rmse

Author: joegasewicz

README.md

@@ -47,3 +47,16 @@ $$
 \text{RMSE} = \sqrt{\frac{1}{n} \sum_{i=1}^{n} (y_i - \hat{y}_i)^2}
 $$
 
+```python
+from rmse import RMSE
+rmse = RMSE(
+    actual_vals=[34, 37, 44, 47, 48, 48, 46, 43, 32, 27, 26, 24],
+    predicted_vals=[37, 40, 46, 44, 46, 50, 45, 44, 34, 30, 22, 23],
+)
+rmse.calc_errors()
+rmse.square_errors()
+rmse.sum_errors()
+rmse.set_mean()
+result = rmse.get_square_root()
+assert round(result, 5) == 2.43242
+```

mse.py

@@ -18,8 +18,4 @@ def __init__(self, *,
             predicted_vals=predicted_vals,
         )
 
-    def square_errors(self):
-        squ_errs = []
-        for e in self.errors:
-            squ_errs.append(pow(e, 2))
-        self.errors = squ_errs
+

rem_base.py

@@ -26,10 +26,18 @@ def calc_errors(self) -> None:
         for i in range(range_len):
             self.errors.append(self.actual_vals[i]-self.predicted_vals[i])
 
+    def square_errors(self):
+        squ_errs = []
+        for e in self.errors:
+            squ_errs.append(pow(e, 2))
+        self.errors = squ_errs
+
     def sum_errors(self) -> None:
         for e in self.errors:
             self.result += e
 
+
+
     def get_mean(self) -> float:
         """
         :return: Mean absolute error as a float

rmse.py

@@ -0,0 +1,25 @@
+from typing import List
+import math
+
+from rem_base import BaseREM
+
+
+class RMSE(BaseREM):
+
+    square_root: float
+
+    def __init__(self, *,
+                 actual_vals: List[int],
+                 predicted_vals: List[int],
+                 ):
+        super().__init__(
+            actual_vals=actual_vals,
+            predicted_vals=predicted_vals,
+        )
+        self.square_root = 0
+
+    def set_mean(self) -> None:
+        self.square_root = self.get_mean()
+
+    def get_square_root(self) -> float:
+        return math.sqrt(self.square_root)

test_mse.py

@@ -32,7 +32,7 @@ def test_square_errors(self):
         )
         mse2.calc_errors()
         mse2.square_errors()
-        assert len(mse.errors) == len(mse.actual_vals)
+        assert len(mse2.errors) == len(mse2.actual_vals)
         assert mse2.errors == [9, 9, 4, 9, 4, 4, 1, 1, 4, 9, 16, 1]
 
     def test_sum_errors(self):

test_rmse.py

@@ -0,0 +1,75 @@
+from rmse import RMSE
+
+
+class TestMAE:
+
+    def test_new(self):
+        rmse = RMSE(actual_vals=[3, 5, 2], predicted_vals=[4, 4, 3])
+        assert isinstance(rmse, RMSE)
+
+    def test_calc_errors(self):
+        rmse = RMSE(actual_vals=[3, 5, 2], predicted_vals=[4, 4, 3])
+        rmse.calc_errors()
+        assert rmse.errors == [-1, 1, -1]
+
+        rmse2 = RMSE(
+            actual_vals=[34, 37, 44, 47, 48, 48, 46, 43, 32, 27, 26, 24],
+            predicted_vals=[37, 40, 46, 44, 46, 50, 45, 44, 34, 30, 22, 23],
+        )
+        rmse2.calc_errors()
+        assert rmse2.errors == [-3, -3, -2, 3, 2, -2, 1, -1, -2, -3, 4, 1]
+
+    def test_square_errors(self):
+        rmse = RMSE(actual_vals=[3, 5, 2], predicted_vals=[4, 4, 3])
+        rmse.calc_errors()
+        rmse.square_errors()
+        assert len(rmse.errors) == len(rmse.actual_vals)
+        assert rmse.errors == [1, 1, 1]
+
+        rmse2 = RMSE(
+            actual_vals=[34, 37, 44, 47, 48, 48, 46, 43, 32, 27, 26, 24],
+            predicted_vals=[37, 40, 46, 44, 46, 50, 45, 44, 34, 30, 22, 23],
+        )
+        rmse2.calc_errors()
+        rmse2.square_errors()
+        assert len(rmse2.errors) == len(rmse2.actual_vals)
+        assert rmse2.errors == [9, 9, 4, 9, 4, 4, 1, 1, 4, 9, 16, 1]
+
+    def test_set_mean(self):
+        rmse = RMSE(actual_vals=[3, 5, 2], predicted_vals=[4, 4, 3])
+        rmse.calc_errors()
+        rmse.square_errors()
+        rmse.sum_errors()
+        rmse.set_mean()
+        assert rmse.square_root == 1
+
+        rmse2 = RMSE(
+            actual_vals=[34, 37, 44, 47, 48, 48, 46, 43, 32, 27, 26, 24],
+            predicted_vals=[37, 40, 46, 44, 46, 50, 45, 44, 34, 30, 22, 23],
+        )
+        rmse2.calc_errors()
+        rmse2.square_errors()
+        rmse2.sum_errors()
+        rmse2.set_mean()
+        assert round(rmse2.square_root, 5) == 5.91667
+
+    def test_get_square_root(self):
+        rmse = RMSE(actual_vals=[3, 5, 2], predicted_vals=[4, 4, 3])
+        rmse.calc_errors()
+        rmse.square_errors()
+        rmse.sum_errors()
+        rmse.set_mean()
+        result = rmse.get_square_root()
+        assert result == 1
+
+        rmse2 = RMSE(
+            actual_vals=[34, 37, 44, 47, 48, 48, 46, 43, 32, 27, 26, 24],
+            predicted_vals=[37, 40, 46, 44, 46, 50, 45, 44, 34, 30, 22, 23],
+        )
+        rmse2.calc_errors()
+        rmse2.square_errors()
+        rmse2.sum_errors()
+        rmse2.set_mean()
+        result2 = rmse2.get_square_root()
+        assert round(result2, 5) == 2.43242
+