python code to use %timeit to determine how much faster your function using NumPy arrays is versus your function that uses a sequence numpy function import numpy as np #defining function to calculate cube of an element def cube(x): return x * x * x #function """calculates cube of x""" #Defining input as a Numpy array of positive Integers x = np.array([1, 2, 3, 4]) print("Numpy array of intergers are: ", *x, sep=" ") #test function cube_x = cube(x) #calling function print('\n') print("Cube of array elements are: ", *cube_x, sep=" ") print('\n')
python code to use %timeit to determine how much faster your function using NumPy arrays is versus your function that uses a sequence
numpy function
import numpy as np
#defining function to calculate cube of an element
def cube(x):
return x * x * x #function
"""calculates cube of x"""
#Defining input as a Numpy array of positive Integers
x = np.array([1, 2, 3, 4])
print("Numpy array of intergers are: ", *x, sep=" ")
#test function
cube_x = cube(x)
#calling function
print('\n')
print("Cube of array elements are: ", *cube_x, sep=" ")
print('\n')
sequence function
import math as m
#defining function to calculate cube of an element
def cube(x):
return pow(x) #function
"""calculates cube of x"""
#Defining input as a sequence of positive integer numbers
i = range(1,5)
print("Sequence of intergers are: ", *x, sep=" ")
#test function
cube_x = [pow(x, 3) for x in i]
#calling function
print('\n')
print("Cube of elements in the range is: ", *cube_x, sep=" ")
print('\n')
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