TimeSeriesProperty.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 "MantidKernel/TimeSeriesProperty.h"
#include "MantidKernel/EmptyValues.h"
#include "MantidKernel/Exception.h"
#include "MantidKernel/Logger.h"
#include "MantidKernel/TimeSplitter.h"
 
#include <json/value.h>
#include <nexus/NeXusFile.hpp>
 
#include <boost/regex.hpp>
#include <numeric>
 
namespace Mantid {
using namespace Types::Core;
namespace Kernel {
namespace {
Logger g_log("TimeSeriesProperty");
} // namespace
 
template <typename TYPE>
TimeSeriesProperty<TYPE>::TimeSeriesProperty(const std::string &name)
    : Property(name, typeid(std::vector<TimeValueUnit<TYPE>>)), m_values(), m_size(), m_propSortedFlag(),
      m_filterApplied() {}
 
template <typename TYPE>
TimeSeriesProperty<TYPE>::TimeSeriesProperty(const std::string &name,
                                             const std::vector<Types::Core::DateAndTime> &times,
                                             const std::vector<TYPE> &values)
    : TimeSeriesProperty(name) {
  addValues(times, values);
}
 
template <typename TYPE> TimeSeriesProperty<TYPE>::~TimeSeriesProperty() = default;
 
template <typename TYPE> TimeSeriesProperty<TYPE> *TimeSeriesProperty<TYPE>::clone() const {
  return new TimeSeriesProperty<TYPE>(*this);
}
 
template <typename TYPE> Property *TimeSeriesProperty<TYPE>::cloneWithTimeShift(const double timeShift) const {
  auto timeSeriesProperty = this->clone();
  auto values = timeSeriesProperty->valuesAsVector();
  auto times = timeSeriesProperty->timesAsVector();
  // Shift the time
  for (auto it = times.begin(); it != times.end(); ++it) {
    // There is a known issue which can cause cloneWithTimeShift to be called
    // with a large (~9e+9 s) shift. Actual shifting is capped to be ~4.6e+19
    // seconds in DateAndTime::operator+=
    (*it) += timeShift;
  }
  timeSeriesProperty->clear();
  timeSeriesProperty->addValues(times, values);
  return timeSeriesProperty;
}
 
template <typename TYPE> std::unique_ptr<TimeSeriesProperty<double>> TimeSeriesProperty<TYPE>::getDerivative() const {
 
  if (this->m_values.size() < 2) {
    throw std::runtime_error("Derivative is not defined for a time-series "
                             "property with less then two values");
  }
 
  this->sortIfNecessary();
  auto it = this->m_values.begin();
  int64_t t0 = it->time().totalNanoseconds();
  TYPE v0 = it->value();
 
  it++;
  auto timeSeriesDeriv = std::make_unique<TimeSeriesProperty<double>>(this->name() + "_derivative");
  timeSeriesDeriv->reserve(this->m_values.size() - 1);
  for (; it != m_values.end(); it++) {
    TYPE v1 = it->value();
    int64_t t1 = it->time().totalNanoseconds();
    if (t1 != t0) {
      double deriv = 1.e+9 * (double(v1 - v0) / double(t1 - t0));
      auto tm = static_cast<int64_t>((t1 + t0) / 2);
      timeSeriesDeriv->addValue(Types::Core::DateAndTime(tm), deriv);
    }
    t0 = t1;
    v0 = v1;
  }
  return timeSeriesDeriv;
}
template <> std::unique_ptr<TimeSeriesProperty<double>> TimeSeriesProperty<std::string>::getDerivative() const {
  throw std::runtime_error("Time series property derivative is not defined for strings");
}
 
template <typename TYPE> size_t TimeSeriesProperty<TYPE>::getMemorySize() const {
  // Rough estimate
  return m_values.size() * (sizeof(TYPE) + sizeof(DateAndTime));
}
 
template <typename TYPE> TimeSeriesProperty<TYPE> &TimeSeriesProperty<TYPE>::merge(Property *rhs) {
  return operator+=(rhs);
}
 
template <typename TYPE> TimeSeriesProperty<TYPE> &TimeSeriesProperty<TYPE>::operator+=(Property const *right) {
  auto const *rhs = dynamic_cast<TimeSeriesProperty<TYPE> const *>(right);
 
  if (rhs) {
    if (this->operator!=(*rhs)) {
      m_values.insert(m_values.end(), rhs->m_values.begin(), rhs->m_values.end());
      m_propSortedFlag = TimeSeriesSortStatus::TSUNKNOWN;
    } else {
      // Do nothing if appending yourself to yourself. The net result would be
      // the same anyway
      ;
    }
 
    // Count the REAL size.
    m_size = static_cast<int>(m_values.size());
 
  } else
    g_log.warning() << "TimeSeriesProperty " << this->name()
                    << " could not be added to another property of the same "
                       "name but incompatible type.\n";
 
  return *this;
}
 
template <typename TYPE> bool TimeSeriesProperty<TYPE>::operator==(const TimeSeriesProperty<TYPE> &right) const {
  sortIfNecessary();
 
  if (this->name() != right.name()) // should this be done?
  {
    return false;
  }
 
  if (this->m_size != right.m_size) {
    return false;
  }
 
  if (this->realSize() != right.realSize()) {
    return false;
  } else {
    const std::vector<DateAndTime> lhsTimes = this->timesAsVector();
    const std::vector<DateAndTime> rhsTimes = right.timesAsVector();
    if (!std::equal(lhsTimes.begin(), lhsTimes.end(), rhsTimes.begin())) {
      return false;
    }
 
    const std::vector<TYPE> lhsValues = this->valuesAsVector();
    const std::vector<TYPE> rhsValues = right.valuesAsVector();
    if (!std::equal(lhsValues.begin(), lhsValues.end(), rhsValues.begin())) {
      return false;
    }
  }
 
  return true;
}
 
template <typename TYPE> bool TimeSeriesProperty<TYPE>::operator==(const Property &right) const {
  auto rhs_tsp = dynamic_cast<const TimeSeriesProperty<TYPE> *>(&right);
  if (!rhs_tsp)
    return false;
  return this->operator==(*rhs_tsp);
}
 
template <typename TYPE> bool TimeSeriesProperty<TYPE>::operator!=(const TimeSeriesProperty<TYPE> &right) const {
  return !(*this == right);
}
 
template <typename TYPE> bool TimeSeriesProperty<TYPE>::operator!=(const Property &right) const {
  return !(*this == right);
}
 
template <typename TYPE> void TimeSeriesProperty<TYPE>::setName(const std::string &name) { m_name = name; }
 
template <typename TYPE>
void TimeSeriesProperty<TYPE>::filterByTime(const Types::Core::DateAndTime &start,
                                            const Types::Core::DateAndTime &stop) {
  // 0. Sort
  sortIfNecessary();
 
  // 1. Do nothing for single (constant) value
  if (m_values.size() <= 1)
    return;
 
  typename std::vector<TimeValueUnit<TYPE>>::iterator iterhead, iterend;
 
  // 2. Determine index for start and remove  Note erase is [...)
  int istart = this->findIndex(start);
  if (istart >= 0 && static_cast<size_t>(istart) < m_values.size()) {
    // "start time" is behind time-series's starting time
    iterhead = m_values.begin() + istart;
 
    // False - The filter time is on the mark.  Erase [begin(),  istart)
    // True - The filter time is larger than T[istart]. Erase[begin(), istart)
    // ...
    //       filter start(time) and move istart to filter startime
    bool useprefiltertime = !(m_values[istart].time() == start);
 
    // Remove the series
    m_values.erase(m_values.begin(), iterhead);
 
    if (useprefiltertime) {
      m_values[0].setTime(start);
    }
  } else {
    // "start time" is before/after time-series's starting time: do nothing
    ;
  }
 
  // 3. Determine index for end and remove  Note erase is [...)
  int iend = this->findIndex(stop);
  if (static_cast<size_t>(iend) < m_values.size()) {
    if (m_values[iend].time() == stop) {
      // Filter stop is on a log.  Delete that log
      iterend = m_values.begin() + iend;
    } else {
      // Filter stop is behind iend. Keep iend
      iterend = m_values.begin() + iend + 1;
    }
    // Delete from [iend to mp.end)
    m_values.erase(iterend, m_values.end());
  }
 
  // 4. Make size consistent
  m_size = static_cast<int>(m_values.size());
}
 
template <typename TYPE>
void TimeSeriesProperty<TYPE>::filterByTimes(const std::vector<SplittingInterval> &splittervec) {
  // 1. Sort
  sortIfNecessary();
 
  // 2. Return for single value
  if (m_values.size() <= 1) {
    return;
  }
 
  // 3. Prepare a copy
  std::vector<TimeValueUnit<TYPE>> mp_copy;
 
  g_log.debug() << "DB541  mp_copy Size = " << mp_copy.size() << "  Original MP Size = " << m_values.size() << "\n";
 
  // 4. Create new
  for (const auto &splitter : splittervec) {
    Types::Core::DateAndTime t_start = splitter.start();
    Types::Core::DateAndTime t_stop = splitter.stop();
 
    int tstartindex = findIndex(t_start);
    if (tstartindex < 0) {
      // The splitter is not well defined, and use the first
      tstartindex = 0;
    } else if (tstartindex >= int(m_values.size())) {
      // The splitter is not well defined, adn use the last
      tstartindex = int(m_values.size()) - 1;
    }
 
    int tstopindex = findIndex(t_stop);
 
    if (tstopindex < 0) {
      tstopindex = 0;
    } else if (tstopindex >= int(m_values.size())) {
      tstopindex = int(m_values.size()) - 1;
    } else {
      if (t_stop == m_values[size_t(tstopindex)].time() && size_t(tstopindex) > 0) {
        tstopindex--;
      }
    }
 
    /* Check */
    if (tstartindex < 0 || tstopindex >= int(m_values.size())) {
      g_log.warning() << "Memory Leak In SplitbyTime!\n";
    }
 
    if (tstartindex == tstopindex) {
      TimeValueUnit<TYPE> temp(t_start, m_values[tstartindex].value());
      mp_copy.emplace_back(temp);
    } else {
      mp_copy.emplace_back(t_start, m_values[tstartindex].value());
      for (auto im = size_t(tstartindex + 1); im <= size_t(tstopindex); ++im) {
        mp_copy.emplace_back(m_values[im].time(), m_values[im].value());
      }
    }
  } // ENDFOR
 
  g_log.debug() << "DB530  Filtered Log Size = " << mp_copy.size() << "  Original Log Size = " << m_values.size()
                << "\n";
 
  // 5. Clear
  m_values.clear();
  m_values = mp_copy;
  mp_copy.clear();
 
  m_size = static_cast<int>(m_values.size());
}
 
template <typename TYPE>
void TimeSeriesProperty<TYPE>::splitByTime(std::vector<SplittingInterval> &splitter, std::vector<Property *> outputs,
                                           bool isPeriodic) const {
  // 0. Sort if necessary
  sortIfNecessary();
 
  if (outputs.empty())
    return;
 
  std::vector<TimeSeriesProperty<TYPE> *> outputs_tsp;
 
  size_t numOutputs = outputs.size();
  // 1. Clear the outputs before you start
  for (size_t i = 0; i < numOutputs; i++) {
    auto *myOutput = dynamic_cast<TimeSeriesProperty<TYPE> *>(outputs[i]);
    if (myOutput) {
      outputs_tsp.emplace_back(myOutput);
      if (this->m_values.size() == 1) {
        // Special case for TSP with a single entry = just copy.
        myOutput->m_values = this->m_values;
        myOutput->m_size = 1;
      } else {
        myOutput->m_values.clear();
        myOutput->m_size = 0;
      }
    } else {
      outputs_tsp.emplace_back(nullptr);
    }
  }
 
  // 2. Special case for TSP with a single entry = just copy.
  if (this->m_values.size() == 1)
    return;
 
  // 3. We will be iterating through all the entries in the the map/vector
  size_t i_property = 0;
 
  //    And at the same time, iterate through the splitter
  auto itspl = splitter.begin();
 
  size_t counter = 0;
  g_log.debug() << "[DB] Number of time series entries = " << m_values.size()
                << ", Number of splitters = " << splitter.size() << "\n";
  while (itspl != splitter.end() && i_property < m_values.size()) {
    // Get the splitting interval times and destination
    DateAndTime start = itspl->start();
    DateAndTime stop = itspl->stop();
 
    int output_index = itspl->index();
    // output workspace index is out of range. go to the next splitter
    if (output_index < 0 || output_index >= static_cast<int>(numOutputs))
      continue;
 
    TimeSeriesProperty<TYPE> *myOutput = outputs_tsp[output_index];
    // skip if the input property is of wrong type
    if (!myOutput) {
      ++itspl;
      ++counter;
      continue;
    }
 
    // Skip the events before the start of the time
    while (i_property < m_values.size() && m_values[i_property].time() < start)
      ++i_property;
 
    if (i_property == m_values.size()) {
      // i_property is out of the range. Then use the last entry
      myOutput->addValue(m_values[i_property - 1].time(), m_values[i_property - 1].value());
      break;
    }
 
    // The current entry is within an interval. Record them until out
    if (m_values[i_property].time() > start && i_property > 0 && !isPeriodic) {
      // Record the previous oneif this property is not exactly on start time
      //   and this entry is not recorded
      size_t i_prev = i_property - 1;
      if (myOutput->size() == 0 || m_values[i_prev].time() != myOutput->lastTime())
        myOutput->addValue(m_values[i_prev].time(), m_values[i_prev].value());
    }
 
    // Loop through all the entries until out.
    while (i_property < m_values.size() && m_values[i_property].time() < stop) {
 
      // Copy the log out to the output
      myOutput->addValue(m_values[i_property].time(), m_values[i_property].value());
      ++i_property;
    }
 
    // Go to the next interval
    ++itspl;
    ++counter;
  } // Looping through entries in the splitter vector
 
  // Make sure all entries have the correct size recorded in m_size.
  for (std::size_t i = 0; i < numOutputs; i++) {
    auto *myOutput = dynamic_cast<TimeSeriesProperty<TYPE> *>(outputs[i]);
    if (myOutput) {
      myOutput->m_size = myOutput->realSize();
    }
  }
}
 
template <typename TYPE>
void TimeSeriesProperty<TYPE>::splitByTimeVector(const std::vector<DateAndTime> &timeToFilterTo,
                                                 const std::vector<int> &inputWorkspaceIndicies,
                                                 const std::vector<TimeSeriesProperty *> &output) {
 
  // check inputs
  if (timeToFilterTo.size() != inputWorkspaceIndicies.size() + 1) {
    throw std::runtime_error("Input time vector's size does not match(one more larger than) target "
                             "workspace index vector's size inputWorkspaceIndicies.size() \n");
  }
 
  // return if the output vector TimeSeriesProperties is not defined
  if (output.empty())
    return;
 
  sortIfNecessary();
 
  // work on m_values, m_size, and m_time
  auto const currentTimes = timesAsVector();
  auto const currentValues = valuesAsVector();
  size_t index_splitter = 0;
 
  // move splitter index such that the first entry of TSP is before the stop
  // time of a splitter
  DateAndTime firstPropTime = currentTimes[0];
  auto firstFilterTime = std::lower_bound(timeToFilterTo.begin(), timeToFilterTo.end(), firstPropTime);
  if (firstFilterTime == timeToFilterTo.end()) {
    // do nothing as the first TimeSeriesProperty entry's time is before any
    // splitters
    return;
  } else if (firstFilterTime != timeToFilterTo.begin()) {
    // calculate the splitter's index (now we check the stop time)
    index_splitter = firstFilterTime - timeToFilterTo.begin() - 1;
  }
 
  DateAndTime filterStartTime = timeToFilterTo[index_splitter];
  DateAndTime filterEndTime;
 
  // move along the entries to find the entry inside the current splitter
  auto firstEntryInSplitter = std::lower_bound(currentTimes.begin(), currentTimes.end(), filterStartTime);
  if (firstEntryInSplitter == currentTimes.end()) {
    // the first splitter's start time is LATER than the last TSP entry, then
    // there won't be any
    // TSP entry to be split into any wsIndex splitter.
    DateAndTime last_entry_time = this->lastTime();
    TYPE last_entry_value = this->lastValue();
    for (auto &i : output) {
      i->addValue(last_entry_time, last_entry_value);
    }
    return;
  }
 
  // first splitter start time is between firstEntryInSplitter and the one
  // before it. so the index for firstEntryInSplitter is the first TSP entry
  // in the splitter
  size_t timeIndex = firstEntryInSplitter - currentTimes.begin();
  firstPropTime = *firstEntryInSplitter;
 
  for (; index_splitter < timeToFilterTo.size() - 1; ++index_splitter) {
    int wsIndex = inputWorkspaceIndicies[index_splitter];
 
    filterStartTime = timeToFilterTo[index_splitter];
    filterEndTime = timeToFilterTo[index_splitter + 1];
 
    // get the first entry index (overlap)
    if (timeIndex > 0)
      --timeIndex;
 
    // add the continuous entries to same wsIndex time series property
    const size_t numEntries = currentTimes.size();
 
    // Add properties to the current wsIndex.
    if (timeIndex >= numEntries) {
      // We have run out of TSP entries, so use the last TSP value
      // for all remaining outputs
      auto currentTime = currentTimes.back();
      if (output[wsIndex]->size() == 0 || output[wsIndex]->lastTime() != currentTime) {
        output[wsIndex]->addValue(currentTime, currentValues.back());
      }
    } else {
      // Add TSP values until we run out or go past the current filter
      // end time.
      for (; timeIndex < numEntries; ++timeIndex) {
        auto currentTime = currentTimes[timeIndex];
        if (output[wsIndex]->size() == 0 || output[wsIndex]->lastTime() < currentTime) {
          // avoid to add duplicate entry
          output[wsIndex]->addValue(currentTime, currentValues[timeIndex]);
        }
        if (currentTime > filterEndTime)
          break;
      }
    }
  }
 
  // Add a debugging check such that there won't be any time entry with zero log
  for (size_t i = 0; i < output.size(); ++i) {
    if (output[i]->size() == 0) {
      std::stringstream errss;
      errss << "entry " << m_name << " has 0 size, whose first entry is at " << this->firstTime().toSimpleString();
      g_log.warning(errss.str());
    }
  }
}
 
// The makeFilterByValue & expandFilterToRange methods generate a bunch of
// warnings when the template type is the wider integer types
// (when it's being assigned back to a double such as in a call to minValue or
// firstValue)
// However, in reality these methods are only used for TYPE=int or double (they
// are only called from FilterByLogValue) so suppress the warnings
#ifdef _WIN32
#pragma warning(push)
#pragma warning(disable : 4244)
#pragma warning(disable : 4804) // This one comes about for TYPE=bool - again
                                // the method is never called for this type
#endif
#if defined(__GNUC__) && !(defined(__INTEL_COMPILER))
#pragma GCC diagnostic ignored "-Wconversion"
#endif
 
template <typename TYPE>
void TimeSeriesProperty<TYPE>::makeFilterByValue(std::vector<SplittingInterval> &split, double min, double max,
                                                 double TimeTolerance, bool centre) const {
  const bool emptyMin = (min == EMPTY_DBL());
  const bool emptyMax = (max == EMPTY_DBL());
 
  if (!emptyMin && !emptyMax && max < min) {
    std::stringstream ss;
    ss << "TimeSeriesProperty::makeFilterByValue: 'max' argument must be "
          "greater than 'min' "
       << "(got min=" << min << " max=" << max << ")";
    throw std::invalid_argument(ss.str());
  }
 
  // If min or max were unset ("empty") in the algorithm, set to the min or max
  // value of the log
  if (emptyMin)
    min = static_cast<double>(minValue());
  if (emptyMax)
    max = static_cast<double>(maxValue());
 
  // Make sure the splitter starts out empty
  split.clear();
 
  // Do nothing if the log is empty.
  if (m_values.empty())
    return;
 
  // 1. Sort
  sortIfNecessary();
 
  // 2. Do the rest
  bool lastGood(false);
  time_duration tol = DateAndTime::durationFromSeconds(TimeTolerance);
  int numgood = 0;
  DateAndTime t;
  DateAndTime start, stop;
 
  for (size_t i = 0; i < m_values.size(); ++i) {
    const DateAndTime lastTime = t;
    // The new entry
    t = m_values[i].time();
    TYPE val = m_values[i].value();
 
    // A good value?
    const bool isGood = ((val >= min) && (val <= max));
    if (isGood)
      numgood++;
 
    if (isGood != lastGood) {
      // We switched from bad to good or good to bad
 
      if (isGood) {
        // Start of a good section. Subtract tolerance from the time if
        // boundaries are centred.
        start = centre ? t - tol : t;
      } else {
        // End of the good section. Add tolerance to the LAST GOOD time if
        // boundaries are centred.
        // Otherwise, use the first 'bad' time.
        stop = centre ? lastTime + tol : t;
        split.emplace_back(start, stop, 0);
        // Reset the number of good ones, for next time
        numgood = 0;
      }
      lastGood = isGood;
    }
  }
 
  if (numgood > 0) {
    // The log ended on "good" so we need to close it using the last time we
    // found
    stop = t + tol;
    split.emplace_back(start, stop, 0);
  }
}
 
template <>
void TimeSeriesProperty<std::string>::makeFilterByValue(std::vector<SplittingInterval> & /*split*/, double /*min*/,
                                                        double /*max*/, double /*TimeTolerance*/,
                                                        bool /*centre*/) const {
  throw Exception::NotImplementedError("TimeSeriesProperty::makeFilterByValue "
                                       "is not implemented for string "
                                       "properties");
}
 
template <typename TYPE>
void TimeSeriesProperty<TYPE>::expandFilterToRange(std::vector<SplittingInterval> &split, double min, double max,
                                                   const TimeInterval &range) const {
  const bool emptyMin = (min == EMPTY_DBL());
  const bool emptyMax = (max == EMPTY_DBL());
 
  if (!emptyMin && !emptyMax && max < min) {
    std::stringstream ss;
    ss << "TimeSeriesProperty::expandFilterToRange: 'max' argument must be "
          "greater than 'min' "
       << "(got min=" << min << " max=" << max << ")";
    throw std::invalid_argument(ss.str());
  }
 
  // If min or max were unset ("empty") in the algorithm, set to the min or max
  // value of the log
  if (emptyMin)
    min = static_cast<double>(minValue());
  if (emptyMax)
    max = static_cast<double>(maxValue());
 
  // Assume everything before the 1st value is constant
  double val = static_cast<double>(firstValue());
  if ((val >= min) && (val <= max)) {
    TimeSplitterType extraFilter;
    extraFilter.emplace_back(range.begin(), firstTime(), 0);
    // Include everything from the start of the run to the first time measured
    // (which may be a null time interval; this'll be ignored)
    split = split | extraFilter;
  }
 
  // Assume everything after the LAST value is constant
  val = static_cast<double>(lastValue());
  if ((val >= min) && (val <= max)) {
    TimeSplitterType extraFilter;
    extraFilter.emplace_back(lastTime(), range.end(), 0);
    // Include everything from the start of the run to the first time measured
    // (which may be a null time interval; this'll be ignored)
    split = split | extraFilter;
  }
}
 
template <>
void TimeSeriesProperty<std::string>::expandFilterToRange(std::vector<SplittingInterval> & /*split*/, double /*min*/,
                                                          double /*max*/, const TimeInterval & /*range*/) const {
  throw Exception::NotImplementedError("TimeSeriesProperty::makeFilterByValue "
                                       "is not implemented for string "
                                       "properties");
}
 
template <typename TYPE> double TimeSeriesProperty<TYPE>::timeAverageValue() const {
  double retVal = 0.0;
  try {
    const auto &filter = getSplittingIntervals();
    retVal = this->averageValueInFilter(filter);
  } catch (std::exception &) {
    // just return nan
    retVal = std::numeric_limits<double>::quiet_NaN();
  }
  return retVal;
}
 
template <typename TYPE>
double TimeSeriesProperty<TYPE>::averageValueInFilter(const std::vector<SplittingInterval> &filter) const {
  // TODO: Consider logs that aren't giving starting values.
 
  // First of all, if the log or the filter is empty, return NaN
  if (realSize() == 0 || filter.empty()) {
    return std::numeric_limits<double>::quiet_NaN();
  }
 
  // If there's just a single value in the log, return that.
  if (realSize() == 1) {
    return static_cast<double>(m_values.front().value());
  }
 
  sortIfNecessary();
 
  double numerator(0.0), totalTime(0.0);
  // Loop through the filter ranges
  for (const auto &time : filter) {
    // Calculate the total time duration (in seconds) within by the filter
    totalTime += time.duration();
 
    // Get the log value and index at the start time of the filter
    int index;
    double value = static_cast<double>(getSingleValue(time.start(), index));
    DateAndTime startTime = time.start();
 
    while (index < realSize() - 1 && m_values[index + 1].time() < time.stop()) {
      ++index;
      numerator += DateAndTime::secondsFromDuration(m_values[index].time() - startTime) * value;
      startTime = m_values[index].time();
      value = static_cast<double>(m_values[index].value());
    }
 
    // Now close off with the end of the current filter range
    numerator += DateAndTime::secondsFromDuration(time.stop() - startTime) * value;
  }
 
  // 'Normalise' by the total time
  return numerator / totalTime;
}
 
template <> double TimeSeriesProperty<std::string>::averageValueInFilter(const TimeSplitterType & /*filter*/) const {
  throw Exception::NotImplementedError("TimeSeriesProperty::"
                                       "averageValueInFilter is not "
                                       "implemented for string properties");
}
 
template <typename TYPE> std::pair<double, double> TimeSeriesProperty<TYPE>::timeAverageValueAndStdDev() const {
  std::pair<double, double> retVal{0., 0.}; // mean and stddev
  try {
    const auto &filter = getSplittingIntervals();
    retVal = this->averageAndStdDevInFilter(filter);
  } catch (std::exception &) {
    retVal.first = std::numeric_limits<double>::quiet_NaN();
    retVal.second = std::numeric_limits<double>::quiet_NaN();
  }
  return retVal;
}
 
template <typename TYPE>
std::pair<double, double>
TimeSeriesProperty<TYPE>::averageAndStdDevInFilter(const std::vector<SplittingInterval> &filter) const {
  // the mean to calculate the standard deviation about
  // this will sort the log as necessary as well
  const double mean = this->averageValueInFilter(filter);
 
  // First of all, if the log or the filter is empty or is a single value,
  // return NaN for the uncertainty
  if (realSize() <= 1 || filter.empty()) {
    return std::pair<double, double>{mean, std::numeric_limits<double>::quiet_NaN()};
  }
 
  double numerator(0.0), totalTime(0.0);
  // Loop through the filter ranges
  for (const auto &time : filter) {
    // Calculate the total time duration (in seconds) within by the filter
    totalTime += time.duration();
 
    // Get the log value and index at the start time of the filter
    int index;
    double value = static_cast<double>(getSingleValue(time.start(), index));
    double valuestddev = (value - mean) * (value - mean);
    DateAndTime startTime = time.start();
 
    while (index < realSize() - 1 && m_values[index + 1].time() < time.stop()) {
      ++index;
 
      numerator += DateAndTime::secondsFromDuration(m_values[index].time() - startTime) * valuestddev;
      startTime = m_values[index].time();
      value = static_cast<double>(m_values[index].value());
      valuestddev = (value - mean) * (value - mean);
    }
 
    // Now close off with the end of the current filter range
    numerator += DateAndTime::secondsFromDuration(time.stop() - startTime) * valuestddev;
  }
 
  // Normalise by the total time
  return std::pair<double, double>{mean, std::sqrt(numerator / totalTime)};
}
 
template <>
std::pair<double, double>
TimeSeriesProperty<std::string>::averageAndStdDevInFilter(const TimeSplitterType & /*filter*/) const {
  throw Exception::NotImplementedError("TimeSeriesProperty::"
                                       "averageAndStdDevInFilter is not "
                                       "implemented for string properties");
}
 
// Re-enable the warnings disabled before makeFilterByValue
#ifdef _WIN32
#pragma warning(pop)
#endif
#if defined(__GNUC__) && !(defined(__INTEL_COMPILER))
#pragma GCC diagnostic warning "-Wconversion"
#endif
 
template <typename TYPE> std::map<DateAndTime, TYPE> TimeSeriesProperty<TYPE>::valueAsCorrectMap() const {
  // 1. Sort if necessary
  sortIfNecessary();
 
  // 2. Data Strcture
  std::map<DateAndTime, TYPE> asMap;
 
  if (!m_values.empty()) {
    for (size_t i = 0; i < m_values.size(); i++)
      asMap[m_values[i].time()] = m_values[i].value();
  }
 
  return asMap;
}
 
template <typename TYPE> std::vector<TYPE> TimeSeriesProperty<TYPE>::valuesAsVector() const {
  sortIfNecessary();
 
  std::vector<TYPE> out;
  out.reserve(m_values.size());
 
  for (size_t i = 0; i < m_values.size(); i++)
    out.emplace_back(m_values[i].value());
 
  return out;
}
 
template <typename TYPE> std::multimap<DateAndTime, TYPE> TimeSeriesProperty<TYPE>::valueAsMultiMap() const {
  std::multimap<DateAndTime, TYPE> asMultiMap;
 
  if (!m_values.empty()) {
    for (size_t i = 0; i < m_values.size(); i++)
      asMultiMap.insert(std::make_pair(m_values[i].time(), m_values[i].value()));
  }
 
  return asMultiMap;
}
 
template <typename TYPE> std::vector<DateAndTime> TimeSeriesProperty<TYPE>::timesAsVector() const {
  sortIfNecessary();
 
  std::vector<DateAndTime> out;
  out.reserve(m_values.size());
 
  for (size_t i = 0; i < m_values.size(); i++) {
    out.emplace_back(m_values[i].time());
  }
 
  return out;
}
 
template <typename TYPE> std::vector<DateAndTime> TimeSeriesProperty<TYPE>::filteredTimesAsVector() const {
  if (m_filter.empty()) {
    return this->timesAsVector(); // no filtering to do
  }
  if (!m_filterApplied) {
    applyFilter();
  }
  sortIfNecessary();
 
  std::vector<DateAndTime> out;
 
  for (const auto &value : m_values) {
    if (isTimeFiltered(value.time())) {
      out.emplace_back(value.time());
    }
  }
 
  return out;
}
 
template <typename TYPE> std::vector<double> TimeSeriesProperty<TYPE>::timesAsVectorSeconds() const {
  // 1. Sort if necessary
  sortIfNecessary();
 
  // 2. Output data structure
  std::vector<double> out;
  out.reserve(m_values.size());
 
  Types::Core::DateAndTime start = m_values[0].time();
  for (size_t i = 0; i < m_values.size(); i++) {
    out.emplace_back(DateAndTime::secondsFromDuration(m_values[i].time() - start));
  }
 
  return out;
}
 
template <typename TYPE>
void TimeSeriesProperty<TYPE>::addValue(const Types::Core::DateAndTime &time, const TYPE &value) {
  TimeValueUnit<TYPE> newvalue(time, value);
  // Add the value to the back of the vector
  m_values.emplace_back(newvalue);
  // Increment the separate record of the property's size
  m_size++;
 
  // Toggle the sorted flag if necessary
  // (i.e. if the flag says we're sorted and the added time is before the prior
  // last time)
  if (m_size == 1) {
    // First item, must be sorted.
    m_propSortedFlag = TimeSeriesSortStatus::TSSORTED;
  } else if (m_propSortedFlag == TimeSeriesSortStatus::TSUNKNOWN && m_values.back() < *(m_values.rbegin() + 1)) {
    // Previously unknown and still unknown
    m_propSortedFlag = TimeSeriesSortStatus::TSUNSORTED;
  } else if (m_propSortedFlag == TimeSeriesSortStatus::TSSORTED && m_values.back() < *(m_values.rbegin() + 1)) {
    // Previously sorted but last added is not in order
    m_propSortedFlag = TimeSeriesSortStatus::TSUNSORTED;
  }
 
  m_filterApplied = false;
}
 
template <typename TYPE> void TimeSeriesProperty<TYPE>::addValue(const std::string &time, const TYPE &value) {
  return addValue(Types::Core::DateAndTime(time), value);
}
 
template <typename TYPE> void TimeSeriesProperty<TYPE>::addValue(const std::time_t &time, const TYPE &value) {
  Types::Core::DateAndTime dt;
  dt.set_from_time_t(time);
  return addValue(dt, value);
}
 
template <typename TYPE>
void TimeSeriesProperty<TYPE>::addValues(const std::vector<Types::Core::DateAndTime> &times,
                                         const std::vector<TYPE> &values) {
  size_t length = std::min(times.size(), values.size());
  m_size += static_cast<int>(length);
  for (size_t i = 0; i < length; ++i) {
    m_values.emplace_back(times[i], values[i]);
  }
 
  if (!values.empty())
    m_propSortedFlag = TimeSeriesSortStatus::TSUNKNOWN;
}
 
template <typename TYPE>
void TimeSeriesProperty<TYPE>::replaceValues(const std::vector<Types::Core::DateAndTime> &times,
                                             const std::vector<TYPE> &values) {
  clear();
  addValues(times, values);
}
 
template <typename TYPE> DateAndTime TimeSeriesProperty<TYPE>::lastTime() const {
  if (m_values.empty()) {
    const std::string error("lastTime(): TimeSeriesProperty '" + name() + "' is empty");
    g_log.debug(error);
    throw std::runtime_error(error);
  }
 
  sortIfNecessary();
 
  return m_values.rbegin()->time();
}
 
template <typename TYPE> TYPE TimeSeriesProperty<TYPE>::firstValue() const {
  if (m_values.empty()) {
    const std::string error("firstValue(): TimeSeriesProperty '" + name() + "' is empty");
    g_log.debug(error);
    throw std::runtime_error(error);
  }
 
  sortIfNecessary();
 
  return m_values[0].value();
}
 
template <typename TYPE> DateAndTime TimeSeriesProperty<TYPE>::firstTime() const {
  if (m_values.empty()) {
    const std::string error("firstTime(): TimeSeriesProperty '" + name() + "' is empty");
    g_log.debug(error);
    throw std::runtime_error(error);
  }
 
  sortIfNecessary();
 
  return m_values[0].time();
}
 
template <typename TYPE> TYPE TimeSeriesProperty<TYPE>::lastValue() const {
  if (m_values.empty()) {
    const std::string error("lastValue(): TimeSeriesProperty '" + name() + "' is empty");
    g_log.debug(error);
    throw std::runtime_error(error);
  }
 
  sortIfNecessary();
 
  return m_values.rbegin()->value();
}
 
template <typename TYPE> TYPE TimeSeriesProperty<TYPE>::minValue() const {
  return std::min_element(m_values.begin(), m_values.end(), TimeValueUnit<TYPE>::valueCmp)->value();
}
 
template <typename TYPE> TYPE TimeSeriesProperty<TYPE>::maxValue() const {
  return std::max_element(m_values.begin(), m_values.end(), TimeValueUnit<TYPE>::valueCmp)->value();
}
 
template <typename TYPE> double TimeSeriesProperty<TYPE>::mean() const {
  Mantid::Kernel::Statistics raw_stats =
      Mantid::Kernel::getStatistics(this->filteredValuesAsVector(), StatOptions::Mean);
  return raw_stats.mean;
}
 
template <typename TYPE> int TimeSeriesProperty<TYPE>::size() const { return m_size; }
 
template <typename TYPE> int TimeSeriesProperty<TYPE>::realSize() const { return static_cast<int>(m_values.size()); }
 
/*
 * Get the time series property as a string of 'time  value'
 * @return time series property as a string
 */
template <typename TYPE> std::string TimeSeriesProperty<TYPE>::value() const {
  sortIfNecessary();
 
  std::stringstream ins;
  for (size_t i = 0; i < m_values.size(); i++) {
    try {
      ins << m_values[i].time().toSimpleString();
      ins << "  " << m_values[i].value() << "\n";
    } catch (...) {
      // Some kind of error; for example, invalid year, can occur when
      // converting boost time.
      ins << "Error Error"
          << "\n";
    }
  }
 
  return ins.str();
}
 
template <typename TYPE> std::vector<std::string> TimeSeriesProperty<TYPE>::time_tValue() const {
  sortIfNecessary();
 
  std::vector<std::string> values;
  values.reserve(m_values.size());
 
  for (size_t i = 0; i < m_values.size(); i++) {
    std::stringstream line;
    line << m_values[i].time().toSimpleString() << " " << m_values[i].value();
    values.emplace_back(line.str());
  }
 
  return values;
}
 
template <typename TYPE> std::map<DateAndTime, TYPE> TimeSeriesProperty<TYPE>::valueAsMap() const {
  // 1. Sort if necessary
  sortIfNecessary();
 
  // 2. Build map
 
  std::map<DateAndTime, TYPE> asMap;
  if (m_values.empty())
    return asMap;
 
  TYPE d = m_values[0].value();
  asMap[m_values[0].time()] = d;
 
  for (size_t i = 1; i < m_values.size(); i++) {
    if (m_values[i].value() != d) {
      // Only put entry with different value from last entry to map
      asMap[m_values[i].time()] = m_values[i].value();
      d = m_values[i].value();
    }
  }
  return asMap;
}
 
template <typename TYPE> std::string TimeSeriesProperty<TYPE>::setValue(const std::string & /*unused*/) {
  throw Exception::NotImplementedError("TimeSeriesProperty<TYPE>::setValue - "
                                       "Cannot extract TimeSeries from a "
                                       "std::string");
}
 
template <typename TYPE> std::string TimeSeriesProperty<TYPE>::setValueFromJson(const Json::Value & /*unused*/) {
  throw Exception::NotImplementedError("TimeSeriesProperty<TYPE>::setValue - "
                                       "Cannot extract TimeSeries from a "
                                       "Json::Value");
}
 
template <typename TYPE>
std::string TimeSeriesProperty<TYPE>::setDataItem(const std::shared_ptr<DataItem> & /*unused*/) {
  throw Exception::NotImplementedError("TimeSeriesProperty<TYPE>::setValue - "
                                       "Cannot extract TimeSeries from "
                                       "DataItem");
}
 
template <typename TYPE> void TimeSeriesProperty<TYPE>::clear() {
  m_size = 0;
  m_values.clear();
 
  m_propSortedFlag = TimeSeriesSortStatus::TSSORTED;
  m_filterApplied = false;
}
 
template <typename TYPE> void TimeSeriesProperty<TYPE>::clearOutdated() {
  if (realSize() > 1) {
    auto lastValue = m_values.back();
    clear();
    m_values.emplace_back(lastValue);
    m_size = 1;
  }
}
 
//--------------------------------------------------------------------------------------------
template <typename TYPE>
void TimeSeriesProperty<TYPE>::create(const Types::Core::DateAndTime &start_time, const std::vector<double> &time_sec,
                                      const std::vector<TYPE> &new_values) {
  if (time_sec.size() != new_values.size()) {
    std::stringstream msg;
    msg << "TimeSeriesProperty \"" << name() << "\" create: mismatched size "
        << "for the time and values vectors.";
    throw std::invalid_argument(msg.str());
  }
 
  // Make the times(as seconds) into a vector of DateAndTime in one go.
  std::vector<DateAndTime> times;
  DateAndTime::createVector(start_time, time_sec, times);
 
  this->create(times, new_values);
}
 
//--------------------------------------------------------------------------------------------
template <typename TYPE>
void TimeSeriesProperty<TYPE>::create(const std::vector<Types::Core::DateAndTime> &new_times,
                                      const std::vector<TYPE> &new_values) {
  if (new_times.size() != new_values.size())
    throw std::invalid_argument("TimeSeriesProperty::create: mismatched size "
                                "for the time and values vectors.");
 
  clear();
  m_values.reserve(new_times.size());
 
  std::size_t num = new_values.size();
 
  m_propSortedFlag = TimeSeriesSortStatus::TSSORTED;
  for (std::size_t i = 0; i < num; i++) {
    TimeValueUnit<TYPE> newentry(new_times[i], new_values[i]);
    m_values.emplace_back(newentry);
    if (m_propSortedFlag == TimeSeriesSortStatus::TSSORTED && i > 0 && new_times[i - 1] > new_times[i]) {
      // Status gets to unsorted
      m_propSortedFlag = TimeSeriesSortStatus::TSUNSORTED;
    }
  }
 
  // reset the size
  m_size = static_cast<int>(m_values.size());
}
 
template <typename TYPE> TYPE TimeSeriesProperty<TYPE>::getSingleValue(const Types::Core::DateAndTime &t) const {
  if (m_values.empty()) {
    const std::string error("getSingleValue(): TimeSeriesProperty '" + name() + "' is empty");
    g_log.debug(error);
    throw std::runtime_error(error);
  }
 
  // 1. Get sorted
  sortIfNecessary();
 
  // 2.
  TYPE value;
  if (t < m_values[0].time()) {
    // 1. Out side of lower bound
    value = m_values[0].value();
  } else if (t >= m_values.back().time()) {
    // 2. Out side of upper bound
    value = m_values.back().value();
  } else {
    // 3. Within boundary
    int index = this->findIndex(t);
 
    if (index < 0) {
      // If query time "t" is earlier than the begin time of the series
      index = 0;
    } else if (index == int(m_values.size())) {
      // If query time "t" is later than the end time of the  series
      index = static_cast<int>(m_values.size()) - 1;
    } else if (index > int(m_values.size())) {
      std::stringstream errss;
      errss << "TimeSeriesProperty.findIndex() returns index (" << index << " ) > maximum defined value "
            << m_values.size();
      throw std::logic_error(errss.str());
    }
 
    value = m_values[static_cast<size_t>(index)].value();
  }
 
  return value;
} // END-DEF getSinglevalue()
 
template <typename TYPE>
TYPE TimeSeriesProperty<TYPE>::getSingleValue(const Types::Core::DateAndTime &t, int &index) const {
  if (m_values.empty()) {
    const std::string error("getSingleValue(): TimeSeriesProperty '" + name() + "' is empty");
    g_log.debug(error);
    throw std::runtime_error(error);
  }
 
  // 1. Get sorted
  sortIfNecessary();
 
  // 2.
  TYPE value;
  if (t < m_values[0].time()) {
    // 1. Out side of lower bound
    value = m_values[0].value();
    index = 0;
  } else if (t >= m_values.back().time()) {
    // 2. Out side of upper bound
    value = m_values.back().value();
    index = int(m_values.size()) - 1;
  } else {
    // 3. Within boundary
    index = this->findIndex(t);
 
    if (index < 0) {
      // If query time "t" is earlier than the begin time of the series
      index = 0;
    } else if (index == int(m_values.size())) {
      // If query time "t" is later than the end time of the  series
      index = static_cast<int>(m_values.size()) - 1;
    } else if (index > int(m_values.size())) {
      std::stringstream errss;
      errss << "TimeSeriesProperty.findIndex() returns index (" << index << " ) > maximum defined value "
            << m_values.size();
      throw std::logic_error(errss.str());
    }
 
    value = m_values[static_cast<size_t>(index)].value();
  }
 
  return value;
} // END-DEF getSinglevalue()
 
template <typename TYPE> TimeInterval TimeSeriesProperty<TYPE>::nthInterval(int n) const {
  // 0. Throw exception
  if (m_values.empty()) {
    const std::string error("nthInterval(): TimeSeriesProperty '" + name() + "' is empty");
    g_log.debug(error);
    throw std::runtime_error(error);
  }
 
  // 1. Sort
  sortIfNecessary();
 
  // 2. Calculate time interval
 
  Kernel::TimeInterval deltaT;
 
  if (m_filter.empty()) {
    // I. No filter
    if (n >= static_cast<int>(m_values.size()) ||
        (n == static_cast<int>(m_values.size()) - 1 && m_values.size() == 1)) {
      // 1. Out of bound
      ;
    } else if (n == static_cast<int>(m_values.size()) - 1) {
      // 2. Last one by making up an end time.
      time_duration d = m_values.rbegin()->time() - (m_values.rbegin() + 1)->time();
      DateAndTime endTime = m_values.rbegin()->time() + d;
      Kernel::TimeInterval dt(m_values.rbegin()->time(), endTime);
      deltaT = dt;
    } else {
      // 3. Regular
      DateAndTime startT = m_values[static_cast<std::size_t>(n)].time();
      DateAndTime endT = m_values[static_cast<std::size_t>(n) + 1].time();
      TimeInterval dt(startT, endT);
      deltaT = dt;
    }
  } else {
    // II. Filter
    // II.0 apply Filter
    this->applyFilter();
 
    if (static_cast<size_t>(n) > m_filterQuickRef.back().second + 1) {
      // 1. n > size of the allowed region, do nothing to dt
      ;
    } else if (static_cast<size_t>(n) == m_filterQuickRef.back().second + 1) {
      // 2. n = size of the allowed region, duplicate the last one
      auto ind_t1 = static_cast<long>(m_filterQuickRef.back().first);
      long ind_t2 = ind_t1 - 1;
      Types::Core::DateAndTime t1 = (m_values.begin() + ind_t1)->time();
      Types::Core::DateAndTime t2 = (m_values.begin() + ind_t2)->time();
      time_duration d = t1 - t2;
      Types::Core::DateAndTime t3 = t1 + d;
      Kernel::TimeInterval dt(t1, t3);
      deltaT = dt;
    } else {
      // 3. n < size
      Types::Core::DateAndTime t0;
      Types::Core::DateAndTime tf;
 
      size_t refindex = this->findNthIndexFromQuickRef(n);
      if (refindex + 3 >= m_filterQuickRef.size())
        throw std::logic_error("nthInterval:  Haven't considered this case.");
 
      int diff = n - static_cast<int>(m_filterQuickRef[refindex].second);
      if (diff < 0)
        throw std::logic_error("nthInterval:  diff cannot be less than 0.");
 
      // i) start time
      Types::Core::DateAndTime ftime0 = m_filter[m_filterQuickRef[refindex].first].first;
      size_t iStartIndex = m_filterQuickRef[refindex + 1].first + static_cast<size_t>(diff);
      Types::Core::DateAndTime ltime0 = m_values[iStartIndex].time();
      if (iStartIndex == 0 && ftime0 < ltime0) {
        // a) Special case that True-filter time starts before log time
        t0 = ltime0;
      } else if (diff == 0) {
        // b) First entry... usually start from filter time
        t0 = ftime0;
      } else {
        // c) Not the first entry.. usually in the middle of TRUE filter period.
        // use log time
        t0 = ltime0;
      }
 
      // ii) end time
      size_t iStopIndex = iStartIndex + 1;
      if (iStopIndex >= m_values.size()) {
        // a) Last log entry is for the start
        Types::Core::DateAndTime ftimef = m_filter[m_filterQuickRef[refindex + 3].first].first;
        tf = ftimef;
      } else {
        // b) Using the earlier value of next log entry and next filter entry
        Types::Core::DateAndTime ltimef = m_values[iStopIndex].time();
        Types::Core::DateAndTime ftimef = m_filter[m_filterQuickRef[refindex + 3].first].first;
        if (ltimef < ftimef)
          tf = ltimef;
        else
          tf = ftimef;
      }
 
      Kernel::TimeInterval dt(t0, tf);
      deltaT = dt;
    } // END-IF-ELSE Cases
  }
 
  return deltaT;
}
 
//-----------------------------------------------------------------------------------------------
template <typename TYPE> TYPE TimeSeriesProperty<TYPE>::nthValue(int n) const {
  TYPE value;
 
  // 1. Throw error if property is empty
  if (m_values.empty()) {
    const std::string error("nthValue(): TimeSeriesProperty '" + name() + "' is empty");
    g_log.debug(error);
    throw std::runtime_error(error);
  }
 
  // 2. Sort and apply filter
  sortIfNecessary();
 
  if (m_filter.empty()) {
    // 3. Situation 1:  No filter
    if (static_cast<size_t>(n) < m_values.size()) {
      TimeValueUnit<TYPE> entry = m_values[static_cast<std::size_t>(n)];
      value = entry.value();
    } else {
      TimeValueUnit<TYPE> entry = m_values[static_cast<std::size_t>(m_size) - 1];
      value = entry.value();
    }
  } else {
    // 4. Situation 2: There is filter
    this->applyFilter();
 
    if (static_cast<size_t>(n) > m_filterQuickRef.back().second + 1) {
      // 1. n >= size of the allowed region
      size_t ilog = (m_filterQuickRef.rbegin() + 1)->first;
      value = m_values[ilog].value();
    } else {
      // 2. n < size
      Types::Core::DateAndTime t0;
      Types::Core::DateAndTime tf;
 
      size_t refindex = findNthIndexFromQuickRef(n);
      if (refindex + 3 >= m_filterQuickRef.size()) {
        throw std::logic_error("Not consider out of boundary case here. ");
      }
      size_t ilog =
          m_filterQuickRef[refindex + 1].first + (static_cast<std::size_t>(n) - m_filterQuickRef[refindex].second);
      value = m_values[ilog].value();
    } // END-IF-ELSE Cases
  }
 
  return value;
}
 
template <typename TYPE> Types::Core::DateAndTime TimeSeriesProperty<TYPE>::nthTime(int n) const {
  sortIfNecessary();
 
  if (m_values.empty()) {
    const std::string error("nthTime(): TimeSeriesProperty '" + name() + "' is empty");
    g_log.debug(error);
    throw std::runtime_error(error);
  }
 
  if (n < 0 || n >= static_cast<int>(m_values.size()))
    n = static_cast<int>(m_values.size()) - 1;
 
  return m_values[static_cast<size_t>(n)].time();
}
 
/* Divide the property into  allowed and disallowed time intervals according to
 \a filter.
 * (Repeated time-value pairs (two same time and value entries) mark the start
 of a gap in the values.)
 * If any time-value pair is repeated, it means that this entry is in disallowed
 region.
 * The gap ends and an allowed time interval starts when a single time-value is
 met.
   The disallowed region will be hidden for countSize() and nthInterval()
   Boundary condition
   ?. If filter[0].time > log[0].time, then all log before filter[0] are
 considered TRUE
   2. If filter[-1].time < log[-1].time, then all log after filter[-1] will be
 considered same as filter[-1]
 
   @param filter :: The filter mask to apply
 */
template <typename TYPE> void TimeSeriesProperty<TYPE>::filterWith(const TimeSeriesProperty<bool> *filter) {
  // 1. Clear the current
  m_filter.clear();
  m_filterQuickRef.clear();
 
  if (filter->size() == 0) {
    // if filter is empty, return
    return;
  }
 
  // 2. Construct mFilter
  std::vector<Types::Core::DateAndTime> filtertimes = filter->timesAsVector();
  std::vector<bool> filtervalues = filter->valuesAsVector();
  assert(filtertimes.size() == filtervalues.size());
  const size_t nFilterTimes(filtertimes.size());
  m_filter.reserve(nFilterTimes + 1);
 
  bool lastIsTrue = false;
  auto fend = filtertimes.end();
  auto vit = filtervalues.begin();
  for (auto fit = filtertimes.begin(); fit != fend; ++fit) {
    if (*vit && !lastIsTrue) {
      // Get a true in filter but last recorded value is for false
      m_filter.emplace_back(*fit, true);
      lastIsTrue = true;
    } else if (!(*vit) && lastIsTrue) {
      // Get a False in filter but last recorded value is for TRUE
      m_filter.emplace_back(*fit, false);
      lastIsTrue = false;
    }
    ++vit; // move to next value
  }
 
  // 2b) Get a clean finish
  if (filtervalues.back()) {
    DateAndTime lastTime, nextLastT;
    if (m_values.back().time() > filtertimes.back()) {
      const size_t nvalues(m_values.size());
      // Last log time is later than last filter time
      lastTime = m_values.back().time();
      if (nvalues > 1 && m_values[nvalues - 2].time() > filtertimes.back())
        nextLastT = m_values[nvalues - 2].time();
      else
        nextLastT = filtertimes.back();
    } else {
      // Last log time is no later than last filter time
      lastTime = filtertimes.back();
      const size_t nfilterValues(filtervalues.size());
      // If last-but-one filter time is still later than value then previous is
      // this
      // else it is the last value time
      if (nfilterValues > 1 && m_values.back().time() > filtertimes[nfilterValues - 2])
        nextLastT = filtertimes[nfilterValues - 2];
      else
        nextLastT = m_values.back().time();
    }
 
    time_duration dtime = lastTime - nextLastT;
    m_filter.emplace_back(lastTime + dtime, false);
  }
 
  // 3. Reset flag and do filter
  m_filterApplied = false;
  applyFilter();
}
 
template <typename TYPE> void TimeSeriesProperty<TYPE>::clearFilter() {
  m_filter.clear();
  m_filterQuickRef.clear();
}
 
template <typename TYPE> void TimeSeriesProperty<TYPE>::countSize() const {
  if (m_filter.empty()) {
    // 1. Not filter
    m_size = int(m_values.size());
  } else {
    // 2. With Filter
    if (!m_filterApplied) {
      this->applyFilter();
    }
    size_t nvalues = m_filterQuickRef.empty() ? m_values.size() : m_filterQuickRef.back().second;
    // The filter logic can end up with the quick ref having a duplicate of the
    // last time and value at the end if the last filter time is past the log
    // time See "If it is out of upper boundary, still record it.  but make the
    // log entry to mP.size()+1" in applyFilter
    // Make the log seem the full size
    if (nvalues == m_values.size() + 1) {
      --nvalues;
    }
    m_size = static_cast<int>(nvalues);
  }
}
 
template <typename TYPE> bool TimeSeriesProperty<TYPE>::isTimeString(const std::string &str) {
  static const boost::regex re("^[0-9]{4}.[0-9]{2}.[0-9]{2}.[0-9]{2}.[0-9]{2}.[0-9]{2}");
  return boost::regex_search(str.begin(), str.end(), re);
}
 
template <typename TYPE> std::string TimeSeriesProperty<TYPE>::isValid() const { return ""; }
 
/*
 * A TimeSeriesProperty never has a default, so return empty string
 * @returns Empty string as no defaults can be provided
 */
template <typename TYPE> std::string TimeSeriesProperty<TYPE>::getDefault() const {
  return ""; // No defaults can be provided=empty string
}
 
template <typename TYPE> bool TimeSeriesProperty<TYPE>::isDefault() const { return false; }
 
template <typename TYPE> TimeSeriesPropertyStatistics TimeSeriesProperty<TYPE>::getStatistics() const {
  TimeSeriesPropertyStatistics out;
  Mantid::Kernel::Statistics raw_stats = Mantid::Kernel::getStatistics(this->filteredValuesAsVector());
  out.mean = raw_stats.mean;
  out.standard_deviation = raw_stats.standard_deviation;
  out.median = raw_stats.median;
  out.minimum = raw_stats.minimum;
  out.maximum = raw_stats.maximum;
  if (this->size() > 0) {
    const auto &intervals = this->getSplittingIntervals();
    const double duration_sec =
        std::accumulate(intervals.cbegin(), intervals.cend(), 0.,
                        [](double sum, const auto &interval) { return sum + interval.duration(); });
    out.duration = duration_sec;
    const auto time_weighted = this->timeAverageValueAndStdDev();
    out.time_mean = time_weighted.first;
    out.time_standard_deviation = time_weighted.second;
  } else {
    out.time_mean = std::numeric_limits<double>::quiet_NaN();
    out.time_standard_deviation = std::numeric_limits<double>::quiet_NaN();
    out.duration = std::numeric_limits<double>::quiet_NaN();
  }
 
  return out;
}
 
/*
 * Detects whether there are duplicated entries (of time) in property
 * If there is any, keep one of them
 */
template <typename TYPE> void TimeSeriesProperty<TYPE>::eliminateDuplicates() {
  // 1. Sort if necessary
  sortIfNecessary();
 
  // 2. Detect and Remove Duplicated
  size_t numremoved = 0;
 
  typename std::vector<TimeValueUnit<TYPE>>::iterator vit;
  vit = m_values.begin() + 1;
  Types::Core::DateAndTime prevtime = m_values.begin()->time();
  while (vit != m_values.end()) {
    Types::Core::DateAndTime currtime = vit->time();
    if (prevtime == currtime) {
      // Print out warning
      g_log.debug() << "Entry @ Time = " << prevtime
                    << "has duplicate time stamp.  Remove entry with Value = " << (vit - 1)->value() << "\n";
 
      // A duplicated entry!
      vit = m_values.erase(vit - 1);
 
      numremoved++;
    }
 
    // b) progress
    prevtime = currtime;
    ++vit;
  }
 
  // update m_size
  countSize();
 
  // 3. Finish
  g_log.warning() << "Log " << this->name() << " has " << numremoved << " entries removed due to duplicated time. "
                  << "\n";
}
 
/*
 * Print the content to string
 */
template <typename TYPE> std::string TimeSeriesProperty<TYPE>::toString() const {
  std::stringstream ss;
  for (size_t i = 0; i < m_values.size(); ++i)
    ss << m_values[i].time() << "\t\t" << m_values[i].value() << "\n";
 
  return ss.str();
}
 
//-------------------------------------------------------------------------
// Private methods
//-------------------------------------------------------------------------
 
//----------------------------------------------------------------------------------
/*
 * Sort vector mP and set the flag. Only sorts if the values are not already
 * sorted.
 */
template <typename TYPE> void TimeSeriesProperty<TYPE>::sortIfNecessary() const {
  if (m_propSortedFlag == TimeSeriesSortStatus::TSUNKNOWN) {
    bool sorted = is_sorted(m_values.begin(), m_values.end());
    if (sorted)
      m_propSortedFlag = TimeSeriesSortStatus::TSSORTED;
    else
      m_propSortedFlag = TimeSeriesSortStatus::TSUNSORTED;
  }
 
  if (m_propSortedFlag == TimeSeriesSortStatus::TSUNSORTED) {
    g_log.information("TimeSeriesProperty is not sorted.  Sorting is operated on it. ");
    std::stable_sort(m_values.begin(), m_values.end());
    m_propSortedFlag = TimeSeriesSortStatus::TSSORTED;
  }
}
 
template <typename TYPE> int TimeSeriesProperty<TYPE>::findIndex(Types::Core::DateAndTime t) const {
  // 0. Return with an empty container
  if (m_values.empty())
    return 0;
 
  // 1. Sort
  sortIfNecessary();
 
  // 2. Extreme value
  if (t <= m_values[0].time()) {
    return -1;
  } else if (t >= m_values.back().time()) {
    return (int(m_values.size()));
  }
 
  // 3. Find by lower_bound()
  typename std::vector<TimeValueUnit<TYPE>>::const_iterator fid;
  TimeValueUnit<TYPE> temp(t, m_values[0].value());
  fid = std::lower_bound(m_values.begin(), m_values.end(), temp);
 
  int newindex = int(fid - m_values.begin());
  if (fid->time() > t)
    newindex--;
 
  return newindex;
}
 
template <typename TYPE>
int TimeSeriesProperty<TYPE>::upperBound(Types::Core::DateAndTime t, int istart, int iend) const {
  // 0. Check validity
  if (istart < 0) {
    throw std::invalid_argument("Start Index cannot be less than 0");
  }
  if (iend >= static_cast<int>(m_values.size())) {
    throw std::invalid_argument("End Index cannot exceed the boundary");
  }
  if (istart > iend) {
    throw std::invalid_argument("Start index cannot be greater than end index");
  }
 
  // 1. Return instantly if it is out of boundary
  if (t < (m_values.begin() + istart)->time()) {
    return -1;
  }
  if (t > (m_values.begin() + iend)->time()) {
    return static_cast<int>(m_values.size());
  }
 
  // 2. Sort
  sortIfNecessary();
 
  // 3. Construct the pair for comparison and do lower_bound()
  TimeValueUnit<TYPE> temppair(t, m_values[0].value());
  typename std::vector<TimeValueUnit<TYPE>>::iterator fid;
  fid = std::lower_bound((m_values.begin() + istart), (m_values.begin() + iend + 1), temppair);
  if (fid == m_values.end())
    throw std::runtime_error("Cannot find data");
 
  // 4. Calculate return value
  size_t index = size_t(fid - m_values.begin());
 
  return int(index);
}
 
/*
 * Apply filter
 * Requirement: There is no 2 consecutive 'second' values that are same in
 *mFilter
 *
 * It only works with filter starting from TRUE AND having TRUE and FALSE
 *altered
 */
template <typename TYPE> void TimeSeriesProperty<TYPE>::applyFilter() const {
  // 1. Check and reset
  if (m_filterApplied)
    return;
  if (m_filter.empty())
    return;
 
  m_filterQuickRef.clear();
 
  // 2. Apply filter
  int icurlog = 0;
  for (size_t ift = 0; ift < m_filter.size(); ift++) {
    if (m_filter[ift].second) {
      // a) Filter == True: indicating the start of a quick reference region
      int istart = 0;
      if (icurlog > 0)
        istart = icurlog - 1;
 
      if (icurlog < static_cast<int>(m_values.size()))
        icurlog = this->upperBound(m_filter[ift].first, istart, static_cast<int>(m_values.size()) - 1);
 
      if (icurlog < 0) {
        // i. If it is out of lower boundary, add filter time, add 0 time
        if (!m_filterQuickRef.empty())
          throw std::logic_error("return log index < 0 only occurs with the first log entry");
 
        m_filterQuickRef.emplace_back(ift, 0);
        m_filterQuickRef.emplace_back(0, 0);
 
        icurlog = 0;
      } else if (icurlog >= static_cast<int>(m_values.size())) {
        // ii.  If it is out of upper boundary, still record it.  but make the
        // log entry to mP.size()+1
        size_t ip = 0;
        if (m_filterQuickRef.size() >= 4)
          ip = m_filterQuickRef.back().second;
        m_filterQuickRef.emplace_back(ift, ip);
        m_filterQuickRef.emplace_back(m_values.size() + 1, ip);
      } else {
        // iii. The returned value is in the boundary.
        size_t numintervals = 0;
        if (!m_filterQuickRef.empty()) {
          numintervals = m_filterQuickRef.back().second;
        }
        if (m_filter[ift].first < m_values[static_cast<std::size_t>(icurlog)].time()) {
          if (icurlog == 0) {
            throw std::logic_error("In this case, icurlog won't be zero! ");
          }
          icurlog--;
        }
        m_filterQuickRef.emplace_back(ift, numintervals);
        // Note: numintervals inherits from last filter
        m_filterQuickRef.emplace_back(icurlog, numintervals);
      }
    } // Filter value is True
    else if (m_filterQuickRef.size() % 4 == 2) {
      // b) Filter == False: indicating the end of a quick reference region
      int ilastlog = icurlog;
 
      if (ilastlog < static_cast<int>(m_values.size())) {
        // B1: Last TRUE entry is still within log
        icurlog = this->upperBound(m_filter[ift].first, icurlog, static_cast<int>(m_values.size()) - 1);
 
        if (icurlog < 0) {
          // i.   Some false filter is before the first log entry.  The previous
          // filter does not make sense
          if (m_filterQuickRef.size() != 2)
            throw std::logic_error("False filter is before first log entry.  "
                                   "QuickRef size must be 2.");
          m_filterQuickRef.pop_back();
          m_filterQuickRef.clear();
        } else {
          // ii.  Register the end of a valid log
          if (ilastlog < 0)
            throw std::logic_error("LastLog is not expected to be less than 0");
 
          int delta_numintervals = icurlog - ilastlog;
          if (delta_numintervals < 0)
            throw std::logic_error("Havn't considered delta numinterval can be less than 0.");
 
          size_t new_numintervals = m_filterQuickRef.back().second + static_cast<size_t>(delta_numintervals);
 
          m_filterQuickRef.emplace_back(icurlog, new_numintervals);
          m_filterQuickRef.emplace_back(ift, new_numintervals);
        }
      } else {
        // B2. Last TRUE filter's time is already out side of log.
        size_t new_numintervals = m_filterQuickRef.back().second + 1;
        m_filterQuickRef.emplace_back(icurlog - 1, new_numintervals);
        m_filterQuickRef.emplace_back(ift, new_numintervals);
      }
    } // Filter value is FALSE
 
  } // ENDFOR
 
  // 5. Change flag
  m_filterApplied = true;
 
  // 6. Re-count size
  countSize();
}
 
/*
 * A new algorithm sto find Nth index.  It is simple and leave a lot work to the
 *callers
 *
 * Return: the index of the quick reference vector
 */
template <typename TYPE> size_t TimeSeriesProperty<TYPE>::findNthIndexFromQuickRef(int n) const {
  size_t index = 0;
 
  // 1. Do check
  if (n < 0)
    throw std::invalid_argument("Unable to take into account negative index. ");
  else if (m_filterQuickRef.empty())
    throw std::runtime_error("Quick reference is not established. ");
 
  // 2. Return...
  if (static_cast<size_t>(n) >= m_filterQuickRef.back().second) {
    // 2A.  Out side of boundary
    index = m_filterQuickRef.size();
  } else {
    // 2B. Inside
    for (size_t i = 0; i < m_filterQuickRef.size(); i += 4) {
      if (static_cast<size_t>(n) >= m_filterQuickRef[i].second &&
          static_cast<size_t>(n) < m_filterQuickRef[i + 3].second) {
        index = i;
        break;
      }
    }
  }
 
  return index;
}
 
template <typename TYPE> std::string TimeSeriesProperty<TYPE>::setValueFromProperty(const Property &right) {
  auto prop = dynamic_cast<const TimeSeriesProperty<TYPE> *>(&right);
  if (!prop) {
    return "Could not set value: properties have different type.";
  }
  m_values = prop->m_values;
  m_size = prop->m_size;
  m_propSortedFlag = prop->m_propSortedFlag;
  m_filter = prop->m_filter;
  m_filterQuickRef = prop->m_filterQuickRef;
  m_filterApplied = prop->m_filterApplied;
  return "";
}
 
//----------------------------------------------------------------------------------------------
template <typename TYPE> void TimeSeriesProperty<TYPE>::saveTimeVector(::NeXus::File *file) {
  std::vector<DateAndTime> times = this->timesAsVector();
  const DateAndTime &start = times.front();
  std::vector<double> timeSec(times.size());
  for (size_t i = 0; i < times.size(); i++)
    timeSec[i] = static_cast<double>(times[i].totalNanoseconds() - start.totalNanoseconds()) * 1e-9;
  file->writeData("time", timeSec);
  file->openData("time");
  file->putAttr("start", start.toISO8601String());
  file->closeData();
}
 
//----------------------------------------------------------------------------------------------
template <> void TimeSeriesProperty<std::string>::saveProperty(::NeXus::File *file) {
  std::vector<std::string> values = this->valuesAsVector();
  if (values.empty())
    return;
  file->makeGroup(this->name(), "NXlog", true);
 
  // Find the max length of any string
  auto max_it = std::max_element(values.begin(), values.end(),
                                 [](const std::string &a, const std::string &b) { return a.size() < b.size(); });
  // Increment by 1 to have the 0 terminator
  size_t maxlen = max_it->size() + 1;
  // Copy into one array
  std::vector<char> strs(values.size() * maxlen);
  size_t index = 0;
  for (const auto &prop : values) {
    std::copy(prop.begin(), prop.end(), &strs[index]);
    index += maxlen;
  }
 
  std::vector<int> dims{static_cast<int>(values.size()), static_cast<int>(maxlen)};
  file->makeData("value", ::NeXus::CHAR, dims, true);
  file->putData(strs.data());
  file->closeData();
  saveTimeVector(file);
  file->closeGroup();
}
 
template <> void TimeSeriesProperty<bool>::saveProperty(::NeXus::File *file) {
  std::vector<bool> value = this->valuesAsVector();
  if (value.empty())
    return;
  std::vector<uint8_t> asUint(value.begin(), value.end());
  file->makeGroup(this->name(), "NXlog", true);
  file->writeData("value", asUint);
  file->putAttr("boolean", "1");
  saveTimeVector(file);
  file->closeGroup();
}
 
template <typename TYPE> void TimeSeriesProperty<TYPE>::saveProperty(::NeXus::File *file) {
  auto value = this->valuesAsVector();
  if (value.empty())
    return;
  file->makeGroup(this->name(), "NXlog", 1);
  file->writeData("value", value);
  file->openData("value");
  file->putAttr("units", this->units());
  file->closeData();
  saveTimeVector(file);
  file->closeGroup();
}
 
template <typename TYPE> Json::Value TimeSeriesProperty<TYPE>::valueAsJson() const { return Json::Value(value()); }
 
template <typename TYPE>
void TimeSeriesProperty<TYPE>::histogramData(const Types::Core::DateAndTime &tMin, const Types::Core::DateAndTime &tMax,
                                             std::vector<double> &counts) const {
 
  size_t nPoints = counts.size();
  if (nPoints == 0)
    return; // nothing to do
 
  auto t0 = static_cast<double>(tMin.totalNanoseconds());
  auto t1 = static_cast<double>(tMax.totalNanoseconds());
  if (t0 > t1)
    throw std::invalid_argument("invalid arguments for histogramData; tMax<tMin");
 
  double dt = (t1 - t0) / static_cast<double>(nPoints);
 
  for (auto &ev : m_values) {
    auto time = static_cast<double>(ev.time().totalNanoseconds());
    if (time < t0 || time >= t1)
      continue;
    auto ind = static_cast<size_t>((time - t0) / dt);
    counts[ind] += static_cast<double>(ev.value());
  }
}
 
template <>
void TimeSeriesProperty<std::string>::histogramData(const Types::Core::DateAndTime &tMin,
                                                    const Types::Core::DateAndTime &tMax,
                                                    std::vector<double> &counts) const {
  UNUSED_ARG(tMin);
  UNUSED_ARG(tMax);
  UNUSED_ARG(counts);
  throw std::runtime_error("histogramData is not implememnted for time series "
                           "properties containing strings");
}
 
template <typename TYPE> std::vector<TYPE> TimeSeriesProperty<TYPE>::filteredValuesAsVector() const {
  if (m_filter.empty()) {
    return this->valuesAsVector(); // no filtering to do
  }
  if (!m_filterApplied) {
    applyFilter();
  }
  sortIfNecessary();
 
  std::vector<TYPE> filteredValues;
  for (const auto &value : m_values) {
    if (isTimeFiltered(value.time())) {
      filteredValues.emplace_back(value.value());
    }
  }
 
  return filteredValues;
}
 
template <typename TYPE> bool TimeSeriesProperty<TYPE>::isTimeFiltered(const Types::Core::DateAndTime &time) const {
  // Each time/value pair in the filter defines a point where the region defined
  // after that time is either included/excluded depending on the boolean value.
  // By definition of the filter construction the region before a given filter
  // time must have the opposite value. For times outside the filter region:
  //   1. time < first filter time: inverse of the first filter value
  //   2. time > last filter time: value of the last filter value
  // If time == a filter time then the value is taken to belong to that filter
  // region and not the previous
 
  // Find first fitler time strictly greater than time
  auto filterEntry = std::lower_bound(m_filter.begin(), m_filter.end(), time,
                                      [](const std::pair<Types::Core::DateAndTime, bool> &filterEntry,
                                         const Types::Core::DateAndTime &t) { return filterEntry.first <= t; });
 
  if (filterEntry == m_filter.begin()) {
    return !filterEntry->second;
  } else {
    // iterator points to filter greater than time and but we want the previous
    // region
    --filterEntry;
    return filterEntry->second;
  }
}
 
template <typename TYPE> std::vector<SplittingInterval> TimeSeriesProperty<TYPE>::getSplittingIntervals() const {
  std::vector<SplittingInterval> intervals;
  // Case where there is no filter
  if (m_filter.empty()) {
    intervals.emplace_back(firstTime(), lastTime());
    return intervals;
  }
 
  if (!m_filterApplied) {
    applyFilter();
  }
 
  // (local reference to use in lambda)
  const auto &localFilter = m_filter;
  const auto findNext = [&localFilter](size_t &index, const bool val) {
    for (; index < localFilter.size(); ++index) {
      const auto &entry = localFilter[index];
      if (entry.second == val) {
        return entry.first;
      }
    }
    return localFilter.back().first;
  };
 
  // Look through filter to find start/stop pairs
  size_t index = 0;
  while (index < m_filter.size()) {
    DateAndTime start, stop;
    if (index == 0) {
      if (m_filter[0].second) {
        start = m_filter[0].first;
      } else {
        start = firstTime();
      }
    } else {
      start = findNext(index, true);
    }
    stop = findNext(index, false);
    if (stop != start) { // avoid empty ranges
      intervals.emplace_back(start, stop);
    }
  }
 
  return intervals;
}
 
// -------------------------- Macro to instantiation concrete types
// --------------------------------
#define INSTANTIATE(TYPE) template class TimeSeriesProperty<TYPE>;
 
// -------------------------- Concrete instantiation
// -----------------------------------------------
INSTANTIATE(int32_t)
INSTANTIATE(int64_t)
INSTANTIATE(uint32_t)
INSTANTIATE(uint64_t)
INSTANTIATE(float)
INSTANTIATE(double)
INSTANTIATE(std::string)
INSTANTIATE(bool)
 
 
 
} // namespace Kernel
} // namespace Mantid
 
namespace Mantid::Kernel {
//================================================================================================
double filterByStatistic(TimeSeriesProperty<double> const *const propertyToFilter,
                         Kernel::Math::StatisticType statisticType) {
  using namespace Kernel::Math;
  double singleValue = 0;
  switch (statisticType) {
  case FirstValue:
    singleValue = propertyToFilter->nthValue(0);
    break;
  case LastValue:
    singleValue = propertyToFilter->nthValue(propertyToFilter->size() - 1);
    break;
  case Minimum:
    singleValue = propertyToFilter->getStatistics().minimum;
    break;
  case Maximum:
    singleValue = propertyToFilter->getStatistics().maximum;
    break;
  case Mean:
    singleValue = propertyToFilter->getStatistics().mean;
    break;
  case Median:
    singleValue = propertyToFilter->getStatistics().median;
    break;
  default:
    throw std::invalid_argument("filterByStatistic - Unknown statistic type: " +
                                boost::lexical_cast<std::string>(propertyToFilter));
  };
  return singleValue;
}
} // namespace Mantid::Kernel