GenericDataProcessorPresenter.cpp

#include "MantidQtMantidWidgets/DataProcessorUI/GenericDataProcessorPresenter.h"
#include "MantidAPI/AlgorithmManager.h"
#include "MantidAPI/ITableWorkspace.h"
#include "MantidAPI/MatrixWorkspace.h"
#include "MantidAPI/NotebookWriter.h"
#include "MantidAPI/TableRow.h"
#include "MantidAPI/WorkspaceFactory.h"
#include "MantidGeometry/Instrument.h"
#include "MantidKernel/Strings.h"
#include "MantidKernel/TimeSeriesProperty.h"
#include "MantidKernel/Utils.h"
#include "MantidKernel/make_unique.h"
#include "MantidQtMantidWidgets/AlgorithmHintStrategy.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorAppendRowCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorClearSelectedCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorCopySelectedCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorCutSelectedCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorDeleteRowCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorExpandCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorExportTableCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorGenerateNotebook.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorGroupRowsCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorImportTableCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorNewTableCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorOpenTableCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorOptionsCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorPasteSelectedCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorPlotGroupCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorPlotRowCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorPrependRowCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorProcessCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorSaveTableAsCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorSaveTableCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorSeparatorCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorView.h"
#include "MantidQtMantidWidgets/DataProcessorUI/DataProcessorWorkspaceCommand.h"
#include "MantidQtMantidWidgets/DataProcessorUI/ParseKeyValueString.h"
#include "MantidQtMantidWidgets/DataProcessorUI/QDataProcessorTableModel.h"
#include "MantidQtMantidWidgets/DataProcessorUI/QtDataProcessorOptionsDialog.h"
#include "MantidQtMantidWidgets/DataProcessorUI/WorkspaceReceiver.h"
#include "MantidQtMantidWidgets/ProgressPresenter.h"
#include "MantidQtMantidWidgets/ProgressableView.h"

#include <boost/regex.hpp>
#include <boost/tokenizer.hpp>
#include <fstream>
#include <sstream>

using namespace Mantid::API;
using namespace Mantid::Geometry;
using namespace Mantid::Kernel;
using namespace MantidQt::MantidWidgets;

namespace MantidQt {
namespace MantidWidgets {

/**
* Constructor
* @param whitelist : The set of properties we want to show as columns
* @param preprocessMap : A map containing instructions for pre-processing
* @param processor : A DataProcessorProcessingAlgorithm
* @param postprocessor : A DataProcessorPostprocessingAlgorithm
* workspaces
*/
GenericDataProcessorPresenter::GenericDataProcessorPresenter(
    const DataProcessorWhiteList &whitelist,
    const std::map<std::string, DataProcessorPreprocessingAlgorithm>
        &preprocessMap,
    const DataProcessorProcessingAlgorithm &processor,
    const DataProcessorPostprocessingAlgorithm &postprocessor)
    : WorkspaceObserver(), m_view(nullptr), m_progressView(nullptr),
      m_whitelist(whitelist), m_preprocessMap(preprocessMap),
      m_processor(processor), m_postprocessor(postprocessor),
      m_tableDirty(false) {

  // Columns Group and Options must be added to the whitelist
  m_whitelist.addElement("Group", "Group",
                         "<b>Grouping for post-processing</b><br "
                         "/><i>required</i><br />The value of this column "
                         "determines which other rows this row's output will "
                         "be post-processed with. All rows with the same group "
                         "number are post-processed together.");
  m_whitelist.addElement("Options", "Options",
                         "<b>Override <samp>" + processor.name() +
                             "</samp> properties</b><br /><i>optional</i><br "
                             "/>This column allows you to "
                             "override the properties used when executing "
                             "the main reduction algorithm. "
                             "Options are given as "
                             "key=value pairs, separated by commas. Values "
                             "containing commas must be quoted. In case of "
                             "conflict between options "
                             "specified via this column and options specified "
                             "via the <b>Process</b> line edit, the former "
                             "prevail.");
  m_columns = static_cast<int>(m_whitelist.size());
}

/**
* Destructor
*/
GenericDataProcessorPresenter::~GenericDataProcessorPresenter() {}

/**
* Sets the views this presenter is going to handle
* @param tableView : The table view
* @param progressView : The progress view
*/
void GenericDataProcessorPresenter::acceptViews(
    DataProcessorView *tableView, ProgressableView *progressView) {

  // As soon as we are given a view, initialize everything
  m_view = tableView;
  m_progressView = progressView;

  // Initialise options
  // Load saved values from disk
  initOptions();
  // Create the process layout
  createProcessLayout();

  // Populate an initial list of valid tables to open, and subscribe to the ADS
  // to keep it up to date
  Mantid::API::AnalysisDataServiceImpl &ads =
      Mantid::API::AnalysisDataService::Instance();

  auto items = ads.getObjectNames();
  for (auto const &name : items) {
    Workspace_sptr ws = ads.retrieve(name);

    if (isValidModel(ws))
      m_workspaceList.insert(name);
  }
  observeAdd();
  observePostDelete();
  observeRename();
  observeADSClear();
  observeAfterReplace();
  m_view->setTableList(m_workspaceList);

  // Provide autocompletion hints for the options column. We use the algorithm's
  // properties minus those we blacklist. We blacklist any useless properties or
  // ones we're handling that the user should'nt touch.
  IAlgorithm_sptr alg = AlgorithmManager::Instance().create(m_processor.name());
  m_view->setOptionsHintStrategy(
      new AlgorithmHintStrategy(alg, m_processor.blacklist()), m_columns - 1);

  // Start with a blank table
  newTable();
}

/**
Tells the view how to create the HintingLineEdits for pre-, post- and processing
*/
void GenericDataProcessorPresenter::createProcessLayout() {

  std::vector<std::string> stages;
  std::vector<std::string> algNames;
  std::vector<std::map<std::string, std::string>> hints;

  // Pre-process
  // The number of items depends on the number of algorithms needed for
  // pre-processing the data
  for (auto it = m_preprocessMap.begin(); it != m_preprocessMap.end(); ++it) {

    IAlgorithm_sptr alg =
        AlgorithmManager::Instance().create(it->second.name());
    AlgorithmHintStrategy strategy(alg, it->second.blacklist());
    stages.push_back("Pre-process");
    algNames.push_back(alg->name());
    hints.push_back(strategy.createHints());
  }

  // Process
  // Only one algorithm
  {
    IAlgorithm_sptr alg =
        AlgorithmManager::Instance().create(m_processor.name());
    AlgorithmHintStrategy strategy(alg, m_processor.blacklist());
    stages.push_back("Process");
    algNames.push_back(alg->name());
    hints.push_back(strategy.createHints());
  }

  // Post-process
  // Only one algorithm
  {
    IAlgorithm_sptr alg =
        AlgorithmManager::Instance().create(m_postprocessor.name());
    AlgorithmHintStrategy strategy(alg, m_postprocessor.blacklist());
    stages.push_back("Post-process");
    algNames.push_back(alg->name());
    hints.push_back(strategy.createHints());
  }

  m_view->setGlobalOptions(stages, algNames, hints);
}

/**
* Validates a table workspace
* @param model : [input] The table workspace to validate
* @throws std::runtime_error if the model is not valid
*/
void GenericDataProcessorPresenter::validateModel(ITableWorkspace_sptr model) {
  if (!model)
    throw std::runtime_error("Null pointer");

  int columns = static_cast<int>(model->columnCount());
  if (columns != m_columns)
    throw std::runtime_error("Selected table has the incorrect number of "
                             "columns to be used as a data processor table.");

  try {
    // All columns must be strings
    size_t ncols = model->columnCount();
    for (size_t i = 0; i < ncols - 2; i++)
      model->String(0, i);
    // Except Group, which must be int
    model->Int(0, ncols - 2);
    // Options column must be string too
    model->String(0, ncols - 1);
  } catch (const std::runtime_error &) {
    throw std::runtime_error("Selected table does not meet the specifications "
                             "to become a model for this interface.");
  }
}

/**
* Checks if a model is valid
* @param model : [input] The table workspace to validate
* @returns : True if the model is valid. False otherwise
*/
bool GenericDataProcessorPresenter::isValidModel(Workspace_sptr model) {
  try {
    validateModel(boost::dynamic_pointer_cast<ITableWorkspace>(model));
  } catch (...) {
    return false;
  }
  return true;
}

/**
* Creates a model using the whitelist supplied to this presenter
* @returns : The new model
*/
ITableWorkspace_sptr GenericDataProcessorPresenter::createWorkspace() {
  ITableWorkspace_sptr ws = WorkspaceFactory::Instance().createTable();

  for (int col = 0; col < m_columns - 2; col++) {
    // The columns provided to this presenter
    auto column = ws->addColumn("str", m_whitelist.colNameFromColIndex(col));
    column->setPlotType(0);
  }
  // The Group column, must be int
  auto colGroup = ws->addColumn("int", "Group");
  colGroup->setPlotType(0);
  auto colOptions = ws->addColumn("str", "Options");
  colOptions->setPlotType(0);

  return ws;
}

/**
* Creates a default model using the whitelist supplied to this presenter
* @returns : The new model
*/
ITableWorkspace_sptr GenericDataProcessorPresenter::createDefaultWorkspace() {
  auto ws = createWorkspace();
  ws->appendRow();
  return ws;
}

/**
* Finds the first unused group id
*/
int GenericDataProcessorPresenter::getUnusedGroup(
    std::set<int> ignoredRows) const {
  std::set<int> usedGroups;

  // Scan through all the rows, working out which group ids are used
  for (int idx = 0; idx < m_model->rowCount(); ++idx) {
    if (ignoredRows.find(idx) != ignoredRows.end())
      continue;

    // This is an unselected row. Add it to the list of used group ids
    usedGroups.insert(
        m_model->data(m_model->index(idx, m_columns - 2)).toInt());
  }

  int groupId = 0;

  // While the group id is one of the used ones, increment it by 1
  while (usedGroups.find(groupId) != usedGroups.end())
    groupId++;

  return groupId;
}

/**
Process selected rows
*/
void GenericDataProcessorPresenter::process() {
  if (m_model->rowCount() == 0) {
    m_view->giveUserWarning("Cannot process an empty Table", "Warning");
    return;
  }

  std::set<int> rows = m_view->getSelectedRows();
  if (rows.empty()) {
    if (m_options["WarnProcessAll"].toBool()) {
      // Does the user want to abort?
      if (!m_view->askUserYesNo(
              "This will process all rows in the table. Continue?",
              "Process all rows?"))
        return;
    }

    // They want to process all rows, so populate rows with every index in the
    // model
    for (int idx = 0; idx < m_model->rowCount(); ++idx)
      rows.insert(idx);
  }

  // Map group numbers to the set of rows in that group we want to process
  std::map<int, std::set<int>> groups;
  for (auto it = rows.begin(); it != rows.end(); ++it)
    groups[m_model->data(m_model->index(*it, m_columns - 2)).toInt()].insert(
        *it);

  // Check each group and warn if we're only partially processing it
  for (auto gIt = groups.begin(); gIt != groups.end(); ++gIt) {
    const int &groupId = gIt->first;
    const std::set<int> &groupRows = gIt->second;
    // Are we only partially processing a group?
    if (groupRows.size() < numRowsInGroup(gIt->first) &&
        m_options["WarnProcessPartialGroup"].toBool()) {
      std::stringstream err;
      err << "You have only selected " << groupRows.size() << " of the ";
      err << numRowsInGroup(groupId) << " rows in group " << groupId << ".";
      err << " Are you sure you want to continue?";
      if (!m_view->askUserYesNo(err.str(), "Continue Processing?"))
        return;
    }
  }

  if (!rowsValid(rows)) {
    return;
  }

  if (!processGroups(groups, rows)) {
    return;
  }

  // If "Output Notebook" checkbox is checked then create an ipython notebook
  if (m_view->getEnableNotebook()) {
    saveNotebook(groups, rows);
  }
}

/**
Display a dialog to choose save location for notebook, then save the notebook
there
@param groups : groups of rows to stitch
@param rows : rows selected for processing
*/
void GenericDataProcessorPresenter::saveNotebook(
    std::map<int, std::set<int>> groups, std::set<int> rows) {

  std::string filename = m_view->requestNotebookPath();
  if (filename == "") {
    return;
  }

  // Get all the options used for the reduction from the view
  std::map<std::string, std::string> preprocessingOptionsMap;
  for (auto it = m_preprocessMap.begin(); it != m_preprocessMap.end(); ++it) {
    preprocessingOptionsMap[it->first] =
        m_view->getProcessingOptions(it->second.name());
  }
  auto processingOptions = m_view->getProcessingOptions(m_processor.name());
  auto postprocessingOptions =
      m_view->getProcessingOptions(m_postprocessor.name());

  auto notebook = Mantid::Kernel::make_unique<DataProcessorGenerateNotebook>(
      m_wsName, m_model, m_view->getProcessInstrument(), m_whitelist,
      m_preprocessMap, m_processor, m_postprocessor, preprocessingOptionsMap,
      processingOptions, postprocessingOptions);
  std::string generatedNotebook = notebook->generateNotebook(groups, rows);

  std::ofstream file(filename.c_str(), std::ofstream::trunc);
  file << generatedNotebook;
  file.flush();
  file.close();
}

/**
Post-processes the workspaces created by the given rows together.
@param rows : the list of rows
*/
void GenericDataProcessorPresenter::postProcessRows(std::set<int> rows) {
  // If we can get away with doing nothing, do.
  if (rows.size() < 2)
    return;

  // The input workspace names
  std::vector<std::string> inputNames;

  // The name to call the post-processed ws
  const std::string outputWSName =
      getPostprocessedWorkspaceName(rows, m_postprocessor.prefix());

  // Go through each row and get the input ws names
  for (auto rowIt = rows.begin(); rowIt != rows.end(); ++rowIt) {

    // The name of the reduced workspace for this row
    const std::string inputWSName =
        getReducedWorkspaceName(*rowIt, m_processor.prefix(0));

    if (AnalysisDataService::Instance().doesExist(inputWSName)) {

      inputNames.emplace_back(inputWSName);
    }
  }
  const std::string inputWSNames = boost::algorithm::join(inputNames, ", ");

  // If the previous result is in the ADS already, we'll need to remove it.
  // If it's a group, we'll get an error for trying to group into a used group
  // name
  if (AnalysisDataService::Instance().doesExist(outputWSName))
    AnalysisDataService::Instance().remove(outputWSName);

  IAlgorithm_sptr alg =
      AlgorithmManager::Instance().create(m_postprocessor.name());
  alg->initialize();
  alg->setProperty(m_postprocessor.inputProperty(), inputWSNames);
  alg->setProperty(m_postprocessor.outputProperty(), outputWSName);

  // Read the post-processing instructions from the view
  const std::string options =
      m_view->getProcessingOptions(m_postprocessor.name());
  auto optionsMap = parseKeyValueString(options);
  for (auto kvp = optionsMap.begin(); kvp != optionsMap.end(); ++kvp) {
    try {
      alg->setProperty(kvp->first, kvp->second);
    } catch (Mantid::Kernel::Exception::NotFoundError &) {
      throw std::runtime_error("Invalid property in options column: " +
                               kvp->first);
    }
  }

  alg->execute();

  if (!alg->isExecuted())
    throw std::runtime_error("Failed to post-process workspaces.");
}

/**
Process stitch groups
@param rows : rows in the model
@param groups : groups of rows to stitch
@returns true if successful, otherwise false
*/
bool GenericDataProcessorPresenter::processGroups(
    std::map<int, std::set<int>> groups, std::set<int> rows) {
  int progress = 0;
  // Each group and each row within count as a progress step.
  const int maxProgress = (int)(rows.size() + groups.size());
  ProgressPresenter progressReporter(progress, maxProgress, maxProgress,
                                     m_progressView);

  for (auto gIt = groups.begin(); gIt != groups.end(); ++gIt) {
    const std::set<int> groupRows = gIt->second;

    // Reduce each row
    for (auto rIt = groupRows.begin(); rIt != groupRows.end(); ++rIt) {
      try {
        reduceRow(*rIt);
        progressReporter.report();
      } catch (std::exception &ex) {
        const std::string rowNo =
            Mantid::Kernel::Strings::toString<int>(*rIt + 1);
        const std::string message =
            "Error encountered while processing row " + rowNo + ":\n";
        m_view->giveUserCritical(message + ex.what(), "Error");
        progressReporter.clear();
        return false;
      }
    }

    try {
      postProcessRows(groupRows);
      progressReporter.report();
    } catch (std::exception &ex) {
      const std::string groupNo =
          Mantid::Kernel::Strings::toString<int>(gIt->first);
      const std::string message =
          "Error encountered while stitching group " + groupNo + ":\n";
      m_view->giveUserCritical(message + ex.what(), "Error");
      progressReporter.clear();
      return false;
    }
  }
  return true;
}

/**
Validate rows.
@param rows : Rows in the model to validate
@returns true if all rows are valid and false otherwise
*/
bool GenericDataProcessorPresenter::rowsValid(std::set<int> rows) {
  for (auto it = rows.begin(); it != rows.end(); ++it) {
    try {
      validateRow(*it);
    } catch (std::exception &ex) {
      // Allow two theta to be blank
      if (ex.what() ==
          std::string("Value for two theta could not be found in log."))
        continue;

      const std::string rowNo = Mantid::Kernel::Strings::toString<int>(*it + 1);
      m_view->giveUserCritical(
          "Error found in row " + rowNo + ":\n" + ex.what(), "Error");
      return false;
    }
  }
  return true;
}

/**
Validate a row.
A row may pass validation, but it is not necessarily ready for processing.
@param rowNo : The row in the model to validate
@throws std::invalid_argument if the row fails validation
*/
void GenericDataProcessorPresenter::validateRow(int rowNo) const {
  if (rowNo >= m_model->rowCount())
    throw std::invalid_argument("Invalid row");
}

/**
Takes a user specified run, or list of runs, and returns a pointer to the
desired workspace
@param runStr : The run or list of runs (separated by '+')
@param preprocessor : The pre-processing algorithm acting on this column
@param optionsMap : User-specified options as a map
@throws std::runtime_error if the workspace could not be prepared
@returns a shared pointer to the workspace
*/
Workspace_sptr GenericDataProcessorPresenter::prepareRunWorkspace(
    const std::string &runStr,
    const DataProcessorPreprocessingAlgorithm &preprocessor,
    const std::map<std::string, std::string> &optionsMap) {
  const std::string instrument = m_view->getProcessInstrument();

  std::vector<std::string> runs;
  boost::split(runs, runStr, boost::is_any_of("+,"));

  if (runs.empty())
    throw std::runtime_error("No runs given");

  // Remove leading/trailing whitespace from each run
  for (auto runIt = runs.begin(); runIt != runs.end(); ++runIt)
    boost::trim(*runIt);

  // If we're only given one run, just return that
  if (runs.size() == 1)
    return loadRun(runs[0], instrument, preprocessor.prefix());

  const std::string outputName =
      preprocessor.prefix() + boost::algorithm::join(runs, "_");

  /* Ideally, this should be executed as a child algorithm to keep the ADS tidy,
  * but that doesn't preserve history nicely, so we'll just take care of tidying
  * up in the event of failure.
  */
  IAlgorithm_sptr alg =
      AlgorithmManager::Instance().create(preprocessor.name());
  alg->initialize();
  alg->setProperty(preprocessor.lhsProperty(),
                   loadRun(runs[0], instrument, preprocessor.prefix())->name());
  alg->setProperty(preprocessor.outputProperty(), outputName);

  // Drop the first run from the runs list
  runs.erase(runs.begin());

  try {
    // Iterate through all the remaining runs, adding them to the first run
    for (auto runIt = runs.begin(); runIt != runs.end(); ++runIt) {

      for (auto kvp = optionsMap.begin(); kvp != optionsMap.end(); ++kvp) {
        try {
          alg->setProperty(kvp->first, kvp->second);
        } catch (Mantid::Kernel::Exception::NotFoundError &) {
          // We can't apply this option to this pre-processing alg
          throw;
        }
      }

      alg->setProperty(
          preprocessor.rhsProperty(),
          loadRun(*runIt, instrument, preprocessor.prefix())->name());
      alg->execute();

      if (runIt != --runs.end()) {
        // After the first execution we replace the LHS with the previous output
        alg->setProperty(preprocessor.lhsProperty(), outputName);
      }
    }
  } catch (...) {
    // If we're unable to create the full workspace, discard the partial version
    AnalysisDataService::Instance().remove(outputName);

    // We've tidied up, now re-throw.
    throw;
  }

  return AnalysisDataService::Instance().retrieveWS<Workspace>(outputName);
}

/**
Returns the name of the reduced workspace for a given row
@param row : The row
@param prefix : A prefix to be appended to the generated ws name
@throws std::runtime_error if the workspace could not be prepared
@returns : The name of the workspace
*/
std::string GenericDataProcessorPresenter::getReducedWorkspaceName(
    int row, const std::string &prefix) {

  /* This method calculates, for a given row, the name of the output (processed)
   * workspace. This is done using the white list, which contains information
   * about the columns that should be included to create the ws name. In
   * Reflectometry for example, we want to include values in the 'Run(s)' and
   * 'Transmission Run(s)' columns. We may also use a prefix associated with
   * the column when specified. Finally, to construct the ws name we may also
   * use a 'global' prefix associated with the processing algorithm (for
   * instance 'IvsQ_' in Reflectometry) this is given by the second argument to
   * this method */

  // Temporary vector of strings to construct the name
  std::vector<std::string> names;

  for (int col = 0; col < m_columns; col++) {

    // Do we want to use this column to generate the name of the output ws?
    if (m_whitelist.showPrefix(col)) {

      // Get what's in the column
      const std::string valueStr =
          m_model->data(m_model->index(row, col)).toString().toStdString();

      // If it's not empty, use it
      if (!valueStr.empty()) {

        // But we may have things like '1+2' which we want to replace with '1_2'
        std::vector<std::string> value;
        boost::split(value, valueStr, boost::is_any_of("+"));

        names.push_back(m_whitelist.prefix(col) +
                        boost::algorithm::join(value, "_"));
      }
    }
  } // Columns

  std::string wsname = prefix;
  wsname += boost::algorithm::join(names, "_");

  return wsname;
}

/**
Returns the name of the reduced workspace for a given row
@param rows : The set of rows that belong to a group
@param prefix : A prefix to be appended to the generated ws name
@returns : The name of the workspace
*/
std::string GenericDataProcessorPresenter::getPostprocessedWorkspaceName(
    const std::set<int> &rows, const std::string &prefix) {

  /* This method calculates, for a given set of rows, the name of the output
   * (post-processed) workspace */

  std::vector<std::string> outputNames;

  for (auto &row : rows) {
    outputNames.push_back(getReducedWorkspaceName(row));
  }

  return prefix + boost::join(outputNames, "_");
}

/**
Loads a run from disk or fetches it from the AnalysisDataService
@param run : The name of the run
@param instrument : The instrument the run belongs to
@param prefix : The prefix to be prepended to the run number
@throws std::runtime_error if the run could not be loaded
@returns a shared pointer to the workspace
*/
Workspace_sptr
GenericDataProcessorPresenter::loadRun(const std::string &run,
                                       const std::string &instrument,
                                       const std::string &prefix) {
  // First, let's see if the run given is the name of a workspace in the ADS
  if (AnalysisDataService::Instance().doesExist(run))
    return AnalysisDataService::Instance().retrieveWS<Workspace>(run);
  // Try with prefix
  if (AnalysisDataService::Instance().doesExist(prefix + run))
    return AnalysisDataService::Instance().retrieveWS<Workspace>(prefix + run);

  // Is the run string is numeric
  if (boost::regex_match(run, boost::regex("\\d+"))) {
    std::string wsName;

    // Look for "<run_number>" in the ADS
    wsName = run;
    if (AnalysisDataService::Instance().doesExist(wsName))
      return AnalysisDataService::Instance().retrieveWS<Workspace>(wsName);

    // Look for "<instrument><run_number>" in the ADS
    wsName = instrument + run;
    if (AnalysisDataService::Instance().doesExist(wsName))
      return AnalysisDataService::Instance().retrieveWS<Workspace>(wsName);
  }

  // We'll just have to load it ourselves
  const std::string filename = instrument + run;
  const std::string outputName = prefix + run;
  IAlgorithm_sptr algLoadRun = AlgorithmManager::Instance().create("Load");
  algLoadRun->initialize();
  algLoadRun->setProperty("Filename", filename);
  algLoadRun->setProperty("OutputWorkspace", outputName);
  algLoadRun->execute();

  if (!algLoadRun->isExecuted())
    throw std::runtime_error("Could not open " + filename);

  return AnalysisDataService::Instance().retrieveWS<Workspace>(outputName);
}

/**
Reduce a row
@param rowNo : The row in the model to reduce
@throws std::runtime_error if reduction fails
*/
void GenericDataProcessorPresenter::reduceRow(int rowNo) {

  /* Create the processing algorithm */

  IAlgorithm_sptr alg = AlgorithmManager::Instance().create(m_processor.name());
  alg->initialize();

  /* Read input properties from the table */
  /* excluding 'Group' and 'Options' */

  // Loop over all columns except 'Group' and 'Options'
  for (int i = 0; i < m_columns - 2; i++) {

    // The algorithm's property linked to this column
    auto propertyName = m_whitelist.algPropFromColIndex(i);
    // The column's name
    auto columnName = m_whitelist.colNameFromColIndex(i);

    if (m_preprocessMap.count(columnName)) {
      // This column needs pre-processing

      const std::string runStr =
          m_model->data(m_model->index(rowNo, i)).toString().toStdString();

      if (!runStr.empty()) {

        auto preprocessor = m_preprocessMap[columnName];

        // Read the pre-processing options from the view
        const std::string options =
            m_view->getProcessingOptions(preprocessor.name());
        auto optionsMap = parseKeyValueString(options);
        auto runWS = prepareRunWorkspace(runStr, preprocessor, optionsMap);
        alg->setProperty(propertyName, runWS->name());
      }
    } else {
      // No pre-processing needed, read from the table
      auto propertyValue =
          m_model->data(m_model->index(rowNo, i)).toString().toStdString();
      if (!propertyValue.empty())
        alg->setPropertyValue(propertyName, propertyValue);
    }
  }

  /* Deal with processing instructions specified via the hinting line edit */
  std::string options = m_view->getProcessingOptions(m_processor.name());
  // Parse and set any user-specified options
  auto optionsMap = parseKeyValueString(options);
  for (auto kvp = optionsMap.begin(); kvp != optionsMap.end(); ++kvp) {
    try {
      alg->setProperty(kvp->first, kvp->second);
    } catch (Mantid::Kernel::Exception::NotFoundError &) {
      throw std::runtime_error("Invalid property in options column: " +
                               kvp->first);
    }
  }

  /* Now deal with 'Options' column */
  options = m_model->data(m_model->index(rowNo, m_model->columnCount() - 1))
                .toString()
                .toStdString();
  // Parse and set any user-specified options
  optionsMap = parseKeyValueString(options);
  for (auto kvp = optionsMap.begin(); kvp != optionsMap.end(); ++kvp) {
    try {
      alg->setProperty(kvp->first, kvp->second);
    } catch (Mantid::Kernel::Exception::NotFoundError &) {
      throw std::runtime_error("Invalid property in options column: " +
                               kvp->first);
    }
  }

  /* We need to give a name to the output workspaces */
  for (size_t i = 0; i < m_processor.numberOfOutputProperties(); i++) {
    alg->setProperty(m_processor.outputPropertyName(i),
                     getReducedWorkspaceName(rowNo, m_processor.prefix(i)));
  }

  /* Now run the processing algorithm */
  alg->execute();

  if (alg->isExecuted()) {

    /* The reduction is complete, try to populate the columns */
    for (int i = 0; i < m_columns - 2; i++) {
      if (m_model->data(m_model->index(rowNo, i)).toString().isEmpty()) {

        std::string propValue =
            alg->getPropertyValue(m_whitelist.algPropFromColIndex(i));

        m_model->setData(m_model->index(rowNo, i),
                         QString::fromStdString(propValue));
      }
    }
  }
}

/**
Inserts a new row in the specified location
@param index The index to insert the new row before
*/
void GenericDataProcessorPresenter::insertRow(int index) {
  const int groupId = getUnusedGroup();
  if (!m_model->insertRow(index))
    return;
  // Set the group id of the new row
  // m_columns - 2 is the index of column 'Group'
  m_model->setData(m_model->index(index, m_columns - 2), groupId);
}

/**
Insert a row after the last selected row
*/
void GenericDataProcessorPresenter::appendRow() {
  std::set<int> rows = m_view->getSelectedRows();
  if (rows.empty())
    insertRow(m_model->rowCount());
  else
    insertRow(*rows.rbegin() + 1);
  m_tableDirty = true;
}

/**
Insert a row before the first selected row
*/
void GenericDataProcessorPresenter::prependRow() {
  std::set<int> rows = m_view->getSelectedRows();
  if (rows.empty())
    insertRow(0);
  else
    insertRow(*rows.begin());
  m_tableDirty = true;
}

/**
Get the index of the first blank row, or if none exists, returns -1.
*/
int GenericDataProcessorPresenter::getBlankRow() {
  // Go through every column of every row (except for the scale column) and
  // check if it's blank.
  // If there's a blank row, return it.
  const int rowCount = m_model->rowCount();
  for (int i = 0; i < rowCount; ++i) {
    bool isBlank = true;
    for (int j = 0; j < m_columns; ++j) {
      // Don't bother checking the group column, it'll always have a
      // value.
      if (j == m_columns - 2)
        continue;

      if (!m_model->data(m_model->index(i, j)).toString().isEmpty()) {
        isBlank = false;
        break;
      }
    }

    if (isBlank)
      return i;
  }

  // There are no blank rows
  return -1;
}

/**
Delete row(s) from the model
*/
void GenericDataProcessorPresenter::deleteRow() {
  std::set<int> rows = m_view->getSelectedRows();
  for (auto row = rows.rbegin(); row != rows.rend(); ++row)
    m_model->removeRow(*row);

  m_tableDirty = true;
}

/**
Group rows together
*/
void GenericDataProcessorPresenter::groupRows() {
  const std::set<int> rows = m_view->getSelectedRows();
  // Find the first unused group id, ignoring the selected rows
  const int groupId = getUnusedGroup(rows);

  // Now we just have to set the group id on the selected rows
  for (auto it = rows.begin(); it != rows.end(); ++it)
    m_model->setData(m_model->index(*it, m_columns - 2), groupId);

  m_tableDirty = true;
}

/**
Used by the view to tell the presenter something has changed
*/
void GenericDataProcessorPresenter::notify(DataProcessorPresenter::Flag flag) {
  switch (flag) {
  case DataProcessorPresenter::SaveAsFlag:
    saveTableAs();
    break;
  case DataProcessorPresenter::SaveFlag:
    saveTable();
    break;
  case DataProcessorPresenter::AppendRowFlag:
    appendRow();
    break;
  case DataProcessorPresenter::PrependRowFlag:
    prependRow();
    break;
  case DataProcessorPresenter::DeleteRowFlag:
    deleteRow();
    break;
  case DataProcessorPresenter::ProcessFlag:
    process();
    break;
  case DataProcessorPresenter::GroupRowsFlag:
    groupRows();
    break;
  case DataProcessorPresenter::NewTableFlag:
    newTable();
    break;
  case DataProcessorPresenter::TableUpdatedFlag:
    m_tableDirty = true;
    break;
  case DataProcessorPresenter::ExpandSelectionFlag:
    expandSelection();
    break;
  case DataProcessorPresenter::OptionsDialogFlag:
    showOptionsDialog();
    break;
  case DataProcessorPresenter::ClearSelectedFlag:
    clearSelected();
    break;
  case DataProcessorPresenter::CopySelectedFlag:
    copySelected();
    break;
  case DataProcessorPresenter::CutSelectedFlag:
    cutSelected();
    break;
  case DataProcessorPresenter::PasteSelectedFlag:
    pasteSelected();
    break;
  case DataProcessorPresenter::ImportTableFlag:
    importTable();
    break;
  case DataProcessorPresenter::OpenTableFlag:
    openTable();
    break;
  case DataProcessorPresenter::ExportTableFlag:
    exportTable();
    break;
  case DataProcessorPresenter::PlotRowFlag:
    plotRow();
    break;
  case DataProcessorPresenter::PlotGroupFlag:
    plotGroup();