Python in its language allows various mathematical operations, which has manifolds application in scientific domain. One such offering of Python is the inbuilt gamma() function, which numerically computes the gamma value of the number that is passed in the function.
Syntax : math.gamma(x)
Parameters :
x : The number whose gamma value needs to be computed.Returns : The gamma value, which is numerically equal to “factorial(x-1)”.
Code #1 : Demonstrating the working of gamma()
# Python code to demonstrate # working of gamma() import math # initializing argument gamma_var = 6 # Printing the gamma value. print ("The gamma value of the given argument is : " + str(math.gamma(gamma_var))) |
Output:
The gamma value of the given argument is : 120.0
factorial() vs gamma()
The gamma value can also be found using factorial(x-1), but the use case of gamma() is because, if we compare both the function to achieve the similar task, gamma() offers better performance.
Code #2 : Comparing factorial() and gamma()
# Python code to demonstrate # factorial() vs gamma() import math import time # initializing argument gamma_var = 6 # checking performance # gamma() vs factorial() start_fact = time.time() res_fact = math.factorial(gamma_var-1) print ("The gamma value using factorial is : " + str(res_fact)) print ("The time taken to compute is : " + str(time.time() - start_fact)) print ('\n') start_gamma = time.time() res_gamma = math.gamma(gamma_var) print ("The gamma value using gamma() is : " + str(res_gamma)) print ("The time taken to compute is : " + str(time.time() - start_gamma)) |
Output:
The gamma value using factorial is : 120 The time taken to compute is : 9.059906005859375e-06 The gamma value using gamma() is : 120.0 The time taken to compute is : 5.245208740234375e-06
