Commit: 2ace45220db036c448c223286926e1526165fc5d
Author: over0219
Date: Wed Jun 10 14:46:02 2020 -0500
Branches: soc-2020-soft-body
https://developer.blender.org/rB2ace45220db036c448c223286926e1526165fc5d
cache working but lots of copies
===================================================================
M extern/softbody/src/admmpd_energy.h
M extern/softbody/src/admmpd_solver.cpp
M extern/softbody/src/admmpd_solver.h
M intern/softbody/admmpd_api.cpp
M intern/softbody/admmpd_api.h
M source/blender/blenkernel/intern/softbody.c
===================================================================
diff --git a/extern/softbody/src/admmpd_energy.h
b/extern/softbody/src/admmpd_energy.h
index 4245c9cff9c..e58ba36a9e7 100644
--- a/extern/softbody/src/admmpd_energy.h
+++ b/extern/softbody/src/admmpd_energy.h
@@ -12,7 +12,7 @@ namespace admmpd {
class Lame {
public:
- int m_model;
+ int m_model; // 0=ARAP
double m_mu;
double m_lambda;
double m_bulk_mod;
diff --git a/extern/softbody/src/admmpd_solver.cpp
b/extern/softbody/src/admmpd_solver.cpp
index ad64e4ed277..4756cb76fac 100644
--- a/extern/softbody/src/admmpd_solver.cpp
+++ b/extern/softbody/src/admmpd_solver.cpp
@@ -52,15 +52,19 @@ int Solver::solve(
int iters = 0;
for (; iters < options->max_admm_iters; ++iters)
{
-
+ // Update ADMM z/u
solve_local_step(options,data);
+
+ // Perform collision detection and linearization
update_constraints(options,data);
+ // Solve Ax=b s.t. Kx=l
data->b.noalias() = data->M_xbar + data->DtW2*(data->z-data->u);
solve_conjugate_gradients(options,data);
} // end solver iters
+ // Update velocity (if not static solve)
double dt = options->timestep_s;
if (dt > 0.0)
data->v.noalias() = (data->x-data->x_start)*(1.0/dt);
@@ -99,8 +103,9 @@ static void parallel_zu_update(
const int i,
const TaskParallelTLS *__restrict UNUSED(tls))
{
- Lame lame; // TODO lame params as input
ThreadData *td = (ThreadData*)userdata;
+ Lame lame;
+ lame.set_from_youngs_poisson(td->options->youngs,td->options->poisson);
EnergyTerm().update(
td->data->indices[i][0],
lame,
@@ -222,47 +227,53 @@ void Solver::solve_conjugate_gradients(
return dot;
};
+ // Update CGData
+ admmpd::Data::CGData *cgdata = &data->cgdata;
double eps = options->min_res;
- MatrixXd b = data->b;
- int nv = b.rows();
- RowSparseMatrix<double> A[3];
- MatrixXd r(b.rows(),3);
- MatrixXd z(nv,3);
- MatrixXd p(nv,3);
- MatrixXd Ap(nv,3);
+ cgdata->b = data->b;
+ int nv = data->b.rows();
+ if (cgdata->r.rows() !=nv)
+ {
+ cgdata->r.resize(nv,3);
+ cgdata->z.resize(nv,3);
+ cgdata->p.resize(nv,3);
+ cgdata->Ap.resize(nv,3);
+ }
for (int i=0; i<3; ++i)
{
RowSparseMatrix<double> Kt = data->K[i].transpose();
- A[i] = data->A +
data->spring_k*RowSparseMatrix<double>(Kt*data->K[i]);
- b.col(i) += data->spring_k*Kt*data->l;
- r.col(i) = b.col(i) - A[i]*data->x.col(i);
+ cgdata->A[i] = data->A +
data->spring_k*RowSparseMatrix<double>(Kt*data->K[i]);
+ cgdata->b.col(i).noalias() += data->spring_k*Kt*data->l;
+ cgdata->r.col(i).noalias() = cgdata->b.col(i) -
cgdata->A[i]*data->x.col(i);
}
- solve_Ax_b(data,&z,&r);
- p = z;
+ solve_Ax_b(data,&cgdata->z,&cgdata->r);
+ cgdata->p = cgdata->z;
for (int iter=0; iter<options->max_cg_iters; ++iter)
{
for( int i=0; i<3; ++i )
- Ap.col(i) = A[i]*p.col(i);
+ cgdata->Ap.col(i).noalias() =
cgdata->A[i]*cgdata->p.col(i);
- double p_dot_Ap = mat_inner(p,Ap);
+ double p_dot_Ap = mat_inner(cgdata->p,cgdata->Ap);
if( p_dot_Ap==0.0 )
break;
- double zk_dot_rk = mat_inner(z,r);
+ double zk_dot_rk = mat_inner(cgdata->z,cgdata->r);
if( zk_dot_rk==0.0 )
break;
double alpha = zk_dot_rk / p_dot_Ap;
- data->x += alpha * p;
- r -= alpha * Ap;
- if( r.lpNorm<Infinity>() < eps )
+ data->x.noalias() += alpha * cgdata->p;
+ cgdata->r.noalias() -= alpha * cgdata->Ap;
+ if( cgdata->r.lpNorm<Infinity>() < eps )
break;
- solve_Ax_b(data,&z,&r);
- double beta = mat_inner(z,r) / zk_dot_rk;
- p = z + beta*p;
+
+ solve_Ax_b(data,&cgdata->z,&cgdata->r);
+ double beta = mat_inner(cgdata->z,cgdata->r) / zk_dot_rk;
+ cgdata->p = cgdata->z + beta*cgdata->p;
}
+
} // end solve conjugate gradients
void Solver::compute_matrices(
@@ -285,14 +296,14 @@ void Solver::compute_matrices(
compute_masses(options,data);
// Add per-element energies to data
- std::vector< Triplet<double> > trips;
+ std::vector<Triplet<double> > trips;
append_energies(options,data,trips);
int n_row_D = trips.back().row()+1;
double dt2 = options->timestep_s * options->timestep_s;
- if (dt2 <= 0)
- dt2 = 1.0; // static solve
+ if (options->timestep_s <= 0)
+ dt2 = 1.0; // static solve, use dt=1 to not scale matrices
- // Weight matrix
+ // Diagonal weight matrix
RowSparseMatrix<double> W2(n_row_D,n_row_D);
VectorXi W_nnz = VectorXi::Ones(n_row_D);
W2.reserve(W_nnz);
@@ -301,30 +312,27 @@ void Solver::compute_matrices(
{
const Vector2i &idx = data->indices[i];
for (int j=0; j<idx[1]; ++j)
- {
W2.coeffRef(idx[0]+j,idx[0]+j) =
data->weights[i]*data->weights[i];
- }
}
- // Weighted Laplacian
+ // Mass weighted Laplacian
data->D.resize(n_row_D,nx);
data->D.setFromTriplets(trips.begin(), trips.end());
- data->Dt = data->D.transpose();
- data->DtW2 = dt2 * data->Dt * W2;
+ data->DtW2 = dt2 * data->D.transpose() * W2;
data->A = data->DtW2 * data->D;
for (int i=0; i<nx; ++i)
data->A.coeffRef(i,i) += data->m[i];
-
data->ldltA.compute(data->A);
data->b.resize(nx,3);
data->b.setZero();
+ // Constraint data
data->spring_k = options->mult_k*data->A.diagonal().maxCoeff();
data->l = VectorXd::Zero(1);
for (int i=0; i<3; ++i)
data->K[i].resize(1,nx);
- // ADMM variables
+ // ADMM dual/lagrange
data->z.resize(n_row_D,3);
data->z.setZero();
data->u.resize(n_row_D,3);
@@ -338,26 +346,26 @@ void Solver::compute_masses(
{
// Source:
https://github.com/mattoverby/mclscene/blob/master/include/MCL/TetMesh.hpp
// Computes volume-weighted masses for each vertex
- // density_kgm3 is the unit-volume density (e.g. soft rubber: 1100)
- double density_kgm3 = 1100;
+ // density_kgm3 is the unit-volume density
data->m.resize(data->x.rows());
data->m.setZero();
int n_tets = data->tets.rows();
for (int t=0; t<n_tets; ++t)
{
RowVector4i tet = data->tets.row(t);
+ RowVector3d tet0 = data->x.row(tet[0]);
Matrix3d edges;
- edges.col(0) = data->x.row(tet[1]) - data->x.row(tet[0]);
- edges.col(1) = data->x.row(tet[2]) - data->x.row(tet[0]);
- edges.col(2) = data->x.row(tet[3]) - data->x.row(tet[0]);
+ edges.col(0) = data->x.row(tet[1]) - tet0;
+ edges.col(1) = data->x.row(tet[2]) - tet0;
+ edges.col(2) = data->x.row(tet[3]) - tet0;
double v = std::abs((edges).determinant()/6.f);
- double tet_mass = density_kgm3 * v;
- data->m[ tet[0] ] += tet_mass / 4.f;
- data->m[ tet[1] ] += tet_mass / 4.f;
- data->m[ tet[2] ] += tet_mass / 4.f;
- data->m[ tet[3] ] += tet_mass / 4.f;
+ double tet_mass = options->density_kgm3 * v;
+ data->m[tet[0]] += tet_mass / 4.f;
+ data->m[tet[1]] += tet_mass / 4.f;
+ data->m[tet[2]] += tet_mass / 4.f;
+ data->m[tet[3]] += tet_mass / 4.f;
}
-}
+} // end compute masses
void Solver::append_energies(
const Options *options,
@@ -372,6 +380,7 @@ void Solver::append_energies(
data->rest_volumes.reserve(nt);
data->weights.reserve(nt);
Lame lame;
+ lame.set_from_youngs_poisson(options->youngs, options->poisson);
int energy_index = 0;
for (int i=0; i<nt; ++i)
diff --git a/extern/softbody/src/admmpd_solver.h
b/extern/softbody/src/admmpd_solver.h
index 970cbfb6368..0305d535f39 100644
--- a/extern/softbody/src/admmpd_solver.h
+++ b/extern/softbody/src/admmpd_solver.h
@@ -17,6 +17,9 @@ struct Options {
int max_cg_iters;
double mult_k; // stiffness multiplier for constraints
double min_res; // min residual for CG solver
+ double density_kgm3; // unit-volume density
+ double youngs; // Young's modulus
+ double poisson; // Poisson ratio
Eigen::Vector3d grav;
Options() :
timestep_s(1.0/100.0), // TODO: Figure out delta time from blender api
@@ -24,18 +27,21 @@ struct Options {
max_cg_iters(10),
mult_k(1.0),
min_res(1e-4),
+ density_kgm3(1100),
+ youngs(10000000),
+ poisson(0.399),
grav(0,0,-9.8)
{}
};
struct Data {
- // Input:
+ // Set from input
Eigen::MatrixXi tets; // elements t x 4
Eigen::MatrixXd x; // vertices, n x 3
- Eigen::MatrixXd v; // velocity, n x 3 TODO: from cache
+ Eigen::MatrixXd v; // velocity, n x 3
// Set in compute_matrices:
Eigen::MatrixXd x_start; // x at beginning of timestep, n x 3
- Eigen::VectorXd m; // masses, n x 1 TODO: from BodyPoint
+ Eigen::VectorXd m; // masses, n x 1
Eigen::MatrixXd z; // ADMM z variable
Eigen::MatrixXd u; // ADMM u aug lag with W inv
Eigen::MatrixXd M_xbar; // M*(x + dt v)
@@ -43,13 +49,20 @@ struct Data {
Eigen::MatrixXd b; // M xbar + DtW2(z-u)
template <typename T> using RowSparseMatrix =
Eigen::SparseMatrix<T,Eigen::RowMajor>;
RowSparseMatrix<double> D; // reduction matrix
- RowSparseMatrix<double> Dt; // transpose reduction matrix
RowSparseMatrix<double> DtW2; // D'W^2
RowSparseMatrix<double> A; // M + D'W^2D
RowSparseMatrix<double> K[3]; // constraint Jacobian
Eigen::VectorXd l; // constraint rhs (Kx=l)
+ double spring_k; // constraint stiffness
Eigen::SimplicialLDLT<Eigen::SparseMatrix<double> > ldltA;
- double spring_k;
+ struct CGData { // Temporaries used in conjugate gradients
+ RowSparseMatrix<double> A[3]; // (M + D'W^2D) + k * Kt K
+ Eigen::MatrixXd b; // M xbar + DtW2(z-u) + Kt l
+ Eigen::MatrixXd r; // residual
+ Eigen::MatrixXd z;
+ Eigen::MatrixXd p;
+ Eigen::MatrixXd Ap; // A * p
+ } cgdata;
// Set in append_energies:
std::vector<Eigen::Vector2i> indices; // per-energy index into D (row,
num rows)
std::vector<double> rest_volumes; // per-energy rest volume
diff --git a/intern/softbody/admmpd_api.cpp b/intern/softbody/admmpd_api.cpp
index 21e21c4cb9d..915b20b299a 100644
--- a/intern/softbody/admmpd_api.cpp
+++ b/intern/softbody/admmpd_api.cpp
@@ -84,11 +84,12 @@ void admmpd_dealloc(ADMMPDInterfaceData *iface)
delete iface->data;
}
- iface->data = NULL;
iface->in_verts = NULL;
iface->in_vel = NULL;
iface->in_faces = NULL;
iface->out_verts = NULL;
+ iface->out_vel = NULL;
+ iface->data = NULL;
}
int admmpd_init(ADMMPDInterfaceData *iface)
@@ -180,6 +181,19 @@ void admmpd_solve(ADMMPDInterfaceData *iface)
if (iface == NULL)
return;
+ // Whatever is in out_verts and out_vel needs
+ // to be mapped to internal data, as it's used as input
+ /
@@ Diff output truncated at 10240 characters. @@
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