Mark Miyashita

Recall the following definitions from Newton’s Method from discussion:

def approx_deriv(fn, x, dx=0.00001):
    return (fn(x+dx)-fn(x))/dx

def newtons_method(fn, guess=1, max_iterations=100):
    ALLOWED_ERROR_MARGIN = 0.0000001
    i = 1
    while abs(fn(guess)) > ALLOWED_ERROR_MARGIN and i <= max_iterations:
        guess = guess - fn(guess) / approx_deriv(fn, guess)
        i += 1
    return guess

If you don’t understand Newton’s Method at all, be sure to ask your TA during office hours or ask on Piazza.

We want to write a function that will help us find the roots of the following mathematical equation:

f(x) = x^3 + x + 1

Write a function, f that can find the root(s) of the function above.

def f():
    """Returns at least one root of the equation x^3 + x + 1."""
    "***YOUR CODE HERE***"

Now, we want to make this function more general. How can we write a new function g that takes in an argument y and finds the roots of:

f(x, y) = x^3 + y + 1

For any y value.

def g(y):
    """Returns at least one root of the equation x^3 + y + 1.

    >>> round(g(5), 3)
    -1.817
    """
    "***YOUR CODE HERE***"

Toggle Solution

def f():
    return newtons_method(lambda x: x**3 + x + 1

def g(y):
    return newtons_method(lambda x: x**3 + y + 1

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