new format rules

README.md

@@ -60,18 +60,18 @@ V = 1.0
 @named ground = Ground()
 
 rc_eqs = [connect(constant.output, source.V)
-          connect(source.p, resistor.p)
-          connect(resistor.n, capacitor.p)
-          connect(capacitor.n, source.n, ground.g)]
+    connect(source.p, resistor.p)
+    connect(resistor.n, capacitor.p)
+    connect(capacitor.n, source.n, ground.g)]
 
 @named rc_model = ODESystem(rc_eqs, t,
-                            systems = [resistor, capacitor, constant, source, ground])
+    systems = [resistor, capacitor, constant, source, ground])
 sys = structural_simplify(rc_model)
 prob = ODEProblem(sys, Pair[], (0, 10.0))
 sol = solve(prob, Tsit5())
 plot(sol, idxs = [capacitor.v, resistor.i],
-     title = "RC Circuit Demonstration",
-     labels = ["Capacitor Voltage" "Resistor Current"])
+    title = "RC Circuit Demonstration",
+    labels = ["Capacitor Voltage" "Resistor Current"])
 savefig("plot.png")
 ```
 

docs/make.jl

@@ -18,29 +18,29 @@ ENV["GKSwstype"] = "100"
 include("pages.jl")
 
 makedocs(sitename = "ModelingToolkitStandardLibrary.jl",
-         authors = "Julia Computing",
-         clean = true,
-         doctest = false,
-         linkcheck = true,
-         strict = [
-             :linkcheck,
-             :doctest,
-             :example_block,
-         ],
-         modules = [ModelingToolkit,
-             ModelingToolkitStandardLibrary,
-             ModelingToolkitStandardLibrary.Blocks,
-             ModelingToolkitStandardLibrary.Mechanical,
-             ModelingToolkitStandardLibrary.Mechanical.Rotational,
-             ModelingToolkitStandardLibrary.Magnetic,
-             ModelingToolkitStandardLibrary.Magnetic.FluxTubes,
-             ModelingToolkitStandardLibrary.Electrical,
-             ModelingToolkitStandardLibrary.Thermal,
-             ModelingToolkitStandardLibrary.Hydraulic,
-             ModelingToolkitStandardLibrary.Hydraulic.IsothermalCompressible],
-         format = Documenter.HTML(assets = ["assets/favicon.ico"],
-                                  canonical = "https://docs.sciml.ai/ModelingToolkitStandardLibrary/stable/"),
-         pages = pages)
+    authors = "Julia Computing",
+    clean = true,
+    doctest = false,
+    linkcheck = true,
+    strict = [
+        :linkcheck,
+        :doctest,
+        :example_block,
+    ],
+    modules = [ModelingToolkit,
+        ModelingToolkitStandardLibrary,
+        ModelingToolkitStandardLibrary.Blocks,
+        ModelingToolkitStandardLibrary.Mechanical,
+        ModelingToolkitStandardLibrary.Mechanical.Rotational,
+        ModelingToolkitStandardLibrary.Magnetic,
+        ModelingToolkitStandardLibrary.Magnetic.FluxTubes,
+        ModelingToolkitStandardLibrary.Electrical,
+        ModelingToolkitStandardLibrary.Thermal,
+        ModelingToolkitStandardLibrary.Hydraulic,
+        ModelingToolkitStandardLibrary.Hydraulic.IsothermalCompressible],
+    format = Documenter.HTML(assets = ["assets/favicon.ico"],
+        canonical = "https://docs.sciml.ai/ModelingToolkitStandardLibrary/stable/"),
+    pages = pages)
 
 deploydocs(repo = "github.com/SciML/ModelingToolkitStandardLibrary.jl";
-           push_preview = true)
+    push_preview = true)

docs/src/API/linear_analysis.md

@@ -60,7 +60,7 @@ using ModelingToolkitStandardLibrary.Blocks, ModelingToolkit
 @named C = Gain(-1)             # A P controller
 t = ModelingToolkit.get_iv(P)
 eqs = [connect(P.output, :plant_output, C.input)  # Connect with an automatically created analysis point called :plant_output
-       connect(C.output, :plant_input, P.input)]
+    connect(C.output, :plant_input, P.input)]
 sys = ODESystem(eqs, t, systems = [P, C], name = :feedback_system)
 
 matrices_S = get_sensitivity(sys, :plant_input)[1] # Compute the matrices of a state-space representation of the (input)sensitivity function.
@@ -75,7 +75,7 @@ using ControlSystemsBase, Plots
 S = ss(matrices_S...)
 T = ss(matrices_T...)
 bodeplot([S, T], lab = ["S" "" "T" ""], plot_title = "Bode plot of sensitivity functions",
-         margin = 5Plots.mm)
+    margin = 5Plots.mm)
 ```
 
 The sensitivity functions obtained this way should be equivalent to the ones obtained with the code below

docs/src/connectors/connections.md

@@ -99,7 +99,7 @@ using Plots
 @named ground = Ground()
 
 eqs = [connect(capacitor.p, resistor.p)
-       connect(resistor.n, ground.g, capacitor.n)]
+    connect(resistor.n, ground.g, capacitor.n)]
 
 @named model = ODESystem(eqs, t; systems = [resistor, capacitor, ground])
 
@@ -139,7 +139,7 @@ const TV = ModelingToolkitStandardLibrary.Mechanical.Translational
 @named ground = TV.Fixed()
 
 eqs = [connect(damping.flange_a, body.flange)
-       connect(ground.flange, damping.flange_b)]
+    connect(ground.flange, damping.flange_b)]
 
 @named model = ODESystem(eqs, t; systems = [damping, body, ground])
 
@@ -172,7 +172,7 @@ const TP = ModelingToolkitStandardLibrary.Mechanical.TranslationalPosition
 @named ground = TP.Fixed(s_0 = 0)
 
 eqs = [connect(damping.flange_a, body.flange)
-       connect(ground.flange, damping.flange_b)]
+    connect(ground.flange, damping.flange_b)]
 
 @named model = ODESystem(eqs, t; systems = [damping, body, ground])
 
@@ -267,7 +267,7 @@ Let's define a quick function to simplify and solve the 2 different systems. Not
 ```@example connections
 function simplify_and_solve(damping, spring, body, ground)
     eqs = [connect(spring.flange_a, body.flange, damping.flange_a)
-           connect(spring.flange_b, damping.flange_b, ground.flange)]
+        connect(spring.flange_b, damping.flange_b, ground.flange)]
 
     @named model = ODESystem(eqs, t; systems = [ground, body, spring, damping])
 
@@ -345,7 +345,7 @@ Which means both systems are actually solving the same exact system.  We can plo
 
 ```@example connections
 plot(title = "numerical difference: vel. vs. pos. domain", xlabel = "time [s]",
-     ylabel = "solv[bv.v] .- solp[bp.v]")
+    ylabel = "solv[bv.v] .- solp[bp.v]")
 time = 0:0.1:10
 plot!(time, (solv(time)[bv.v] .- solp(time)[bp.v]), label = "")
 Plots.ylims!(-1e-15, 1e-15)

docs/src/tutorials/custom_component.md

@@ -43,10 +43,10 @@ function NonlinearResistor(; name, Ga, Gb, Ve)
     pars = @parameters Ga=Ga Gb=Gb Ve=Ve
     eqs = [
         i ~ ifelse(v < -Ve,
-                   Gb * (v + Ve) - Ga * Ve,
-                   ifelse(v > Ve,
-                          Gb * (v - Ve) + Ga * Ve,
-                          Ga * v)),
+            Gb * (v + Ve) - Ga * Ve,
+            ifelse(v > Ve,
+                Gb * (v - Ve) + Ga * Ve,
+                Ga * v)),
     ]
     extend(ODESystem(eqs, t, [], pars; name = name), oneport)
 end
@@ -97,19 +97,19 @@ The final model can now be created with the components from the library and the
 @named C1 = Capacitor(C = 10, v_start = 4)
 @named C2 = Capacitor(C = 100)
 @named Nr = NonlinearResistor(Ga = -0.757576,
-                              Gb = -0.409091,
-                              Ve = 1)
+    Gb = -0.409091,
+    Ve = 1)
 @named Gnd = Ground()
 
 connections = [connect(L.p, G.p)
-               connect(G.n, Nr.p)
-               connect(Nr.n, Gnd.g)
-               connect(C1.p, G.n)
-               connect(L.n, Ro.p)
-               connect(G.p, C2.p)
-               connect(C1.n, Gnd.g)
-               connect(C2.n, Gnd.g)
-               connect(Ro.n, Gnd.g)]
+    connect(G.n, Nr.p)
+    connect(Nr.n, Gnd.g)
+    connect(C1.p, G.n)
+    connect(L.n, Ro.p)
+    connect(G.p, C2.p)
+    connect(C1.n, Gnd.g)
+    connect(C2.n, Gnd.g)
+    connect(Ro.n, Gnd.g)]
 
 @named model = ODESystem(connections, t, systems = [L, Ro, G, C1, C2, Nr, Gnd])
 nothing # hide
@@ -127,12 +127,12 @@ prob = ODEProblem(sys, Pair[], (0, 5e4), saveat = 0.01)
 sol = solve(prob, Rodas4())
 
 Plots.plot(sol[C1.v], sol[C2.v], title = "Chaotic Attractor", label = "",
-           ylabel = "C1 Voltage in V", xlabel = "C2 Voltage in V")
+    ylabel = "C1 Voltage in V", xlabel = "C2 Voltage in V")
 Plots.savefig("chua_phase_plane.png")
 nothing # hide
 
 Plots.plot(sol; vars = [C1.v, C2.v, L.i],
-           labels = ["C1 Voltage in V" "C1 Voltage in V" "Inductor Current in A"])
+    labels = ["C1 Voltage in V" "C1 Voltage in V" "Inductor Current in A"])
 Plots.savefig("chua.png")
 nothing # hide
 ```

docs/src/tutorials/dc_motor_pi.md

@@ -50,36 +50,36 @@ The actual model can now be composed.
 @named speed_sensor = SpeedSensor()
 
 connections = [connect(fixed.flange, emf.support, friction.flange_b)
-               connect(emf.flange, friction.flange_a, inertia.flange_a)
-               connect(inertia.flange_b, load.flange)
-               connect(inertia.flange_b, speed_sensor.flange)
-               connect(load_step.output, load.tau)
-               connect(ref.output, feedback.input1)
-               connect(speed_sensor.w, :y, feedback.input2)
-               connect(feedback.output, pi_controller.err_input)
-               connect(pi_controller.ctr_output, :u, source.V)
-               connect(source.p, R1.p)
-               connect(R1.n, L1.p)
-               connect(L1.n, emf.p)
-               connect(emf.n, source.n, ground.g)]
+    connect(emf.flange, friction.flange_a, inertia.flange_a)
+    connect(inertia.flange_b, load.flange)
+    connect(inertia.flange_b, speed_sensor.flange)
+    connect(load_step.output, load.tau)
+    connect(ref.output, feedback.input1)
+    connect(speed_sensor.w, :y, feedback.input2)
+    connect(feedback.output, pi_controller.err_input)
+    connect(pi_controller.ctr_output, :u, source.V)
+    connect(source.p, R1.p)
+    connect(R1.n, L1.p)
+    connect(L1.n, emf.p)
+    connect(emf.n, source.n, ground.g)]
 
 @named model = ODESystem(connections, t,
-                         systems = [
-                             ground,
-                             ref,
-                             pi_controller,
-                             feedback,
-                             source,
-                             R1,
-                             L1,
-                             emf,
-                             fixed,
-                             load,
-                             load_step,
-                             inertia,
-                             friction,
-                             speed_sensor,
-                         ])
+    systems = [
+        ground,
+        ref,
+        pi_controller,
+        feedback,
+        source,
+        R1,
+        L1,
+        emf,
+        fixed,
+        load,
+        load_step,
+        inertia,
+        friction,
+        speed_sensor,
+    ])
 nothing # hide
 ```
 
@@ -93,7 +93,7 @@ prob = ODEProblem(sys, [], (0, 6.0))
 sol = solve(prob, Rodas4())
 
 p1 = Plots.plot(sol.t, sol[inertia.w], ylabel = "Angular Vel. in rad/s",
-                label = "Measurement", title = "DC Motor with Speed Controller")
+    label = "Measurement", title = "DC Motor with Speed Controller")
 Plots.plot!(sol.t, sol[ref.output.u], label = "Reference")
 p2 = Plots.plot(sol.t, sol[load.tau.u], ylabel = "Disturbance in Nm", label = "")
 Plots.plot(p1, p2, layout = (2, 1))
@@ -124,7 +124,7 @@ So = ss(matrices_S...) |> minreal # The output-sensitivity function as a StateSp
 matrices_T, simplified_sys = Blocks.get_comp_sensitivity(model, :y)
 To = ss(matrices_T...)# The output complementary sensitivity function as a StateSpace system
 bodeplot([So, To], label = ["S" "T"], plot_title = "Sensitivity functions",
-         plotphase = false)
+    plotphase = false)
 ```
 
 Similarly, we may compute the loop-transfer function and plot its Nyquist curve
@@ -134,5 +134,5 @@ matrices_L, simplified_sys = Blocks.get_looptransfer(model, :y)
 L = -ss(matrices_L...) # The loop-transfer function as a StateSpace system. The negative sign is to negate the built-in negative feedback
 Ms, ωMs = hinfnorm(So) # Compute the peak of the sensitivity function to draw a circle in the Nyquist plot
 nyquistplot(L, label = "\$L(s)\$", ylims = (-2.5, 0.5), xlims = (-1.2, 0.1),
-            Ms_circles = Ms)
+    Ms_circles = Ms)
 ```

docs/src/tutorials/input_component.md

@@ -28,9 +28,9 @@ function System(f; name)
     pars = @parameters m=10 k=1000 d=1
 
     eqs = [f ~ src.output.u
-           ddx * 10 ~ k * x + d * dx + f
-           D(x) ~ dx
-           D(dx) ~ ddx]
+        ddx * 10 ~ k * x + d * dx + f
+        D(x) ~ dx
+        D(dx) ~ ddx]
 
     ODESystem(eqs, t, vars, pars; systems = [src], name)
 end
@@ -74,9 +74,9 @@ function System(; name)
     pars = @parameters m=10 k=1000 d=1
 
     eqs = [f ~ get_sampled_data(t)
-           ddx * 10 ~ k * x + d * dx + f
-           D(x) ~ dx
-           D(dx) ~ ddx]
+        ddx * 10 ~ k * x + d * dx + f
+        D(x) ~ dx
+        D(dx) ~ ddx]
 
     ODESystem(eqs, t, vars, pars; name)
 end
@@ -115,9 +115,9 @@ function System(; name)
     pars = @parameters m=10 k=1000 d=1
 
     eqs = [f ~ src.output.u
-           ddx * 10 ~ k * x + d * dx + f
-           D(x) ~ dx
-           D(dx) ~ ddx]
+        ddx * 10 ~ k * x + d * dx + f
+        D(x) ~ dx
+        D(dx) ~ ddx]
 
     ODESystem(eqs, t, vars, pars; systems = [src], name)
 end

docs/src/tutorials/rc_circuit.md

@@ -22,18 +22,18 @@ V = 1.0
 @named ground = Ground()
 
 rc_eqs = [connect(constant.output, source.V)
-          connect(source.p, resistor.p)
-          connect(resistor.n, capacitor.p)
-          connect(capacitor.n, source.n, ground.g)]
+    connect(source.p, resistor.p)
+    connect(resistor.n, capacitor.p)
+    connect(capacitor.n, source.n, ground.g)]
 
 @named rc_model = ODESystem(rc_eqs, t,
-                            systems = [resistor, capacitor, constant, source, ground])
+    systems = [resistor, capacitor, constant, source, ground])
 sys = structural_simplify(rc_model)
 prob = ODAEProblem(sys, Pair[], (0, 10.0))
 sol = solve(prob, Tsit5())
 plot(sol, vars = [capacitor.v, resistor.i],
-     title = "RC Circuit Demonstration",
-     labels = ["Capacitor Voltage" "Resistor Current"])
+    title = "RC Circuit Demonstration",
+    labels = ["Capacitor Voltage" "Resistor Current"])
 savefig("plot.png");
 nothing; # hide
 ```

docs/src/tutorials/thermal_model.md

@@ -27,7 +27,7 @@ connections = [
 ]
 
 @named model = ODESystem(connections, t,
-                         systems = [mass1, mass2, conduction, Tsensor1, Tsensor2])
+    systems = [mass1, mass2, conduction, Tsensor1, Tsensor2])
 sys = structural_simplify(model)
 prob = ODEProblem(sys, Pair[], (0, 5.0))
 sol = solve(prob, Tsit5())

src/Blocks/Blocks.jl

@@ -18,7 +18,7 @@ export Log, Log10
 include("math.jl")
 
 export Constant, TimeVaryingFunction, Sine, Cosine, ContinuousClock, Ramp, Step, ExpSine,
-       Square, Triangular, Parameter, SampledData
+    Square, Triangular, Parameter, SampledData
 include("sources.jl")
 
 export Limiter, DeadZone, SlewRateLimiter
@@ -29,7 +29,7 @@ export PI, LimPI, PID, LimPID
 include("continuous.jl")
 
 export AnalysisPoint, get_sensitivity, get_comp_sensitivity,
-       get_looptransfer, open_loop
+    get_looptransfer, open_loop
 include("analysis_points.jl")
 
 end