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//! Spline interpolations
//!
//! # Available splines
//!
//! * Cubic spline
//! * Cubic Hermite spline
//!
//! # `Spline` trait
//!
//! ## Methods
//!
//! Let `T: Into<f64> + Copy`
//! * `fn eval<T>(&self, x: T) -> f64` : Evaluate the spline at x
//! * `fn eval_vec<T>(&self, v: &[T]) -> Vec<f64>` : Evaluate spline values for an array v
//! * `fn polynomial_at<T>(&self, x: T) -> &Polynomial` : Get the polynomial at x
//! * `fn number_of_polynomials(&self) -> usize` : Get the number of polynomials
//! * `fn get_ranged_polynomials(&self) -> &Vec<(Range<f64>, Polynomial)>` : Get the polynomials
//! * `fn eval_with_cond<F>(&self, x: f64, cond: F) -> f64` : Evaluate the spline at x, with a condition
//! * `fn eval_vec_with_cond<F>(&self, v: &[f64], cond: F) -> Vec<f64>` : Evaluate spline values for an array v, with a condition
//!
//! # Low-level interface
//!
//! ## Members
//!
//! * `CubicSpline`: Structure for cubic spline
//! * `fn from_nodes(node_x: &[f64], node_y: &[f64]) -> Self` : Create a cubic spline from nodes
//! * `fn extend_with_nodes(&mut self, node_x: Vec<f64>, node_y: Vec<f64>)` : Extend the spline with nodes
//! * `CubicHermiteSpline`: Structure for cubic Hermite spline
//! * `fn from_nodes_with_slopes(node_x: &[f64], node_y: &[f64], m: &[f64]) -> Self` : Create a Cubic Hermite spline from nodes with slopes
//! * `fn from_nodes(node_x: &[f64], node_y: &[f64], slope_method: SlopeMethod) -> Self` : Create a Cubic Hermite spline from nodes with slope estimation methods
//! * `SlopeMethod`: Enum for slope estimation methods
//! * `Akima`: Akima's method to estimate slopes ([Akima (1970)](https://dl.acm.org/doi/abs/10.1145/321607.321609))
//! * `Quadratic`: Using quadratic interpolation to estimate slopes
//!
//! ## Usage
//!
//! ```rust
//! use peroxide::fuga::*;
//!
//! fn main() {
//! let x = seq(0, 10, 1);
//! let y = x.fmap(|t| t.sin());
//!
//! let cs = CubicSpline::from_nodes(&x, &y);
//! let cs_akima = CubicHermiteSpline::from_nodes(&x, &y, SlopeMethod::Akima);
//! let cs_quad = CubicHermiteSpline::from_nodes(&x, &y, SlopeMethod::Quadratic);
//!
//! cs.polynomial_at(0f64).print();
//! cs_akima.polynomial_at(0f64).print();
//! cs_quad.polynomial_at(0f64).print();
//! // -0.1523x^3 + 0.9937x
//! // 0.1259x^3 - 0.5127x^2 + 1.2283x
//! // -0.0000x^3 - 0.3868x^2 + 1.2283x
//!
//! let new_x = seq(4, 6, 0.1);
//! let new_y = new_x.fmap(|t| t.sin());
//!
//! let y_cs = cs.eval_vec(&new_x);
//! let y_akima = cs_akima.eval_vec(&new_x);
//! let y_quad = cs_quad.eval_vec(&new_x);
//!
//! let mut df = DataFrame::new(vec![]);
//! df.push("x", Series::new(new_x));
//! df.push("y", Series::new(new_y));
//! df.push("y_cs", Series::new(y_cs));
//! df.push("y_akima", Series::new(y_akima));
//! df.push("y_quad", Series::new(y_quad));
//!
//! df.print();
//! // x y y_cs y_akima y_quad
//! // r[0] 5 -0.9589 -0.9589 -0.9589 -0.9589
//! // r[1] 5.2 -0.8835 -0.8826 -0.8583 -0.8836
//! // r[2] 5.4 -0.7728 -0.7706 -0.7360 -0.7629
//! // r[3] 5.6 -0.6313 -0.6288 -0.5960 -0.6120
//! // r[4] 5.8 -0.4646 -0.4631 -0.4424 -0.4459
//! // r[5] 6 -0.2794 -0.2794 -0.2794 -0.2794
//! }
//! ```
//!
//! # High-level interface
//!
//! ## Functions
//!
//! * `fn cubic_spline(node_x: &[f64], node_y: &[f64]) -> CubicSpline` : Create a cubic spline from nodes
//! * `fn cubic_hermite_spline(node_x: &[f64], node_y: &[f64], m: &[f64]) -> CubicHermiteSpline` : Create a cubic Hermite spline from nodes with slopes
//!
//! ## Usage
//!
//! ```rust
//! use peroxide::fuga::*;
//!
//! fn main() {
//! let x = seq(0, 10, 1);
//! let y = x.fmap(|t| t.sin());
//!
//! let cs = cubic_spline(&x, &y);
//! let cs_akima = cubic_hermite_spline(&x, &y, SlopeMethod::Akima);
//! let cs_quad = cubic_hermite_spline(&x, &y, SlopeMethod::Quadratic);
//!
//! cs.polynomial_at(0f64).print();
//! cs_akima.polynomial_at(0f64).print();
//! cs_quad.polynomial_at(0f64).print();
//! // -0.1523x^3 + 0.9937x
//! // 0.1259x^3 - 0.5127x^2 + 1.2283x
//! // -0.0000x^3 - 0.3868x^2 + 1.2283x
//!
//! let new_x = seq(4, 6, 0.1);
//! let new_y = new_x.fmap(|t| t.sin());
//!
//! let y_cs = cs.eval_vec(&new_x);
//! let y_akima = cs_akima.eval_vec(&new_x);
//! let y_quad = cs_quad.eval_vec(&new_x);
//!
//! let mut df = DataFrame::new(vec![]);
//! df.push("x", Series::new(new_x));
//! df.push("y", Series::new(new_y));
//! df.push("y_cs", Series::new(y_cs));
//! df.push("y_akima", Series::new(y_akima));
//! df.push("y_quad", Series::new(y_quad));
//!
//! df.print();
//! // x y y_cs y_akima y_quad
//! // r[0] 5 -0.9589 -0.9589 -0.9589 -0.9589
//! // r[1] 5.2 -0.8835 -0.8826 -0.8583 -0.8836
//! // r[2] 5.4 -0.7728 -0.7706 -0.7360 -0.7629
//! // r[3] 5.6 -0.6313 -0.6288 -0.5960 -0.6120
//! // r[4] 5.8 -0.4646 -0.4631 -0.4424 -0.4459
//! // r[5] 6 -0.2794 -0.2794 -0.2794 -0.2794
//! }
//! ```
//!
//! # Calculus with splines
//!
//! ## Usage
//!
//! ```rust
//! use peroxide::fuga::*;
//! use std::f64::consts::PI;
//!
//! fn main() {
//! let x = seq(0, 10, 1);
//! let y = x.fmap(|t| t.sin());
//!
//! let cs = cubic_spline(&x, &y);
//! let cs_akima = cubic_hermite_spline(&x, &y, SlopeMethod::Akima);
//! let cs_quad = cubic_hermite_spline(&x, &y, SlopeMethod::Quadratic);
//!
//! println!("============ Polynomial at x=0 ============");
//!
//! cs.polynomial_at(0f64).print();
//! cs_akima.polynomial_at(0f64).print();
//! cs_quad.polynomial_at(0f64).print();
//!
//! println!("============ Derivative at x=0 ============");
//!
//! cs.derivative().polynomial_at(0f64).print();
//! cs_akima.derivative().polynomial_at(0f64).print();
//! cs_quad.derivative().polynomial_at(0f64).print();
//!
//! println!("============ Integral at x=0 ============");
//!
//! cs.integral().polynomial_at(0f64).print();
//! cs_akima.integral().polynomial_at(0f64).print();
//! cs_quad.integral().polynomial_at(0f64).print();
//!
//! println!("============ Integrate from x=0 to x=pi ============");
//!
//! cs.integrate((0f64, PI)).print();
//! cs_akima.integrate((0f64, PI)).print();
//! cs_quad.integrate((0f64, PI)).print();
//!
//! // ============ Polynomial at x=0 ============
//! // -0.1523x^3 + 0.9937x
//! // 0.1259x^3 - 0.5127x^2 + 1.2283x
//! // -0.0000x^3 - 0.3868x^2 + 1.2283x
//! // ============ Derivative at x=0 ============
//! // -0.4568x^2 + 0.9937
//! // 0.3776x^2 - 1.0254x + 1.2283
//! // -0.0000x^2 - 0.7736x + 1.2283
//! // ============ Integral at x=0 ============
//! // -0.0381x^4 + 0.4969x^2
//! // 0.0315x^4 - 0.1709x^3 + 0.6141x^2
//! // -0.0000x^4 - 0.1289x^3 + 0.6141x^2
//! // ============ Integrate from x=0 to x=pi ============
//! // 1.9961861265456702
//! // 2.0049920614062775
//! // 2.004327391790717
//! }
//! ```
//!
//! # References
//!
//! * Gary D. Knott, *Interpolating Splines*, Birkhäuser Boston, MA, (2000).
#[allow(unused_imports)]
use crate::structure::matrix::*;
#[allow(unused_imports)]
use crate::structure::polynomial::*;
#[allow(unused_imports)]
use crate::structure::vector::*;
use peroxide_num::PowOps;
#[allow(unused_imports)]
use crate::util::non_macro::*;
use crate::util::useful::zip_range;
#[cfg(feature = "serde")]
use serde::{Deserialize, Serialize};
use std::cmp::{max, min};
use std::convert::{From, Into};
use std::ops::{Index, Range};
/// Trait for spline interpolation
///
/// # Available Splines
///
/// - `CubicSpline`
/// - `CubicHermiteSpline`
pub trait Spline {
fn eval<T: std::convert::Into<f64> + Copy>(&self, x: T) -> f64 {
let x = x.into();
self.polynomial_at(x).eval(x)
}
fn eval_vec<T: std::convert::Into<f64> + Copy>(&self, v: &[T]) -> Vec<f64> {
let mut result = vec![0f64; v.len()];
for (i, x) in v.iter().enumerate() {
result[i] = self.eval(*x);
}
result
}
fn polynomial_at<T: std::convert::Into<f64> + Copy>(&self, x: T) -> &Polynomial {
let x = x.into();
let poly = self.get_ranged_polynomials();
let index = match poly.binary_search_by(|(range, _)| {
if range.contains(&x) {
core::cmp::Ordering::Equal
} else if x < range.start {
core::cmp::Ordering::Greater
} else {
core::cmp::Ordering::Less
}
}) {
Ok(index) => index,
Err(index) => max(0, min(index, poly.len() - 1)),
};
&poly[index].1
}
fn number_of_polynomials(&self) -> usize {
self.get_ranged_polynomials().len()
}
fn get_ranged_polynomials(&self) -> &Vec<(Range<f64>, Polynomial)>;
fn eval_with_cond<F: Fn(f64) -> f64>(&self, x: f64, cond: F) -> f64 {
cond(self.eval(x))
}
fn eval_vec_with_cond<F: Fn(f64) -> f64 + Copy>(&self, x: &[f64], cond: F) -> Vec<f64> {
x.iter().map(|&x| self.eval_with_cond(x, cond)).collect()
}
}
// =============================================================================
// High level functions
// =============================================================================
/// Cubic Spline (Natural)
///
/// # Description
///
/// Implement traits of Natural cubic splines, by Arne Morten Kvarving.
///
/// # Type
/// `(&[f64], &[f64]) -> Cubic Spline`
///
/// # Examples
/// ```
/// #[macro_use]
/// extern crate peroxide;
/// use peroxide::fuga::*;
///
/// fn main() {
/// let x = c!(0.9, 1.3, 1.9, 2.1);
/// let y = c!(1.3, 1.5, 1.85, 2.1);
///
/// let s = cubic_spline(&x, &y);
///
/// let new_x = c!(1, 1.5, 2.0);
///
/// // Generate Cubic polynomial
/// for t in new_x.iter() {
/// s.polynomial_at(*t).print();
/// }
/// // -0.2347x^3 + 0.6338x^2 - 0.0329x + 0.9873
/// // 0.9096x^3 - 3.8292x^2 + 5.7691x - 1.5268
/// // -2.2594x^3 + 14.2342x^2 - 28.5513x + 20.2094
///
/// // Evaluation
/// for t in new_x.iter() {
/// s.eval(*t).print();
/// }
/// }
/// ```
pub fn cubic_spline(node_x: &[f64], node_y: &[f64]) -> CubicSpline {
CubicSpline::from_nodes(node_x, node_y)
}
pub fn cubic_hermite_spline(node_x: &[f64], node_y: &[f64], slope_method: SlopeMethod) -> CubicHermiteSpline {
CubicHermiteSpline::from_nodes(node_x, node_y, slope_method)
}
// =============================================================================
// Cubic Spline
// =============================================================================
/// Cubic Spline (Natural)
///
/// # Description
///
/// Implement traits of Natural cubic splines, by Arne Morten Kvarving.
///
/// # Type
/// `(&[f64], &[f64]) -> Cubic Spline`
///
/// # Examples
/// ```
/// #[macro_use]
/// extern crate peroxide;
/// use peroxide::fuga::*;
///
/// fn main() {
/// let x = c!(0.9, 1.3, 1.9, 2.1);
/// let y = c!(1.3, 1.5, 1.85, 2.1);
///
/// let s = CubicSpline::from_nodes(&x, &y);
///
/// let new_x = c!(1, 1.5, 2.0);
///
/// // Generate Cubic polynomial
/// for t in new_x.iter() {
/// s.polynomial_at(*t).print();
/// }
/// // -0.2347x^3 + 0.6338x^2 - 0.0329x + 0.9873
/// // 0.9096x^3 - 3.8292x^2 + 5.7691x - 1.5268
/// // -2.2594x^3 + 14.2342x^2 - 28.5513x + 20.2094
///
/// // Evaluation
/// for t in new_x.iter() {
/// s.eval(*t).print();
/// }
/// }
/// ```
#[derive(Debug, Clone, Default)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub struct CubicSpline {
polynomials: Vec<(Range<f64>, Polynomial)>,
}
impl Spline for CubicSpline {
fn get_ranged_polynomials(&self) -> &Vec<(Range<f64>, Polynomial)> {
&self.polynomials
}
}
impl CubicSpline {
/// # Examples
/// ```
/// #[macro_use]
/// extern crate peroxide;
/// use peroxide::fuga::*;
///
/// fn main() {
/// let x = c!(0.9, 1.3, 1.9, 2.1);
/// let y = c!(1.3, 1.5, 1.85, 2.1);
///
/// let s = CubicSpline::from_nodes(&x, &y);
///
/// for i in 0 .. 4 {
/// println!("{}", s.eval(i as f64 / 2.0));
/// }
/// }
/// ```
pub fn from_nodes(node_x: &[f64], node_y: &[f64]) -> Self {
let polynomials = CubicSpline::cubic_spline(node_x, node_y);
CubicSpline {
polynomials: zip_range(node_x, &polynomials),
}
}
fn cubic_spline(node_x: &[f64], node_y: &[f64]) -> Vec<Polynomial> {
//! Pre calculated variables
//! node_x: n+1
//! node_y: n+1
//! h : n
//! b : n
//! v : n
//! u : n
//! z : n+1
let n = node_x.len() - 1;
assert_eq!(n, node_y.len() - 1);
// Pre-calculations
let mut h = vec![0f64; n];
let mut b = vec![0f64; n];
let mut v = vec![0f64; n];
let mut u = vec![0f64; n];
for i in 0..n {
if i == 0 {
h[i] = node_x[i + 1] - node_x[i];
b[i] = (node_y[i + 1] - node_y[i]) / h[i];
} else {
h[i] = node_x[i + 1] - node_x[i];
b[i] = (node_y[i + 1] - node_y[i]) / h[i];
v[i] = 2. * (h[i] + h[i - 1]);
u[i] = 6. * (b[i] - b[i - 1]);
}
}
// Tri-diagonal matrix
let mut m = matrix(vec![0f64; (n - 1) * (n - 1)], n - 1, n - 1, Col);
for i in 0..n - 2 {
m[(i, i)] = v[i + 1];
m[(i + 1, i)] = h[i + 1];
m[(i, i + 1)] = h[i + 1];
}
m[(n - 2, n - 2)] = v[n - 1];
// Calculate z
let z_inner = m.inv() * Vec::from(&u[1..]);
let mut z = vec![0f64];
z.extend(&z_inner);
z.push(0f64);
// Declare empty spline
let mut s: Vec<Polynomial> = Vec::new();
// Main process
for i in 0..n {
// Memoization
let t_i = node_x[i];
let t_i1 = node_x[i + 1];
let z_i = z[i];
let z_i1 = z[i + 1];
let h_i = h[i];
let y_i = node_y[i];
let y_i1 = node_y[i + 1];
let temp1 = poly(vec![1f64, -t_i]);
let temp2 = poly(vec![1f64, -t_i1]);
let term1 = temp1.powi(3) * (z_i1 / (6f64 * h_i));
let term2 = temp2.powi(3) * (-z_i / (6f64 * h_i));
let term3 = temp1 * (y_i1 / h_i - z_i1 * h_i / 6.);
let term4 = temp2 * (-y_i / h_i + h_i * z_i / 6.0);
s.push(term1 + term2 + term3 + term4);
}
return s;
}
/// Extends the spline with the given nodes.
///
/// # Description
///
/// The method ensures that the transition between each polynomial is smooth and that the spline
/// interpolation of the new nodes is calculated around `x = 0` in order to avoid that
/// successive spline extensions with large x values become inaccurate.
pub fn extend_with_nodes(&mut self, node_x: Vec<f64>, node_y: Vec<f64>) {
let mut ext_node_x = Vec::with_capacity(node_x.len() + 1);
let mut ext_node_y = Vec::with_capacity(node_x.len() + 1);
let (r, polynomial) = &self.polynomials[self.polynomials.len() - 1];
ext_node_x.push(0.0f64);
ext_node_y.push(polynomial.eval(r.end));
// translating the node towards x = 0 increases accuracy tremendously
let tx = r.end;
ext_node_x.extend(node_x.into_iter().map(|x| x - tx));
ext_node_y.extend(node_y);
let polynomials = zip_range(
&ext_node_x,
&CubicSpline::cubic_spline(&ext_node_x, &ext_node_y),
);
self.polynomials
.extend(polynomials.into_iter().map(|(r, p)| {
(
Range {
start: r.start + tx,
end: r.end + tx,
},
p.translate_x(tx),
)
}));
}
}
impl std::convert::Into<Vec<Polynomial>> for CubicSpline {
fn into(self) -> Vec<Polynomial> {
self.polynomials
.into_iter()
.map(|(_, polynomial)| polynomial)
.collect()
}
}
impl From<Vec<(Range<f64>, Polynomial)>> for CubicSpline {
fn from(polynomials: Vec<(Range<f64>, Polynomial)>) -> Self {
CubicSpline { polynomials }
}
}
impl Into<Vec<(Range<f64>, Polynomial)>> for CubicSpline {
fn into(self) -> Vec<(Range<f64>, Polynomial)> {
self.polynomials
}
}
impl Index<usize> for CubicSpline {
type Output = (Range<f64>, Polynomial);
fn index(&self, index: usize) -> &Self::Output {
&self.polynomials[index]
}
}
impl Calculus for CubicSpline {
fn derivative(&self) -> Self {
let mut polynomials: Vec<(Range<f64>, Polynomial)> = self.clone().into();
polynomials = polynomials
.into_iter()
.map(|(r, poly)| (r, poly.derivative()))
.collect();
Self::from(polynomials)
}
fn integral(&self) -> Self {
let mut polynomials: Vec<(Range<f64>, Polynomial)> = self.clone().into();
polynomials = polynomials
.into_iter()
.map(|(r, poly)| (r, poly.integral()))
.collect();
Self::from(polynomials)
}
fn integrate<T: Into<f64> + Copy>(&self, interval: (T, T)) -> f64 {
let (a, b) = interval;
let a = a.into();
let b = b.into();
let mut s = 0f64;
for (r, p) in self.polynomials.iter() {
if r.start > b {
break;
} else if r.end < a {
continue;
} else {
// r.start <= b, r.end >= a
let x = r.start.max(a);
let y = r.end.min(b);
s += p.integrate((x, y));
}
}
s
}
}
// =============================================================================
// Cubic Hermite Spline
// =============================================================================
#[derive(Debug, Clone)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub struct CubicHermiteSpline {
polynomials: Vec<(Range<f64>, Polynomial)>,
}
impl Spline for CubicHermiteSpline {
fn get_ranged_polynomials(&self) -> &Vec<(Range<f64>, Polynomial)> {
&self.polynomials
}
}
impl CubicHermiteSpline {
pub fn from_nodes_with_slopes(node_x: &[f64], node_y: &[f64], m: &[f64]) -> Self {
let mut r = vec![Range::default(); node_x.len()-1];
let mut u = vec![Polynomial::default(); node_x.len()-1];
for i in 0 .. node_x.len()-1 {
let a_i = node_y[i];
let b_i = m[i];
let dx = node_x[i+1] - node_x[i];
let dy = node_y[i+1] - node_y[i];
let c_i = (3f64 * dy/dx - 2f64*m[i] - m[i+1]) / dx;
let d_i = (m[i] + m[i+1] - 2f64 * dy/dx) / dx.powi(2);
let p = Polynomial::new(vec![1f64, -node_x[i]]);
r[i] = Range { start: node_x[i], end: node_x[i+1] };
u[i] = p.powi(3) * d_i + p.powi(2) * c_i + p.clone() * b_i;
u[i].coef[3] += a_i;
}
CubicHermiteSpline {
polynomials: r.into_iter().zip(u).collect(),
}
}
pub fn from_nodes(node_x: &[f64], node_y: &[f64], slope_method: SlopeMethod) -> Self {
match slope_method {
SlopeMethod::Akima => {
CubicHermiteSpline::from_nodes_with_slopes(node_x, node_y, &akima_slopes(node_x, node_y))
},
SlopeMethod::Quadratic => {
CubicHermiteSpline::from_nodes_with_slopes(node_x, node_y, &quadratic_slopes(node_x, node_y))
},
}
}
}
impl std::convert::Into<Vec<Polynomial>> for CubicHermiteSpline {
fn into(self) -> Vec<Polynomial> {
self.polynomials
.into_iter()
.map(|(_, polynomial)| polynomial)
.collect()
}
}
impl From<Vec<(Range<f64>, Polynomial)>> for CubicHermiteSpline {
fn from(polynomials: Vec<(Range<f64>, Polynomial)>) -> Self {
CubicHermiteSpline { polynomials }
}
}
impl Into<Vec<(Range<f64>, Polynomial)>> for CubicHermiteSpline {
fn into(self) -> Vec<(Range<f64>, Polynomial)> {
self.polynomials
}
}
impl Index<usize> for CubicHermiteSpline {
type Output = (Range<f64>, Polynomial);
fn index(&self, index: usize) -> &Self::Output {
&self.polynomials[index]
}
}
impl Calculus for CubicHermiteSpline {
fn derivative(&self) -> Self {
let mut polynomials: Vec<(Range<f64>, Polynomial)> = self.clone().into();
polynomials = polynomials
.into_iter()
.map(|(r, poly)| (r, poly.derivative()))
.collect();
Self::from(polynomials)
}
fn integral(&self) -> Self {
let mut polynomials: Vec<(Range<f64>, Polynomial)> = self.clone().into();
polynomials = polynomials
.into_iter()
.map(|(r, poly)| (r, poly.integral()))
.collect();
Self::from(polynomials)
}
fn integrate<T: Into<f64> + Copy>(&self, interval: (T, T)) -> f64 {
let (a, b) = interval;
let a = a.into();
let b = b.into();
let mut s = 0f64;
for (r, p) in self.polynomials.iter() {
if r.start > b {
break;
} else if r.end < a {
continue;
} else {
// r.start <= b, r.end >= a
let x = r.start.max(a);
let y = r.end.min(b);
s += p.integrate((x, y));
}
}
s
}
}
// =============================================================================
// Estimate Slopes
// =============================================================================
#[derive(Debug, Copy, Clone, PartialEq, Eq)]
pub enum SlopeMethod {
Akima,
Quadratic,
}
fn akima_slopes(x: &[f64], y: &[f64]) -> Vec<f64> {
if x.len() < 3 {
panic!("Cubic spline need at least 3 nodes");
}
let mut m = vec![0f64; x.len()];
let mut s = vec![0f64; x.len()+3]; // -2, -1, 0, ..., x.len()-1, x.len()
let l_i = lagrange_polynomial(x[0..3].to_vec(), y[0..3].to_vec());
let l_f = lagrange_polynomial(x[x.len()-3..].to_vec(), y[y.len()-3..].to_vec());
let x_i = x[0] - (x[1] - x[0]) / 10f64;
let x_ii = x_i - (x[1] - x[0]) / 10f64;
let x_f = x[x.len()-1] + (x[x.len()-1] - x[x.len()-2]) / 10f64;
let x_ff = x_f + (x[x.len()-1] - x[x.len()-2]) / 10f64;
let y_i = l_i.eval(x_i);
let y_ii = l_i.eval(x_ii);
let y_f = l_f.eval(x_f);
let y_ff = l_f.eval(x_ff);
let new_x = concat(&concat(&vec![x_ii, x_i], &x.to_vec()), &vec![x_f, x_ff]);
let new_y = concat(&concat(&vec![y_ii, y_i], &y.to_vec()), &vec![y_f, y_ff]);
for i in 0 .. new_x.len()-1 {
let dx = new_x[i+1] - new_x[i];
if dx == 0f64 {
panic!("x nodes should be different!");
}
s[i] = (new_y[i+1] - new_y[i]) / dx;
}
for i in 0 .. x.len() {
let j = i+2;
let ds_f = (s[j+1] - s[j]).abs();
let ds_i = (s[j-1] - s[j-2]).abs();
m[i] = if ds_f == 0f64 && ds_i == 0f64 {
(s[j-1] + s[j]) / 2f64
} else {
(ds_f * s[j-1] + ds_i * s[j]) / (ds_f + ds_i)
};
}
m
}
fn quadratic_slopes(x: &[f64], y: &[f64]) -> Vec<f64> {
let mut m = vec![0f64; x.len()];
let q_i = lagrange_polynomial(x[0..3].to_vec(), y[0..3].to_vec());
let q_f = lagrange_polynomial(x[x.len()-3..].to_vec(), y[y.len()-3..].to_vec());
m[0] = q_i.derivative().eval(x[0]);
m[x.len()-1] = q_f.derivative().eval(x[x.len()-1]);
for i in 1 .. x.len()-1 {
let q = lagrange_polynomial(x[i-1..i+2].to_vec(), y[i-1..i+2].to_vec());
m[i] = q.derivative().eval(x[i]);
}
m
}