refactor newton's method code

This commit is contained in:
Simon Gardling
2022-03-10 10:27:53 -05:00
parent cc2722e58c
commit 3e00657ade
2 changed files with 92 additions and 99 deletions

View File

@@ -2,7 +2,7 @@
use crate::function_output::FunctionOutput;
#[allow(unused_imports)]
use crate::misc::{debug_log, SteppedVector};
use crate::misc::{debug_log, newtons_method, SteppedVector};
use crate::egui_app::{DEFAULT_FUNCION, DEFAULT_RIEMANN};
use crate::parsing::BackingFunction;
@@ -228,109 +228,35 @@ impl FunctionEntry {
// Finds roots
fn roots(&mut self) {
let resolution: f64 = (self.pixel_width as f64 / (self.max_x - self.min_x).abs()) as f64;
let mut root_list: Vec<Value> = Vec::new();
let mut last_ele: Option<Value> = None;
for ele in self.output.back.as_ref().unwrap().iter() {
if last_ele.is_none() {
last_ele = Some(*ele);
continue;
}
let last_ele_signum = last_ele.unwrap().y.signum();
let ele_signum = ele.y.signum();
if last_ele_signum.is_nan() | ele_signum.is_nan() {
continue;
}
if last_ele_signum != ele_signum {
// Do 50 iterations of newton's method, should be more than accurate
let x = {
let mut x1: f64 = last_ele.unwrap().x;
let mut x2: f64;
let mut fail: bool = false;
loop {
x2 = x1 - (self.function.get(x1) / self.function.get_derivative_1(x1));
if !(self.min_x..self.max_x).contains(&x2) {
fail = true;
break;
}
if (x2 - x1).abs() < resolution {
break;
}
x1 = x2;
}
match fail {
true => f64::NAN,
false => x1,
}
};
if !x.is_nan() {
root_list.push(Value::new(x, self.function.get(x)));
}
}
last_ele = Some(*ele);
}
self.output.roots = Some(root_list);
self.output.roots = Some(
newtons_method(
resolution,
self.min_x..self.max_x,
self.output.back.to_owned().unwrap(),
&|x: f64| self.function.get(x),
&|x: f64| self.function.get_derivative_1(x),
)
.iter()
.map(|x| Value::new(*x, self.function.get(*x)))
.collect(),
);
}
// Finds extrema
fn extrema(&mut self) {
let resolution: f64 = (self.pixel_width as f64 / (self.max_x - self.min_x).abs()) as f64;
let mut extrama_list: Vec<Value> = Vec::new();
let mut last_ele: Option<Value> = None;
for ele in self.output.derivative.as_ref().unwrap().iter() {
if last_ele.is_none() {
last_ele = Some(*ele);
continue;
}
let last_ele_signum = last_ele.unwrap().y.signum();
let ele_signum = ele.y.signum();
if last_ele_signum.is_nan() | ele_signum.is_nan() {
continue;
}
if last_ele_signum != ele_signum {
// Do 50 iterations of newton's method, should be more than accurate
let x = {
let mut x1: f64 = last_ele.unwrap().x;
let mut x2: f64;
let mut fail: bool = false;
loop {
x2 = x1
- (self.function.get_derivative_1(x1)
/ self.function.get_derivative_2(x1));
if !(self.min_x..self.max_x).contains(&x2) {
fail = true;
break;
}
if (x2 - x1).abs() < resolution {
break;
}
x1 = x2;
}
match fail {
true => f64::NAN,
false => x1,
}
};
if !x.is_nan() {
extrama_list.push(Value::new(x, self.function.get(x)));
}
}
last_ele = Some(*ele);
}
self.output.extrema = Some(extrama_list);
self.output.extrema = Some(
newtons_method(
resolution,
self.min_x..self.max_x,
self.output.derivative.to_owned().unwrap(),
&|x: f64| self.function.get_derivative_1(x),
&|x: f64| self.function.get_derivative_2(x),
)
.iter()
.map(|x| Value::new(*x, self.function.get(*x)))
.collect(),
);
}
pub fn display(