Update median_of_medians.py

Made the changes needed

Author: coderbeta1

Diff for: searches/median_of_medians.py

@@ -1,52 +1,69 @@
 """
-A Python implementation of the Median of Medians algorithm to select pivots for QuickSelect,
-which is efficient for calculating the value that would appear in the index of a list if it
-would be sorted, even if it is not already sorted. Search in time complexity O(n) at any rank
+A Python implementation of the Median of Medians algorithm
+to select pivots for quick_select, which is efficient for
+calculating the value that would appear in the index of a
+list if it would be sorted, even if it is not already
+sorted. Search in time complexity O(n) at any rank
 deterministically
 https://en.wikipedia.org/wiki/Median_of_medians
 """
 
+"""
+>>> quick_select([2, 4, 5, 7, 899, 54, 32], 5)
+32
+>>> quick_select([2, 4, 5, 7, 899, 54, 32], 1)
+2
+>>> quick_select([5, 4, 3, 2], 2)
+3
+>>> quick_select([3, 5, 7, 10, 2, 12], 3)
+5
+"""
 
-def MedianofFive(arr: list) -> int:
+def median_of_five(arr:list) -> int:
+    """
+    >>> median_of_five([2, 4, 5, 7, 899])
+    5
+    >>> median_of_five([5, 7, 899, 54, 32])
+    32
+    >>> median_of_five([5, 4, 3, 2])
+    3
+    >>> median_of_five([3, 5, 7, 10, 2])
+    5
+    """
     """
     Return the median of the input list
     :param arr: Array to find median of
     :return: median of arr
     """
-    arr = sorted(arr)
-    return arr[len(arr) // 2]
-
+    arr=sorted(arr)
+    return arr[len(arr)//2]
 
-def MedianofMedians(arr: list) -> int:
+def median_of_medians(arr:list) -> int:
     """
     Return a pivot to partition data on by calculating
     Median of medians of input data
     :param arr: The data to be sorted (a list)
     :param k: The rank to be searched
     :return: element at rank k
     """
-    if len(arr) <= 5:
-        return MedianofFive(arr)
+    if len(arr) <= 5:        return median_of_five(arr)
     medians = []
-    i = 0
-    while i < len(arr):
-        if (i + 4) <= len(arr):
-            medians.append(MedianofFive(arr[i:].copy()))
-        else:
-            medians.append(MedianofFive(arr[i : i + 5].copy()))
-        i += 5
-    return MedianofMedians(medians)
-
+    i=0
+    while i<len(arr):
+        if (i + 4) <= len(arr):            medians.append(median_of_five(arr[i:].copy()))
+        else:                              medians.append(median_of_five(arr[i:i+5].copy()))
+        i+=5
+    return median_of_medians(medians)
 
-def QuickSelect(arr: list, k: int) -> int:
+def quick_select(arr:list, k:int) -> int:
     """
-    >>> QuickSelect([2, 4, 5, 7, 899, 54, 32], 5)
+    >>> quick_select([2, 4, 5, 7, 899, 54, 32], 5)
     32
-    >>> QuickSelect([2, 4, 5, 7, 899, 54, 32], 1)
+    >>> quick_select([2, 4, 5, 7, 899, 54, 32], 1)
     2
-    >>> QuickSelect([5, 4, 3, 2], 2)
+    >>> quick_select([5, 4, 3, 2], 2)
     3
-    >>> QuickSelect([3, 5, 7, 10, 2, 12], 3)
+    >>> quick_select([3, 5, 7, 10, 2, 12], 3)
     5
     """
 
@@ -59,15 +76,14 @@ def QuickSelect(arr: list, k: int) -> int:
     """
 
     # Invalid Input
-    if k > len(arr):
-        return None
+    if k>len(arr):
+        return -1
 
     # x is the estimated pivot by median of medians algorithm
-    x = MedianofMedians(arr)
+    x = median_of_medians(arr)
     left = []
     right = []
     check = False
-    smaller = 0
     for i in range(len(arr)):
         if arr[i] < x:
             left.append(arr[i])
@@ -77,11 +93,8 @@ def QuickSelect(arr: list, k: int) -> int:
             check = True
         else:
             right.append(arr[i])
-    rankX = len(left) + 1
-    if rankX == k:
-        answer = x
-    elif rankX > k:
-        answer = QuickSelect(left, k)
-    elif rankX < k:
-        answer = QuickSelect(right, k - rankX)
-    return answer
+    rank_X = len(left) + 1
+    if(rank_X==k):        answer = x
+    elif rank_X>k:        answer = quick_select(left,k)
+    elif rank_X<k:        answer = quick_select(right,k-rank_X)
+    return answer;