void MayaMeshWriter::writeColor()
{
MStatus status = MS::kSuccess;
MFnMesh lMesh( mDagPath, &status );
if ( !status )
{
MGlobal::displayError(
"MFnMesh() failed for MayaMeshWriter::writeColor" );
return;
}
//Write colors
std::vector<Alembic::AbcGeom::OC4fGeomParam>::iterator rgbaIt;
std::vector<Alembic::AbcGeom::OC4fGeomParam>::iterator rgbaItEnd;
rgbaIt = mRGBAParams.begin();
rgbaItEnd = mRGBAParams.end();
for (; rgbaIt != rgbaItEnd; ++rgbaIt)
{
std::vector<float> colors;
std::vector< Alembic::Util::uint32_t > colorIndices;
MString colorSetName(rgbaIt->getName().c_str());
getColorSet(lMesh, &colorSetName, true, colors, colorIndices);
//cast the vector to the sample type
Alembic::AbcGeom::OC4fGeomParam::Sample samp(
Alembic::Abc::C4fArraySample(
(const Imath::C4f *) &colors.front(), colors.size()/4),
Alembic::Abc::UInt32ArraySample(colorIndices),
Alembic::AbcGeom::kFacevaryingScope );
rgbaIt->set(samp);
}
std::vector<Alembic::AbcGeom::OC3fGeomParam>::iterator rgbIt;
std::vector<Alembic::AbcGeom::OC3fGeomParam>::iterator rgbItEnd;
rgbIt = mRGBParams.begin();
rgbItEnd = mRGBParams.end();
for (; rgbIt != rgbItEnd; ++rgbIt)
{
std::vector<float> colors;
std::vector< Alembic::Util::uint32_t > colorIndices;
MString colorSetName(rgbIt->getName().c_str());
getColorSet(lMesh, &colorSetName, false, colors, colorIndices);
//cast the vector to the sample type
Alembic::AbcGeom::OC3fGeomParam::Sample samp(
Alembic::Abc::C3fArraySample(
(const Imath::C3f *) &colors.front(), colors.size()/3),
Alembic::Abc::UInt32ArraySample(colorIndices),
Alembic::AbcGeom::kFacevaryingScope);
rgbIt->set(samp);
}
}
//Add a training sample
void LearningInterface::addTrainingSample(FeatureSet &features, double label)
{
sample_type samp;
// samp(0) = (double)features.bandwidth();
// samp(1) = (double)features.contentType();
for(int i = 0; i < FEATURE_SET_NUM_FEATURES; i++)
samp(i) = features.getFeatureByIndex((FeatureSetIndexType) i);
m_training_set.push_back(samp);
if(label == 1.0)
m_labels.push_back(+1);
else
m_labels.push_back(-1);
m_num_training_samples++;
//Test to see if user falls into only one class
if(m_one_class_only)
{
//This is the first sample
if(m_single_class_val == -2)
{
//Set this as the single class value
m_single_class_val = (int) label;
}
//See if this is the other class
else if((int)label != m_single_class_val)
{
//Lower flags
m_one_class_only = false;
}
}
}
// write the frame ranges and statistic string on the root
// Also call the post callbacks
void AbcWriteJob::postCallback(double iFrame)
{
std::string statsStr = "";
addToString(statsStr, "TransStaticNum", mStats.mTransStaticNum);
addToString(statsStr, "TransAnimNum", mStats.mTransAnimNum);
addToString(statsStr, "TransColNum", mStats.mTransColNum);
if (statsStr.length() > 0)
{
Alembic::Abc::OStringProperty stats(mRoot.getTop().getProperties(),
"statistics");
stats.set(statsStr);
}
if (mTransTimeIndex != 0)
{
MString propName;
propName += static_cast<int>(mTransTimeIndex);
propName += ".samples";
Alembic::Abc::OUInt32Property samp(mRoot.getTop().getProperties(),
propName.asChar());
samp.set(mTransSamples);
}
MBoundingBox bbox;
processCallback(mArgs.melPostCallback, true, iFrame, bbox);
processCallback(mArgs.pythonPostCallback, false, iFrame, bbox);
}
int main()
{
char *src = (char *) malloc (3);
src = "hi";
samp(&src);
printf ("%s", src);
}
//-*****************************************************************************
// much like lib/Alembic/Abc/OTypedProperty.cpp, this is just a compile test,
// due to the implementation being in the .h file, due to templates.
void __testOGeomParamCompile( Abc::OCompoundProperty &iParent )
{
OV2fGeomParam uvs( iParent, "uv", false, kVertexScope, 1 );
std::vector<V2f> vec;
vec.push_back( V2f( 1.0f, 2.0f ) );
V2fArraySample val( vec );
OV2fGeomParam::Sample samp( val, kUnknownScope );
uvs.set( samp );
}
/* PARAM width, height : width and height of image plane
PARAM depth : the depth of recursion
PARAM outputFileName : the output file name that film needs to create the PNG output file.
PARAM Sampler : needs Sampler object to get access to a Sample and the Camera */
void render(int width, int height, int depth, std::string outputFileName,
Sampler *sampler){
//Initializing a sample object to cam.ul coordinates:
Sample samp(sampler->camera->ul.at(0), sampler->camera->ul.at(1), sampler->camera->ul.at(2));
for(int j = 0; j < height; j++) {
for(int i = 0; i < width; i++) {
//using GenerateRay to create a ray shooting to the sample position
Ray outRay = sampler->camera->generateRay(samp);
//getting the rgb value returned by calling raytracer.trace
samp.rgb = sampler->raytracer->trace(outRay, 5);
// Progress
if (i + j * width == 0)
printf("...0%% done...\n");
if (i + j * width == (height*width)/5)
printf("...20%% done...\n");
if (i + j * width == (2*height*width)/5)
printf("...40%% done...\n");
if (i + j * width == (3*height*width)/5)
printf("...60%% done...\n");
if (i + j * width == (4*height*width)/5)
printf("...80%% done...\n");
//Passing the rgb value to film (this rgb value will to be saved in the Film.bitmap)
sampler->film->setPixel(i, height - 1 - j, samp.rgb);
// Increment samp.x, samp.y, and samp.z by cam->right
samp.x += sampler->camera->right.at(0);
samp.y += sampler->camera->right.at(1);
samp.z += sampler->camera->right.at(2);
}
// Reset the i portion
samp.x -= sampler->camera->right.at(0) * width;
samp.y -= sampler->camera->right.at(1) * width;
samp.z -= sampler->camera->right.at(2) * width;
// Increment samp.x, samp.y, and samp.z by cam->down
samp.x += sampler->camera->down.at(0);
samp.y += sampler->camera->down.at(1);
samp.z += sampler->camera->down.at(2);
}
/* film->outputImage is called to print the image and complete the program.
* the bitmap should be completely filled by now */
sampler->film->outputImage(outputFileName);
}
void MayaMeshWriter::writePoly(
const Alembic::AbcGeom::OV2fGeomParam::Sample & iUVs)
{
MStatus status = MS::kSuccess;
MFnMesh lMesh( mDagPath, &status );
if ( !status )
{
MGlobal::displayError( "MFnMesh() failed for MayaMeshWriter" );
}
std::vector<float> points;
std::vector<Alembic::Util::int32_t> facePoints;
std::vector<Alembic::Util::int32_t> pointCounts;
fillTopology(points, facePoints, pointCounts);
Alembic::AbcGeom::ON3fGeomParam::Sample normalsSamp;
std::vector<float> normals;
getPolyNormals(normals);
if (!normals.empty())
{
normalsSamp.setScope( Alembic::AbcGeom::kFacevaryingScope );
normalsSamp.setVals(Alembic::AbcGeom::N3fArraySample(
(const Imath::V3f *) &normals.front(), normals.size() / 3));
}
Alembic::AbcGeom::OPolyMeshSchema::Sample samp(
Alembic::Abc::V3fArraySample((const Imath::V3f *)&points.front(),
points.size() / 3),
Alembic::Abc::Int32ArraySample(facePoints),
Alembic::Abc::Int32ArraySample(pointCounts), iUVs, normalsSamp);
// if this mesh is animated, write out the animated geometry
if (mIsGeometryAnimated)
{
mPolySchema.set(samp);
}
else
{
mPolySchema.set(samp);
}
writeColor();
}
// generate samples from a distribution using inverse CDF sampling
// pdf input is expected to be an Nx2 matrix with col 1 = values and col 2 = probabilities of those values
// step size scales pdf to equal 1, set equal
Matrix invCDFsample(const int& samples, const double& step,
const Matrix& pdf)
{
Matrix samp(samples,1);
double tempSamp = 0.;
int j = 0;
// integrate to generate CDF
Matrix CDF(pdf.rows(),1);
CDF[0][0] = pdf[0][1]*step;
for(int i=0;i<CDF.rows()-1;i++)
{
//cout << "CDF[i] = " << CDF[i][0] << " pdf[i] = " << pdf[i][1] << endl;
CDF[i+1][0] = CDF[i][0] + pdf[i+1][1];
//cout << "CDF[i+1] = " << CDF[i+1][0] << endl;
}
// multiply by step size to scale integral correctly
CDF = CDF*step;
//CDF.print();
// choose sample from uniform generator according to CDF
for(int i=0;i<samples;i++)
{
j = 0;
tempSamp = rvStdUniform();
while( CDF[j][0] < tempSamp )
{
j++;
}
if( j == 0 )
samp[i][0] = pdf[j][0];
else
samp[i][0] = (pdf[j-1][0]+pdf[j][0])/2;
}
return samp;
}
int main (int argc, char * argv[]) {
/* System parameters */
int ** F; /* The 2D array of spins */
int L = 1000; /* The sidelength of the array */
int N; /* The total number of spins = L*L */
double T = 1.0; /* Dimensionless temperature = (T*k)/J */
/* Run parameters */
int nCycles = 1000000; /* number of MC cycles to run; one cycle is N
consecutive attempted spin flips */
int fSamp = 1000; /* Frequency with which samples are taken */
/* Computational variables */
int nSamp; /* Number of samples taken */
int de; /* energy change due to flipping a spin */
double b; /* Boltzman factor */
double x; /* random number */
int i,j,a,c; /* loop counters */
/* Observables */
double s=0.0, ssum=0.0; /* average magnetization */
double e=0.0, esum=0.0; /* average energy per spin */
/* This line creates a random number generator
of the "Mersenne Twister" type, which is much
better than the default random number generator. */
gsl_rng * r = gsl_rng_alloc(gsl_rng_mt19937);
unsigned long int Seed = 23410981;
/* Here we parse the command line arguments */
for (i=1;i<argc;i++) {
if (!strcmp(argv[i],"-L")) L=atoi(argv[++i]);
else if (!strcmp(argv[i],"-T")) T=atof(argv[++i]);
else if (!strcmp(argv[i],"-nc")) nCycles = atoi(argv[++i]);
else if (!strcmp(argv[i],"-fs")) fSamp = atoi(argv[++i]);
else if (!strcmp(argv[i],"-s")) Seed = (unsigned long)atoi(argv[++i]);
}
/* Output some initial information */
/*fprintf(stdout,"# command: ");
for (i=0;i<argc;i++) fprintf(stdout,"%s ",argv[i]);
fprintf(stdout,"\n");
fprintf(stdout,"# ISING simulation, NVT Metropolis Monte Carlo\n");
fprintf(stdout,"# L = %i, T = %.3lf, nCycles %i, fSamp %i, Seed %u\n",
L,T,nCycles,fSamp,Seed);*/
/* Seed the random number generator */
gsl_rng_set(r,Seed);
/* Compute the number of spins */
N=L*L;
/* Allocate memory for the system */
F=(int**)malloc(L*sizeof(int*));
for (i=0;i<L;i++) F[i]=(int*)malloc(L*sizeof(int));
/* Generate an initial state */
init(F,L,r);
/* For computational efficiency, convert T to reciprocal T */
T=1.0/T;
s = 0.0;
e = 0.0;
nSamp = 0;
for (c=0;c<nCycles;c++) {
/* Make N flip attempts */
#pragma omp parallel for private(i,j,de,b,x) shared(F)
for (a=0;a<N;a++) {
/* randomly select a spin */
i=(int)gsl_rng_uniform_int(r,L);
j=(int)gsl_rng_uniform_int(r,L);
/* get the "new" energy as the incremental change due
to flipping spin (i,j) */
de = E(F,L,i,j);
/* compute the Boltzmann factor; recall T is now
reciprocal temperature */
b = exp(de*T);
/* pick a random number between 0 and 1 */
x = gsl_rng_uniform(r);
/* accept or reject this flip */
if (x<b) { /* accept */
/* flip it */
F[i][j]*=-1;
}
}
/* Sample and accumulate averages */
if (!(c%fSamp)) {
samp(F,L,&s,&e);
//fprintf(stdout,"%i %.5le %.5le\n",c,s,e);
fflush(stdout);
ssum+=s;
esum+=e;
nSamp++;
}
#pragma omp barrier
}
fprintf(stdout,"# The average magnetization is %.5lf\n",ssum/nSamp);
fprintf(stdout,"# The average energy per spin is %.5lf\n",esum/nSamp);
fprintf(stdout,"# Program ends.\n");
}
void hist2(double M[16], unsigned char g[], unsigned char f[], const int dg[3], const int df[3],
double H[65536], float s[3])
{
static float ran[] = {0.656619,0.891183,0.488144,0.992646,0.373326,0.531378,0.181316,0.501944,0.422195,
0.660427,0.673653,0.95733,0.191866,0.111216,0.565054,0.969166,0.0237439,0.870216,
0.0268766,0.519529,0.192291,0.715689,0.250673,0.933865,0.137189,0.521622,0.895202,
0.942387,0.335083,0.437364,0.471156,0.14931,0.135864,0.532498,0.725789,0.398703,
0.358419,0.285279,0.868635,0.626413,0.241172,0.978082,0.640501,0.229849,0.681335,
0.665823,0.134718,0.0224933,0.262199,0.116515,0.0693182,0.85293,0.180331,0.0324186,
0.733926,0.536517,0.27603,0.368458,0.0128863,0.889206,0.866021,0.254247,0.569481,
0.159265,0.594364,0.3311,0.658613,0.863634,0.567623,0.980481,0.791832,0.152594,
0.833027,0.191863,0.638987,0.669,0.772088,0.379818,0.441585,0.48306,0.608106,
0.175996,0.00202556,0.790224,0.513609,0.213229,0.10345,0.157337,0.407515,0.407757,
0.0526927,0.941815,0.149972,0.384374,0.311059,0.168534,0.896648};
int iran=0;
float z;
for(z=1.0; z<dg[2]-s[2]; z+=s[2])
{
float y;
for(y=1.0; y<dg[1]-s[1]; y+=s[1])
{
float x;
for(x=1.0; x<dg[0]-s[0]; x+=s[0])
{
float rx, ry, rz, xp, yp, zp;
rx = x + ran[iran = (iran+1)%97]*s[0];
ry = y + ran[iran = (iran+1)%97]*s[1];
rz = z + ran[iran = (iran+1)%97]*s[2];
xp = M[0]*rx + M[4]*ry + M[ 8]*rz + M[12];
yp = M[1]*rx + M[5]*ry + M[ 9]*rz + M[13];
zp = M[2]*rx + M[6]*ry + M[10]*rz + M[14];
if (zp>=1.0 && zp<df[2] && yp>=1.0 && yp<df[1] && xp>=1.0 && xp<df[0])
{
float vf;
int ivf, ivg;
vf = samp(df, f, xp,yp,zp);
ivf = floor(vf);
ivg = floor(samp(dg, g, rx,ry,rz)+0.5);
H[ivf+ivg*256] += (1-(vf-ivf));
if (ivf<255)
H[ivf+1+ivg*256] += (vf-ivf);
/*
float vf, vg;
int ivf, ivg;
vg = samp(dg, g, rx,ry,rz);
vf = samp(df, f, xp,yp,zp);
ivg = floor(vg);
ivf = floor(vf);
H[ivf+ivg*256] += (1-(vf-ivf))*(1-(vg-ivg));
if (ivf<255)
H[ivf+1+ivg*256] += (vf-ivf)*(1-(vg-ivg));
if (ivg<255)
{
H[ivf+(ivg+1)*256] += (1-(vf-ivf))*(vg-ivg);
if (ivf<255)
H[ivf+1+(ivg+1)*256] += (vf-ivf)*(vg-ivg);
}
*/
}
}
}
}
}
void Recoloring::Recolor(Mat& _source, Mat& source_mask, Mat& _target, Mat& target_mask) {
Mat source; _source.convertTo(source,CV_32F,1.0/255.0);
Mat target; _target.convertTo(target,CV_32F,1.0/255.0);
CvEM source_model,target_model;
//cvtColor(target,target,CV_BGR2Lab);
//cvtColor(source,source,CV_BGR2Lab);
TrainGMM(source_model,source,source_mask);
TrainGMM(target_model,target,target_mask);
vector<int> match = MatchGaussians(source_model,target_model);
Mat target_32f;
//if(target.type() != CV_32F)
// target.convertTo(target_32f,CV_32F,1.0/255.0);
//else
target.copyTo(target_32f);
const CvMat** target_covs = target_model.get_covs();
const CvMat** source_covs = source_model.get_covs();
Mat sMu(source_model.get_means()); Mat sMu_64f; sMu.convertTo(sMu_64f,CV_64F);
Mat tMu(target_model.get_means()); Mat tMu_64f; tMu.convertTo(tMu_64f,CV_64F);
int num_g = target_model.get_nclusters();
Mat pr; Mat samp(1,3,CV_32FC1);
for(int y=0;y<target.rows;y++) {
Vec3f* row = target_32f.ptr<Vec3f>(y);
uchar* mask_row = target_mask.ptr<uchar>(y);
for(int x=0;x<target.cols;x++) {
if(mask_row[x] > 0) {
memcpy(samp.data,&(row[x][0]),3*sizeof(float));
float res = target_model.predict(samp,&pr);
//cout << res << ":" << ((float*)pr.data)[0] << "," <<
// ((float*)pr.data)[1] << "," <<
// ((float*)pr.data)[2] << "," <<
// ((float*)pr.data)[3] << "," <<
// ((float*)pr.data)[4] << "," << endl;
Mat samp_64f; samp.convertTo(samp_64f,CV_64F);
//From Shapira09: Xnew = Sum_i { pr(i) * Sigma_source_i * (Sigma_target_i)^-1 * (x - mu_target) + mu_source }
Mat Xnew(1,3,CV_64FC1,Scalar(0));
for(int i=0;i<num_g;i++) {
if(((float*)pr.data)[i] <= 0) continue;
Mat A = /*Mat(*/
//Mat(target_covs[i]) *
//Mat(source_covs[match[i]]).inv() *
Mat(samp_64f - tMu_64f(Range(i,i+1),Range(0,3))).t();
Mat B = sMu_64f(Range(match[i],match[i]+1),Range(0,3)).t();
Xnew += Mat((A + B) * (double)(((float*)pr.data)[i])).t();
}
Mat _tmp; Xnew.convertTo(_tmp,CV_32F);
//allow for mask with alpha
float* _d = ((float*)_tmp.data);
float alpha = mask_row[x] / 255.0f;
for(int cl=0;cl<3;cl++)
_d[cl] = _d[cl] * (alpha) + row[x][cl] * (1-alpha);
memcpy(&(row[x][0]),_tmp.data,sizeof(float)*3);
}
}
}
//cvtColor(target,target,CV_Lab2BGR);
//cvtColor(source,source,CV_Lab2BGR);
//cvtColor(target_32f,target_32f,CV_Lab2BGR);
if(!this->m_p.no_gui) {
namedWindow("orig target");
imshow("orig target",target);
namedWindow("source orig");
imshow("source orig",source);
namedWindow("source masked");
Mat _tmp_S; source.copyTo(_tmp_S,source_mask);
imshow("source masked",_tmp_S);
namedWindow("dest target");
imshow("dest target",target_32f);
waitKey(this->m_p.wait_time);
}
target_32f.convertTo(_target,CV_8UC3,255.0);
}
// write the frame ranges and statistic string on the root
// Also call the post callbacks
void AbcWriteJob::postCallback(double iFrame)
{
std::string statsStr = "";
addToString(statsStr, "SubDStaticNum", mStats.mSubDStaticNum);
addToString(statsStr, "SubDAnimNum", mStats.mSubDAnimNum);
addToString(statsStr, "SubDStaticCVs", mStats.mSubDStaticCVs);
addToString(statsStr, "SubDAnimCVs", mStats.mSubDAnimCVs);
addToString(statsStr, "SubDStaticFaces", mStats.mSubDStaticFaces);
addToString(statsStr, "SubDAnimFaces", mStats.mSubDAnimFaces);
addToString(statsStr, "PolyStaticNum", mStats.mPolyStaticNum);
addToString(statsStr, "PolyAnimNum", mStats.mPolyAnimNum);
addToString(statsStr, "PolyStaticCVs", mStats.mPolyStaticCVs);
addToString(statsStr, "PolyAnimCVs", mStats.mPolyAnimCVs);
addToString(statsStr, "PolyStaticFaces", mStats.mPolyStaticFaces);
addToString(statsStr, "PolyAnimFaces", mStats.mPolyAnimFaces);
addToString(statsStr, "CurveStaticNum", mStats.mCurveStaticNum);
addToString(statsStr, "CurveStaticCurves", mStats.mCurveStaticCurves);
addToString(statsStr, "CurveAnimNum", mStats.mCurveAnimNum);
addToString(statsStr, "CurveAnimCurves", mStats.mCurveAnimCurves);
addToString(statsStr, "CurveStaticCVs", mStats.mCurveStaticCVs);
addToString(statsStr, "CurveAnimCVs", mStats.mCurveAnimCVs);
addToString(statsStr, "PointStaticNum", mStats.mPointStaticNum);
addToString(statsStr, "PointAnimNum", mStats.mPointAnimNum);
addToString(statsStr, "PointStaticCVs", mStats.mPointStaticCVs);
addToString(statsStr, "PointAnimCVs", mStats.mPointAnimCVs);
addToString(statsStr, "NurbsStaticNum", mStats.mNurbsStaticNum);
addToString(statsStr, "NurbsAnimNum", mStats.mNurbsAnimNum);
addToString(statsStr, "NurbsStaticCVs", mStats.mNurbsStaticCVs);
addToString(statsStr, "NurbsAnimCVs", mStats.mNurbsAnimCVs);
addToString(statsStr, "TransStaticNum", mStats.mTransStaticNum);
addToString(statsStr, "TransAnimNum", mStats.mTransAnimNum);
addToString(statsStr, "LocatorStaticNum", mStats.mLocatorStaticNum);
addToString(statsStr, "LocatorAnimNum", mStats.mLocatorAnimNum);
addToString(statsStr, "CameraStaticNum", mStats.mCameraStaticNum);
addToString(statsStr, "CameraAnimNum", mStats.mCameraAnimNum);
if (statsStr.length() > 0)
{
Alembic::Abc::OStringProperty stats(mRoot.getTop().getProperties(),
"statistics");
stats.set(statsStr);
}
if (mTransTimeIndex != 0)
{
MString propName;
propName += static_cast<int>(mTransTimeIndex);
propName += ".samples";
Alembic::Abc::OUInt32Property samp(mRoot.getTop().getProperties(),
propName.asChar());
samp.set(mTransSamples);
}
if (mShapeTimeIndex != 0 && mShapeTimeIndex != mTransTimeIndex)
{
MString propName;
propName += static_cast<int>(mShapeTimeIndex);
propName += ".samples";
Alembic::Abc::OUInt32Property samp(mRoot.getTop().getProperties(),
propName.asChar());
samp.set(mShapeSamples);
}
MBoundingBox bbox;
if (mArgs.melPostCallback.find("#BOUNDS#") != std::string::npos ||
mArgs.pythonPostCallback.find("#BOUNDS#") != std::string::npos ||
mArgs.melPostCallback.find("#BOUNDSARRAY#") != std::string::npos ||
mArgs.pythonPostCallback.find("#BOUNDSARRAY#") != std::string::npos)
{
util::ShapeSet::const_iterator it = mArgs.dagPaths.begin();
const util::ShapeSet::const_iterator end = mArgs.dagPaths.end();
for (; it != end; it ++)
{
mCurDag = *it;
MMatrix eMInvMat;
if (mArgs.worldSpace)
{
eMInvMat.setToIdentity();
}
else
{
eMInvMat = mCurDag.exclusiveMatrixInverse();
}
bbox.expand(getBoundingBox(iFrame, eMInvMat));
}
}
processCallback(mArgs.melPostCallback, true, iFrame, bbox);
processCallback(mArgs.pythonPostCallback, false, iFrame, bbox);
}
void MayaMeshWriter::writeSubD(
const Alembic::AbcGeom::OV2fGeomParam::Sample & iUVs)
{
MStatus status = MS::kSuccess;
MFnMesh lMesh( mDagPath, &status );
if ( !status )
{
MGlobal::displayError( "MFnMesh() failed for MayaMeshWriter" );
}
std::vector<float> points;
std::vector<Alembic::Util::int32_t> facePoints;
std::vector<Alembic::Util::int32_t> pointCounts;
fillTopology(points, facePoints, pointCounts);
Alembic::AbcGeom::OSubDSchema::Sample samp(
Alembic::AbcGeom::V3fArraySample((const Imath::V3f *)&points.front(),
points.size() / 3),
Alembic::Abc::Int32ArraySample(facePoints),
Alembic::Abc::Int32ArraySample(pointCounts));
samp.setUVs( iUVs );
MPlug plug = lMesh.findPlug("faceVaryingInterpolateBoundary");
if (!plug.isNull())
samp.setFaceVaryingInterpolateBoundary(plug.asInt());
plug = lMesh.findPlug("interpolateBoundary");
if (!plug.isNull())
samp.setInterpolateBoundary(plug.asInt());
plug = lMesh.findPlug("faceVaryingPropagateCorners");
if (!plug.isNull())
samp.setFaceVaryingPropagateCorners(plug.asInt());
std::vector <Alembic::Util::int32_t> creaseIndices;
std::vector <Alembic::Util::int32_t> creaseLengths;
std::vector <float> creaseSharpness;
std::vector <Alembic::Util::int32_t> cornerIndices;
std::vector <float> cornerSharpness;
MUintArray edgeIds;
MDoubleArray creaseData;
if (lMesh.getCreaseEdges(edgeIds, creaseData) == MS::kSuccess)
{
unsigned int numCreases = creaseData.length();
creaseIndices.resize(numCreases * 2);
creaseLengths.resize(numCreases, 2);
creaseSharpness.resize(numCreases);
for (unsigned int i = 0; i < numCreases; ++i)
{
int verts[2];
lMesh.getEdgeVertices(edgeIds[i], verts);
creaseIndices[2 * i] = verts[0];
creaseIndices[2 * i + 1] = verts[1];
creaseSharpness[i] = static_cast<float>(creaseData[i]);
}
samp.setCreaseIndices(Alembic::Abc::Int32ArraySample(creaseIndices));
samp.setCreaseLengths(Alembic::Abc::Int32ArraySample(creaseLengths));
samp.setCreaseSharpnesses(
Alembic::Abc::FloatArraySample(creaseSharpness));
}
MUintArray cornerIds;
MDoubleArray cornerData;
if (lMesh.getCreaseVertices(cornerIds, cornerData) == MS::kSuccess)
{
unsigned int numCorners = cornerIds.length();
cornerIndices.resize(numCorners);
cornerSharpness.resize(numCorners);
for (unsigned int i = 0; i < numCorners; ++i)
{
cornerIndices[i] = cornerIds[i];
cornerSharpness[i] = static_cast<float>(cornerData[i]);
}
samp.setCornerSharpnesses(
Alembic::Abc::FloatArraySample(cornerSharpness));
samp.setCornerIndices(
Alembic::Abc::Int32ArraySample(cornerIndices));
}
#if MAYA_API_VERSION >= 201100
MUintArray holes = lMesh.getInvisibleFaces();
unsigned int numHoles = holes.length();
std::vector <Alembic::Util::int32_t> holeIndices(numHoles);
for (unsigned int i = 0; i < numHoles; ++i)
{
holeIndices[i] = holes[i];
}
if (!holeIndices.empty())
{
samp.setHoles(holeIndices);
}
#endif
mSubDSchema.set(samp);
writeColor();
writeUVSets();
}
void squaring(int dm[], int k, int save_transf, double b[], double A[], double t0[], double t1[], double J0[], double J1[])
{
int i, j, m = dm[0]*dm[1];
double *ptr = t0;
for(i=0; i<k; i++)
{
double *buf1, *buf2;
buf1 = t1; /* Re-use some memory */
buf2 = J1;
for(j=0; j<m; j++)
{
double tmp00, tmp01, tmp11, tmp1, tmp2, tmp3, tmp4;
double x, y;
double j11, j21, j12, j22, dt;
x = t0[j ]-1.0;
y = t0[j+m]-1.0;
j11 = J0[j ]; j12 = J0[j+2*m];
j21 = J0[j+m]; j22 = J0[j+3*m];
dt = j11*j22 - j12*j21;
/* if (dt < 1e-9) dt = 1e-9;
if (dt > 1e9 ) dt = 1e9; */
tmp1 = samp(dm,b ,x,y);
tmp2 = samp(dm,b+m,x,y);
buf1[j ] = dt*(tmp1*j11+tmp2*j21);
buf1[j+m] = dt*(tmp1*j12+tmp2*j22);
tmp00 = samp(dm,A ,x,y);
tmp11 = samp(dm,A+ m,x,y);
tmp01 = samp(dm,A+2*m,x,y);
tmp1 = tmp00*j11+tmp01*j21;
tmp2 = tmp01*j11+tmp11*j21;
tmp3 = tmp00*j12+tmp01*j22;
tmp4 = tmp01*j12+tmp11*j22;
/* if (dt < 1e-9) dt = 1e-9; */
/* if (dt > 1e9 ) dt = 1e9; */
buf2[j ] = dt*(tmp1*j11+tmp2*j21);
buf2[j+ m] = dt*(tmp3*j12+tmp4*j22);
buf2[j+2*m] = dt*(tmp1*j12+tmp2*j22);
}
for(j=0; j<2*m; j++) b[j] += buf1[j];
for(j=0; j<3*m; j++) A[j] += buf2[j];
if (save_transf || (i<k-1))
{
double *tmpp;
composition_jacobian(dm, t0, J0, t0, J0, t1, J1);
tmpp = t0; t0 = t1; t1 = tmpp;
tmpp = J0; J0 = J1; J1 = tmpp;
}
}
if (save_transf && ptr!=t0)
{
for(j=0; j<m*2; j++) t1[j] = t0[j];
for(j=0; j<m*4; j++) J1[j] = J0[j];
}
}
int run_sampler(unsigned epochs,float alpha,unsigned batch_size){
//load sampler
string training_path = "PPAttachData/training.lemma";
string param_path = "PPAttachData/wordsketches/";
string vpath = param_path + string("vdistrib");
string x1vpath = param_path + string("x1givenv");
string pvpath = param_path + string("pgivenv");
string x2vppath = param_path + string("x2givenvp");
string px1path = param_path + string("pgivenx1");
string x2x1ppath = param_path + string("x2givenx1p");
DataSampler samp(training_path.c_str(),
vpath.c_str(),
x1vpath.c_str(),
pvpath.c_str(),
x2vppath.c_str(),
px1path.c_str(),
x2x1ppath.c_str());
//load dev and test
PPADataEncoder dev_set("PPAttachData/devset.lemma");
PPADataEncoder test_set("PPAttachData/test.lemma");
//load Word vectors
Word2vec w2v;
vector<string> wvdict;
af::array w2v_embeddings;
w2v.load_dictionary("PPAttachData/embeddings/deps.words.lemmatized");
//w2v.filter(xdict);
//make network
vector<string> ydict;
samp.getYdictionary(ydict);
SymbolicFeedForwardNetwork<string,string> net;
net.set_output_layer("loss",new SoftMaxLoss<string>(ydict));
net.add_layer("top",new LinearLayer());
net.add_layer("hidden",new ReLUActivation(400));
net.add_layer("A",new LinearLayer());
net.add_input_layer("lookupA",new LinearLookup<string>(w2v.get_keys(),w2v.get_values(),4,false));
net.connect_layers("loss","top");
net.connect_layers("top","hidden");
net.connect_layers("hidden","A");
net.connect_layers("A","lookupA");
for(int E = 0; E < epochs;++E){
vector<string> ydata;
vector<vector<string>> xdata;
//af::timer start1 = af::timer::start();
samp.generate_sample(ydata,xdata,batch_size);
//printf("elapsed seconds (sampling): %g\n", af::timer::stop(start1));
PPADataEncoder sampdata(ydata,xdata);
vector<string> enc_ydata;
vector<vector<string>> enc_xdata(1,vector<string>());
sampdata.getYdata(enc_ydata);
sampdata.getXdata(enc_xdata[0]);
//af::timer start2 = af::timer::start();
net.set_batch_data(enc_ydata,enc_xdata);
float loss = net.train_one(alpha,true,true);
//printf("elapsed seconds (backprop): %g\n", af::timer::stop(start2));
if (E % 20 == 0){
vector<string> devy;
vector<vector<string>> devx(1,vector<string>());
dev_set.getYdata(devy);
dev_set.getXdata(devx[0]);
float acc = net.eval_avg(devy,devx); //auto-eval on dev data
cout << "epoch " << E << ", loss= " << loss << ", eval (dev) = " << acc << endl;
}else {
cout << "epoch" << E <<endl;
}
}
vector<string> testy;
vector<vector<string>> testx(1,vector<string>());
test_set.getYdata(testy);
test_set.getXdata(testx[0]);
float acc = net.eval_avg(testy,testx);
cout << "final eval (test) = " << acc << endl;
return 0;
}
//-*****************************************************************************
void SpwImpl::setSample( const void *iSamp )
{
// Make sure we aren't writing more samples than we have times for
// This applies to acyclic sampling only
ABCA_ASSERT(
!m_header->header.getTimeSampling()->getTimeSamplingType().isAcyclic()
|| m_header->header.getTimeSampling()->getNumStoredTimes() >
m_header->nextSampleIndex,
"Can not write more samples than we have times for when using "
"Acyclic sampling." );
AbcA::ArraySample samp( iSamp, m_header->header.getDataType(),
AbcA::Dimensions(1) );
// The Key helps us analyze the sample.
AbcA::ArraySample::Key key = samp.getKey();
// mask out the non-string POD since Ogawa can safely share the same data
// even if it originated from a different POD
// the non-fixed sizes of our strings (plus added null characters) makes
// determing the sie harder so strings are handled seperately
if ( key.origPOD != Alembic::Util::kStringPOD &&
key.origPOD != Alembic::Util::kWstringPOD )
{
key.origPOD = Alembic::Util::kInt8POD;
key.readPOD = Alembic::Util::kInt8POD;
}
// We need to write the sample
if ( m_header->nextSampleIndex == 0 ||
!( m_previousWrittenSampleID &&
key == m_previousWrittenSampleID->getKey() ) )
{
// we only need to repeat samples if this is not the first change
if (m_header->firstChangedIndex != 0)
{
// copy the samples from after the last change to the latest index
for ( index_t smpI = m_header->lastChangedIndex + 1;
smpI < m_header->nextSampleIndex; ++smpI )
{
assert( smpI > 0 );
CopyWrittenData( m_group, m_previousWrittenSampleID );
}
}
// Write this sample, which will update its internal
// cache of what the previously written sample was.
AbcA::ArchiveWriterPtr awp = this->getObject()->getArchive();
// Write the sample.
// This distinguishes between string, wstring, and regular arrays.
m_previousWrittenSampleID =
WriteData( GetWrittenSampleMap( awp ), m_group, samp, key );
if (m_header->firstChangedIndex == 0)
{
m_header->firstChangedIndex = m_header->nextSampleIndex;
}
// this index is now the last change
m_header->lastChangedIndex = m_header->nextSampleIndex;
}
if ( m_header->nextSampleIndex == 0 )
{
m_hash = m_previousWrittenSampleID->getKey().digest;
}
else
{
Util::Digest digest = m_previousWrittenSampleID->getKey().digest;
Util::SpookyHash::ShortEnd( m_hash.words[0], m_hash.words[1],
digest.words[0], digest.words[1] );
}
m_header->nextSampleIndex ++;
}
