Merge pull request #64 from perfanalytics/draft

Merge draft to main

Pose2Sim/Demo/S00_Demo_Session/Config.toml

@@ -26,13 +26,9 @@ frame_range = [] # For example [10,300], or [] for all frames
 
 exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['<participant_dir/trial_dir>', 'etc'].
 # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial']
-
-## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon!
-participant_height = 1.7 # m
-participant_mass = 70 # kg
-
-
 # Take heart, calibration is not that complicated once you get the hang of it!
+
+
 [calibration]
 calibration_type = 'convert' # 'convert' or 'calculate'
 
@@ -94,8 +90,7 @@ calibration_type = 'convert' # 'convert' or 'calculate'
 
 [pose]
 pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' 
-pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII, 
-                        #               BODY_25_AUGMENTED # Coming soon!
+pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII
 						      #With mediapipe: BLAZEPOSE. 
 						      #With alphapose: HALPE_26, HALPE_68, HALPE_136, COCO_133. 
 						      #With deeplabcut: CUSTOM. See example at the end of the file.
@@ -141,7 +136,7 @@ make_c3d = false # save triangulated data in c3d format in addition to trc # Com
 
 [filtering]
 type = 'butterworth' # butterworth, kalman, gaussian, LOESS, median, butterworth_on_speed
-display_figures = false # true or false (lowercase)
+display_figures = true # true or false (lowercase)
 
    [filtering.butterworth]
    order = 4 
@@ -161,6 +156,12 @@ display_figures = false # true or false (lowercase)
    kernel_size = 9
 
 
+[markerAugmentation] 
+## Only works on BODY_25 and BODY_25B models
+participant_height = 1.7 # m
+participant_mass = 70 # kg
+
+
 [opensim]
 static_trial = ['S00_P00_Participant/S00_P00_T00_StaticTrial']
 #            # If this Config.toml file is at the Trial level, set to true or false (lowercase);

Pose2Sim/Demo/S00_Demo_Session/S00_P00_Participant/Config.toml

@@ -26,13 +26,9 @@
 
 # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['<participant_dir/trial_dir>', 'etc'].
 # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial']
-
-## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon!
-# participant_height = 1.7 # m
-# participant_mass = 70 # kg
-
-
 ## Take heart, calibration is not that complicated once you get the hang of it!
+
+
 # [calibration]
 # calibration_type = 'convert' # 'convert' or 'calculate'
 
@@ -96,7 +92,6 @@
 # [pose]
 # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' 
 # pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII,
-                        #               BODY_25_AUGMENTED # Coming soon! 
 # 						      #With mediapipe: BLAZEPOSE. 
 # 						      #With alphapose: HALPE_26, HALPE_68, HALPE_136, COCO_133. 
 # 						      #With deeplabcut: CUSTOM. See example at the end of the file.
@@ -162,6 +157,12 @@
    # kernel_size = 9
 
 
+# [markerAugmentation] 
+# ## Only works on BODY_25 and BODY_25B models
+# participant_height = 1.7 # m
+# participant_mass = 70 # kg
+
+
 # [opensim]
 # static_trial = ['S00_P00_Participant/S00_P00_T00_StaticTrial']
 #              # If this Config.toml file is at the Trial level, set to true or false (lowercase);

Pose2Sim/Demo/S00_Demo_Session/S00_P00_Participant/S00_P00_T00_StaticTrial/Config.toml

@@ -27,10 +27,6 @@
 # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['<participant_dir/trial_dir>', 'etc'].
 # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial']
 
-## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon!
-# participant_height = 1.7 # m
-# participant_mass = 70 # kg
-
 
 ## Take heart, calibration is not that complicated once you get the hang of it!
 # [calibration]
@@ -96,7 +92,6 @@
 # [pose]
 # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' 
 # pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII,
-                        #               BODY_25_AUGMENTED # Coming soon! 
 # 						      #With mediapipe: BLAZEPOSE. 
 # 						      #With alphapose: HALPE_26, HALPE_68, HALPE_136, COCO_133. 
 # 						      #With deeplabcut: CUSTOM. See example at the end of the file.
@@ -140,9 +135,9 @@
 # make_c3d = false # save triangulated data in c3d format in addition to trc # Coming soon!
 
 
-# [filtering]
+[filtering]
 # type = 'butterworth' # butterworth, kalman, gaussian, LOESS, median, butterworth_on_speed
-# display_figures = true # true or false (lowercase)
+display_figures = false # true or false (lowercase)
 
    # [filtering.butterworth]
    # order = 4 
@@ -162,6 +157,12 @@
    # kernel_size = 9
 
 
+# [markerAugmentation] 
+# ## Only works on BODY_25 and BODY_25B models
+# participant_height = 1.7 # m
+# participant_mass = 70 # kg
+
+
 # [opensim]
 # static_trial = ['S00_P00_Participant/S00_P00_T00_StaticTrial']
 #              # If this Config.toml file is at the Trial level, set to true or false (lowercase);

Pose2Sim/Demo/S00_Demo_Session/S00_P00_Participant/S00_P00_T01_BalancingTrial/Config.toml

@@ -27,10 +27,6 @@
 # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['<participant_dir/trial_dir>', 'etc'].
 # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial']
 
-## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon!
-# participant_height = 1.7 # m
-# participant_mass = 70 # kg
-
 
 ## Take heart, calibration is not that complicated once you get the hang of it!
 # [calibration]
@@ -96,7 +92,6 @@
 # [pose]
 # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' 
 # pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII,
-                        #               BODY_25_AUGMENTED # Coming soon! 
 # 						      #With mediapipe: BLAZEPOSE. 
 # 						      #With alphapose: HALPE_26, HALPE_68, HALPE_136, COCO_133. 
 # 						      #With deeplabcut: CUSTOM. See example at the end of the file.
@@ -140,9 +135,9 @@
 # make_c3d = false # save triangulated data in c3d format in addition to trc # Coming soon!
 
 
-[filtering]
+# [filtering]
 # type = 'butterworth' # butterworth, kalman, gaussian, LOESS, median, butterworth_on_speed
-display_figures = true # true or false (lowercase)
+# display_figures = true # true or false (lowercase)
 
    # [filtering.butterworth]
    # order = 4 
@@ -162,6 +157,12 @@ display_figures = true # true or false (lowercase)
    # kernel_size = 9
 
 
+# [markerAugmentation] 
+# ## Only works on BODY_25 and BODY_25B models
+# participant_height = 1.7 # m
+# participant_mass = 70 # kg
+
+
 # [opensim]
 # static_trial = ['S00_P00_Participant/S00_P00_T00_StaticTrial']
 #              # If this Config.toml file is at the Trial level, set to true or false (lowercase);

Pose2Sim/Demo/S00_Demo_Session/test.py

@@ -22,6 +22,7 @@ def test_workflow():
   Pose2Sim.personAssociation(config_dict)
   Pose2Sim.triangulation(config_dict)
   Pose2Sim.filtering(config_dict)
+  Pose2Sim.markerAugmentation(config_dict)
   # Pose2Sim.kinematics(config_dict)
 
 
@@ -35,4 +36,5 @@ def test_workflow():
   Pose2Sim.personAssociation(config_dict)
   Pose2Sim.triangulation(config_dict)
   Pose2Sim.filtering(config_dict)
+  Pose2Sim.markerAugmentation(config_dict)
   # Pose2Sim.kinematics(config_dict)

Pose2Sim/Demo/S01_Empty_Session/Config.toml

@@ -26,13 +26,9 @@ frame_range = [] # For example [10,300], or [] for all frames
 
 exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['<participant_dir/trial_dir>', 'etc'].
 # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial']
-
-## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon!
-participant_height = 1.7 # m
-participant_mass = 70 # kg
-
-
 # Take heart, calibration is not that complicated once you get the hang of it!
+
+
 [calibration]
 calibration_type = 'convert' # 'convert' or 'calculate'
 
@@ -94,8 +90,7 @@ calibration_type = 'convert' # 'convert' or 'calculate'
 
 [pose]
 pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' 
-pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII, 
-                        #               BODY_25_AUGMENTED # Coming soon! 
+pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII
 						      #With mediapipe: BLAZEPOSE. 
 						      #With alphapose: HALPE_26, HALPE_68, HALPE_136, COCO_133. 
 						      #With deeplabcut: CUSTOM. See example at the end of the file.
@@ -123,7 +118,7 @@ single_person = true # false for multi-person analysis (not supported yet), true
 tracked_keypoint = 'Neck' # If the neck is not detected by the pose_model, check skeleton.py 
 # and choose a stable point for tracking the person of interest (e.g., 'right_shoulder' with BLAZEPOSE)
 reproj_error_threshold_association = 20 # px
-likelihood_error_threshold_association = 0.2
+likelihood_threshold_association = 0.2
 
 
 [triangulation]
@@ -131,17 +126,17 @@ reproj_error_threshold_triangulation = 15 # px
 likelihood_threshold_triangulation = 0.3
 min_cameras_for_triangulation = 2
 interpolation = 'cubic' #linear, slinear, quadratic, cubic, or none
-# 'none' if you don't want to interpolate missing points
+                        # 'none' if you don't want to interpolate missing points
 interp_if_gap_smaller_than = 10 # do not interpolate bigger gaps
 show_interp_indices = true # true or false (lowercase). For each keypoint, return the frames that need to be interpolated
-# handle_LR_swap = false # Better if few cameras (eg less than 4) with risk of limb swapping (eg camera facing sagittal plane), otherwise slightly less accurate and slower
-# undistort_points = false # Better if distorted image (parallel lines curvy on the edge or at least one param > 10^-2), but unnecessary (and slightly slower) if distortions are low
-# make_c3d = false # save triangulated data in c3d format in addition to trc # Coming soon!
+handle_LR_swap = false # Better if few cameras (eg less than 4) with risk of limb swapping (eg camera facing sagittal plane), otherwise slightly less accurate and slower
+undistort_points = false # Better if distorted image (parallel lines curvy on the edge or at least one param > 10^-2), but unnecessary (and slightly slower) if distortions are low
+make_c3d = false # save triangulated data in c3d format in addition to trc # Coming soon!
 
 
 [filtering]
 type = 'butterworth' # butterworth, kalman, gaussian, LOESS, median, butterworth_on_speed
-display_figures = false # true or false (lowercase)
+display_figures = true # true or false (lowercase)
 
    [filtering.butterworth]
    order = 4 
@@ -161,8 +156,14 @@ display_figures = false # true or false (lowercase)
    kernel_size = 9
 
 
+[markerAugmentation] 
+## Only works on BODY_25 and BODY_25B models
+participant_height = 1.7 # m
+participant_mass = 70 # kg
+
+
 [opensim]
-static_trial = ['S01_P00_Participant0/S01_P00_T00_StaticTrial']
+static_trial = ['S00_P00_Participant/S00_P00_T00_StaticTrial']
 #            # If this Config.toml file is at the Trial level, set to true or false (lowercase);
 #            # At the Participant level, specify the name of the static trial folder name, e.g. ['S00_P00_T00_StaticTrial'];
 #            # At the Session level, add participant subdirectory, e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P01_Participant/S00_P00_T00_StaticTrial']
@@ -170,17 +171,17 @@ opensim_bin_path = 'C:\OpenSim 4.4\bin'
 
 
 
-## CUSTOM skeleton, if you trained your own DeepLabCut model for example. 
-## Make sure the node ids correspond to the column numbers of the 2D pose file, starting from zero.
-## 
-## If you want to perform inverse kinematics, you will also need to create an OpenSim model
-## and add to its markerset the location where you expect the triangulated keypoints to be detected.
-## 
-## In this example, CUSTOM reproduces the BODY_25B skeleton  (default skeletons are stored in skeletons.py).
-## You can create as many custom skeletons as you want, just add them further down and rename them.
-## 
-## Check your model hierarchy with:  for pre, _, node in RenderTree(model): 
-##                                      print(f'{pre}{node.name} id={node.id}')
+# CUSTOM skeleton, if you trained your own DeepLabCut model for example. 
+# Make sure the node ids correspond to the column numbers of the 2D pose file, starting from zero.
+# 
+# If you want to perform inverse kinematics, you will also need to create an OpenSim model
+# and add to its markerset the location where you expect the triangulated keypoints to be detected.
+# 
+# In this example, CUSTOM reproduces the BODY_25B skeleton  (default skeletons are stored in skeletons.py).
+# You can create as many custom skeletons as you want, just add them further down and rename them.
+# 
+# Check your model hierarchy with:  for pre, _, node in RenderTree(model): 
+#                                      print(f'{pre}{node.name} id={node.id}')
 [pose.CUSTOM]
 name = "CHip"
 id = "None"

Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/Config.toml

@@ -26,13 +26,9 @@
 
 # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['<participant_dir/trial_dir>', 'etc'].
 # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial']
-
-# participant_height = 1.7 # m
-# participant_mass = 70 # kg
-## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon!
-
-
 ## Take heart, calibration is not that complicated once you get the hang of it!
+
+
 # [calibration]
 # calibration_type = 'convert' # 'convert' or 'calculate'
 
@@ -96,7 +92,6 @@
 # [pose]
 # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' 
 # pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII,
-                        #               BODY_25_AUGMENTED # Coming soon! 
 # 						      #With mediapipe: BLAZEPOSE. 
 # 						      #With alphapose: HALPE_26, HALPE_68, HALPE_136, COCO_133. 
 # 						      #With deeplabcut: CUSTOM. See example at the end of the file.
@@ -162,8 +157,14 @@
    # kernel_size = 9
 
 
+# [markerAugmentation] 
+# ## Only works on BODY_25 and BODY_25B models
+# participant_height = 1.7 # m
+# participant_mass = 70 # kg
+
+
 # [opensim]
-# static_trial = ['S01_P00_Participant0/S01_P00_T00_StaticTrial']
+# static_trial = ['S00_P00_Participant/S00_P00_T00_StaticTrial']
 #              # If this Config.toml file is at the Trial level, set to true or false (lowercase);
 #              # At the Participant level, specify the name of the static trial folder name, e.g. ['S00_P00_T00_StaticTrial'];
 #              # At the Session level, add participant subdirectory, e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P01_Participant/S00_P00_T00_StaticTrial']

Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/S01_P00_T00_StaticTrial/Config.toml

@@ -9,6 +9,7 @@
 # If a parameter is not found here, Pose2Sim will look for its value in the 
 # Config.toml file of the level above. This way, you can set global 
 # instructions for the Session and alter them for specific Participants or Trials.
+# 
 # If you wish to overwrite a parameter for a specific trial or participant, 
 # edit its Config.toml file by uncommenting its key (e.g., [project])
 # and editing its value (e.g., frame_range = [10,300]). Or else, uncomment 
@@ -25,13 +26,9 @@
 
 # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['<participant_dir/trial_dir>', 'etc'].
 # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial']
-
-# participant_height = 1.7 # m
-# participant_mass = 70 # kg
-## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon!
-
-
 ## Take heart, calibration is not that complicated once you get the hang of it!
+
+
 # [calibration]
 # calibration_type = 'convert' # 'convert' or 'calculate'
 
@@ -95,7 +92,6 @@
 # [pose]
 # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' 
 # pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII,
-#                                         BODY_25_AUGMENTED # Coming soon! 
 # 						      #With mediapipe: BLAZEPOSE. 
 # 						      #With alphapose: HALPE_26, HALPE_68, HALPE_136, COCO_133. 
 # 						      #With deeplabcut: CUSTOM. See example at the end of the file.
@@ -161,8 +157,14 @@
    # kernel_size = 9
 
 
+# [markerAugmentation] 
+# ## Only works on BODY_25 and BODY_25B models
+# participant_height = 1.7 # m
+# participant_mass = 70 # kg
+
+
 # [opensim]
-# static_trial = ['S01_P00_Participant0/S01_P00_T00_StaticTrial']
+# static_trial = ['S00_P00_Participant/S00_P00_T00_StaticTrial']
 #              # If this Config.toml file is at the Trial level, set to true or false (lowercase);
 #              # At the Participant level, specify the name of the static trial folder name, e.g. ['S00_P00_T00_StaticTrial'];
 #              # At the Session level, add participant subdirectory, e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P01_Participant/S00_P00_T00_StaticTrial']

Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/S01_P00_T01_MotionTrial1/Config.toml

@@ -9,6 +9,7 @@
 # If a parameter is not found here, Pose2Sim will look for its value in the 
 # Config.toml file of the level above. This way, you can set global 
 # instructions for the Session and alter them for specific Participants or Trials.
+# 
 # If you wish to overwrite a parameter for a specific trial or participant, 
 # edit its Config.toml file by uncommenting its key (e.g., [project])
 # and editing its value (e.g., frame_range = [10,300]). Or else, uncomment 
@@ -25,13 +26,9 @@
 
 # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['<participant_dir/trial_dir>', 'etc'].
 # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial']
-
-# participant_height = 1.7 # m
-# participant_mass = 70 # kg
-## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon!
-
-
 ## Take heart, calibration is not that complicated once you get the hang of it!
+
+
 # [calibration]
 # calibration_type = 'convert' # 'convert' or 'calculate'
 
@@ -95,7 +92,6 @@
 # [pose]
 # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' 
 # pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII,
-                        #               BODY_25_AUGMENTED # Coming soon! 
 # 						      #With mediapipe: BLAZEPOSE. 
 # 						      #With alphapose: HALPE_26, HALPE_68, HALPE_136, COCO_133. 
 # 						      #With deeplabcut: CUSTOM. See example at the end of the file.
@@ -139,9 +135,9 @@
 # make_c3d = false # save triangulated data in c3d format in addition to trc # Coming soon!
 
 
-[filtering]
+# [filtering]
 # type = 'butterworth' # butterworth, kalman, gaussian, LOESS, median, butterworth_on_speed
-display_figures = true # true or false (lowercase)
+# display_figures = true # true or false (lowercase)
 
    # [filtering.butterworth]
    # order = 4 
@@ -161,8 +157,14 @@ display_figures = true # true or false (lowercase)
    # kernel_size = 9
 
 
+# [markerAugmentation] 
+# ## Only works on BODY_25 and BODY_25B models
+# participant_height = 1.7 # m
+# participant_mass = 70 # kg
+
+
 # [opensim]
-# static_trial = ['S01_P00_Participant/0S01_P00_T00_StaticTrial']
+# static_trial = ['S00_P00_Participant/S00_P00_T00_StaticTrial']
 #              # If this Config.toml file is at the Trial level, set to true or false (lowercase);
 #              # At the Participant level, specify the name of the static trial folder name, e.g. ['S00_P00_T00_StaticTrial'];
 #              # At the Session level, add participant subdirectory, e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P01_Participant/S00_P00_T00_StaticTrial']

Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/S01_P00_T02_MotionTrial2/Config.toml

@@ -9,6 +9,7 @@
 # If a parameter is not found here, Pose2Sim will look for its value in the 
 # Config.toml file of the level above. This way, you can set global 
 # instructions for the Session and alter them for specific Participants or Trials.
+# 
 # If you wish to overwrite a parameter for a specific trial or participant, 
 # edit its Config.toml file by uncommenting its key (e.g., [project])
 # and editing its value (e.g., frame_range = [10,300]). Or else, uncomment 
@@ -25,13 +26,9 @@
 
 # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['<participant_dir/trial_dir>', 'etc'].
 # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial']
-
-# participant_height = 1.7 # m
-# participant_mass = 70 # kg
-## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon!
-
-
 ## Take heart, calibration is not that complicated once you get the hang of it!
+
+
 # [calibration]
 # calibration_type = 'convert' # 'convert' or 'calculate'
 
@@ -95,7 +92,6 @@
 # [pose]
 # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' 
 # pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII,
-                        #               BODY_25_AUGMENTED # Coming soon! 
 # 						      #With mediapipe: BLAZEPOSE. 
 # 						      #With alphapose: HALPE_26, HALPE_68, HALPE_136, COCO_133. 
 # 						      #With deeplabcut: CUSTOM. See example at the end of the file.
@@ -139,9 +135,9 @@
 # make_c3d = false # save triangulated data in c3d format in addition to trc # Coming soon!
 
 
-[filtering]
+# [filtering]
 # type = 'butterworth' # butterworth, kalman, gaussian, LOESS, median, butterworth_on_speed
-display_figures = true # true or false (lowercase)
+# display_figures = true # true or false (lowercase)
 
    # [filtering.butterworth]
    # order = 4 
@@ -161,8 +157,14 @@ display_figures = true # true or false (lowercase)
    # kernel_size = 9
 
 
+# [markerAugmentation] 
+# ## Only works on BODY_25 and BODY_25B models
+# participant_height = 1.7 # m
+# participant_mass = 70 # kg
+
+
 # [opensim]
-# static_trial = ['S01_P00_Participant0/S01_P00_T00_StaticTrial']
+# static_trial = ['S00_P00_Participant/S00_P00_T00_StaticTrial']
 #              # If this Config.toml file is at the Trial level, set to true or false (lowercase);
 #              # At the Participant level, specify the name of the static trial folder name, e.g. ['S00_P00_T00_StaticTrial'];
 #              # At the Session level, add participant subdirectory, e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P01_Participant/S00_P00_T00_StaticTrial']

Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/Config.toml

@@ -26,13 +26,9 @@
 
 # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['<participant_dir/trial_dir>', 'etc'].
 # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial']
-
-# participant_height = 1.7 # m
-# participant_mass = 70 # kg
-## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon!
-
-
 ## Take heart, calibration is not that complicated once you get the hang of it!
+
+
 # [calibration]
 # calibration_type = 'convert' # 'convert' or 'calculate'
 
@@ -96,7 +92,6 @@
 # [pose]
 # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' 
 # pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII,
-                        #               BODY_25_AUGMENTED # Coming soon! 
 # 						      #With mediapipe: BLAZEPOSE. 
 # 						      #With alphapose: HALPE_26, HALPE_68, HALPE_136, COCO_133. 
 # 						      #With deeplabcut: CUSTOM. See example at the end of the file.
@@ -162,8 +157,14 @@
    # kernel_size = 9
 
 
+# [markerAugmentation] 
+# ## Only works on BODY_25 and BODY_25B models
+# participant_height = 1.7 # m
+# participant_mass = 70 # kg
+
+
 # [opensim]
-# static_trial = ['S01_P01_Participant1/S01_P01_T00_StaticTrial']
+# static_trial = ['S00_P00_Participant/S00_P00_T00_StaticTrial']
 #              # If this Config.toml file is at the Trial level, set to true or false (lowercase);
 #              # At the Participant level, specify the name of the static trial folder name, e.g. ['S00_P00_T00_StaticTrial'];
 #              # At the Session level, add participant subdirectory, e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P01_Participant/S00_P00_T00_StaticTrial']

Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/S01_P01_T00_StaticTrial/Config.toml

@@ -26,13 +26,9 @@
 
 # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['<participant_dir/trial_dir>', 'etc'].
 # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial']
-
-# participant_height = 1.7 # m
-# participant_mass = 70 # kg
-## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon!
-
-
 ## Take heart, calibration is not that complicated once you get the hang of it!
+
+
 # [calibration]
 # calibration_type = 'convert' # 'convert' or 'calculate'
 
@@ -96,7 +92,6 @@
 # [pose]
 # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' 
 # pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII,
-                        #               BODY_25_AUGMENTED # Coming soon! 
 # 						      #With mediapipe: BLAZEPOSE. 
 # 						      #With alphapose: HALPE_26, HALPE_68, HALPE_136, COCO_133. 
 # 						      #With deeplabcut: CUSTOM. See example at the end of the file.
@@ -162,8 +157,14 @@
    # kernel_size = 9
 
 
+# [markerAugmentation] 
+# ## Only works on BODY_25 and BODY_25B models
+# participant_height = 1.7 # m
+# participant_mass = 70 # kg
+
+
 # [opensim]
-# static_trial = ['S01_P01_Participant1/S01_P01_T00_StaticTrial']
+# static_trial = ['S00_P00_Participant/S00_P00_T00_StaticTrial']
 #              # If this Config.toml file is at the Trial level, set to true or false (lowercase);
 #              # At the Participant level, specify the name of the static trial folder name, e.g. ['S00_P00_T00_StaticTrial'];
 #              # At the Session level, add participant subdirectory, e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P01_Participant/S00_P00_T00_StaticTrial']

Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/S01_P01_T01_MotionTrial1/Config.toml

@@ -26,13 +26,9 @@
 
 # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['<participant_dir/trial_dir>', 'etc'].
 # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial']
-
-# participant_height = 1.7 # m
-# participant_mass = 70 # kg
-## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon!
-
-
 ## Take heart, calibration is not that complicated once you get the hang of it!
+
+
 # [calibration]
 # calibration_type = 'convert' # 'convert' or 'calculate'
 
@@ -96,7 +92,6 @@
 # [pose]
 # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' 
 # pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII,
-                        #               BODY_25_AUGMENTED # Coming soon! 
 # 						      #With mediapipe: BLAZEPOSE. 
 # 						      #With alphapose: HALPE_26, HALPE_68, HALPE_136, COCO_133. 
 # 						      #With deeplabcut: CUSTOM. See example at the end of the file.
@@ -140,9 +135,9 @@
 # make_c3d = false # save triangulated data in c3d format in addition to trc # Coming soon!
 
 
-[filtering]
+# [filtering]
 # type = 'butterworth' # butterworth, kalman, gaussian, LOESS, median, butterworth_on_speed
-display_figures = true # true or false (lowercase)
+# display_figures = true # true or false (lowercase)
 
    # [filtering.butterworth]
    # order = 4 
@@ -162,8 +157,14 @@ display_figures = true # true or false (lowercase)
    # kernel_size = 9
 
 
+# [markerAugmentation] 
+# ## Only works on BODY_25 and BODY_25B models
+# participant_height = 1.7 # m
+# participant_mass = 70 # kg
+
+
 # [opensim]
-# static_trial = ['S01_P01_Participant1/S01_P01_T00_StaticTrial']
+# static_trial = ['S00_P00_Participant/S00_P00_T00_StaticTrial']
 #              # If this Config.toml file is at the Trial level, set to true or false (lowercase);
 #              # At the Participant level, specify the name of the static trial folder name, e.g. ['S00_P00_T00_StaticTrial'];
 #              # At the Session level, add participant subdirectory, e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P01_Participant/S00_P00_T00_StaticTrial']

Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/S01_P01_T02_MotionTrial2/Config.toml

@@ -26,13 +26,9 @@
 
 # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['<participant_dir/trial_dir>', 'etc'].
 # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial']
-
-# participant_height = 1.7 # m
-# participant_mass = 70 # kg
-## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon!
-
-
 ## Take heart, calibration is not that complicated once you get the hang of it!
+
+
 # [calibration]
 # calibration_type = 'convert' # 'convert' or 'calculate'
 
@@ -96,7 +92,6 @@
 # [pose]
 # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' 
 # pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII,
-                        #               BODY_25_AUGMENTED # Coming soon! 
 # 						      #With mediapipe: BLAZEPOSE. 
 # 						      #With alphapose: HALPE_26, HALPE_68, HALPE_136, COCO_133. 
 # 						      #With deeplabcut: CUSTOM. See example at the end of the file.
@@ -140,9 +135,9 @@
 # make_c3d = false # save triangulated data in c3d format in addition to trc # Coming soon!
 
 
-[filtering]
+# [filtering]
 # type = 'butterworth' # butterworth, kalman, gaussian, LOESS, median, butterworth_on_speed
-display_figures = true # true or false (lowercase)
+# display_figures = true # true or false (lowercase)
 
    # [filtering.butterworth]
    # order = 4 
@@ -162,8 +157,14 @@ display_figures = true # true or false (lowercase)
    # kernel_size = 9
 
 
+# [markerAugmentation] 
+# ## Only works on BODY_25 and BODY_25B models
+# participant_height = 1.7 # m
+# participant_mass = 70 # kg
+
+
 # [opensim]
-# static_trial = ['S01_P01_Participant1/S01_P01_T00_StaticTrial']
+# static_trial = ['S00_P00_Participant/S00_P00_T00_StaticTrial']
 #              # If this Config.toml file is at the Trial level, set to true or false (lowercase);
 #              # At the Participant level, specify the name of the static trial folder name, e.g. ['S00_P00_T00_StaticTrial'];
 #              # At the Session level, add participant subdirectory, e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P01_Participant/S00_P00_T00_StaticTrial']

Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/metadata.json

@@ -0,0 +1 @@
+{"reference_marker": "midHip"}

Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/model.json

@@ -0,0 +1 @@
+{"class_name": "Sequential", "config": {"name": "sequential_2", "layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, null, 47], "dtype": "float32", "sparse": false, "ragged": false, "name": "lstm_8_input"}}, {"class_name": "LSTM", "config": {"name": "lstm_8", "trainable": true, "dtype": "float32", "batch_input_shape": [null, null, 47], "return_sequences": true, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 128, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}}, {"class_name": "LSTM", "config": {"name": "lstm_9", "trainable": true, "dtype": "float32", "return_sequences": true, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 128, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}}, {"class_name": "LSTM", "config": {"name": "lstm_10", "trainable": true, "dtype": "float32", "return_sequences": true, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 128, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}}, {"class_name": "LSTM", "config": {"name": "lstm_11", "trainable": true, "dtype": "float32", "return_sequences": true, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 128, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}}, {"class_name": "TimeDistributed", "config": {"name": "time_distributed_2", "trainable": true, "dtype": "float32", "layer": {"class_name": "Dense", "config": {"name": "dense_2", "trainable": true, "dtype": "float32", "units": 105, "activation": "linear", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}}}}]}, "keras_version": "2.12.0", "backend": "tensorflow"}

Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/metadata.json

@@ -0,0 +1 @@
+{"reference_marker": "midHip"}

Pose2Sim/MarkerAugmenter/utils.py

@@ -0,0 +1,191 @@
+from . import utilsDataman
+import numpy as np
+import os
+
+def TRC2numpy(pathFile, markers,rotation=None):
+    # rotation is a dict, eg. {'y':90} with axis, angle for rotation
+    
+    trc_file = utilsDataman.TRCFile(pathFile)
+    time = trc_file.time
+    num_frames = time.shape[0]
+    data = np.zeros((num_frames, len(markers)*3))
+    
+    if rotation != None:
+        for axis,angle in rotation.items():
+            trc_file.rotate(axis,angle)
+    for count, marker in enumerate(markers):
+        data[:,3*count:3*count+3] = trc_file.marker(marker)    
+    this_dat = np.empty((num_frames, 1))
+    this_dat[:, 0] = time
+    data_out = np.concatenate((this_dat, data), axis=1)
+    
+    return data_out
+
+def numpy2TRC(f, data, headers, fc=50.0, t_start=0.0, units="m"):
+    
+    header_mapping = {}
+    for count, header in enumerate(headers):
+        header_mapping[count+1] = header 
+        
+    # Line 1.
+    f.write('PathFileType  4\t(X/Y/Z) %s\n' % os.getcwd())
+    
+    # Line 2.
+    f.write('DataRate\tCameraRate\tNumFrames\tNumMarkers\t'
+                'Units\tOrigDataRate\tOrigDataStartFrame\tOrigNumFrames\n')
+    
+    num_frames=data.shape[0]
+    num_markers=len(header_mapping.keys())
+    
+    # Line 3.
+    f.write('%.1f\t%.1f\t%i\t%i\t%s\t%.1f\t%i\t%i\n' % (
+            fc, fc, num_frames,
+            num_markers, units, fc,
+            1, num_frames))
+    
+    # Line 4.
+    f.write("Frame#\tTime\t")
+    for key in sorted(header_mapping.keys()):
+        f.write("%s\t\t\t" % format(header_mapping[key]))
+
+    # Line 5.
+    f.write("\n\t\t")
+    for imark in np.arange(num_markers) + 1:
+        f.write('X%i\tY%s\tZ%s\t' % (imark, imark, imark))
+    f.write('\n')
+    
+    # Line 6.
+    f.write('\n')
+
+    for frame in range(data.shape[0]):
+        f.write("{}\t{:.8f}\t".format(frame+1,(frame)/fc+t_start)) # opensim frame labeling is 1 indexed
+
+        for key in sorted(header_mapping.keys()):
+            f.write("{:.5f}\t{:.5f}\t{:.5f}\t".format(data[frame,0+(key-1)*3], data[frame,1+(key-1)*3], data[frame,2+(key-1)*3]))
+        f.write("\n")
+
+def getOpenPoseMarkerNames():
+    
+    markerNames = ["Nose", "Neck", "RShoulder", "RElbow", "RWrist",
+                   "LShoulder", "LElbow", "LWrist", "midHip", "RHip",
+                   "RKnee", "RAnkle", "LHip", "LKnee", "LAnkle", "REye",
+                   "LEye", "REar", "LEar", "LBigToe", "LSmallToe",
+                   "LHeel", "RBigToe", "RSmallToe", "RHeel"]
+    
+    return markerNames
+
+def getOpenPoseFaceMarkers():
+    
+    faceMarkerNames = ['Nose', 'REye', 'LEye', 'REar', 'LEar']
+    markerNames = getOpenPoseMarkerNames()
+    idxFaceMarkers = [markerNames.index(i) for i in faceMarkerNames]
+    
+    return faceMarkerNames, idxFaceMarkers
+
+def getOpenPoseMarkers_fullBody():
+
+    feature_markers = [
+        "Neck", "RShoulder", "LShoulder", "RHip", "LHip", "RKnee", "LKnee",
+        "RAnkle", "LAnkle", "RHeel", "LHeel", "RSmallToe", "LSmallToe",
+        "RBigToe", "LBigToe", "RElbow", "LElbow", "RWrist", "LWrist"]
+
+    response_markers = ["C7_study", "r_shoulder_study", "L_shoulder_study",
+                        "r.ASIS_study", "L.ASIS_study", "r.PSIS_study", 
+                        "L.PSIS_study", "r_knee_study", "L_knee_study",
+                        "r_mknee_study", "L_mknee_study", "r_ankle_study", 
+                        "L_ankle_study", "r_mankle_study", "L_mankle_study",
+                        "r_calc_study", "L_calc_study", "r_toe_study", 
+                        "L_toe_study", "r_5meta_study", "L_5meta_study",
+                        "r_lelbow_study", "L_lelbow_study", "r_melbow_study",
+                        "L_melbow_study", "r_lwrist_study", "L_lwrist_study",
+                        "r_mwrist_study", "L_mwrist_study",
+                        "r_thigh1_study", "r_thigh2_study", "r_thigh3_study",
+                        "L_thigh1_study", "L_thigh2_study", "L_thigh3_study", 
+                        "r_sh1_study", "r_sh2_study", "r_sh3_study", 
+                        "L_sh1_study", "L_sh2_study", "L_sh3_study",
+                        "RHJC_study", "LHJC_study"]
+
+    return feature_markers, response_markers
+
+def getOpenPoseMarkers_lowerExtremity():
+
+    feature_markers = [
+        "Neck", "RShoulder", "LShoulder", "RHip", "LHip", "RKnee", "LKnee",
+        "RAnkle", "LAnkle", "RHeel", "LHeel", "RSmallToe", "LSmallToe",
+        "RBigToe", "LBigToe"]
+
+    response_markers = ["C7_study", "r_shoulder_study", "L_shoulder_study",
+                        "r.ASIS_study", "L.ASIS_study", "r.PSIS_study", 
+                        "L.PSIS_study", "r_knee_study", "L_knee_study",
+                        "r_mknee_study", "L_mknee_study", "r_ankle_study", 
+                        "L_ankle_study", "r_mankle_study", "L_mankle_study",
+                        "r_calc_study", "L_calc_study", "r_toe_study", 
+                        "L_toe_study", "r_5meta_study", "L_5meta_study",
+                        "r_thigh1_study", "r_thigh2_study", "r_thigh3_study",
+                        "L_thigh1_study", "L_thigh2_study", "L_thigh3_study", 
+                        "r_sh1_study", "r_sh2_study", "r_sh3_study", 
+                        "L_sh1_study", "L_sh2_study", "L_sh3_study",
+                        "RHJC_study", "LHJC_study"]
+
+    return feature_markers, response_markers
+
+# Different order of markers compared to getOpenPoseMarkers_lowerExtremity 
+def getOpenPoseMarkers_lowerExtremity2():
+
+    feature_markers = [
+        "Neck", "RShoulder", "LShoulder", "RHip", "LHip", "RKnee", "LKnee",
+        "RAnkle", "LAnkle", "RHeel", "LHeel", "RSmallToe", "LSmallToe",
+        "RBigToe", "LBigToe"]
+
+    response_markers = [
+        'r.ASIS_study', 'L.ASIS_study', 'r.PSIS_study',
+        'L.PSIS_study', 'r_knee_study', 'r_mknee_study', 
+        'r_ankle_study', 'r_mankle_study', 'r_toe_study', 
+        'r_5meta_study', 'r_calc_study', 'L_knee_study', 
+        'L_mknee_study', 'L_ankle_study', 'L_mankle_study',
+        'L_toe_study', 'L_calc_study', 'L_5meta_study', 
+        'r_shoulder_study', 'L_shoulder_study', 'C7_study', 
+        'r_thigh1_study', 'r_thigh2_study', 'r_thigh3_study',
+        'L_thigh1_study', 'L_thigh2_study', 'L_thigh3_study',
+        'r_sh1_study', 'r_sh2_study', 'r_sh3_study', 'L_sh1_study',
+        'L_sh2_study', 'L_sh3_study', 'RHJC_study', 'LHJC_study']
+
+    return feature_markers, response_markers
+
+
+def getMarkers_upperExtremity_pelvis():
+
+    feature_markers = [
+        "Neck", "RShoulder", "LShoulder", "RHip", "LHip", "RElbow", "LElbow",
+        "RWrist", "LWrist"]
+
+    response_markers = ["r_lelbow_study", "L_lelbow_study", "r_melbow_study",
+                        "L_melbow_study", "r_lwrist_study", "L_lwrist_study",
+                        "r_mwrist_study", "L_mwrist_study"]
+
+    return feature_markers, response_markers
+
+def getMarkers_upperExtremity_noPelvis():
+
+    feature_markers = [
+        "Neck", "RShoulder", "LShoulder", "RElbow", "LElbow", "RWrist",
+        "LWrist"]
+
+    response_markers = ["r_lelbow_study", "L_lelbow_study", "r_melbow_study",
+                        "L_melbow_study", "r_lwrist_study", "L_lwrist_study",
+                        "r_mwrist_study", "L_mwrist_study"]
+
+    return feature_markers, response_markers
+
+# Different order of markers compared to getMarkers_upperExtremity_noPelvis.
+def getMarkers_upperExtremity_noPelvis2():
+
+    feature_markers = [
+        "Neck", "RShoulder", "LShoulder", "RElbow", "LElbow", "RWrist",
+        "LWrist"]
+
+    response_markers = ["r_lelbow_study", "r_melbow_study", "r_lwrist_study",
+                        "r_mwrist_study", "L_lelbow_study", "L_melbow_study",
+                        "L_lwrist_study", "L_mwrist_study"]
+
+    return feature_markers, response_markers

Pose2Sim/MarkerAugmenter/utilsDataman.py

@@ -0,0 +1,282 @@
+"""Manages the movement and use of data files."""
+
+import os
+import warnings
+from scipy.spatial.transform import Rotation as R
+
+import numpy as np
+from numpy.lib.recfunctions import append_fields
+
+class TRCFile(object):
+    """A plain-text file format for storing motion capture marker trajectories.
+    TRC stands for Track Row Column.
+
+    The metadata for the file is stored in attributes of this object.
+
+    See
+    http://simtk-confluence.stanford.edu:8080/display/OpenSim/Marker+(.trc)+Files
+    for more information.
+
+    """
+    def __init__(self, fpath=None, **kwargs):
+            #path=None,
+            #data_rate=None,
+            #camera_rate=None,
+            #num_frames=None,
+            #num_markers=None,
+            #units=None,
+            #orig_data_rate=None,
+            #orig_data_start_frame=None,
+            #orig_num_frames=None,
+            #marker_names=None,
+            #time=None,
+            #):
+        """
+        Parameters
+        ----------
+        fpath : str
+            Valid file path to a TRC (.trc) file.
+
+        """
+        self.marker_names = []
+        if fpath != None:
+            self.read_from_file(fpath)
+        else:
+            for k, v in kwargs.items():
+                setattr(self, k, v)
+
+    def read_from_file(self, fpath):
+        # Read the header lines / metadata.
+        # ---------------------------------
+        # Split by any whitespace.
+        # TODO may cause issues with paths that have spaces in them.
+        f = open(fpath)
+        # These are lists of each entry on the first few lines.
+        first_line = f.readline().split()
+        # Skip the 2nd line.
+        f.readline()
+        third_line = f.readline().split()
+        fourth_line = f.readline().split()
+        f.close()
+
+        # First line.
+        if len(first_line) > 3:
+            self.path = first_line[3]
+        else:
+            self.path = ''
+
+        # Third line.
+        self.data_rate = float(third_line[0])
+        self.camera_rate = float(third_line[1])
+        self.num_frames = int(third_line[2])
+        self.num_markers = int(third_line[3])
+        self.units = third_line[4]
+        self.orig_data_rate = float(third_line[5])
+        self.orig_data_start_frame = int(third_line[6])
+        self.orig_num_frames = int(third_line[7])
+
+        # Marker names.
+        # The first and second column names are 'Frame#' and 'Time'.
+        self.marker_names = fourth_line[2:]
+
+        len_marker_names = len(self.marker_names)
+        if len_marker_names != self.num_markers:
+            warnings.warn('Header entry NumMarkers, %i, does not '
+                    'match actual number of markers, %i. Changing '
+                    'NumMarkers to match actual number.' % (
+                        self.num_markers, len_marker_names))
+            self.num_markers = len_marker_names
+
+        # Load the actual data.
+        # ---------------------
+        col_names = ['frame_num', 'time']
+        # This naming convention comes from OpenSim's Inverse Kinematics tool,
+        # when it writes model marker locations.
+        for mark in self.marker_names:
+            col_names += [mark + '_tx', mark + '_ty', mark + '_tz']
+        dtype = {'names': col_names,
+                'formats': ['int'] + ['float64'] * (3 * self.num_markers + 1)}
+        usecols = [i for i in range(3 * self.num_markers + 1 + 1)]
+        self.data = np.loadtxt(fpath, delimiter='\t', skiprows=5, dtype=dtype,
+                               usecols=usecols)
+        self.time = self.data['time']
+
+        # Check the number of rows.
+        n_rows = self.time.shape[0]
+        if n_rows != self.num_frames:
+            warnings.warn('%s: Header entry NumFrames, %i, does not '
+                    'match actual number of frames, %i, Changing '
+                    'NumFrames to match actual number.' % (fpath,
+                        self.num_frames, n_rows))
+            self.num_frames = n_rows
+
+    def __getitem__(self, key):
+        """See `marker()`.
+
+        """
+        return self.marker(key)
+    
+    def units(self):
+        return self.units
+    
+    def time(self):
+        this_dat = np.empty((self.num_frames, 1))
+        this_dat[:, 0] = self.time
+        return this_dat        
+
+    def marker(self, name):
+        """The trajectory of marker `name`, given as a `self.num_frames` x 3
+        array. The order of the columns is x, y, z.
+
+        """
+        this_dat = np.empty((self.num_frames, 3))
+        this_dat[:, 0] = self.data[name + '_tx']
+        this_dat[:, 1] = self.data[name + '_ty']
+        this_dat[:, 2] = self.data[name + '_tz']
+        return this_dat
+
+    def add_marker(self, name, x, y, z):
+        """Add a marker, with name `name` to the TRCFile.
+
+        Parameters
+        ----------
+        name : str
+            Name of the marker; e.g., 'R.Hip'.
+        x, y, z: array_like
+            Coordinates of the marker trajectory. All 3 must have the same
+            length.
+
+        """
+        if (len(x) != self.num_frames or len(y) != self.num_frames or len(z) !=
+                self.num_frames):
+            raise Exception('Length of data (%i, %i, %i) is not '
+                    'NumFrames (%i).', len(x), len(y), len(z), self.num_frames)
+        self.marker_names += [name]
+        self.num_markers += 1
+        if not hasattr(self, 'data'):
+            self.data = np.array(x, dtype=[('%s_tx' % name, 'float64')])
+            self.data = append_fields(self.data,
+                    ['%s_t%s' % (name, s) for s in 'yz'],
+                    [y, z], usemask=False)
+        else:
+            self.data = append_fields(self.data,
+                    ['%s_t%s' % (name, s) for s in 'xyz'],
+                    [x, y, z], usemask=False)
+
+    def marker_at(self, name, time):
+        x = np.interp(time, self.time, self.data[name + '_tx'])
+        y = np.interp(time, self.time, self.data[name + '_ty'])
+        z = np.interp(time, self.time, self.data[name + '_tz'])
+        return [x, y, z]
+
+    def marker_exists(self, name):
+        """
+        Returns
+        -------
+        exists : bool
+            Is the marker in the TRCFile?
+
+        """
+        return name in self.marker_names
+
+    def write(self, fpath):
+        """Write this TRCFile object to a TRC file.
+
+        Parameters
+        ----------
+        fpath : str
+            Valid file path to which this TRCFile is saved.
+
+        """
+        f = open(fpath, 'w')
+
+        # Line 1.
+        f.write('PathFileType  4\t(X/Y/Z) %s\n' % os.path.split(fpath)[0])
+
+        # Line 2.
+        f.write('DataRate\tCameraRate\tNumFrames\tNumMarkers\t'
+                'Units\tOrigDataRate\tOrigDataStartFrame\tOrigNumFrames\n')
+
+        # Line 3.
+        f.write('%.1f\t%.1f\t%i\t%i\t%s\t%.1f\t%i\t%i\n' % (
+            self.data_rate, self.camera_rate, self.num_frames,
+            self.num_markers, self.units, self.orig_data_rate,
+            self.orig_data_start_frame, self.orig_num_frames))
+
+        # Line 4.
+        f.write('Frame#\tTime\t')
+        for imark in range(self.num_markers):
+            f.write('%s\t\t\t' % self.marker_names[imark])
+        f.write('\n')
+
+        # Line 5.
+        f.write('\t\t')
+        for imark in np.arange(self.num_markers) + 1:
+            f.write('X%i\tY%s\tZ%s\t' % (imark, imark, imark))
+        f.write('\n')
+
+        # Line 6.
+        f.write('\n')
+
+        # Data.
+        for iframe in range(self.num_frames):
+            f.write('%i' % (iframe + 1))
+            f.write('\t%.7f' % self.time[iframe])
+            for mark in self.marker_names:
+                idxs = [mark + '_tx', mark + '_ty', mark + '_tz']
+                f.write('\t%.7f\t%.7f\t%.7f' % tuple(
+                    self.data[coln][iframe] for coln in idxs))
+            f.write('\n')
+
+        f.close()
+
+    def add_noise(self, noise_width):
+        """ add random noise to each component of the marker trajectory
+            The noise mean will be zero, with the noise_width being the
+            standard deviation.
+
+            noise_width : int
+        """
+        for imarker in range(self.num_markers):
+            components = ['_tx', '_ty', '_tz']
+            for iComponent in range(3):
+                # generate noise
+                noise = np.random.normal(0, noise_width, self.num_frames)
+                # add noise to each component of marker data.
+                self.data[self.marker_names[imarker] + components[iComponent]] += noise
+                
+    def rotate(self, axis, value):
+        """ rotate the data.
+
+            axis : rotation axis
+            value : angle in degree
+        """
+        for imarker in range(self.num_markers):   
+            
+            temp = np.zeros((self.num_frames, 3))
+            temp[:,0] = self.data[self.marker_names[imarker] + '_tx']
+            temp[:,1] = self.data[self.marker_names[imarker] + '_ty']
+            temp[:,2] = self.data[self.marker_names[imarker] + '_tz']          
+            
+            r = R.from_euler(axis, value, degrees=True)            
+            temp_rot = r.apply(temp)
+            
+            self.data[self.marker_names[imarker] + '_tx'] = temp_rot[:,0]
+            self.data[self.marker_names[imarker] + '_ty'] = temp_rot[:,1]
+            self.data[self.marker_names[imarker] + '_tz'] = temp_rot[:,2]
+            
+    def offset(self, axis, value):
+        """ offset the data.
+
+            axis : rotation axis
+            value : offset in m
+        """
+        for imarker in range(self.num_markers):            
+            if axis.lower() == 'x':
+                self.data[self.marker_names[imarker] + '_tx'] += value
+            elif axis.lower() == 'y':
+                self.data[self.marker_names[imarker] + '_ty'] += value       
+            elif axis.lower() == 'z':
+                self.data[self.marker_names[imarker] + '_tz'] += value          
+            else:
+                raise ValueError("Axis not recognized")