Stator is a header-only compile-time and runtime C++17 Computer Algebra System. Its designed to be fast, and uses metaprogramming to achieve much of this speed.
Aside from the math, it has some tools for application in event-driven dynamics/ray-tracing/collision-detection and is being extended towards thermodynamics applications.
For full details, see the Documentation: https://toastedcrumpets.github.io/stator
Example to come!
Stator has python bindings to allow "fast" math in python. Its built around the parser
import stator
# Use the built-in expression parser to make objects like variables
x = Expr("x")
# You can then create more complex expressions
f = x*x+2
# And print them
print(f) # x*x+2
# They're still Expr objects
print(repr(f)) # Expr('x*x+2')
# You can evaluate them by substitution
result = sub(f, {x:2})
# And the result becomes a python float
print(result) # 6.0
# We can parse more complex expressions, like lists
funcs = Expr('[1, x, x^2/2, x^3/6, sin(x), sin(y)]')
# And take derivatives
print(derivative(funcs, x)) # [0, 1, 4*x/4, 18*x^2/36, cos x, 0]
# You'll note simplification is not very advanced (yet)
# Substitution can use dictionaries to provide computation 'contexts'
print(sub(funcs, {x:1, Expr('y'): 2})) # [1.0, 1.0, 0.5, 0.16666666666666666, 0.8414709848078965, 0.9092974268256817]You need the Google test library to build the unit tests. The Boost interval library is needed for interval arithmetic support.
For the compile-time C++ library:
- ViennaMath: A nice compile-time math library, stator has most of this functionality except the extensions to FEM.
- SymbolicC++: A nice library, but behind in adopting modern compiler extensions (last released in 2010). Also you seem to need to buy the book to get the docs, but at least it has them!
For the python bindings:
- sympy: The full-featured CAS for python, but also quite slow.
- symengine: Just like stator. It's actually a C++ CAS engine with python wrappers.
For the interval arithmetic