general.odin 9.6 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362
  1. package linalg
  2. import "core:math"
  3. import "core:intrinsics"
  4. // Generic
  5. TAU :: 6.28318530717958647692528676655900576
  6. PI :: 3.14159265358979323846264338327950288
  7. E :: 2.71828182845904523536
  8. τ :: TAU
  9. π :: PI
  10. e :: E
  11. SQRT_TWO :: 1.41421356237309504880168872420969808
  12. SQRT_THREE :: 1.73205080756887729352744634150587236
  13. SQRT_FIVE :: 2.23606797749978969640917366873127623
  14. LN2 :: 0.693147180559945309417232121458176568
  15. LN10 :: 2.30258509299404568401799145468436421
  16. MAX_F64_PRECISION :: 16 // Maximum number of meaningful digits after the decimal point for 'f64'
  17. MAX_F32_PRECISION :: 8 // Maximum number of meaningful digits after the decimal point for 'f32'
  18. RAD_PER_DEG :: TAU/360.0
  19. DEG_PER_RAD :: 360.0/TAU
  20. @private IS_NUMERIC :: intrinsics.type_is_numeric
  21. @private IS_QUATERNION :: intrinsics.type_is_quaternion
  22. @private IS_ARRAY :: intrinsics.type_is_array
  23. @private IS_FLOAT :: intrinsics.type_is_float
  24. @private BASE_TYPE :: intrinsics.type_base_type
  25. @private ELEM_TYPE :: intrinsics.type_elem_type
  26. scalar_dot :: proc(a, b: $T) -> T where IS_FLOAT(T), !IS_ARRAY(T) {
  27. return a * b
  28. }
  29. vector_dot :: proc(a, b: $T/[$N]$E) -> (c: E) where IS_NUMERIC(E) #no_bounds_check {
  30. for i in 0..<N {
  31. c += a[i] * b[i]
  32. }
  33. return
  34. }
  35. quaternion64_dot :: proc(a, b: $T/quaternion64) -> (c: f16) {
  36. return a.w*a.w + a.x*b.x + a.y*b.y + a.z*b.z
  37. }
  38. quaternion128_dot :: proc(a, b: $T/quaternion128) -> (c: f32) {
  39. return a.w*a.w + a.x*b.x + a.y*b.y + a.z*b.z
  40. }
  41. quaternion256_dot :: proc(a, b: $T/quaternion256) -> (c: f64) {
  42. return a.w*a.w + a.x*b.x + a.y*b.y + a.z*b.z
  43. }
  44. dot :: proc{scalar_dot, vector_dot, quaternion64_dot, quaternion128_dot, quaternion256_dot}
  45. inner_product :: dot
  46. outer_product :: proc(a: $A/[$M]$E, b: $B/[$N]E) -> (out: [M][N]E) where IS_NUMERIC(E) #no_bounds_check {
  47. for i in 0..<M {
  48. for j in 0..<N {
  49. out[i][j] = a[i]*b[j]
  50. }
  51. }
  52. return
  53. }
  54. quaternion_inverse :: proc(q: $Q) -> Q where IS_QUATERNION(Q) {
  55. return conj(q) * quaternion(1.0/dot(q, q), 0, 0, 0)
  56. }
  57. scalar_cross :: proc(a, b: $T) -> T where IS_FLOAT(T), !IS_ARRAY(T) {
  58. return a * b
  59. }
  60. vector_cross2 :: proc(a, b: $T/[2]$E) -> E where IS_NUMERIC(E) {
  61. return a[0]*b[1] - b[0]*a[1]
  62. }
  63. vector_cross3 :: proc(a, b: $T/[3]$E) -> (c: T) where IS_NUMERIC(E) {
  64. c[0] = a[1]*b[2] - b[1]*a[2]
  65. c[1] = a[2]*b[0] - b[2]*a[0]
  66. c[2] = a[0]*b[1] - b[0]*a[1]
  67. return
  68. }
  69. quaternion_cross :: proc(q1, q2: $Q) -> (q3: Q) where IS_QUATERNION(Q) {
  70. q3.x = q1.w * q2.x + q1.x * q2.w + q1.y * q2.z - q1.z * q2.y
  71. q3.y = q1.w * q2.y + q1.y * q2.w + q1.z * q2.x - q1.x * q2.z
  72. q3.z = q1.w * q2.z + q1.z * q2.w + q1.x * q2.y - q1.y * q2.x
  73. q3.w = q1.w * q2.w - q1.x * q2.x - q1.y * q2.y - q1.z * q2.z
  74. return
  75. }
  76. vector_cross :: proc{scalar_cross, vector_cross2, vector_cross3}
  77. cross :: proc{scalar_cross, vector_cross2, vector_cross3, quaternion_cross}
  78. vector_normalize :: proc(v: $T/[$N]$E) -> T where IS_NUMERIC(E) {
  79. return v / length(v)
  80. }
  81. quaternion_normalize :: proc(q: $Q) -> Q where IS_QUATERNION(Q) {
  82. return q/abs(q)
  83. }
  84. normalize :: proc{vector_normalize, quaternion_normalize}
  85. vector_normalize0 :: proc(v: $T/[$N]$E) -> T where IS_NUMERIC(E) {
  86. m := length(v)
  87. return 0 if m == 0 else v/m
  88. }
  89. quaternion_normalize0 :: proc(q: $Q) -> Q where IS_QUATERNION(Q) {
  90. m := abs(q)
  91. return 0 if m == 0 else q/m
  92. }
  93. normalize0 :: proc{vector_normalize0, quaternion_normalize0}
  94. vector_length :: proc(v: $T/[$N]$E) -> E where IS_NUMERIC(E) {
  95. return math.sqrt(dot(v, v))
  96. }
  97. vector_length2 :: proc(v: $T/[$N]$E) -> E where IS_NUMERIC(E) {
  98. return dot(v, v)
  99. }
  100. quaternion_length :: proc(q: $Q) -> Q where IS_QUATERNION(Q) {
  101. return abs(q)
  102. }
  103. quaternion_length2 :: proc(q: $Q) -> Q where IS_QUATERNION(Q) {
  104. return dot(q, q)
  105. }
  106. scalar_triple_product :: proc(a, b, c: $T/[$N]$E) -> E where IS_NUMERIC(E) {
  107. // a . (b x c)
  108. // b . (c x a)
  109. // c . (a x b)
  110. return dot(a, cross(b, c))
  111. }
  112. vector_triple_product :: proc(a, b, c: $T/[$N]$E) -> T where IS_NUMERIC(E) {
  113. // a x (b x c)
  114. // (a . c)b - (a . b)c
  115. return cross(a, cross(b, c))
  116. }
  117. length :: proc{vector_length, quaternion_length}
  118. length2 :: proc{vector_length2, quaternion_length2}
  119. projection :: proc(x, normal: $T/[$N]$E) -> T where IS_NUMERIC(E) {
  120. return dot(x, normal) / dot(normal, normal) * normal
  121. }
  122. identity :: proc($T: typeid/[$N][N]$E) -> (m: T) #no_bounds_check {
  123. for i in 0..<N {
  124. m[i][i] = E(1)
  125. }
  126. return m
  127. }
  128. trace :: proc(m: $T/[$N][N]$E) -> (tr: E) {
  129. for i in 0..<N {
  130. tr += m[i][i]
  131. }
  132. return
  133. }
  134. transpose :: proc(a: $T/[$N][$M]$E) -> (m: (T when N == M else [M][N]E)) #no_bounds_check {
  135. for j in 0..<M {
  136. for i in 0..<N {
  137. m[j][i] = a[i][j]
  138. }
  139. }
  140. return
  141. }
  142. matrix_mul :: proc(a, b: $M/[$N][N]$E) -> (c: M)
  143. where !IS_ARRAY(E), IS_NUMERIC(E) #no_bounds_check {
  144. for i in 0..<N {
  145. for k in 0..<N {
  146. for j in 0..<N {
  147. c[k][i] += a[j][i] * b[k][j]
  148. }
  149. }
  150. }
  151. return
  152. }
  153. matrix_comp_mul :: proc(a, b: $M/[$J][$I]$E) -> (c: M)
  154. where !IS_ARRAY(E), IS_NUMERIC(E) #no_bounds_check {
  155. for j in 0..<J {
  156. for i in 0..<I {
  157. c[j][i] = a[j][i] * b[j][i]
  158. }
  159. }
  160. return
  161. }
  162. matrix_mul_differ :: proc(a: $A/[$J][$I]$E, b: $B/[$K][J]E) -> (c: [K][I]E)
  163. where !IS_ARRAY(E), IS_NUMERIC(E), I != K #no_bounds_check {
  164. for k in 0..<K {
  165. for j in 0..<J {
  166. for i in 0..<I {
  167. c[k][i] += a[j][i] * b[k][j]
  168. }
  169. }
  170. }
  171. return
  172. }
  173. matrix_mul_vector :: proc(a: $A/[$I][$J]$E, b: $B/[I]E) -> (c: B)
  174. where !IS_ARRAY(E), IS_NUMERIC(E) #no_bounds_check {
  175. for i in 0..<I {
  176. for j in 0..<J {
  177. c[j] += a[i][j] * b[i]
  178. }
  179. }
  180. return
  181. }
  182. quaternion_mul_quaternion :: proc(q1, q2: $Q) -> Q where IS_QUATERNION(Q) {
  183. return q1 * q2
  184. }
  185. quaternion64_mul_vector3 :: proc(q: $Q/quaternion64, v: $V/[3]$F/f16) -> V {
  186. Raw_Quaternion :: struct {xyz: [3]f16, r: f16}
  187. q := transmute(Raw_Quaternion)q
  188. v := transmute([3]f16)v
  189. t := cross(2*q.xyz, v)
  190. return V(v + q.r*t + cross(q.xyz, t))
  191. }
  192. quaternion128_mul_vector3 :: proc(q: $Q/quaternion128, v: $V/[3]$F/f32) -> V {
  193. Raw_Quaternion :: struct {xyz: [3]f32, r: f32}
  194. q := transmute(Raw_Quaternion)q
  195. v := transmute([3]f32)v
  196. t := cross(2*q.xyz, v)
  197. return V(v + q.r*t + cross(q.xyz, t))
  198. }
  199. quaternion256_mul_vector3 :: proc(q: $Q/quaternion256, v: $V/[3]$F/f64) -> V {
  200. Raw_Quaternion :: struct {xyz: [3]f64, r: f64}
  201. q := transmute(Raw_Quaternion)q
  202. v := transmute([3]f64)v
  203. t := cross(2*q.xyz, v)
  204. return V(v + q.r*t + cross(q.xyz, t))
  205. }
  206. quaternion_mul_vector3 :: proc{quaternion64_mul_vector3, quaternion128_mul_vector3, quaternion256_mul_vector3}
  207. mul :: proc{
  208. matrix_mul,
  209. matrix_mul_differ,
  210. matrix_mul_vector,
  211. quaternion64_mul_vector3,
  212. quaternion128_mul_vector3,
  213. quaternion256_mul_vector3,
  214. quaternion_mul_quaternion,
  215. }
  216. vector_to_ptr :: proc(v: ^$V/[$N]$E) -> ^E where IS_NUMERIC(E), N > 0 #no_bounds_check {
  217. return &v[0]
  218. }
  219. matrix_to_ptr :: proc(m: ^$A/[$I][$J]$E) -> ^E where IS_NUMERIC(E), I > 0, J > 0 #no_bounds_check {
  220. return &m[0][0]
  221. }
  222. to_ptr :: proc{vector_to_ptr, matrix_to_ptr}
  223. // Splines
  224. vector_slerp :: proc(x, y: $T/[$N]$E, a: E) -> T {
  225. cos_alpha := dot(x, y)
  226. alpha := math.acos(cos_alpha)
  227. sin_alpha := math.sin(alpha)
  228. t1 := math.sin((1 - a) * alpha) / sin_alpha
  229. t2 := math.sin(a * alpha) / sin_alpha
  230. return x * t1 + y * t2
  231. }
  232. catmull_rom :: proc(v1, v2, v3, v4: $T/[$N]$E, s: E) -> T {
  233. s2 := s*s
  234. s3 := s2*s
  235. f1 := -s3 + 2 * s2 - s
  236. f2 := 3 * s3 - 5 * s2 + 2
  237. f3 := -3 * s3 + 4 * s2 + s
  238. f4 := s3 - s2
  239. return (f1 * v1 + f2 * v2 + f3 * v3 + f4 * v4) * 0.5
  240. }
  241. hermite :: proc(v1, t1, v2, t2: $T/[$N]$E, s: E) -> T {
  242. s2 := s*s
  243. s3 := s2*s
  244. f1 := 2 * s3 - 3 * s2 + 1
  245. f2 := -2 * s3 + 3 * s2
  246. f3 := s3 - 2 * s2 + s
  247. f4 := s3 - s2
  248. return f1 * v1 + f2 * v2 + f3 * t1 + f4 * t2
  249. }
  250. cubic :: proc(v1, v2, v3, v4: $T/[$N]$E, s: E) -> T {
  251. return ((v1 * s + v2) * s + v3) * s + v4
  252. }
  253. array_cast :: proc(v: $A/[$N]$T, $Elem_Type: typeid) -> (w: [N]Elem_Type) #no_bounds_check {
  254. for i in 0..<N {
  255. w[i] = Elem_Type(v[i])
  256. }
  257. return
  258. }
  259. matrix_cast :: proc(v: $A/[$M][$N]$T, $Elem_Type: typeid) -> (w: [M][N]Elem_Type) #no_bounds_check {
  260. for i in 0..<M {
  261. for j in 0..<N {
  262. w[i][j] = Elem_Type(v[i][j])
  263. }
  264. }
  265. return
  266. }
  267. to_f32 :: #force_inline proc(v: $A/[$N]$T) -> [N]f32 { return array_cast(v, f32) }
  268. to_f64 :: #force_inline proc(v: $A/[$N]$T) -> [N]f64 { return array_cast(v, f64) }
  269. to_i8 :: #force_inline proc(v: $A/[$N]$T) -> [N]i8 { return array_cast(v, i8) }
  270. to_i16 :: #force_inline proc(v: $A/[$N]$T) -> [N]i16 { return array_cast(v, i16) }
  271. to_i32 :: #force_inline proc(v: $A/[$N]$T) -> [N]i32 { return array_cast(v, i32) }
  272. to_i64 :: #force_inline proc(v: $A/[$N]$T) -> [N]i64 { return array_cast(v, i64) }
  273. to_int :: #force_inline proc(v: $A/[$N]$T) -> [N]int { return array_cast(v, int) }
  274. to_u8 :: #force_inline proc(v: $A/[$N]$T) -> [N]u8 { return array_cast(v, u8) }
  275. to_u16 :: #force_inline proc(v: $A/[$N]$T) -> [N]u16 { return array_cast(v, u16) }
  276. to_u32 :: #force_inline proc(v: $A/[$N]$T) -> [N]u32 { return array_cast(v, u32) }
  277. to_u64 :: #force_inline proc(v: $A/[$N]$T) -> [N]u64 { return array_cast(v, u64) }
  278. to_uint :: #force_inline proc(v: $A/[$N]$T) -> [N]uint { return array_cast(v, uint) }
  279. to_complex32 :: #force_inline proc(v: $A/[$N]$T) -> [N]complex32 { return array_cast(v, complex32) }
  280. to_complex64 :: #force_inline proc(v: $A/[$N]$T) -> [N]complex64 { return array_cast(v, complex64) }
  281. to_complex128 :: #force_inline proc(v: $A/[$N]$T) -> [N]complex128 { return array_cast(v, complex128) }
  282. to_quaternion64 :: #force_inline proc(v: $A/[$N]$T) -> [N]quaternion64 { return array_cast(v, quaternion64) }
  283. to_quaternion128 :: #force_inline proc(v: $A/[$N]$T) -> [N]quaternion128 { return array_cast(v, quaternion128) }
  284. to_quaternion256 :: #force_inline proc(v: $A/[$N]$T) -> [N]quaternion256 { return array_cast(v, quaternion256) }