residual update

Author: sivasathyaseeelan

src/simple_regular_solve.jl

@@ -56,7 +56,7 @@ struct SimpleImplicitTauLeaping <: DiffEqBase.DEAlgorithm
     critical_threshold::Float64
 end
 
-SimpleImplicitTauLeaping(; epsilon=0.05, L=10.0) = SimpleImplicitTauLeaping(epsilon, L)
+SimpleImplicitTauLeaping(; epsilon=0.05, critical_threshold=10.0) = SimpleImplicitTauLeaping(epsilon, critical_threshold)
 
 function compute_hor(nu)
     hor = zeros(Int64, size(nu, 2))
@@ -116,9 +116,10 @@ function implicit_tau_step(u_prev, t_prev, tau, rate_cache, counts, nu, p, rate,
     function f(u_new, p)
         rate_new = zeros(eltype(u_new), numjumps)
         rate(rate_new, u_new, p, t_prev + tau)
-        residual = u_new - u_prev
+        residual = zeros(eltype(u_new), length(u_new))
+        residual .= u_new - u_prev
         for j in 1:numjumps
-            residual -= nu[:, j] * (counts[j] - tau * (rate_cache[j] - rate_new[j]))
+            residual .-= nu[:, j] * (counts[j] - tau * (rate_cache[j] - rate_new[j]))
         end
         return residual
     end

test/regular_jumps.jl

@@ -1,5 +1,5 @@
 using JumpProcesses, DiffEqBase
-using Test, LinearAlgebra, Statistics
+using Test, LinearAlgebra
 using StableRNGs
 rng = StableRNG(12345)
 
@@ -32,4 +32,4 @@ prob_disc = DiscreteProblem(u0, tspan, p)
 rj = RegularJump(regular_rate, regular_c, 3)
 jump_prob_tau = JumpProblem(prob_disc, Direct(), rj; rng=StableRNG(12345))
 
-sol_implicit = solve(EnsembleProblem(jump_prob_tau), SimpleImplicitTauLeaping(), EnsembleSerial(); trajectories=Nsims, saveat=1.0)
+sol = solve(EnsembleProblem(jump_prob_tau), SimpleImplicitTauLeaping(), EnsembleSerial(); trajectories=Nsims, saveat=1.0)