fixed derivative

Author: Brad Carman

src/Blocks/sources.jl

@@ -525,14 +525,10 @@ Symbolics.@register_symbolic get_sample_time(memory)
 
 Symbolics.@register_symbolic get_sampled_data(t, memory)
 
-get_sampled_data_const(t, memory::Parameter) = get_sampled_data(t, memory)
-Symbolics.@register_symbolic get_sampled_data_const(t, memory)
-Symbolics.derivative(::typeof(get_sampled_data_const), args::NTuple{2, Any}, ::Val{1}) = 0
-
 function first_order_backwards_difference(t, memory)
     Δt = get_sample_time(memory)
     x1 = get_sampled_data(t, memory)
-    x0 = get_sampled_data_const(t - Δt, memory)
+    x0 = get_sampled_data(t - Δt, memory)
 
     return (x1 - x0) / Δt
 end
@@ -611,11 +607,11 @@ function Symbolics.derivative(::typeof(set_sampled_data!), args::NTuple{4, Any},
     Δt = @inbounds args[4]
     first_order_backwards_difference(t, x, Δt, memory)
 end
-Symbolics.derivative(::typeof(set_sampled_data!), args::NTuple{4, Any}, ::Val{3}) = 1
+Symbolics.derivative(::typeof(set_sampled_data!), args::NTuple{4, Any}, ::Val{3}) = 1 #set_sampled_data returns x, therefore d/dx (x) = 1
 
 function first_order_backwards_difference(t, x, Δt, memory)
     x1 = set_sampled_data!(memory, t, x, Δt)
-    x0 = get_sampled_data_const(t - Δt, memory)
+    x0 = get_sampled_data(t - Δt, memory)
 
     return (x1 - x0) / Δt
 end

test/Blocks/sources.jl

@@ -414,12 +414,13 @@ end
     time = 0:dt:t_end
     x = @. time^2 + 1.0
 
-    vars = @variables y(t)=1 dy(t)=0
+    vars = @variables y(t)=1 dy(t)=0 ddy(t)=0
 
     @named src = SampledData(Float64)
     @named int = Integrator()
     @named iosys = ODESystem([y ~ src.output.u
             D(y) ~ dy
+            D(dy) ~ ddy
             connect(src.output, int.input)],
         t,
         systems = [int, src])
@@ -436,4 +437,5 @@ end
     @test sol(time)[src.output.u]≈x atol=1e-3
     @test sol[int.output.u][end]≈1 / 3 * 10^3 + 10.0 atol=1e-3 # closed-form solution to integral
     @test sol[dy][end]≈2 * time[end] atol=1e-3
+    @test sol[ddy][end]≈2 atol=1e-3
 end