void DiagonalLinearFunction::doUpdateInputSizeBegin()
{
bool increase = _dim < x.getSize();
if (!_useDefaultValue && increase)
throw std::runtime_error("[ocra::DiagonalLinearFunction::doUpdateSize] No default value to increase the size of A");
int oldDim = _dim;
int dim = x.getSize();
if (increase)
{
VectorXd tmpb(_b); //we need to save _b before resizing
_b.resize(dim);
_b.head(oldDim) = tmpb;
_b.tail(dim-oldDim).setConstant(_defaultbValue);
_d.resize(dim); //value of _d are in _jacobian, no need to save them
_d.head(oldDim) = _jacobian.diagonal();
_d.tail(dim-oldDim).setConstant(_defaultDiagonalValue);
}
else
{
VectorXd tmpb(_b); //we need to save _b before resizing
_b.resize(dim);
_b = tmpb.head(dim);
_d.resize(dim); //value of _d are in _jacobian, no need to save them
_d = _jacobian.diagonal().head(dim);
}
}
std::wstring utf8_to_ucs2(const std::string & data) {
//from utf8 to ucs2
int tmpbsize = MultiByteToWideChar(CP_UTF8, 0, data.data(), data.size(), 0, 0);
if (tmpbsize > 0) {
std::unique_ptr<wchar_t[] > tmpb(new wchar_t[tmpbsize + 1]);
MultiByteToWideChar(CP_UTF8, 0, data.data(), data.size(), tmpb.get(), tmpbsize);
return std::wstring(tmpb.get(), tmpb.get() + tmpbsize);
}
return std::wstring();
}
/*************************************************************************
Testing Nearest Neighbor Search on uniformly distributed hypercube
NormType: 0, 1, 2
D: space dimension
N: points count
*************************************************************************/
static void testkdtuniform(const ap::real_2d_array& xy,
const int& n,
const int& nx,
const int& ny,
const int& normtype,
bool& kdterrors)
{
double errtol;
ap::integer_1d_array tags;
ap::real_1d_array ptx;
ap::real_1d_array tmpx;
ap::boolean_1d_array tmpb;
kdtree treex;
kdtree treexy;
kdtree treext;
ap::real_2d_array qx;
ap::real_2d_array qxy;
ap::integer_1d_array qtags;
ap::real_1d_array qr;
int kx;
int kxy;
int kt;
int kr;
double eps;
int i;
int j;
int k;
int task;
bool isequal;
double r;
int q;
int qcount;
qcount = 10;
//
// Tol - roundoff error tolerance (for '>=' comparisons)
//
errtol = 100000*ap::machineepsilon;
//
// fill tags
//
tags.setlength(n);
for(i = 0; i <= n-1; i++)
{
tags(i) = i;
}
//
// build trees
//
kdtreebuild(xy, n, nx, 0, normtype, treex);
kdtreebuild(xy, n, nx, ny, normtype, treexy);
kdtreebuildtagged(xy, tags, n, nx, 0, normtype, treext);
//
// allocate arrays
//
tmpx.setlength(nx);
tmpb.setlength(n);
qx.setlength(n, nx);
qxy.setlength(n, nx+ny);
qtags.setlength(n);
qr.setlength(n);
ptx.setlength(nx);
//
// test general K-NN queries (with self-matches):
// * compare results from different trees (must be equal) and
// check that correct (value,tag) pairs are returned
// * test results from XT tree - let R be radius of query result.
// then all points not in result must be not closer than R.
//
for(q = 1; q <= qcount; q++)
{
//
// Select K: 1..N
//
if( ap::fp_greater(ap::randomreal(),0.5) )
{
k = 1+ap::randominteger(n);
}
else
{
k = 1;
}
//
// Select point (either one of the points, or random)
//
if( ap::fp_greater(ap::randomreal(),0.5) )
{
i = ap::randominteger(n);
ap::vmove(&ptx(0), 1, &xy(i, 0), 1, ap::vlen(0,nx-1));
}
else
{
for(i = 0; i <= nx-1; i++)
{
ptx(i) = 2*ap::randomreal()-1;
}
}
//
// Test:
// * consistency of results from different queries
// * points in query are IN the R-sphere (or at the boundary),
// and points not in query are outside of the R-sphere (or at the boundary)
// * distances are correct and are ordered
//
kx = kdtreequeryknn(treex, ptx, k, true);
kxy = kdtreequeryknn(treexy, ptx, k, true);
kt = kdtreequeryknn(treext, ptx, k, true);
if( kx!=k||kxy!=k||kt!=k )
{
kdterrors = true;
return;
}
kx = 0;
kxy = 0;
kt = 0;
kdtreequeryresultsx(treex, qx, kx);
kdtreequeryresultsxy(treexy, qxy, kxy);
kdtreequeryresultstags(treext, qtags, kt);
kdtreequeryresultsdistances(treext, qr, kr);
if( kx!=k||kxy!=k||kt!=k||kr!=k )
{
kdterrors = true;
return;
}
kdterrors = kdterrors||kdtresultsdifferent(xy, n, qx, qxy, qtags, k, nx, ny);
for(i = 0; i <= n-1; i++)
{
tmpb(i) = true;
}
r = 0;
for(i = 0; i <= k-1; i++)
{
tmpb(qtags(i)) = false;
ap::vmove(&tmpx(0), 1, &ptx(0), 1, ap::vlen(0,nx-1));
ap::vsub(&tmpx(0), 1, &qx(i, 0), 1, ap::vlen(0,nx-1));
r = ap::maxreal(r, vnorm(tmpx, nx, normtype));
}
for(i = 0; i <= n-1; i++)
{
if( tmpb(i) )
{
ap::vmove(&tmpx(0), 1, &ptx(0), 1, ap::vlen(0,nx-1));
ap::vsub(&tmpx(0), 1, &xy(i, 0), 1, ap::vlen(0,nx-1));
kdterrors = kdterrors||ap::fp_less(vnorm(tmpx, nx, normtype),r*(1-errtol));
}
}
for(i = 0; i <= k-2; i++)
{
kdterrors = kdterrors||ap::fp_greater(qr(i),qr(i+1));
}
for(i = 0; i <= k-1; i++)
{
ap::vmove(&tmpx(0), 1, &ptx(0), 1, ap::vlen(0,nx-1));
ap::vsub(&tmpx(0), 1, &xy(qtags(i), 0), 1, ap::vlen(0,nx-1));
kdterrors = kdterrors||ap::fp_greater(fabs(vnorm(tmpx, nx, normtype)-qr(i)),errtol);
}
}
//
// test general approximate K-NN queries (with self-matches):
// * compare results from different trees (must be equal) and
// check that correct (value,tag) pairs are returned
// * test results from XT tree - let R be radius of query result.
// then all points not in result must be not closer than R/(1+Eps).
//
for(q = 1; q <= qcount; q++)
{
//
// Select K: 1..N
//
if( ap::fp_greater(ap::randomreal(),0.5) )
{
k = 1+ap::randominteger(n);
}
else
{
k = 1;
}
//
// Select Eps
//
eps = 0.5+ap::randomreal();
//
// Select point (either one of the points, or random)
//
if( ap::fp_greater(ap::randomreal(),0.5) )
{
i = ap::randominteger(n);
ap::vmove(&ptx(0), 1, &xy(i, 0), 1, ap::vlen(0,nx-1));
}
else
{
for(i = 0; i <= nx-1; i++)
{
ptx(i) = 2*ap::randomreal()-1;
}
}
//
// Test:
// * consistency of results from different queries
// * points in query are IN the R-sphere (or at the boundary),
// and points not in query are outside of the R-sphere (or at the boundary)
// * distances are correct and are ordered
//
kx = kdtreequeryaknn(treex, ptx, k, true, eps);
kxy = kdtreequeryaknn(treexy, ptx, k, true, eps);
kt = kdtreequeryaknn(treext, ptx, k, true, eps);
if( kx!=k||kxy!=k||kt!=k )
{
kdterrors = true;
return;
}
kx = 0;
kxy = 0;
kt = 0;
kdtreequeryresultsx(treex, qx, kx);
kdtreequeryresultsxy(treexy, qxy, kxy);
kdtreequeryresultstags(treext, qtags, kt);
kdtreequeryresultsdistances(treext, qr, kr);
if( kx!=k||kxy!=k||kt!=k||kr!=k )
{
kdterrors = true;
return;
}
kdterrors = kdterrors||kdtresultsdifferent(xy, n, qx, qxy, qtags, k, nx, ny);
for(i = 0; i <= n-1; i++)
{
tmpb(i) = true;
}
r = 0;
for(i = 0; i <= k-1; i++)
{
tmpb(qtags(i)) = false;
ap::vmove(&tmpx(0), 1, &ptx(0), 1, ap::vlen(0,nx-1));
ap::vsub(&tmpx(0), 1, &qx(i, 0), 1, ap::vlen(0,nx-1));
r = ap::maxreal(r, vnorm(tmpx, nx, normtype));
}
for(i = 0; i <= n-1; i++)
{
if( tmpb(i) )
{
ap::vmove(&tmpx(0), 1, &ptx(0), 1, ap::vlen(0,nx-1));
ap::vsub(&tmpx(0), 1, &xy(i, 0), 1, ap::vlen(0,nx-1));
kdterrors = kdterrors||ap::fp_less(vnorm(tmpx, nx, normtype),r*(1-errtol)/(1+eps));
}
}
for(i = 0; i <= k-2; i++)
{
kdterrors = kdterrors||ap::fp_greater(qr(i),qr(i+1));
}
for(i = 0; i <= k-1; i++)
{
ap::vmove(&tmpx(0), 1, &ptx(0), 1, ap::vlen(0,nx-1));
ap::vsub(&tmpx(0), 1, &xy(qtags(i), 0), 1, ap::vlen(0,nx-1));
kdterrors = kdterrors||ap::fp_greater(fabs(vnorm(tmpx, nx, normtype)-qr(i)),errtol);
}
}
//
// test general R-NN queries (with self-matches):
// * compare results from different trees (must be equal) and
// check that correct (value,tag) pairs are returned
// * test results from XT tree - let R be radius of query result.
// then all points not in result must be not closer than R.
//
for(q = 1; q <= qcount; q++)
{
//
// Select R
//
if( ap::fp_greater(ap::randomreal(),0.3) )
{
r = ap::maxreal(ap::randomreal(), ap::machineepsilon);
}
else
{
r = ap::machineepsilon;
}
//
// Select point (either one of the points, or random)
//
if( ap::fp_greater(ap::randomreal(),0.5) )
{
i = ap::randominteger(n);
ap::vmove(&ptx(0), 1, &xy(i, 0), 1, ap::vlen(0,nx-1));
}
else
{
for(i = 0; i <= nx-1; i++)
{
ptx(i) = 2*ap::randomreal()-1;
}
}
//
// Test:
// * consistency of results from different queries
// * points in query are IN the R-sphere (or at the boundary),
// and points not in query are outside of the R-sphere (or at the boundary)
// * distances are correct and are ordered
//
kx = kdtreequeryrnn(treex, ptx, r, true);
kxy = kdtreequeryrnn(treexy, ptx, r, true);
kt = kdtreequeryrnn(treext, ptx, r, true);
if( kxy!=kx||kt!=kx )
{
kdterrors = true;
return;
}
kx = 0;
kxy = 0;
kt = 0;
kdtreequeryresultsx(treex, qx, kx);
kdtreequeryresultsxy(treexy, qxy, kxy);
kdtreequeryresultstags(treext, qtags, kt);
kdtreequeryresultsdistances(treext, qr, kr);
if( kxy!=kx||kt!=kx||kr!=kx )
{
kdterrors = true;
return;
}
kdterrors = kdterrors||kdtresultsdifferent(xy, n, qx, qxy, qtags, kx, nx, ny);
for(i = 0; i <= n-1; i++)
{
tmpb(i) = true;
}
for(i = 0; i <= kx-1; i++)
{
tmpb(qtags(i)) = false;
}
for(i = 0; i <= n-1; i++)
{
ap::vmove(&tmpx(0), 1, &ptx(0), 1, ap::vlen(0,nx-1));
ap::vsub(&tmpx(0), 1, &xy(i, 0), 1, ap::vlen(0,nx-1));
if( tmpb(i) )
{
kdterrors = kdterrors||ap::fp_less(vnorm(tmpx, nx, normtype),r*(1-errtol));
}
else
{
kdterrors = kdterrors||ap::fp_greater(vnorm(tmpx, nx, normtype),r*(1+errtol));
}
}
for(i = 0; i <= kx-2; i++)
{
kdterrors = kdterrors||ap::fp_greater(qr(i),qr(i+1));
}
}
//
// Test self-matching:
// * self-match - nearest neighbor of each point in XY is the point itself
// * no self-match - nearest neighbor is NOT the point itself
//
if( n>1 )
{
//
// test for N=1 have non-general form, but it is not really needed
//
for(task = 0; task <= 1; task++)
{
for(i = 0; i <= n-1; i++)
{
ap::vmove(&ptx(0), 1, &xy(i, 0), 1, ap::vlen(0,nx-1));
kx = kdtreequeryknn(treex, ptx, 1, task==0);
kdtreequeryresultsx(treex, qx, kx);
if( kx!=1 )
{
kdterrors = true;
return;
}
isequal = true;
for(j = 0; j <= nx-1; j++)
{
isequal = isequal&&ap::fp_eq(qx(0,j),ptx(j));
}
if( task==0 )
{
kdterrors = kdterrors||!isequal;
}
else
{
kdterrors = kdterrors||isequal;
}
}
}
}
}
void gmp_fe::set_double_pow_mul(fe* b1, num* e1, fe* b2, num* e2) {
gmp_fe tmpa(field), tmpb(field);
tmpa.set_pow(b1, e1);
tmpb.set_pow(b2, e2);
set_mul(&tmpa, &tmpb);
}
avi_hdr::avi_hdr(bool push_stdout){
uint8_t buf[16];
if (!cin.read((char*) buf,16))
throw std::invalid_argument( err_msg_a );
if (push_stdout)
cout << buf;
string file_type((char*) buf);
bool success = file_type.find("RIFF");
success |= file_type.find("AVI");
success |= file_type.find("LIST");
if (!success)
throw std::invalid_argument( err_msg_a );
//add length of first two words
_file_size = _uint8_to_uint32(buf, 4);
_file_size += 8;
if (!cin.read((char*) buf,16))
throw std::invalid_argument( err_msg_a );
if (push_stdout)
cout << buf;
string avih_head((char*) buf);
success = avih_head.find("hdrl");
success |= avih_head.find("avih");
if (!success)
throw std::invalid_argument( err_msg_b );
_avih_size = _uint8_to_uint32(buf, 0);
//ignore text
_avih_size -= 12;
if ((_avih_size < 0) || (_avih_size > _MAX_AVIH_SIZE))
throw std::invalid_argument( err_msg_b );
uint8_t * avih_buf = new uint8_t[_avih_size];
if (!cin.read((char*) avih_buf,_avih_size))
throw std::invalid_argument( err_msg_a );
if (push_stdout)
cout << avih_buf;
_micro_sec_per_frame = _uint8_to_uint32(avih_buf, 0);
_max_bytes_per_sec = _uint8_to_uint32(avih_buf, 4);
_padding_granularity = _uint8_to_uint32(avih_buf, 8);
_flags = _uint8_to_uint32(avih_buf, 12);
_frames = _uint8_to_uint32(avih_buf, 16);
_streams = _uint8_to_uint32(avih_buf, 24);
_width = _uint8_to_uint32(avih_buf, 28);
_height = _uint8_to_uint32(avih_buf, 32);
//position at end LIST word
int offset=68,length;
length= _uint8_to_uint32(avih_buf, 60);
offset+=length;
strl tmp(avih_buf,60);
_stream_hdr_list.push_back(tmp);
if (_streams==2){
strl tmpb(avih_buf,offset);
_stream_hdr_list.push_back(tmpb);
} else if (_streams>=2)
throw std::invalid_argument( err_msg_d );
delete[] avih_buf;
};
