bool Segment::doesIntersect(const Segment &that, Point* intersectionPoint) const
{
const Vector r(this->b - this->a);
const Vector s(that.b - that.a);
const Vector thatAMinThisA(that.a - this->a);
const double rCrossS(r.cross(s));
if (almost_equal(rCrossS, 0.))
{
if (almost_equal(thatAMinThisA.cross(r), 0.))
{
// colinear, check if overlap
if (this->isDegenerate())
{
if (that.isDegenerate())
{
// both degenerate, are they equal?
if (this->a == that.a)
{
// yes? intersection
if (intersectionPoint)
*intersectionPoint = a;
return true;
}
return false;
}
else
{
// only this is degenerate, is it on that?
if ((a.x >= fmin(that.a.x, that.b.x)) &&
(a.y >= fmin(that.a.y, that.b.y)) &&
(a.x <= fmax(that.a.x, that.b.x)) &&
(a.y <= fmax(that.a.y, that.b.y)))
{
// yes, intersection
if (intersectionPoint)
*intersectionPoint = a;
return true;
}
return false;
}
}
// both segments have non-zero length
const Vector rOnNorm2(r / r.norm2());
const double t0(thatAMinThisA * rOnNorm2);
const double t1(t0 + s * rOnNorm2);
if (fmin(t0, t1) > 1)
return false;
if (fmax(t0, t1) < 0)
return false;
if (intersectionPoint)
{
// intersection is in the middle of the overlapping interval
const double t0Clamped(fmax(fmin(t0, 1.), 0.));
const double t1Clamped(fmax(fmin(t1, 1.), 0.));
const double tMean((t0Clamped + t1Clamped) / 2);
*intersectionPoint = a + r * tMean;
}
return true;
}
return false;
}
else
{
const double t(thatAMinThisA.cross(s) / rCrossS);
const double u(thatAMinThisA.cross(r) / rCrossS);
if (0 <= t && t <= 1 && 0 <= u && u <= 1)
{
if (intersectionPoint)
*intersectionPoint = a + r * t;
return true;
}
return false;
}
}
vector<SubstitutionalCorrelation*> correlators_from_cuns(ChemicalUnitNode* node1,ChemicalUnitNode* node2,vector<double> corr) {
int s1 = node1->chemical_units.size();
int s2 = node2->chemical_units.size();
vector<double> correlations(s1*s2);
//check there are enough numbers in the matrix
//fill the correlations
//if full version, check the last column-row
bool full_version;
if(corr.size()==(s1-1)*(s2-1)) {
full_version = false;
//fill upper-right corner of correlation matrix
for(int i=0; i<s1-1; i++)
for(int j=0; j<s2-1; j++)
correlations[i+s1*j] = corr[i+j*(s1-1)];
} else if(corr.size()==s1*s2) {
full_version = true;
correlations = corr;
} else {
REPORT(ERROR) << "Wrong number of joint probabilities, expected a " << (s1-1)<< "x" << (s2-1) << " or a " << s1 << "x" << s2 << " matrix. Found " << corr.size() << " values.\n";
throw "fail";
}
//fill last row
for(int j=0; j<s2-1; j++){
correlations[s1*j+s1-1]=node2->chemical_units[j].get_occupancy();
for(int i=0; i<s1-1; i++)
correlations[s1*j+s1-1]-=correlations[i+s1*j];
}
//fill last coloumn
for(int i=0; i<s1; i++) {
correlations[(s2-1)*s1+i]=node1->chemical_units[i].get_occupancy();
for(int j=0; j<s2-1; j++)
correlations[(s2-1)*s1+i] -= correlations[i+s1*j];
}
if(full_version)
for(int i=0; i<correlations.size(); ++i)
if(!(almost_equal(corr[i],correlations[i]))){
REPORT(ERROR) << "The joint probabilities are incompatible with the average structure.\n";
throw "fail";
}
//create correlations
vector<SubstitutionalCorrelation*> res;
for(int j=0; j<s2; j++)
{
for(int i=0; i<s1; i++)
{
res.push_back( new SubstitutionalCorrelation(& node1->chemical_units[i],& node2->chemical_units[j], correlations[i+s1*j]));
}
}
return res;
}
END_TEST
START_TEST (test_reject_p2_n3_c4) {
int i;
s_array * paths;
c_array * line_buffer;
i_array * stat_indices;
d_array * obs_stats;
d_array * means;
d_array * std_devs;
s_array * header;
sample_array * samples;
int num_to_retain;
num_to_retain = 3;
paths = init_s_array(1);
line_buffer = init_c_array(1023);
stat_indices = init_i_array(4);
means = init_d_array(1);
std_devs = init_d_array(1);
obs_stats = init_d_array(1);
header = init_s_array(1);
append_s_array(paths, "data/test_parameter_stat_samples4.txt");
append_s_array(paths, "data/test_parameter_stat_samples.txt");
parse_header(get_s_array(paths, 0), line_buffer, header);
for (i = 2; i < header->length; i++) {
append_i_array(stat_indices, i);
}
append_d_array(obs_stats, 0.1);
append_d_array(obs_stats, 0.21);
append_d_array(obs_stats, 1.0);
append_d_array(obs_stats, 2.0);
append_d_array(means, 0.25);
append_d_array(means, 0.2225);
append_d_array(means, 2.5);
append_d_array(means, 3.0);
append_d_array(std_devs, 0.1290994);
append_d_array(std_devs, 0.009574271);
append_d_array(std_devs, 1.290994);
append_d_array(std_devs, 1.154701);
standardize_vector(obs_stats, means, std_devs);
samples = reject(paths, line_buffer, stat_indices, obs_stats, means,
std_devs, num_to_retain, header);
ck_assert_int_eq(samples->length, num_to_retain);
ck_assert_int_eq(samples->capacity, num_to_retain);
ck_assert_msg((almost_equal(samples->a[0]->distance, 0.0, 0.000001)),
"euclidean distance was %lf, expected %lf",
samples->a[0]->distance, 0.0);
ck_assert_msg((almost_equal(samples->a[1]->distance, 0.130035, 0.000001)),
"euclidean distance was %lf, expected %lf",
samples->a[1]->distance, 0.130035);
ck_assert_msg((almost_equal(samples->a[2]->distance, 0.1433004, 0.000001)),
"euclidean distance was %lf, expected %lf",
samples->a[2]->distance, 0.1433004);
free_s_array(paths);
free_c_array(line_buffer);
free_i_array(stat_indices);
free_d_array(obs_stats);
free_sample_array(samples);
free_d_array(means);
free_d_array(std_devs);
free_s_array(header);
}
