/**
* Just one of many ways of computing a quantile from a discrete set.
* This corresponds to R's default method.
*/
double quantile( double *x, int n, double p ) {
const double index = (n-1)*p;
const double lo = floor( index );
const double hi = ceil( index );
double xlo = qselect( x, n, (int)lo );
double xhi = qselect( x, n, (int)hi );
double Q = xlo;
if( index > lo ) {
double h = index - lo;
Q = (1-h)*Q + h*xhi;
}
return Q;
}
static float qselect(float *v, int len, int k)
{
int i, st;
for(st = i = 0; i < len - 1; i++) {
if(v[i] > v[len - 1]) {
continue;
}
SWAP(float, v[i], v[st]);
st++;
}
SWAP(float, v[len - 1], v[st]);
return k == st ? v[st] : st > k ? qselect(v, st, k) : qselect(v + st, len - st, k - st);
}
int qselect(int *v, int len, int k)
{
# define SWAP(a, b) { tmp = v[a]; v[a] = v[b]; v[b] = tmp; }
int i, st, tmp;
for (st = i = 0; i < len - 1; i++) {
if (v[i] > v[len - 1]) continue;
SWAP(i, st);
st++;
}
SWAP(len - 1, st);
return k == st ? v[st]
: st > k ? qselect(v, st, k)
: qselect(v + st, len - st, k - st);
}
double qselectFunction(double *v, int len, int k){
int i, st, tmp;
for (st = i = 0; i < len - 1; i++) {
if (v[i] > v[len-1]) continue;
SWAP(i, st);
st++;
}
SWAP(len-1, st);
return k == st ?v[st]
:st > k ? qselect(v, st, k)
: qselect(v + st, len - st, k - st);
}
int main(void)
{
int num, result;
scanf("%d %d", &num, &result);
for (int i = 0; i < num; i++) {
scanf("%d", &arr2[i]);
}
printf("%d\n", qselect(arr2, num, result-1));
return 0;
}
static void* extractThread(void* param) {
ExtractContext* context = (ExtractContext*) param;
DbAlignmentData** dbAlignmentData = context->dbAlignmentData;
int* dbAlignmentLen = context->dbAlignmentLen;
Chain* query = context->query;
Chain** database = context->database;
int databaseLen = context->databaseLen;
int* scores = context->scores;
int maxAlignments = context->maxAlignments;
ValueFunction valueFunction = context->valueFunction;
void* valueFunctionParam = context->valueFunctionParam;
double valueThreshold = context->valueThreshold;
int* cards = context->cards;
int cardsLen = context->cardsLen;
int i;
size_t packedSize = databaseLen * sizeof(DbAlignmentData);
DbAlignmentData* packed = (DbAlignmentData*) malloc(packedSize);
double* values = (double*) malloc(databaseLen * sizeof(double));
valueFunction(values, scores, query, database, databaseLen,
cards, cardsLen, valueFunctionParam);
int thresholded = 0;
for (i = 0; i < databaseLen; ++i) {
packed[i].idx = i;
packed[i].value = values[i];
packed[i].score = scores[i];
packed[i].name = chainGetName(database[i]);
if (packed[i].value <= valueThreshold) {
thresholded++;
}
}
int k = MIN(thresholded, maxAlignments);
qselect((void*) packed, databaseLen, sizeof(DbAlignmentData), k, dbAlignmentDataCmp);
qsort((void*) packed, k, sizeof(DbAlignmentData), dbAlignmentDataCmp);
*dbAlignmentData = (DbAlignmentData*) malloc(k * sizeof(DbAlignmentData));
*dbAlignmentLen = k;
for (i = 0; i < k; ++i) {
(*dbAlignmentData)[i] = packed[i];
}
free(packed);
free(values);
return NULL;
}
double qselect(double *v, int len, int k){
int i, st, tmp;
for (st = i = 0; i < len - 1; i++) {
if (v[i] > v[len-1])
continue;
//SWAP(i, st);
tmp = v[i];
v[i] = v[st];
v[st] = tmp;
st++;
}
//SWAP(len-1, st);
tmp = v[len-1];
v[len-1] = v[st];
v[st] = tmp;
return k == st ?v[st]
:st > k ? qselect(v, st, k)
: qselect(v + st, len - st, k - st);
}
int main(void)
{
# define N (sizeof(x)/sizeof(x[0]))
int x[] = {9, 8, 7, 6, 5, 0, 1, 2, 3, 4};
int y[N];
int i;
for (i = 0; i < 10; i++) {
memcpy(y, x, sizeof(x)); // qselect modifies array
printf("%d: %d\n", i, qselect(y, 10, i));
}
return 0;
}
heman_image* heman_ops_percentiles(heman_image* hmap, int nsteps,
heman_image* mask, heman_color mask_color, int invert_mask,
HEMAN_FLOAT offset)
{
assert(hmap->nbands == 1);
assert(!mask || mask->nbands == 3);
int size = hmap->height * hmap->width;
HEMAN_FLOAT* src = hmap->data;
HEMAN_FLOAT minv = 1000;
HEMAN_FLOAT maxv = -1000;
int npixels = 0;
for (int i = 0; i < size; ++i) {
if (!mask || _match(mask, mask_color, invert_mask, i)) {
minv = MIN(minv, src[i]);
maxv = MAX(maxv, src[i]);
npixels++;
}
}
HEMAN_FLOAT* vals = malloc(sizeof(HEMAN_FLOAT) * npixels);
npixels = 0;
for (int i = 0; i < size; ++i) {
if (!mask || _match(mask, mask_color, invert_mask, i)) {
vals[npixels++] = src[i];
}
}
HEMAN_FLOAT* percentiles = malloc(sizeof(HEMAN_FLOAT) * nsteps);
for (int tier = 0; tier < nsteps; tier++) {
float height = qselect(vals, npixels, tier * npixels / nsteps);
percentiles[tier] = height;
}
free(vals);
for (int i = 0; i < size; ++i) {
HEMAN_FLOAT e = *src;
if (!mask || _match(mask, mask_color, invert_mask, i)) {
for (int tier = nsteps - 1; tier >= 0; tier--) {
if (e > percentiles[tier]) {
e = percentiles[tier];
break;
}
}
}
*src++ = e + offset;
}
free(percentiles);
return hmap;
}
/**
* get the median of HiDistanceMatrixActual(x, x1, x2)
* for every x in our dataset
*
**/
double GetMedian(value* x1, value* x2) {
int i;
value* x = malloc(sizeof(value));
double* values = malloc(sizeof(double) * dm->dataNum);
for (i = 0; i < dm->dataNum; ++i) {
GetIthData(i, x);
values[i] = HiDistanceMatrixActual(x, x1, x2);
}
// for (i = 0; i < dm->dataNum; ++i) {
// }
// return values[2];
// return 0;
//
double res = qselect(values,dm->dataNum,0);
free(values);
free(x);
return res;
}
