Update precompile.jl to decreate TTFX

Author: ferrolho

src/precompile.jl

@@ -1,13 +1,56 @@
-import PrecompileTools
-
-PrecompileTools.@compile_workload begin
-    vis = Visualizer()
-    robot = create_robot_franka("panda_arm", vis)
-    problem = Problem(robot, 201, 1/100)
-    fix_joint_velocities!(problem, robot, 1, zeros(robot.n_v))
-    cpu_time, x, solver_log = solve_with_ipopt(problem, robot)
-    play_trajectory(vis, problem, robot, x)
-    plot_results(problem, robot, x)
-    Plots.closeall()
-    MeshCat.close_server!(vis.core)
+using PrecompileTools: @setup_workload, @compile_workload
+
+# PrecompileTools allows you to reduce the latency of the first execution of Julia code.
+# It is applicable for package developers and for "ordinary users" in their personal workflows.
+# See the GitHub repository and docs for more details: https://github.com/JuliaLang/PrecompileTools.jl.
+
+@setup_workload begin
+
+    # Putting some things in `@setup_workload` instead of `@compile_workload` can
+    # reduce the size of the precompile file and potentially make loading faster.
+
+    # CAREFUL! Objects defined here will persist in every session including this package.
+
+    @compile_workload begin
+
+        # All calls in this block will be precompiled, regardless of whether they belong to this package or not.
+
+        # Options for the Ipopt numerical solver
+        ipopt_options = Dict(
+            # "acceptable_compl_inf_tol" => 0.1,
+            # "acceptable_constr_viol_tol" => 0.1,
+            # "acceptable_dual_inf_tol" => 1.0,
+            "acceptable_iter" => 1,
+            "acceptable_tol" => 1.0,
+            "hessian_approximation" => "limited-memory",
+            # "max_cpu_time" => 15.0,
+            "max_iter" => 1,
+            "mu_strategy" => "monotone",
+            "print_level" => 0,  # default: 5
+        )
+
+        vis = Visualizer()
+        robot = create_robot_franka("panda_arm", vis)
+        problem = Problem(robot, 2, 1 / 100)
+
+        initial_q = Float64[0, 0, 0, -π/2, 0, π, 0]
+
+        fix_joint_positions!(problem, robot, 1, initial_q)
+        fix_joint_velocities!(problem, robot, 1, zeros(robot.n_v))
+        constrain_ee_position!(problem, 1, zeros(3))
+
+        initial_guess = zeros(problem.num_knots * (robot.n_q + robot.n_v + robot.n_τ) - robot.n_τ)
+
+        cpu_time, x, solver_log = solve_with_ipopt(problem, robot, initial_guess=initial_guess, user_options=ipopt_options, use_inv_dyn=false, minimise_τ=false)
+        cpu_time, x, solver_log = solve_with_ipopt(problem, robot, initial_guess=initial_guess, user_options=ipopt_options, use_inv_dyn=false, minimise_τ=true)
+        cpu_time, x, solver_log = solve_with_ipopt(problem, robot, initial_guess=initial_guess, user_options=ipopt_options, use_inv_dyn=true, minimise_τ=false)
+
+        play_trajectory(vis, problem, robot, x)
+        plot_results(problem, robot, x)
+
+        Plots.closeall()
+        MeshCat.close_server!(vis.core)
+
+    end
+
 end