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[Closed] Lerp for matrix3 values

 JHN

Is there an existing way to lerp between 2 matrix values or do I have to decompose the PRS values, (s)lerp them and rebuilt the matrix each step?

Thanks,
-Johan

8 Replies
1 Reply
(@denist)
Joined: 1 year ago

Posts: 0

there is no lerp for matrices. use lerp for rotation (in quaternions), and average for position and scale.

 JHN

Found a thread about it : http://forums.cgsociety.org/showthread.php?f=98&t=859470

Thanks,
-Johan

Just saw your 2nd post but I’ll post my solution anyhow…

(
	fn lerp matArray weights =
	(
		local resMat = matrix3 [0,0,0] [0,0,0] [0,0,0] [0,0,0]
		for i = 1 to matArray.count do (
			local w = weights[i]
			local intMat = matrix3 [w,0,0] [0,w,0] [0,0,w] [w,w,w]
			resMat += matArray[i] * intMat
		)
		
		resMat
	)
	
	if selection.count == 3 then (
		local a = $[1]
		local b = $[2]
		local c = $[3]
		local d = copy a
		
		d.transform = lerp #(a.transform, b.transform, c.transform) #(0.5, 0.5, 0.5)
	) else
		messageBox "Please select 3 objects!"
)
 JHN

@ Matan : Thanks, I’m using something else since I just need to blend between 2 matrices (making a pose tool for CAT). Will test you code as it looks more compact.

@ Denis : I’m using a slightly modified variant on your code

fn blendMatrix m1: m2: weight:0.5 =
(
	fn dotQuat q q_prev =
	( 
		(q.w * q_prev.w + q.x * q_prev.x + q.y * q_prev.y + q.z * q_prev.z) < 0 
	)	
	
	r1 = m1.rotationpart
	r2 = m2.rotationpart
	if (dotQuat r1 r2) do r1 *=-1
	
	r = slerp (normalize r1) (normalize r2) weight
	t = m1.translationpart + (m2.translationpart - m1.translationpart) * weight
	s = m1.scalepart + (m2.scalepart - m1.scalepart) * weight
	translate (rotate (scale (matrix3 1) s true) r) t  -- ignores scale
)				

 

I added the scale averaging, and encapsulated the dotQuat fn.

Thanks!
-Johan

 JHN

@Matan, does it work between 2 transforms. I tried:


for i = 1 to 10 do point transform:(lerpM #($[1].transform, $[2].transform) #((i/10.), (1 - (i/10))))

Between 2 objects that are transformed differently, but the results are not good. How does your function work with 2 matrices?

Thanks,
-Johan

it won’t work correct if the weights don’t sum up to exactly 1.0
here is an example of what you tried to do:

local a = $[1]
local b = $[2]
local n = 10

for i = 1 to n - 1 do (
	local c = copy a
	local w = 1.0 * i / n
	c.transform = lerp #(a.transform, b.transform) #(w, 1.0 - w)
)

EDIT:
just playing around with it, here is another nice test:

(
	fn lerp matArray weights =
	(
		local resMat = matrix3 [0,0,0] [0,0,0] [0,0,0] [0,0,0]
		for i = 1 to matArray.count do (
			local w = weights[i]
			local intMat = matrix3 [w,0,0] [0,w,0] [0,0,w] [w,w,w]
			resMat += matArray[i] * intMat
		)
		
		resMat
	)
	
	local a = teapot transform:(matrix3 [0.543478,1.19095,-0.738627] [-1.22502,0.788501,0.370005] [1.21654,0.836836,2.24443] [204.994,154.378,224.798]) wirecolor:red
	local b = teapot transform:(matrix3 [1,0,0] [0,1,0] [0,0,1] [122.507,3.13654,0]) wirecolor:green
	local c = teapot transform:(matrix3 [1.06301,0.5229,0.250736] [-0.301877,-0.31541,1.93761] [0.425891,-0.832628,-0.0691843] [288.803,-141.283,52.8861]) wirecolor:blue
	local n = 10
	
	for j = 0 to n do (
		local w1 = 1.0 * j / n
		for i = 0 to n do (
			local d = copy a
			local w2 = (1.0 - w1) * i / n
			local w3 = 1.0 - w1 - w2
			d.transform = lerp #(a.transform, b.transform, c.transform) #(w1, w2, w3)
			d.wireColor = a.wireColor * w1 + b.wireColor * w2 + c.wireColor * w3
		)
	)
)
 JHN

I went wrong because my code produced an integer as weight instead of a float. But still your solution is not as good because the scale of the matrix is not avaraged, but get’s distorted. So I’m sticking with my (Denis’ actually) code. But there’s some nice motion design effects to be made with your code!

Thanks,
-Johan

 eek

local matrices = #((matrix3 1), ((eulerangles 0 45 32) as matrix3), (transMatrix [50,40,10]))

local mc = for each in matrices collect each
local tmp = #()
local t = 0.5

while mc.count > 1 do
(
  for i = 1 to (mc.count-1) do
  (
       append tmp ((slerp mc[i].rotation mc[i+1].rotation t) as matrix3 * transMatrix((1-t) * mc[i].row4 + mc[i+1].row4 * t))
  )
  mc = tmp
  tmp = #()
)
mc[1]


This is a quadratic form of blending between multiple matrices roughly.