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/* This file is part of bacon. * Copyright (c) Wyatt Campbell. * * See repository LICENSE for information. */ use alga::general::{ComplexField, RealField}; use nalgebra::DVector; mod polynomial; pub use polynomial::*; /// Use the bisection method to solve for a zero of an equation. /// /// This function takes an interval and uses a binary search to find /// where in that interval a function has a root. The signs of the function /// at each end of the interval must be different /// /// # Returns /// Ok(root) when a root has been found, Err on failure /// /// # Params /// `(left, right)` The starting interval. f(left) * f(right) > 0.0 /// /// `f` The function to find the root for /// /// `tol` The tolerance of the relative error between iterations. /// /// `n_max` The maximum number of iterations to use. /// /// # Examples /// ``` /// use nalgebra::DVector; /// use bacon_sci::roots::bisection; /// /// fn cubic(x: f64) -> f64 { /// x*x*x /// } /// //... /// fn example() { /// let solution = bisection((-1.0, 1.0), cubic, 0.001, 1000).unwrap(); /// } /// ``` pub fn bisection<N: RealField>( (mut left, mut right): (N, N), f: fn(N) -> N, tol: N, n_max: usize, ) -> Result<N, String> { if left >= right { return Err("Bisection: requirement: right > left".to_owned()); } let mut n = 1; let mut f_a = f(left); if (f_a * f(right)).is_sign_positive() { return Err("Bisection: requirement: Signs must be different".to_owned()); } let mut half_interval = (left - right) * N::from_f64(0.5).unwrap(); let mut middle = left + half_interval; if middle.abs() <= tol { return Ok(middle); } while n <= n_max { let f_p = f(middle); if (f_p * f_a).is_sign_positive() { left = middle; f_a = f_p; } else { right = middle; } half_interval = (right - left) * N::from_f64(0.5).unwrap(); let middle_new = left + half_interval; if (middle - middle_new).abs() / middle.abs() < tol || middle_new.abs() < tol { return Ok(middle_new); } middle = middle_new; n += 1; } Err("Bisection: Maximum iterations exceeded".to_owned()) } /// Use steffenson's method to find a fixed point /// /// Use steffenson's method to find a value x so that f(x) = x, given /// a starting point. /// /// # Returns /// `Ok(x)` so that `f(x) - x < tol` on success, `Err` on failure /// /// # Params /// `initial` inital guess for the fixed point /// /// `f` Function to find the fixed point of /// /// `tol` Tolerance from 0 to try and achieve /// /// `n_max` maximum number of iterations /// /// # Examples /// ``` /// use bacon_sci::roots::steffensen; /// fn cosine(x: f64) -> f64 { /// x.cos() /// } /// //... /// fn example() -> Result<(), String> { /// let solution = steffensen(0.5f64, cosine, 0.0001, 1000)?; /// Ok(()) /// } pub fn steffensen<N: RealField + From<f64> + Copy>( mut initial: N, f: fn(N) -> N, tol: N, n_max: usize, ) -> Result<N, String> { let mut n = 0; while n < n_max { let guess = f(initial); let new_guess = f(guess); let diff = initial - (guess - initial).powi(2) / (new_guess - N::from(2.0) * guess + initial); if (diff - initial).abs() <= tol { return Ok(diff); } initial = diff; n += 1; } Err("Steffensen: Maximum number of iterations exceeded".to_owned()) } /// Use Newton's method to find a root of a vector function. /// /// Using a vector function and its derivative, find a root based on an initial guess /// using Newton's method. /// /// # Returns /// `Ok(vec)` on success, where `vec` is a vector input for which the function is /// zero. `Err` on failure. /// /// # Params /// `initial` Initial guess of the root. Should be near actual root. Slice since this /// function finds roots of vector functions. /// /// `f` Vector function for which to find the root /// /// `f_deriv` Derivative of `f` /// /// `tol` tolerance for error between iterations of Newton's method /// /// `n_max` Maximum number of iterations /// /// # Examples /// ``` /// use nalgebra::DVector; /// use bacon_sci::roots::newton; /// fn cubic(x: &[f64]) -> DVector<f64> { /// DVector::from_iterator(x.len(), x.iter().map(|x| x.powi(3))) /// } /// /// fn cubic_deriv(x: &[f64]) -> DVector<f64> { /// DVector::from_iterator(x.len(), x.iter().map(|x| 3.0*x.powi(2))) /// } /// //... /// fn example() { /// let solution = newton(&[0.1], cubic, cubic_deriv, 0.001, 1000).unwrap(); /// } /// ``` pub fn newton<N: ComplexField>( initial: &[N], f: fn(&[N]) -> DVector<N>, f_deriv: fn(&[N]) -> DVector<N>, tol: <N as ComplexField>::RealField, n_max: usize, ) -> Result<DVector<N>, String> { let mut guess = DVector::from_column_slice(initial); let mut norm = guess.dot(&guess).sqrt().abs(); let mut n = 0; if norm <= tol { return Ok(guess); } while n < n_max { let f_val = f(guess.column(0).as_slice()); let f_deriv_val = f_deriv(guess.column(0).as_slice()); let adjustment = DVector::from_iterator( guess.column(0).len(), f_val .column(0) .iter() .zip(f_deriv_val.column(0).iter()) .map(|(f, f_d)| *f / *f_d), ); let new_guess = &guess - adjustment; let new_norm = new_guess.dot(&new_guess).sqrt().abs(); if ((norm - new_norm) / norm).abs() <= tol || new_norm <= tol { return Ok(new_guess); } norm = new_norm; guess = new_guess; n += 1; } Err("Newton: Maximum iterations exceeded".to_owned()) } /// Use secant method to find a root of a vector function. /// /// Using a vector function and its derivative, find a root based on two initial guesses /// using secant method. /// /// # Returns /// `Ok(vec)` on success, where `vec` is a vector input for which the function is /// zero. `Err` on failure. /// /// # Params /// `initial` Initial guesses of the root. Should be near actual root. Slice since this /// function finds roots of vector functions. /// /// `f` Vector function for which to find the root /// /// `tol` tolerance for error between iterations of Newton's method /// /// `n_max` Maximum number of iterations /// /// # Examples /// ``` /// use nalgebra::DVector; /// use bacon_sci::roots::secant; /// fn cubic(x: &[f64]) -> DVector<f64> { /// DVector::from_iterator(x.len(), x.iter().map(|x| x.powi(3))) /// } /// //... /// fn example() { /// let solution = secant((&[0.1], &[-0.1]), cubic, 0.001, 1000).unwrap(); /// } /// ``` pub fn secant<N: ComplexField>( initial: (&[N], &[N]), f: fn(&[N]) -> DVector<N>, tol: <N as ComplexField>::RealField, n_max: usize, ) -> Result<DVector<N>, String> { let mut n = 0; let mut left = DVector::from_column_slice(initial.0); let mut right = DVector::from_column_slice(initial.1); let mut left_val = f(initial.0); let mut right_val = f(initial.1); let mut norm = right.dot(&right).sqrt().abs(); if norm <= tol { return Ok(right); } while n <= n_max { let adjustment = DVector::from_iterator( right_val.iter().len(), right_val.iter().enumerate().map(|(i, q)| { *q * (*right.get(i).unwrap() - *left.get(i).unwrap()) / (*q - *left_val.get(i).unwrap()) }), ); let new_guess = &right - adjustment; let new_norm = new_guess.dot(&new_guess).sqrt().abs(); if ((norm - new_norm) / norm).abs() <= tol || new_norm <= tol { return Ok(new_guess); } norm = new_norm; left_val = right_val; left = right; right = new_guess; right_val = f(right.column(0).as_slice()); n += 1; } Err("Secant: Maximum iterations exceeded".to_owned()) } /* pub fn muller<N: ComplexField+From<f64>+Into<N>>( initial: (N, N, N), f: fn(N) -> N, tol: <N as ComplexField>::RealField, n_max: usize ) -> Result<N, String> { let mut n = 0; let mut poly_0 = initial.0; let mut poly_1 = initial.1; let mut poly_2 = initial.2; let mut h_1 = poly_1 - poly_0; let mut h_2 = poly_2 - poly_1; let mut f_at_1 = f(poly_1); let mut f_at_2 = f(poly_2); let mut delta_1 = (f_at_1 - f(poly_0)) / h_2; let mut delta_2 = (f_at_2 - f_at_1) / h_2; let mut d = (delta_2 - delta_1) / (h_2 + h_1); while n < n_max { let b = delta_2 + h_2*d; let determinant = (b.powi(2) - N::from(4.0)*f_at_2*d).sqrt(); let error = if (b - determinant).abs() < (b + determinant).abs() { b + determinant } else { b - determinant }; let h = N::from(-2.0) * f_at_2 / error; let p = poly_2 + h; if h.abs() <= tol { return Ok(p); } poly_0 = poly_1; poly_1 = poly_2; poly_2 = p; f_at_1 = f(poly_1); f_at_2 = f(poly_2); h_1 = poly_1 - poly_2; h_2 = poly_2 - poly_1; delta_1 = (f_at_1 - f(poly_0)) / h_1; delta_2 = (f_at_2 - f_at_1) / h_2; d = (delta_2 - delta_1) / (h_1 + h_2); n += 1; } Err("Muller: maximum iterations exceeded".to_owned()) } */