Factors of a number (#1493)

* Factors of a number

* Update factors.py

* Fix mypy issue in basic_maths.py

* Fix mypy error in perceptron.py

* def primes(max: int) -> List[int]:

* Update binomial_heap.py

* Add a space

* Remove a space

* Add a space

data_structures/heap/binomial_heap.py

@@ -1,7 +1,6 @@
 """
-    Binomial Heap 
+Binomial Heap
-    
+Reference: Advanced Data Structures, Peter Brass
-    Reference: Advanced Data Structures, Peter Brass   
 """
 
 
@@ -47,10 +46,9 @@ class Node:
 
 
 class BinomialHeap:
-    """
+    r"""
     Min-oriented priority queue implemented with the Binomial Heap data
     structure implemented with the BinomialHeap class. It supports:
-    
         - Insert element in a heap with n elemnts: Guaranteed logn, amoratized 1
         - Merge (meld) heaps of size m and n: O(logn + logm)
         - Delete Min: O(logn)
@@ -58,13 +56,11 @@ class BinomialHeap:
 
     Example:
 
-        Create a random permutation of 30 integers to be inserted and 
+    Create a random permutation of 30 integers to be inserted and 19 of them deleted
-        19 of them deleted
     >>> import numpy as np
     >>> permutation = np.random.permutation(list(range(30)))
 
     Create a Heap and insert the 30 integers
-        
     __init__() test
     >>> first_heap = BinomialHeap()
 
@@ -123,7 +119,6 @@ class BinomialHeap:
     >>> while not first_heap.isEmpty():
     ...     print(first_heap.deleteMin(), end=" ")
     17 20 25 26 27 28 29 31 34 
-        
     """
 
     def __init__(self, bottom_root=None, min_node=None, heap_size=0):

maths/basic_maths.py

@@ -67,10 +67,8 @@ def euler_phi(n: int) -> int:
     >>> euler_phi(100)
     40
     """
-    l = prime_factors(n)
-    l = set(l)
     s = n
-    for x in l:
+    for x in set(prime_factors(n)):
         s *= (x - 1) / x
     return int(s)
 

maths/factors.py

@@ -0,0 +1,18 @@
+def factors_of_a_number(num: int) -> list:
+    """
+    >>> factors_of_a_number(1)
+    [1]
+    >>> factors_of_a_number(5)
+    [1, 5]
+    >>> factors_of_a_number(24)
+    [1, 2, 3, 4, 6, 8, 12, 24]
+    >>> factors_of_a_number(-24)
+    []
+    """
+    return [i for i in range(1, num + 1) if num % i == 0]
+
+
+if __name__ == "__main__":
+    num = int(input("Enter a number to find its factors: "))
+    factors = factors_of_a_number(num)
+    print(f"{num} has {len(factors)} factors: {', '.join(str(f) for f in factors)}")

maths/prime_numbers.py

@@ -1,9 +1,9 @@
-"""Prime numbers calculation."""
+from typing import List
 
 
-def primes(max: int) -> int:
+def primes(max: int) -> List[int]:
     """
-    Return a list of all primes up to max.
+    Return a list of all primes numbers up to max.
     >>> primes(10)
     [2, 3, 5, 7]
     >>> primes(11)

neural_network/perceptron.py

@@ -95,8 +95,7 @@ class Perceptron:
         ...
         >>> perceptron.sort([-0.6508, 0.1097, 4.0009]) # doctest: +ELLIPSIS
         ('Sample: ', ...)
-        classification: P1
+        classification: P...
-
         """
         if len(self.sample) == 0:
             raise AttributeError("Sample data can not be empty")