3 unstable releases
Uses old Rust 2015
0.1.0 | Dec 20, 2016 |
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0.0.2 | Jun 29, 2015 |
0.0.1 | Jun 28, 2015 |
#1124 in Algorithms
78KB
1.5K
SLoC
Symbolic Polynomials
A Rust library for manipulation and evaluation of symbolic integer polynomials.
Template types arguments
All of the symbolic expressions have three template types associated with them.
- I - the type that uniquely identifies a single symbolic variable
- C - the type of the free coefficient in every monomial
- P - the type of the power used in every monomial
Overview
The main class you most likely will be using is Polynomial<I, C, P>
, which
represents any symbolic polynomial. The easiest way to create single variables
(e.g. like a
, b
, c
...) is by calling variable(I id)
. The will be a
unique identification of the variable. From there you can use standard
arithmetic operators with both other symbolic expressions and with constants.
If you want to evaluate a symbolic expression, you can call its eval
method,
which requires you to specify a mapping from unique identifiers to their assignments.
You can also use automatic deduction to solve a system of equations.
The ordering of both the polynomials and monomials are based on
Graded reverse lexicographic order
derived from the ordering on I
. Note that this requires the comparison operators
to be implemented for type I
.
The library provide implements Display
to convert any expression to a humanly
readable format. Additionally the to_code
method renders powers as repeated
multiplications, and the output string would look like code snippet.
One drawback is that all of the operators are defined for references.
Installation
Just add the dependency in your Cargo.toml
file and then import the crate.
Example usage
Below is the code for a the example found in the examples
folder.
use std::collections::HashMap;
extern crate symbolic_polynomials;
use symbolic_polynomials::*;
type SymInt = Polynomial<String, i64, u8>;
pub fn main() {
// Create symbolic variables
let a: SymInt = variable("a".into());
let b: SymInt = variable("b".into());
let c: SymInt = variable("c".into());
// Build polynomials
// 5b + 2
let poly1 = &(&b * 5) + 2;
// ab
let poly2 = &a * &b;
// ab + ac + b + c
let poly3 = &(&b + &c) * &(&a + 1);
// a^2 - ab + 12
let poly4 = &(&(&a * &a) - &(&a * &b)) + 12;
// ac^2 + 3a + bc^2 + 3b + c^2 + 3
let poly5 = &(&(&a + &b) + 1) * &(&(&c * 2) + 3);
// floor(a^2, b^2)
let poly6 = floor(&(&b * &b), &(&a * &a));
// ceil(a^2, b^2)
let poly7 = ceil(&(&b * &b), &(&a * &a));
// min(ab + 12, ab + a)
let poly8 = min(&(&(&a * &b) + 12), &(&(&a * &b) + &a));
// max (ab + 12, ab + a)
let poly9 = max(&(&(&a * &b) + 12), &(&(&a * &b) + &a));
// max(floor(a^2, b) - 4, ceil(c, b) + 1)
let poly10 = max(&(&floor(&(&a *&a), &b) - 2), &(&ceil(&c, &b) + 1));
// Polynomial printing
println!("{}", (0..50).map(|_| "=").collect::<String>());
println!("Displaying polynomials");
println!("{}", poly1);
println!("{}", poly2);
println!("{}", poly3);
println!("{}", poly4);
println!("{}", poly5);
println!("{}", poly6);
println!("{}", poly7);
println!("{}", poly8);
println!("{}", poly9);
println!("{}", poly10);
println!("{}", (0..50).map(|_| "=").collect::<String>());
// Polynomial evaluation
let mut values = HashMap::<String, i64>::new();
values.insert("a".into(), 3);
values.insert("b".into(), 2);
values.insert("c".into(), 5);
println!("Evaluating for a = 3, b = 2, c = 5.");
println!("{} = {} [Expected 12]", poly1, poly1.eval(&values).unwrap());
println!("{} = {} [Expected 6]", poly2, poly2.eval(&values).unwrap());
println!("{} = {} [Expected 28]", poly3, poly3.eval(&values).unwrap());
println!("{} = {} [Expected 15]", poly4, poly4.eval(&values).unwrap());
println!("{} = {} [Expected 78]", poly5, poly5.eval(&values).unwrap());
println!("{} = {} [Expected 0]", poly6, poly6.eval(&values).unwrap());
println!("{} = {} [Expected 1]", poly7, poly7.eval(&values).unwrap());
println!("{} = {} [Expected 9]", poly8, poly8.eval(&values).unwrap());
println!("{} = {} [Expected 18]", poly9, poly9.eval(&values).unwrap());
println!("{} = {} [Expected 4]", poly10, poly10.eval(&values).unwrap());
println!("{}", (0..50).map(|_| "=").collect::<String>());
// Variable deduction
values.insert("a".into(), 5);
values.insert("b".into(), 3);
values.insert("c".into(), 8);
let implicit_values = vec![(poly1.clone(), poly1.eval(&values).unwrap()),
(poly2.clone(), poly2.eval(&values).unwrap()),
(poly3.clone(), poly3.eval(&values).unwrap())];
let deduced_values = deduce_values(&implicit_values).unwrap();
println!("Deduced values:");
println!("a = {} [Expected 5]", deduced_values["a"]);
println!("b = {} [Expected 3]", deduced_values["b"]);
println!("c = {} [Expected 8]", deduced_values["c"]);
println!("{}", (0..50).map(|_| "=").collect::<String>());
}
The output of the program:
==================================================
Displaying polynomials (string representation = code representation):
5b + 2 = 5 * b + 2
ab = a * b
ab + ac + b + c = a * b + a * c + b + c
a^2 - ab + 12 = a * a - a * b + 12
2ac + 3a + 2bc + 3b + 2c + 3 = 2 * a * c + 3 * a + 2 * b * c + 3 * b + 2 * c + 3
floor(b^2, a^2) = floor(b * b, a * a)
ceil(b^2, a^2) = ceil(b * b, a * a)
min(ab + 12, ab + a) = min(a * b + 12, a * b + a)
max(ab + 12, ab + a) = max(a * b + 12, a * b + a)
max(floor(a^2, b) - 2, ceil(c, b) + 1) = max(floor(a * a, b) - 2, ceil(c, b) + 1)
==================================================
Evaluating for a = 3, b = 2, c = 5.
5b + 2 = 12 [Expected 12]
ab = 6 [Expected 6]
ab + ac + b + c = 28 [Expected 28]
a^2 - ab + 12 = 15 [Expected 15]
2ac + 3a + 2bc + 3b + 2c + 3 = 78 [Expected 78]
floor(b^2, a^2) = 0 [Expected 0]
ceil(b^2, a^2) = 1 [Expected 1]
min(ab + 12, ab + a) = 9 [Expected 9]
max(ab + 12, ab + a) = 18 [Expected 18]
max(floor(a^2, b) - 2, ceil(c, b) + 1) = 4 [Expected 4]
==================================================
Deduced values:
a = 5 [Expected 5]
b = 3 [Expected 3]
c = 8 [Expected 8]
==================================================
You can check out the tests in the tests
folder for more examples.
Limitations
Currently, the automatic deduction for solving system of equations is pretty limited. The main reason is that for the purposes that the project has been developed it is sufficient. A more powerful and complete algorithm would probably use Grobner basis.
License
The project is distrusted under the Apache 2.0 License.
Contributing
If you want to contribute in any way please make an Issue or submit a PR request describing its functionality.
Dependencies
~240KB