Workspace2D.cpp

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// Mantid Repository : https://github.com/mantidproject/mantid
//
// Copyright © 2018 ISIS Rutherford Appleton Laboratory UKRI,
//   NScD Oak Ridge National Laboratory, European Spallation Source,
//   Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
// SPDX - License - Identifier: GPL - 3.0 +
#include "MantidDataObjects/Workspace2D.h"
#include "MantidAPI/ISpectrum.h"
#include "MantidAPI/RefAxis.h"
#include "MantidAPI/SpectraAxis.h"
#include "MantidAPI/WorkspaceFactory.h"
#include "MantidHistogramData/LinearGenerator.h"
#include "MantidKernel/Exception.h"
#include "MantidKernel/IPropertyManager.h"
#include "MantidKernel/VectorHelper.h"
 
#include <algorithm>
#include <sstream>
 
using Mantid::API::MantidImage;
 
namespace Mantid::DataObjects {
using std::size_t;
 
DECLARE_WORKSPACE(Workspace2D)
 
 
Workspace2D::Workspace2D(const Parallel::StorageMode storageMode) : HistoWorkspace(storageMode) {}
 
Workspace2D::Workspace2D(const Workspace2D &other) : HistoWorkspace(other), m_monitorList(other.m_monitorList) {
  data.resize(other.data.size());
  for (size_t i = 0; i < data.size(); ++i) {
    data[i] = std::make_unique<Histogram1D>(*(other.data[i]));
  }
}
 
Workspace2D::~Workspace2D() = default;
 
void Workspace2D::init(const std::size_t &NVectors, const std::size_t &XLength, const std::size_t &YLength) {
  data.resize(NVectors);
 
  auto x = Kernel::make_cow<HistogramData::HistogramX>(XLength, HistogramData::LinearGenerator(1.0, 1.0));
  HistogramData::Counts y(YLength);
  HistogramData::CountStandardDeviations e(YLength);
  Histogram1D spec(HistogramData::getHistogramXMode(XLength, YLength), HistogramData::Histogram::YMode::Counts);
  spec.setX(x);
  spec.setCounts(y);
  spec.setCountStandardDeviations(e);
  for (size_t i = 0; i < data.size(); i++) {
    data[i] = std::make_unique<Histogram1D>(spec);
    // Default spectrum number = starts at 1, for workspace index 0.
    data[i]->setSpectrumNo(specnum_t(i + 1));
  }
 
  // Add axes that reference the data
  m_axes.resize(2);
  m_axes[0] = std::make_unique<API::RefAxis>(this);
  m_axes[1] = std::make_unique<API::SpectraAxis>(this);
}
 
void Workspace2D::init(const HistogramData::Histogram &histogram) {
  data.resize(numberOfDetectorGroups());
 
  HistogramData::Histogram initializedHistogram(histogram);
  if (!histogram.sharedY()) {
    if (histogram.yMode() == HistogramData::Histogram::YMode::Frequencies) {
      initializedHistogram.setFrequencies(histogram.size(), 0.0);
      initializedHistogram.setFrequencyStandardDeviations(histogram.size(), 0.0);
    } else { // YMode::Counts or YMode::Uninitialized -> default to Counts
      initializedHistogram.setCounts(histogram.size(), 0.0);
      initializedHistogram.setCountStandardDeviations(histogram.size(), 0.0);
    }
  }
 
  Histogram1D spec(initializedHistogram.xMode(), initializedHistogram.yMode());
  spec.setHistogram(initializedHistogram);
  std::transform(data.begin(), data.end(), data.begin(),
                 [&spec](const auto &) { return std::move(std::make_unique<Histogram1D>(spec)); });
 
  // Add axes that reference the data
  m_axes.resize(2);
  m_axes[0] = std::make_unique<API::RefAxis>(this);
  m_axes[1] = std::make_unique<API::SpectraAxis>(this);
}
 
bool Workspace2D::isRaggedWorkspace() const {
  if (data.empty()) {
    throw std::runtime_error("There is no data in the Workspace2D, "
                             "therefore cannot determine if it is ragged.");
  } else {
    const auto numberOfBins = data[0]->size();
    return std::any_of(data.cbegin(), data.cend(),
                       [&numberOfBins](const auto &histogram) { return numberOfBins != histogram->size(); });
  }
}
 
size_t Workspace2D::getNumberHistograms() const { return getHistogramNumberHelper(); }
 
size_t Workspace2D::size() const {
  return std::accumulate(
      data.begin(), data.end(), static_cast<size_t>(0),
      [](const size_t value, const std::unique_ptr<Histogram1D> &histo) { return value + histo->size(); });
}
 
size_t Workspace2D::blocksize() const {
  if (data.empty()) {
    return 0;
  } else {
    size_t numBins = data[0]->size();
    const auto it =
        std::find_if_not(data.cbegin(), data.cend(), [numBins](const auto &iter) { return numBins == iter->size(); });
    if (it != data.cend())
      throw std::length_error("blocksize undefined because size of histograms is not equal");
    return numBins;
  }
}
 
std::size_t Workspace2D::getNumberBins(const std::size_t &index) const {
  if (index < data.size())
    return data[index]->size();
 
  throw std::invalid_argument("Could not find number of bins in a histogram at index " + std::to_string(index) +
                              ": index is too large.");
}
 
std::size_t Workspace2D::getMaxNumberBins() const {
  if (data.empty()) {
    return 0;
  } else {
    auto maxNumberOfBins = data[0]->size();
    for (const auto &iter : data) {
      const auto numberOfBins = iter->size();
      if (numberOfBins > maxNumberOfBins)
        maxNumberOfBins = numberOfBins;
    }
    return maxNumberOfBins;
  }
}
 
void Workspace2D::setImageY(const MantidImage &image, size_t start, bool parallelExecution) {
  MantidImage m;
  setImageYAndE(image, m, start, parallelExecution);
}
 
void Workspace2D::setImageE(const MantidImage &image, size_t start, bool parallelExecution) {
  MantidImage m;
  setImageYAndE(m, image, start, parallelExecution);
}
 
void Workspace2D::setImageYAndE(const API::MantidImage &imageY, const API::MantidImage &imageE, size_t start,
                                bool loadAsRectImg, double scale_1, [[maybe_unused]] bool parallelExecution) {
  if (imageY.empty() && imageE.empty())
    return;
  if (imageY.empty() && imageE[0].empty())
    return;
  if (imageE.empty() && imageY[0].empty())
    return;
 
  const size_t numBins = blocksize();
  if (!loadAsRectImg && numBins != 1) {
    throw std::runtime_error("Cannot set image in workspace: a single bin workspace is "
                             "required when initializing a workspace from an "
                             "image using a histogram per pixel.");
  }
 
  size_t height;
  size_t width;
  if (!imageY.empty()) {
    height = imageY.size();
    width = imageY.front().size();
  } else {
    height = imageE.size();
    width = imageE.front().size();
  }
  size_t dataSize = width * height;
 
  if (start + dataSize > getNumberHistograms() * numBins) {
    throw std::runtime_error("Cannot set image: image is bigger than workspace.");
  }
 
  if (!loadAsRectImg) {
    // 1 pixel - one spectrum
    PARALLEL_FOR_IF(parallelExecution)
    for (int i = 0; i < static_cast<int>(height); ++i) {
 
      const auto &rowY = imageY[i];
      const auto &rowE = imageE[i];
      size_t spec = start + static_cast<size_t>(i) * width;
      auto pE = rowE.begin();
      for (auto pY = rowY.begin(); pY != rowY.end() && pE != rowE.end(); ++pY, ++pE, ++spec) {
        data[spec]->dataY()[0] = *pY;
        data[spec]->dataE()[0] = *pE;
      }
    }
  } else {
 
    if (height != (getNumberHistograms()))
      throw std::runtime_error(std::string("To load an image into a workspace with one spectrum per "
                                           "row, then number of spectra (") +
                               std::to_string(getNumberHistograms()) +
                               ") needs to be equal to the height (rows) of the image (" + std::to_string(height) +
                               ")");
 
    if (width != numBins)
      throw std::runtime_error(std::string("To load an image into a workspace with one spectrum per "
                                           "row, then number of bins (") +
                               std::to_string(numBins) + ") needs to be equal to the width (columns) of the image (" +
                               std::to_string(width) + ")");
 
    // one spectrum - one row
    PARALLEL_FOR_IF(parallelExecution)
    for (int i = 0; i < static_cast<int>(height); ++i) {
 
      const auto &rowY = imageY[i];
      const auto &rowE = imageE[i];
      data[i]->dataY() = rowY;
      data[i]->dataE() = rowE;
    }
    // X values. Set first spectrum and copy/propagate that one to all the other
    // spectra
    PARALLEL_FOR_IF(parallelExecution)
    for (int i = 0; i < static_cast<int>(width) + 1; ++i) {
      data[0]->dataX()[i] = i * scale_1;
    }
    PARALLEL_FOR_IF(parallelExecution)
    for (int i = 1; i < static_cast<int>(height); ++i) {
      data[i]->setX(data[0]->ptrX());
    }
  }
}
 
Histogram1D &Workspace2D::getSpectrumWithoutInvalidation(const size_t index) {
  auto &spec = const_cast<Histogram1D &>(static_cast<const Workspace2D &>(*this).getSpectrum(index));
  spec.setMatrixWorkspace(this, index);
  return spec;
}
 
const Histogram1D &Workspace2D::getSpectrum(const size_t index) const {
  if (index >= data.size()) {
    std::ostringstream ss;
    ss << "Workspace2D::getSpectrum, histogram number " << index << " out of range " << data.size();
    throw std::range_error(ss.str());
  }
  return *data[index];
}
 
//--------------------------------------------------------------------------------------------
size_t Workspace2D::getHistogramNumberHelper() const { return data.size(); }
 
//---------------------------------------------------------------------------
void Workspace2D::generateHistogram(const std::size_t index, const MantidVec &X, MantidVec &Y, MantidVec &E,
                                    bool skipError) const {
  UNUSED_ARG(skipError);
  if (index >= data.size())
    throw std::range_error("Workspace2D::generateHistogram, histogram number out of range");
  // output data arrays are implicitly filled by function
  const auto &spec = this->getSpectrum(index);
  const MantidVec &currentX = spec.readX();
  const MantidVec &currentY = spec.readY();
  const MantidVec &currentE = spec.readE();
  if (X.size() <= 1)
    throw std::runtime_error("Workspace2D::generateHistogram(): X vector must be at least length 2");
  Y.resize(X.size() - 1, 0);
  E.resize(X.size() - 1, 0);
 
  // Perform the rebin from the current bins to the new ones
  if (currentX.size() == currentY.size()) // First, convert to bin boundaries if needed.  The
  {                                       // VectorHelper::rebin, assumes bin boundaries, even if
    std::vector<double> histX;            // it is a distribution!
    histX.resize(currentX.size() + 1);
    Mantid::Kernel::VectorHelper::convertToBinBoundary(currentX, histX);
    Mantid::Kernel::VectorHelper::rebin(histX, currentY, currentE, X, Y, E, true);
  } else // assume x_size = y_size + 1
  {
    Mantid::Kernel::VectorHelper::rebin(currentX, currentY, currentE, X, Y, E, this->isDistribution());
  }
}
 
Workspace2D *Workspace2D::doClone() const { return new Workspace2D(*this); }
Workspace2D *Workspace2D::doCloneEmpty() const { return new Workspace2D(storageMode()); }
} // namespace Mantid::DataObjects
 
namespace Mantid::Kernel {
template <>
DLLExport Mantid::DataObjects::Workspace2D_sptr
IPropertyManager::getValue<Mantid::DataObjects::Workspace2D_sptr>(const std::string &name) const {
  auto *prop = dynamic_cast<PropertyWithValue<Mantid::DataObjects::Workspace2D_sptr> *>(getPointerToProperty(name));
  if (prop) {
    return *prop;
  } else {
    std::string message =
        "Attempt to assign property " + name + " to incorrect type. Expected shared_ptr<Workspace2D>.";
    throw std::runtime_error(message);
  }
}
 
template <>
DLLExport Mantid::DataObjects::Workspace2D_const_sptr
IPropertyManager::getValue<Mantid::DataObjects::Workspace2D_const_sptr>(const std::string &name) const {
  auto *prop = dynamic_cast<PropertyWithValue<Mantid::DataObjects::Workspace2D_sptr> *>(getPointerToProperty(name));
  if (prop) {
    return prop->operator()();
  } else {
    std::string message =
        "Attempt to assign property " + name + " to incorrect type. Expected const shared_ptr<Workspace2D>.";
    throw std::runtime_error(message);
  }
}
} // namespace Mantid::Kernel