lab 2 and solutions 1

labs/ex02/template/grid_search.py

@@ -0,0 +1,32 @@
+# -*- coding: utf-8 -*-
+"""Exercise 2.
+
+Grid Search
+"""
+
+import numpy as np
+
+
+def generate_w(num_intervals):
+    """Generate a grid of values for w0 and w1."""
+    w0 = np.linspace(-100, 200, num_intervals)
+    w1 = np.linspace(-150, 150, num_intervals)
+    return w0, w1
+
+
+def grid_search(y, tx, w0, w1):
+    """Algorithm for grid search."""
+    losses = np.zeros((len(w0), len(w1)))
+    # compute loss for each combination of w0 and w1.
+    for ind_row, row in enumerate(w0):
+        for ind_col, col in enumerate(w1):
+            w = np.array([row, col])
+            e = y - tx.dot(w)
+            losses[ind_row, ind_col] = 1/2*np.mean(e**2)
+    return losses
+
+
+def get_best_parameters(w0, w1, losses):
+    """Get the best w from the result of grid search."""
+    min_row, min_col = np.unravel_index(np.argmin(losses), losses.shape)
+    return losses[min_row, min_col], w0[min_row], w1[min_col]