angular mean and spread

.gitignore

 .idea/*
+build/
+skais.egg-info/
+*.coverage
\ No newline at end of file

skais/stats/angluar.py

+import numpy as np
+
+
+def angular_dispersion(x):
+    n = len(x)
+    X = np.sum(np.cos(x)) / n
+    Y = np.sum(np.sin(x)) / n
+
+    r = np.sqrt(X ** 2 + Y ** 2)
+
+    return r
+
+
+def angular_mean(x):
+    n = len(x)
+    X = np.sum(np.cos(x)) / n
+    Y = np.sum(np.sin(x)) / n
+
+    theta = abs(np.arctan2(X, Y))
+
+    if Y > 0 and X > 0:
+        return theta
+
+    if Y > 0 >= X:
+        return np.pi/2 - theta
+
+    if Y <= 0 < X:
+        return np.pi + theta
+    else:
+        return 2 * np.pi + theta

skais/tests/stats/test_angular.py

+import unittest
+
+import numpy as np
+
+from skais.stats.angluar import angular_mean
+
+
+class TestAngular(unittest.TestCase):
+    def test_angular_mean_simple(self):
+        x = np.radians(np.array([1, 359]))
+
+        self.assertEqual(0.0, angular_mean(x))
+
+    def test_angular_mean_simple_2(self):
+        x = np.radians(np.array([180, 180, 180, 180, 179, 181]))
+
+        self.assertEqual(np.pi, angular_mean(x))
+
+    def test_angular_mean_simple_3(self):
+        x = np.radians(np.array([0, 0, 0, 0, 359, 1]))
+
+        self.assertEqual(0.0, angular_mean(x))
+
+    def test_angular_mean_first_quadrant(self):
+        x = np.radians(np.array([43, 44, 45, 46, 47]))
+
+        self.assertEqual(np.pi / 4, angular_mean(x))
+
+    def test_angular_mean_second_quadrant(self):
+        x = np.radians(np.array([133, 134, 135, 136, 137]))
+
+        self.assertEqual(3*np.pi / 4, angular_mean(x))
+
+    def test_angular_mean_third_quadrant(self):
+        x = np.radians(np.array([223, 224, 225, 226, 227]))
+
+        self.assertEqual(5*np.pi / 4, angular_mean(x))
+
+    def test_angular_mean_fourth_quadrant(self):
+        x = np.radians(np.array([313, 314, 315, 316, 317]))
+
+        self.assertEqual(7*np.pi / 4, angular_mean(x))