_un_, (int, float))
         self.assertIsInstance(uniformity_test.v_statistic_vn_, (int, float))
+        self.assertIsInstance(uniformity_test.u_statistic_cv_ ,(int, float))
+        self.assertIsInstance(uniformity_test.v_statistic_h0_, np.bool_)