void plot_add_model(plot *p, model_func *f, const mat *x_0, const size_t j, \
const mat *par, void *f_param, const double xmin, \
const double xmax, const size_t npt, const strbuf title,\
const strbuf color)
{
mat *x,*y,*X;
size_t i;
double x_i,y_i;
x = mat_create(npt,1);
y = mat_create(npt,1);
X = mat_create_from_mat(x_0);
for (i=0;i<npt;i++)
{
x_i = xmin + (xmax-xmin)*DRATIO(i,npt-1);
mat_set(X,j,0,x_i);
y_i = f(X,par,f_param);
mat_set(x,i,0,x_i);
mat_set(y,i,0,y_i);
}
plot_add_line(p,x,y,title,color);
mat_destroy(x);
mat_destroy(y);
mat_destroy(X);
}
//Brief: QR decomposition
void qrdec(mat *A, mat* R){
double proj = 0;
double norm = 0;
// Allocates pointers of type *vec
//vec *coli = (vec*)malloc(sizeof(vec));
//vec *colj = (vec*)malloc(sizeof(vec));
vec* coli = vec_new(A->row);
vec* colj = vec_new(A->row);
for(int i=0; i<A->col; i++){
mat_get_col(coli, A, i);
norm = vec_norm(coli);
mat_set(R, i, i, norm);
vec_scale(coli, 1.0/norm);
mat_set_col(A, coli, i);
for(int j=i+1; j<A->col; j++){
mat_get_col(colj, A, j);
proj = vec_dot(coli,colj);
vec_add(colj,coli,-proj);
mat_set_col(A, colj, j);
mat_set(R, i, j, proj);
}
}
// Free pointers
vec_free(coli);
vec_free(colj);
}
extern inline void mat_exchange(Matrix dest,int i,int j){
int k;
double s;
for(k=0;k<dest.column;k++){
s=mat_get(dest,i,k);
mat_set(dest,i,k,mat_get(dest,j,k));
mat_set(dest,j,k,s);
}
}
extern inline Matrix mat_I(int m,int n){
Matrix I;
int i,j;
mat_init(&I,m,n);
for(i=0;i<m;i++){
for(j=0;j<m;j++){
if(i==j)
mat_set(I,i,j,1.0);
else
mat_set(I,i,j,0.0);
}
}
return I;
}
/* Read substitution scores from specified file and return as a kind
of pseudo substitution matrix. All nonspecified elements in matrix
will be equal to NEGINFTY, which is to be interpretted as "NA" */
Matrix* read_subst_scores(TreeModel *mod, FILE *F) {
Matrix *retval = mat_new(mod->rate_matrix->size,
mod->rate_matrix->size);
String *line = str_new(STR_MED_LEN), *tuple1, *tuple2;
List *l = lst_new_ptr(3);
int alph_size = (int)strlen(mod->rate_matrix->states);
int *inv_alph = mod->rate_matrix->inv_states;
double val;
mat_set_all(retval, NEGINFTY);
while (str_readline(line, F) != EOF) {
str_double_trim(line);
if (str_starts_with_charstr(line, "#") || line->length == 0)
continue;
str_split(line, NULL, l);
if (lst_size(l) < 3) {
die("ERROR: wrong number of columns in subst. score file.\n");
}
tuple1 = lst_get_ptr(l, 0);
tuple2 = lst_get_ptr(l, 1);
if (str_as_dbl(lst_get_ptr(l, 2), &val) != 0) {
die("ERROR: bad value in subst. score file.\n");
}
mat_set(retval, tuple_index(tuple1->chars, inv_alph, alph_size),
tuple_index(tuple2->chars, inv_alph, alph_size), val);
str_free(tuple1); str_free(tuple2); str_free(lst_get_ptr(l, 2));
}
lst_free(l);
str_free(line);
return retval;
}
Matrix* unproject_rates(TreeModel *mod_tuples, TreeModel *mod_single) {
int dim = mod_tuples->rate_matrix->size;
int alph_size = (int)strlen(mod_tuples->rate_matrix->states);
char tuple_i[mod_tuples->order+1], tuple_j[mod_tuples->order+1];
int position, i, j;
Matrix *retval = mat_new(dim, dim);
mat_zero(retval);
for (i = 0; i < dim; i++) {
get_tuple_str(tuple_i, i, mod_tuples->order+1,
mod_tuples->rate_matrix->states);
for (j = 0; j < dim; j++) {
if (i == j || mm_get(mod_tuples->rate_matrix, i, j) == 0) continue;
/* WARNING: we'll ignore any rate matrix elements that have
*actually been estimated* to be zero */
get_tuple_str(tuple_j, j, mod_tuples->order+1,
mod_tuples->rate_matrix->states);
position = mod_tuples->order - (int)(floor(log(abs(i - j))/log(alph_size)));
mat_set(retval, i, j,
mm_get(mod_single->rate_matrix,
mod_single->rate_matrix->inv_states[(int)tuple_i[position]],
mod_single->rate_matrix->inv_states[(int)tuple_j[position]]));
}
}
return retval;
}
/* Read an amino acid rate matrix in the format used by PAML. Reorder
the rows and columns to match 'alph'. Warning: the ordering in the
file is assumed to match that used in the files in the PAML
distribution (alphabetical order of 3-letter codes), which is also
the order of AA_ALPHABET (therefore AA_ALPHABET may not be
changed!). Equilibrium frequencies are ignored. */
Matrix *read_paml_matrix(FILE *F, char *alph) {
char *paml_alph = "ARNDCQEGHILKMFPSTWYV$";
int size = (int)strlen(paml_alph);
Matrix *retval = mat_new(size, size);
List *fields = lst_new_ptr(100);
String *line = str_new(STR_MED_LEN);
int i, j;
if (strcmp(alph, paml_alph) != 0)
die("ERROR read_paml_matrix (alph (%s) != paml_alph (%s))\n",
alph, paml_alph);
mat_zero(retval);
for (i = 1; i < size-1 && str_readline(line, F) != EOF; ) {
/* NOTE: size of matrix allows for stop, but stop not included in
file; therefore, only read size-1 lines */
str_double_trim(line);
if (line->length == 0) continue;
str_split(line, NULL, fields);
if (lst_size(fields) != i) {
die("ERROR: row %d of matrix must have %d columns.\n",
i+1, i);
}
for (j = 0; j < lst_size(fields); j++) {
double val;
if (str_as_dbl(lst_get_ptr(fields, j), &val) != 0) {
die("ERROR: non-numeric matrix element in subst. matrix ('%s')\n",
((String*)lst_get_ptr(fields, j+1))->chars);
}
str_free(lst_get_ptr(fields, j));
if (j >= size)
die("ERROR read_paml_matrix j (%i) should be < size (%i)\n", j, size);
mat_set(retval, i, j, val);
mat_set(retval, j, i, val);
}
i++;
}
if (i != size - 1) {
die("ERROR: too few rows in subst. matrix.\n");
}
lst_free(fields);
str_free(line);
return retval;
}
extern inline void mat_cp_rt(Matrix dest,Matrix src){
int i,j;
int r_max=MIN(dest.raw,src.raw);
int c_max=MIN(dest.column,src.column);
for(i=0;i<r_max;i++){
for(j=0;j<c_max;j++){
mat_set(dest,i,dest.column-j-1,mat_get(src,i,src.column-j-1));
}
}
}
void plot_add_fit_predband(plot *p, const fit_data *d, const size_t ky,\
const mat *x_ex, const size_t kx, \
const rs_sample *par, const double xmin, \
const double xmax, const size_t npt, \
const strbuf color)
{
mat *x,*yp,*ym,*y_i_err,*X;
rs_sample *s_y_i;
size_t i;
double x_i,yp_i,ym_i;
x = mat_create(npt,1);
yp = mat_create(npt,1);
ym = mat_create(npt,1);
y_i_err = mat_create(1,1);
s_y_i = rs_sample_create(1,1,rs_sample_get_nsample(par));
X = mat_create_from_mat(x_ex);
for (i=0;i<npt;i++)
{
x_i = xmin + (xmax-xmin)*DRATIO(i,npt-1);
mat_set(X,kx,0,x_i);
fit_data_model_rs_xeval(s_y_i,d,ky,X,par);
rs_sample_var(y_i_err,s_y_i);
mat_eqsqrt(y_i_err);
yp_i = mat_get(rs_sample_pt_cent_val(s_y_i),0,0) + mat_get(y_i_err,0,0);
ym_i = mat_get(rs_sample_pt_cent_val(s_y_i),0,0) - mat_get(y_i_err,0,0);
mat_set(yp,i,0,yp_i);
mat_set(ym,i,0,ym_i);
mat_set(x,i,0,x_i);
}
plot_add_line(p,x,yp,"",color);
plot_add_line(p,x,ym,"",color);
mat_destroy(x);
mat_destroy(yp);
mat_destroy(ym);
mat_destroy(y_i_err);
rs_sample_destroy(s_y_i);
mat_destroy(X);
}
int mat_lup_decompose(mat_t out, long *pi, const mat_t mat,
const ctx_t ctx)
{
if (!(mat->m == out->m && mat->n && out->n && mat->m == mat->n))
{
printf("ERROR (mat_lup_decompose).\n\n");
abort();
}
mat_set(out, mat, ctx);
return _mat_lup_decompose(pi, out->rows, out->m, ctx);
}
void plot_add_func(plot *p, univar_func *f, void *f_param, const double xmin,\
const double xmax, const size_t npt, const strbuf title, \
const strbuf color)
{
mat *x,*y;
size_t i;
double x_i,y_i;
x = mat_create(npt,1);
y = mat_create(npt,1);
for (i=0;i<npt;i++)
{
x_i = xmin + (xmax-xmin)*DRATIO(i,npt-1);
y_i = f(x_i,f_param);
mat_set(x,i,0,x_i);
mat_set(y,i,0,y_i);
}
plot_add_line(p,x,y,title,color);
mat_destroy(x);
mat_destroy(y);
}
latan_errno finite_diff(mat *ddat, const mat *dat)
{
size_t i,j;
double ddat_ij;
if (nrow(ddat) != nrow(dat) - 2)
{
LATAN_ERROR("derivative matrix have wrong dimensions",LATAN_EBADLEN);
}
FOR_VAL(ddat,i,j)
{
ddat_ij = 0.5*(mat_get(dat,i+2,j) - mat_get(dat,i,j));
mat_set(ddat,i,j,ddat_ij);
}
t_mat *mat_translation(t_mat *dest, t_pt3f direction)
{
if (dest == NULL)
dest = mat_new(4, 4);
mat_zero(dest);
mat_set(dest, 0, 0, 1);
mat_set(dest, 1, 1, 1);
mat_set(dest, 2, 2, 1);
mat_set(dest, 3, 3, 1);
mat_set(dest, 3, 0, direction.x);
mat_set(dest, 3, 1, direction.y);
mat_set(dest, 3, 2, direction.z);
return (dest);
}
/* Invert square, real, nonsymmetric matrix. Uses LU decomposition
(LAPACK routines dgetrf and dgetri). Returns 0 on success, 1 on
failure. */
int mat_invert(Matrix *M_inv, Matrix *M) {
#ifdef SKIP_LAPACK
die("ERROR: LAPACK required for matrix inversion.\n");
#else
int i, j;
LAPACK_INT info, n = (LAPACK_INT)M->nrows, ipiv[n], lwork=(LAPACK_INT)n;
LAPACK_DOUBLE tmp[n][n], work[lwork];
if (!(M->nrows == M->ncols && M_inv->nrows == M_inv->ncols &&
M->nrows == M_inv->nrows))
die("ERROR mat_invert: bad dimensions\n");
for (i = 0; i < n; i++)
for (j = 0; j < n; j++)
tmp[i][j] = (LAPACK_DOUBLE)mat_get(M, j, i);
#ifdef R_LAPACK
F77_CALL(dgetrf)(&n, &n, (LAPACK_DOUBLE*)tmp, &n, ipiv, &info);
#else
dgetrf_(&n, &n, (LAPACK_DOUBLE*)tmp, &n, ipiv, &info);
#endif
if (info != 0) {
fprintf(stderr, "ERROR: unable to compute LU factorization of matrix (for matrix inversion); dgetrf returned value of %d.\n", (int)info);
return 1;
}
#ifdef R_LAPACK
F77_CALL(dgetri)(&n, (LAPACK_DOUBLE*)tmp, &n, ipiv, work, &lwork, &info);
#else
dgetri_(&n, (LAPACK_DOUBLE*)tmp, &n, ipiv, work, &lwork, &info);
#endif
if (info != 0) {
if (info > 0)
fprintf(stderr, "ERROR: matrix is singular -- cannot invert.\n");
else
fprintf(stderr, "ERROR: unable to invert matrix. Element %d had an illegal value (according to dgetri).\n", (int)info);
return 1;
}
for (i = 0; i < M->nrows; i++)
for (j = 0; j < M->nrows; j++)
mat_set(M_inv, i, j, (double)tmp[j][i]);
#endif
return 0;
}
/* multiply two complex matrices whose product is expected to be real */
void zmat_mult_real(Matrix *prod, Zmatrix *m1, Zmatrix *m2) {
int i, j, k;
if (!(m1->ncols == m2->nrows && m1->nrows == m2->ncols &&
prod->nrows == m1->nrows && prod->ncols == m2->ncols))
die("ERROR zmat_mult_real: bad dimensions\n");
mat_zero(prod);
for (i = 0; i < prod->nrows; i++) {
for (j = 0; j < prod->ncols; j++) {
Complex z = z_set(0, 0);
for (k = 0; k < m1->ncols; k++)
z = z_add(z, z_mul(m1->data[i][k], m2->data[k][j]));
if (z.y > 1e-6)
die("ERROR in zmat_mult_real: product of complex matrices not real.\n");
mat_set(prod, i, j, z.x);
}
}
}
static void get_inertia_factor(const double *inertia, const mat_t *rotmat,
mat_t *inertia_fact)
{
double fact[3];
for (size_t i = 0; i < 3; i++)
fact[i] = inertia[i] < EPSILON ? 0.0 : 1.0 / sqrt(inertia[i]);
for (size_t i = 0; i < 3; i++) {
for (size_t j = 0; j < 3; j++) {
double sum = 0.0;
for (size_t k = 0; k < 3; k++)
sum += fact[k] * mat_get(rotmat, i, k) * mat_get(rotmat, j, k);
mat_set(inertia_fact, i, j, sum);
}
}
}
extern inline int mat_mul(Matrix dest,Matrix a,Matrix b){
int i,j,k;
double s;
if(dest.raw==a.raw&&dest.column==b.column&&a.column==b.raw){
for(i=0;i<dest.raw;i++){
for(j=0;j<dest.column;j++){
s=0;
for(k=0;k<a.column;k++){
s+=mat_get(a,i,k)*mat_get(b,k,j);
}
mat_set(dest,i,j,s);
}
}
return 0;
}else{
fprintf(stderr,"Error:乗法を行おうとしている行列の大きさが合っていません\n");
return -1;
}
}
static void rotate_step(size_t a1, size_t a2, double angle, vec_t *angmom, mat_t *rotmat)
{
mat_t rot = { 1.0, 0.0, 0.0,
0.0, 1.0, 0.0,
0.0, 0.0, 1.0 };
double cosa = cos(angle);
double sina = sin(angle);
mat_set(&rot, a1, a1, cosa);
mat_set(&rot, a2, a2, cosa);
mat_set(&rot, a1, a2, sina);
mat_set(&rot, a2, a1, -sina);
*angmom = mat_vec(&rot, angmom);
/* transpose */
mat_set(&rot, a1, a2, -sina);
mat_set(&rot, a2, a1, sina);
*rotmat = mat_mat(rotmat, &rot);
}
int
main(void)
{
int i, result;
flint_rand_t state;
printf("transpose... ");
fflush(stdout);
_randinit(state);
/* Check aliasing */
/* Unmanaged element type (long) */
for (i = 0; i < 100; i++)
{
long m, n;
ctx_t ctx;
mat_t A, B, C;
m = n_randint(state, 50) + 1;
n = m;
ctx_init_long(ctx);
mat_init(A, m, n, ctx);
mat_init(B, m, n, ctx);
mat_init(C, m, n, ctx);
mat_randtest(A, state, ctx);
mat_set(B, A, ctx);
mat_transpose(C, B, ctx);
mat_transpose(B, B, ctx);
result = mat_equal(B, C, ctx);
if (!result)
{
printf("FAIL:\n\n");
printf("Matrix A\n");
mat_print(A, ctx);
printf("\n");
printf("Matrix B\n");
mat_print(B, ctx);
printf("\n");
printf("Matrix C\n");
mat_print(C, ctx);
printf("\n");
}
mat_clear(A, ctx);
mat_clear(B, ctx);
mat_clear(C, ctx);
ctx_clear(ctx);
}
/* Check that (A^t)^t == A */
/* Unmanaged element type (long) */
for (i = 0; i < 100; i++)
{
long m, n;
ctx_t ctx;
mat_t A, B, C;
m = n_randint(state, 50) + 1;
n = n_randint(state, 50) + 1;
ctx_init_long(ctx);
mat_init(A, m, n, ctx);
mat_init(B, n, m, ctx);
mat_init(C, m, n, ctx);
mat_randtest(A, state, ctx);
mat_transpose(B, A, ctx);
mat_transpose(C, B, ctx);
result = mat_equal(A, C, ctx);
if (!result)
{
printf("FAIL:\n\n");
printf("Matrix A\n");
mat_print(A, ctx);
printf("\n");
printf("Matrix B\n");
mat_print(B, ctx);
printf("\n");
printf("Matrix C\n");
mat_print(C, ctx);
printf("\n");
}
mat_clear(A, ctx);
mat_clear(B, ctx);
mat_clear(C, ctx);
ctx_clear(ctx);
}
_randclear(state);
_fmpz_cleanup();
printf("PASS\n");
return EXIT_SUCCESS;
}
void sc_light_updateSpotMtx(ENTITY* inLight)
{
SC_OBJECT* ObjData = (SC_OBJECT*)(inLight.SC_SKILL);
float fTexAdj[16] =
{ 0.5, 0.0, 0.0, 0.0,
0.0,-0.5, 0.0, 0.0,
0.0, 0.0, 1.0, 0.0,
0.0, 0.0, 0.0, 1.0 };
fTexAdj[12] = 0.5 + ((float)0.5/(float)256);
fTexAdj[13] = 0.5 + ((float)0.5/(float)256);
VECTOR lightDir;
//lightDir = malloc(sizeof(VECTOR));
if(inLight.tilt > 89.9 && inLight.tilt < 90.1 || inLight.tilt < -89.9 && inLight.tilt > -90.1)
{
vec_set(lightDir, inLight.pan);
lightDir.y += 0.2;
vec_for_angle(lightDir,lightDir);
}
else vec_for_angle(lightDir, inLight.pan);
sc_skill(inLight, SC_OBJECT_LIGHT_DIR, lightDir);
//if(lightDir.y == -90) lightDir.y = 80; //might have to comment this in again (?)
/*
//if spotlight has a shadowview attached
if(ObjData.light.view != NULL)
{
D3DXMATRIX matView_, matProj_;
view_to_matrix(ObjData.light.view, &matView_, &matProj_);
mat_multiply(&matView_, &matProj_);
mat_multiply(&matView_, fTexAdj);
sc_skill(inLight, SC_OBJECT_LIGHT_MATRIX, &matView_);
ptr_remove(matView_);
ptr_remove(matProj_);
return;
}
*/
//create lightViewMatrix
D3DXVECTOR3 vEyePt;
D3DXVECTOR3 vLookatPt;
D3DXVECTOR3 vUpVec;
//vEyePt = sys_malloc(sizeof(D3DXVECTOR3));
//vLookatPt = sys_malloc(sizeof(D3DXVECTOR3));
//vUpVec = sys_malloc(sizeof(D3DXVECTOR3));
vEyePt.x = inLight.x;
vEyePt.y = inLight.z;
vEyePt.z = inLight.y;
vLookatPt.x = inLight.x + lightDir.x;
vLookatPt.y = inLight.z + lightDir.z;
vLookatPt.z = inLight.y + lightDir.y;
vUpVec.x = 0;
vUpVec.y = 1;
vUpVec.z = 0;
D3DXMATRIX mtxLightView;
//mtxLightView = sys_malloc(sizeof(D3DXMATRIX));
D3DXMatrixLookAtLH( &mtxLightView, vEyePt, vLookatPt, vUpVec);
//create lightProjectionMatrix
D3DXMATRIX mtxLightProj;
D3DXMatrixPerspectiveFovLH(&mtxLightProj, (((float)ObjData.light.arc/(float)180))*SC_PI, (float)1, (float)1, (float)ObjData.light.range );
//pass projection matrix to light
D3DXMATRIX mtxLightWorldViewProj;
//mtxLightWorldViewProj = sys_malloc(sizeof(D3DXMATRIX));
mat_set(&mtxLightWorldViewProj, &mtxLightView);
mat_multiply(&mtxLightWorldViewProj, &mtxLightProj);
mat_multiply(&mtxLightWorldViewProj, fTexAdj);
sc_skill(inLight, SC_OBJECT_LIGHT_MATRIX, &mtxLightWorldViewProj);
/*
//this lags like hell
sys_free(vEyePt);
sys_free(vLookatPt);
sys_free(vUpVec);
sys_free(mtxLightView);
sys_free(mtxLightProj);
sys_free(mtxLightWorldViewProj);
*/
//better
ptr_remove(vEyePt);
ptr_remove(vLookatPt);
ptr_remove(vUpVec);
ptr_remove(mtxLightView);
ptr_remove(mtxLightProj);
ptr_remove(mtxLightWorldViewProj);
}
List *pwm_read(const char *filename) {
List *result;
Matrix *pwm = NULL;
int i, currBase, nBases = 0;
FILE * F;
// char *motifName;
String *line = str_new(STR_MED_LEN);
List *l = lst_new_ptr(3);
List *probabilitiesStr = lst_new_ptr(4);
List *probabilitiesDbl;
Regex *pssm_re = NULL;
Regex *motif_name_re = NULL;
int alphabetLength;
result = lst_new_ptr(1);
//letter-probability matrix: alength= 4 w= 8 nsites= 2 E= 1.5e+004
pssm_re = str_re_new("^letter-probability matrix: alength= ([0-9]+) w= ([0-9]+)");
motif_name_re = str_re_new("^MOTIF[[:space:]]+(.+?)[[:space:]].*");
//open PWM file
F = phast_fopen(filename, "r");
currBase = 0;
nBases = -1;
//For each line in the MEME file
while ((str_readline(line, F)) != EOF) {
//If line matches Motif name
if (str_re_match(line, motif_name_re, l, 1) > 0) {
// motifName = copy_charstr(((String*)lst_get_ptr(l, 1))->chars);
//printf("motifName=%s\n", motifName);
}
//If line matches beginning of a probability matrix
else if (str_re_match(line, pssm_re, l, 2) > 0) {
//Extract the alphabet size & number of bases in matrix
if (str_as_int((String*)lst_get_ptr(l, 1), &alphabetLength) != 0)
die("ERROR: Unable to parse 'alength=' from MEME file, expected integer, read %s", ((String*)lst_get_ptr(l, 1))->chars);
if (str_as_int((String*)lst_get_ptr(l, 2), &nBases) != 0)
die("ERROR: Unable to parse 'w=' from MEME file, expected integer, read %s ", ((String*)lst_get_ptr(l, 2))->chars);
currBase = 0;
if (nBases <= 0) //We must have at least one base in the PWM
die("ERROR: No Position Weight Matrices were detected in the provided PWM file");
if (alphabetLength <= 0) //We must have a positive alphabet length
die("ERROR: Alphabet lengh specified in PWM file must be greater than zero");
pwm = mat_new(nBases, alphabetLength);
mat_set_all(pwm, -1);
continue;
//If this row contains matrix data
} else if (currBase < nBases) {
//Parse row of probabilities
str_double_trim(line);
str_split(line, NULL, probabilitiesStr);
probabilitiesDbl = str_list_as_dbl(probabilitiesStr);
for (i = 0; i < lst_size(probabilitiesDbl); i++)
mat_set(pwm, currBase, i, log(lst_get_dbl(probabilitiesDbl, i)));
currBase++;
} else if ((currBase == nBases) && (pwm != NULL)) {
//Push full matrix
lst_push_ptr(result, pwm);
pwm = NULL;
}
}
if (currBase == nBases && pwm != NULL)
lst_push_ptr(result, pwm);
else if (pwm != NULL)
die("Premature end of PWM file\n");
str_re_free(motif_name_re);
str_re_free(pssm_re);
phast_fclose(F);
return result;
}
Matrix *mm_build_helper(MS *inputMS, int norder, int pseudoCount, int considerReverse) {
int alph_size, i, j, ignore, tup_idx, l, alph_idx, seqLen;
double sum = 0, val;
Vector *freqs = vec_new(int_pow(4, norder+1));
Matrix *mm;
char c;
if(inputMS == NULL)
die("ERROR: GC% group passed to mm_build_helper was null");
if (inputMS->nseqs <= 0) //Must have at least one sequence
die("ERROR: At least one sequence must be present to build a markov model");
if (norder < 0)//Order of Markov matrix must be positive
die("Order of markov model to create must be zero or greater");
vec_zero(freqs);
alph_size = (int)strlen(inputMS->alphabet);
//Apply Pseudo-Counts
vec_set_all(freqs, pseudoCount);
//For each sequence
for (j = 0; j < inputMS->nseqs; j++) {
seqLen = (int)strlen(inputMS->seqs[j]);
//For each site
for (i = 0; i < seqLen; i++) {
checkInterruptN(i, 10000);
ignore = 0;
tup_idx = 0;
//For each base in the tuple
for (l = 0; !ignore && l <= norder; l++) {
c = inputMS->seqs[j][i + l];
if ((alph_idx = inputMS->inv_alphabet[(int)c]) == -1) //If we get an unknown base
ignore = 1;
else
tup_idx += alph_idx * int_pow(alph_size, (norder - l));
}
if (!ignore)
vec_set(freqs, tup_idx,
vec_get(freqs, tup_idx) + 1);
}
}
//Take into account reverse complement frequencies
if(considerReverse == 1)
{
//For each sequence
for (j = 0; j < inputMS->nseqs; j++) {
//For each site
for (i = (int)strlen(inputMS->seqs[j]); i >= 0 ; i--) {
checkInterruptN(i, 10000);
ignore = 0;
tup_idx = 0;
//For each base in the tuple
for (l = 0; !ignore && l <= norder; l++) {
c = inputMS->seqs[j][i - l];
switch(c)
{
case 'A':
c = 'T';
break;
case 'C':
c = 'G';
break;
case 'G':
c = 'C';
break;
case 'T':
c = 'A';
break;
}
if ((alph_idx = inputMS->inv_alphabet[(int)c]) == -1) //If we get an unknown base
ignore = 1;
else
tup_idx += alph_idx * int_pow(alph_size, (norder - l));
}
if (!ignore)
vec_set(freqs, tup_idx,
vec_get(freqs, tup_idx) + 1);
}
}
}
mm = mat_new(int_pow(alph_size, norder), alph_size);
//Transform count vector into Markov Matrix of order norder
for (i = 0; i < freqs->size; i = i + alph_size) {
sum = 0;
for (j = 0; j < alph_size; j++) //Calculate sum i.e. for AA = count(AAA) + count(AAC) + count(AAG) + count(AAT)
sum += vec_get(freqs, i + j);
for (j = 0; j < alph_size; j++) { //For each base in alphabet
if (sum == 0) //Handle unknown <prefix, base> tuples
val = 1.0/alph_size;
else
val = vec_get(freqs, i + j) / sum; //i.e. for AAT, AA identified by i, T defined by j; #AAT/#AA
if((val < 0) || (val > 1)) //Value should be a probability between 0 and 1
die("ERROR: Generating Markov Models, generated probability must be between 0 and 1");
mat_set(mm, i / alph_size, j, val);
}
}
return mm;
}
int
main(int argc, char *argv[])
{
int i,j,k,nn;
int imax,jmax,kmax,mimax,mjmax,mkmax,msize[3];
float gosa;
double cpu0,cpu1,cpu,flop;
// hardcode to S size
msize[0]= 64;
msize[1]= 64;
msize[2]= 128;
mimax= msize[0];
mjmax= msize[1];
mkmax= msize[2];
imax= mimax-1;
jmax= mjmax-1;
kmax= mkmax-1;
printf("mimax = %d mjmax = %d mkmax = %d\n",mimax,mjmax,mkmax);
printf("imax = %d jmax = %d kmax =%d\n",imax,jmax,kmax);
/*
* Initializing matrixes
*/
newMat(&p,1,mimax,mjmax,mkmax);
newMat(&bnd,1,mimax,mjmax,mkmax);
newMat(&wrk1,1,mimax,mjmax,mkmax);
newMat(&wrk2,1,mimax,mjmax,mkmax);
newMat(&a,4,mimax,mjmax,mkmax);
newMat(&b,3,mimax,mjmax,mkmax);
newMat(&c,3,mimax,mjmax,mkmax);
mat_set_init(&p);
mat_set(&bnd,0,1.0);
mat_set(&wrk1,0,0.0);
mat_set(&wrk2,0,0.0);
mat_set(&a,0,1.0);
mat_set(&a,1,1.0);
mat_set(&a,2,1.0);
mat_set(&a,3,1.0/6.0);
mat_set(&b,0,0.0);
mat_set(&b,1,0.0);
mat_set(&b,2,0.0);
mat_set(&c,0,1.0);
mat_set(&c,1,1.0);
mat_set(&c,2,1.0);
/*
* Start measuring
*/
nn= 64;
gosa = jacobi(nn,&a,&b,&c,&p,&bnd,&wrk1,&wrk2);
printf(" Loop executed for %d times\n",nn);
printf(" Gosa : %e \n",gosa);
/*
* Matrix free
*/
clearMat(&p);
clearMat(&bnd);
clearMat(&wrk1);
clearMat(&wrk2);
clearMat(&a);
clearMat(&b);
clearMat(&c);
return (0);
}
void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
{
double M;
double log_thr;
int Xs,D,Ys,i,j,ep=0;
int maxentep;
int pxy_size;
double mx;
Matrix phi,psi,phi_tr,psi_tr,phi_exp_d,psi_exp_d,psi_exp_m,phi_exp_m,grad_phi,grad_psi;
double *px0,*py0,*px,*py,*pa,*pb,*grad_a,*grad_b;
double Z,loglik;
int xi,yi,di;
int b_cond; /* Says if the model is conditioned on x, or joint */
double *p0_i,*p0_j,*p0_val;
int Np0;
MatFromMLab(prhs[0],&phi); /* Size NX,D */
MatFromMLab(prhs[1],&psi); /* Size NX,D */
MatFromMLab(prhs[2],&phi_tr); /* Size D,NX */
MatFromMLab(prhs[3],&psi_tr); /* Size D,NY */
px0 = mxGetPr(prhs[4]);
py0 = mxGetPr(prhs[5]);
MatFromMLab(prhs[6],&phi_exp_d);
MatFromMLab(prhs[7],&psi_exp_d);
pa = mxGetPr(prhs[8]);
pb = mxGetPr(prhs[9]);
b_cond = *mxGetPr(prhs[10]);
p0_i = mxGetPr(prhs[11]);
p0_j = mxGetPr(prhs[12]);
p0_val = mxGetPr(prhs[13]);
Xs = mxGetM(prhs[0]);
D = mxGetN(prhs[0]);
Ys = mxGetM(prhs[1]);
Np0 = mxGetNumberOfElements(prhs[13]);
pxy_size = Xs*Ys;
plhs[0] = mxCreateDoubleMatrix(D,Xs,mxREAL);
plhs[1] = mxCreateDoubleMatrix(D,Ys,mxREAL);
plhs[2] = mxCreateDoubleMatrix(1,Xs,mxREAL);
plhs[3] = mxCreateDoubleMatrix(1,Ys,mxREAL);
plhs[4] = mxCreateDoubleMatrix(1,1,mxREAL);
grad_phi.dat = mxGetPr(plhs[0]);
grad_psi.dat = mxGetPr(plhs[1]);
grad_phi.nx = D;
grad_phi.ny = Xs;
grad_phi.nall = Xs*D;
grad_psi.nx = D;
grad_psi.ny = Ys;
grad_psi.nall = Ys*D;
grad_a = mxGetPr(plhs[2]);
grad_b = mxGetPr(plhs[3]);
AllocMat(D,Ys,&phi_exp_m);
AllocMat(D,Xs,&psi_exp_m);
px = malloc(Xs*sizeof(double));
py = malloc(Ys*sizeof(double));
if (px==NULL || py==NULL)
printf("Error in allocation\n");
if (!b_cond)
mat_logemb_model(phi_tr, psi_tr, pa, pb, phi_exp_m, psi_exp_m, px, py, p0_i, p0_j, p0_val, Np0, mxGetPr(plhs[4]),b_cond) ;
else
{
/* Run logemb model one time to get the x partition function in px */
mat_logemb_model(phi_tr, psi_tr, pa, pb, phi_exp_m, psi_exp_m, px, py, p0_i, p0_j, p0_val, Np0, mxGetPr(plhs[4]),b_cond) ;
/* Create new x factor */
for (xi=0; xi<Xs; xi++)
grad_a[xi] = pa[xi]-log(px[xi])+log(px0[xi]);
mat_logemb_model(phi_tr, psi_tr, grad_a, pb, phi_exp_m, psi_exp_m, px, py, p0_i, p0_j, p0_val, Np0, mxGetPr(plhs[4]),0) ;
}
/* Matlab line: diag(px)*phi-pxy*psi - (diag(px0)*phi-pxy0*psi);
/* equivalent to diag(px-px0)*phi+psi_expect_d - psi_expect_m */
vec_subtract(px,px0,Xs);
mat_set(grad_phi,phi_tr);
/* printf("\n Phi1 Max=%g MaxPx=%g\n",mat_max_abs(grad_phi.dat,grad_phi.nall),mat_max_abs(px,Xs)); */
mat_mul_cols(grad_phi,px);
/* printf("\n Phi2 Max=%g MaxPx=%g\n",mat_max_abs(grad_phi.dat,grad_phi.nall),mat_max_abs(px,Xs)); */
mat_subtract(psi_exp_d.dat,psi_exp_m.dat,psi_exp_d.nall);
/* printf("\n Phi3 Max=%g\n",mat_max_abs(grad_phi.dat,grad_phi.nall)); */
mat_add(grad_phi.dat,psi_exp_d.dat,psi_exp_d.nall);
/* printf("\n Phi4 Max=%g\n",mat_max_abs(grad_phi.dat,grad_phi.nall)); */
vec_subtract(py,py0,Ys);
mat_set(grad_psi,psi_tr);
mat_mul_cols(grad_psi,py);
mat_subtract(phi_exp_d.dat,phi_exp_m.dat,phi_exp_d.nall);
mat_add(grad_psi.dat,phi_exp_d.dat,phi_exp_d.nall);
/* Generate gradient for a and b. Remember px already has px subtracted. Just need to flip sign */
memcpy(grad_a,px,Xs*sizeof(double));
vec_mul_scalar(grad_a,-1,Xs);
memcpy(grad_b,py,Ys*sizeof(double));
vec_mul_scalar(grad_b,-1,Ys);
free(psi_exp_m.dat);
free(phi_exp_m.dat);
free(px);
free(py);
}
int main(int argc, char* argv[])
{
/* parsing arguments */
/********************************************/
double latspac_nu;
qcd_options *opt;
strbuf name[3],manf_name,unit,sink[3],source[3];
size_t binsize,nboot,propdim[2],nt;
char *cpt1,*cpt2;
corr_no lastc;
fit_model *fm_pt;
opt = qcd_arg_parse(argc,argv,A_PLOT|A_SAVE_RS|A_LOAD_RG|A_PROP_NAME\
|A_PROP_LOAD|A_LATSPAC|A_QCOMP|A_FIT,2,0);
cpt1 = strtok(opt->ss,"/");
printf("%s\n",cpt1);
if (cpt1)
{
cpt2 = strchr(cpt1,':');
if (cpt2 == NULL)
{
fprintf(stderr,"error: sink/source option %s is invalid\n",\
cpt1);
exit(EXIT_FAILURE);
}
strbufcpy(source[PP],cpt2+1);
*cpt2 = '\0';
strbufcpy(sink[PP],cpt1);
}
else
{
fprintf(stderr,"error: sink/source option %s is invalid\n",\
opt->ss);
exit(EXIT_FAILURE);
}
cpt1 = strtok(NULL,"/");
if (cpt1)
{
cpt2 = strchr(cpt1,':');
if (cpt2 == NULL)
{
fprintf(stderr,"error: sink/source option %s is invalid\n",\
cpt1);
exit(EXIT_FAILURE);
}
strbufcpy(source[AP],cpt2+1);
*cpt2 = '\0';
strbufcpy(sink[AP],cpt1);
}
else
{
strbufcpy(sink[AP],sink[PP]);
strbufcpy(source[AP],source[PP]);
}
cpt1 = strtok(NULL,"/");
if (cpt1)
{
cpt2 = strchr(cpt1,':');
if (cpt2 == NULL)
{
fprintf(stderr,"error: sink/source option %s is invalid\n",\
cpt1);
exit(EXIT_FAILURE);
}
strbufcpy(source[AA],cpt2+1);
*cpt2 = '\0';
strbufcpy(sink[AA],cpt1);
}
else
{
strbufcpy(sink[AA],sink[PP]);
strbufcpy(source[AA],source[PP]);
}
cpt1 = strtok(opt->channel[0],"/");
if (cpt1)
{
sprintf(name[PP],"%s_%s_%s_%s",cpt1,opt->quark[0],sink[PP],source[PP]);
}
else
{
fprintf(stderr,"error: channel option %s is invalid\n",\
opt->channel[0]);
exit(EXIT_FAILURE);
}
cpt1 = strtok(NULL,"/");
if (cpt1)
{
sprintf(name[AP],"%s_%s_%s_%s",cpt1,opt->quark[0],sink[AP],source[AP]);
}
else
{
fprintf(stderr,"error: channel option %s is invalid\n",\
opt->channel[0]);
exit(EXIT_FAILURE);
}
cpt1 = strtok(NULL,"/");
if (cpt1)
{
sprintf(name[AA],"%s_%s_%s_%s",cpt1,opt->quark[0],sink[AA],source[AA]);
lastc = AA;
fm_pt = &fm_pseudosc3;
}
else
{
lastc = AP;
fm_pt = &fm_pseudosc2;
}
strbufcpy(manf_name,opt->manf_name);
binsize = opt->binsize;
nboot = opt->nboot;
latspac_nu = opt->latspac_nu;
if (opt->have_latspac)
{
strbufcpy(unit," (MeV)");
}
else
{
strbufcpy(unit,"");
}
latan_set_verb(opt->latan_verb);
minimizer_set_alg(opt->minimizer);
mat_ar_loadbin(NULL,propdim,manf_name,name[PP],1);
nt = propdim[0];
io_set_fmt(opt->latan_fmt);
io_init();
/* loading datas */
/********************************************/
size_t ndat,nbdat;
mat **prop[3];
corr_no c;
ndat = (size_t)get_nfile(manf_name);
nbdat = ndat/binsize + ((ndat%binsize == 0) ? 0 : 1);
for (c=PP;c<=lastc;c++)
{
prop[c] = mat_ar_create(nbdat,propdim[0],propdim[1]);
qcd_printf(opt,"-- loading %s datas from %s...\n",name[c],manf_name);
mat_ar_loadbin(prop[c],NULL,manf_name,name[c],binsize);
}
/* propagator */
/********************************************/
rs_sample *s_mprop[3];
mat *mprop[3],*sigmprop[3];
for (c=PP;c<=lastc;c++)
{
s_mprop[c] = rs_sample_create(propdim[0],propdim[1],nboot);
sigmprop[c] = mat_create(propdim[0],propdim[1]);
qcd_printf(opt,"-- resampling %s mean propagator...\n",name[c]);
randgen_set_state(opt->state);
resample(s_mprop[c],prop[c],nbdat,&rs_mean,BOOT,NULL);
mprop[c] = rs_sample_pt_cent_val(s_mprop[c]);
rs_sample_varp(sigmprop[c],s_mprop[c]);
mat_eqsqrt(sigmprop[c]);
}
/* effective mass */
/********************************************/
rs_sample *s_effmass[3];
mat *tem,*em[3],*sigem[3];
size_t emdim[2];
get_effmass_size(emdim,mprop[PP],1,EM_ACOSH);
tem = mat_create(emdim[0],1);
for (c=PP;c<=lastc;c++)
{
s_effmass[c] = rs_sample_create(emdim[0],emdim[1],nboot);
sigem[c] = mat_create(emdim[0],emdim[1]);
qcd_printf(opt,"-- resampling %s effective mass...\n",name[c]);
rs_sample_effmass(s_effmass[c],tem,s_mprop[c],1,EM_ACOSH);
em[c] = rs_sample_pt_cent_val(s_effmass[c]);
rs_sample_varp(sigem[c],s_effmass[c]);
mat_eqsqrt(sigem[c]);
}
/* fit mass */
/********************************************/
fit_data *d;
rs_sample *s_fit;
mat *fit,*limit,*sigfit,*scanres_t,*scanres_chi2,*scanres_mass,\
*scanres_masserr;
size_t npar,nti,tibeg,range[2],ta;
size_t i,j;
strbuf buf,range_info,latan_path;
double pref_i,mass_i;
d = fit_data_create(nt,1,(size_t)(lastc+1));
tibeg = (size_t)(opt->range[0][0]);
range[0] = 0;
range[1] = 0;
npar = fit_model_get_npar(fm_pt,&nt);
s_fit = rs_sample_create(npar,1,nboot);
fit = rs_sample_pt_cent_val(s_fit);
limit = mat_create(npar,2);
sigfit = mat_create(npar,1);
/** print operation **/
if (!opt->do_range_scan)
{
qcd_printf(opt,"-- fitting and resampling...\n");
}
else
{
qcd_printf(opt,"-- scanning ranges [ti,%u] from ti= %u\n",\
opt->range[0][1],opt->range[0][0]);
opt->nmanrange = 1;
}
/** check ranges **/
strbufcpy(range_info,"");
qcd_printf(opt,"%-20s: ","corrected range(s)");
fit_data_fit_all_points(d,false);
for (i=0;i<opt->nmanrange;i++)
{
sprintf(buf,"_%u_%u",opt->range[i][0],opt->range[i][1]);
strbufcat(range_info,buf);
range[0] = (size_t)(opt->range[i][0]);
range[1] = (size_t)(opt->range[i][1]);
correct_range(range,mprop[PP],sigmprop[PP],opt);
fit_data_fit_range(d,range[0],range[1],true);
}
qcd_printf(opt,"\n");
nti = MAX(range[1] - 1 - tibeg,1);
scanres_t = mat_create(nti,1);
scanres_chi2 = mat_create(nti,1);
scanres_mass = mat_create(nti,1);
scanres_masserr = mat_create(nti,1);
/** set model **/
fit_data_set_model(d,fm_pt,&nt);
/** set correlation filter **/
if (opt->corr == NO_COR)
{
for (i=0;i<nt;i++)
for (j=0;j<nt;j++)
{
if (i != j)
{
fit_data_set_data_cor(d,i,j,false);
}
}
}
/** set initial parameter values **/
ta = nt/8-(size_t)(mat_get(tem,0,0));
mass_i = mat_get(em[PP],ta,0);
if (latan_isnan(mass_i))
{
mass_i = 0.3;
}
mat_set(fit,0,0,mass_i);
pref_i = mat_get(mprop[PP],ta,0)/(exp(-mass_i*ta)+exp(-mass_i*(nt-ta)));
if (latan_isnan(pref_i))
{
pref_i = 1.0;
}
mat_set(fit,1,0,sqrt(pref_i));
mat_set(fit,2,0,sqrt(pref_i));
qcd_printf(opt,"%-22smass= %e -- prefactor_0= %e\n","initial parameters: ",\
mat_get(fit,0,0),pref_i);
/** set parameter limits **/
mat_cst(limit,latan_nan());
mat_set(limit,0,0,0.0);
mat_set(limit,1,0,0.0);
mat_set(limit,2,0,0.0);
/** positive AP correlator **/
rs_sample_eqabs(s_mprop[AP]);
/** set x **/
for (i=0;i<nt;i++)
{
fit_data_set_x(d,i,0,(double)(i)-opt->tshift);
}
/** regular correlator fit... **/
if (!opt->do_range_scan)
{
latan_set_warn(false);
rs_data_fit(s_fit,limit,NULL,s_mprop,d,NO_COR,NULL);
latan_set_warn(true);
rs_data_fit(s_fit,limit,NULL,s_mprop,d,opt->corr,NULL);
rs_sample_varp(sigfit,s_fit);
mat_eqsqrt(sigfit);
if (fit_data_get_chi2pdof(d) > 2.0)
{
fprintf(stderr,"warning: bad final fit (chi^2/dof= %.2e)\n",\
fit_data_get_chi2pdof(d));
}
qcd_printf(opt,"-- results:\n");
qcd_printf(opt,"%-10s= %.8f +/- %.8e %s\n","mass",\
mat_get(fit,0,0)/latspac_nu, \
mat_get(sigfit,0,0)/latspac_nu,unit);
qcd_printf(opt,"%-10s= %.8f +/- %.8e %s\n","decay",\
mat_get(fit,1,0)/latspac_nu, \
mat_get(sigfit,1,0)/latspac_nu,unit);
qcd_printf(opt,"%-10s= %.8f +/- %.8e %s\n","norm",\
mat_get(fit,2,0)/latspac_nu, \
mat_get(sigfit,2,0)/latspac_nu,unit);
qcd_printf(opt,"%-10s= %d\n","dof",fit_data_get_dof(d));
qcd_printf(opt,"%-10s= %e\n","chi^2/dof",fit_data_get_chi2pdof(d));
if (opt->do_save_rs_sample)
{
sprintf(latan_path,"%s_pseudosc_fit%s_%s.boot:%s_pseudosc_fit%s_%s",\
opt->quark[0],range_info,manf_name,opt->quark[0],\
range_info,manf_name);
rs_sample_save_subsamp(latan_path,'w',s_fit,0,0,1,0);
}
}
/** ...or fit range scanning **/
else
{
qcd_printf(opt,"\n%-5s %-12s a*M_%-8s %-12s","ti/a","chi^2/dof",\
opt->quark[0],"error");
for (i=tibeg;i<range[1]-1;i++)
{
latan_set_warn(false);
rs_data_fit(s_fit,limit,NULL,s_mprop,d,NO_COR,NULL);
latan_set_warn(true);
rs_data_fit(s_fit,limit,NULL,s_mprop,d,opt->corr,NULL);
rs_sample_varp(sigfit,s_fit);
mat_eqsqrt(sigfit);
mat_set(scanres_t,i-tibeg,0,(double)(i));
mat_set(scanres_chi2,i-tibeg,0,fit_data_get_chi2pdof(d));
mat_set(scanres_mass,i-tibeg,0,mat_get(fit,0,0));
mat_set(scanres_masserr,i-tibeg,0,mat_get(sigfit,0,0));
qcd_printf(opt,"\n% -4d % -.5e % -.5e % -.5e",(int)(i),\
fit_data_get_chi2pdof(d),mat_get(fit,0,0), \
mat_get(sigfit,0,0));
fit_data_fit_point(d,i,false);
}
qcd_printf(opt,"\n\n");
}
/* plot */
/********************************************/
if (opt->do_plot)
{
mat *mbuf,*em_i,*sigem_i,*par,*ft[3],*comp[3];
plot *p;
strbuf key,dirname,color;
size_t maxt,t,npoint;
double dmaxt,nmass;
mbuf = mat_create(1,1);
em_i = mat_create(nrow(em[PP]),1);
sigem_i = mat_create(nrow(em[PP]),1);
par = mat_create(2,1);
if (!opt->do_range_scan)
{
maxt = nt;
dmaxt = (double)maxt;
npoint = fit_data_fit_point_num(d);
/** chi^2 plot **/
p = plot_create();
i = 0;
for (c=PP;c<=lastc;c++)
{
ft[c] = mat_create(npoint,1);
comp[c] = mat_create(npoint,1);
for (t=0;t<nt;t++)
{
if (fit_data_is_fit_point(d,t))
{
mat_set(ft[c],i%npoint,0,(double)(t)+0.33*(double)(c));
mat_set(comp[c],i%npoint,0,mat_get(d->chi2_comp,i,0));
i++;
}
}
}
plot_set_scale_manual(p,-1.0,dmaxt,-5.0,5.0);
plot_add_plot(p,"0.0 lt -1 lc rgb 'black' notitle","");
plot_add_plot(p,"1.0 lt -1 lc rgb 'black' notitle","");
plot_add_plot(p,"-1.0 lt -1 lc rgb 'black' notitle","");
plot_add_plot(p,"2.0 lt -1 lc rgb 'dark-gray' notitle","");
plot_add_plot(p,"-2.0 lt -1 lc rgb 'dark-gray' notitle","");
plot_add_plot(p,"3.0 lt -1 lc rgb 'gray' notitle","");
plot_add_plot(p,"-3.0 lt -1 lc rgb 'gray' notitle","");
plot_add_plot(p,"4.0 lt -1 lc rgb 'light-gray' notitle","");
plot_add_plot(p,"-4.0 lt -1 lc rgb 'light-gray' notitle","");
plot_set_ylabel(p,"standard deviations");
for (c=PP;c<=lastc;c++)
{
sprintf(color,"%d",(int)(c)+1);
plot_add_points(p,ft[c],comp[c],c_name[c],color,"impulses");
}
plot_disp(p);
if (opt->do_save_plot)
{
sprintf(dirname,"%s_dev",opt->save_plot_dir);
plot_save(dirname,p);
}
plot_destroy(p);
for (c=PP;c<=lastc;c++)
{
/** propagator plot **/
p = plot_create();
fit_data_fit_all_points(d,true);
plot_set_scale_ylog(p);
plot_set_scale_xmanual(p,0,dmaxt);
sprintf(key,"%s %s propagator",opt->quark[0],c_name[c]);
mat_eqabs(mprop[c]);
plot_add_fit(p,d,c,mbuf,0,fit,0,dmaxt,1000,false,\
PF_FIT|PF_DATA,key,"","rgb 'red'","rgb 'red'");
plot_disp(p);
if (opt->do_save_plot)
{
sprintf(dirname,"%s_prop_%s",opt->save_plot_dir,c_name[c]);
plot_save(dirname,p);
}
plot_destroy(p);
/** effective mass plot **/
p = plot_create();
mat_eqmuls(em[c],1.0/latspac_nu);
mat_eqmuls(sigem[c],1.0/latspac_nu);
nmass = mat_get(fit,0,0)/latspac_nu;
plot_add_hlineerr(p,nmass, mat_get(sigfit,0,0)/latspac_nu,\
"rgb 'red'");
sprintf(key,"%s %s effective mass",opt->quark[0],c_name[c]);
plot_add_dat(p,tem,em[c],NULL,sigem[c],key,"rgb 'blue'");
plot_disp(p);
if (opt->do_save_plot)
{
sprintf(dirname,"%s_em_%s",opt->save_plot_dir,c_name[c]);
plot_save(dirname,p);
}
plot_destroy(p);
}
}
else
{
/* chi^2 plot */
p = plot_create();
plot_set_scale_manual(p,0,(double)(nt/2),0,5.0);
plot_add_hline(p,1.0,"rgb 'black'");
plot_add_dat(p,scanres_t,scanres_chi2,NULL,NULL,"chi^2/dof",\
"rgb 'blue'");
plot_disp(p);
if (opt->do_save_plot)
{
sprintf(dirname,"%s_chi2",opt->save_plot_dir);
plot_save(dirname,p);
}
plot_destroy(p);
/* mass plot */
p = plot_create();
plot_set_scale_xmanual(p,0,(double)(nt/2));
sprintf(key,"a*M_%s",opt->quark[0]);
plot_add_dat(p,scanres_t,scanres_mass,NULL,scanres_masserr,key,\
"rgb 'red'");
plot_disp(p);
if (opt->do_save_plot)
{
sprintf(dirname,"%s_mass",opt->save_plot_dir);
plot_save(dirname,p);
}
plot_destroy(p);
}
mat_destroy(em_i);
mat_destroy(sigem_i);
mat_destroy(mbuf);
mat_destroy(par);
for (c=PP;c<=lastc;c++)
{
mat_destroy(ft[c]);
mat_destroy(comp[c]);
}
}
/* desallocation */
/********************************************/
free(opt);
io_finish();
mat_ar_destroy(prop[0],nbdat);
mat_ar_destroy(prop[1],nbdat);
for (c=PP;c<=lastc;c++)
{
rs_sample_destroy(s_mprop[c]);
mat_destroy(sigmprop[c]);
rs_sample_destroy(s_effmass[c]);
mat_destroy(sigem[c]);
}
mat_destroy(tem);
fit_data_destroy(d);
rs_sample_destroy(s_fit);
mat_destroy(limit);
mat_destroy(sigfit);
mat_destroy(scanres_t);
mat_destroy(scanres_chi2);
mat_destroy(scanres_mass);
mat_destroy(scanres_masserr);
return EXIT_SUCCESS;
}
void plot_fit(const rs_sample *s_fit, fit_data *d, fit_param *param, const plot_flag f)
{
plot *p[N_EX_VAR];
double *xb[N_EX_VAR] = {NULL,NULL,NULL,NULL,NULL,NULL,NULL};
double x_range[N_EX_VAR][2],b_int[2],dbind,a;
size_t bind,vind,eind,k,phy_ind,s;
strbuf color,gtitle,title,xlabel,ylabel;
mat *phy_pt,*x_k,*fit,*cordat,**vol_av_corr,*yerrtmp;
ens *ept;
phy_pt = mat_create(N_EX_VAR,1);
x_k = mat_create(param->nens,1);
cordat = mat_create(param->nens,1);
MALLOC(vol_av_corr,mat **,param->nbeta);
for (bind=0;bind<param->nbeta;bind++)
{
vol_av_corr[bind] = mat_create(param->nvol[bind],1);
}
for (k=0;k<N_EX_VAR;k++)
{
p[k] = plot_create();
}
param->scale_model = 1;
fit = rs_sample_pt_cent_val(s_fit);
if (IS_AN(param,AN_PHYPT)&&IS_AN(param,AN_SCALE))
{
phy_ind = 1;
s = fm_scaleset_taylor_npar(param);
}
else
{
phy_ind = 0;
s = 0;
}
for (k=0;k<N_EX_VAR;k++)
{
if (k == i_vind)
{
fit_data_get_x_k(x_k,d,i_Linv);
}
else
{
fit_data_get_x_k(x_k,d,k);
}
if ((k == i_a)||(k == i_ud)||(k == i_Linv)||(k == i_alpha)\
||(k == i_vind))
{
x_range[k][0] = 0.0;
}
else
{
x_range[k][0] = mat_get_min(x_k)-0.15*fabs(mat_get_min(x_k));
}
x_range[k][1] = mat_get_max(x_k)+0.15*fabs(mat_get_min(x_k));
plot_set_scale_xmanual(p[k],x_range[k][0],x_range[k][1]);
}
if (f == Q)
{
sprintf(gtitle,"quantity: %s -- scale: %s -- datasets: %s -- ensembles: %s",\
param->q_name,param->scale_part,param->dataset_cat,param->manifest);
mat_set(phy_pt,i_ud,0,SQ(param->M_ud));
mat_set(phy_pt,i_s,0,SQ(param->M_s));
mat_set(phy_pt,i_umd,0,param->M_umd_val);
mat_set(phy_pt,i_alpha,0,param->alpha);
mat_set(phy_pt,i_bind,0,0.0);
mat_set(phy_pt,i_vind,0,0.0);
mat_set(phy_pt,i_a,0,0.0);
mat_set(phy_pt,i_Linv,0,0.0);
mat_set(phy_pt,i_fvM,0,param->qed_fvol_mass);
/* regular plots */
PLOT_ADD_FIT(PF_FIT,i_ud,phy_ind,"","rgb 'black'");
PLOT_ADD_PB(i_ud,phy_ind,"rgb 'black'");
PLOT_ADD_FIT(PF_FIT,i_s,phy_ind,"","rgb 'black'");
PLOT_ADD_PB(i_s,phy_ind,"rgb 'black'");
PLOT_ADD_FIT(PF_FIT,i_umd,phy_ind,"","rgb 'black'");
PLOT_ADD_PB(i_umd,phy_ind,"rgb 'black'");
PLOT_ADD_FIT(PF_FIT,i_alpha,phy_ind,"","rgb 'black'");
PLOT_ADD_PB(i_alpha,phy_ind,"rgb 'black'");
PLOT_ADD_FIT(PF_FIT,i_a,phy_ind,"","rgb 'black'");
PLOT_ADD_PB(i_a,phy_ind,"rgb 'black'");
PLOT_ADD_FIT(PF_FIT,i_Linv,phy_ind,"","rgb 'black'");
PLOT_ADD_PB(i_Linv,phy_ind,"rgb 'black'");
for (bind=0;bind<param->nbeta;bind++)
{
dbind = (double)(bind);
b_int[0] = dbind - 0.1;
b_int[1] = dbind + 0.1;
xb[i_bind] = b_int;
fit_data_fit_region(d,xb);
sprintf(color,"%d",1+(int)bind);
sprintf(title,"beta = %s",param->beta[bind]);
PLOT_ADD_FIT(PF_DATA,i_ud,phy_ind,title,color);
PLOT_ADD_FIT(PF_DATA,i_s,phy_ind,title,color);
PLOT_ADD_FIT(PF_DATA,i_umd,phy_ind,title,color);
PLOT_ADD_FIT(PF_DATA,i_alpha,phy_ind,title,color);
PLOT_ADD_FIT(PF_DATA,i_a,phy_ind,title,color);
PLOT_ADD_FIT(PF_DATA,i_Linv,phy_ind,title,color);
fit_data_fit_all_points(d,true);
}
/* volume averages plot */
plot_add_fit(p[i_vind],d,phy_ind,phy_pt,i_Linv,fit,x_range[i_Linv][0],\
x_range[i_Linv][1],MOD_PLOT_NPT,true,PF_FIT,"","", \
"rgb 'black'","rgb 'black'");
plot_add_fit_predband(p[i_vind],d,phy_ind,phy_pt,i_Linv,s_fit,\
x_range[i_Linv][0],x_range[i_Linv][1], \
MOD_PLOT_NPT/4,"rgb 'black'");
fit_partresidual(cordat,d,phy_ind,phy_pt,i_Linv,fit);
for(bind=0;bind<param->nbeta;bind++)
{
mat_zero(vol_av_corr[bind]);
}
for(eind=0;eind<param->nens;eind++)
{
ept = param->point + eind;
bind = (size_t)ind_beta(ept->beta,param);
vind = (size_t)ind_volume((unsigned int)ept->L,(int)bind,param);
mat_inc(vol_av_corr[bind],vind,0,mat_get(cordat,eind,0));
}
for (bind=0;bind<param->nbeta;bind++)
for (vind=0;vind<param->nvol[bind];vind++)
{
mat_set(vol_av_corr[bind],vind,0, \
mat_get(vol_av_corr[bind],vind,0) \
/((double)(param->nenspvol[bind][vind])));
}
for(bind=0;bind<param->nbeta;bind++)
{
yerrtmp = mat_create(param->nvol[bind],1);
rs_sample_varp(yerrtmp,param->s_vol_av[bind]);
mat_eqsqrt(yerrtmp);
sprintf(color,"%d",1+(int)bind);
sprintf(title,"beta = %s",param->beta[bind]);
plot_add_dat_yerr(p[i_vind], \
rs_sample_pt_cent_val(param->s_vol_Linv[bind]),\
vol_av_corr[bind],yerrtmp,title,color);
mat_destroy(yerrtmp);
}
/* display plots */
switch (param->q_dim)
{
case 0:
strbufcpy(ylabel,param->q_name);
break;
case 1:
sprintf(ylabel,"%s (MeV)",param->q_name);
break;
default:
sprintf(ylabel,"%s^%d (MeV^%d)",param->q_name,param->q_dim,\
param->q_dim);
break;
}
sprintf(xlabel,"M_%s^2 (MeV^2)",param->ud_name);
PLOT_ADD_EX(i_ud,s);
PLOT_DISP(i_ud,"ud");
sprintf(xlabel,"M_%s^2 (MeV^2)",param->s_name);
PLOT_ADD_EX(i_s,s);
PLOT_DISP(i_s,"s");
strbufcpy(xlabel,"a (MeV^-1)");
PLOT_ADD_EX(i_a,s);
PLOT_DISP(i_a,"a");
if (param->have_umd)
{
sprintf(xlabel,"%s (MeV^2)",param->umd_name);
PLOT_ADD_EX(i_umd,s);
PLOT_DISP(i_umd,"umd");
}
if (param->have_alpha)
{
strbufcpy(xlabel,"alpha");
PLOT_ADD_EX(i_alpha,s);
PLOT_DISP(i_alpha,"alpha");
}
strbufcpy(xlabel,"1/L (MeV)");
PLOT_ADD_EX(i_Linv,s);
PLOT_DISP(i_Linv,"Linv");
PLOT_ADD_EX(i_vind,s);
PLOT_DISP(i_vind,"Linv_av");
}
else if (f == SCALE)
{
sprintf(gtitle,"scale setting: %s -- datasets: %s -- ensembles: %s",
param->scale_part,param->dataset_cat,param->manifest);
for (bind=0;bind<param->nbeta;bind++)
{
dbind = (double)(bind);
b_int[0] = dbind - 0.1;
b_int[1] = dbind + 0.1;
xb[i_bind] = b_int;
a = mat_get(fit,bind,0);
fit_data_fit_region(d,xb);
mat_set(phy_pt,i_ud,0,SQ(a*param->M_ud));
mat_set(phy_pt,i_s,0,SQ(a*param->M_s));
mat_set(phy_pt,i_umd,0,SQ(a)*param->M_umd_val);
mat_set(phy_pt,i_bind,0,bind);
mat_set(phy_pt,i_a,0,a);
mat_set(phy_pt,i_Linv,0,0.0);
sprintf(color,"%d",1+(int)bind);
sprintf(title,"beta = %s",param->beta[bind]);
PLOT_ADD_FIT(PF_DATA|PF_FIT,i_ud,0,title,color);
PLOT_ADD_FIT(PF_DATA|PF_FIT,i_s,0,title,color);
PLOT_ADD_FIT(PF_DATA|PF_FIT,i_umd,0,title,color);
PLOT_ADD_FIT(PF_DATA|PF_FIT,i_Linv,0,title,color);
fit_data_fit_all_points(d,true);
}
sprintf(ylabel,"(a*M_%s)^2",param->scale_part);
sprintf(xlabel,"(a*M_%s)^2",param->ud_name);
PLOT_DISP(i_ud,"ud");
sprintf(xlabel,"(a*M_%s)^2",param->s_name);
PLOT_DISP(i_s,"s");
if (param->have_umd)
{
sprintf(xlabel,"a^2*%s",param->umd_name);
PLOT_DISP(i_umd,"umd");
}
strbufcpy(xlabel,"a/L");
PLOT_DISP(i_Linv,"Linv");
}
param->scale_model = 0;
mat_destroy(phy_pt);
mat_destroy(x_k);
mat_destroy(cordat);
for (bind=0;bind<param->nbeta;bind++)
{
mat_destroy(vol_av_corr[bind]);
}
free(vol_av_corr);
for (k=0;k<N_EX_VAR;k++)
{
plot_destroy(p[k]);
}
}
int
main(void)
{
int i, result;
flint_rand_t state;
printf("inv... ");
fflush(stdout);
_randinit(state);
/* Check aliasing */
/* Managed element type (mpq_t) */
for (i = 0; i < 50; i++)
{
long n;
ctx_t ctx;
mat_t A, B, C;
long ansB, ansC;
n = n_randint(state, 20) + 1;
ctx_init_mpq(ctx);
mat_init(A, n, n, ctx);
mat_init(B, n, n, ctx);
mat_init(C, n, n, ctx);
mat_randtest(A, state, ctx);
mat_set(B, A, ctx);
ansC = mat_inv(C, B, ctx);
ansB = mat_inv(B, B, ctx);
result = ((ansB == ansC) && (!ansB || mat_equal(B, C, ctx)));
if (!result)
{
printf("FAIL:\n\n");
printf("A: \n"), mat_print(A, ctx), printf("\n");
printf("B: \n"), mat_print(B, ctx), printf("\n");
printf("C: \n"), mat_print(C, ctx), printf("\n");
printf("ansB = %ld\n", ansB);
printf("ansC = %ld\n", ansC);
}
mat_clear(A, ctx);
mat_clear(B, ctx);
mat_clear(C, ctx);
ctx_clear(ctx);
}
/* Check A * A^{-1} == A^{-1} * A == Id */
/* Managed element type (mpq_t) */
for (i = 0; i < 50; i++)
{
long n;
ctx_t ctx;
mat_t A, B, C, D, I;
long ansB;
n = n_randint(state, 20) + 1;
ctx_init_mpq(ctx);
mat_init(A, n, n, ctx);
mat_init(B, n, n, ctx);
mat_init(C, n, n, ctx);
mat_init(D, n, n, ctx);
mat_init(I, n, n, ctx);
mat_randtest(A, state, ctx);
ansB = mat_inv(B, A, ctx);
if (!ansB)
{
mat_mul(C, A, B, ctx);
mat_mul(D, B, A, ctx);
}
result = (ansB || (mat_equal(C, D, ctx) && mat_is_one(C, ctx)));
if (!result)
{
printf("FAIL:\n\n");
printf("A: \n"), mat_print(A, ctx), printf("\n");
printf("B: \n"), mat_print(B, ctx), printf("\n");
printf("C: \n"), mat_print(C, ctx), printf("\n");
printf("D: \n"), mat_print(D, ctx), printf("\n");
printf("ansB = %ld\n", ansB);
}
mat_clear(A, ctx);
mat_clear(B, ctx);
mat_clear(C, ctx);
mat_clear(D, ctx);
ctx_clear(ctx);
}
_randclear(state);
_fmpz_cleanup();
printf("PASS\n");
return EXIT_SUCCESS;
}
void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
{
double M;
double log_thr;
int Xs,D,Ys,i,j,ep=0;
int maxentep;
int pxy_size;
double mx;
Matrix pxy,phi,psi,phi_tr,psi_tr,phi_exp_d,psi_exp_d,psi_exp_m,phi_exp_m,grad_phi,grad_psi;
double *px0,*py0,*px,*py,*pa,*pb,*grad_a,*grad_b;
double Z;
int xi,yi,di;
MatFromMLab(prhs[0],&phi); /* Size NX,D */
MatFromMLab(prhs[1],&psi); /* Size NX,D */
MatFromMLab(prhs[2],&phi_tr); /* Size D,NX */
MatFromMLab(prhs[3],&psi_tr); /* Size D,NY */
px0 = mxGetPr(prhs[4]);
py0 = mxGetPr(prhs[5]);
MatFromMLab(prhs[6],&phi_exp_d);
MatFromMLab(prhs[7],&psi_exp_d);
pa = mxGetPr(prhs[8]);
pb = mxGetPr(prhs[9]);
Xs = mxGetM(prhs[0]);
D = mxGetN(prhs[0]);
Ys = mxGetM(prhs[1]);
pxy_size = Xs*Ys;
plhs[0] = mxCreateDoubleMatrix(Xs,D,mxREAL);
plhs[1] = mxCreateDoubleMatrix(D,Ys,mxREAL);
plhs[2] = mxCreateDoubleMatrix(Xs,Ys,mxREAL);
plhs[3] = mxCreateDoubleMatrix(1,Xs,mxREAL);
plhs[4] = mxCreateDoubleMatrix(1,Ys,mxREAL);
grad_phi.dat = mxGetPr(plhs[0]);
grad_psi.dat = mxGetPr(plhs[1]);
grad_phi.nx = Xs;
grad_phi.ny = D;
grad_phi.nall = Xs*D;
grad_psi.nx = D;
grad_psi.ny = Ys;
grad_psi.nall = Ys*D;
/* Will hold the models distribution */
pxy.dat = mxGetPr(plhs[2]);
pxy.nx = Xs;
pxy.ny = Ys;
pxy.nall = Xs*Ys;
grad_a = mxGetPr(plhs[3]);
grad_b = mxGetPr(plhs[4]);
AllocMat(D,Ys,&phi_exp_m);
AllocMat(Xs,D,&psi_exp_m);
px = malloc(Xs*sizeof(double));
py = malloc(Ys*sizeof(double));
mat_logemb_model(phi_tr,psi_tr,pa,pb,pxy);
Z = mat_el_exp_sum(pxy.dat, pxy_size);
mat_el_mul_scalar(pxy.dat, 1/Z, pxy_size);
mat_sum_rows(pxy,px);
mat_sum_cols(pxy,py);
mat_mul_a_tr_b(phi,pxy,phi_exp_m);
mat_mul(pxy,psi,psi_exp_m);
/* Matlab line: diag(px)*phi-pxy*psi - (diag(px0)*phi-pxy0*psi);
/* equivalent to diag(px-px0)*phi+psi_expect_d - psi_expect_m */
vec_subtract(px,px0,Xs);
mat_set(grad_phi,phi);
mat_mul_rows(grad_phi,px);
mat_subtract(psi_exp_d.dat,psi_exp_m.dat,psi_exp_d.nall);
mat_add(grad_phi.dat,psi_exp_d.dat,psi_exp_d.nall);
vec_subtract(py,py0,Ys);
mat_set(grad_psi,psi_tr);
mat_mul_cols(grad_psi,py);
mat_subtract(phi_exp_d.dat,phi_exp_m.dat,phi_exp_d.nall);
mat_add(grad_psi.dat,phi_exp_d.dat,phi_exp_d.nall);
mat_el_log(pxy.dat,pxy.nall);
/* Generate gradient for a and b. Remember px already has px subtracted. Just need to flip sign */
memcpy(grad_a,px,Xs*sizeof(double));
vec_mul_scalar(grad_a,-1,Xs);
memcpy(grad_b,py,Ys*sizeof(double));
vec_mul_scalar(grad_b,-1,Ys);
free(psi_exp_m.dat);
free(phi_exp_m.dat);
free(px);
free(py);
}
void plot_add_fit(plot *p, const fit_data *d, const size_t ky, const mat *x_ex,\
const size_t kx, const mat *par, const double xmin, \
const double xmax, const size_t npt, const bool do_sub, \
const unsigned int obj, const strbuf dat_title, \
const strbuf fit_title, const strbuf dat_color, \
const strbuf fit_color)
{
mat *x,*x_err,*y,*y_err,*cor_data;
bool have_x_err;
size_t nfitpt,ndata;
size_t i,j;
nfitpt = fit_data_fit_point_num(d);
ndata = fit_data_get_ndata(d);
j = 0;
have_x_err = fit_data_have_x_covar(d,kx);
x = mat_create(nfitpt,1);
y = mat_create(nfitpt,1);
x_err = mat_create(nfitpt,1);
y_err = mat_create(nfitpt,1);
cor_data = mat_create(ndata,1);
if (par != NULL)
{
if (obj & PF_FIT)
{
plot_add_model(p,d->model->func[ky],x_ex,kx,par,d->model_param,\
xmin,xmax,npt,fit_title,fit_color);
}
if ((obj & PF_DATA)&&(do_sub))
{
fit_partresidual(cor_data,d,ky,x_ex,kx,par);
}
else
{
fit_data_get_y_k(cor_data,d,ky);
}
}
else
{
fit_data_get_y_k(cor_data,d,ky);
}
if (obj & PF_DATA)
{
for (i=0;i<ndata;i++)
{
if (fit_data_is_fit_point(d,i))
{
mat_set(x,j,0,fit_data_get_x(d,i,kx));
if (have_x_err)
{
mat_set(x_err,j,0, \
sqrt(mat_get(fit_data_pt_x_covar(d,kx,kx),i,i)));
}
mat_set(y,j,0,mat_get(cor_data,i,0));
mat_set(y_err,j,0, \
sqrt(mat_get(fit_data_pt_y_covar(d,ky,ky),i,i)));
j++;
}
}
if (have_x_err)
{
plot_add_dat(p,x,y,x_err,y_err,dat_title,dat_color);
}
else
{
plot_add_dat(p,x,y,NULL,y_err,dat_title,dat_color);
}
}
mat_destroy(x);
mat_destroy(x_err);
mat_destroy(y);
mat_destroy(y_err);
mat_destroy(cor_data);
}
