/** Constructor with normal and point
*
* @param normal :: normal to the plane. Points that are in the direction of the
*normal of the plane are considered to be bounded by it.
* @param point :: any point that is on the plane
*/
MDPlane::MDPlane(const Mantid::Kernel::VMD &normal,
const Mantid::Kernel::VMD &point) {
m_nd = normal.getNumDims();
if ((m_nd < 1) || (m_nd > 100))
throw std::invalid_argument(
"MDPlane::ctor(): Invalid number of dimensions in the normal vector !");
if (point.getNumDims() != normal.getNumDims())
throw std::invalid_argument("MDPlane::ctor(): Inconsistent number of "
"dimensions in the normal/point vectors!");
construct(normal, point);
}
/** Apply the transformation to an input vector (as a VMD type).
* This wraps the apply(in,out) method (and will be slower!)
*
* @param inputVector :: an inD-length vector
* @return the output vector as VMD
*/
Mantid::Kernel::VMD
CoordTransform::applyVMD(const Mantid::Kernel::VMD &inputVector) const {
if (inputVector.getNumDims() != inD)
throw std::runtime_error("CoordTransform::apply(): inputVector has the "
"wrong number of coordinates!");
coord_t *outArray = new coord_t[outD];
this->apply(inputVector.getBareArray(), outArray);
VMD out(outD, outArray);
delete[] outArray;
return out;
}
/** Constructor
*
* @param workspace :: IMDWorkspace to plot
* @param logScale :: true to plot Y in log scale
* @param start :: start point in N-dimensions of the line
* @param end :: end point in N-dimensions of the line
* @param normalize :: method for normalizing the line
* @param isDistribution :: is this a distribution (divide by bin width?)
* @return
*/
MantidQwtIMDWorkspaceData::MantidQwtIMDWorkspaceData(Mantid::API::IMDWorkspace_const_sptr workspace, const bool logScale,
Mantid::Kernel::VMD start, Mantid::Kernel::VMD end,
Mantid::API::MDNormalization normalize,
bool isDistribution)
: m_workspace(workspace),
m_logScale(logScale), m_minPositive(0),
m_preview(false),
m_start(start),
m_end(end),
m_normalization(normalize),
m_isDistribution(isDistribution),
m_transform(NULL),
m_plotAxis(PlotDistance), m_currentPlotAxis(PlotDistance)
{
if (start.getNumDims() == 1 && end.getNumDims() == 1)
{
if (start[0] == 0.0 && end[0] == 0.0)
{
// Default start and end. Find the limits
Mantid::Geometry::VecIMDDimension_const_sptr nonIntegDims = m_workspace->getNonIntegratedDimensions();
std::string alongDim = "";
if (!nonIntegDims.empty())
alongDim = nonIntegDims[0]->getName();
else
alongDim = m_workspace->getDimension(0)->getName();
size_t nd = m_workspace->getNumDims();
m_start = VMD(nd);
m_end = VMD(nd);
for (size_t d=0; d<nd; d++)
{
IMDDimension_const_sptr dim = m_workspace->getDimension(d);
if (dim->getDimensionId() == alongDim)
{
// All the way through in the single dimension
m_start[d] = dim->getMinimum();
m_end[d] = dim->getMaximum();
}
else
{
// Mid point along each dimension
m_start[d] = (dim->getMaximum() + dim->getMinimum()) / 2.0f;
m_end[d] = m_start[d];
}
}
}
}
// Unit direction of the line
m_dir = m_end - m_start;
m_dir.normalize();
// And cache the X/Y values
this->cacheLinePlot();
}
/** Set the width of the line in each dimensions
* @param width :: vector for the width in each dimension. X dimension stands in for the XY plane width */
void LineViewer::setThickness(Mantid::Kernel::VMD width)
{
if (m_ws && width.getNumDims() != m_ws->getNumDims())
throw std::runtime_error("LineViewer::setThickness(): Invalid number of dimensions in the width vector.");
m_thickness = width;
updateStartEnd();
}
/** Set the end point of the line to integrate
* @param end :: vector for the end point */
void LineViewer::setEnd(Mantid::Kernel::VMD end)
{
if (m_ws && end.getNumDims() != m_ws->getNumDims())
throw std::runtime_error("LineViewer::setEnd(): Invalid number of dimensions in the end vector.");
m_end = end;
updateStartEnd();
}
/** Set the start point of the line to integrate
* @param start :: vector for the start point */
void LineViewer::setStart(Mantid::Kernel::VMD start)
{
if (m_ws && start.getNumDims() != m_ws->getNumDims())
throw std::runtime_error("LineViewer::setStart(): Invalid number of dimensions in the start vector.");
m_start = start;
updateStartEnd();
}
/** Constructor helper method
* @param min :: nd-sized vector of the minimum edge of the box in each
* dimension
* @param max :: nd-sized vector of the maximum edge of the box
* */
void MDBoxImplicitFunction::construct(const Mantid::Kernel::VMD &min,
const Mantid::Kernel::VMD &max) {
size_t nd = min.size();
if (max.size() != nd)
throw std::invalid_argument(
"MDBoxImplicitFunction::ctor(): Min and max vector sizes must match!");
if (nd == 0 || nd > 100)
throw std::invalid_argument(
"MDBoxImplicitFunction::ctor(): Invalid number of dimensions!");
double volume = 1;
for (size_t d = 0; d < nd; d++) {
volume *= (max[d] - min[d]);
// Make two parallel planes per dimension
// Normal on the min side, so it faces towards +X
std::vector<coord_t> normal_min(nd, 0);
normal_min[d] = +1.0;
// Origin just needs to have its X set to the value. Other coords are
// irrelevant
std::vector<coord_t> origin_min(nd, 0);
origin_min[d] = static_cast<coord_t>(min[d]);
// Build the plane
MDPlane p_min(normal_min, origin_min);
this->addPlane(p_min);
// Normal on the max side, so it faces towards -X
std::vector<coord_t> normal_max(nd, 0);
normal_max[d] = -1.0;
// Origin just needs to have its X set to the value. Other coords are
// irrelevant
std::vector<coord_t> origin_max(nd, 0);
origin_max[d] = static_cast<coord_t>(max[d]);
// Build the plane
MDPlane p_max(normal_max, origin_max);
this->addPlane(p_max);
}
m_volume = volume;
}
/** Build a coordinate transformation based on an origin and orthogonal basis vectors.
* This can reduce the number of dimensions. For example:
*
* - The input position is X=(x,y,z)
* - The origin is X0=(x0,y0,z0)
* - The basis vectors are U and V (reducing from 3 to 2D)
* - The output position u = (X-X0).U = X.U - X0.U = x*Ux + y*Uy + z*Uz + (X0.U)
* - The output position v = (X-X0).V = X.V - X0.V = x*Vx + y*Vy + z*Vz + (X0.V)
*
* And this allows us to create the affine matrix:
*
* | Ux Uy Uz X0.U | | x | | u |
* | Vx Vy Vz X0.V | | y | = | v |
* | 0 0 0 1 | | z | | 1 |
* | 1 |
*
* @param origin :: origin (in the inDimension), which corresponds to (0,0,...) in outD
* @param axes :: a list of basis vectors. There must be outD vectors (one for each output dimension)
* and each vector must be of length inD (all coordinates in the input dimension).
* The vectors must be properly orthogonal: not coplanar or collinear. This is not checked!
* @param scaling :: a vector of size outD of the scaling to perform in each of the
* OUTPUT dimensions.
* @throw if inconsistent vector sizes are received, or zero-length
*/
void CoordTransformAffine::buildOrthogonal(const Mantid::Kernel::VMD & origin, const std::vector< Mantid::Kernel::VMD> & axes,
const Mantid::Kernel::VMD & scaling)
{
if (origin.size() != inD)
throw std::runtime_error("CoordTransformAffine::buildOrthogonal(): the origin must be in the dimensions of the input workspace (length inD).");
if (axes.size() != outD)
throw std::runtime_error("CoordTransformAffine::buildOrthogonal(): you must give as many basis vectors as there are dimensions in the output workspace.");
if (scaling.size() != outD)
throw std::runtime_error("CoordTransformAffine::buildOrthogonal(): the size of the scaling vector must be the same as the number of dimensions in the output workspace.");
// Start with identity
affineMatrix.identityMatrix();
for (size_t i=0; i<axes.size(); i++)
{
if (axes[i].length() == 0.0)
throw std::runtime_error("CoordTransformAffine::buildOrthogonal(): one of the basis vector was of zero length.");
if (axes[i].size() != inD)
throw std::runtime_error("CoordTransformAffine::buildOrthogonal(): one of the basis vectors had the wrong number of dimensions (must be inD).");
// Normalize each axis to unity
VMD basis = axes[i];
basis.normalize();
// The row of the affine matrix = the unit vector
for (size_t j=0; j<basis.size(); j++)
affineMatrix[i][j] = basis[j] * scaling[i];
// Now account for the translation
coord_t transl = 0;
for (size_t j=0; j<basis.size(); j++)
transl += origin[j] * basis[j]; // dot product of origin * basis aka ( X0 . U )
// The last column of the matrix = the translation movement
affineMatrix[i][inD] = -transl * scaling[i];
}
// Copy into the raw matrix (for speed)
copyRawMatrix();
}
/** Returns the signal (normalized by volume) at a given coordinates
* or 0 if masked
*
* @param coords :: coordinate as a VMD vector
* @param normalization :: how to normalize the signal returned
* @return normalized signal
*/
signal_t IMDWorkspace::getSignalWithMaskAtVMD(
const Mantid::Kernel::VMD &coords,
const Mantid::API::MDNormalization &normalization) const {
return this->getSignalWithMaskAtCoord(coords.getBareArray(), normalization);
}
/**
* Make 1D MatrixWorkspace
*/
void ConvertMDHistoToMatrixWorkspace::make1DWorkspace() {
IMDHistoWorkspace_sptr inputWorkspace = getProperty("InputWorkspace");
// This code is copied from MantidQwtIMDWorkspaceData
Mantid::Geometry::VecIMDDimension_const_sptr nonIntegDims =
inputWorkspace->getNonIntegratedDimensions();
std::string alongDim = "";
if (!nonIntegDims.empty())
alongDim = nonIntegDims[0]->getDimensionId();
else
alongDim = inputWorkspace->getDimension(0)->getDimensionId();
size_t nd = inputWorkspace->getNumDims();
Mantid::Kernel::VMD start = VMD(nd);
Mantid::Kernel::VMD end = VMD(nd);
size_t id = 0;
for (size_t d = 0; d < nd; d++) {
Mantid::Geometry::IMDDimension_const_sptr dim =
inputWorkspace->getDimension(d);
if (dim->getDimensionId() == alongDim) {
// All the way through in the single dimension
start[d] = dim->getMinimum();
end[d] = dim->getMaximum();
id = d; // We take the first non integrated dimension to be the diemnsion
// of interest.
} else {
// Mid point along each dimension
start[d] = (dim->getMaximum() + dim->getMinimum()) / 2.0f;
end[d] = start[d];
}
}
// Unit direction of the line
Mantid::Kernel::VMD dir = end - start;
dir.normalize();
std::string normProp = getPropertyValue("Normalization");
Mantid::API::MDNormalization normalization;
if (normProp == "NoNormalization") {
normalization = NoNormalization;
} else if (normProp == "VolumeNormalization") {
normalization = VolumeNormalization;
} else if (normProp == "NumEventsNormalization") {
normalization = NumEventsNormalization;
} else {
normalization = NoNormalization;
}
auto line = inputWorkspace->getLineData(start, end, normalization);
MatrixWorkspace_sptr outputWorkspace = WorkspaceFactory::Instance().create(
"Workspace2D", 1, line.x.size(), line.y.size());
outputWorkspace->dataY(0).assign(line.y.begin(), line.y.end());
outputWorkspace->dataE(0).assign(line.e.begin(), line.e.end());
const size_t numberTransformsToOriginal =
inputWorkspace->getNumberTransformsToOriginal();
CoordTransform_const_sptr transform =
boost::make_shared<NullCoordTransform>(inputWorkspace->getNumDims());
if (numberTransformsToOriginal > 0) {
const size_t indexToLastTransform = numberTransformsToOriginal - 1;
transform = CoordTransform_const_sptr(
inputWorkspace->getTransformToOriginal(indexToLastTransform),
NullDeleter());
}
assert(line.x.size() == outputWorkspace->dataX(0).size());
std::string xAxisLabel = inputWorkspace->getDimension(id)->getName();
const bool autoFind = this->getProperty("FindXAxis");
if (autoFind) {
// We look to the original workspace if possbible to find the dimension of
// interest to plot against.
id = findXAxis(start, end, transform.get(), inputWorkspace.get(), g_log, id,
xAxisLabel);
}
for (size_t i = 0; i < line.x.size(); ++i) {
// Coordinates in the workspace being plotted
VMD wsCoord = start + dir * line.x[i];
VMD inTargetCoord = transform->applyVMD(wsCoord);
outputWorkspace->dataX(0)[i] = inTargetCoord[id];
}
boost::shared_ptr<Kernel::Units::Label> labelX =
boost::dynamic_pointer_cast<Kernel::Units::Label>(
Kernel::UnitFactory::Instance().create("Label"));
labelX->setLabel(xAxisLabel);
outputWorkspace->getAxis(0)->unit() = labelX;
outputWorkspace->setYUnitLabel("Signal");
setProperty("OutputWorkspace", outputWorkspace);
}
/** Obtain coordinates for a line plot through a MDWorkspace.
* Cross the workspace from start to end points, recording the signal along the
*lin at either bin boundaries, or halfway between bin boundaries (which is bin
*centres if the line is dimension aligned). If recording halfway values then
*omit points in masked bins.
*
* @param start :: coordinates of the start point of the line
* @param end :: coordinates of the end point of the line
* @param normalize :: how to normalize the signal
* @returns :: LinePlot with x as the boundaries of the bins, relative
* to start of the line, y set to the normalized signal for each bin with
* Length = length(x) - 1 and e as the error vector for each bin.
* @param bin_centres :: if true then record points halfway between bin
*boundaries, otherwise record on bin boundaries
*/
IMDWorkspace::LinePlot MDHistoWorkspace::getLinePoints(
const Mantid::Kernel::VMD &start, const Mantid::Kernel::VMD &end,
Mantid::API::MDNormalization normalize, const bool bin_centres) const {
LinePlot line;
size_t nd = this->getNumDims();
if (start.getNumDims() != nd)
throw std::runtime_error("Start point must have the same number of "
"dimensions as the workspace.");
if (end.getNumDims() != nd)
throw std::runtime_error(
"End point must have the same number of dimensions as the workspace.");
// Unit-vector of the direction
VMD dir = end - start;
const auto length = dir.normalize();
// Vector with +1 where direction is positive, -1 where negative
#define sgn(x) ((x < 0) ? -1.0f : ((x > 0.) ? 1.0f : 0.0f))
VMD dirSign(nd);
for (size_t d = 0; d < nd; d++) {
dirSign[d] = sgn(dir[d]);
}
const size_t BADINDEX = size_t(-1);
// Dimensions of the workspace
boost::scoped_array<size_t> index(new size_t[nd]);
boost::scoped_array<size_t> numBins(new size_t[nd]);
for (size_t d = 0; d < nd; d++) {
IMDDimension_const_sptr dim = this->getDimension(d);
index[d] = BADINDEX;
numBins[d] = dim->getNBins();
}
const std::set<coord_t> boundaries =
getBinBoundariesOnLine(start, end, nd, dir, length);
if (boundaries.empty()) {
this->makeSinglePointWithNaN(line.x, line.y, line.e);
// Require x.size() = y.size()+1 if recording bin boundaries
if (!bin_centres)
line.x.push_back(length);
return line;
} else {
// Get the first point
std::set<coord_t>::iterator it;
it = boundaries.cbegin();
coord_t lastLinePos = *it;
VMD lastPos = start + (dir * lastLinePos);
if (!bin_centres) {
line.x.push_back(lastLinePos);
}
++it;
coord_t linePos = 0;
for (; it != boundaries.cend(); ++it) {
// This is our current position along the line
linePos = *it;
// This is the full position at this boundary
VMD pos = start + (dir * linePos);
// Position in the middle of the bin
VMD middle = (pos + lastPos) * 0.5;
// Find the signal in this bin
const auto linearIndex =
this->getLinearIndexAtCoord(middle.getBareArray());
if (bin_centres && !this->getIsMaskedAt(linearIndex)) {
coord_t bin_centrePos =
static_cast<coord_t>((linePos + lastLinePos) * 0.5);
line.x.push_back(bin_centrePos);
} else if (!bin_centres)
line.x.push_back(linePos);
if (linearIndex < m_length) {
auto normalizer = getNormalizationFactor(normalize, linearIndex);
// And add the normalized signal/error to the list too
auto signal = this->getSignalAt(linearIndex) * normalizer;
if (boost::math::isinf(signal)) {
// The plotting library (qwt) doesn't like infs.
signal = std::numeric_limits<signal_t>::quiet_NaN();
}
if (!bin_centres || !this->getIsMaskedAt(linearIndex)) {
line.y.push_back(signal);
line.e.push_back(this->getErrorAt(linearIndex) * normalizer);
}
// Save the position for next bin
lastPos = pos;
} else {
// Invalid index. This shouldn't happen
line.y.push_back(std::numeric_limits<signal_t>::quiet_NaN());
line.e.push_back(std::numeric_limits<signal_t>::quiet_NaN());
}
lastLinePos = linePos;
} // for each unique boundary
// If all bins were masked
if (line.x.size() == 0) {
this->makeSinglePointWithNaN(line.x, line.y, line.e);
}
}
return line;
}