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lubgr / tsym

Tiny symbolic library
GNU General Public License v3.0
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computer-algebra cpp library

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tsym: Tiny Symbolic Library Coverage Status

This library is currently not maintained or otherwise being worked on.

This small C++ library intends to provide a simple approach to symbolic algebra. In contrast to fully-fledged computer algebra systems or libraries (e.g. maxima, GiNaC, sympy), only basic features are implemented and the scope is limited to real-valued symbols: no complex numbers are taken into account during expression simplification (this prohibits some simplifications and allows for some). The main features are:

Most algorithms are implemented according to Cohen, Computer Algebra and Symbolic Computation [2003], modifications are made for the handling of numeric power expressions and when not taking complex numbers into account. Absent features often implemented in other CAS are e.g. arbitrary precision arithmetics for floating point numbers, collecting parts of an expression or series expansion.

Note that this library is under development and far from being stable. Breaking changes are to be expected.

Setup

To compile tsym, you need a compiler supporting C++17, cmake and the boost headers (build dependency only, version >= 1.65). The easiest way to integrate tsym into a project is to leverage cmake in conjunction with git submdodules:

cd path/to/your/project
git submodule add https://github.com/lubgr/tsym external/tsym

In the CMakeLists.txt of your application, add

add_subdirectory(external/tsym)

target_link_libraries(yourTarget PRIVATE tsym::tsym)

and on Linux or MacOS, you should now be able to compile via the usual

mkdir build && cd build
cmake .. # pass e.g. -D BOOST_ROOT=/non/standard/path
make

The configuration step can be tweaked with common cmake options (CMAKE_BUILD_TYPE, BUILD_SHARED_LIBS, BOOST_ROOT, CMAKE_INSTALL_PREFIX etc.). An alternative is a system-wide installation (git clone, cmake -D [OPTIONS] [path/to/tsym], make install). In case of Archlinux, there is also an AUR package. When using cmake for the client application, use find_package(tsym) instead of add_subdirectory, otherwise pass e.g. -std=c++17, -ltsym and -I/-L to your compiler where appropriate. For compiling unit tests, configure the tsym build with BUILD_TESTING=ON. The test executable links to the boost test framework, and the appropriate static library must be available.

Usage

There is only one header that needs to be included: tsym/tsym.h (don't worry about compile times, the library is indeed tiny). The library provides a tsym::Var class holding all expressions. It can be instantiated as a symbol or a number, and arithmetic as well as stream operators are overloaded:

#include <iostream>
#include "tsym/tsym.h"

int main(int argc, char **argv)
{
    tsym::Var a("a");
    tsym::Var b("b_{subscript}");
    tsym::Var fraction(2, 3);

    std::cout << a + b*fraction << "\n";
}

Variable names and subscripts must be ASCII characters or numbers. A variable name can't start with a number, curly braces around the subscript can be omitted when it's only one character. Big integers can be constructed by a digit-only string, and implicit constructors are available for int and double arguments, such that intuitive calculations are possible:

tsym::Var largeInt("98938498203948203948203948209384029384092834098");
tsym::Var a("a");
tsym::Var b; /* Initialized to zero by default constructor. */

b = 2*a + a/1.2345 - largeInt;

std::cout << b << "\n";

/* Careful - this will be zero, because 2/3 is evaluated first and as plain integral type: */
b = 2/3*a;

Functions for square root, power, logarithm and (inverse) trigonometric maps including atan2 as well as Euler and Pi constants are available inside of the tsym namespace:

tsym::Var minusPiFourth = tsym::pi()/4 - tsym::asin(1);
tsym::Var onePlusPiFourth = tsym::log(tsym::euler()) + tsym::acos(1/tsym::sqrt(2));
tsym::Var eToTheFour = tsym::pow(tsym::euler(), 4);

Information about expressions can be queried via free functions accepting a Var instance or member functions:

tsym::Var b("b");
tsym::Var c = 2*tsym::Var("a")/b/5;

if (tsym::has(c, b) && c.type() == tsym::Var::Type::PRODUCT)
    std::cout << "c contains " << b << " and is a " << c.type() << "\n";

std::cout << tsym::numerator(c) << ", " << tsym::denominator(c) << "\n"; /* 2*a, 5*b */

tsym::collectSymbols(c); /* Returns a vector containing the symbols a and b. */
tsym::operands(c); /* Returns a vector with a, b^(-1) and the fraction 2/5. */

The type() method used in this snippet returns a enum class inside of Var with possible values PRODUCT, SYMBOL, INT, FRACTION, DOUBLE, CONSTANT, UNDEFINED, FUNCTION, SUM and POWER. Simplification, expansion and differentiation can be done as follows (all Var parameters are const, thus don't modify the object).

tsym::Var a = tsym::Var("a");
tsym::Var b = tsym::Var("b");
tsym::Var c = a/b + 1/(5*b);

std::cout << tsym::subst(c, b, tsym::Var(1, 3)) << "\n"; /* 3/5 + 3a */
std::cout << tsym::diff(c, b) << "\n"; /* (-1/5)/b^2 - a/b^2 */

c = c*b;

std::cout << tsym::expand(c) << "\n"; /* 1/5 + a */

The construction of expressions can be done by parsing of strings, too, by invocation of a free function

const std::optional<tsym::Var> parsedFromString = tsym::parse("a*cos(pi/5) + sqrt(3)*log(euler)");

This can go wrong, hence the return value.

const auto parseAttempt = tsym::parse("a*cos(3!)");

if (!parseAttempt)
    std::cout << "Factorials aren't implemented\n";

The parser does very limited error recovery, and partially parsed result are simply discarded. Three standard operations for matrices are provided as free functions: solution of linear systems of equations, matrix inversion and computing determinants. All three use an LU decomposition and a partial pivoting scheme. They are wrapped by helper templates that accept arbitrary vector and matrix types, which support element access via an overloaded call operator (matrix(i, j) and vector(i)) or an array subscript operator (matrix[i][j] and vector[i]). It's fine to use simple container types (std::vector<tsym::Var>, std::vector<std::vector<tsym::Var>, plain C-style arrays, std::array and so on. More sophisticated matrix/vector types don't help the performance that is solely governed by internal algebraic simplifications.

std::vector<std::vector<tsym::Var>> A;
boost::numeric::ublas::matrix<tsym::Var> B;

/* ... fill matrices with values ... */

tsym::determinant(A, A.size());
tsym::invert(B, B.size1());

The dimension (second parameter in the example above) should be passed as the container index type. Instantiating the function with a different type might result in many unwanted sign conversions warnings. When using a type that doesn't support the access operators mentioned above, wrap it into a forwarding lambda.

std::array<tsym::Var, 16> C; /* A 4x4 matrix with elements stored contingously. */
std::unique_ptr<tsym::Var[]> rhs(new tsym::Var[4]);
std::unique_ptr<tsym::Var[]> x(new tsym::Var[4]);

/* ... fill matrix and and right hand side with values ... */

auto wrappedC = [&C](auto i, auto j) -> tsym::Var& { return C[4u*i + j]; };

tsym::solve(wrappedC, rhs, x, std::size_t{4});

/* A and rhs are untouched, x contains the solution. */

When the given coefficient matrix is singular, all functions will throw an instance of std::invalid_argument. To keep the requirements on vector/matrix types low, no sanity checks are made (client code is hence responsible for correct dimensions, violating these preconditions leads to undefined behavior). Further note that solve and determinant don't mutate the input matrix and (if applicable) the right hand side vector (this differs from most LU decomposition approaches for numerical types), and an additional, one-dimensional skip field sequence can be passed to solve, determinant and invert as the last but one argument (before the dimension parameter) for indicating subproblems to be solved. The skip field is handled identically to matrix/vector arguments, and rows/columns for which the skip field element evaluates to true are ignored by the procedures.

Additional notes