# Expression Manipulation

Symbolics.jl provides functionality for easily manipulating expressions. Most of the functionality comes by the expression objects obeying the standard mathematical semantics. For example, if one has A a matrix of symbolic expressions wrapped in Num, then A^2 calculates the expressions for the squared matrix. In that sense, it is encouraged that one uses standard Julia for performing a lot of the manipulation on the IR, as, for example, calculating the sparse form of the matrix via sparse(A) is valid, legible, and easily understandable to all Julia programmers.

## Functionality Inherited From SymbolicUtils.jl

SymbolicUtils.substituteFunction
substitute(expr, s::Dict)

Performs the substitution on expr according to rule(s) s.

Examples

julia> @parameters t
(t,)
julia> @variables x y z(t)
(x, y, z(t))
julia> ex = x + y + sin(z)
(x + y) + sin(z(t))
julia> substitute(ex, Dict([x => z, sin(z) => z^2]))
(z(t) + y) + (z(t) ^ 2)
source
substitute(expr, dict)

substitute any subexpression that matches a key in dict with the corresponding value.

SymbolicUtils.simplifyFunction
simplify(x; expand=false,
rewriter=nothing)

Simplify an expression (x) by applying rewriter until there are no changes. expand=true applies expand in the beginning of each fixpoint iteration.

Other additional manipulation functions are given below.

Symbolics.get_variablesFunction
get_variables(O) -> Vector{Union{Sym, Term}}

Returns the variables in the expression. Note that the returned variables are not wrapped in the Num type.

Examples

julia> @parameters t
(t,)

julia> @variables x y z(t)
(x, y, z(t))

julia> ex = x + y + sin(z)
(x + y) + sin(z(t))

julia> Symbolics.get_variables(ex)
3-element Vector{Any}:
x
y
z(t)
source
Symbolics.tosymbolFunction
tosymbol(x::Union{Num,Symbolic}; states=nothing, escape=true) -> Symbol

Convert x to a symbol. states are the states of a system, and escape means if the target has escapes like val"y(t)". If escape then it will only output y instead of y(t).

Examples

julia> @parameters t; @variables z(t)
(z(t),)

julia> Symbolics.tosymbol(z)
Symbol("z(t)")
source
Symbolics.makesymFunction
makesym(x::Union{Num,Symbolic}, kwargs...) -> Sym

makesym takes the same arguments as tosymbol, but it converts a Term in the form of x(t) to a Sym in the form of x⦗t⦘.

Examples

julia> @parameters t; @variables x(t)
(x(t),)

julia> Symbolics.makesym(x)
x⦗t⦘
source
Symbolics.diff2termFunction
diff2term(x::Term) -> Symbolic
diff2term(x) -> x

Convert a differential variable to a Term. Note that it only takes a Term not a Num.

julia> @variables x t u(x, t); Dt = Differential(t); Dx = Differential(x);

julia> Symbolics.diff2term(Symbolics.value(Dx(Dt(u))))
uˍtx(x, t)
source
Symbolics.solve_forFunction
solve_for(eq::Any, var::Any; simplify, check) -> Any


Solve equation(s) eqs for a set of variables vars.

Assumes length(eqs) == length(vars)

Currently only works if all equations are linear. check if the expr is linear w.r.t vars.

source