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// -*- Mode: C++; tab-width: 2; -*-
// vi: set ts=2:
//
// $Id: fieldLineCreator.C,v 1.1.4.2 2007/04/11 11:55:53 amoll Exp $
#include <BALL/VIEW/MODELS/fieldLineCreator.h>
#include <BALL/KERNEL/atomContainer.h>
#include <BALL/KERNEL/atom.h>
#include <BALL/VIEW/PRIMITIVES/multiLine.h>
#include <BALL/VIEW/PRIMITIVES/point.h>
#include <BALL/VIEW/PRIMITIVES/sphere.h>
using namespace std;
namespace BALL
{
namespace VIEW
{
FieldLineCreator::FieldLineCreator()
: tolerance_(0.0001),
max_steps_(10000),
interpolation_steps_(2),
icosaeder_steps_(1),
atom_distance_(1),
field_line_errors_(0),
use_atoms_(false),
monte_carlo_nr_lines_(500),
potential_grid_(0),
vector_grid_(0),
ac_(0),
use_potential_grid_(false)
{
}
FieldLineCreator::FieldLineCreator(const FieldLineCreator& )
{
}
FieldLineCreator::~FieldLineCreator()
{
#ifdef BALL_VIEW_DEBUG
Log.error() << "Destructing object " << (void *)this
<< " of class " << RTTI::getName<FieldLineCreator>() << std::endl;
#endif
}
Representation* FieldLineCreator::createLines()
{
if (vector_grid_ == 0)
{
BALLVIEW_DEBUG
return 0;
}
field_line_errors_ = 0;
TRegularData3D<Vector3>::CoordinateType spacing = vector_grid_->getSpacing();
TRegularData3D<Vector3>::IndexType size = vector_grid_->getSize();
if (Maths::isZero(spacing.x) ||
Maths::isZero(spacing.y) ||
Maths::isZero(spacing.z))
{
Log.error() << "Aborting, since vector grid has a spacing of 0!" << std::endl;
return 0;
}
if (size.x == 0 ||
size.y == 0 ||
size.z == 0)
{
Log.error() << "Aborting, since vector grid has a size of 0!" << std::endl;
return 0;
}
if (use_atoms_ && ac_ == 0)
{
Log.error() << "No System available for this gradient grid, aborting field line calculation!" << std::endl;
return 0;
}
Representation* rep = new Representation();
rep->setModelType(MODEL_FIELD_LINES);
if (use_atoms_)
{
// seed points from spheres around atoms:
vector<Vector3> start_diffs;
if (icosaeder_steps_ == 0)
{
start_diffs.push_back(Vector3(0,0,0));
}
else
{
start_diffs = VIEW::createSphere(icosaeder_steps_ - 1);
}
AtomIterator ait = ac_->beginAtom();
for (; +ait; ++ait)
{
for (Position p = 0; p < start_diffs.size(); p++)
{
const Vector3& point = ait->getPosition();
const Vector3& diff = start_diffs[p];
createFieldLine_(point + diff * atom_distance_, *rep);
}
}
}
else
{
// method from "Fast Display of Multi Field Lines"
// from Stalling, Zaeckler, Hege; 1997
// Monte Carlo Approach in relation to potential strenght at the individual points
if (use_potential_grid_)
{
if (potential_grid_ == 0)
{
delete rep;
Log.error() << "No potential grid loaded, aborting..." << std::endl;
return 0;
}
TRegularData3D<Vector3>::CoordinateType pspacing = potential_grid_->getSpacing();
TRegularData3D<float>::IndexType psize = potential_grid_->getSize();
if (Maths::isZero(pspacing.x) ||
Maths::isZero(pspacing.y) ||
Maths::isZero(pspacing.z))
{
delete rep;
Log.error() << "Aborting, since grid has a spacing of 0!" << std::endl;
return 0;
}
if (psize.x == 0 ||
psize.y == 0 ||
psize.z == 0)
{
delete rep;
Log.error() << "Aborting, since grid has a size of 0!" << std::endl;
return 0;
}
}
Vector3 origin = vector_grid_->getOrigin();
Vector3 dimension = vector_grid_->getDimension();
VectorGrid::IndexType size = vector_grid_->getSize();
Size sx = (Size)(size.x / 2.0 + 1);
Size sy = (Size)(size.y / 2.0 + 1);
Size sz = (Size)(size.z / 2.0 + 1);
RegularData3D::IndexType st(sx, sy, sz);
Vector3 diff = Vector3(0.001);
RegularData3D new_grid(st, origin - diff, vector_grid_->getDimension() + diff * 2.);
const Size new_grid_size = sx * sy * sz;
for (Position p = 0; p < new_grid_size; p++)
{
new_grid[p] = 0;
}
// use strength of potential grid?
if (use_potential_grid_)
{
if (potential_grid_->getOrigin() != vector_grid_->getOrigin() ||
potential_grid_->getDimension() != vector_grid_->getDimension())
{
delete rep;
Log.error() << "Potential and vector grid have different sizes, aborting..." << std::endl;
return 0;
}
const vector<float>& values = potential_grid_->getData();
for (Position p = 0; p < values.size(); p++)
{
new_grid.getClosestValue((potential_grid_->getCoordinates(p))) += std::abs(values[p]);
}
}
else
{
const vector<Vector3>& values = vector_grid_->getData();
for (Position p = 0; p < values.size(); p++)
{
new_grid.getClosestValue((vector_grid_->getCoordinates(p))) += values[p].getLength();
}
// use strength of vector field
}
vector<Vector3> result_points;
calculateRandomPoints(new_grid, monte_carlo_nr_lines_, result_points);
for (Position p = 0; p < monte_carlo_nr_lines_; p++)
{
createFieldLine_(result_points[p], *rep);
/*
Sphere* s = new Sphere();
s->setPosition(point);
s->setRadius(0.05);
s->setColor(ColorRGBA(0.,0.1,0));
rep->insert(*s);
*/
} // all lines
}
return rep;
}
void FieldLineCreator::createFieldLine_(const Vector3& point, Representation& rep)
{
for (Size backwards = 0; backwards < 2; backwards++)
{
MultiLine* line = new MultiLine;
vector<Vector3> points;
calculateLinePoints_(point, points, (backwards == 0) ? 1. : -1.);
// somethis way may run over the grid's borders:
Index p = 0;
try
{
for (; p < (Index)points.size(); p++)
{
vector_grid_->getClosestIndex(points[p]);
}
}
catch(...)
{
p--;
}
if (p < 3)
{
field_line_errors_ ++;
delete line;
return;
}
// throw away errorous points:
points.resize(p);
// take only points that are at least 0.05 A apart:
Size nrp = points.size();
vector<Vector3>& points_ok = line->vertices;
points_ok.push_back(points[0]);
float min_d = 0.05 * 0.05;
float d = 0;
for (Position p = 1; p < nrp; p++)
{
d += points[p].getSquareDistance(points[p - 1]);
if (d > min_d)
{
points_ok.push_back(points[p]);
d = 0;
}
}
nrp = points_ok.size();
if (nrp < 3)
{
field_line_errors_ ++;
delete line;
return;
}
line->tangents.resize(nrp);
for (Position v = 0; v < nrp - 1; v++)
{
(*line).tangents[v] = points_ok[v+1] - points_ok[v];
}
(*line).tangents[nrp -1] = (*line).tangents[nrp -2];
(*line).colors.push_back(ColorRGBA(0.,0.,1.));
rep.insert(*line);
}
}
/** Compute a field line using a Runge-Kutta of fourth order with adaptive step
* size control. factor can be used to iterate _against_ the gradient, i.e. backwards in time.
*/
void FieldLineCreator::calculateLinePoints_(Vector3 point, vector<Vector3>& points, float factor)
{
TRegularData3D<Vector3>::CoordinateType spacing = vector_grid_->getSpacing();
TRegularData3D<Vector3>::IndexType size = vector_grid_->getSize();
Vector3 k1, k2, k3, k4, k5, k6;
Vector3 p2, p3, p4, p5, p6;
Vector3 error_estimate_vector;
Vector3 scaling;
float error_estimate = 0.;
float min_spacing = std::min(std::min(spacing.x, spacing.y), spacing.z);
float rho = 0.9; // chose sensible values
float lower_limit = min_spacing * 0.00001;
float h = min_spacing;// * 0.1;
// use interpolation_steps interpolation points
std::vector<Vector3> interpolated_values(interpolation_steps_);
Vector3 rk_estimate;
Vector3 grad_current = (*vector_grid_)(point) * factor;
Vector3 grad_old = grad_current;
// Runge - Kutta of order 4 with adaptive step size and
// error control as described in Schwarz: "Numerische Mathematik"
// with step size control taken from Numerical Recipes
for (Size i = 0; i < max_steps_; i++)
{
// compute scaling values for the step size computation (see Numerical Recipes)
scaling.x = fabs(point.x) + fabs(grad_current.x*h) + 1e-30;
scaling.y = fabs(point.y) + fabs(grad_current.y*h) + 1e-30;
scaling.z = fabs(point.z) + fabs(grad_current.z*h) + 1e-30;
if (Maths::isZero(tolerance_))
{
logString("Value 0 for tolerance of field line! Aborting...\n");
return;
}
if (Maths::isZero(h))
{
logString("Value 0 for h of field line! Aborting...\n");
return;
}
if (Maths::isZero(scaling.x) ||
Maths::isZero(scaling.y) ||
Maths::isZero(scaling.z))
{
return;
}
// repeat the Runge-Kutta until the step size is either accepted or completely rejected
bool accepted = false;
while (!accepted)
{
try
{
k1 = h*grad_current;
p2 = point + k1*2./9.;
k2 = h*vector_grid_->getInterpolatedValue(p2)*factor;
p3 = point + k1*1./12. + k2*1./4.;
k3 = h*vector_grid_->getInterpolatedValue(p3)*factor;
p4 = point + k1*69./128. - k2*243./128. + k3*135./64.;
k4 = h*vector_grid_->getInterpolatedValue(p4)*factor;
p5 = point - k1*17./12. + k2*27./4. - k3*27./5.+ k4*16./15.;
k5 = h*vector_grid_->getInterpolatedValue(p5)*factor;
p6 = point + k1*65./432. - k2*5./16. + k3 * 13./16. + k4*4./27. + k5*5./144.;
k6 = h*vector_grid_->getInterpolatedValue(p6)*factor;
// let's see if the steps have become that small that we don't proceed at all...
if (p6 == point)
{
return;
}
rk_estimate = (k1 / 9. + k3 * 9./20. + k4*16./45. + k5 / 12.);
error_estimate_vector = (-k1*2. + k3*9. - k4*64. - k5*15. + k6*72.) / 300.;
error_estimate = std::max(fabs(error_estimate_vector.x/scaling.x),
std::max(fabs(error_estimate_vector.y/scaling.y),
fabs(error_estimate_vector.z/scaling.z)));
error_estimate /= tolerance_;
if (error_estimate > 1.0)
{
// update h using the error estimate
double h_new = h * rho * pow((double)error_estimate, (double)-0.25);
h = (h >= 0) ? std::max(h_new, 0.1*h) : std::min(h_new, 0.1*h);
}
else
{
accepted = true;
}
} catch (Exception::OutOfGrid& e)
{
h /= 2.;
// horrible heuristic... :-)
if (fabs(h) < 1e-7)
{
return;
}
}
}
// compute a step size for the next step (the magic numbers are taken from Numerical Recipes)
if (error_estimate > 1.89e-4) h = rho * h * pow((double)error_estimate, (double)-0.2);
else h = 5.*h;
grad_old = grad_current;
grad_current = (*vector_grid_)(point+rk_estimate)*factor;
cubicInterpolation(point, point+rk_estimate, grad_old, grad_current, interpolated_values);
points.push_back(point);
for (Position p = 0; p < interpolated_values.size(); p++)
{
points.push_back(interpolated_values[p]);
}
point += rk_estimate;
if (rk_estimate.getLength() < lower_limit) break;
}
}
} // namespace VIEW
} // namespace BALL
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