from scipy.optimize import fsolve import numpy as np #y = (10 ln(x+1)+30)x^0.5 def inverse_function(y_val): """ Approximate the inverse of the function y = (10 * ln(x + 1) + 30) * x**0.5. This function takes a y value and returns the corresponding x value. """ # Define the function to solve def equation(x): return (10 * np.log(x + 1) + 30) * np.sqrt(x) - y_val # Initial guess for x, can be adjusted based on the range of expected x values initial_guess = 1 # Solve for x x_val = fsolve(equation, initial_guess) return x_val[0] # Example usage 12,295 10119 y_example = 12295 x_result = inverse_function(y_example) print(x_result)
