remove extra return by formatter

README.md

@@ -56,7 +56,7 @@ ps = [1e-4, 1e-2]
 # Model: non-Markovian part (delay reactions)
 τ = 20.0
 delay_trigger_affect! = function (integrator, rng)
-    return append!(integrator.de_chan[1], τ) # add a delay time τ to the first delay channel
+    append!(integrator.de_chan[1], τ) # add a delay time τ to the first delay channel
 end
 delay_trigger = Dict(1 => delay_trigger_affect!) # the first reaction S+I -> E+I will trigger a delay reaction: E --> I after τ time.  
 delay_complete = Dict(1 => [2 => 1, 3 => -1]) # E --> I after τ time: transfer from E (minus 1) to I (plus 1) after the completed delay reaction
@@ -111,7 +111,7 @@ ps = [0.0282, 3.46]
 delay_trigger_affect! = []
 for i in 1:burst_sup
     push!(delay_trigger_affect!, function (integrator, rng)
-        return append!(integrator.de_chan[1], fill(τ, i))
+        append!(integrator.de_chan[1], fill(τ, i))
     end)
 end
 delay_trigger = Dict([Pair(i, delay_trigger_affect![i]) for i in 1:burst_sup])

docs/src/tutorials/bursty.md

@@ -44,7 +44,7 @@ Next, we define the non-Markovian part. Here we mainly need to consider the dela
 delay_trigger_affect! = []
 for n in 1:burst_sup
     push!(delay_trigger_affect!, function (integrator, rng)
-        return append!(integrator.de_chan[1], fill(τ, n))
+        append!(integrator.de_chan[1], fill(τ, n))
     end)
 end
 delay_trigger = Dict([Pair(i, delay_trigger_affect![i]) for i in 1:burst_sup])

docs/src/tutorials/delay_degradation.md

@@ -58,7 +58,7 @@ Then we turn to the definition of delay reactions
 ```julia
 τ = 15.0
 delay_trigger_affect! = function (integrator, rng)
-    return append!(integrator.de_chan[1], τ)
+    append!(integrator.de_chan[1], τ)
 end
 delay_trigger = Dict(3 => delay_trigger_affect!)
 delay_complete = Dict(1 => [2 => -1])
@@ -177,7 +177,7 @@ dprob = DiscreteProblem(u0, tspan, p)
 τ = 15.0
 delay_trigger_affect! = function (integrator, rng)
     append!(integrator.de_chan[1], τ)
-    return append!(integrator.de_chan[2], τ)
+    append!(integrator.de_chan[2], τ)
 end
 delay_trigger = Dict(3 => delay_trigger_affect!)
 delay_complete = Dict(1 => [2 => -1], 2 => [3 => -1])

docs/src/tutorials/stochastic_delay.md

@@ -43,7 +43,7 @@ Unlike other examples, the elongation time $\tau$ is a random variable sampled f
 ```julia
 delay_trigger_affect! = function (integrator, rng)
     τ = rand(LogNormal(1, sqrt(2))) + 120
-    return append!(integrator.de_chan[1], τ)
+    append!(integrator.de_chan[1], τ)
 end
 delay_trigger = Dict(3 => delay_trigger_affect!)
 delay_complete = Dict(1 => [3 => -1])

examples/bursty.jl

@@ -1,6 +1,6 @@
 ## This example shows an application of `DelaySSA.jl` for a bursty model with delay
 
-## A Bursty model with delay is described as 
+## A Bursty model with delay is described as
 # ab^n/(1+b)^(n+1): 0 -> n P, which triggers n P to degrade after delay time τ
 
 using DelaySSAToolkit
@@ -30,7 +30,7 @@ dprob = DiscreteProblem(jumpsys, u0, tspan, ps)
 delay_trigger_affect! = []
 for i in 1:burst_sup
     push!(delay_trigger_affect!, function (integrator, rng)
-        return append!(integrator.de_chan[1], fill(τ, i))
+        append!(integrator.de_chan[1], fill(τ, i))
     end)
 end
 delay_trigger_affect!

examples/delay_degradation.jl

@@ -37,7 +37,7 @@ dprob = DiscreteProblem(u0, tspan, p)
 
 τ = 15.0
 delay_trigger_affect! = function (integrator, rng)
-    return append!(integrator.de_chan[1], τ)
+    append!(integrator.de_chan[1], τ)
 end
 delay_trigger = Dict(3 => delay_trigger_affect!)
 delay_complete = Dict(1 => [2 => -1])

examples/delay_oscillator.jl

@@ -3,7 +3,7 @@ using Catalyst
 # using Plots
 ################################################################################
 # the following example illustrates how to deal with a oscillatory system
-# d: X-> 0; k1/(1+Y^2): 0-> X; [trigger X-> Y after τ time;] k2*Y/(1+Y):  Y-> 0;  
+# d: X-> 0; k1/(1+Y^2): 0-> X; [trigger X-> Y after τ time;] k2*Y/(1+Y):  Y-> 0;
 
 rn = @reaction_network begin
     1 / (1 + Y^2), 0 --> X
@@ -21,7 +21,7 @@ dprob = DiscreteProblem(jumpsys, u0, tspan)
 # jumpsys.dep_graph
 
 delay_trigger_affect! = function (integrator, rng)
-    return append!(integrator.de_chan[1], τ)
+    append!(integrator.de_chan[1], τ)
 end
 delay_trigger = Dict(1 => delay_trigger_affect!)
 delay_complete = Dict(1 => [2 => 1, 1 => -1])

examples/seir.jl

@@ -17,7 +17,7 @@ ps = [1e-4, 1e-2]
 τ = 20.0
 dprob = DiscreteProblem(jumpsys, u0, tspan, ps)
 delay_trigger_affect! = function (integrator, rng)
-    return append!(integrator.de_chan[1], τ)
+    append!(integrator.de_chan[1], τ)
 end
 delay_trigger = Dict(1 => delay_trigger_affect!)
 # delay_trigger = Dict(1=>[1=>τ])

examples/stochastic_delay.jl

@@ -17,7 +17,7 @@ dprob = DiscreteProblem(u0, tspan, p)
 
 delay_trigger_affect! = function (integrator, rng)
     τ = rand(LogNormal(1, sqrt(2))) + 120
-    return append!(integrator.de_chan[1], τ)
+    append!(integrator.de_chan[1], τ)
 end
 delay_trigger = Dict(3 => delay_trigger_affect!)
 delay_complete = Dict(1 => [3 => -1])
@@ -49,7 +49,7 @@ histogram(
 
 delay_trigger_affect2! = function (integrator, rng)
     τ = rand(LogNormal(0, 2)) + 120
-    return append!(integrator.de_chan[1], τ)
+    append!(integrator.de_chan[1], τ)
 end
 delay_trigger2 = Dict(3 => delay_trigger_affect2!)
 delayjumpset2 = DelayJumpSet(delay_trigger2, delay_complete, delay_interrupt)

test/cascade_of_delay_reaction.jl

@@ -8,7 +8,7 @@ end
 delay_trigger_affect! = []
 chain_len = 10
 delay_trigger_affect! = function (integrator, rng)
-    return append!(integrator.de_chan[1], 1.0)
+    append!(integrator.de_chan[1], 1.0)
 end
 
 u0 = zeros(chain_len)
@@ -22,7 +22,7 @@ for i in 1:(chain_len - 1)
     push!(delay_complete_affect!, function (integrator, rng)
         integrator.u[i] -= 1 # A_prev minus 1
         integrator.u[i + 1] += 1 # A plus 1
-        return append!(integrator.de_chan[i + 1], 1.0) # add to the delay channel
+        append!(integrator.de_chan[i + 1], 1.0) # add to the delay channel
     end)
 end
 push!(delay_complete_affect!, function (integrator, rng)

test/delay_problem_test.jl

@@ -15,7 +15,7 @@ ps = [1e-4, 1e-2] # parameters for ρ, r
 dprob = DiscreteProblem(u0, tspan, ps)
 
 delay_trigger_affect! = function (integrator, rng)
-    return append!(integrator.de_chan[1], τ)
+    append!(integrator.de_chan[1], τ)
 end
 delay_trigger = Dict(1 => delay_trigger_affect!)
 delay_complete = Dict(1 => [2 => 1, 3 => -1])

test/dep_gr_delay.jl

@@ -15,7 +15,7 @@ tspan = (0, tf)
 dprob = DiscreteProblem(jumpsys, u0, tspan)
 
 delay_trigger_affect! = function (integrator, rng)
-    return append!(integrator.de_chan[1], τ)
+    append!(integrator.de_chan[1], τ)
 end
 delay_trigger = Dict(1 => delay_trigger_affect!)
 delay_complete = Dict(1 => [2 => 1], 2 => [1 => -1])

test/remake_test.jl

@@ -14,7 +14,7 @@ ps = [1e-4, 1e-2] # parameters for ρ, r
 dprob = DiscreteProblem(u0, tspan, ps)
 
 delay_trigger_affect! = function (integrator, rng)
-    return append!(integrator.de_chan[1], τ)
+    append!(integrator.de_chan[1], τ)
 end
 delay_trigger = Dict(1 => delay_trigger_affect!)
 delay_complete = Dict(1 => [2 => 1, 3 => -1])