Merge pull request #1491 from ValentinKaisermayer/patch-@register

fixes deprecation from Symbolics

Author: ChrisRackauckas

docs/src/basics/FAQ.md

@@ -41,5 +41,5 @@ ERROR: TypeError: non-boolean (Num) used in boolean context
 
 then it's likely you are trying to trace through a function which cannot be
 directly represented in Julia symbols. The techniques to handle this problem,
-such as `@register`, are described in detail 
+such as `@register_symbolic`, are described in detail 
 [in the Symbolics.jl documentation](https://symbolics.juliasymbolics.org/dev/manual/faq/#Transforming-my-function-to-a-symbolic-equation-has-failed.-What-do-I-do?-1).

docs/src/basics/Validation.md

@@ -82,7 +82,7 @@ D = Differential(t)
 struct NewType
     f
 end
-@register dummycomplex(complex::Num, scalar)
+@register_symbolic dummycomplex(complex::Num, scalar)
 dummycomplex(complex, scalar) = complex.f - scalar
 
 c = NewType(1)

docs/src/tutorials/ode_modeling.md

@@ -165,7 +165,7 @@ of random values:
 ```julia
 value_vector = randn(10)
 f_fun(t) = t >= 10 ? value_vector[end] : value_vector[Int(floor(t))+1]
-@register f_fun(t)
+@register_symbolic f_fun(t)
 
 @named fol_external_f = ODESystem([f ~ f_fun(t), D(x) ~ (f - x)/τ])
 prob = ODEProblem(structural_simplify(fol_external_f), [x => 0.0], (0.0,10.0), [τ => 0.75])

test/direct.jl

@@ -17,7 +17,7 @@ canonequal(a, b) = isequal(simplify(a), simplify(b))
                  -sin(x) * cos(cos(x))
                 )
 
-@register no_der(x)
+@register_symbolic no_der(x)
 @test canonequal(
                  ModelingToolkit.derivative([sin(cos(x)), hypot(x, no_der(x))], x),
                  [
@@ -26,7 +26,7 @@ canonequal(a, b) = isequal(simplify(a), simplify(b))
                  ]
                 )
 
-@register intfun(x)::Int
+@register_symbolic intfun(x)::Int
 @test ModelingToolkit.symtype(intfun(x)) === Int
 
 eqs = [σ*(y-x),
@@ -196,7 +196,7 @@ test_worldage()
 @test_nowarn [x, y, z]'
 
 let
-    @register foo(x)
+    @register_symbolic foo(x)
     @variables t
     D = Differential(t)
 

test/discretesystem.jl

@@ -141,7 +141,7 @@ RHS2 = RHS
         end
 
     dummy_identity(x, _) = x
-    @register dummy_identity(x, y)
+    @register_symbolic dummy_identity(x, y)
 
     u0 = ones(5)
     p0 = Float64[]

test/function_registration.jl

@@ -15,7 +15,7 @@ module MyModule
     function do_something(a)
         a + 10
     end
-    @register do_something(a)
+    @register_symbolic do_something(a)
 
     eq  = Dt(u) ~ do_something(x) + MyModule.do_something(x)
     @named sys = ODESystem([eq], t, [u], [x])
@@ -38,7 +38,7 @@ module MyModule2
         function do_something_2(a)
             a + 20
         end
-        @register do_something_2(a)
+        @register_symbolic do_something_2(a)
 
         eq  = Dt(u) ~ do_something_2(x) + MyNestedModule.do_something_2(x)
         @named sys = ODESystem([eq], t, [u], [x])
@@ -60,7 +60,7 @@ Dt = Differential(t)
 function do_something_3(a)
     a + 30
 end
-@register do_something_3(a)
+@register_symbolic do_something_3(a)
 
 eq  = Dt(u) ~ do_something_3(x) + (@__MODULE__).do_something_3(x)
 @named sys = ODESystem([eq], t, [u], [x])
@@ -74,7 +74,7 @@ u0 = 7.0
 # ---------------------------------------------------
 foo(x, y) = sin(x) * cos(y)
 @parameters t; @variables x(t) y(t) z(t); D = Differential(t)
-@register foo(x, y)
+@register_symbolic foo(x, y)
 
 using ModelingToolkit: value, arguments, operation
 expr = value(foo(x, y))
@@ -95,7 +95,7 @@ ModelingToolkit.derivative(::typeof(foo), (x, y), ::Val{2}) = -sin(x) * sin(y) #
 function do_something_4(a)
     a + 30
 end
-@register do_something_4(a)
+@register_symbolic do_something_4(a)
 function build_ode()
     @parameters t x
     @variables u(t)
@@ -113,6 +113,6 @@ run_test()
 
 using ModelingToolkit: arguments
 @variables a
-@register foo(x,y,z)
+@register_symbolic foo(x,y,z)
 @test 1 * foo(a,a,a) * Num(1) isa Num
 @test !any(x->x isa Num, arguments(value(1 * foo(a,a,a) * Num(1))))

test/odesystem.jl

@@ -552,7 +552,7 @@ eqs[end] = D(D(z)) ~ α*x - β*y
     end
 
     dummy_identity(x, _) = x
-    @register dummy_identity(x, y)
+    @register_symbolic dummy_identity(x, y)
 
     u0 = ones(5)
     p0 = Float64[]