Resolve docsstyle

Author: SalmaAlkhalily

numpy_questions.py

@@ -1,14 +1,53 @@
+"""Assignment - using numpy and making a PR.
+
+The goals of this assignment are:
+    * Use numpy in practice with two easy exercises.
+    * Use automated tools to validate the code (`pytest` and `flake8`)
+    * Submit a Pull-Request on github to practice `git`.
+
+The two functions below are skeleton functions. The docstrings explain what
+are the inputs, the outputs and the expected error. Fill the function to
+complete the assignment. The code should be able to pass the test that we
+wrote. To run the tests, use `pytest test_numpy_question.py` at the root of
+the repo. It should say that 2 tests ran with success.
+
+We also ask to respect the pep8 convention: https://pep8.org.
+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
 
 
 def max_index(X):
-    # Raises
+    """
+    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.
+    """
     if not isinstance(X, np.ndarray):
         raise ValueError("The input is not a numpy array")
     if X.ndim != 2:
         raise ValueError("The shape is not 2D")
-    """ Return the index of the maximum in a numpy array
-     (The row and columnd index of the maximum)"""
+    """
+    Return the index of the maximum in a numpy array
+    (The row and columnd index of the maximum)
+    """
     i = 0
     j = 0
     max_index = np.argmax(X)
@@ -18,6 +57,23 @@ def max_index(X):
 
 
 def wallis_product(n_terms):
+    """
+    Implement the Wallis product to compute an approximation of pi.
+
+    See:
+    https://en.wikipedia.org/wiki/Wallis_product
+
+    Parameters
+    ----------
+    n_terms : int
+        Number of steps in the Wallis product. Note that `n_terms=0` will
+        consider the product to be `1`.
+
+    Returns
+    -------
+    pi : float
+        The approximation of order `n_terms` of pi using the Wallis product.
+    """
     # So if n_terms = 0 -> product = 1
     product = 1.0
     for n in range(1, n_terms + 1):