From ef1fb78921dded21efd6dd301253ad109dc2e86d Mon Sep 17 00:00:00 2001 From: Dimitra Blana Date: Mon, 5 Jun 2023 16:31:25 +0100 Subject: [PATCH] Update ReadMe.md --- Code/Model/OptimalControl/Pareto/ReadMe.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/Code/Model/OptimalControl/Pareto/ReadMe.md b/Code/Model/OptimalControl/Pareto/ReadMe.md index ed5e1cf..0b6a195 100644 --- a/Code/Model/OptimalControl/Pareto/ReadMe.md +++ b/Code/Model/OptimalControl/Pareto/ReadMe.md @@ -7,6 +7,6 @@ Include TechForParalysis\Code\Model and TechForParalysis\Code\Model\OptimalContr To optimise elbow trajectory and muscle activations. 1. First run find_das3elbow_feas_solutions.m to find a range of feasible solutions. This 'runs' an optimisation with the cost function set to zero just to generate a set of feasible solutions for an initial population. -2. Run create_initial_population_elbow.m selects the successful outputs from the previous step and saves them in a matrix (mat file init_pop_elbow_pareto). -3. Run das3elbow_optimize_pareto.m by entering ```result = das3elbow_optimize_pareto("output_filename");``` at the command line +2. Run create_initial_population_elbow.m selects the successful outputs from the previous step and saves them in a matrix (mat file init_pop_elbow_pareto). It also plots histograms and a scatterplot of the two cost functions. +3. Run das3elbow_optimize_pareto.m by entering ```result = das3elbow_optimize_pareto('output_filename');``` at the command line