diff options
author | Alexander Gavrilov <angavrilov@gmail.com> | 2018-11-06 21:04:53 +0300 |
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committer | Alexander Gavrilov <angavrilov@gmail.com> | 2018-11-06 21:20:17 +0300 |
commit | f600b4bc67667b867899cac3725ac7ed44bfbfe3 (patch) | |
tree | 145927ae29bd2e5fe2b09228176a9644f143db6f /source/blender/blenlib/intern/math_solvers.c | |
parent | 0709fac41ef0a20955069fcd6609577189e96d5c (diff) |
Shrinkwrap: new mode that projects along the target normal.
The Nearest Surface Point shrink method, while fast, is neither
smooth nor continuous: as the source point moves, the projected
point can both stop and jump. This causes distortions in the
deformation of the shrinkwrap modifier, and the motion of an
animated object with a shrinkwrap constraint.
This patch implements a new mode, which, instead of using the simple
nearest point search, iteratively solves an equation for each triangle
to find a point which has its interpolated normal point to or from the
original vertex. Non-manifold boundary edges are treated as infinitely
thin cylinders that cast normals in all perpendicular directions.
Since this is useful for the constraint, and having multiple
objects with constraints targeting the same guide mesh is a quite
reasonable use case, rather than calculating the mesh boundary edge
data over and over again, it is precomputed and cached in the mesh.
Reviewers: mont29
Differential Revision: https://developer.blender.org/D3836
Diffstat (limited to 'source/blender/blenlib/intern/math_solvers.c')
-rw-r--r-- | source/blender/blenlib/intern/math_solvers.c | 95 |
1 files changed, 95 insertions, 0 deletions
diff --git a/source/blender/blenlib/intern/math_solvers.c b/source/blender/blenlib/intern/math_solvers.c index e3174d8340a..7b9727ead8e 100644 --- a/source/blender/blenlib/intern/math_solvers.c +++ b/source/blender/blenlib/intern/math_solvers.c @@ -179,3 +179,98 @@ bool BLI_tridiagonal_solve_cyclic(const float *a, const float *b, const float *c return success; } + +/** + * \brief Solve a generic f(x) = 0 equation using Newton's method. + * + * \param func_delta Callback computing the value of f(x). + * \param func_jacobian Callback computing the Jacobian matrix of the function at x. + * \param func_correction Callback for forcing the search into an arbitrary custom domain. May be NULL. + * \param userdata Data for the callbacks. + * \param epsilon Desired precision. + * \param max_iterations Limit on the iterations. + * \param max_corrections Limit on the number of times the correction callback can fire before giving up. + * \param trace Enables logging to console. + * \param x_init Initial solution vector. + * \param result Final result. + * \return true if success + */ +bool BLI_newton3d_solve( + Newton3D_DeltaFunc func_delta, Newton3D_JacobianFunc func_jacobian, Newton3D_CorrectionFunc func_correction, void *userdata, + float epsilon, int max_iterations, bool trace, const float x_init[3], float result[3]) +{ + float fdelta[3], fdeltav, next_fdeltav; + float jacobian[3][3], step[3], x[3], x_next[3]; + + epsilon *= epsilon; + + copy_v3_v3(x, x_init); + + func_delta(userdata, x, fdelta); + fdeltav = len_squared_v3(fdelta); + + if (trace) { + printf("START (%g, %g, %g) %g\n", x[0], x[1], x[2], fdeltav); + } + + for (int i = 0; i < max_iterations && fdeltav > epsilon; i++) { + /* Newton's method step. */ + func_jacobian(userdata, x, jacobian); + + if (!invert_m3(jacobian)) { + return false; + } + + mul_v3_m3v3(step, jacobian, fdelta); + sub_v3_v3v3(x_next, x, step); + + /* Custom out-of-bounds value correction. */ + if (func_correction) { + if (trace) { + printf("%3d * (%g, %g, %g)\n", i, x_next[0], x_next[1], x_next[2]); + } + + if (!func_correction(userdata, x, step, x_next)) { + return false; + } + } + + func_delta(userdata, x_next, fdelta); + next_fdeltav = len_squared_v3(fdelta); + + if (trace) { + printf("%3d ? (%g, %g, %g) %g\n", i, x_next[0], x_next[1], x_next[2], next_fdeltav); + } + + /* Line search correction. */ + while (next_fdeltav > fdeltav) { + float g0 = sqrtf(fdeltav), g1 = sqrtf(next_fdeltav); + float g01 = -g0 / len_v3(step); + float det = 2.0f * (g1 - g0 - g01); + float l = (det == 0.0f) ? 0.1f : -g01 / det; + CLAMP_MIN(l, 0.1f); + + mul_v3_fl(step, l); + sub_v3_v3v3(x_next, x, step); + + func_delta(userdata, x_next, fdelta); + next_fdeltav = len_squared_v3(fdelta); + + if (trace) { + printf("%3d . (%g, %g, %g) %g\n", i, x_next[0], x_next[1], x_next[2], next_fdeltav); + } + } + + copy_v3_v3(x, x_next); + fdeltav = next_fdeltav; + } + + bool success = (fdeltav <= epsilon); + + if (trace) { + printf("%s (%g, %g, %g) %g\n", success ? "OK " : "FAIL", x[0], x[1], x[2], fdeltav); + } + + copy_v3_v3(result, x); + return success; +} |