Python in its language allows various mathematical operations, which has manifolds application in scientific domain. One such offering of Python is the inbuilt
Python3
Output:
Python3 1==
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)))
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