minor

UtilsDynamicSimulations/OpenSimAD/mainOpenSimAD.py

@@ -313,7 +313,7 @@ def run_tracking(baseDir, dataDir, subject, settings, case='0',
     # also specify the optimal forces as part of the problem settings. For
     # example, to set the optimal force of the right hip flexion to 400, add
     # coordinate_optimal_forces['hip_flexion_r'] = 400 in the settings dict.
-    # See example under drop_jump_torque_driven in settingsOpenSimAD.
+    # See example under running_torque_driven in settingsOpenSimAD.
     torque_driven_model = False
     if 'torque_driven_model' in settings:
         torque_driven_model = settings['torque_driven_model']

example_kinetics.py

@@ -129,7 +129,7 @@
 case = '0' # Change this to compare across settings.
 # Options are 'squat', 'STS', and 'jump'.
 if session_type == 'overground': 
-    trial_name = 'squat'
+    trial_name = 'STS'
     if trial_name == 'squat': # Squat
         motion_type = 'squats'
         repetition = 1
@@ -160,7 +160,7 @@
         treadmill_speed = 4.0
 
 # Set to True to solve the optimal control problem.
-solveProblem = False
+solveProblem = True
 # Set to True to analyze the results of the optimal control problem. If you
 # solved the problem already, and only want to analyze/process the results, you
 # can set solveProblem to False and run this script with analyzeResults set to
@@ -184,7 +184,7 @@
 
 # %% Simulation.
 run_tracking(baseDir, dataFolder, session_id, settings, case=case, 
-              solveProblem=solveProblem, analyzeResults=analyzeResults)
+             solveProblem=solveProblem, analyzeResults=analyzeResults)
 
 # %% Plots.
 # To compare different cases, add to the cases list, eg cases=['0','1'].