""" This module implements a method to find Euler-Lagrange Equations for given Lagrangian. """ from itertools import combinations_with_replacement from sympy.core.function import (Derivative, Function, diff) from sympy.core.relational import Eq from sympy.core.singleton import S from sympy.core.symbol import Symbol from sympy.core.sympify import sympify from sympy.utilities.iterables import iterable def euler_equations(L, funcs=(), vars=()): r""" Find the Euler-Lagrange equations [1]_ for a given Lagrangian. Parameters ========== L : Expr The Lagrangian that should be a function of the functions listed in the second argument and their derivatives. For example, in the case of two functions $f(x,y)$, $g(x,y)$ and two independent variables $x$, $y$ the Lagrangian has the form: .. math:: L\left(f(x,y),g(x,y),\frac{\partial f(x,y)}{\partial x}, \frac{\partial f(x,y)}{\partial y}, \frac{\partial g(x,y)}{\partial x}, \frac{\partial g(x,y)}{\partial y},x,y\right) In many cases it is not necessary to provide anything, except the Lagrangian, it will be auto-detected (and an error raised if this cannot be done). funcs : Function or an iterable of Functions The functions that the Lagrangian depends on. The Euler equations are differential equations for each of these functions. vars : Symbol or an iterable of Symbols The Symbols that are the independent variables of the functions. Returns ======= eqns : list of Eq The list of differential equations, one for each function. Examples ======== >>> from sympy import euler_equations, Symbol, Function >>> x = Function('x') >>> t = Symbol('t') >>> L = (x(t).diff(t))**2/2 - x(t)**2/2 >>> euler_equations(L, x(t), t) [Eq(-x(t) - Derivative(x(t), (t, 2)), 0)] >>> u = Function('u') >>> x = Symbol('x') >>> L = (u(t, x).diff(t))**2/2 - (u(t, x).diff(x))**2/2 >>> euler_equations(L, u(t, x), [t, x]) [Eq(-Derivative(u(t, x), (t, 2)) + Derivative(u(t, x), (x, 2)), 0)] References ========== .. [1] https://en.wikipedia.org/wiki/Euler%E2%80%93Lagrange_equation """ funcs = tuple(funcs) if iterable(funcs) else (funcs,) if not funcs: funcs = tuple(L.atoms(Function)) else: for f in funcs: if not isinstance(f, Function): raise TypeError('Function expected, got: %s' % f) vars = tuple(vars) if iterable(vars) else (vars,) if not vars: vars = funcs[0].args else: vars = tuple(sympify(var) for var in vars) if not all(isinstance(v, Symbol) for v in vars): raise TypeError('Variables are not symbols, got %s' % vars) for f in funcs: if not vars == f.args: raise ValueError("Variables %s do not match args: %s" % (vars, f)) order = max([len(d.variables) for d in L.atoms(Derivative) if d.expr in funcs] + [0]) eqns = [] for f in funcs: eq = diff(L, f) for i in range(1, order + 1): for p in combinations_with_replacement(vars, i): eq = eq + S.NegativeOne**i*diff(L, diff(f, *p), *p) new_eq = Eq(eq, 0) if isinstance(new_eq, Eq): eqns.append(new_eq) return eqns