oxiz_math/lib.rs
1//! # oxiz-math
2//!
3//! Mathematical foundations for the OxiZ SMT solver.
4//!
5//! This crate provides Pure Rust implementations of mathematical algorithms
6//! required for SMT solving, including:
7//!
8//! ## Linear Arithmetic
9//! - **Simplex**: Dual simplex algorithm for linear programming (LRA theory)
10//! - **Interior Point**: Primal-dual interior point method for large-scale LP
11//! - **Matrix**: Dense and sparse matrix operations with Gaussian elimination
12//! - **Interval**: Interval arithmetic for bound propagation
13//! - **Delta Rational**: Support for strict inequalities in simplex
14//! - **BLAS**: High-performance BLAS operations for large-scale LP (1000+ variables)
15//!
16//! ## Non-Linear Arithmetic
17//! - **Polynomial**: Multivariate polynomial arithmetic with GCD and factorization
18//! - **Rational Function**: Arithmetic on quotients of polynomials (p/q operations)
19//! - **Gröbner**: Gröbner basis computation (Buchberger, F4, and F5 algorithms)
20//! - **Real Closure**: Algebraic number representation and root isolation
21//! - **Hilbert**: Hilbert basis computation for integer cones
22//!
23//! ## Decision Diagrams
24//! - **BDD**: Reduced Ordered Binary Decision Diagrams
25//! - **ZDD**: Zero-suppressed BDDs for sparse set representation
26//! - **ADD**: Algebraic Decision Diagrams for rational-valued functions
27//!
28//! ## Numerical Utilities
29//! - **Rational**: Arbitrary precision rational arithmetic utilities
30//! - **MPFR**: Arbitrary precision floating-point arithmetic (MPFR-like)
31//!
32//! # Examples
33//!
34//! ## Polynomial Arithmetic
35//!
36//! ```
37//! use oxiz_math::polynomial::{Polynomial, Var};
38//!
39//! // Create polynomial for variable x (index 0)
40//! let x: Var = 0;
41//!
42//! // Create polynomial representing just x
43//! let p = Polynomial::from_var(x);
44//!
45//! // Compute x * x = x^2
46//! let p_squared = p.clone() * p.clone();
47//! ```
48//!
49//! ## BDD Operations
50//!
51//! ```
52//! use oxiz_math::bdd::BddManager;
53//!
54//! let mut mgr = BddManager::new();
55//!
56//! // Create variables (VarId is u32)
57//! let x = mgr.variable(0);
58//! let y = mgr.variable(1);
59//!
60//! // Compute x AND y
61//! let and_xy = mgr.and(x, y);
62//!
63//! // Compute x OR y
64//! let or_xy = mgr.or(x, y);
65//! ```
66//!
67//! ## BLAS Operations
68//!
69//! ```
70//! use oxiz_math::blas::{ddot, dgemv, Transpose};
71//!
72//! // Vector dot product
73//! let x = vec![1.0, 2.0, 3.0];
74//! let y = vec![4.0, 5.0, 6.0];
75//! let dot = ddot(&x, &y);
76//! assert_eq!(dot, 32.0);
77//! ```
78//!
79//! ## Arbitrary Precision Floats
80//!
81//! ```
82//! use oxiz_math::mpfr::{ArbitraryFloat, Precision, RoundingMode};
83//!
84//! let prec = Precision::new(128);
85//! let a = ArbitraryFloat::from_f64(3.14159, prec);
86//! let b = ArbitraryFloat::from_f64(2.71828, prec);
87//! let sum = a.add(&b, RoundingMode::RoundNearest);
88//! ```
89
90#![cfg_attr(not(feature = "std"), no_std)]
91#![warn(missing_docs)]
92
93#[cfg(not(feature = "std"))]
94extern crate alloc;
95
96mod prelude;
97
98pub mod algebraic;
99pub mod bdd;
100#[cfg(feature = "std")]
101pub mod blas;
102#[cfg(feature = "std")]
103pub mod blas_ops;
104pub mod delta_rational;
105pub mod fast_rational;
106pub mod grobner;
107pub mod hilbert;
108pub mod interior_point;
109pub mod interval;
110pub mod lp;
111pub mod lp_core;
112pub mod matrix;
113#[cfg(feature = "std")]
114pub mod mpfr;
115pub mod polynomial;
116pub mod rational;
117pub mod rational_function;
118pub mod realclosure;
119pub mod realclosure_advanced;
120#[cfg(feature = "std")]
121pub mod simd;
122pub mod simplex;
123pub mod simplex_parametric;
124pub mod simplex_solver;
125
126pub use simplex_solver::{
127 Constraint as SimplexConstraint, ConstraintKind, SimplexError, SimplexSolver, SolveResult,
128 SolveStatus,
129};
130
131#[cfg(test)]
132mod integration_tests {
133 use super::*;
134 use num_bigint::BigInt;
135 use num_rational::BigRational;
136
137 fn rat(n: i64) -> BigRational {
138 BigRational::from_integer(BigInt::from(n))
139 }
140
141 #[test]
142 fn test_grobner_with_root_isolation() {
143 // Integration test: Use Gröbner basis to simplify, then isolate roots
144 // System: x^2 - 2 = 0, y - x = 0
145 // Should reduce to y^2 - 2 = 0
146
147 let x_squared_minus_2 = polynomial::Polynomial::from_coeffs_int(&[
148 (1, &[(0, 2)]), // x^2
149 (-2, &[]), // -2
150 ]);
151
152 let y_minus_x = polynomial::Polynomial::from_coeffs_int(&[
153 (1, &[(1, 1)]), // y
154 (-1, &[(0, 1)]), // -x
155 ]);
156
157 let gb = grobner::grobner_basis(&[x_squared_minus_2.clone(), y_minus_x]);
158
159 // The Gröbner basis should contain polynomials
160 assert!(!gb.is_empty());
161
162 // One of the polynomials should be univariate
163 let has_univariate = gb.iter().any(|p| p.is_univariate());
164 assert!(has_univariate || gb.len() == 1);
165 }
166
167 #[test]
168 fn test_nra_solver_with_algebraic_numbers() {
169 // Integration test: NRA solver with algebraic number evaluation
170 // Solve x^2 - 2 = 0
171
172 let mut solver = grobner::NraSolver::new();
173
174 let x_squared_minus_2 = polynomial::Polynomial::from_coeffs_int(&[
175 (1, &[(0, 2)]), // x^2
176 (-2, &[]), // -2
177 ]);
178
179 solver.add_equality(x_squared_minus_2.clone());
180
181 // Should be satisfiable
182 assert_eq!(solver.check_sat(), grobner::SatResult::Sat);
183
184 // Create algebraic number for sqrt(2)
185 // AlgebraicNumber::new(poly, var, lower, upper)
186 let sqrt_2 = realclosure::AlgebraicNumber::new(
187 x_squared_minus_2,
188 0, // variable 0
189 rat(1),
190 rat(2),
191 );
192
193 // Algebraic number should be valid
194 let _ = sqrt_2;
195 }
196
197 #[test]
198 fn test_interval_with_polynomial_bounds() {
199 // Integration test: Use interval arithmetic with polynomial evaluation
200 // Evaluate x^2 over [1, 2] should give [1, 4]
201
202 let x_squared = polynomial::Polynomial::from_coeffs_int(&[(1, &[(0, 2)])]);
203
204 // Evaluate at x = 1
205 let mut assignment1 = crate::prelude::FxHashMap::default();
206 assignment1.insert(0, rat(1));
207 let val1 = x_squared.eval(&assignment1);
208 assert_eq!(val1, rat(1));
209
210 // Evaluate at x = 2
211 let mut assignment2 = crate::prelude::FxHashMap::default();
212 assignment2.insert(0, rat(2));
213 let val2 = x_squared.eval(&assignment2);
214 assert_eq!(val2, rat(4));
215
216 // Create interval [1, 4]
217 let interval = interval::Interval::closed(rat(1), rat(4));
218 assert!(interval.contains(&val1));
219 assert!(interval.contains(&val2));
220 }
221
222 #[test]
223 fn test_delta_rationals_ordering() {
224 // Integration test: Delta rationals for strict inequalities
225 let delta_zero = delta_rational::DeltaRational::from_rational(rat(0));
226 let delta_small = delta_rational::DeltaRational::new(rat(0), 1); // delta_coeff is i64
227
228 // 0 + delta > 0
229 assert!(delta_small > delta_zero);
230
231 // Delta rationals maintain ordering
232 let delta_one = delta_rational::DeltaRational::from_rational(rat(1));
233 assert!(delta_one > delta_small);
234 }
235
236 #[test]
237 fn test_matrix_operations() {
238 // Integration test: Matrix operations (used in F4 algorithm)
239 use matrix::Matrix;
240 use num_rational::Rational64;
241
242 // Create a simple 2x2 matrix
243 let m = Matrix::from_vec(
244 2,
245 2,
246 vec![
247 Rational64::new(2, 1),
248 Rational64::new(1, 1),
249 Rational64::new(1, 1),
250 Rational64::new(1, 1),
251 ],
252 );
253
254 // Check matrix values
255 assert_eq!(m.get(0, 0), Rational64::new(2, 1));
256 assert_eq!(m.get(0, 1), Rational64::new(1, 1));
257 }
258
259 #[test]
260 fn test_polynomial_factorization_with_grobner() {
261 // Integration test: Factorization helps with Gröbner basis computation
262 // x^2 - y^2 can be analyzed via Gröbner basis
263
264 let x_sq_minus_y_sq = polynomial::Polynomial::from_coeffs_int(&[
265 (1, &[(0, 2)]), // x^2
266 (-1, &[(1, 2)]), // -y^2
267 ]);
268
269 // Compute Gröbner basis of {x^2 - y^2}
270 let gb = grobner::grobner_basis(&[x_sq_minus_y_sq]);
271
272 assert!(!gb.is_empty());
273 }
274
275 #[test]
276 fn test_real_closure_root_isolation_integration() {
277 // Integration test: Real closure and root isolation
278 // Find roots of x^3 - 2 = 0
279
280 let poly = polynomial::Polynomial::from_coeffs_int(&[
281 (1, &[(0, 3)]), // x^3
282 (-2, &[]), // -2
283 ]);
284
285 // Isolate roots (for variable 0)
286 let roots = poly.isolate_roots(0);
287
288 // Should find at least one real root (cube root of 2)
289 assert!(!roots.is_empty());
290 }
291
292 #[test]
293 fn test_polynomial_gcd_univariate() {
294 // Integration test: GCD computation for univariate polynomials
295 // gcd(x^2 - 1, x - 1) = x - 1
296
297 let p1 = polynomial::Polynomial::from_coeffs_int(&[
298 (1, &[(0, 2)]), // x^2
299 (-1, &[]), // -1
300 ]);
301
302 let p2 = polynomial::Polynomial::from_coeffs_int(&[
303 (1, &[(0, 1)]), // x
304 (-1, &[]), // -1
305 ]);
306
307 let gcd = p1.gcd_univariate(&p2);
308
309 // GCD should be x - 1 (or a scalar multiple)
310 assert_eq!(gcd.total_degree(), 1);
311 }
312}