committing Motion Capture Add-on - Final deliverable for GSoC project 2011

thanks to Benjy Cook
well done!

4 files changed, 2793 insertions, 0 deletions

diff --git a/mocap/__init__.py b/mocap/__init__.py
new file mode 100644
index 00000000..7a8547a9
--- /dev/null
+++ b/mocap/__init__.py
@@ -0,0 +1,886 @@
+# ##### BEGIN GPL LICENSE BLOCK #####
+#
+#  This program is free software; you can redistribute it and/or
+#  modify it under the terms of the GNU General Public License
+#  as published by the Free Software Foundation; either version 2
+#  of the License, or (at your option) any later version.
+#
+#  This program is distributed in the hope that it will be useful,
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#  GNU General Public License for more details.
+#
+#  You should have received a copy of the GNU General Public License
+#  along with this program; if not, write to the Free Software Foundation,
+#  Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
+#
+# ##### END GPL LICENSE BLOCK #####
+
+# <pep8 compliant>
+
+bl_info = {
+    "name": "Motion Capture Tools",
+    "author": "Benjy Cook",
+    "blender": (2, 5, 9),
+    "api": 39523,
+    "location": "Object UI -> Mocap tools",
+    "description": "Various tools for working with motion capture animation",
+    "warning": "",
+    "wiki_url": ("http://wiki.blender.org/index.php/User:Benjycook/GSOC/Manual"),
+    "tracker_url": "",
+    "support": 'OFFICIAL',
+    "category": "Animation"}
+
+if "bpy" in locals():
+    import imp
+    if "mocap_constraints" in locals():
+        imp.reload(mocap_constraints)
+    if "retarget" in locals():
+        imp.reload(retarget)
+    if "mocap_tools" in locals():
+        imp.reload(mocap_tools)
+else:
+    import bpy
+    from bpy.props import *
+    from bpy import *
+    from . import mocap_constraints
+    from . import retarget
+    from . import mocap_tools
+    from .mocap_constraints import *
+
+# MocapConstraint class
+# Defines MocapConstraint datatype, used to add and configute mocap constraints
+# Attached to Armature data
+
+
+class MocapConstraint(bpy.types.PropertyGroup):
+    name = bpy.props.StringProperty(name="Name",
+        default="Mocap Fix",
+        description="Name of Mocap Fix",
+        update=setConstraint)
+    constrained_bone = bpy.props.StringProperty(name="Bone",
+        default="",
+        description="Constrained Bone",
+        update=updateConstraintBoneType)
+    constrained_boneB = bpy.props.StringProperty(name="Bone (2)",
+        default="",
+        description="Other Constrained Bone (optional, depends on type)",
+        update=setConstraint)
+    s_frame = bpy.props.IntProperty(name="S",
+        default=0,
+        description="Start frame of Fix",
+        update=setConstraint)
+    e_frame = bpy.props.IntProperty(name="E",
+        default=100,
+        description="End frame of Fix",
+        update=setConstraint)
+    smooth_in = bpy.props.IntProperty(name="In",
+        default=10,
+        description="Amount of frames to smooth in",
+        update=setConstraint,
+        min=0)
+    smooth_out = bpy.props.IntProperty(name="Out",
+        default=10,
+        description="Amount of frames to smooth out",
+        update=setConstraint,
+        min=0)
+    targetMesh = bpy.props.StringProperty(name="Mesh",
+        default="",
+        description="Target of Fix - Mesh (optional, depends on type)",
+        update=setConstraint)
+    active = bpy.props.BoolProperty(name="Active",
+        default=True,
+        description="Fix is active",
+        update=setConstraint)
+    show_expanded = bpy.props.BoolProperty(name="Show Expanded",
+        default=True,
+        description="Fix is fully shown")
+    targetPoint = bpy.props.FloatVectorProperty(name="Point", size=3,
+        subtype="XYZ", default=(0.0, 0.0, 0.0),
+        description="Target of Fix - Point",
+        update=setConstraint)
+    targetDist = bpy.props.FloatProperty(name="Offset",
+        default=0.0,
+        description="Distance and Floor Fixes - Desired offset",
+        update=setConstraint)
+    targetSpace = bpy.props.EnumProperty(
+        items=[("WORLD", "World Space", "Evaluate target in global space"),
+            ("LOCAL", "Object space", "Evaluate target in object space"),
+            ("constrained_boneB", "Other Bone Space", "Evaluate target in specified other bone space")],
+        name="Space",
+        description="In which space should Point type target be evaluated",
+        update=setConstraint)
+    type = bpy.props.EnumProperty(name="Type of constraint",
+        items=[("point", "Maintain Position", "Bone is at a specific point"),
+            ("freeze", "Maintain Position at frame", "Bone does not move from location specified in target frame"),
+            ("floor", "Stay above", "Bone does not cross specified mesh object eg floor"),
+            ("distance", "Maintain distance", "Target bones maintained specified distance")],
+        description="Type of Fix",
+        update=updateConstraintBoneType)
+    real_constraint = bpy.props.StringProperty()
+    real_constraint_bone = bpy.props.StringProperty()
+
+
+
+# Animation Stitch Settings, used for animation stitching of 2 retargeted animations.
+class AnimationStitchSettings(bpy.types.PropertyGroup):
+    first_action = bpy.props.StringProperty(name="Action 1",
+            description="First action in stitch")
+    second_action = bpy.props.StringProperty(name="Action 2",
+            description="Second action in stitch")
+    blend_frame = bpy.props.IntProperty(name="Stitch frame",
+            description="Frame to locate stitch on")
+    blend_amount = bpy.props.IntProperty(name="Blend amount",
+            description="Size of blending transitiion, on both sides of the stitch",
+            default=10)
+    second_offset = bpy.props.IntProperty(name="Second offset",
+            description="Frame offset for 2nd animation, where it should start",
+            default=10)
+    stick_bone = bpy.props.StringProperty(name="Stick Bone",
+            description="Bone to freeze during transition",
+            default="")
+
+
+
+# MocapNLA Tracks. Stores which tracks/actions are associated with each retargeted animation.
+class MocapNLATracks(bpy.types.PropertyGroup):
+    name = bpy.props.StringProperty()
+    base_track = bpy.props.StringProperty()
+    auto_fix_track = bpy.props.StringProperty()
+    manual_fix_track = bpy.props.StringProperty()
+    stride_action = bpy.props.StringProperty()
+
+
+
+
+#Update function for Advanced Retarget boolean variable.
+def advancedRetargetToggle(self, context):
+    enduser_obj = context.active_object
+    performer_obj = [obj for obj in context.selected_objects if obj != enduser_obj]
+    if enduser_obj is None or len(performer_obj) != 1:
+        print("Need active and selected armatures")
+        return
+    else:
+        performer_obj = performer_obj[0]
+    if self.advancedRetarget:
+        retarget.preAdvancedRetargeting(performer_obj, enduser_obj)
+    else:
+        retarget.cleanTempConstraints(enduser_obj)
+
+
+
+def toggleIKBone(self, context):
+    #Update function for IK functionality. Is called when IK prop checkboxes are toggled.
+    if self.IKRetarget:
+        if not self.is_in_ik_chain:
+            print(self.name + " IK toggled ON!")
+            ik = self.constraints.new('IK')
+            #ik the whole chain up to the root, excluding
+            chainLen = 0
+            for parent_bone in self.parent_recursive:
+                chainLen += 1
+                if hasIKConstraint(parent_bone):
+                    break
+                deformer_children = [child for child in parent_bone.children if child.bone.use_deform]
+                #~ if len(deformer_children) > 1:
+                    #~ break
+            ik.chain_count = chainLen
+            for bone in self.parent_recursive:
+                if bone.is_in_ik_chain:
+                    bone.IKRetarget = True
+    else:
+        print(self.name + " IK toggled OFF!")
+        cnstrn_bones = []
+        newChainLength = []
+        if hasIKConstraint(self):
+            cnstrn_bones = [self]
+        elif self.is_in_ik_chain:
+            cnstrn_bones = [child for child in self.children_recursive if hasIKConstraint(child)]
+            for cnstrn_bone in cnstrn_bones:
+                newChainLength.append(cnstrn_bone.parent_recursive.index(self) + 1)
+        if cnstrn_bones:
+            # remove constraint, and update IK retarget for all parents of cnstrn_bone up to chain_len
+            for i, cnstrn_bone in enumerate(cnstrn_bones):
+                print(cnstrn_bone.name)
+                if newChainLength:
+                    ik = hasIKConstraint(cnstrn_bone)
+                    ik.chain_count = newChainLength[i]
+                else:
+                    ik = hasIKConstraint(cnstrn_bone)
+                    cnstrn_bone.constraints.remove(ik)
+                    cnstrn_bone.IKRetarget = False
+            for bone in cnstrn_bone.parent_recursive:
+                if not bone.is_in_ik_chain:
+                    bone.IKRetarget = False
+
+
+#MocapMap class for storing mapping on enduser performer,
+# where a bone may be linked to more than one on the performer
+class MocapMapping(bpy.types.PropertyGroup):
+    name = bpy.props.StringProperty()
+
+
+
+def updateIKRetarget():
+    # ensures that Blender constraints and IK properties are in sync
+    # currently runs when module is loaded, should run when scene is loaded
+    # or user adds a constraint to armature. Will be corrected in the future,
+    # once python callbacks are implemented
+    for obj in bpy.data.objects:
+        if obj.pose:
+            bones = obj.pose.bones
+            for pose_bone in bones:
+                if pose_bone.is_in_ik_chain or hasIKConstraint(pose_bone):
+                    pose_bone.IKRetarget = True
+                else:
+                    pose_bone.IKRetarget = False
+
+updateIKRetarget()
+
+def hasIKConstraint(pose_bone):
+    #utility function / predicate, returns True if given bone has IK constraint
+    ik = [constraint for constraint in pose_bone.constraints if constraint.type == "IK"]
+    if ik:
+        return ik[0]
+    else:
+        return False
+
+class MocapPanel(bpy.types.Panel):
+    # Motion capture retargeting panel
+    bl_label = "Mocap tools"
+    bl_space_type = "PROPERTIES"
+    bl_region_type = "WINDOW"
+    bl_context = "object"
+
+    def draw(self, context):
+        self.layout.label("Preprocessing")
+        row = self.layout.row(align=True)
+        row.alignment = 'EXPAND'
+        row.operator("mocap.denoise", text='Clean noise')
+        row.operator("mocap.rotate_fix", text='Fix BVH Axis Orientation')
+        row.operator("mocap.scale_fix", text='Auto scale Performer')
+        row2 = self.layout.row(align=True)
+        row2.operator("mocap.looper", text='Loop animation')
+        row2.operator("mocap.limitdof", text='Constrain Rig')
+        row2.operator("mocap.removelimitdof", text='Unconstrain Rig')
+        self.layout.label("Retargeting")
+        enduser_obj = bpy.context.active_object
+        performer_obj = [obj for obj in bpy.context.selected_objects if obj != enduser_obj]
+        if enduser_obj is None or len(performer_obj) != 1:
+            self.layout.label("Select performer rig and target rig (as active)")
+        else:
+            self.layout.operator("mocap.guessmapping", text="Guess Hiearchy Mapping")
+            labelRow = self.layout.row(align=True)
+            labelRow.label("Performer Rig")
+            labelRow.label("End user Rig")
+            performer_obj = performer_obj[0]
+            if performer_obj.data and enduser_obj.data:
+                if performer_obj.data.name in bpy.data.armatures and enduser_obj.data.name in bpy.data.armatures:
+                    perf = performer_obj.data
+                    enduser_arm = enduser_obj.data
+                    perf_pose_bones = enduser_obj.pose.bones
+                    MappingRow = self.layout.row(align=True)
+                    footCol = MappingRow.column(align=True)
+                    nameCol =MappingRow.column(align=True)
+                    nameCol.scale_x = 2
+                    mapCol = MappingRow.column(align=True)
+                    mapCol.scale_x = 2
+                    selectCol = MappingRow.column(align=True)
+                    twistCol = MappingRow.column(align=True)
+                    twistCol.scale_x = 0.1
+                    IKCol = MappingRow.column(align=True)
+                    IKCol.scale_x = 0.3
+                    IKLabel = MappingRow.column(align=True)
+                    IKLabel.scale_x = 0.2
+                    for bone in perf.bones:
+                        footCol.prop(data=bone, property='foot', text='', icon='POSE_DATA')
+                        nameCol.label(bone.name)
+                        mapCol.prop_search(bone, "map", enduser_arm, "bones")
+                        selectCol.operator("mocap.selectmap", text='', icon='CURSOR').perf_bone = bone.name
+                        label_mod = "FK"
+                        if bone.map:
+                            pose_bone = perf_pose_bones[bone.map]
+                            if pose_bone.is_in_ik_chain:
+                                label_mod = "ik chain"
+                            if hasIKConstraint(pose_bone):
+                                label_mod = "ik end"
+                            end_bone = enduser_obj.data.bones[bone.map]
+                            twistCol.prop(data=end_bone, property='twistFix', text='', icon='RNA')
+                            IKCol.prop(pose_bone, 'IKRetarget')
+                            IKLabel.label(label_mod)
+                        else:
+                            twistCol.label(" ")
+                            IKCol.label(" ")
+                            IKLabel.label(" ")
+                    mapRow = self.layout.row()
+                    mapRow.operator("mocap.savemapping", text='Save mapping')
+                    mapRow.operator("mocap.loadmapping", text='Load mapping')
+                    extraSettings = self.layout.box()
+                    if performer_obj.animation_data:
+                        extraSettings.prop(data=performer_obj.animation_data.action, property='name', text='Action Name')
+                    extraSettings.prop(enduser_arm, "frameStep")
+                    extraSettings.prop(enduser_arm, "advancedRetarget", text='Advanced Retarget')
+                    self.layout.operator("mocap.retarget", text='RETARGET!')
+
+
+class MocapConstraintsPanel(bpy.types.Panel):
+    #Motion capture constraints panel
+    bl_label = "Mocap Fixes"
+    bl_space_type = "PROPERTIES"
+    bl_region_type = "WINDOW"
+    bl_context = "object"
+
+    def draw(self, context):
+        layout = self.layout
+        if context.active_object:
+            if context.active_object.data:
+                if context.active_object.data.name in bpy.data.armatures:
+                    enduser_obj = context.active_object
+                    enduser_arm = enduser_obj.data
+                    layout.operator_menu_enum("mocap.addmocapfix", "type")
+                    layout.operator("mocap.updateconstraints", text='Update Fixes')
+                    bakeRow = layout.row()
+                    bakeRow.operator("mocap.bakeconstraints", text='Bake Fixes')
+                    bakeRow.operator("mocap.unbakeconstraints", text='Unbake Fixes')
+                    layout.separator()
+                    for i, m_constraint in enumerate(enduser_arm.mocap_constraints):
+                        box = layout.box()
+                        headerRow = box.row()
+                        headerRow.prop(m_constraint, 'show_expanded', text='', icon='TRIA_DOWN' if m_constraint.show_expanded else 'TRIA_RIGHT', emboss=False)
+                        headerRow.prop(m_constraint, 'type', text='')
+                        headerRow.prop(m_constraint, 'name', text='')
+                        headerRow.prop(m_constraint, 'active', icon='MUTE_IPO_ON' if not m_constraint.active else'MUTE_IPO_OFF', text='', emboss=False)
+                        headerRow.operator("mocap.removeconstraint", text="", icon='X', emboss=False).constraint = i
+                        if m_constraint.show_expanded:
+                            box.separator()
+                            box.prop_search(m_constraint, 'constrained_bone', enduser_obj.pose, "bones", icon='BONE_DATA')
+                            if m_constraint.type == "distance" or m_constraint.type == "point":
+                                box.prop_search(m_constraint, 'constrained_boneB', enduser_obj.pose, "bones", icon='CONSTRAINT_BONE')
+                            frameRow = box.row()
+                            frameRow.label("Frame Range:")
+                            frameRow.prop(m_constraint, 's_frame')
+                            frameRow.prop(m_constraint, 'e_frame')
+                            smoothRow = box.row()
+                            smoothRow.label("Smoothing:")
+                            smoothRow.prop(m_constraint, 'smooth_in')
+                            smoothRow.prop(m_constraint, 'smooth_out')
+                            targetRow = box.row()
+                            targetLabelCol = targetRow.column()
+                            targetLabelCol.label("Target settings:")
+                            targetPropCol = targetRow.column()
+                            if m_constraint.type == "floor":
+                                targetPropCol.prop_search(m_constraint, 'targetMesh', bpy.data, "objects")
+                            if m_constraint.type == "point" or m_constraint.type == "freeze":
+                                box.prop(m_constraint, 'targetSpace')
+                            if m_constraint.type == "point":
+                                targetPropCol.prop(m_constraint, 'targetPoint')
+                            if m_constraint.type == "distance" or m_constraint.type == "floor":
+                                targetPropCol.prop(m_constraint, 'targetDist')
+                            layout.separator()
+
+
+class ExtraToolsPanel(bpy.types.Panel):
+    # Motion capture retargeting panel
+    bl_label = "Extra Mocap Tools"
+    bl_space_type = "PROPERTIES"
+    bl_region_type = "WINDOW"
+    bl_context = "object"
+
+    def draw(self, context):
+        layout = self.layout
+        layout.operator("mocap.samples", text='Samples to Beziers')
+        layout.operator('mocap.pathediting', text="Follow Path")
+        activeIsArmature = isinstance(context.active_object.data, bpy.types.Armature)
+        if activeIsArmature:
+            enduser_arm = context.active_object.data
+            selectBox = layout.box()
+            selectRetargets = selectBox.row()
+            selectRetargets.label("Retargeted Animations:")
+            selectRetargets.prop_search(enduser_arm, "active_mocap", enduser_arm, "mocapNLATracks")
+            stitchBox = layout.box()
+            stitchBox.label("Animation Stitching")
+            settings = enduser_arm.stitch_settings
+            stitchBox.prop_search(settings, "first_action", enduser_arm, "mocapNLATracks")
+            stitchBox.prop_search(settings, "second_action", enduser_arm, "mocapNLATracks")
+            stitchSettings = stitchBox.row()
+            stitchSettings.prop(settings, "blend_frame")
+            stitchSettings.prop(settings, "blend_amount")
+            stitchSettings.prop(settings, "second_offset")
+            stitchBox.prop_search(settings, "stick_bone", context.active_object.pose, "bones")
+            stitchBox.operator('mocap.animstitchguess', text="Guess Settings")
+            stitchBox.operator('mocap.animstitch', text="Stitch Animations")
+
+
+class OBJECT_OT_RetargetButton(bpy.types.Operator):
+    #Retargeting operator. Assumes selected and active armatures, where the performer (the selected one)
+    # has an action for retargeting
+    '''Retarget animation from selected armature to active armature '''
+    bl_idname = "mocap.retarget"
+    bl_label = "Retargets active action from Performer to Enduser"
+    bl_options = {'REGISTER', 'UNDO'}
+
+    def execute(self, context):
+        scene = context.scene
+        s_frame = scene.frame_start
+        e_frame = scene.frame_end
+        enduser_obj = context.active_object
+        performer_obj = [obj for obj in context.selected_objects if obj != enduser_obj]
+        if enduser_obj is None or len(performer_obj) != 1:
+            print("Need active and selected armatures")
+        else:
+            performer_obj = performer_obj[0]
+            s_frame, e_frame = performer_obj.animation_data.action.frame_range
+            s_frame = int(s_frame)
+            e_frame = int(e_frame)
+        if retarget.isRigAdvanced(enduser_obj) and not enduser_obj.data.advancedRetarget:
+            print("Recommended to use Advanced Retargeting method")
+            enduser_obj.data.advancedRetarget = True
+        else:
+            retarget.totalRetarget(performer_obj, enduser_obj, scene, s_frame, e_frame)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        if context.active_object:
+            activeIsArmature = isinstance(context.active_object.data, bpy.types.Armature)
+        performer_obj = [obj for obj in context.selected_objects if obj != context.active_object]
+        if performer_obj:
+            return activeIsArmature and isinstance(performer_obj[0].data, bpy.types.Armature) and performer_obj[0].animation_data
+        else:
+            return False
+
+
+class OBJECT_OT_SaveMappingButton(bpy.types.Operator):
+    #Operator for saving mapping to enduser armature
+    '''Save mapping to active armature (for future retargets) '''
+    bl_idname = "mocap.savemapping"
+    bl_label = "Saves user generated mapping from Performer to Enduser"
+
+    def execute(self, context):
+        enduser_obj = bpy.context.active_object
+        performer_obj = [obj for obj in bpy.context.selected_objects if obj != enduser_obj][0]
+        retarget.createDictionary(performer_obj.data, enduser_obj.data)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        if context.active_object:
+            activeIsArmature = isinstance(context.active_object.data, bpy.types.Armature)
+        performer_obj = [obj for obj in context.selected_objects if obj != context.active_object]
+        if performer_obj:
+            return activeIsArmature and isinstance(performer_obj[0].data, bpy.types.Armature)
+        else:
+            return False
+
+
+class OBJECT_OT_LoadMappingButton(bpy.types.Operator):
+    '''Load saved mapping from active armature'''
+    #Operator for loading mapping to enduser armature
+    bl_idname = "mocap.loadmapping"
+    bl_label = "Loads user generated mapping from Performer to Enduser"
+
+    def execute(self, context):
+        enduser_obj = bpy.context.active_object
+        performer_obj = [obj for obj in bpy.context.selected_objects if obj != enduser_obj][0]
+        retarget.loadMapping(performer_obj.data, enduser_obj.data)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        if context.active_object:
+            activeIsArmature = isinstance(context.active_object.data, bpy.types.Armature)
+        performer_obj = [obj for obj in context.selected_objects if obj != context.active_object]
+        if performer_obj:
+            return activeIsArmature and isinstance(performer_obj[0].data, bpy.types.Armature)
+        else:
+            return False
+
+
+class OBJECT_OT_SelectMapBoneButton(bpy.types.Operator):
+    #Operator for setting selected bone in enduser armature to the performer mapping
+    '''Select a bone for faster mapping'''
+    bl_idname = "mocap.selectmap"
+    bl_label = "Select a bone for faster mapping"
+    perf_bone = bpy.props.StringProperty()
+
+    def execute(self, context):
+        enduser_obj = bpy.context.active_object
+        performer_obj = [obj for obj in bpy.context.selected_objects if obj != enduser_obj][0]
+        selectedBone = ""
+        for bone in enduser_obj.data.bones:
+            boneVis = bone.layers
+            for i in range(32):
+                if boneVis[i] and enduser_obj.data.layers[i]:
+                    if bone.select:
+                        selectedBone = bone.name
+                        break
+        performer_obj.data.bones[self.perf_bone].map = selectedBone
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        if context.active_object:
+            activeIsArmature = isinstance(context.active_object.data, bpy.types.Armature)
+        performer_obj = [obj for obj in context.selected_objects if obj != context.active_object]
+        if performer_obj:
+            return activeIsArmature and isinstance(performer_obj[0].data, bpy.types.Armature)
+        else:
+            return False
+
+
+class OBJECT_OT_ConvertSamplesButton(bpy.types.Operator):
+    #Operator to convert samples to beziers on the selected object
+    '''Convert active armature's sampled keyframed to beziers'''
+    bl_idname = "mocap.samples"
+    bl_label = "Converts samples / simplifies keyframes to beziers"
+
+    def execute(self, context):
+        mocap_tools.fcurves_simplify(context, context.active_object)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        return context.active_object.animation_data
+
+
+class OBJECT_OT_LooperButton(bpy.types.Operator):
+    #Operator to trim fcurves which contain a few loops to a single one on the selected object
+    '''Trim active armature's animation to a single cycle, given a cyclic animation (such as a walk cycle)'''
+    bl_idname = "mocap.looper"
+    bl_label = "loops animation / sampled mocap data"
+
+    def execute(self, context):
+        mocap_tools.autoloop_anim()
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        return context.active_object.animation_data
+
+
+class OBJECT_OT_DenoiseButton(bpy.types.Operator):
+    #Operator to denoise impluse noise on the active object's fcurves
+    '''Denoise active armature's animation. Good for dealing with 'bad' frames inherent in mocap animation'''
+    bl_idname = "mocap.denoise"
+    bl_label = "Denoises sampled mocap data "
+
+    def execute(self, context):
+        mocap_tools.denoise_median()
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        return context.active_object
+
+    @classmethod
+    def poll(cls, context):
+        return context.active_object.animation_data
+
+
+class OBJECT_OT_LimitDOFButton(bpy.types.Operator):
+    #Operator to analyze performer armature and apply rotation constraints on the enduser armature
+    '''Create limit constraints on the active armature from the selected armature's animation's range of motion'''
+    bl_idname = "mocap.limitdof"
+    bl_label = "Analyzes animations Max/Min DOF and adds hard/soft constraints"
+
+    def execute(self, context):
+        performer_obj = [obj for obj in context.selected_objects if obj != context.active_object][0]
+        mocap_tools.limit_dof(context, performer_obj, context.active_object)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        if context.active_object:
+            activeIsArmature = isinstance(context.active_object.data, bpy.types.Armature)
+        performer_obj = [obj for obj in context.selected_objects if obj != context.active_object]
+        if performer_obj:
+            return activeIsArmature and isinstance(performer_obj[0].data, bpy.types.Armature)
+        else:
+            return False
+
+
+class OBJECT_OT_RemoveLimitDOFButton(bpy.types.Operator):
+    #Removes constraints created by above operator
+    '''Removes previously created limit constraints on the active armature'''
+    bl_idname = "mocap.removelimitdof"
+    bl_label = "Removes previously created limit constraints on the active armature"
+
+    def execute(self, context):
+        mocap_tools.limit_dof_toggle_off(context, context.active_object)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        activeIsArmature = False
+        if context.active_object:
+            activeIsArmature = isinstance(context.active_object.data, bpy.types.Armature)
+        return activeIsArmature
+
+
+class OBJECT_OT_RotateFixArmature(bpy.types.Operator):
+    #Operator to fix common imported Mocap data issue of wrong axis system on active object
+    '''Realign the active armature's axis system to match Blender (Commonly needed after bvh import)'''
+    bl_idname = "mocap.rotate_fix"
+    bl_label = "Rotates selected armature 90 degrees (fix for bvh import)"
+
+    def execute(self, context):
+        mocap_tools.rotate_fix_armature(context.active_object.data)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        if context.active_object:
+            return isinstance(context.active_object.data, bpy.types.Armature)
+
+
+class OBJECT_OT_ScaleFixArmature(bpy.types.Operator):
+    #Operator to scale down the selected armature to match the active one
+    '''Rescale selected armature to match the active animation, for convienence'''
+    bl_idname = "mocap.scale_fix"
+    bl_label = "Scales performer armature to match target armature"
+
+    def execute(self, context):
+        enduser_obj = bpy.context.active_object
+        performer_obj = [obj for obj in bpy.context.selected_objects if obj != enduser_obj][0]
+        mocap_tools.scale_fix_armature(performer_obj, enduser_obj)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        if context.active_object:
+            activeIsArmature = isinstance(context.active_object.data, bpy.types.Armature)
+        performer_obj = [obj for obj in context.selected_objects if obj != context.active_object]
+        if performer_obj:
+            return activeIsArmature and isinstance(performer_obj[0].data, bpy.types.Armature)
+        else:
+            return False
+
+
+class MOCAP_OT_AddMocapFix(bpy.types.Operator):
+    #Operator to add a post-retarget fix
+    '''Add a post-retarget fix - useful for fixing certain artifacts following the retarget'''
+    bl_idname = "mocap.addmocapfix"
+    bl_label = "Add Mocap Fix to target armature"
+    type = bpy.props.EnumProperty(name="Type of Fix",
+    items=[("point", "Maintain Position", "Bone is at a specific point"),
+        ("freeze", "Maintain Position at frame", "Bone does not move from location specified in target frame"),
+        ("floor", "Stay above", "Bone does not cross specified mesh object eg floor"),
+        ("distance", "Maintain distance", "Target bones maintained specified distance")],
+    description="Type of fix")
+
+    def execute(self, context):
+        enduser_obj = bpy.context.active_object
+        enduser_arm = enduser_obj.data
+        new_mcon = enduser_arm.mocap_constraints.add()
+        new_mcon.type = self.type
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        if context.active_object:
+            return isinstance(context.active_object.data, bpy.types.Armature)
+
+
+class OBJECT_OT_RemoveMocapConstraint(bpy.types.Operator):
+    #Operator to remove a post-retarget fix
+    '''Remove this post-retarget fix'''
+    bl_idname = "mocap.removeconstraint"
+    bl_label = "Removes fixes from target armature"
+    constraint = bpy.props.IntProperty()
+
+    def execute(self, context):
+        enduser_obj = bpy.context.active_object
+        enduser_arm = enduser_obj.data
+        m_constraints = enduser_arm.mocap_constraints
+        m_constraint = m_constraints[self.constraint]
+        if m_constraint.real_constraint:
+            bone = enduser_obj.pose.bones[m_constraint.real_constraint_bone]
+            cons_obj = getConsObj(bone)
+            removeConstraint(m_constraint, cons_obj)
+        m_constraints.remove(self.constraint)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        if context.active_object:
+            return isinstance(context.active_object.data, bpy.types.Armature)
+
+
+class OBJECT_OT_BakeMocapConstraints(bpy.types.Operator):
+    #Operator to bake all post-retarget fixes
+    '''Bake all post-retarget fixes to the Retarget Fixes NLA Track'''
+    bl_idname = "mocap.bakeconstraints"
+    bl_label = "Bake all fixes to target armature"
+
+    def execute(self, context):
+        bakeConstraints(context)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        if context.active_object:
+            return isinstance(context.active_object.data, bpy.types.Armature)
+
+
+class OBJECT_OT_UnbakeMocapConstraints(bpy.types.Operator):
+    #Operator to unbake all post-retarget fixes
+    '''Unbake all post-retarget fixes - removes the baked data from the Retarget Fixes NLA Track'''
+    bl_idname = "mocap.unbakeconstraints"
+    bl_label = "Unbake all fixes to target armature"
+
+    def execute(self, context):
+        unbakeConstraints(context)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        if context.active_object:
+            return isinstance(context.active_object.data, bpy.types.Armature)
+
+
+class OBJECT_OT_UpdateMocapConstraints(bpy.types.Operator):
+    #Operator to update all post-retarget fixes, similar to update dependencies on drivers
+    #Needed because python properties lack certain callbacks and some fixes take a while to recalculate.
+    '''Updates all post-retarget fixes - needed after changes to armature object or pose'''
+    bl_idname = "mocap.updateconstraints"
+    bl_label = "Updates all fixes to target armature - neccesary to take under consideration changes to armature object or pose"
+
+    def execute(self, context):
+        updateConstraints(context.active_object, context)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        if context.active_object:
+            return isinstance(context.active_object.data, bpy.types.Armature)
+
+
+class OBJECT_OT_GuessHierachyMapping(bpy.types.Operator):
+    #Operator which calls heurisitic function to guess mapping between 2 armatures
+    '''Attemps to auto figure out hierarchy mapping'''
+    bl_idname = "mocap.guessmapping"
+    bl_label = "Attemps to auto figure out hierarchy mapping"
+
+    def execute(self, context):
+        enduser_obj = bpy.context.active_object
+        performer_obj = [obj for obj in bpy.context.selected_objects if obj != enduser_obj][0]
+        mocap_tools.guessMapping(performer_obj, enduser_obj)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        if context.active_object:
+            activeIsArmature = isinstance(context.active_object.data, bpy.types.Armature)
+        performer_obj = [obj for obj in context.selected_objects if obj != context.active_object]
+        if performer_obj:
+            return activeIsArmature and isinstance(performer_obj[0].data, bpy.types.Armature)
+        else:
+            return False
+
+
+class OBJECT_OT_PathEditing(bpy.types.Operator):
+    #Operator which calls path editing function, making active object follow the selected curve.
+    '''Sets active object (stride object) to follow the selected curve'''
+    bl_idname = "mocap.pathediting"
+    bl_label = "Sets active object (stride object) to follow the selected curve"
+
+    def execute(self, context):
+        path = [obj for obj in context.selected_objects if obj != context.active_object][0]
+        mocap_tools.path_editing(context, context.active_object, path)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        if context.active_object:
+            selected_objs = [obj for obj in context.selected_objects if obj != context.active_object and isinstance(obj.data, bpy.types.Curve)]
+            return selected_objs
+        else:
+            return False
+
+
+class OBJECT_OT_AnimationStitchingButton(bpy.types.Operator):
+    #Operator which calls stitching function, combining 2 animations onto the NLA.
+    '''Stitches two defined animations into a single one via alignment of NLA Tracks'''
+    bl_idname = "mocap.animstitch"
+    bl_label = "Stitches two defined animations into a single one via alignment of NLA Tracks"
+
+    def execute(self, context):
+        mocap_tools.anim_stitch(context, context.active_object)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        activeIsArmature = False
+        if context.active_object:
+            activeIsArmature = isinstance(context.active_object.data, bpy.types.Armature)
+            if activeIsArmature:
+                stitch_settings = context.active_object.data.stitch_settings
+                return (stitch_settings.first_action and stitch_settings.second_action)
+        return False
+
+
+class OBJECT_OT_GuessAnimationStitchingButton(bpy.types.Operator):
+    #Operator which calls stitching function heuristic, setting good values for above operator.
+    '''Guesses the stitch frame and second offset for animation stitch'''
+    bl_idname = "mocap.animstitchguess"
+    bl_label = "Guesses the stitch frame and second offset for animation stitch"
+
+    def execute(self, context):
+        mocap_tools.guess_anim_stitch(context, context.active_object)
+        return {"FINISHED"}
+
+    @classmethod
+    def poll(cls, context):
+        activeIsArmature = False
+        if context.active_object:
+            activeIsArmature = isinstance(context.active_object.data, bpy.types.Armature)
+            if activeIsArmature:
+                stitch_settings = context.active_object.data.stitch_settings
+                return (stitch_settings.first_action and stitch_settings.second_action)
+        return False
+
+
+def register():
+    bpy.utils.register_class(MocapConstraint)
+    bpy.types.Armature.mocap_constraints = bpy.props.CollectionProperty(type=MocapConstraint)
+    bpy.utils.register_class(MocapMapping)
+    #string property for storing performer->enduser mapping
+    bpy.types.Bone.map = bpy.props.StringProperty()
+    #Collection Property for storing enduser->performer mapping
+    bpy.types.Bone.reverseMap = bpy.props.CollectionProperty(type=MocapMapping)
+    #Boolean property for storing foot bone toggle
+    bpy.types.Bone.foot = bpy.props.BoolProperty(name="Foot",
+        description="Marks this bone as a 'foot', which determines retargeted animation's translation",
+        default=False)
+    #Boolean property for storing if this bone is twisted along the y axis,
+    # which can happen due to various sources of performers
+    bpy.types.Bone.twistFix = bpy.props.BoolProperty(name="Twist Fix",
+        description="Fix Twist on this bone",
+        default=False)
+    #Boolean property for toggling ik retargeting for this bone
+    bpy.types.PoseBone.IKRetarget = bpy.props.BoolProperty(name="IK",
+        description="Toggles IK Retargeting method for given bone",
+        update=toggleIKBone, default=False)
+    bpy.utils.register_class(AnimationStitchSettings)
+    bpy.utils.register_class(MocapNLATracks)
+    #Animation Stitch Settings Property
+    bpy.types.Armature.stitch_settings = bpy.props.PointerProperty(type=AnimationStitchSettings)
+    #Current/Active retargeted animation on the armature
+    bpy.types.Armature.active_mocap = bpy.props.StringProperty(update=retarget.NLASystemInitialize)
+    #Collection of retargeted animations and their NLA Tracks on the armature
+    bpy.types.Armature.mocapNLATracks = bpy.props.CollectionProperty(type=MocapNLATracks)
+    #Advanced retargeting boolean property
+    bpy.types.Armature.advancedRetarget = bpy.props.BoolProperty(default=False, update=advancedRetargetToggle)
+    #frame step - frequency of frames to retarget. Skipping is useful for previewing, faster work etc.
+    bpy.types.Armature.frameStep = smooth_out = bpy.props.IntProperty(name="Frame Skip",
+            default=1,
+            description="Amount of frames to skip - for previewing retargets quickly. 1 is fully sampled",
+            min=1)
+    bpy.utils.register_module(__name__)
+    
+    
+def unregister():
+    bpy.utils.unregister_module(__name__)
+
+if __name__ == "__main__":
+    register()
diff --git a/mocap/mocap_constraints.py b/mocap/mocap_constraints.py
new file mode 100644
index 00000000..5e349454
--- /dev/null
+++ b/mocap/mocap_constraints.py
@@ -0,0 +1,442 @@
+# ##### BEGIN GPL LICENSE BLOCK #####
+#
+#  This program is free software; you can redistribute it and/or
+#  modify it under the terms of the GNU General Public License
+#  as published by the Free Software Foundation; either version 2
+#  of the License, or (at your option) any later version.
+#
+#  This program is distributed in the hope that it will be useful,
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#  GNU General Public License for more details.
+#
+#  You should have received a copy of the GNU General Public License
+#  along with this program; if not, write to the Free Software Foundation,
+#  Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
+#
+# ##### END GPL LICENSE BLOCK #####
+
+# <pep8 compliant>
+
+import bpy
+from mathutils import *
+from bl_operators import nla
+from .  import retarget
+
+
+### Utility Functions
+
+
+def getConsObj(bone):
+    #utility function - returns related IK target if bone has IK
+    ik = [constraint for constraint in bone.constraints if constraint.type == "IK"]
+    if ik:
+        ik = ik[0]
+        cons_obj = ik.target
+        if ik.subtarget:
+            cons_obj = ik.target.pose.bones[ik.subtarget]
+    else:
+        cons_obj = bone
+    return cons_obj
+
+
+def consObjToBone(cons_obj):
+    #Utility function - returns related bone from ik object
+    if cons_obj.name[-3:] == "Org":
+        return cons_obj.name[:-3]
+    else:
+        return cons_obj.name
+
+### And and Remove Constraints (called from operators)
+
+
+def addNewConstraint(m_constraint, cons_obj):
+     #Decide the correct Blender constraint according to the Mocap constraint type
+    if m_constraint.type == "point" or m_constraint.type == "freeze":
+        c_type = "LIMIT_LOCATION"
+    if m_constraint.type == "distance":
+        c_type = "LIMIT_DISTANCE"
+    if m_constraint.type == "floor":
+        c_type = "LIMIT_LOCATION"
+        #create and store the new constraint within m_constraint
+    real_constraint = cons_obj.constraints.new(c_type)
+    real_constraint.name = "Auto fixes " + str(len(cons_obj.constraints))
+    m_constraint.real_constraint_bone = consObjToBone(cons_obj)
+    m_constraint.real_constraint = real_constraint.name
+    #set the rest of the constraint properties
+    setConstraint(m_constraint, bpy.context)
+
+
+def removeConstraint(m_constraint, cons_obj):
+    #remove the influence fcurve and Blender constraint
+    oldConstraint = cons_obj.constraints[m_constraint.real_constraint]
+    removeFcurves(cons_obj, bpy.context.active_object, oldConstraint, m_constraint)
+    cons_obj.constraints.remove(oldConstraint)
+
+### Update functions. There are 3: UpdateType/Bone
+### update framing (deals with changes in the desired frame range)
+### And setConstraint which deals with the rest
+
+
+def updateConstraintBoneType(m_constraint, context):
+    #If the constraint exists, we need to remove it
+    #from the old bone
+    obj = context.active_object
+    bones = obj.pose.bones
+    if m_constraint.real_constraint:
+        bone = bones[m_constraint.real_constraint_bone]
+        cons_obj = getConsObj(bone)
+        removeConstraint(m_constraint, cons_obj)
+    #Regardless, after that we create a new constraint
+    if m_constraint.constrained_bone:
+        bone = bones[m_constraint.constrained_bone]
+        cons_obj = getConsObj(bone)
+        addNewConstraint(m_constraint, cons_obj)
+
+
+def setConstraintFraming(m_constraint, context):
+    obj = context.active_object
+    bones = obj.pose.bones
+    bone = bones[m_constraint.constrained_bone]
+    cons_obj = getConsObj(bone)
+    real_constraint = cons_obj.constraints[m_constraint.real_constraint]
+    #remove the old keyframes
+    removeFcurves(cons_obj, obj, real_constraint, m_constraint)
+    #set the new ones according to the m_constraint properties
+    s, e = m_constraint.s_frame, m_constraint.e_frame
+    s_in, s_out = m_constraint.smooth_in, m_constraint.smooth_out
+    real_constraint.influence = 1
+    real_constraint.keyframe_insert(data_path="influence", frame=s)
+    real_constraint.keyframe_insert(data_path="influence", frame=e)
+    real_constraint.influence = 0
+    real_constraint.keyframe_insert(data_path="influence", frame=s - s_in)
+    real_constraint.keyframe_insert(data_path="influence", frame=e + s_out)
+
+
+def removeFcurves(cons_obj, obj, real_constraint, m_constraint):
+    #Determine if the constrained object is a bone or an empty
+    if isinstance(cons_obj, bpy.types.PoseBone):
+        fcurves = obj.animation_data.action.fcurves
+    else:
+        fcurves = cons_obj.animation_data.action.fcurves
+    #Find the RNA data path of the constraint's influence
+    RNA_paths = []
+    RNA_paths.append(real_constraint.path_from_id("influence"))
+    if m_constraint.type == "floor" or m_constraint.type == "point":
+        RNA_paths += [real_constraint.path_from_id("max_x"), real_constraint.path_from_id("min_x")]
+        RNA_paths += [real_constraint.path_from_id("max_y"), real_constraint.path_from_id("min_y")]
+        RNA_paths += [real_constraint.path_from_id("max_z"), real_constraint.path_from_id("min_z")]
+    #Retrieve the correct fcurve via the RNA data path and remove it
+    fcurves_del = [fcurve for fcurve in fcurves if fcurve.data_path in RNA_paths]
+    #clear the fcurve and set the frames.
+    if fcurves_del:
+        for fcurve in fcurves_del:
+            fcurves.remove(fcurve)
+    #remove armature fcurves (if user keyframed m_constraint properties)
+    if obj.data.animation_data and m_constraint.type == "point":
+        if obj.data.animation_data.action:
+            path = m_constraint.path_from_id("targetPoint")
+            m_fcurves = [fcurve for fcurve in obj.data.animation_data.action.fcurves if fcurve.data_path == path]
+            for curve in m_fcurves:
+                obj.data.animation_data.action.fcurves.remove(curve)
+
+#Utility function for copying property fcurves over
+
+
+def copyFCurve(newCurve, oldCurve):
+    for point in oldCurve.keyframe_points:
+        newCurve.keyframe_points.insert(frame=point.co.x, value=point.co.y)
+
+#Creates new fcurves for the constraint properties (for floor and point)
+
+
+def createConstraintFCurves(cons_obj, obj, real_constraint):
+    if isinstance(cons_obj, bpy.types.PoseBone):
+        c_fcurves = obj.animation_data.action.fcurves
+    else:
+        c_fcurves = cons_obj.animation_data.action.fcurves
+    c_x_path = [real_constraint.path_from_id("max_x"), real_constraint.path_from_id("min_x")]
+    c_y_path = [real_constraint.path_from_id("max_y"), real_constraint.path_from_id("min_y")]
+    c_z_path = [real_constraint.path_from_id("max_z"), real_constraint.path_from_id("min_z")]
+    c_constraints_path = c_x_path + c_y_path + c_z_path
+    existing_curves = [fcurve for fcurve in c_fcurves if fcurve.data_path in c_constraints_path]
+    if existing_curves:
+        for curve in existing_curves:
+            c_fcurves.remove(curve)
+    xCurves, yCurves, zCurves = [], [], []
+    for path in c_constraints_path:
+        newCurve = c_fcurves.new(path)
+        if path in c_x_path:
+            xCurves.append(newCurve)
+        elif path in c_y_path:
+            yCurves.append(newCurve)
+        else:
+            zCurves.append(newCurve)
+    return xCurves, yCurves, zCurves
+
+
+# Function that copies all settings from m_constraint to the real Blender constraints
+# Is only called when blender constraint already exists
+
+
+def setConstraint(m_constraint, context):
+    if not m_constraint.constrained_bone:
+        return
+    obj = context.active_object
+    bones = obj.pose.bones
+    bone = bones[m_constraint.constrained_bone]
+    cons_obj = getConsObj(bone)
+    real_constraint = cons_obj.constraints[m_constraint.real_constraint]
+    NLATracks = obj.data.mocapNLATracks[obj.data.active_mocap]
+    obj.animation_data.action = bpy.data.actions[NLATracks.auto_fix_track]
+
+    #frame changing section
+    setConstraintFraming(m_constraint, context)
+    s, e = m_constraint.s_frame, m_constraint.e_frame
+    s_in, s_out = m_constraint.smooth_in, m_constraint.smooth_out
+    s -= s_in
+    e += s_out
+    #Set the blender constraint parameters
+    if m_constraint.type == "point":
+        constraint_settings = False  # are fix settings keyframed?
+        if not m_constraint.targetSpace == "constrained_boneB":
+            real_constraint.owner_space = m_constraint.targetSpace
+        else:
+            real_constraint.owner_space = "LOCAL"
+        if obj.data.animation_data:
+            if obj.data.animation_data.action:
+                path = m_constraint.path_from_id("targetPoint")
+                m_fcurves = [fcurve for fcurve in obj.data.animation_data.action.fcurves if fcurve.data_path == path]
+                if m_fcurves:
+                    constraint_settings = True
+                    xCurves, yCurves, zCurves = createConstraintFCurves(cons_obj, obj, real_constraint)
+                    for curve in xCurves:
+                        copyFCurve(curve, m_fcurves[0])
+                    for curve in yCurves:
+                        copyFCurve(curve, m_fcurves[1])
+                    for curve in zCurves:
+                        copyFCurve(curve, m_fcurves[2])
+        if m_constraint.targetSpace == "constrained_boneB" and m_constraint.constrained_boneB:
+            c_frame = context.scene.frame_current
+            bakedPos = {}
+            src_bone = bones[m_constraint.constrained_boneB]
+            if not constraint_settings:
+                xCurves, yCurves, zCurves = createConstraintFCurves(cons_obj, obj, real_constraint)
+            print("please wait a moment, calculating fix")
+            for t in range(s, e):
+                context.scene.frame_set(t)
+                src_bone_pos = src_bone.matrix.to_translation()
+                bakedPos[t] = src_bone_pos + m_constraint.targetPoint  # final position for constrained bone in object space
+            context.scene.frame_set(c_frame)
+            for frame in bakedPos.keys():
+                pos = bakedPos[frame]
+                for xCurve in xCurves:
+                    xCurve.keyframe_points.insert(frame=frame, value=pos.x)
+                for yCurve in yCurves:
+                    yCurve.keyframe_points.insert(frame=frame, value=pos.y)
+                for zCurve in zCurves:
+                    zCurve.keyframe_points.insert(frame=frame, value=pos.z)
+
+        if not constraint_settings:
+            x, y, z = m_constraint.targetPoint
+            real_constraint.max_x = x
+            real_constraint.max_y = y
+            real_constraint.max_z = z
+            real_constraint.min_x = x
+            real_constraint.min_y = y
+            real_constraint.min_z = z
+            real_constraint.use_max_x = True
+            real_constraint.use_max_y = True
+            real_constraint.use_max_z = True
+            real_constraint.use_min_x = True
+            real_constraint.use_min_y = True
+            real_constraint.use_min_z = True
+
+    if m_constraint.type == "freeze":
+        context.scene.frame_set(s)
+        real_constraint.owner_space = m_constraint.targetSpace
+        bpy.context.scene.frame_set(m_constraint.s_frame)
+        if isinstance(cons_obj, bpy.types.PoseBone):
+            vec = obj.matrix_world * (cons_obj.matrix.to_translation())
+            #~ if obj.parent:
+                #~ vec = obj.parent.matrix_world * vec
+            x, y, z = vec
+        else:
+            x, y, z = cons_obj.matrix_world.to_translation()
+
+        real_constraint.max_x = x
+        real_constraint.max_y = y
+        real_constraint.max_z = z
+        real_constraint.min_x = x
+        real_constraint.min_y = y
+        real_constraint.min_z = z
+        real_constraint.use_max_x = True
+        real_constraint.use_max_y = True
+        real_constraint.use_max_z = True
+        real_constraint.use_min_x = True
+        real_constraint.use_min_y = True
+        real_constraint.use_min_z = True
+
+    if m_constraint.type == "distance" and m_constraint.constrained_boneB:
+        real_constraint.owner_space = "WORLD"
+        real_constraint.target = obj
+        real_constraint.subtarget = getConsObj(bones[m_constraint.constrained_boneB]).name
+        real_constraint.limit_mode = "LIMITDIST_ONSURFACE"
+        if m_constraint.targetDist<0.01:
+            m_constraint.targetDist = 0.01
+        real_constraint.distance = m_constraint.targetDist
+
+    if m_constraint.type == "floor" and m_constraint.targetMesh:
+        real_constraint.mute = True
+        real_constraint.owner_space = "WORLD"
+        #calculate the positions thoughout the range
+        s, e = m_constraint.s_frame, m_constraint.e_frame
+        s_in, s_out = m_constraint.smooth_in, m_constraint.smooth_out
+        s -= s_in
+        e += s_out
+        bakedPos = {}
+        floor = bpy.data.objects[m_constraint.targetMesh]
+        c_frame = context.scene.frame_current
+        print("please wait a moment, calculating fix")
+        for t in range(s, e):
+            context.scene.frame_set(t)
+            axis = obj.matrix_world.to_3x3() * Vector((0, 0, 100))
+            offset = obj.matrix_world.to_3x3() * Vector((0, 0, m_constraint.targetDist))
+            ray_origin = (cons_obj.matrix * obj.matrix_world).to_translation() - offset  # world position of constrained bone
+            ray_target = ray_origin + axis
+            #convert ray points to floor's object space
+            ray_origin = floor.matrix_world.inverted() * ray_origin
+            ray_target = floor.matrix_world.inverted() * ray_target
+            hit, nor, ind = floor.ray_cast(ray_origin, ray_target)
+            if hit != Vector((0, 0, 0)):
+                bakedPos[t] = (floor.matrix_world * hit)
+                bakedPos[t] += Vector((0, 0, m_constraint.targetDist))
+            else:
+                bakedPos[t] = (cons_obj.matrix * obj.matrix_world).to_translation()
+        context.scene.frame_set(c_frame)
+        #create keyframes for real constraint
+        xCurves, yCurves, zCurves = createConstraintFCurves(cons_obj, obj, real_constraint)
+        for frame in bakedPos.keys():
+            pos = bakedPos[frame]
+            for xCurve in xCurves:
+                xCurve.keyframe_points.insert(frame=frame, value=pos.x)
+            for yCurve in yCurves:
+                yCurve.keyframe_points.insert(frame=frame, value=pos.y)
+            for zCurve in zCurves:
+                zCurve.keyframe_points.insert(frame=frame, value=pos.z)
+        real_constraint.use_max_x = True
+        real_constraint.use_max_y = True
+        real_constraint.use_max_z = True
+        real_constraint.use_min_x = True
+        real_constraint.use_min_y = True
+        real_constraint.use_min_z = True
+
+    # active/baked check
+    real_constraint.mute = (not m_constraint.active)
+
+
+def locBake(s_frame, e_frame, bones):
+    scene = bpy.context.scene
+    bakeDict = {}
+    for bone in bones:
+        bakeDict[bone.name] = {}
+    for t in range(s_frame, e_frame):
+        scene.frame_set(t)
+        for bone in bones:
+            bakeDict[bone.name][t] = bone.matrix.copy()
+    for t in range(s_frame, e_frame):
+        for bone in bones:
+            print(bone.bone.matrix_local.to_translation())
+            bone.matrix = bakeDict[bone.name][t]
+            bone.keyframe_insert("location", frame=t)
+
+
+# Baking function which bakes all bones effected by the constraint
+def bakeAllConstraints(obj, s_frame, e_frame, bones):
+    for bone in bones:
+        bone.bone.select = False
+    selectedBones = []  # Marks bones that need a full bake
+    simpleBake = []  # Marks bones that need only a location bake
+    for end_bone in bones:
+        if end_bone.name in [m_constraint.real_constraint_bone for m_constraint in obj.data.mocap_constraints]:
+            #For all bones that have a constraint:
+            ik = retarget.hasIKConstraint(end_bone)
+            cons_obj = getConsObj(end_bone)
+            if ik:
+                    #If it's an auto generated IK:
+                    if ik.chain_count == 0:
+                        selectedBones += bones  # Chain len 0, bake everything
+                    else:
+                        selectedBones += [end_bone] + end_bone.parent_recursive[:ik.chain_count - 1]  # Bake the chain
+            else:
+                #It's either an FK bone which we should just bake
+                #OR a user created IK target bone
+                simpleBake += [end_bone]
+    for bone in selectedBones:
+        bone.bone.select = True
+    NLATracks = obj.data.mocapNLATracks[obj.data.active_mocap]
+    obj.animation_data.action = bpy.data.actions[NLATracks.auto_fix_track]
+    constraintTrack = obj.animation_data.nla_tracks[NLATracks.auto_fix_track]
+    constraintStrip = constraintTrack.strips[0]
+    constraintStrip.action_frame_start = s_frame
+    constraintStrip.action_frame_end = e_frame
+    constraintStrip.frame_start = s_frame
+    constraintStrip.frame_end = e_frame
+    if selectedBones:
+        #Use bake function from NLA Bake Action operator
+        nla.bake(s_frame, e_frame, action=constraintStrip.action, only_selected=True, do_pose=True, do_object=False)
+    if simpleBake:
+        #Do a "simple" bake, location only, world space only.
+        locBake(s_frame, e_frame, simpleBake)
+
+
+#Calls the baking function and decativates releveant constraints
+def bakeConstraints(context):
+    obj = context.active_object
+    bones = obj.pose.bones
+    s_frame, e_frame = context.scene.frame_start, context.scene.frame_end
+    #Bake relevant bones
+    bakeAllConstraints(obj, s_frame, e_frame, bones)
+    for m_constraint in obj.data.mocap_constraints:
+        end_bone = bones[m_constraint.real_constraint_bone]
+        cons_obj = getConsObj(end_bone)
+        # It's a control empty: turn the ik off
+        if not isinstance(cons_obj, bpy.types.PoseBone):
+            ik_con = retarget.hasIKConstraint(end_bone)
+            if ik_con:
+                ik_con.mute = True
+        # Deactivate related Blender Constraint
+        m_constraint.active = False
+
+
+#Deletes the baked fcurves and reactivates relevant constraints
+def unbakeConstraints(context):
+    # to unbake constraints we delete the whole strip
+    obj = context.active_object
+    bones = obj.pose.bones
+    scene = bpy.context.scene
+    NLATracks = obj.data.mocapNLATracks[obj.data.active_mocap]
+    obj.animation_data.action = bpy.data.actions[NLATracks.auto_fix_track]
+    constraintTrack = obj.animation_data.nla_tracks[NLATracks.auto_fix_track]
+    constraintStrip = constraintTrack.strips[0]
+    action = constraintStrip.action
+    # delete the fcurves on the strip
+    for fcurve in action.fcurves:
+        action.fcurves.remove(fcurve)
+    # reactivate relevant constraints
+    for m_constraint in obj.data.mocap_constraints:
+        end_bone = bones[m_constraint.real_constraint_bone]
+        cons_obj = getConsObj(end_bone)
+        # It's a control empty: turn the ik back on
+        if not isinstance(cons_obj, bpy.types.PoseBone):
+            ik_con = retarget.hasIKConstraint(end_bone)
+            if ik_con:
+                ik_con.mute = False
+        m_constraint.active = True
+
+
+def updateConstraints(obj, context):
+    fixes = obj.data.mocap_constraints
+    for fix in fixes:
+        fix.active = False
+        fix.active = True
diff --git a/mocap/mocap_tools.py b/mocap/mocap_tools.py
new file mode 100644
index 00000000..ede55db4
--- /dev/null
+++ b/mocap/mocap_tools.py
@@ -0,0 +1,908 @@
+# ##### BEGIN GPL LICENSE BLOCK #####
+#
+#  This program is free software; you can redistribute it and/or
+#  modify it under the terms of the GNU General Public License
+#  as published by the Free Software Foundation; either version 2
+#  of the License, or (at your option) any later version.
+#
+#  This program is distributed in the hope that it will be useful,
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#  GNU General Public License for more details.
+#
+#  You should have received a copy of the GNU General Public License
+#  along with this program; if not, write to the Free Software Foundation,
+#  Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
+#
+# ##### END GPL LICENSE BLOCK #####
+
+# <pep8 compliant>
+
+from math import hypot, sqrt, isfinite, radians, pi
+import bpy
+import time
+from mathutils import Vector, Matrix
+
+
+# A Python implementation of n sized Vectors.
+# Mathutils has a max size of 4, and we need at least 5 for Simplify Curves and even more for Cross Correlation.
+# Vector utility functions
+class NdVector:
+    vec = []
+
+    def __init__(self, vec):
+        self.vec = vec[:]
+
+    def __len__(self):
+        return len(self.vec)
+
+    def __mul__(self, otherMember):
+        if (isinstance(otherMember, int) or
+            isinstance(otherMember, float)):
+            return NdVector([otherMember * x for x in self.vec])
+        else:
+            a = self.vec
+            b = otherMember.vec
+            n = len(self)
+            return sum([a[i] * b[i] for i in range(n)])
+
+    def __sub__(self, otherVec):
+        a = self.vec
+        b = otherVec.vec
+        n = len(self)
+        return NdVector([a[i] - b[i] for i in range(n)])
+
+    def __add__(self, otherVec):
+        a = self.vec
+        b = otherVec.vec
+        n = len(self)
+        return NdVector([a[i] + b[i] for i in range(n)])
+
+    def __div__(self, scalar):
+        return NdVector([x / scalar for x in self.vec])
+
+    def vecLength(self):
+        return sqrt(self * self)
+
+    def vecLengthSq(self):
+        return (self * self)
+
+    def normalize(self):
+        len = self.length
+        self.vec = [x / len for x in self.vec]
+
+    def copy(self):
+        return NdVector(self.vec)
+
+    def __getitem__(self, i):
+        return self.vec[i]
+
+    def x(self):
+        return self.vec[0]
+
+    def y(self):
+        return self.vec[1]
+
+    def resize_2d(self):
+        return Vector((self.x, self.y))
+
+    length = property(vecLength)
+    lengthSq = property(vecLengthSq)
+    x = property(x)
+    y = property(y)
+
+
+#Sampled Data Point class for Simplify Curves
+class dataPoint:
+    index = 0
+    # x,y1,y2,y3 coordinate of original point
+    co = NdVector((0, 0, 0, 0, 0))
+    #position according to parametric view of original data, [0,1] range
+    u = 0
+    #use this for anything
+    temp = 0
+
+    def __init__(self, index, co, u=0):
+        self.index = index
+        self.co = co
+        self.u = u
+
+
+#Cross Correlation Function
+#http://en.wikipedia.org/wiki/Cross_correlation
+#IN:   curvesA, curvesB - bpy_collection/list of fcurves to analyze. Auto-Correlation is when they are the same.
+#        margin - When searching for the best "start" frame, how large a neighborhood of frames should we inspect (similar to epsilon in Calculus)
+#OUT:   startFrame, length of new anim, and curvesA
+def crossCorrelationMatch(curvesA, curvesB, margin):
+    dataA = []
+    dataB = []
+    start = int(max(curvesA[0].range()[0],curvesB[0].range()[0]))
+    end = int(min(curvesA[0].range()[1],curvesB[0].range()[1]))
+
+    #transfer all fcurves data on each frame to a single NdVector.
+    for i in range(1, end):
+        vec = []
+        for fcurve in curvesA:
+            if fcurve.data_path in [otherFcurve.data_path for otherFcurve in curvesB]:
+                vec.append(fcurve.evaluate(i))
+        dataA.append(NdVector(vec))
+        vec = []
+        for fcurve in curvesB:
+            if fcurve.data_path in [otherFcurve.data_path for otherFcurve in curvesA]:
+                vec.append(fcurve.evaluate(i))
+        dataB.append(NdVector(vec))
+    #Comparator for Cross Correlation. "Classic" implementation uses dot product, as do we.
+    def comp(a, b):
+        return a * b
+
+    #Create Rxy, which holds the Cross Correlation data.
+    N = len(dataA)
+    Rxy = [0.0] * N
+    for i in range(N):
+        for j in range(i, min(i + N, N)):
+            Rxy[i] += comp(dataA[j], dataB[j - i])
+        for j in range(i):
+            Rxy[i] += comp(dataA[j], dataB[j - i + N])
+        Rxy[i] /= float(N)
+
+    #Find the Local maximums in the Cross Correlation data via numerical derivative.
+    def LocalMaximums(Rxy):
+        Rxyd = [Rxy[i] - Rxy[i - 1] for i in range(1, len(Rxy))]
+        maxs = []
+        for i in range(1, len(Rxyd) - 1):
+            a = Rxyd[i - 1]
+            b = Rxyd[i]
+            #sign change (zerocrossing) at point i, denoting max point (only)
+            if (a >= 0 and b < 0) or (a < 0 and b >= 0):
+                maxs.append((i, max(Rxy[i], Rxy[i - 1])))
+        return [x[0] for x in maxs]
+        #~ return max(maxs, key=lambda x: x[1])[0]
+
+    #flms - the possible offsets of the first part of the animation. In Auto-Corr, this is the length of the loop.
+    flms = LocalMaximums(Rxy[0:int(len(Rxy))])
+    ss = []
+
+    #for every local maximum, find the best one - i.e. also has the best start frame.
+    for flm in flms:
+        diff = []
+
+        for i in range(len(dataA) - flm):
+            diff.append((dataA[i] - dataB[i + flm]).lengthSq)
+
+        def lowerErrorSlice(diff, e):
+            #index, error at index
+            bestSlice = (0, 100000)
+            for i in range(e, len(diff) - e):
+                errorSlice = sum(diff[i - e:i + e + 1])
+                if errorSlice < bestSlice[1]:
+                    bestSlice = (i, errorSlice, flm)
+            return bestSlice
+
+        s = lowerErrorSlice(diff, margin)
+        ss.append(s)
+
+    #Find the best result and return it.
+    ss.sort(key=lambda x: x[1])
+    return ss[0][2], ss[0][0], dataA
+
+
+#Uses auto correlation (cross correlation of the same set of curves) and trims the active_object's fcurves
+#Except for location curves (which in mocap tend to be not cyclic, e.g. a walk cycle forward)
+#Transfers the fcurve data to a list of NdVector (length of list is number of fcurves), and calls the cross correlation function.
+#Then trims the fcurve accordingly.
+#IN: Nothing, set the object you want as active and call. Assumes object has animation_data.action!
+#OUT: Trims the object's fcurves (except location curves).
+def autoloop_anim():
+    context = bpy.context
+    obj = context.active_object
+
+    def locCurve(x):
+        x.data_path == "location"
+
+    fcurves = [x for x in obj.animation_data.action.fcurves if not locCurve(x)]
+
+    margin = 10
+
+    flm, s, data = crossCorrelationMatch(fcurves, fcurves, margin)
+    loop = data[s:s + flm]
+
+    #performs blending with a root falloff on the seam's neighborhood to ensure good tiling.
+    for i in range(1, margin + 1):
+        w1 = sqrt(float(i) / margin)
+        loop[-i] = (loop[-i] * w1) + (loop[0] * (1 - w1))
+
+    for curve in fcurves:
+        pts = curve.keyframe_points
+        for i in range(len(pts) - 1, -1, -1):
+            pts.remove(pts[i])
+
+    for c, curve in enumerate(fcurves):
+        pts = curve.keyframe_points
+        for i in range(len(loop)):
+            pts.insert(i + 2, loop[i][c])
+
+    context.scene.frame_end = flm
+
+
+#simplifyCurves: performes the bulk of the samples to bezier conversion.
+#IN:    curveGroup - which can be a collection of singleFcurves, or grouped (via nested lists) .
+#         error - threshold of permittable error (max distance) of the new beziers to the original data
+#         reparaError - threshold of error where we should try to fix the parameterization rather than split the existing curve. > error, usually by a small constant factor for best performance.
+#         maxIterations - maximum number of iterations of reparameterizations we should attempt. (Newton-Rahpson is not guarenteed to converge, so this is needed).
+#         group_mode - boolean, indicating wether we should place bezier keyframes on the same x (frame), or optimize each individual curve.
+#OUT: None. Deletes the existing curves and creates the new beziers.
+def simplifyCurves(curveGroup, error, reparaError, maxIterations, group_mode):
+
+    #Calculates the unit tangent of point v
+    def unitTangent(v, data_pts):
+        tang = NdVector((0, 0, 0, 0, 0))
+        if v != 0:
+            #If it's not the first point, we can calculate a leftside tangent
+            tang += data_pts[v].co - data_pts[v - 1].co
+        if v != len(data_pts) - 1:
+            #If it's not the last point, we can calculate a rightside tangent
+            tang += data_pts[v + 1].co - data_pts[v].co
+        tang.normalize()
+        return tang
+
+    #assign parametric u value for each point in original data, via relative arc length
+    #http://en.wikipedia.org/wiki/Arc_length
+    def chordLength(data_pts, s, e):
+        totalLength = 0
+        for pt in data_pts[s:e + 1]:
+            i = pt.index
+            if i == s:
+                chordLength = 0
+            else:
+                chordLength = (data_pts[i].co - data_pts[i - 1].co).length
+            totalLength += chordLength
+            pt.temp = totalLength
+        for pt in data_pts[s:e + 1]:
+            if totalLength == 0:
+                print(s, e)
+            pt.u = (pt.temp / totalLength)
+
+    # get binomial coefficient lookup table, this function/table is only called with args
+    # (3,0),(3,1),(3,2),(3,3),(2,0),(2,1),(2,2)!
+    binomDict = {(3, 0): 1,
+    (3, 1): 3,
+    (3, 2): 3,
+    (3, 3): 1,
+    (2, 0): 1,
+    (2, 1): 2,
+    (2, 2): 1}
+
+    #value at pt t of a single bernstein Polynomial
+    def bernsteinPoly(n, i, t):
+        binomCoeff = binomDict[(n, i)]
+        return binomCoeff * pow(t, i) * pow(1 - t, n - i)
+
+    # fit a single cubic to data points in range [s(tart),e(nd)].
+    def fitSingleCubic(data_pts, s, e):
+
+        # A - matrix used for calculating C matrices for fitting
+        def A(i, j, s, e, t1, t2):
+            if j == 1:
+                t = t1
+            if j == 2:
+                t = t2
+            u = data_pts[i].u
+            return t * bernsteinPoly(3, j, u)
+
+        # X component, used for calculating X matrices for fitting
+        def xComponent(i, s, e):
+            di = data_pts[i].co
+            u = data_pts[i].u
+            v0 = data_pts[s].co
+            v3 = data_pts[e].co
+            a = v0 * bernsteinPoly(3, 0, u)
+            b = v0 * bernsteinPoly(3, 1, u)
+            c = v3 * bernsteinPoly(3, 2, u)
+            d = v3 * bernsteinPoly(3, 3, u)
+            return (di - (a + b + c + d))
+
+        t1 = unitTangent(s, data_pts)
+        t2 = unitTangent(e, data_pts)
+        c11 = sum([A(i, 1, s, e, t1, t2) * A(i, 1, s, e, t1, t2) for i in range(s, e + 1)])
+        c12 = sum([A(i, 1, s, e, t1, t2) * A(i, 2, s, e, t1, t2) for i in range(s, e + 1)])
+        c21 = c12
+        c22 = sum([A(i, 2, s, e, t1, t2) * A(i, 2, s, e, t1, t2) for i in range(s, e + 1)])
+
+        x1 = sum([xComponent(i, s, e) * A(i, 1, s, e, t1, t2) for i in range(s, e + 1)])
+        x2 = sum([xComponent(i, s, e) * A(i, 2, s, e, t1, t2) for i in range(s, e + 1)])
+
+        # calculate Determinate of the 3 matrices
+        det_cc = c11 * c22 - c21 * c12
+        det_cx = c11 * x2 - c12 * x1
+        det_xc = x1 * c22 - x2 * c12
+
+        # if matrix is not homogenous, fudge the data a bit
+        if det_cc == 0:
+            det_cc = 0.01
+
+        # alpha's are the correct offset for bezier handles
+        alpha0 = det_xc / det_cc   # offset from right (first) point
+        alpha1 = det_cx / det_cc   # offset from left (last) point
+
+        sRightHandle = data_pts[s].co.copy()
+        sTangent = t1 * abs(alpha0)
+        sRightHandle += sTangent  # position of first pt's handle
+        eLeftHandle = data_pts[e].co.copy()
+        eTangent = t2 * abs(alpha1)
+        eLeftHandle += eTangent  # position of last pt's handle.
+
+        # return a 4 member tuple representing the bezier
+        return (data_pts[s].co,
+              sRightHandle,
+              eLeftHandle,
+              data_pts[e].co)
+
+    # convert 2 given data points into a cubic bezier.
+    # handles are offset along the tangent at
+    # a 3rd of the length between the points.
+    def fitSingleCubic2Pts(data_pts, s, e):
+        alpha0 = alpha1 = (data_pts[s].co - data_pts[e].co).length / 3
+
+        sRightHandle = data_pts[s].co.copy()
+        sTangent = unitTangent(s, data_pts) * abs(alpha0)
+        sRightHandle += sTangent  # position of first pt's handle
+        eLeftHandle = data_pts[e].co.copy()
+        eTangent = unitTangent(e, data_pts) * abs(alpha1)
+        eLeftHandle += eTangent  # position of last pt's handle.
+
+        #return a 4 member tuple representing the bezier
+        return (data_pts[s].co,
+          sRightHandle,
+          eLeftHandle,
+          data_pts[e].co)
+
+    #evaluate bezier, represented by a 4 member tuple (pts) at point t.
+    def bezierEval(pts, t):
+        sumVec = NdVector((0, 0, 0, 0, 0))
+        for i in range(4):
+            sumVec += pts[i] * bernsteinPoly(3, i, t)
+        return sumVec
+
+    #calculate the highest error between bezier and original data
+    #returns the distance and the index of the point where max error occurs.
+    def maxErrorAmount(data_pts, bez, s, e):
+        maxError = 0
+        maxErrorPt = s
+        if e - s < 3:
+            return 0, None
+        for pt in data_pts[s:e + 1]:
+            bezVal = bezierEval(bez, pt.u)
+            normalize_error = pt.co.length
+            if normalize_error == 0:
+                normalize_error = 1
+            tmpError = (pt.co - bezVal).length / normalize_error
+            if tmpError >= maxError:
+                maxError = tmpError
+                maxErrorPt = pt.index
+        return maxError, maxErrorPt
+
+    #calculated bezier derivative at point t.
+    #That is, tangent of point t.
+    def getBezDerivative(bez, t):
+        n = len(bez) - 1
+        sumVec = NdVector((0, 0, 0, 0, 0))
+        for i in range(n - 1):
+            sumVec += (bez[i + 1] - bez[i]) * bernsteinPoly(n - 1, i, t)
+        return sumVec
+
+    #use Newton-Raphson to find a better paramterization of datapoints,
+    #one that minimizes the distance (or error)
+    # between bezier and original data.
+    def newtonRaphson(data_pts, s, e, bez):
+        for pt in data_pts[s:e + 1]:
+            if pt.index == s:
+                pt.u = 0
+            elif pt.index == e:
+                pt.u = 1
+            else:
+                u = pt.u
+                qu = bezierEval(bez, pt.u)
+                qud = getBezDerivative(bez, u)
+                #we wish to minimize f(u),
+                #the squared distance between curve and data
+                fu = (qu - pt.co).length ** 2
+                fud = (2 * (qu.x - pt.co.x) * (qud.x)) - (2 * (qu.y - pt.co.y) * (qud.y))
+                if fud == 0:
+                    fu = 0
+                    fud = 1
+                pt.u = pt.u - (fu / fud)
+
+    #Create data_pts, a list of dataPoint type, each is assigned index i, and an NdVector
+    def createDataPts(curveGroup, group_mode):
+        data_pts = []
+        if group_mode:
+            print([x.data_path for x in curveGroup])
+            for i in range(len(curveGroup[0].keyframe_points)):
+                x = curveGroup[0].keyframe_points[i].co.x
+                y1 = curveGroup[0].evaluate(i)
+                y2 = curveGroup[1].evaluate(i)
+                y3 = curveGroup[2].evaluate(i)
+                y4 = 0
+                if len(curveGroup) == 4:
+                    y4 = curveGroup[3].evaluate(i)
+                data_pts.append(dataPoint(i, NdVector((x, y1, y2, y3, y4))))
+        else:
+            for i in range(len(curveGroup.keyframe_points)):
+                x = curveGroup.keyframe_points[i].co.x
+                y1 = curveGroup.keyframe_points[i].co.y
+                y2 = 0
+                y3 = 0
+                y4 = 0
+                data_pts.append(dataPoint(i, NdVector((x, y1, y2, y3, y4))))
+        return data_pts
+
+    #Recursively fit cubic beziers to the data_pts between s and e
+    def fitCubic(data_pts, s, e):
+        # if there are less than 3 points, fit a single basic bezier
+        if e - s < 3:
+            bez = fitSingleCubic2Pts(data_pts, s, e)
+        else:
+            #if there are more, parameterize the points
+            # and fit a single cubic bezier
+            chordLength(data_pts, s, e)
+            bez = fitSingleCubic(data_pts, s, e)
+
+        #calculate max error and point where it occurs
+        maxError, maxErrorPt = maxErrorAmount(data_pts, bez, s, e)
+        #if error is small enough, reparameterization might be enough
+        if maxError < reparaError and maxError > error:
+            for i in range(maxIterations):
+                newtonRaphson(data_pts, s, e, bez)
+                if e - s < 3:
+                    bez = fitSingleCubic2Pts(data_pts, s, e)
+                else:
+                    bez = fitSingleCubic(data_pts, s, e)
+
+        #recalculate max error and point where it occurs
+        maxError, maxErrorPt = maxErrorAmount(data_pts, bez, s, e)
+
+        #repara wasn't enough, we need 2 beziers for this range.
+        #Split the bezier at point of maximum error
+        if maxError > error:
+            fitCubic(data_pts, s, maxErrorPt)
+            fitCubic(data_pts, maxErrorPt, e)
+        else:
+            #error is small enough, return the beziers.
+            beziers.append(bez)
+            return
+
+    # deletes the sampled points and creates beziers.
+    def createNewCurves(curveGroup, beziers, group_mode):
+        #remove all existing data points
+        if group_mode:
+            for fcurve in curveGroup:
+                for i in range(len(fcurve.keyframe_points) - 1, 0, -1):
+                    fcurve.keyframe_points.remove(fcurve.keyframe_points[i])
+        else:
+            fcurve = curveGroup
+            for i in range(len(fcurve.keyframe_points) - 1, 0, -1):
+                fcurve.keyframe_points.remove(fcurve.keyframe_points[i])
+
+        #insert the calculated beziers to blender data.\
+        if group_mode:
+            for fullbez in beziers:
+                for i, fcurve in enumerate(curveGroup):
+                    bez = [Vector((vec[0], vec[i + 1])) for vec in fullbez]
+                    newKey = fcurve.keyframe_points.insert(frame=bez[0].x, value=bez[0].y)
+                    newKey.handle_right = (bez[1].x, bez[1].y)
+
+                    newKey = fcurve.keyframe_points.insert(frame=bez[3].x, value=bez[3].y)
+                    newKey.handle_left = (bez[2].x, bez[2].y)
+        else:
+            for bez in beziers:
+                for vec in bez:
+                    vec.resize_2d()
+                newKey = fcurve.keyframe_points.insert(frame=bez[0].x, value=bez[0].y)
+                newKey.handle_right = (bez[1].x, bez[1].y)
+
+                newKey = fcurve.keyframe_points.insert(frame=bez[3].x, value=bez[3].y)
+                newKey.handle_left = (bez[2].x, bez[2].y)
+
+    # indices are detached from data point's frame (x) value and
+    # stored in the dataPoint object, represent a range
+
+    data_pts = createDataPts(curveGroup, group_mode)
+
+    s = 0  # start
+    e = len(data_pts) - 1  # end
+
+    beziers = []
+
+    #begin the recursive fitting algorithm.
+    fitCubic(data_pts, s, e)
+    #remove old Fcurves and insert the new ones
+    createNewCurves(curveGroup, beziers, group_mode)
+
+
+#Main function of simplification, which called by Operator
+#IN:
+#       sel_opt- either "sel" (selected) or "all" for which curves to effect
+#       error- maximum error allowed, in fraction (20% = 0.0020, which is the default),
+#       i.e. divide by 10000 from percentage wanted.
+#       group_mode- boolean, to analyze each curve seperately or in groups,
+#       where a group is all curves that effect the same property/RNA path
+def fcurves_simplify(context, obj, sel_opt="all", error=0.002, group_mode=True):
+    # main vars
+    fcurves = obj.animation_data.action.fcurves
+
+    if sel_opt == "sel":
+        sel_fcurves = [fcurve for fcurve in fcurves if fcurve.select]
+    else:
+        sel_fcurves = fcurves[:]
+
+    #Error threshold for Newton Raphson reparamatizing
+    reparaError = error * 32
+    maxIterations = 16
+
+    if group_mode:
+        fcurveDict = {}
+        #this loop sorts all the fcurves into groups of 3 or 4,
+        #based on their RNA Data path, which corresponds to
+        #which property they effect
+        for curve in sel_fcurves:
+            if curve.data_path in fcurveDict:  # if this bone has been added, append the curve to its list
+                fcurveDict[curve.data_path].append(curve)
+            else:
+                fcurveDict[curve.data_path] = [curve]  # new bone, add a new dict value with this first curve
+        fcurveGroups = fcurveDict.values()
+    else:
+        fcurveGroups = sel_fcurves
+
+    if error > 0.00000:
+        #simplify every selected curve.
+        totalt = 0
+        for i, fcurveGroup in enumerate(fcurveGroups):
+            print("Processing curve " + str(i + 1) + "/" + str(len(fcurveGroups)))
+            t = time.clock()
+            simplifyCurves(fcurveGroup, error, reparaError, maxIterations, group_mode)
+            t = time.clock() - t
+            print(str(t)[:5] + " seconds to process last curve")
+            totalt += t
+            print(str(totalt)[:5] + " seconds, total time elapsed")
+
+    return
+
+
+# Implementation of non-linear median filter, with variable kernel size
+# Double pass - one marks spikes, the other smooths them
+# Expects sampled keyframes on everyframe
+# IN: None. Performs the operations on the active_object's fcurves. Expects animation_data.action to exist!
+# OUT: None. Fixes the fcurves "in-place".
+def denoise_median():
+    context = bpy.context
+    obj = context.active_object
+    fcurves = obj.animation_data.action.fcurves
+    medKernel = 1  # actually *2+1... since it this is offset
+    flagKernel = 4
+    highThres = (flagKernel * 2) - 1
+    lowThres = 0
+    for fcurve in fcurves:
+        orgPts = fcurve.keyframe_points[:]
+        flaggedFrames = []
+        # mark frames that are spikes by sorting a large kernel
+        for i in range(flagKernel, len(fcurve.keyframe_points) - flagKernel):
+            center = orgPts[i]
+            neighborhood = orgPts[i - flagKernel: i + flagKernel]
+            neighborhood.sort(key=lambda pt: pt.co[1])
+            weight = neighborhood.index(center)
+            if weight >= highThres or weight <= lowThres:
+                flaggedFrames.append((i, center))
+        # clean marked frames with a simple median filter
+        # averages all frames in the kernel equally, except center which has no weight
+        for i, pt in flaggedFrames:
+            newValue = 0
+            sumWeights = 0
+            neighborhood = [neighpt.co[1] for neighpt in orgPts[i - medKernel: i + medKernel + 1] if neighpt != pt]
+            newValue = sum(neighborhood) / len(neighborhood)
+            pt.co[1] = newValue
+    return
+
+
+# Recieves armature, and rotations all bones by 90 degrees along the X axis
+# This fixes the common axis issue BVH files have when importing.
+# IN: Armature (bpy.types.Armature)
+def rotate_fix_armature(arm_data):
+    global_matrix = Matrix.Rotation(radians(90), 4, "X")
+    bpy.ops.object.mode_set(mode='EDIT', toggle=False)
+    #disconnect all bones for ease of global rotation
+    connectedBones = []
+    for bone in arm_data.edit_bones:
+        if bone.use_connect:
+            connectedBones.append(bone.name)
+            bone.use_connect = False
+
+    #rotate all the bones around their center
+    for bone in arm_data.edit_bones:
+        bone.transform(global_matrix)
+
+    #reconnect the bones
+    for bone in connectedBones:
+        arm_data.edit_bones[bone].use_connect = True
+    bpy.ops.object.mode_set(mode='OBJECT', toggle=False)
+
+
+#Roughly scales the performer armature to match the enduser armature
+#IN: perfromer_obj, enduser_obj, Blender objects whose .data is an armature.
+def scale_fix_armature(performer_obj, enduser_obj):
+        perf_bones = performer_obj.data.bones
+        end_bones = enduser_obj.data.bones
+
+        def calculateBoundingRadius(bones):
+            center = Vector()
+            for bone in bones:
+                center += bone.head_local
+            center /= len(bones)
+            radius = 0
+            for bone in bones:
+                dist = (bone.head_local - center).length
+                if dist > radius:
+                    radius = dist
+            return radius
+
+        perf_rad = calculateBoundingRadius(performer_obj.data.bones)
+        end_rad = calculateBoundingRadius(enduser_obj.data.bones)
+        #end_avg = enduser_obj.dimensions
+        factor = end_rad / perf_rad * 1.2
+        performer_obj.scale *= factor
+
+
+#Guess Mapping
+#Given a performer and enduser armature, attempts to guess the hiearchy mapping
+def guessMapping(performer_obj, enduser_obj):
+        perf_bones = performer_obj.data.bones
+        end_bones = enduser_obj.data.bones
+
+        root = perf_bones[0]
+
+        def findBoneSide(bone):
+            if "Left" in bone:
+                return "Left", bone.replace("Left", "").lower().replace(".", "")
+            if "Right" in bone:
+                return "Right", bone.replace("Right", "").lower().replace(".", "")
+            if "L" in bone:
+                return "Left", bone.replace("Left", "").lower().replace(".", "")
+            if "R" in bone:
+                return "Right", bone.replace("Right", "").lower().replace(".", "")
+            return "", bone
+
+        def nameMatch(bone_a, bone_b):
+            # nameMatch - recieves two strings, returns 2 if they are relatively the same, 1 if they are the same but R and L and 0 if no match at all
+            side_a, noside_a = findBoneSide(bone_a)
+            side_b, noside_b = findBoneSide(bone_b)
+            if side_a == side_b:
+                if noside_a in noside_b or noside_b in noside_a:
+                    return 2
+            else:
+                if noside_a in noside_b or noside_b in noside_a:
+                    return 1
+            return 0
+
+        def guessSingleMapping(perf_bone):
+            possible_bones = [end_bones[0]]
+
+            while possible_bones:
+                for end_bone in possible_bones:
+                    match = nameMatch(perf_bone.name, end_bone.name)
+                    if match == 2 and not perf_bone.map:
+                        perf_bone.map = end_bone.name
+                    #~ elif match == 1 and not perf_bone.map:
+                        #~ oppo = perf_bones[oppositeBone(perf_bone)].map
+                        # if oppo:
+                        #   perf_bone = oppo
+                newPossibleBones = []
+                for end_bone in possible_bones:
+                    newPossibleBones += list(end_bone.children)
+                possible_bones = newPossibleBones
+
+            for child in perf_bone.children:
+                guessSingleMapping(child)
+
+        guessSingleMapping(root)
+
+
+# Creates limit rotation constraints on the enduser armature based on range of motion (max min of fcurves) of the performer.
+# IN: context (bpy.context, etc.), and 2 blender objects which are armatures
+# OUT: creates the limit constraints.
+def limit_dof(context, performer_obj, enduser_obj):
+    limitDict = {}
+    perf_bones = [bone for bone in performer_obj.pose.bones if bone.bone.map]
+    c_frame = context.scene.frame_current
+    for bone in perf_bones:
+        limitDict[bone.bone.map] = [1000, 1000, 1000, -1000, -1000, -1000]
+    for t in range(context.scene.frame_start, context.scene.frame_end):
+        context.scene.frame_set(t)
+        for bone in perf_bones:
+            end_bone = enduser_obj.pose.bones[bone.bone.map]
+            bake_matrix = bone.matrix
+            rest_matrix = end_bone.bone.matrix_local
+
+            if end_bone.parent and end_bone.bone.use_inherit_rotation:
+                srcParent = bone.parent
+                parent_mat = srcParent.matrix
+                parent_rest = end_bone.parent.bone.matrix_local
+                parent_rest_inv = parent_rest.inverted()
+                parent_mat_inv = parent_mat.inverted()
+                bake_matrix = parent_mat_inv * bake_matrix
+                rest_matrix = parent_rest_inv * rest_matrix
+
+            rest_matrix_inv = rest_matrix.inverted()
+            bake_matrix = rest_matrix_inv * bake_matrix
+
+            mat = bake_matrix
+            euler = mat.to_euler()
+            limitDict[bone.bone.map][0] = min(limitDict[bone.bone.map][0], euler.x)
+            limitDict[bone.bone.map][1] = min(limitDict[bone.bone.map][1], euler.y)
+            limitDict[bone.bone.map][2] = min(limitDict[bone.bone.map][2], euler.z)
+            limitDict[bone.bone.map][3] = max(limitDict[bone.bone.map][3], euler.x)
+            limitDict[bone.bone.map][4] = max(limitDict[bone.bone.map][4], euler.y)
+            limitDict[bone.bone.map][5] = max(limitDict[bone.bone.map][5], euler.z)
+    for bone in enduser_obj.pose.bones:
+        existingConstraint = [constraint for constraint in bone.constraints if constraint.name == "DOF Limitation"]
+        if existingConstraint:
+            bone.constraints.remove(existingConstraint[0])
+    end_bones = [bone for bone in enduser_obj.pose.bones if bone.name in limitDict.keys()]
+    for bone in end_bones:
+        #~ if not bone.is_in_ik_chain:
+        newCons = bone.constraints.new("LIMIT_ROTATION")
+        newCons.name = "DOF Limitation"
+        newCons.owner_space = "LOCAL"
+        newCons.min_x, newCons.min_y, newCons.min_z, newCons.max_x, newCons.max_y, newCons.max_z = limitDict[bone.name]
+        newCons.use_limit_x = True
+        newCons.use_limit_y = True
+        newCons.use_limit_z = True
+    context.scene.frame_set(c_frame)
+
+
+# Removes the constraints that were added by limit_dof on the enduser_obj
+def limit_dof_toggle_off(context, enduser_obj):
+    for bone in enduser_obj.pose.bones:
+        existingConstraint = [constraint for constraint in bone.constraints if constraint.name == "DOF Limitation"]
+        if existingConstraint:
+            bone.constraints.remove(existingConstraint[0])
+
+
+# Reparameterizes a blender path via keyframing it's eval_time to match a stride_object's forward velocity.
+# IN: Context, stride object (blender object with location keyframes), path object.
+def path_editing(context, stride_obj, path):
+    y_fcurve = [fcurve for fcurve in stride_obj.animation_data.action.fcurves if fcurve.data_path == "location"][1]
+    s, e = context.scene.frame_start, context.scene.frame_end  # y_fcurve.range()
+    s = int(s)
+    e = int(e)
+    y_s = y_fcurve.evaluate(s)
+    y_e = y_fcurve.evaluate(e)
+    direction = (y_e - y_s) / abs(y_e - y_s)
+    existing_cons = [constraint for constraint in stride_obj.constraints if constraint.type == "FOLLOW_PATH"]
+    for cons in existing_cons:
+        stride_obj.constraints.remove(cons)
+    path_cons = stride_obj.constraints.new("FOLLOW_PATH")
+    if direction < 0:
+        path_cons.forward_axis = "TRACK_NEGATIVE_Y"
+    else:
+        path_cons.forward_axis = "FORWARD_Y"
+    path_cons.target = path
+    path_cons.use_curve_follow = True
+    path.data.path_duration = e - s
+    try:
+        path.data.animation_data.action.fcurves
+    except AttributeError:
+        path.data.keyframe_insert("eval_time", frame=0)
+    eval_time_fcurve = [fcurve for fcurve in path.data.animation_data.action.fcurves if fcurve.data_path == "eval_time"]
+    eval_time_fcurve = eval_time_fcurve[0]
+    totalLength = 0
+    parameterization = {}
+    print("evaluating curve")
+    for t in range(s, e - 1):
+        if s == t:
+            chordLength = 0
+        else:
+            chordLength = (y_fcurve.evaluate(t) - y_fcurve.evaluate(t + 1))
+        totalLength += chordLength
+        parameterization[t] = totalLength
+    for t in range(s + 1, e - 1):
+        if totalLength == 0:
+            print("no forward motion")
+        parameterization[t] /= totalLength
+        parameterization[t] *= e - s
+    parameterization[e] = e - s
+    for t in parameterization.keys():
+        eval_time_fcurve.keyframe_points.insert(frame=t, value=parameterization[t])
+    y_fcurve.mute = True
+    print("finished path editing")
+
+
+#Animation Stitching
+#Stitches two retargeted animations together via NLA settings.
+#IN: enduser_obj, a blender armature that has had two retargets applied.
+def anim_stitch(context, enduser_obj):
+    stitch_settings = enduser_obj.data.stitch_settings
+    action_1 = stitch_settings.first_action
+    action_2 = stitch_settings.second_action
+    if stitch_settings.stick_bone != "":
+        selected_bone = enduser_obj.pose.bones[stitch_settings.stick_bone]
+    else:
+        selected_bone = enduser_obj.pose.bones[0]
+    scene = context.scene
+    TrackNamesA = enduser_obj.data.mocapNLATracks[action_1]
+    TrackNamesB = enduser_obj.data.mocapNLATracks[action_2]
+    enduser_obj.data.active_mocap = action_1
+    anim_data = enduser_obj.animation_data
+    # add tracks for action 2
+    mocapAction = bpy.data.actions[TrackNamesB.base_track]
+    mocapTrack = anim_data.nla_tracks.new()
+    mocapTrack.name = TrackNamesB.base_track
+    mocapStrip = mocapTrack.strips.new(TrackNamesB.base_track, stitch_settings.blend_frame, mocapAction)
+    mocapStrip.extrapolation = "HOLD_FORWARD"
+    mocapStrip.blend_in = stitch_settings.blend_amount
+    mocapStrip.action_frame_start += stitch_settings.second_offset
+    mocapStrip.action_frame_end += stitch_settings.second_offset
+    constraintTrack = anim_data.nla_tracks.new()
+    constraintTrack.name = TrackNamesB.auto_fix_track
+    constraintAction = bpy.data.actions[TrackNamesB.auto_fix_track]
+    constraintStrip = constraintTrack.strips.new(TrackNamesB.auto_fix_track, stitch_settings.blend_frame, constraintAction)
+    constraintStrip.extrapolation = "HOLD_FORWARD"
+    constraintStrip.blend_in = stitch_settings.blend_amount
+    userTrack = anim_data.nla_tracks.new()
+    userTrack.name = TrackNamesB.manual_fix_track
+    userAction = bpy.data.actions[TrackNamesB.manual_fix_track]
+    userStrip = userTrack.strips.new(TrackNamesB.manual_fix_track, stitch_settings.blend_frame, userAction)
+    userStrip.extrapolation = "HOLD_FORWARD"
+    userStrip.blend_in = stitch_settings.blend_amount
+    #stride bone
+    if enduser_obj.parent:
+        if enduser_obj.parent.name == "stride_bone":
+            stride_bone = enduser_obj.parent
+            stride_anim_data = stride_bone.animation_data
+            stride_anim_data.use_nla = True
+            stride_anim_data.action = None
+            for track in stride_anim_data.nla_tracks:
+                stride_anim_data.nla_tracks.remove(track)
+            actionATrack = stride_anim_data.nla_tracks.new()
+            actionATrack.name = TrackNamesA.stride_action
+            actionAStrip = actionATrack.strips.new(TrackNamesA.stride_action, 0, bpy.data.actions[TrackNamesA.stride_action])
+            actionAStrip.extrapolation = "NOTHING"
+            actionBTrack = stride_anim_data.nla_tracks.new()
+            actionBTrack.name = TrackNamesB.stride_action
+            actionBStrip = actionBTrack.strips.new(TrackNamesB.stride_action, stitch_settings.blend_frame, bpy.data.actions[TrackNamesB.stride_action])
+            actionBStrip.action_frame_start += stitch_settings.second_offset
+            actionBStrip.action_frame_end += stitch_settings.second_offset
+            actionBStrip.extrapolation = "NOTHING"
+            #we need to change the stride_bone's action to add the offset
+            aStrideCurves = [fcurve for fcurve in bpy.data.actions[TrackNamesA.stride_action].fcurves if fcurve.data_path == "location"]
+            bStrideCurves = [fcurve for fcurve in bpy.data.actions[TrackNamesB.stride_action].fcurves if fcurve.data_path == "location"]
+            scene.frame_set(stitch_settings.blend_frame - 1)
+            desired_pos = (enduser_obj.matrix_world * selected_bone.matrix.to_translation())
+            scene.frame_set(stitch_settings.blend_frame)
+            actual_pos = (enduser_obj.matrix_world * selected_bone.matrix.to_translation() )
+            print(desired_pos, actual_pos)
+            offset = Vector(actual_pos) - Vector(desired_pos)
+
+            for i, fcurve in enumerate(bStrideCurves):
+                print(offset[i], i, fcurve.array_index)
+                for pt in fcurve.keyframe_points:
+                    pt.co.y -= offset[i]
+                    pt.handle_left.y -= offset[i]
+                    pt.handle_right.y -= offset[i]
+            
+            #actionBStrip.blend_in = stitch_settings.blend_amount
+
+
+#Guesses setting for animation stitching via Cross Correlation
+def guess_anim_stitch(context, enduser_obj):
+    stitch_settings = enduser_obj.data.stitch_settings
+    action_1 = stitch_settings.first_action
+    action_2 = stitch_settings.second_action
+    TrackNamesA = enduser_obj.data.mocapNLATracks[action_1]
+    TrackNamesB = enduser_obj.data.mocapNLATracks[action_2]
+    mocapA = bpy.data.actions[TrackNamesA.base_track]
+    mocapB = bpy.data.actions[TrackNamesB.base_track]
+    curvesA = mocapA.fcurves
+    curvesB = mocapB.fcurves
+    flm, s, data = crossCorrelationMatch(curvesA, curvesB, 10)
+    print("Guessed the following for start and offset: ", s, flm)
+    enduser_obj.data.stitch_settings.blend_frame = flm
+    enduser_obj.data.stitch_settings.second_offset = s
diff --git a/mocap/retarget.py b/mocap/retarget.py
new file mode 100644
index 00000000..6e669434
--- /dev/null
+++ b/mocap/retarget.py
@@ -0,0 +1,557 @@
+# ##### BEGIN GPL LICENSE BLOCK #####
+#
+#  This program is free software; you can redistribute it and/or
+#  modify it under the terms of the GNU General Public License
+#  as published by the Free Software Foundation; either version 2
+#  of the License, or (at your option) any later version.
+#
+#  This program is distributed in the hope that it will be useful,
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#  GNU General Public License for more details.
+#
+#  You should have received a copy of the GNU General Public License
+#  along with this program; if not, write to the Free Software Foundation,
+#  Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
+#
+# ##### END GPL LICENSE BLOCK #####
+
+# <pep8 compliant>
+
+import bpy
+from mathutils import *
+from math import radians, acos, pi
+from bl_operators import nla
+
+
+def hasIKConstraint(pose_bone):
+    #utility function / predicate, returns True if given bone has IK constraint
+    ik = [constraint for constraint in pose_bone.constraints if constraint.type == "IK"]
+    if ik:
+        return ik[0]
+    else:
+        return False
+
+
+def createDictionary(perf_arm, end_arm):
+    # clear any old data
+    for end_bone in end_arm.bones:
+        for mapping in end_bone.reverseMap:
+            end_bone.reverseMap.remove(0)
+
+    for perf_bone in perf_arm.bones:
+        #find its match and add perf_bone to the match's mapping
+        if perf_bone.map:
+            end_bone = end_arm.bones[perf_bone.map]
+            newMap = end_bone.reverseMap.add()
+            newMap.name = perf_bone.name
+            end_bone.foot = perf_bone.foot
+
+    #root is the root of the enduser
+    root = end_arm.bones[0].name
+    feetBones = [bone.name for bone in perf_arm.bones if bone.foot]
+    return feetBones, root
+
+
+def loadMapping(perf_arm, end_arm):
+    for end_bone in end_arm.bones:
+        #find its match and add perf_bone to the match's mapping
+        if end_bone.reverseMap:
+            for perf_bone in end_bone.reverseMap:
+                perf_arm.bones[perf_bone.name].map = end_bone.name
+
+#creation of intermediate armature
+# the intermediate armature has the hiearchy of the end user,
+# does not have rotation inheritence
+# and bone roll is identical to the performer
+# its purpose is to copy over the rotations
+# easily while concentrating on the hierarchy changes
+
+
+def createIntermediate(performer_obj, enduser_obj, root, s_frame, e_frame, scene, step):
+    #creates and keyframes an empty with its location
+    #the original position of the tail bone
+    #useful for storing the important data in the original motion
+    #i.e. using this empty to IK the chain to that pos / DEBUG
+
+    #Simple 1to1 retarget of a bone
+    def singleBoneRetarget(inter_bone, perf_bone):
+            perf_world_rotation = perf_bone.matrix
+            inter_world_base_rotation = inter_bone.bone.matrix_local
+            inter_world_base_inv = inter_world_base_rotation.inverted()
+            bake_matrix = (inter_world_base_inv.to_3x3() * perf_world_rotation.to_3x3())
+            return bake_matrix.to_4x4()
+
+    #uses 1to1 and interpolation/averaging to match many to 1 retarget
+    def manyPerfToSingleInterRetarget(inter_bone, performer_bones_s):
+        retarget_matrices = [singleBoneRetarget(inter_bone, perf_bone) for perf_bone in performer_bones_s]
+        lerp_matrix = Matrix()
+        for i in range(len(retarget_matrices) - 1):
+            first_mat = retarget_matrices[i]
+            next_mat = retarget_matrices[i + 1]
+            lerp_matrix = first_mat.lerp(next_mat, 0.5)
+        return lerp_matrix
+
+    #determines the type of hierachy change needed and calls the
+    #right function
+    def retargetPerfToInter(inter_bone):
+        if inter_bone.bone.reverseMap:
+            perf_bone_name = inter_bone.bone.reverseMap
+                # 1 to many not supported yet
+                # then its either a many to 1 or 1 to 1
+            if len(perf_bone_name) > 1:
+                performer_bones_s = [performer_bones[map.name] for map in perf_bone_name]
+                #we need to map several performance bone to a single
+                inter_bone.matrix_basis = manyPerfToSingleInterRetarget(inter_bone, performer_bones_s)
+            else:
+                perf_bone = performer_bones[perf_bone_name[0].name]
+                inter_bone.matrix_basis = singleBoneRetarget(inter_bone, perf_bone)
+        #Some bones have incorrect roll on the source armature, and need to be marked for fixing
+        if inter_bone.bone.twistFix:
+            inter_bone.matrix_basis *= Matrix.Rotation(radians(180), 4, "Y")
+        rot_mode = inter_bone.rotation_mode
+        if rot_mode == "QUATERNION":
+            inter_bone.keyframe_insert("rotation_quaternion")
+        elif rot_mode == "AXIS_ANGLE":
+            inter_bone.keyframe_insert("rotation_axis_angle")
+        else:
+            inter_bone.keyframe_insert("rotation_euler")
+
+    #creates the intermediate armature object
+    inter_obj = enduser_obj.copy()
+    inter_obj.data = inter_obj.data.copy()  # duplicate data
+    bpy.context.scene.objects.link(inter_obj)
+    inter_obj.name = "intermediate"
+    bpy.context.scene.objects.active = inter_obj
+    bpy.ops.object.mode_set(mode='EDIT')
+    #add some temporary connecting bones in case end user bones are not connected to their parents
+    rollDict = {}
+    print("creating temp bones")
+    for bone in inter_obj.data.edit_bones:
+        if not bone.use_connect and bone.parent:
+            if inter_obj.data.bones[bone.parent.name].reverseMap or inter_obj.data.bones[bone.name].reverseMap:
+                newBone = inter_obj.data.edit_bones.new("Temp")
+                newBone.head = bone.parent.tail
+                newBone.tail = bone.head
+                newBone.parent = bone.parent
+                bone.parent = newBone
+                bone.use_connect = True
+                newBone.use_connect = True
+        rollDict[bone.name] = bone.roll
+        bone.roll = 0
+    #resets roll
+    print("retargeting to intermediate")
+    bpy.ops.object.mode_set(mode="OBJECT")
+    inter_obj.data.name = "inter_arm"
+    inter_arm = inter_obj.data
+    performer_bones = performer_obj.pose.bones
+    inter_bones = inter_obj.pose.bones
+    #clears inheritance
+    for inter_bone in inter_bones:
+        if inter_bone.bone.reverseMap:
+            inter_bone.bone.use_inherit_rotation = False
+        else:
+            inter_bone.bone.use_inherit_rotation = True
+
+    for t in range(s_frame, e_frame, step):
+        if (t - s_frame) % 10 == 0:
+            print("First pass: retargeting frame {0}/{1}".format(t, e_frame - s_frame))
+        scene.frame_set(t)
+        for bone in inter_bones:
+            retargetPerfToInter(bone)
+
+    return inter_obj
+
+# this procedure copies the rotations over from the intermediate
+# armature to the end user one.
+# As the hierarchies are 1 to 1, this is a simple matter of
+# copying the rotation, while keeping in mind bone roll, parenting, etc.
+# TODO: Control Bones: If a certain bone is constrained in a way
+#       that its rotation is determined by another (a control bone)
+#       We should determine the right pos of the control bone.
+#       Scale: ? Should work but needs testing.
+
+
+def retargetEnduser(inter_obj, enduser_obj, root, s_frame, e_frame, scene, step):
+    inter_bones = inter_obj.pose.bones
+    end_bones = enduser_obj.pose.bones
+
+    #Basic "visual baking" function, for transfering rotations from intermediate to end user
+    def bakeTransform(end_bone):
+        src_bone = inter_bones[end_bone.name]
+        trg_bone = end_bone
+        bake_matrix = src_bone.matrix
+        rest_matrix = trg_bone.bone.matrix_local
+
+        if trg_bone.parent and trg_bone.bone.use_inherit_rotation:
+            srcParent = src_bone.parent
+            if "Temp" in srcParent.name:
+                srcParent = srcParent.parent
+            parent_mat = srcParent.matrix
+            parent_rest = trg_bone.parent.bone.matrix_local
+            parent_rest_inv = parent_rest.inverted()
+            parent_mat_inv = parent_mat.inverted()
+            bake_matrix = parent_mat_inv * bake_matrix
+            rest_matrix = parent_rest_inv * rest_matrix
+
+        rest_matrix_inv = rest_matrix.inverted()
+        bake_matrix = rest_matrix_inv * bake_matrix
+        end_bone.matrix_basis = bake_matrix
+        rot_mode = end_bone.rotation_mode
+        if rot_mode == "QUATERNION":
+            end_bone.keyframe_insert("rotation_quaternion")
+        elif rot_mode == "AXIS_ANGLE":
+            end_bone.keyframe_insert("rotation_axis_angle")
+        else:
+            end_bone.keyframe_insert("rotation_euler")
+        if not end_bone.bone.use_connect:
+            end_bone.keyframe_insert("location")
+
+        for bone in end_bone.children:
+            bakeTransform(bone)
+
+    for t in range(s_frame, e_frame, step):
+        if (t - s_frame) % 10 == 0:
+            print("Second pass: retargeting frame {0}/{1}".format(t, e_frame - s_frame))
+        scene.frame_set(t)
+        end_bone = end_bones[root]
+        end_bone.location = Vector((0, 0, 0))
+        end_bone.keyframe_insert("location")
+        bakeTransform(end_bone)
+
+#recieves the performer feet bones as a variable
+# by "feet" I mean those bones that have plants
+# (they don't move, despite root moving) somewhere in the animation.
+
+
+def copyTranslation(performer_obj, enduser_obj, perfFeet, root, s_frame, e_frame, scene, enduser_obj_mat):
+
+    perf_bones = performer_obj.pose.bones
+    end_bones = enduser_obj.pose.bones
+
+    perfRoot = perf_bones[0].name
+    endFeet = [perf_bones[perfBone].bone.map for perfBone in perfFeet]
+    locDictKeys = perfFeet + endFeet + [perfRoot]
+
+    def tailLoc(bone):
+        return bone.center + (bone.vector / 2)
+
+    #Step 1 - we create a dict that contains these keys:
+    #(Performer) Hips, Feet
+    #(End user) Feet
+    # where the values are their world position on each frame in range (s,e)
+
+    locDict = {}
+    for key in locDictKeys:
+        locDict[key] = []
+
+    for t in range(scene.frame_start, scene.frame_end):
+        scene.frame_set(t)
+        for bone in perfFeet:
+            locDict[bone].append(tailLoc(perf_bones[bone]))
+        locDict[perfRoot].append(tailLoc(perf_bones[perfRoot]))
+        for bone in endFeet:
+            locDict[bone].append(tailLoc(end_bones[bone]))
+
+    # now we take our locDict and analyze it.
+    # we need to derive all chains
+
+    def locDeriv(key, t):
+        graph = locDict[key]
+        return graph[t + 1] - graph[t]
+
+    # now find the plant frames, where perfFeet don't move much
+
+    linearAvg = []
+
+    for key in perfFeet:
+        for i in range(len(locDict[key]) - 1):
+            v = locDeriv(key, i)
+            if (v.length < 0.1):
+                hipV = locDeriv(perfRoot, i)
+                endV = locDeriv(perf_bones[key].bone.map, i)
+                #this is a plant frame.
+                #lets see what the original hip delta is, and the corresponding
+                #end bone's delta
+                if endV.length != 0:
+                    linearAvg.append(hipV.length / endV.length)
+
+    action_name = performer_obj.animation_data.action.name
+    #is there a stride_bone?
+    if "stride_bone" in bpy.data.objects:
+        stride_action = bpy.data.actions.new("Stride Bone " + action_name)
+        stride_action.use_fake_user = True
+        stride_bone = enduser_obj.parent
+        stride_bone.animation_data.action = stride_action
+    else:
+        bpy.ops.object.mode_set(mode='OBJECT')
+        bpy.ops.object.add()
+        stride_bone = bpy.context.active_object
+        stride_bone.name = "stride_bone"
+    stride_bone.location = enduser_obj_mat.to_translation()
+    if linearAvg:
+        #determine the average change in scale needed
+        avg = sum(linearAvg) / len(linearAvg)
+        scene.frame_set(s_frame)
+        initialPos = (tailLoc(perf_bones[perfRoot]) / avg)
+        for t in range(s_frame, e_frame):
+            scene.frame_set(t)
+            #calculate the new position, by dividing by the found ratio between performer and enduser
+            newTranslation = (tailLoc(perf_bones[perfRoot]) / avg)
+            stride_bone.location = enduser_obj_mat * (newTranslation - initialPos)
+            stride_bone.keyframe_insert("location")
+    else:
+        stride_bone.keyframe_insert("location")
+    stride_bone.animation_data.action.name = ("Stride Bone " + action_name)
+
+    return stride_bone
+
+
+def IKRetarget(performer_obj, enduser_obj, s_frame, e_frame, scene, step):
+    bpy.ops.object.select_name(name=enduser_obj.name, extend=False)
+    end_bones = enduser_obj.pose.bones
+    for pose_bone in end_bones:
+        ik_constraint = hasIKConstraint(pose_bone)
+        if ik_constraint:
+            target_is_bone = False
+            # set constraint target to corresponding empty if targetless,
+            # if not, keyframe current target to corresponding empty
+            perf_bone = pose_bone.bone.reverseMap[-1].name
+            bpy.ops.object.mode_set(mode='EDIT')
+            orgLocTrg = originalLocationTarget(pose_bone, enduser_obj)
+            bpy.ops.object.mode_set(mode='OBJECT')
+            if not ik_constraint.target:
+                ik_constraint.target = enduser_obj
+                ik_constraint.subtarget = pose_bone.name + "IK"
+                target = orgLocTrg
+
+            # There is a target now
+            if ik_constraint.subtarget:
+                target = ik_constraint.target.pose.bones[ik_constraint.subtarget]
+                target.bone.use_local_location = False
+                target_is_bone = True
+            else:
+                target = ik_constraint.target
+
+            # bake the correct locations for the ik target bones
+            for t in range(s_frame, e_frame, step):
+                scene.frame_set(t)
+                if target_is_bone:
+                    final_loc = pose_bone.tail - target.bone.matrix_local.to_translation()
+                else:
+                    final_loc = pose_bone.tail
+                target.location = final_loc
+                target.keyframe_insert("location")
+            ik_constraint.mute = False
+    scene.frame_set(s_frame)
+    bpy.ops.object.mode_set(mode='OBJECT')
+
+
+def turnOffIK(enduser_obj):
+    end_bones = enduser_obj.pose.bones
+    for pose_bone in end_bones:
+        ik_constraint = hasIKConstraint(pose_bone)
+        if ik_constraint:
+            ik_constraint.mute = True
+
+
+#copy the object matrixes and clear them (to be reinserted later)
+def cleanAndStoreObjMat(performer_obj, enduser_obj):
+    perf_obj_mat = performer_obj.matrix_world.copy()
+    enduser_obj_mat = enduser_obj.matrix_world.copy()
+    zero_mat = Matrix()
+    performer_obj.matrix_world = zero_mat
+    enduser_obj.matrix_world = zero_mat
+    return perf_obj_mat, enduser_obj_mat
+
+
+#restore the object matrixes after parenting the auto generated IK empties
+def restoreObjMat(performer_obj, enduser_obj, perf_obj_mat, enduser_obj_mat, stride_bone, scene, s_frame):
+    pose_bones = enduser_obj.pose.bones
+    for pose_bone in pose_bones:
+        if pose_bone.name + "Org" in bpy.data.objects:
+            empty = bpy.data.objects[pose_bone.name + "Org"]
+            empty.parent = stride_bone
+    performer_obj.matrix_world = perf_obj_mat
+    enduser_obj.parent = stride_bone
+    scene.frame_set(s_frame)
+    enduser_obj_mat = enduser_obj_mat.to_3x3().to_4x4() * Matrix.Translation(stride_bone.matrix_world.to_translation())
+    enduser_obj.matrix_world = enduser_obj_mat
+
+
+#create (or return if exists) the related IK empty to the bone
+def originalLocationTarget(end_bone, enduser_obj):
+    if not end_bone.name + "IK" in enduser_obj.data.bones:
+        newBone = enduser_obj.data.edit_bones.new(end_bone.name + "IK")
+        newBone.head = end_bone.tail
+        newBone.tail = end_bone.tail + Vector((0, 0.1, 0))
+    else:
+        newBone = enduser_obj.pose.bones[end_bone.name + "IK"]
+    return newBone
+
+
+#create the specified NLA setup for base animation, constraints and tweak layer.
+def NLASystemInitialize(enduser_arm, context):
+    enduser_obj = context.active_object
+    NLATracks = enduser_arm.mocapNLATracks[enduser_obj.data.active_mocap]
+    name = NLATracks.name
+    anim_data = enduser_obj.animation_data
+    s_frame = 0
+    if ("Base " + name) in bpy.data.actions:
+        mocapAction = bpy.data.actions[("Base " + name)]
+    else:
+        print("That retargeted anim has no base action")
+    anim_data.use_nla = True
+    for track in anim_data.nla_tracks:
+        anim_data.nla_tracks.remove(track)
+    mocapTrack = anim_data.nla_tracks.new()
+    mocapTrack.name = "Base " + name
+    NLATracks.base_track = mocapTrack.name
+    mocapStrip = mocapTrack.strips.new("Base " + name, s_frame, mocapAction)
+    constraintTrack = anim_data.nla_tracks.new()
+    constraintTrack.name = "Auto fixes " + name
+    NLATracks.auto_fix_track = constraintTrack.name
+    if ("Auto fixes " + name) in bpy.data.actions:
+        constraintAction = bpy.data.actions[("Auto fixes " + name)]
+    else:
+        constraintAction = bpy.data.actions.new("Auto fixes " + name)
+        constraintAction.use_fake_user = True
+    constraintStrip = constraintTrack.strips.new("Auto fixes " + name, s_frame, constraintAction)
+    constraintStrip.extrapolation = "NOTHING"
+    userTrack = anim_data.nla_tracks.new()
+    userTrack.name = "Manual fixes " + name
+    NLATracks.manual_fix_track = userTrack.name
+    if ("Manual fixes " + name) in bpy.data.actions:
+        userAction = bpy.data.actions[("Manual fixes " + name)]
+    else:
+        userAction = bpy.data.actions.new("Manual fixes " + name)
+        userAction.use_fake_user = True
+    userStrip = userTrack.strips.new("Manual fixes " + name, s_frame, userAction)
+    userStrip.extrapolation = "HOLD"
+    userStrip.blend_type = "ADD"
+    anim_data.nla_tracks.active = constraintTrack
+    anim_data.action_extrapolation = "NOTHING"
+    #set the stride_bone's action
+    if "stride_bone" in bpy.data.objects:
+        stride_bone = bpy.data.objects["stride_bone"]
+        if NLATracks.stride_action:
+            stride_bone.animation_data.action = bpy.data.actions[NLATracks.stride_action]
+        else:
+            NLATracks.stride_action = stride_bone.animation_data.action.name
+            stride_bone.animation_data.action.use_fake_user = True
+    anim_data.action = None
+
+
+def preAdvancedRetargeting(performer_obj, enduser_obj):
+    createDictionary(performer_obj.data, enduser_obj.data)
+    bones = enduser_obj.pose.bones
+    map_bones = [bone for bone in bones if bone.bone.reverseMap]
+    perf_root = performer_obj.pose.bones[0].name
+    for bone in map_bones:
+        perf_bone = bone.bone.reverseMap[0].name
+
+        cons = bone.constraints.new('COPY_ROTATION')
+        cons.name = "retargetTemp"
+        locks = bone.lock_rotation
+        cons.use_x = not locks[0]
+        cons.use_y = not locks[1]
+        cons.use_z = not locks[2]
+        cons.target = performer_obj
+        cons.subtarget = perf_bone
+        cons.target_space = 'WORLD'
+        cons.owner_space = 'WORLD'
+
+        if (not bone.bone.use_connect) and (perf_bone != perf_root):
+            cons = bone.constraints.new('COPY_LOCATION')
+            cons.name = "retargetTemp"
+            cons.target = performer_obj
+            cons.subtarget = perf_bone
+            cons.use_x = True
+            cons.use_y = True
+            cons.use_z = True
+            cons.target_space = 'LOCAL'
+            cons.owner_space = 'LOCAL'
+
+
+def prepareForBake(enduser_obj):
+    bones = enduser_obj.pose.bones
+    for bone in bones:
+        bone.bone.select = False
+    map_bones = [bone for bone in bones if bone.bone.reverseMap]
+    for bone in map_bones:
+        for cons in bone.constraints:
+            if "retargetTemp" in cons.name:
+                bone.bone.select = True
+
+
+def cleanTempConstraints(enduser_obj):
+    bones = enduser_obj.pose.bones
+    map_bones = [bone for bone in bones if bone.bone.reverseMap]
+    for bone in map_bones:
+        for cons in bone.constraints:
+            if "retargetTemp" in cons.name:
+                bone.constraints.remove(cons)
+
+
+#Main function that runs the retargeting sequence.
+#If advanced == True, we assume constraint's were already created
+def totalRetarget(performer_obj, enduser_obj, scene, s_frame, e_frame):
+    perf_arm = performer_obj.data
+    end_arm = enduser_obj.data
+    advanced = end_arm.advancedRetarget
+    step = end_arm.frameStep
+
+    try:
+        enduser_obj.animation_data.action = bpy.data.actions.new("temp")
+        enduser_obj.animation_data.action.use_fake_user = True
+    except:
+        print("no need to create new action")
+
+    print("creating Dictionary")
+    feetBones, root = createDictionary(perf_arm, end_arm)
+    print("cleaning stuff up")
+    perf_obj_mat, enduser_obj_mat = cleanAndStoreObjMat(performer_obj, enduser_obj)
+    if not advanced:
+        turnOffIK(enduser_obj)
+        print("Creating intermediate armature (for first pass)")
+        inter_obj = createIntermediate(performer_obj, enduser_obj, root, s_frame, e_frame, scene, step)
+        print("First pass: retargeting from intermediate to end user")
+        retargetEnduser(inter_obj, enduser_obj, root, s_frame, e_frame, scene, step)
+    else:
+        prepareForBake(enduser_obj)
+        print("Retargeting pose (Advanced Retarget)")
+        nla.bake(s_frame, e_frame, action=enduser_obj.animation_data.action, only_selected=True, do_pose=True, do_object=False, step=step)
+    name = performer_obj.animation_data.action.name
+    enduser_obj.animation_data.action.name = "Base " + name
+    print("Second pass: retargeting root translation and clean up")
+    stride_bone = copyTranslation(performer_obj, enduser_obj, feetBones, root, s_frame, e_frame, scene, enduser_obj_mat)
+    if not advanced:
+        IKRetarget(performer_obj, enduser_obj, s_frame, e_frame, scene, step)
+        bpy.ops.object.select_name(name=stride_bone.name, extend=False)
+    restoreObjMat(performer_obj, enduser_obj, perf_obj_mat, enduser_obj_mat, stride_bone, scene, s_frame)
+    bpy.ops.object.mode_set(mode='OBJECT')
+    if not advanced:
+        bpy.ops.object.select_name(name=inter_obj.name, extend=False)
+        bpy.ops.object.delete()
+    else:
+        cleanTempConstraints(enduser_obj)
+    bpy.ops.object.select_name(name=enduser_obj.name, extend=False)
+
+    if not name in [tracks.name for tracks in end_arm.mocapNLATracks]:
+        NLATracks = end_arm.mocapNLATracks.add()
+        NLATracks.name = name
+    else:
+        NLATracks = end_arm.mocapNLATracks[name]
+    end_arm.active_mocap = name
+    print("retargeting done!")
+
+
+def isRigAdvanced(enduser_obj):
+    bones = enduser_obj.pose.bones
+    for bone in bones:
+        for constraint in bone.constraints:
+            if constraint.type != "IK":
+                return True
+        if enduser_obj.data.animation_data:
+            if enduser_obj.data.animation_data.drivers:
+                return True