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Add basic 4x4 matrix "class" (for b3d to glTF)
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1
init.lua
1
init.lua
@ -11,6 +11,7 @@ for _, file in pairs{
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"text",
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"utf8",
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"vector",
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"matrix4",
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"quaternion",
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"trie",
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"kdtree",
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167
matrix4.lua
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167
matrix4.lua
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@ -0,0 +1,167 @@
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-- Simple 4x4 matrix for 3d transformations (translation, rotation, scale);
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-- provides exactly the methods needed to calculate inverse bind matrices (for b3d -> glTF conversion)
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local mat4 = {}
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local metatable = {__index = mat4}
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function mat4.new(rows)
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assert(#rows == 4)
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for i = 1, 4 do
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assert(#rows[i] == 4)
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end
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return setmetatable(rows, metatable)
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end
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function mat4.identity()
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return mat4.new{
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{1, 0, 0, 0},
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{0, 1, 0, 0},
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{0, 0, 1, 0},
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{0, 0, 0, 1},
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}
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end
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-- Matrices can't properly represent translation:
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-- => work with 4d vectors, assume w = 1.
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function mat4.translation(vec)
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assert(#vec == 3)
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local x, y, z = unpack(vec)
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return mat4.new{
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{1, 0, 0, x},
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{0, 1, 0, y},
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{0, 0, 1, z},
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{0, 0, 0, 1},
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}
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end
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-- See https://en.wikipedia.org/wiki/Quaternions_and_spatial_rotation
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function mat4.rotation(unit_quat)
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assert(#unit_quat == 4)
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local x, y, z, w = unpack(unit_quat) -- TODO (?) assert unit quaternion
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return mat4.new{
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{1 - 2*(y^2 + z^2), 2*(x*y - z*w), 2*(x*z + y*w), 0},
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{2*(x*y + z*w), 1 - 2*(x^2 + z^2), 2*(y*z - x*w), 0},
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{2*(x*z - y*w), 2*(y*z + x*w), 1 - 2*(x^2 + y^2), 0},
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{0, 0, 0, 1},
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}
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end
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function mat4.scale(vec)
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assert(#vec == 3)
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local x, y, z = unpack(vec)
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return mat4.new{
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{x, 0, 0, 0},
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{0, y, 0, 0},
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{0, 0, z, 0},
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{0, 0, 0, 1},
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}
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end
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-- Multiplication: First apply other, then self
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function mat4:multiply(other)
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local res = {}
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for i = 1, 4 do
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res[i] = {}
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for j = 1, 4 do
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local sum = 0 -- dot product of row & col vec
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for k = 1, 4 do
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sum = sum + self[i][k] * other[k][j]
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end
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res[i][j] = sum
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end
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end
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return mat4.new(res)
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end
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-- Composition: First apply self, then other
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function mat4:compose(other)
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return other:multiply(self) -- equivalent to `other * self` in terms of matrix multiplication
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end
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-- Matrix inversion using Gauss-Jordan elimination
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do
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-- Fundamental operations
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local function _swap_rows(mat, i, j)
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mat[i], mat[j] = mat[j], mat[i]
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end
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local function _scale_row(mat, factor, row_idx)
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for i = 1, 4 do
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mat[row_idx][i] = factor * mat[row_idx][i]
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end
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end
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local function _add_row_with_factor(mat, factor, src_row_idx, dst_row_idx)
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assert(src_row_idx ~= dst_row_idx)
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for i = 1, 4 do
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mat[dst_row_idx][i] = mat[dst_row_idx][i] + factor * mat[src_row_idx][i]
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end
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end
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local epsilon = 1e-6 -- small threshold; values below this are considered zero
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function mat4:inverse()
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local inv = mat4.identity() -- inverse matrix: all elimination operations will also be applied to this
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local copy = {} -- copy of `self` the Gaussian elimination is being executed on
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for i = 1, 4 do
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copy[i] = {}
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for j = 1, 4 do
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copy[i][j] = self[i][j]
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end
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end
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-- All operations must be mirrored to the inverse matrix
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local function swap_rows(i, j)
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_swap_rows(copy, i, j)
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_swap_rows(inv, i, j)
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end
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local function scale_row(factor, row_idx)
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_scale_row(copy, factor, row_idx)
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_scale_row(inv, factor, row_idx)
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end
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local function add_with_factor(factor, src_row_idx, dst_row_idx)
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_add_row_with_factor(copy, factor, src_row_idx, dst_row_idx)
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_add_row_with_factor(inv, factor, src_row_idx, dst_row_idx)
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end
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-- Elimination phase
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for col_idx = 1, 4 do
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-- Find a pivot row: Choose the row with the largest absolute component
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local max_row_idx = col_idx
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local max_abs_comp = math.abs(copy[max_row_idx][col_idx])
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for row_idx = col_idx, 4 do
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local cand_comp = math.abs(copy[row_idx][col_idx])
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if cand_comp > max_abs_comp then
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max_row_idx, max_abs_comp = row_idx, cand_comp
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end
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end
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-- Assert that there is a row that has this component "nonzero"
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assert(max_abs_comp >= epsilon, "matrix not invertible!")
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swap_rows(col_idx, max_row_idx) -- swap row to correct position
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-- Eliminate the `col_idx`-th component in all rows *below* the pivot row
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local pivot_value = copy[col_idx][col_idx]
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for row_idx = col_idx + 1, 4 do
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local factor = -copy[row_idx][col_idx] / pivot_value
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add_with_factor(factor, col_idx, row_idx)
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assert(math.abs(copy[row_idx][col_idx]) < epsilon) -- should be eliminated now
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end
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end
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-- Resubstitution phase - pretty much the same but in reverse and without swapping
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for col_idx = 4, 1, -1 do
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local pivot_value = copy[col_idx][col_idx]
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-- Eliminate the `col_idx`-th component in all rows *above* the pivot row
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for row_idx = col_idx - 1, 1, -1 do
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local factor = -copy[row_idx][col_idx] / pivot_value
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add_with_factor(factor, col_idx, row_idx)
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assert(math.abs(copy[row_idx][col_idx]) < epsilon) -- should be eliminated now
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end
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scale_row(1/pivot_value, col_idx) -- normalize row
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end
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-- Done: `copy` should now be the identity matrix <=> `inv` is the inverse.
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return inv
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end
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end
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return mat4
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