UP my solution

x-datascience-datacamp · Dec 18, 2023 · 8869ef7 · 8869ef7
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Showing 8 changed files with 70 additions and 2 deletions.
diff --git a/.idea/.gitignore b/.idea/.gitignore
diff --git a/.idea/2023-assignment-numpy.iml b/.idea/2023-assignment-numpy.iml
diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml
diff --git a/.idea/misc.xml b/.idea/misc.xml
diff --git a/.idea/modules.xml b/.idea/modules.xml
diff --git a/.idea/vcs.xml b/.idea/vcs.xml
diff --git a/numpy_questions.py b/numpy_questions.py
@@ -40,7 +40,10 @@ def max_index(X):
     i = 0
     j = 0
 
-    # TODO
+    if not isinstance(X, np.ndarray) or X.ndim != 2:
+        raise ValueError("Input must be a 2D numpy array")
+
+    i, j = np.unravel_index(np.argmax(X), X.shape)
 
     return i, j
 
@@ -64,4 +67,16 @@ 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 2.0
+
+    result = 1.0
+    for i in range(1, n_terms + 1):
+        term = 4.0 * i ** 2
+        result *= term / (term - 1)
+
+    # Multiply by 2 to get the final Wallis product
+    pi_approximation = 2 * result
+
+    return pi_approximation
diff --git a/test_numpy_questions.py b/test_numpy_questions.py
@@ -37,3 +37,4 @@ def test_wallis_product():
 
     pi_approx = wallis_product(100000)
     assert abs(pi_approx - m.pi) < 1e-4
+