Merge pull request #736 from NonDairyNeutrino/fix_vars_warning

fix warning: update vars to idxs

docs/Project.toml

@@ -62,7 +62,7 @@ ModelingToolkit = "8"
 ODEProblemLibrary = "0.1"
 Optimization = "3"
 OptimizationNLopt = "0.1, 0.2"
-OrdinaryDiffEq = "6.31"
+OrdinaryDiffEq = "6.76"
 Plots = "1"
 RecursiveArrayTools = "2, 3"
 SDEProblemLibrary = "0.1"

docs/src/examples/classical_physics.md

@@ -85,7 +85,7 @@ prob = SecondOrderODEProblem(harmonicoscillator, dx₀, x₀, tspan, ω)
 sol = solve(prob, DPRKN6())
 
 #Plot
-plot(sol, vars = [2, 1], linewidth = 2, title = "Simple Harmonic Oscillator",
+plot(sol, idxs = [2, 1], linewidth = 2, title = "Simple Harmonic Oscillator",
     xaxis = "Time", yaxis = "Elongation", label = ["x" "dx"])
 plot!(t -> A * cos(ω * t - ϕ), lw = 3, ls = :dash, label = "Analytical Solution x")
 plot!(t -> -A * ω * sin(ω * t - ϕ), lw = 3, ls = :dash, label = "Analytical Solution dx")
@@ -147,12 +147,12 @@ plot(sol, linewidth = 2, title = "Simple Pendulum Problem", xaxis = "Time",
 So now we know that behaviour of the position versus time. However, it will be useful to us to look at the phase space of the pendulum, i.e., and representation of all possible states of the system in question (the pendulum) by looking at its velocity and position. Phase space analysis is ubiquitous in the analysis of dynamical systems, and thus we will provide a few facilities for it.
 
 ```@example physics
-p = plot(sol, vars = (1, 2), xlims = (-9, 9), title = "Phase Space Plot",
+p = plot(sol, idxs = (1, 2), xlims = (-9, 9), title = "Phase Space Plot",
     xaxis = "Velocity", yaxis = "Position", leg = false)
 function phase_plot(prob, u0, p, tspan = 2pi)
     _prob = ODEProblem(prob.f, u0, (0.0, tspan))
     sol = solve(_prob, Vern9()) # Use Vern9 solver for higher accuracy
-    plot!(p, sol, vars = (1, 2), xlims = nothing, ylims = nothing)
+    plot!(p, sol, idxs = (1, 2), xlims = nothing, ylims = nothing)
 end
 for i in (-4pi):(pi / 2):(4π)
     for j in (-4pi):(pi / 2):(4π)
@@ -267,13 +267,13 @@ function poincare_map(prob, u₀, p; callback = cb)
     _prob = ODEProblem(prob.f, u₀, prob.tspan)
     sol = solve(_prob, Vern9(), save_everystep = false, save_start = false,
         save_end = false, callback = cb, abstol = 1e-16, reltol = 1e-16)
-    scatter!(p, sol, vars = (3, 4), markersize = 3, msw = 0)
+    scatter!(p, sol, idxs = (3, 4), markersize = 3, msw = 0)
 end
 ```
 
 ```@example physics
 lβrange = -0.02:0.0025:0.02
-p = scatter(sol2, vars = (3, 4), leg = false, markersize = 3, msw = 0)
+p = scatter(sol2, idxs = (3, 4), leg = false, markersize = 3, msw = 0)
 for lβ in lβrange
     poincare_map(poincare, [0.01, 0.01, 0.01, lβ], p)
 end
@@ -334,7 +334,7 @@ sol = solve(prob, Vern9(), abstol = 1e-16, reltol = 1e-16);
 
 ```@example physics
 # Plot the orbit
-plot(sol, vars = (1, 2), title = "The orbit of the Hénon-Heiles system", xaxis = "x",
+plot(sol, idxs = (1, 2), title = "The orbit of the Hénon-Heiles system", xaxis = "x",
     yaxis = "y", leg = false)
 ```
 
@@ -343,9 +343,9 @@ plot(sol, vars = (1, 2), title = "The orbit of the Hénon-Heiles system", xaxis
 @show sol.retcode
 
 #Plot -
-plot(sol, vars = (1, 3), title = "Phase space for the Hénon-Heiles system",
+plot(sol, idxs = (1, 3), title = "Phase space for the Hénon-Heiles system",
     xaxis = "Position", yaxis = "Velocity")
-plot!(sol, vars = (2, 4), leg = false)
+plot!(sol, idxs = (2, 4), leg = false)
 ```
 
 ```@example physics
@@ -382,14 +382,14 @@ Notice that we get the same results:
 
 ```@example physics
 # Plot the orbit
-plot(sol2, vars = (3, 4), title = "The orbit of the Hénon-Heiles system", xaxis = "x",
+plot(sol2, idxs = (3, 4), title = "The orbit of the Hénon-Heiles system", xaxis = "x",
     yaxis = "y", leg = false)
 ```
 
 ```@example physics
-plot(sol2, vars = (3, 1), title = "Phase space for the Hénon-Heiles system",
+plot(sol2, idxs = (3, 1), title = "Phase space for the Hénon-Heiles system",
     xaxis = "Position", yaxis = "Velocity")
-plot!(sol2, vars = (4, 2), leg = false)
+plot!(sol2, idxs = (4, 2), leg = false)
 ```
 
 but now the energy change is essentially zero:

docs/src/examples/kepler_problem.md

@@ -10,8 +10,7 @@ Also, we know that
 $${\displaystyle {\frac {\mathrm {d} {\boldsymbol {p}}}{\mathrm {d} t}}=-{\frac {\partial {\mathcal {H}}}{\partial {\boldsymbol {q}}}}\quad ,\quad {\frac {\mathrm {d} {\boldsymbol {q}}}{\mathrm {d} t}}=+{\frac {\partial {\mathcal {H}}}{\partial {\boldsymbol {p}}}}}$$
 
 ```@example kepler
-using OrdinaryDiffEq, LinearAlgebra, ForwardDiff, Plots;
-gr();
+using OrdinaryDiffEq, LinearAlgebra, ForwardDiff, Plots
 H(q, p) = norm(p)^2 / 2 - inv(norm(q))
 L(q, p) = q[1] * p[2] - p[1] * q[2]
 
@@ -30,12 +29,12 @@ sol = solve(prob, KahanLi6(), dt = 1 // 10);
 Let's plot the orbit and check the energy and angular momentum variation. We know that energy and angular momentum should be constant, and they are also called first integrals.
 
 ```@example kepler
-plot_orbit(sol) = plot(sol, vars = (3, 4), lab = "Orbit", title = "Kepler Problem Solution")
+plot_orbit(sol) = plot(sol, idxs = (3, 4), lab = "Orbit", title = "Kepler Problem Solution")
 
 function plot_first_integrals(sol, H, L)
-    plot(initial_first_integrals[1] .- map(u -> H(u[2, :], u[1, :]), sol.u),
+    plot(initial_first_integrals[1] .- map(u -> H(u.x[2], u.x[1]), sol.u),
         lab = "Energy variation", title = "First Integrals")
-    plot!(initial_first_integrals[2] .- map(u -> L(u[2, :], u[1, :]), sol.u),
+    plot!(initial_first_integrals[2] .- map(u -> L(u.x[2], u.x[1]), sol.u),
         lab = "Angular momentum variation")
 end
 analysis_plot(sol, H, L) = plot(plot_orbit(sol), plot_first_integrals(sol, H, L))

docs/src/solvers/ode_solve.md

@@ -556,20 +556,18 @@ to be thread safe. It parallelizes the `nlsolve` calls inside the method.
   - `ROS2PR` - A 2nd order stiffly accurate Rosenbrock-Wanner method with 3 internal stages with Rinf=0.
     For problems with medium stiffness the convergence behaviour is very poor
     and it is recommended to use `ROS2S` instead.
-  - `ROS3PR` - A 3nd order stiffly accurate Rosenbrock-Wanner method 
+  - `ROS3PR` - A 3nd order stiffly accurate Rosenbrock-Wanner method
     with 3 internal stages and B_PR consistent of order 3, which is strongly A-stable with Rinf~=-0.73.
-  - `Scholz47` - A 3nd order stiffly accurate Rosenbrock-Wanner method 
+  - `Scholz47` - A 3nd order stiffly accurate Rosenbrock-Wanner method
     with 3 internal stages and B_PR consistent of order 3, which is strongly A-stable with Rinf~=-0.73.
     Convergence with order 4 for the stiff case, but has a poor accuracy.
   - `ROS3PRL` - A 3nd order stiffly accurate Rosenbrock-Wanner method with 4 internal stages
     with B_PR consistent of order 2 with Rinf=0. The order of convergence decreases if medium stiff problems
     are considered, but it has good results for very stiff cases.
   - `ROS3PRL2` - A 3nd order stiffly accurate Rosenbrock-Wanner method with 4 internal stages
-    with B_PR consistent of order 3. The order of convergence does NOT decreases if 
+    with B_PR consistent of order 3. The order of convergence does NOT decreases if
     medium stiff problems are considered as it does for ROS3PRL.
 
-
-
 #### Rosenbrock-W Methods
 
   - `Rosenbrock23` - An Order 2/3 L-Stable Rosenbrock-W method which is good for very
@@ -588,9 +586,9 @@ to be thread safe. It parallelizes the `nlsolve` calls inside the method.
   - `ROS34PW2` - A 4th order stiffy accurate Rosenbrock-W method for PDAEs.
   - `ROS34PW3` - A 4th order strongly A-stable (Rinf~0.63) Rosenbrock-W method.
   - `ROS34PRw` - A 3nd order stiffly accurate Rosenbrock-Wanner W-method with 4 internal stages with B_PR consistent of order 2
-  - `ROS2S` - A 2nd order stiffly accurate Rosenbrock-Wanner W-method 
+  - `ROS2S` - A 2nd order stiffly accurate Rosenbrock-Wanner W-method
     with 3 internal stages with B_PR consistent of order 2 with Rinf=0.
-    
+
 #### Stabilized Explicit Methods
 
   - `ROCK2` - Second order stabilized Runge-Kutta method. Exhibits high stability