NumPy - Find maximum element in large array using For loop and optimization
NumPy: Performance Optimization Exercise-9 with Solution
Write a NumPy program to generate a large NumPy array and write a function to find the maximum element using a for loop. Optimize it using NumPy's built-in functions.
Sample Solution:
Python Code:
import numpy as np
# Generate a large NumPy array with random integers
large_array = np.random.randint(1, 1000000, size=1000000)
# Function to find the maximum element using a for loop
def find_max_with_loop(arr):
max_element = arr[0]
for element in arr:
if element > max_element:
max_element = element
return max_element
# Find the maximum element using the for loop method
max_with_loop = find_max_with_loop(large_array)
# Find the maximum element using NumPy's built-in function
max_with_numpy = np.max(large_array)
# Display the results
print(f"Maximum element using for loop: {max_with_loop}")
print(f"Maximum element using NumPy: {max_with_numpy}")
Output:
Maximum element using for loop: 999997 Maximum element using NumPy: 999997
Explanation:
- Importing numpy: We first import the numpy library for array manipulations.
- Generating a large array: A large NumPy array with random integers is generated.
- Defining the function: A function find_max_with_loop is defined to find the maximum element using a for loop.
- Finding maximum with loop: The maximum element is found using the for loop method.
- Finding maximum with numpy: The maximum element is found using NumPy's built-in np.max function.
- Displaying results: The results from both methods are printed out.
Python-Numpy Code Editor:
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