From 9675372a9660d37589f0bf5dff39e5d04b60de2b Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 17:23:55 +0100
Subject: [PATCH 01/17] numpy_questions.py

---
 numpy_questions.py | 26 ++++++++++++++++++++++----
 1 file changed, 22 insertions(+), 4 deletions(-)

diff --git a/numpy_questions.py b/numpy_questions.py
index 21fcec4b..577771b0 100644
--- a/numpy_questions.py
+++ b/numpy_questions.py
@@ -37,11 +37,17 @@ def max_index(X):
         If the input is not a numpy array or
         if the shape is not 2D.
     """
-    i = 0
-    j = 0
 
     # TODO
-
+    if not isinstance(X, np.ndarray):
+        raise ValueError("Input must be a numpy array")
+    
+    if X.ndim != 2:
+        raise ValueError("Input array must be 2D")
+    
+    flat_index = np.argmax(X, axis=None)
+    
+    i, j = np.unravel_index(flat_index, X.shape)
     return i, j
 
 
@@ -64,4 +70,16 @@ 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.
+    if n_terms == 0:
+        return 1.0
+    
+    product = 1.0
+    
+    for n in range(1, n_terms + 1):
+        term1 = (2.0 * n) / (2.0 * n - 1.0)
+        term2 = (2.0 * n) / (2.0 * n + 1.0)
+        product = product * term1 * term2
+    
+    pi_approx = 2.0 * product
+    
+    return pi_approx
\ No newline at end of file

From fea94283ab1f163666f1fc3924dd10e48483a517 Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 17:25:25 +0100
Subject: [PATCH 02/17] sklearn_questions.py

---
 sklearn_questions.py | 12 +++++++++---
 1 file changed, 9 insertions(+), 3 deletions(-)

diff --git a/sklearn_questions.py b/sklearn_questions.py
index f65038c6..599e3be9 100644
--- a/sklearn_questions.py
+++ b/sklearn_questions.py
@@ -43,7 +43,8 @@ def fit(self, X, y):
         check_classification_targets(y)
         self.classes_ = np.unique(y)
         self.n_features_in_ = X.shape[1]
-
+        self.X_ = X
+        self.y_ = y
         # XXX fix
         return self
 
@@ -58,7 +59,10 @@ def predict(self, X):
             shape=len(X), fill_value=self.classes_[0],
             dtype=self.classes_.dtype
         )
-
+        for i, x_test in enumerate(X):
+            distances = np.sqrt(np.sum((self.X_ - x_test) ** 2, axis=1))
+            nearest_idx = np.argmin(distances)
+            y_pred[i] = self.y_[nearest_idx]
         # XXX fix
         return y_pred
 
@@ -71,4 +75,6 @@ def score(self, X, y):
         y_pred = self.predict(X)
 
         # XXX fix
-        return y_pred.sum()
+        accuracy = np.mean(y_pred == y)
+        
+        return accuracy

From 1b1d778db5b19ffc0c613af68fa407cacb2dcd39 Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 20:06:34 +0100
Subject: [PATCH 03/17] sklearn_questions.py

---
 sklearn_questions.py | 19 +++++++++++--------
 1 file changed, 11 insertions(+), 8 deletions(-)

diff --git a/sklearn_questions.py b/sklearn_questions.py
index 599e3be9..b189e00e 100644
--- a/sklearn_questions.py
+++ b/sklearn_questions.py
@@ -28,7 +28,7 @@
 from sklearn.utils.multiclass import check_classification_targets
 
 
-class OneNearestNeighbor(BaseEstimator, ClassifierMixin):
+class OneNearestNeighbor(ClassifierMixin, BaseEstimator):
     "OneNearestNeighbor classifier."
 
     def __init__(self):  # noqa: D107
@@ -36,7 +36,7 @@ def __init__(self):  # noqa: D107
 
     def fit(self, X, y):
         """Write docstring.
-
+        
         And describe parameters
         """
         X, y = check_X_y(X, y)
@@ -45,16 +45,21 @@ def fit(self, X, y):
         self.n_features_in_ = X.shape[1]
         self.X_ = X
         self.y_ = y
-        # XXX fix
         return self
 
     def predict(self, X):
         """Write docstring.
-
+        
         And describe parameters
         """
         check_is_fitted(self)
-        X = check_array(X)
+        X = check_array(X, ensure_2d=True)
+        if X.shape[1] != self.n_features_in_:      
+            raise ValueError(
+                f'X has {X.shape[1]} features, but {self.__class__.__name__} '
+                f'is expecting {self.n_features_in_} features as input.'
+            )
+
         y_pred = np.full(
             shape=len(X), fill_value=self.classes_[0],
             dtype=self.classes_.dtype
@@ -68,13 +73,11 @@ def predict(self, X):
 
     def score(self, X, y):
         """Write docstring.
-
+        
         And describe parameters
         """
         X, y = check_X_y(X, y)
         y_pred = self.predict(X)
-
         # XXX fix
         accuracy = np.mean(y_pred == y)
-        
         return accuracy

From a34a5a2b3b95907e8f26022df7c59622e63a28eb Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 20:08:09 +0100
Subject: [PATCH 04/17] numpy_questions.py

---
 numpy_questions.py | 10 ++--------
 1 file changed, 2 insertions(+), 8 deletions(-)

diff --git a/numpy_questions.py b/numpy_questions.py
index 577771b0..dbf2cdb3 100644
--- a/numpy_questions.py
+++ b/numpy_questions.py
@@ -41,12 +41,9 @@ def max_index(X):
     # TODO
     if not isinstance(X, np.ndarray):
         raise ValueError("Input must be a numpy array")
-    
     if X.ndim != 2:
         raise ValueError("Input array must be 2D")
-    
     flat_index = np.argmax(X, axis=None)
-    
     i, j = np.unravel_index(flat_index, X.shape)
     return i, j
 
@@ -72,14 +69,11 @@ def wallis_product(n_terms):
     # terms in the product. For example 10000.
     if n_terms == 0:
         return 1.0
-    
     product = 1.0
-    
     for n in range(1, n_terms + 1):
         term1 = (2.0 * n) / (2.0 * n - 1.0)
         term2 = (2.0 * n) / (2.0 * n + 1.0)
         product = product * term1 * term2
-    
     pi_approx = 2.0 * product
-    
-    return pi_approx
\ No newline at end of file
+    return pi_approx
+    
\ No newline at end of file

From 7f24370c3520c48050f8c87302856af471adf0d2 Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 20:12:14 +0100
Subject: [PATCH 05/17] numpy_questions.py

---
 numpy_questions.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/numpy_questions.py b/numpy_questions.py
index dbf2cdb3..2b184753 100644
--- a/numpy_questions.py
+++ b/numpy_questions.py
@@ -75,5 +75,4 @@ def wallis_product(n_terms):
         term2 = (2.0 * n) / (2.0 * n + 1.0)
         product = product * term1 * term2
     pi_approx = 2.0 * product
-    return pi_approx
-    
\ No newline at end of file
+    return pi_approx
\ No newline at end of file

From 4fbd8ef2ce856a8456872cb7a0a422e18061ae6b Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 20:12:43 +0100
Subject: [PATCH 06/17] numpy_questions.py

---
 sklearn_questions.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/sklearn_questions.py b/sklearn_questions.py
index b189e00e..592651c1 100644
--- a/sklearn_questions.py
+++ b/sklearn_questions.py
@@ -54,7 +54,7 @@ def predict(self, X):
         """
         check_is_fitted(self)
         X = check_array(X, ensure_2d=True)
-        if X.shape[1] != self.n_features_in_:      
+        if X.shape[1] != self.n_features_in_:
             raise ValueError(
                 f'X has {X.shape[1]} features, but {self.__class__.__name__} '
                 f'is expecting {self.n_features_in_} features as input.'
@@ -80,4 +80,4 @@ def score(self, X, y):
         y_pred = self.predict(X)
         # XXX fix
         accuracy = np.mean(y_pred == y)
-        return accuracy
+        return accuracy
\ No newline at end of file

From 6e5ba4b35568e36537d7b8ecf6e34a06f0832c9f Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 20:18:42 +0100
Subject: [PATCH 07/17] numpy_questions.py

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

diff --git a/numpy_questions.py b/numpy_questions.py
index 2b184753..f37111e2 100644
--- a/numpy_questions.py
+++ b/numpy_questions.py
@@ -75,4 +75,4 @@ def wallis_product(n_terms):
         term2 = (2.0 * n) / (2.0 * n + 1.0)
         product = product * term1 * term2
     pi_approx = 2.0 * product
-    return pi_approx
\ No newline at end of file
+    return pi_approx

From c21fe5b41fdc216acd8218f8941135da0b9658bc Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 20:19:39 +0100
Subject: [PATCH 08/17] sklearn_questions.py

---
 sklearn_questions.py | 14 ++------------
 1 file changed, 2 insertions(+), 12 deletions(-)

diff --git a/sklearn_questions.py b/sklearn_questions.py
index 592651c1..4ee623cc 100644
--- a/sklearn_questions.py
+++ b/sklearn_questions.py
@@ -35,10 +35,6 @@ def __init__(self):  # noqa: D107
         pass
 
     def fit(self, X, y):
-        """Write docstring.
-        
-        And describe parameters
-        """
         X, y = check_X_y(X, y)
         check_classification_targets(y)
         self.classes_ = np.unique(y)
@@ -48,10 +44,6 @@ def fit(self, X, y):
         return self
 
     def predict(self, X):
-        """Write docstring.
-        
-        And describe parameters
-        """
         check_is_fitted(self)
         X = check_array(X, ensure_2d=True)
         if X.shape[1] != self.n_features_in_:
@@ -59,7 +51,6 @@ def predict(self, X):
                 f'X has {X.shape[1]} features, but {self.__class__.__name__} '
                 f'is expecting {self.n_features_in_} features as input.'
             )
-
         y_pred = np.full(
             shape=len(X), fill_value=self.classes_[0],
             dtype=self.classes_.dtype
@@ -73,11 +64,10 @@ def predict(self, X):
 
     def score(self, X, y):
         """Write docstring.
-        
         And describe parameters
         """
         X, y = check_X_y(X, y)
-        y_pred = self.predict(X)
+        y_pred=self.predict(X)
         # XXX fix
         accuracy = np.mean(y_pred == y)
-        return accuracy
\ No newline at end of file
+        return accuracy

From 2d9a9a2911d98dc4a962c3fdb214bf8322da46db Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 20:22:52 +0100
Subject: [PATCH 09/17] sklearn_questions.py

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

diff --git a/sklearn_questions.py b/sklearn_questions.py
index 4ee623cc..75e7bb2c 100644
--- a/sklearn_questions.py
+++ b/sklearn_questions.py
@@ -67,7 +67,7 @@ def score(self, X, y):
         And describe parameters
         """
         X, y = check_X_y(X, y)
-        y_pred=self.predict(X)
+        y_pred = self.predict(X)
         # XXX fix
         accuracy = np.mean(y_pred == y)
         return accuracy

From 6f2187f6bdafb1f3809d4f0378432df3fa49b31e Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 20:27:27 +0100
Subject: [PATCH 10/17] sklearn_questions.py

---
 sklearn_questions.py | 5 -----
 1 file changed, 5 deletions(-)

diff --git a/sklearn_questions.py b/sklearn_questions.py
index 75e7bb2c..1a81f5d7 100644
--- a/sklearn_questions.py
+++ b/sklearn_questions.py
@@ -29,8 +29,6 @@
 
 
 class OneNearestNeighbor(ClassifierMixin, BaseEstimator):
-    "OneNearestNeighbor classifier."
-
     def __init__(self):  # noqa: D107
         pass
 
@@ -63,9 +61,6 @@ def predict(self, X):
         return y_pred
 
     def score(self, X, y):
-        """Write docstring.
-        And describe parameters
-        """
         X, y = check_X_y(X, y)
         y_pred = self.predict(X)
         # XXX fix

From 52d41bb56489a40688b6393122dff62956c7c3cc Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 20:34:34 +0100
Subject: [PATCH 11/17] numpy_questions.py

---
 numpy_questions.py | 4 ----
 1 file changed, 4 deletions(-)

diff --git a/numpy_questions.py b/numpy_questions.py
index f37111e2..f331d194 100644
--- a/numpy_questions.py
+++ b/numpy_questions.py
@@ -20,24 +20,20 @@
 
 def max_index(X):
     """Return the index of the maximum in a numpy array.
-
     Parameters
     ----------
     X : ndarray of shape (n_samples, n_features)
         The input array.
-
     Returns
     -------
     (i, j) : tuple(int)
         The row and columnd index of the maximum.
-
     Raises
     ------
     ValueError
         If the input is not a numpy array or
         if the shape is not 2D.
     """
-
     # TODO
     if not isinstance(X, np.ndarray):
         raise ValueError("Input must be a numpy array")

From 8d17098de6bbc39ef9c316f92a5f7f3c7add2744 Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 20:34:53 +0100
Subject: [PATCH 12/17] sklearn_questions.py

---
 sklearn_questions.py | 10 ++++++++++
 1 file changed, 10 insertions(+)

diff --git a/sklearn_questions.py b/sklearn_questions.py
index 1a81f5d7..9e0aec89 100644
--- a/sklearn_questions.py
+++ b/sklearn_questions.py
@@ -29,10 +29,14 @@
 
 
 class OneNearestNeighbor(ClassifierMixin, BaseEstimator):
+    "OneNearestNeighbor classifier."
     def __init__(self):  # noqa: D107
         pass
 
     def fit(self, X, y):
+        """Write docstring.
+        And describe parameters
+        """
         X, y = check_X_y(X, y)
         check_classification_targets(y)
         self.classes_ = np.unique(y)
@@ -42,6 +46,9 @@ def fit(self, X, y):
         return self
 
     def predict(self, X):
+        """Write docstring.
+        And describe parameters
+        """
         check_is_fitted(self)
         X = check_array(X, ensure_2d=True)
         if X.shape[1] != self.n_features_in_:
@@ -61,6 +68,9 @@ def predict(self, X):
         return y_pred
 
     def score(self, X, y):
+        """Write docstring.
+        And describe parameters
+        """
         X, y = check_X_y(X, y)
         y_pred = self.predict(X)
         # XXX fix

From ae579714ba543ad31d9a3fdb7c8baf263a2e12f6 Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 20:39:38 +0100
Subject: [PATCH 13/17] numpy_questions.py

---
 numpy_questions.py   | 1 +
 sklearn_questions.py | 6 +++++-
 2 files changed, 6 insertions(+), 1 deletion(-)

diff --git a/numpy_questions.py b/numpy_questions.py
index f331d194..48629fb1 100644
--- a/numpy_questions.py
+++ b/numpy_questions.py
@@ -19,6 +19,7 @@
 
 
 def max_index(X):
+
     """Return the index of the maximum in a numpy array.
     Parameters
     ----------
diff --git a/sklearn_questions.py b/sklearn_questions.py
index 9e0aec89..03393491 100644
--- a/sklearn_questions.py
+++ b/sklearn_questions.py
@@ -29,12 +29,14 @@
 
 
 class OneNearestNeighbor(ClassifierMixin, BaseEstimator):
-    "OneNearestNeighbor classifier."
+    """OneNearestNeighbor classifier."""
+
     def __init__(self):  # noqa: D107
         pass
 
     def fit(self, X, y):
         """Write docstring.
+
         And describe parameters
         """
         X, y = check_X_y(X, y)
@@ -47,6 +49,7 @@ def fit(self, X, y):
 
     def predict(self, X):
         """Write docstring.
+
         And describe parameters
         """
         check_is_fitted(self)
@@ -69,6 +72,7 @@ def predict(self, X):
 
     def score(self, X, y):
         """Write docstring.
+
         And describe parameters
         """
         X, y = check_X_y(X, y)

From 9f3ed7140ca83f8dd90ca1bcaaa787cdb6ffc92b Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 20:41:05 +0100
Subject: [PATCH 14/17] numpy_questions.py

---
 numpy_questions.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/numpy_questions.py b/numpy_questions.py
index 48629fb1..8cf60c1b 100644
--- a/numpy_questions.py
+++ b/numpy_questions.py
@@ -16,11 +16,10 @@
 errors by calling `flake8` at the root of the repo.
 """
 import numpy as np
-
-
 def max_index(X):
 
     """Return the index of the maximum in a numpy array.
+
     Parameters
     ----------
     X : ndarray of shape (n_samples, n_features)

From c3733b35a62f2acd523f6f6ed0adfc8b4133ca18 Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 20:42:59 +0100
Subject: [PATCH 15/17] numpy_questions.py

---
 numpy_questions.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/numpy_questions.py b/numpy_questions.py
index 8cf60c1b..acdf285f 100644
--- a/numpy_questions.py
+++ b/numpy_questions.py
@@ -24,10 +24,12 @@ def max_index(X):
     ----------
     X : ndarray of shape (n_samples, n_features)
         The input array.
+
     Returns
     -------
     (i, j) : tuple(int)
         The row and columnd index of the maximum.
+
     Raises
     ------
     ValueError

From 0b5db3e9d79d432c7135a84344d7d22fd25b0c95 Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 20:44:37 +0100
Subject: [PATCH 16/17] numpy_questions.py

---
 numpy_questions.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/numpy_questions.py b/numpy_questions.py
index acdf285f..e1bf930d 100644
--- a/numpy_questions.py
+++ b/numpy_questions.py
@@ -16,6 +16,8 @@
 errors by calling `flake8` at the root of the repo.
 """
 import numpy as np
+
+
 def max_index(X):
 
     """Return the index of the maximum in a numpy array.

From 1bf3e997a16d0956f63e5fb1915fd5296f5165dd Mon Sep 17 00:00:00 2001
From: Zixiao Guo <zixiaoguo1@gmail.com>
Date: Thu, 13 Nov 2025 20:46:23 +0100
Subject: [PATCH 17/17] numpy_questions.py

---
 numpy_questions.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/numpy_questions.py b/numpy_questions.py
index e1bf930d..60a8609f 100644
--- a/numpy_questions.py
+++ b/numpy_questions.py
@@ -19,7 +19,6 @@
 
 
 def max_index(X):
-
     """Return the index of the maximum in a numpy array.
 
     Parameters