Differential D3746 Diff 11996 mocap/mocap_tools.py

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mocap/mocap_tools.py

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	context.scene.frame_end = flm	context.scene.frame_end = flm


	#simplifyCurves: performes the bulk of the samples to bezier conversion.	#simplifyCurves: performs the bulk of the samples to bezier conversion.
	#IN: curveGroup - which can be a collection of singleFcurves, or grouped (via nested lists) .	#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	# 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.	# 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).	# maxIterations - maximum number of iterations of reparameterizations we should attempt. (Newton-Rahpson is not guaranteed 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.	# group_mode - boolean, indicating whether 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.	#OUT: None. Deletes the existing curves and creates the new beziers.
	def simplifyCurves(curveGroup, error, reparaError, maxIterations, group_mode):	def simplifyCurves(curveGroup, error, reparaError, maxIterations, group_mode):
	#Calculates the unit tangent of point v	#Calculates the unit tangent of point v
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	sumVec += (bez[i + 1] - bez[i]) * bernsteinPoly(n - 1, i, t)	sumVec += (bez[i + 1] - bez[i]) * bernsteinPoly(n - 1, i, t)
	return sumVec	return sumVec

	#use Newton-Raphson to find a better paramterization of datapoints,	#use Newton-Raphson to find a better parameterization of datapoints,
	#one that minimizes the distance (or error)	#one that minimizes the distance (or error)
	# between bezier and original data.	# between bezier and original data.
	def newtonRaphson(data_pts, s, e, bez):	def newtonRaphson(data_pts, s, e, bez):
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	# sel_opt- either "sel" (selected) or "all" for which curves to effect	# 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),	# error- maximum error allowed, in fraction (20% = 0.0020, which is the default),
	# i.e. divide by 10000 from percentage wanted.	# i.e. divide by 10000 from percentage wanted.
	# group_mode- boolean, to analyze each curve seperately or in groups,	# group_mode- boolean, to analyze each curve separately or in groups,
	# where a group is all curves that effect the same property/RNA path	# 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):	def fcurves_simplify(context, obj, sel_opt="all", error=0.002, group_mode=True):
	# main vars	# main vars
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	fcurve.update()	fcurve.update()


	# Recieves armature, and rotations all bones by 90 degrees along the X axis	# Receives armature, and rotations all bones by 90 degrees along the X axis
	# This fixes the common axis issue BVH files have when importing.	# This fixes the common axis issue BVH files have when importing.
	# IN: Armature (bpy.types.Armature)	# IN: Armature (bpy.types.Armature)
	def rotate_fix_armature(arm_data):	def rotate_fix_armature(arm_data):
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	#Guess Mapping	#Guess Mapping
	#Given a performer and enduser armature, attempts to guess the hiearchy mapping	#Given a performer and enduser armature, attempts to guess the hierarchy mapping
	def guessMapping(performer_obj, enduser_obj):	def guessMapping(performer_obj, enduser_obj):
	perf_bones = performer_obj.data.bones	perf_bones = performer_obj.data.bones
	end_bones = enduser_obj.data.bones	end_bones = enduser_obj.data.bones
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	return "", bone	return "", bone

	def nameMatch(bone_a, bone_b):	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	# nameMatch - receives 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_a, noside_a = findBoneSide(bone_a)
	side_b, noside_b = findBoneSide(bone_b)	side_b, noside_b = findBoneSide(bone_b)
	if side_a == side_b:	if side_a == side_b:
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