Update probability_of_n_heads_in_m_tossing.py

Author: dipuk0506

maths/probability_of_n_heads_in_m_tossing.py

@@ -1,56 +1,57 @@
+
 import numpy as np
 
 
 def probability_of_n_heads_in_m_tossing(head_count: int, toss_count: int) -> int:
     """
-    The probability of getting exactly n heads in m tossing.
+   The probability of getting exactly n heads in m tossing.
 
-     Algorithm Explanation:
-     If you toss 0 time -> 0 head
-     Distribution [1] -> Meaning: 1 in the 0-index
+    Algorithm Explanation:
+    If you toss 0 time -> 0 head
+    Distribution [1] -> Meaning: 1 in the 0-index
 
-     If you toss 1 time -> 0 or 1 head
-     Distribution [0.5 0.5] -> Meaning: 0.5 in both indexes
+    If you toss 1 time -> 0 or 1 head
+    Distribution [0.5 0.5] -> Meaning: 0.5 in both indexes
 
-     If you toss 2 times -> 0 to 2 heads
-     Distribution [0.25 0.5 0.25] ->
-     Meaning:  probability of n heads from the distribution
-     {HH, HT, TH, TT}
+    If you toss 2 times -> 0 to 2 heads
+    Distribution [0.25 0.5 0.25] ->
+    Meaning:  probability of n heads from the distribution
+    {HH, HT, TH, TT}
 
-     If you toss 3 times -> 0 to 3 heads
-     Distribution [0.125 0.375 0.375 0.125] ->
-     Meaning:  probability of n heads from the distribution
-     {HHH, HHT, HTH, HTT, THH, THT, TTH, TTT}
+    If you toss 3 times -> 0 to 3 heads
+    Distribution [0.125 0.375 0.375 0.125] ->
+    Meaning:  probability of n heads from the distribution
+    {HHH, HHT, HTH, HTT, THH, THT, TTH, TTT}
 
-     Therefore,
-     Probability_distribution(N+1) =
-           [Probability_distribution(N) 0]/2 + [0 Probability_distribution(N)]/2
+    Therefore,
+    Probability_distribution(N+1) =
+          [Probability_distribution(N) 0]/2 + [0 Probability_distribution(N)]/2
 
-     I used that method in my paper
-     Titled: Uncertainty-aware Decisions in Cloud Computing:
-     Foundations and Future Directions
-     Journal: ACM Computing Surveys (CSUR)
+    I used that method in my paper
+    Titled: Uncertainty-aware Decisions in Cloud Computing:
+    Foundations and Future Directions
+    Journal: ACM Computing Surveys (CSUR)
 
-     >>> import numpy as np
-     >>> Probability_of_n_heads_in_m_tossing(.2,.5)
-     Traceback (most recent call last):
-         ...
-     ValueError: The function only accepts integer values
-     >>> Probability_of_n_heads_in_m_tossing(-1,5)
-     Traceback (most recent call last):
-         ...
-     ValueError: The function is not defined for negative values
-     >>> Probability_of_n_heads_in_m_tossing(3,2)
-     Traceback (most recent call last):
-         ...
-     ValueError: Head count should be smaller than toss count
+    >>> import numpy as np
+    >>> probability_of_n_heads_in_m_tossing(.2,.5)
+    Traceback (most recent call last):
+        ...
+    ValueError: The function only accepts integer values
+    >>> probability_of_n_heads_in_m_tossing(-1,5)
+    Traceback (most recent call last):
+        ...
+    ValueError: The function is not defined for negative values
+    >>> probability_of_n_heads_in_m_tossing(3,2)
+    Traceback (most recent call last):
+        ...
+    ValueError: Head count should be smaller than toss count
 
-     >>> Probability_of_n_heads_in_m_tossing(1,1)
-     0.5
-     >>> Probability_of_n_heads_in_m_tossing(0,2)
-     0.25
-     >>> Probability_of_n_heads_in_m_tossing(2,3)
-     0.375
+    >>> probability_of_n_heads_in_m_tossing(1,1)
+    0.5
+    >>> probability_of_n_heads_in_m_tossing(0,2)
+    0.25
+    >>> probability_of_n_heads_in_m_tossing(2,3)
+    0.375
     """
     if head_count != int(head_count) or toss_count != int(toss_count):
         raise ValueError("The function only accepts integer values")