diff options
Diffstat (limited to 'third_party/skcms/src/GaussNewton.c')
| -rw-r--r-- | third_party/skcms/src/GaussNewton.c | 18 |
1 files changed, 5 insertions, 13 deletions
diff --git a/third_party/skcms/src/GaussNewton.c b/third_party/skcms/src/GaussNewton.c index 5bbc64475d..efbda240a4 100644 --- a/third_party/skcms/src/GaussNewton.c +++ b/third_party/skcms/src/GaussNewton.c @@ -12,18 +12,14 @@ #include <assert.h> #include <string.h> -bool skcms_gauss_newton_step(float (* t)(float x, const void*), - const void* t_ctx, - float (* f)(float x, const void*, const float P[3]), - const void* f_ctx, - void (*grad_f)(float x, const void*, const float P[3], float dfdP[3]), - const void* g_ctx, +bool skcms_gauss_newton_step(float (*rg)(float x, const void*, const float P[3], float dfdP[3]), + const void* ctx, float P[3], float x0, float x1, int N) { // We'll sample x from the range [x0,x1] (both inclusive) N times with even spacing. // // We want to do P' = P + (Jf^T Jf)^-1 Jf^T r(P), - // where r(P) is the residual vector t(x) - f(x,P) + // where r(P) is the residual vector // and Jf is the Jacobian matrix of f(), ∂r/∂P. // // Let's review the shape of each of these expressions: @@ -63,10 +59,8 @@ bool skcms_gauss_newton_step(float (* t)(float x, const void*), for (int i = 0; i < N; i++) { float x = x0 + i*dx; - float resid = t(x,t_ctx) - f(x,f_ctx,P); - float dfdP[3] = {0,0,0}; - grad_f(x,g_ctx,P, dfdP); + float resid = rg(x,ctx,P, dfdP); for (int r = 0; r < 3; r++) { for (int c = 0; c < 3; c++) { @@ -99,9 +93,7 @@ bool skcms_gauss_newton_step(float (* t)(float x, const void*), return true; } -float skcms_eval_curve(float x, const void* vctx) { - const skcms_Curve* curve = (const skcms_Curve*)vctx; - +float skcms_eval_curve(float x, const skcms_Curve* curve) { if (curve->table_entries == 0) { return skcms_TransferFunction_eval(&curve->parametric, x); } |