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Approximating a functions area in an interval

I am trying to approximate an area for a function f within an interval [a, b] using N + 1 equally spaced points.

a and b should be inputted with type int or float, N should be input with type int, and f should be input as a lambda function implemented so that it can be applied to numpy arrays.

This is what I have so far, how could I go about fixing it?

import numpy as np # Importing necessary librariesdef area_approximator(a = 0, b = 1, N = 1, f = lambda x: 0):    x_values = np.linspace(a, b, N+1) # Generate N+1 equidistant points between a and b    dx = (b - a) / N # Calculate the width of each subinterval    area = 0 # Initialize the area variable    # Iterate over each subinterval    for i in range(N):        # Calculate the midpoint of the subinterval        x_mid = (x_values[i] + x_values[i+1]) / 2        # Calculate the function value at the midpoint        f_mid = f(x_mid)        # Add the area of the rectangle (width * height) to the total area        area += dx * f_mid    return area# Prompt the user to input values for a, b, N, and fa_input = float(input("Enter the value of a: "))b_input = float(input("Enter the value of b: "))N_input = int(input("Enter the value of N: "))f_input = input("Enter the function f(x): ")# Convert the input string to a lambda functionf = eval(f_input)# Call the area_approximator function with user inputsresult = area_approximator(a=a_input, b=b_input, N=N_input, f=f)print(result)

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