int
w2xconv_convert_rgb(struct W2XConv *conv,
unsigned char *dst, size_t dst_step_byte, /* rgb24 (src_w*ratio, src_h*ratio) */
unsigned char *src, size_t src_step_byte, /* rgb24 (src_w, src_h) */
int src_w, int src_h,
int denoise_level, /* 0:none, 1:L1 denoise, other:L2 denoise */
double scale,
int block_size)
{
int dst_h = src_h * scale;
int dst_w = src_w * scale;
cv::Mat srci(src_h, src_w, CV_8UC3, src, src_step_byte);
cv::Mat dsti(dst_h, dst_w, CV_8UC3, dst, dst_step_byte);
cv::Mat image;
bool is_rgb = (conv->impl->scale2_models[0]->getNInputPlanes() == 3);
if (is_rgb) {
srci.copyTo(image);
convert_mat(conv, image, denoise_level, scale, dst_w, dst_h, block_size, w2xc::IMAGE_RGB);
image.copyTo(dsti);
} else {
srci.convertTo(image, CV_32F, 1.0 / 255.0);
cv::cvtColor(image, image, cv::COLOR_RGB2YUV);
convert_mat(conv, image, denoise_level, scale, dst_w, dst_h, block_size, w2xc::IMAGE_Y);
cv::cvtColor(image, image, cv::COLOR_YUV2RGB);
image.convertTo(dsti, CV_8U, 255.0);
}
return 0;
}
int
w2xconv_convert_yuv(struct W2XConv *conv,
unsigned char *dst, size_t dst_step_byte, /* float32x3 (src_w*ratio, src_h*ratio) */
unsigned char *src, size_t src_step_byte, /* float32x3 (src_w, src_h) */
int src_w, int src_h,
int denoise_level, /* 0:none, 1:L1 denoise, other:L2 denoise */
double scale,
int block_size)
{
int dst_h = src_h * scale;
int dst_w = src_w * scale;
bool is_rgb = (conv->impl->scale2_models[0]->getNInputPlanes() == 3);
if (is_rgb) {
setError(conv, W2XCONV_ERROR_RGB_MODEL_MISMATCH_TO_Y);
return -1;
}
cv::Mat srci(src_h, src_w, CV_32FC3, src, src_step_byte);
cv::Mat dsti(dst_h, dst_w, CV_32FC3, dst, dst_step_byte);
cv::Mat image = srci.clone();
convert_mat(conv, image, denoise_level, scale, dst_w, dst_h, block_size, w2xc::IMAGE_Y);
image.copyTo(dsti);
return 0;
}
int gmx_cluster(int argc,char *argv[])
{
static char *desc[] = {
"g_cluster can cluster structures with several different methods.",
"Distances between structures can be determined from a trajectory",
"or read from an XPM matrix file with the [TT]-dm[tt] option.",
"RMS deviation after fitting or RMS deviation of atom-pair distances",
"can be used to define the distance between structures.[PAR]",
"single linkage: add a structure to a cluster when its distance to any",
"element of the cluster is less than [TT]cutoff[tt].[PAR]",
"Jarvis Patrick: add a structure to a cluster when this structure",
"and a structure in the cluster have each other as neighbors and",
"they have a least [TT]P[tt] neighbors in common. The neighbors",
"of a structure are the M closest structures or all structures within",
"[TT]cutoff[tt].[PAR]",
"Monte Carlo: reorder the RMSD matrix using Monte Carlo.[PAR]",
"diagonalization: diagonalize the RMSD matrix.[PAR]"
"gromos: use algorithm as described in Daura [IT]et al.[it]",
"([IT]Angew. Chem. Int. Ed.[it] [BB]1999[bb], [IT]38[it], pp 236-240).",
"Count number of neighbors using cut-off, take structure with",
"largest number of neighbors with all its neighbors as cluster",
"and eleminate it from the pool of clusters. Repeat for remaining",
"structures in pool.[PAR]",
"When the clustering algorithm assigns each structure to exactly one",
"cluster (single linkage, Jarvis Patrick and gromos) and a trajectory",
"file is supplied, the structure with",
"the smallest average distance to the others or the average structure",
"or all structures for each cluster will be written to a trajectory",
"file. When writing all structures, separate numbered files are made",
"for each cluster.[PAR]"
"Two output files are always written:[BR]",
"[TT]-o[tt] writes the RMSD values in the upper left half of the matrix",
"and a graphical depiction of the clusters in the lower right half",
"When [TT]-minstruct[tt] = 1 the graphical depiction is black",
"when two structures are in the same cluster.",
"When [TT]-minstruct[tt] > 1 different colors will be used for each",
"cluster.[BR]",
"[TT]-g[tt] writes information on the options used and a detailed list",
"of all clusters and their members.[PAR]",
"Additionally, a number of optional output files can be written:[BR]",
"[TT]-dist[tt] writes the RMSD distribution.[BR]",
"[TT]-ev[tt] writes the eigenvectors of the RMSD matrix",
"diagonalization.[BR]",
"[TT]-sz[tt] writes the cluster sizes.[BR]",
"[TT]-tr[tt] writes a matrix of the number transitions between",
"cluster pairs.[BR]",
"[TT]-ntr[tt] writes the total number of transitions to or from",
"each cluster.[BR]",
"[TT]-clid[tt] writes the cluster number as a function of time.[BR]",
"[TT]-cl[tt] writes average (with option [TT]-av[tt]) or central",
"structure of each cluster or writes numbered files with cluster members",
"for a selected set of clusters (with option [TT]-wcl[tt], depends on",
"[TT]-nst[tt] and [TT]-rmsmin[tt]).[BR]",
};
FILE *fp,*log;
int i,i1,i2,j,nf,nrms;
matrix box;
rvec *xtps,*usextps,*x1,**xx=NULL;
char *fn,*trx_out_fn;
t_clusters clust;
t_mat *rms;
real *eigval;
t_topology top;
int ePBC;
t_atoms useatoms;
t_matrix *readmat;
real *tmp;
int isize=0,ifsize=0,iosize=0;
atom_id *index=NULL, *fitidx, *outidx;
char *grpname;
real rmsd,**d1,**d2,*time,time_invfac,*mass=NULL;
char buf[STRLEN],buf1[80],title[STRLEN];
bool bAnalyze,bUseRmsdCut,bJP_RMSD=FALSE,bReadMat,bReadTraj;
int method,ncluster=0;
static char *methodname[] = {
NULL, "linkage", "jarvis-patrick","monte-carlo",
"diagonalization", "gromos", NULL
};
enum { m_null, m_linkage, m_jarvis_patrick,
m_monte_carlo, m_diagonalize, m_gromos, m_nr };
/* Set colors for plotting: white = zero RMS, black = maximum */
static t_rgb rlo_top = { 1.0, 1.0, 1.0 };
static t_rgb rhi_top = { 0.0, 0.0, 0.0 };
static t_rgb rlo_bot = { 1.0, 1.0, 1.0 };
static t_rgb rhi_bot = { 0.0, 0.0, 1.0 };
static int nlevels=40,skip=1;
static real scalemax=-1.0,rmsdcut=0.1,rmsmin=0.0;
static bool bRMSdist=FALSE,bBinary=FALSE,bAverage=FALSE,bFit=TRUE;
static int niter=10000,seed=1993,write_ncl=0,write_nst=1,minstruct=1;
static real kT=1e-3;
static int M=10,P=3;
t_pargs pa[] = {
{ "-dista", FALSE, etBOOL, {&bRMSdist},
"Use RMSD of distances instead of RMS deviation" },
{ "-nlevels",FALSE,etINT, {&nlevels},
"Discretize RMSD matrix in # levels" },
{ "-cutoff",FALSE, etREAL, {&rmsdcut},
"RMSD cut-off (nm) for two structures to be neighbor" },
{ "-fit", FALSE, etBOOL, {&bFit},
"Use least squares fitting before RMSD calculation" },
{ "-max", FALSE, etREAL, {&scalemax},
"Maximum level in RMSD matrix" },
{ "-skip", FALSE, etINT, {&skip},
"Only analyze every nr-th frame" },
{ "-av", FALSE, etBOOL, {&bAverage},
"Write average iso middle structure for each cluster" },
{ "-wcl", FALSE, etINT, {&write_ncl},
"Write all structures for first # clusters to numbered files" },
{ "-nst", FALSE, etINT, {&write_nst},
"Only write all structures if more than # per cluster" },
{ "-rmsmin",FALSE, etREAL, {&rmsmin},
"minimum rms difference with rest of cluster for writing structures" },
{ "-method",FALSE, etENUM, {methodname},
"Method for cluster determination" },
{ "-minstruct", FALSE, etINT, {&minstruct},
"Minimum number of structures in cluster for coloring in the xpm file" },
{ "-binary",FALSE, etBOOL, {&bBinary},
"Treat the RMSD matrix as consisting of 0 and 1, where the cut-off "
"is given by -cutoff" },
{ "-M", FALSE, etINT, {&M},
"Number of nearest neighbors considered for Jarvis-Patrick algorithm, "
"0 is use cutoff" },
{ "-P", FALSE, etINT, {&P},
"Number of identical nearest neighbors required to form a cluster" },
{ "-seed", FALSE, etINT, {&seed},
"Random number seed for Monte Carlo clustering algorithm" },
{ "-niter", FALSE, etINT, {&niter},
"Number of iterations for MC" },
{ "-kT", FALSE, etREAL, {&kT},
"Boltzmann weighting factor for Monte Carlo optimization "
"(zero turns off uphill steps)" }
};
t_filenm fnm[] = {
{ efTRX, "-f", NULL, ffOPTRD },
{ efTPS, "-s", NULL, ffOPTRD },
{ efNDX, NULL, NULL, ffOPTRD },
{ efXPM, "-dm", "rmsd", ffOPTRD },
{ efXPM, "-o", "rmsd-clust", ffWRITE },
{ efLOG, "-g", "cluster", ffWRITE },
{ efXVG, "-dist", "rmsd-dist", ffOPTWR },
{ efXVG, "-ev", "rmsd-eig", ffOPTWR },
{ efXVG, "-sz", "clust-size", ffOPTWR},
{ efXPM, "-tr", "clust-trans",ffOPTWR},
{ efXVG, "-ntr", "clust-trans",ffOPTWR},
{ efXVG, "-clid", "clust-id.xvg",ffOPTWR},
{ efTRX, "-cl", "clusters.pdb", ffOPTWR }
};
#define NFILE asize(fnm)
CopyRight(stderr,argv[0]);
parse_common_args(&argc,argv,PCA_CAN_VIEW | PCA_CAN_TIME | PCA_TIME_UNIT | PCA_BE_NICE,
NFILE,fnm,asize(pa),pa,asize(desc),desc,0,NULL);
/* parse options */
bReadMat = opt2bSet("-dm",NFILE,fnm);
bReadTraj = opt2bSet("-f",NFILE,fnm) || !bReadMat;
if ( opt2parg_bSet("-av",asize(pa),pa) ||
opt2parg_bSet("-wcl",asize(pa),pa) ||
opt2parg_bSet("-nst",asize(pa),pa) ||
opt2parg_bSet("-rmsmin",asize(pa),pa) ||
opt2bSet("-cl",NFILE,fnm) )
trx_out_fn = opt2fn("-cl",NFILE,fnm);
else
trx_out_fn = NULL;
if (bReadMat && time_factor()!=1) {
fprintf(stderr,
"\nWarning: assuming the time unit in %s is %s\n",
opt2fn("-dm",NFILE,fnm),time_unit());
}
if (trx_out_fn && !bReadTraj)
fprintf(stderr,"\nWarning: "
"cannot write cluster structures without reading trajectory\n"
" ignoring option -cl %s\n", trx_out_fn);
method=1;
while ( method < m_nr && strcasecmp(methodname[0], methodname[method])!=0 )
method++;
if (method == m_nr)
gmx_fatal(FARGS,"Invalid method");
bAnalyze = (method == m_linkage || method == m_jarvis_patrick ||
method == m_gromos );
/* Open log file */
log = ftp2FILE(efLOG,NFILE,fnm,"w");
fprintf(stderr,"Using %s method for clustering\n",methodname[0]);
fprintf(log,"Using %s method for clustering\n",methodname[0]);
/* check input and write parameters to log file */
bUseRmsdCut = FALSE;
if (method == m_jarvis_patrick) {
bJP_RMSD = (M == 0) || opt2parg_bSet("-cutoff",asize(pa),pa);
if ((M<0) || (M == 1))
gmx_fatal(FARGS,"M (%d) must be 0 or larger than 1",M);
if (M < 2) {
sprintf(buf1,"Will use P=%d and RMSD cutoff (%g)",P,rmsdcut);
bUseRmsdCut = TRUE;
} else {
if (P >= M)
gmx_fatal(FARGS,"Number of neighbors required (P) must be less than M");
if (bJP_RMSD) {
sprintf(buf1,"Will use P=%d, M=%d and RMSD cutoff (%g)",P,M,rmsdcut);
bUseRmsdCut = TRUE;
} else
sprintf(buf1,"Will use P=%d, M=%d",P,M);
}
ffprintf1(stderr,log,buf,"%s for determining the neighbors\n\n",buf1);
} else /* method != m_jarvis */
bUseRmsdCut = ( bBinary || method == m_linkage || method == m_gromos );
if (bUseRmsdCut && method != m_jarvis_patrick)
fprintf(log,"Using RMSD cutoff %g nm\n",rmsdcut);
if ( method==m_monte_carlo )
fprintf(log,"Using %d iterations\n",niter);
if (skip < 1)
gmx_fatal(FARGS,"skip (%d) should be >= 1",skip);
/* get input */
if (bReadTraj) {
/* don't read mass-database as masses (and top) are not used */
read_tps_conf(ftp2fn(efTPS,NFILE,fnm),buf,&top,&ePBC,&xtps,NULL,box,
bAnalyze);
fprintf(stderr,"\nSelect group for least squares fit%s:\n",
bReadMat?"":" and RMSD calculation");
get_index(&(top.atoms),ftp2fn_null(efNDX,NFILE,fnm),
1,&ifsize,&fitidx,&grpname);
if (trx_out_fn) {
fprintf(stderr,"\nSelect group for output:\n");
get_index(&(top.atoms),ftp2fn_null(efNDX,NFILE,fnm),
1,&iosize,&outidx,&grpname);
/* merge and convert both index groups: */
/* first copy outidx to index. let outidx refer to elements in index */
snew(index,iosize);
isize = iosize;
for(i=0; i<iosize; i++) {
index[i]=outidx[i];
outidx[i]=i;
}
/* now lookup elements from fitidx in index, add them if necessary
and also let fitidx refer to elements in index */
for(i=0; i<ifsize; i++) {
j=0;
while (j<isize && index[j]!=fitidx[i])
j++;
if (j>=isize) {
/* slow this way, but doesn't matter much */
isize++;
srenew(index,isize);
}
index[j]=fitidx[i];
fitidx[i]=j;
}
} else { /* !trx_out_fn */
isize = ifsize;
snew(index, isize);
for(i=0; i<ifsize; i++) {
index[i]=fitidx[i];
fitidx[i]=i;
}
}
}
/* Initiate arrays */
snew(d1,isize);
snew(d2,isize);
for(i=0; (i<isize); i++) {
snew(d1[i],isize);
snew(d2[i],isize);
}
if (bReadTraj) {
/* Loop over first coordinate file */
fn = opt2fn("-f",NFILE,fnm);
xx = read_whole_trj(fn,isize,index,skip,&nf,&time);
convert_times(nf, time);
if (!bRMSdist || bAnalyze) {
/* Center all frames on zero */
snew(mass,isize);
for(i=0; i<ifsize; i++)
mass[fitidx[i]] = top.atoms.atom[index[fitidx[i]]].m;
if (bFit)
for(i=0; i<nf; i++)
reset_x(ifsize,fitidx,isize,NULL,xx[i],mass);
}
}
if (bReadMat) {
fprintf(stderr,"Reading rms distance matrix ");
read_xpm_matrix(opt2fn("-dm",NFILE,fnm),&readmat);
fprintf(stderr,"\n");
if (readmat[0].nx != readmat[0].ny)
gmx_fatal(FARGS,"Matrix (%dx%d) is not square",
readmat[0].nx,readmat[0].ny);
if (bReadTraj && bAnalyze && (readmat[0].nx != nf))
gmx_fatal(FARGS,"Matrix size (%dx%d) does not match the number of "
"frames (%d)",readmat[0].nx,readmat[0].ny,nf);
nf = readmat[0].nx;
sfree(time);
time = readmat[0].axis_x;
time_invfac = time_invfactor();
for(i=0; i<nf; i++)
time[i] *= time_invfac;
rms = init_mat(readmat[0].nx,method == m_diagonalize);
convert_mat(&(readmat[0]),rms);
nlevels = readmat[0].nmap;
} else { /* !bReadMat */
rms = init_mat(nf,method == m_diagonalize);
nrms = (nf*(nf-1))/2;
if (!bRMSdist) {
fprintf(stderr,"Computing %dx%d RMS deviation matrix\n",nf,nf);
snew(x1,isize);
for(i1=0; (i1<nf); i1++) {
for(i2=i1+1; (i2<nf); i2++) {
for(i=0; i<isize; i++)
copy_rvec(xx[i1][i],x1[i]);
if (bFit)
do_fit(isize,mass,xx[i2],x1);
rmsd = rmsdev(isize,mass,xx[i2],x1);
set_mat_entry(rms,i1,i2,rmsd);
}
nrms -= (nf-i1-1);
fprintf(stderr,"\r# RMSD calculations left: %d ",nrms);
}
} else { /* bRMSdist */
fprintf(stderr,"Computing %dx%d RMS distance deviation matrix\n",nf,nf);
for(i1=0; (i1<nf); i1++) {
calc_dist(isize,xx[i1],d1);
for(i2=i1+1; (i2<nf); i2++) {
calc_dist(isize,xx[i2],d2);
set_mat_entry(rms,i1,i2,rms_dist(isize,d1,d2));
}
nrms -= (nf-i1-1);
fprintf(stderr,"\r# RMSD calculations left: %d ",nrms);
}
}
fprintf(stderr,"\n\n");
}
ffprintf2(stderr,log,buf,"The RMSD ranges from %g to %g nm\n",
rms->minrms,rms->maxrms);
ffprintf1(stderr,log,buf,"Average RMSD is %g\n",2*rms->sumrms/(nf*(nf-1)));
ffprintf1(stderr,log,buf,"Number of structures for matrix %d\n",nf);
ffprintf1(stderr,log,buf,"Energy of the matrix is %g nm\n",mat_energy(rms));
if (bUseRmsdCut && (rmsdcut < rms->minrms || rmsdcut > rms->maxrms) )
fprintf(stderr,"WARNING: rmsd cutoff %g is outside range of rmsd values "
"%g to %g\n",rmsdcut,rms->minrms,rms->maxrms);
if (bAnalyze && (rmsmin < rms->minrms) )
fprintf(stderr,"WARNING: rmsd minimum %g is below lowest rmsd value %g\n",
rmsmin,rms->minrms);
if (bAnalyze && (rmsmin > rmsdcut) )
fprintf(stderr,"WARNING: rmsd minimum %g is above rmsd cutoff %g\n",
rmsmin,rmsdcut);
/* Plot the rmsd distribution */
rmsd_distribution(opt2fn("-dist",NFILE,fnm),rms);
if (bBinary) {
for(i1=0; (i1 < nf); i1++)
for(i2=0; (i2 < nf); i2++)
if (rms->mat[i1][i2] < rmsdcut)
rms->mat[i1][i2] = 0;
else
rms->mat[i1][i2] = 1;
}
snew(clust.cl,nf);
switch (method) {
case m_linkage:
/* Now sort the matrix and write it out again */
gather(rms,rmsdcut,&clust);
break;
case m_diagonalize:
/* Do a diagonalization */
snew(eigval,nf);
snew(tmp,nf*nf);
memcpy(tmp,rms->mat[0],nf*nf*sizeof(real));
eigensolver(tmp,nf,0,nf,eigval,rms->mat[0]);
sfree(tmp);
fp = xvgropen(opt2fn("-ev",NFILE,fnm),"RMSD matrix Eigenvalues",
"Eigenvector index","Eigenvalues (nm\\S2\\N)");
for(i=0; (i<nf); i++)
fprintf(fp,"%10d %10g\n",i,eigval[i]);
ffclose(fp);
break;
case m_monte_carlo:
mc_optimize(log,rms,niter,&seed,kT);
swap_mat(rms);
reset_index(rms);
break;
case m_jarvis_patrick:
jarvis_patrick(rms->nn,rms->mat,M,P,bJP_RMSD ? rmsdcut : -1,&clust);
break;
case m_gromos:
gromos(rms->nn,rms->mat,rmsdcut,&clust);
break;
default:
gmx_fatal(FARGS,"DEATH HORROR unknown method \"%s\"",methodname[0]);
}
if (method == m_monte_carlo || method == m_diagonalize)
fprintf(stderr,"Energy of the matrix after clustering is %g nm\n",
mat_energy(rms));
if (bAnalyze) {
if (minstruct > 1) {
ncluster = plot_clusters(nf,rms->mat,&clust,nlevels,minstruct);
} else {
mark_clusters(nf,rms->mat,rms->maxrms,&clust);
}
init_t_atoms(&useatoms,isize,FALSE);
snew(usextps, isize);
useatoms.resname=top.atoms.resname;
for(i=0; i<isize; i++) {
useatoms.atomname[i]=top.atoms.atomname[index[i]];
useatoms.atom[i].resnr=top.atoms.atom[index[i]].resnr;
useatoms.nres=max(useatoms.nres,useatoms.atom[i].resnr+1);
copy_rvec(xtps[index[i]],usextps[i]);
}
useatoms.nr=isize;
analyze_clusters(nf,&clust,rms->mat,isize,&useatoms,usextps,mass,xx,time,
ifsize,fitidx,iosize,outidx,
bReadTraj?trx_out_fn:NULL,
opt2fn_null("-sz",NFILE,fnm),
opt2fn_null("-tr",NFILE,fnm),
opt2fn_null("-ntr",NFILE,fnm),
opt2fn_null("-clid",NFILE,fnm),
bAverage, write_ncl, write_nst, rmsmin, bFit, log,
rlo_bot,rhi_bot);
}
ffclose(log);
if (bBinary && !bAnalyze)
/* Make the clustering visible */
for(i2=0; (i2 < nf); i2++)
for(i1=i2+1; (i1 < nf); i1++)
if (rms->mat[i1][i2])
rms->mat[i1][i2] = rms->maxrms;
fp = opt2FILE("-o",NFILE,fnm,"w");
fprintf(stderr,"Writing rms distance/clustering matrix ");
if (bReadMat) {
write_xpm(fp,0,readmat[0].title,readmat[0].legend,readmat[0].label_x,
readmat[0].label_y,nf,nf,readmat[0].axis_x,readmat[0].axis_y,
rms->mat,0.0,rms->maxrms,rlo_top,rhi_top,&nlevels);
}
else {
sprintf(buf,"Time (%s)",time_unit());
sprintf(title,"RMS%sDeviation / Cluster Index",
bRMSdist ? " Distance " : " ");
if (minstruct > 1) {
write_xpm_split(fp,0,title,"RMSD (nm)",buf,buf,
nf,nf,time,time,rms->mat,0.0,rms->maxrms,&nlevels,
rlo_top,rhi_top,0.0,(real) ncluster,
&ncluster,TRUE,rlo_bot,rhi_bot);
} else {
write_xpm(fp,0,title,"RMSD (nm)",buf,buf,
nf,nf,time,time,rms->mat,0.0,rms->maxrms,
rlo_top,rhi_top,&nlevels);
}
}
fprintf(stderr,"\n");
ffclose(fp);
/* now show what we've done */
do_view(opt2fn("-o",NFILE,fnm),"-nxy");
do_view(opt2fn_null("-sz",NFILE,fnm),"-nxy");
if (method == m_diagonalize)
do_view(opt2fn_null("-ev",NFILE,fnm),"-nxy");
do_view(opt2fn("-dist",NFILE,fnm),"-nxy");
if (bAnalyze) {
do_view(opt2fn_null("-tr",NFILE,fnm),"-nxy");
do_view(opt2fn_null("-ntr",NFILE,fnm),"-nxy");
do_view(opt2fn_null("-clid",NFILE,fnm),"-nxy");
}
/* Thank the user for her patience */
thanx(stderr);
return 0;
}
