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UP my solution #209

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23 changes: 15 additions & 8 deletions numpy_questions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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 must be 2D")
max_val = X[0, 0]
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Copilot AI Dec 17, 2025

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This implementation assumes the array has at least one element by accessing X[0, 0]. If an empty array or an array with shape (0, n) or (n, 0) is passed, this will raise an IndexError. The function should handle empty arrays gracefully, either by checking if the array has elements first or by catching this edge case.

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i, j = 0, 0
for row in range(X.shape[0]):
for col in range(X.shape[1]):
if X[row, col] > max_val:
max_val = X[row, col]
i, j = row, col
Comment on lines +46 to +50
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The nested loop implementation is inefficient for finding the maximum index in a numpy array. NumPy provides built-in optimized functions like np.argmax() or np.unravel_index() that are significantly faster and more idiomatic. Using these would avoid the O(n*m) Python loop overhead and leverage NumPy's vectorized operations.

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return i, j


Expand All @@ -62,6 +68,7 @@ def wallis_product(n_terms):
pi : float
The approximation of order `n_terms` of pi using the Wallis product.
"""
# 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
for n in range(1, n_terms + 1):
product *= (4 * n ** 2) / (4 * n ** 2 - 1)
return 2 * product