Merge pull request #51 from JuliaDiffEq/minor_basis_fix

Minor basis fix

src/basis.jl

@@ -32,21 +32,21 @@ function Basis(basis::AbstractVector{Operation}, variables::AbstractVector{Opera
     bs = unique(basis)
     fix_single_vars_in_basis!(bs, variables)
 
-    vs = sort!([b for b in [ModelingToolkit.vars(bs)...] if !b.known], by = x -> x.name)
-    ps = sort!([b for b in [ModelingToolkit.vars(bs)...] if b.known], by = x -> x.name )
+    vs = [ModelingToolkit.Variable(Symbol(i)) for i in variables]
+    ps = [ModelingToolkit.Variable(Symbol(i)) for i in parameters]
 
     f_ = ModelingToolkit.build_function(bs, vs, ps, (), simplified_expr, Val{false})[1]
     return Basis(bs, variables, parameters, f_)
 end
 
-function update!(b::Basis)
-    vs = sort!([bi for bi in [ModelingToolkit.vars(b.basis)...] if !bi.known], by = x->x.name)
-    ps = sort!([bi for bi in [ModelingToolkit.vars(b.basis)...] if bi.known], by = x->x.name)
+function update!(basis::Basis)
+    vs = [ModelingToolkit.Variable(Symbol(i)) for i in variables(basis)]
+    ps = [ModelingToolkit.Variable(Symbol(i)) for i in parameters(basis)]
 
-    b.f_ = ModelingToolkit.build_function(b.basis, vs, ps, (), simplified_expr, Val{false})[1]
+    basis.f_ = ModelingToolkit.build_function(basis.basis, vs, ps, (), simplified_expr, Val{false})[1]
     return
 end
-                               
+
 function Base.push!(b::Basis, ops::AbstractArray{Operation})
     @inbounds for o in ops
         push!(b.basis, o)
@@ -139,10 +139,12 @@ Base.length(b::Basis) = length(b.basis)
 ModelingToolkit.parameters(b::Basis) = b.parameter
 variables(b::Basis) = b.variables
 
-function jacobian(b::Basis)
-    vs = sort!([bi for bi in [ModelingToolkit.vars(b.basis)...] if !bi.known], by = x-> x.name)
-    ps = sort!([bi for bi in [ModelingToolkit.vars(b.basis)...] if bi.known], by = x-> x.name)
-    j = calculate_jacobian(b.basis, variables(b))
+function jacobian(basis::Basis)
+
+    vs = [ModelingToolkit.Variable(Symbol(i)) for i in variables(basis)]
+    ps = [ModelingToolkit.Variable(Symbol(i)) for i in parameters(basis)]
+
+    j = calculate_jacobian(basis.basis, variables(basis))
     return ModelingToolkit.build_function(expand_derivatives.(j), vs, ps, (), simplified_expr, Val{false})[1]
 end
 

test/runtests.jl

@@ -37,6 +37,10 @@ using Test
     unique!(basis)
     @test size(basis) == size(h)
 
+    @variables a
+    g = [u[1]; u[3]; a]
+    basis = Basis(g, [u; a])
+    @test basis([1; 2; 3; 4]) == [1; 3; 4]
     g = [1.0*u[1]; 1.0*u[3]; 1.0*u[2]]
     basis = Basis(g, u, parameters = [])
     X = ones(Float64, 3, 10)
@@ -230,7 +234,7 @@ end
     X = sol[:, :] + 1e-3*randn(size(sol[:,:])...)
     set_threshold!(opt, 3.5e-1)
     Ψ = SInDy(X, DX, basis, maxiter = 10000, opt = opt, denoise = true, normalize = true)
-    
+
     estimator = ODEProblem(dynamics(Ψ), u0, tspan, [])
     sol_4 = solve(estimator,Tsit5(), saveat = dt)
     @test norm(sol[:,:] - sol_4[:,:], 2) < 5e-1