From 3910a1533642708b51acbc867cbda729e3b0d867 Mon Sep 17 00:00:00 2001
From: Andreea Patarlageanu <andreeapatarlageanu.uni@gmail.com>
Date: Thu, 13 Nov 2025 16:16:15 +0200
Subject: [PATCH 1/3] exercises done

---
 numpy_questions.py   | 34 ++++++++++++++++++++++++++++++++--
 sklearn_questions.py | 19 +++++++++++--------
 2 files changed, 43 insertions(+), 10 deletions(-)

diff --git a/numpy_questions.py b/numpy_questions.py
index 21fcec4b..999a70ff 100644
--- a/numpy_questions.py
+++ b/numpy_questions.py
@@ -15,6 +15,7 @@
 This will be enforced with `flake8`. You can check that there is no flake8
 errors by calling `flake8` at the root of the repo.
 """
+
 import numpy as np
 
 
@@ -40,7 +41,21 @@ def max_index(X):
     i = 0
     j = 0
 
-    # TODO
+    if not isinstance(X, np.ndarray):
+        raise ValueError("Not a numpy array")
+
+    if X.ndim != 2:
+        raise ValueError("Not a 2D array")
+
+    n = X.shape[0]
+    m = X.shape[1]
+    max = 0
+    for k in range(n):
+        for l in range(m):
+            if X[k][l] > max:
+                max = X[k][l]
+                i = k
+                j = l
 
     return i, j
 
@@ -64,4 +79,19 @@ def wallis_product(n_terms):
     """
     # XXX : The n_terms is an int that corresponds to the number of
     # terms in the product. For example 10000.
-    return 0.
+    product = 1.0
+
+    if n_terms == 0:
+        return 1.0
+
+    n = 1
+    while n <= n_terms:
+        numerator = 4 * n * n
+        denominator = (2 * n - 1) * (2 * n + 1)
+        product = product * (numerator / denominator)
+        n += 1
+
+    pi = product * 2
+
+    # approximation of order n_terms
+    return pi
diff --git a/sklearn_questions.py b/sklearn_questions.py
index f65038c6..864bd188 100644
--- a/sklearn_questions.py
+++ b/sklearn_questions.py
@@ -19,6 +19,7 @@
 for the methods you code and for the class. The docstring will be checked using
 `pydocstyle` that you can also call at the root of the repo.
 """
+
 import numpy as np
 from sklearn.base import BaseEstimator
 from sklearn.base import ClassifierMixin
@@ -44,7 +45,9 @@ def fit(self, X, y):
         self.classes_ = np.unique(y)
         self.n_features_in_ = X.shape[1]
 
-        # XXX fix
+        self.X_train_ = X
+        self.y_train_ = y
+
         return self
 
     def predict(self, X):
@@ -54,13 +57,13 @@ def predict(self, X):
         """
         check_is_fitted(self)
         X = check_array(X)
-        y_pred = np.full(
-            shape=len(X), fill_value=self.classes_[0],
-            dtype=self.classes_.dtype
+
+        distances = np.sqrt(
+            np.sum((X[:, np.newaxis, :] - self.X_train_[np.newaxis, :, :]) ** 2, axis=2)
         )
+        nearest_indices = np.argmin(distances, axis=1)
 
-        # XXX fix
-        return y_pred
+        return self.y_train_[nearest_indices]
 
     def score(self, X, y):
         """Write docstring.
@@ -70,5 +73,5 @@ def score(self, X, y):
         X, y = check_X_y(X, y)
         y_pred = self.predict(X)
 
-        # XXX fix
-        return y_pred.sum()
+        accuracy = np.mean(y == y_pred)
+        return accuracy

From 38dd250236dde8ab882bfad440bd82034d7b2953 Mon Sep 17 00:00:00 2001
From: Andreea Patarlageanu <andreeapatarlageanu.uni@gmail.com>
Date: Thu, 13 Nov 2025 16:28:37 +0200
Subject: [PATCH 2/3] erros fixed

---
 numpy_questions.py   | 8 ++++----
 sklearn_questions.py | 5 ++++-
 2 files changed, 8 insertions(+), 5 deletions(-)

diff --git a/numpy_questions.py b/numpy_questions.py
index 999a70ff..7de4bdcc 100644
--- a/numpy_questions.py
+++ b/numpy_questions.py
@@ -51,11 +51,11 @@ def max_index(X):
     m = X.shape[1]
     max = 0
     for k in range(n):
-        for l in range(m):
-            if X[k][l] > max:
-                max = X[k][l]
+        for p in range(m):
+            if X[k][p] > max:
+                max = X[k][p]
                 i = k
-                j = l
+                j = p
 
     return i, j
 
diff --git a/sklearn_questions.py b/sklearn_questions.py
index 864bd188..9785880e 100644
--- a/sklearn_questions.py
+++ b/sklearn_questions.py
@@ -59,7 +59,10 @@ def predict(self, X):
         X = check_array(X)
 
         distances = np.sqrt(
-            np.sum((X[:, np.newaxis, :] - self.X_train_[np.newaxis, :, :]) ** 2, axis=2)
+            np.sum((
+                X[:, np.newaxis, :] - self.X_train_[np.newaxis, :, :]
+                ) ** 2, axis=2
+            )
         )
         nearest_indices = np.argmin(distances, axis=1)
 

From ef38197ab459b3d096d1a567bed3fb131aab132e Mon Sep 17 00:00:00 2001
From: Andreea Patarlageanu <andreeapatarlageanu.uni@gmail.com>
Date: Thu, 13 Nov 2025 16:34:46 +0200
Subject: [PATCH 3/3] erros fixed again

---
 sklearn_questions.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn_questions.py b/sklearn_questions.py
index 9785880e..aba5ad5b 100644
--- a/sklearn_questions.py
+++ b/sklearn_questions.py
@@ -30,7 +30,7 @@
 
 
 class OneNearestNeighbor(BaseEstimator, ClassifierMixin):
-    "OneNearestNeighbor classifier."
+    """OneNearestNeighbor classifier."""
 
     def __init__(self):  # noqa: D107
         pass