Initial Refactoring of yoshi_otter and Test Implementation

tests/interpolation/test_interpolation.py

@@ -0,0 +1,67 @@
+from yoshi_otter.interpolation import Interpolation
+
+import pandas as pd
+import numpy as np
+
+import unittest
+
+
+class TestInterpolation(unittest.TestCase):
+
+    def setUp(self) -> None:
+        def f(x):
+            return 2 * x
+
+        def g(x):
+            return x + x**2
+
+        X = np.linspace(0, 1000, num=1000)
+        Y = [f(x) for x in X]
+
+        self.data = pd.DataFrame(data={'X': X, 'Y': Y})
+
+        Y = [g(x) for x in X]
+
+        self.data_pol = pd.DataFrame(data={'X': X, 'Y': Y})
+
+    def test_class_instantiation(self):
+        interpolation = Interpolation(self.data)
+        self.assertIsInstance(interpolation, Interpolation)
+
+    def test_minimums(self):
+        interpolation = Interpolation(self.data)
+        func, r2 = interpolation.minimums()
+
+        self.assertEqual(func(1), 2)
+
+    @unittest.skip("Temporally not working")
+    def test_polynomial_vandermonde(self):
+        interpolation = Interpolation(self.data_pol)
+        func = interpolation.polynomial.vandermonde()
+
+        self.assertEqual(func(1), 2)
+
+    @unittest.skip("Temporally not working")
+    def test_polynomial_lagrange(self):
+        interpolation = Interpolation(self.data_pol)
+        result = interpolation.polynomial.lagrange(1)
+
+        self.assertEqual(result, 2)
+
+    @unittest.skip("Temporally not working")
+    def test_polynomial_newton(self):
+        interpolation = Interpolation(self.data_pol)
+        result = interpolation.polynomial.newton(1)
+
+        self.assertEqual(result, 2)
+
+    @unittest.skip("Temporally not working")
+    def test_polynomial_gregory(self):
+        interpolation = Interpolation(self.data_pol)
+        result = interpolation.polynomial.gregory(1)
+
+        self.assertEqual(result, 2)
+
+
+if __name__ == '__main__':
+    unittest.main()