/// <summary>
/// Constructor for process tracker: Initialises the trackers for individual processes
/// </summary>
/// <param name="numTimesteps">The number of time steps in the model</param>
/// <param name="lats">The latitudes of active grid cells in the model</param>
/// <param name="lons">The longitudes of active grid cells in the model</param>
/// <param name="cellIndices">List of indices of active cells in the model grid</param>
/// <param name="Filenames">The filenames of the output files to write the tracking results to</param>
/// <param name="trackProcesses">Whether to track processes</param>
/// <param name="cohortDefinitions">The definitions for cohort functional groups in the model</param>
/// <param name="missingValue">The missing value to use in process tracking output files</param>
/// <param name="outputFileSuffix">The suffix to be applied to output files from process tracking</param>
/// <param name="outputPath">The path to the folder to be used for process tracking outputs</param>
/// <param name="trackerMassBins">The mass bins to use for categorising output data in the process trackers</param>
/// <param name="specificLocations">Whether the model is being run for specific locations</param>
/// <param name="initialisation">The Madingley Model initialisation</param>
/// <param name="latCellSize">The size of grid cells latitudinally</param>
/// <param name="lonCellSize">The size of grid cells longitudinally</param>
public GlobalProcessTracker(uint numTimesteps,
float[] lats, float[] lons,
List<uint[]> cellIndices,
SortedList<string, string> Filenames,
Boolean trackProcesses,
FunctionalGroupDefinitions cohortDefinitions,
FunctionalGroupDefinitions stockDefinitions,
double missingValue,
string outputFileSuffix,
string outputPath, MassBinsHandler trackerMassBins,
Boolean specificLocations,
MadingleyModelInitialisation initialisation,
float latCellSize,
float lonCellSize)
{
// Initialise trackers for ecological processes
_TrackProcesses = trackProcesses;
if (_TrackProcesses)
{
_TrackNPP = new GlobalNPPTracker(outputPath, lats.Length, lons.Length, lats, lons, latCellSize, lonCellSize,
(int)numTimesteps,stockDefinitions.GetNumberOfFunctionalGroups(),outputFileSuffix);
}
}
/// <summary>
/// Constructor for process tracker: Initialises the trackers for individual processes
/// </summary>
/// <param name="numTimesteps">The number of time steps in the model</param>
/// <param name="lats">The latitudes of active grid cells in the model</param>
/// <param name="lons">The longitudes of active grid cells in the model</param>
/// <param name="cellIndices">List of indices of active cells in the model grid</param>
/// <param name="Filenames">The filenames of the output files to write the tracking results to</param>
/// <param name="trackProcesses">Whether to track processes</param>
/// <param name="cohortDefinitions">The definitions for cohort functional groups in the model</param>
/// <param name="missingValue">The missing value to use in process tracking output files</param>
/// <param name="outputFileSuffix">The suffix to be applied to output files from process tracking</param>
/// <param name="outputPath">The path to the folder to be used for process tracking outputs</param>
/// <param name="trackerMassBins">The mass bins to use for categorising output data in the process trackers</param>
/// <param name="specificLocations">Whether the model is being run for specific locations</param>
/// <param name="initialisation">The Madingley Model initialisation</param>
/// <param name="latCellSize">The size of grid cells latitudinally</param>
/// <param name="lonCellSize">The size of grid cells longitudinally</param>
public GlobalProcessTracker(uint numTimesteps,
float[] lats, float[] lons,
List <uint[]> cellIndices,
SortedList <string, string> Filenames,
Boolean trackProcesses,
FunctionalGroupDefinitions cohortDefinitions,
FunctionalGroupDefinitions stockDefinitions,
double missingValue,
string outputFileSuffix,
string outputPath, MassBinsHandler trackerMassBins,
Boolean specificLocations,
MadingleyModelInitialisation initialisation,
float latCellSize,
float lonCellSize)
{
// Initialise trackers for ecological processes
_TrackProcesses = trackProcesses;
if (_TrackProcesses)
{
_TrackNPP = new GlobalNPPTracker(outputPath, lats.Length, lons.Length, lats, lons, latCellSize, lonCellSize,
(int)numTimesteps, stockDefinitions.GetNumberOfFunctionalGroups(), outputFileSuffix);
}
}
/// <summary>
/// Seed grid cell with stocks, as specified in the model input files
/// </summary>
/// <param name="functionalGroups">A reference to the stock functional group handler</param>
/// <param name="cellEnvironment">The environment in the grid cell</param>
/// <param name="globalDiagnostics">A list of global diagnostic variables for the model grid</param>
private void SeedGridCellStocks(ref FunctionalGroupDefinitions functionalGroups, ref SortedList<string, double[]>
cellEnvironment, SortedList<string, double> globalDiagnostics)
{
// Set the seed for the random number generator from the system time
RandomNumberGenerator.SetSeedFromSystemTime();
Stock NewStock;
// Define local variables
int[] FunctionalGroupsToUse;
// Get the individual body masses for organisms in each stock functional group
double[] IndividualMass = functionalGroups.GetBiologicalPropertyAllFunctionalGroups("individual mass");
// Check which realm the cell is in
if (cellEnvironment["Realm"][0] == 1.0 && _CellEnvironment["Precipitation"][0] != _CellEnvironment["Missing Value"][0] && _CellEnvironment["Temperature"][0] != _CellEnvironment["Missing Value"][0])
{
// Get the indices of all terrestrial functional groups
FunctionalGroupsToUse = functionalGroups.GetFunctionalGroupIndex("realm", "terrestrial", true);
}
else if (cellEnvironment["Realm"][0] == 2.0 && _CellEnvironment["NPP"][0] != _CellEnvironment["Missing Value"][0])
{
// Get the indices of all marine functional groups
FunctionalGroupsToUse = functionalGroups.GetFunctionalGroupIndex("realm", "marine", true);
}
else
{
// For cells without a realm designation, no functional groups will be used
FunctionalGroupsToUse = new int[0];
}
// Loop over all functional groups in the model
for (int FunctionalGroup = 0; FunctionalGroup < functionalGroups.GetNumberOfFunctionalGroups(); FunctionalGroup++)
{
// Create a new list to hold the stocks in the grid cell
_GridCellStocks[FunctionalGroup] = new List<Stock>();
// If it is a functional group that corresponds to the current realm, then seed the stock
if (FunctionalGroupsToUse.Contains(FunctionalGroup))
{
if (_CellEnvironment["Realm"][0] == 1.0)
{
// An instance of the terrestrial carbon model class
RevisedTerrestrialPlantModel PlantModel = new RevisedTerrestrialPlantModel();
// Calculate predicted leaf mass at equilibrium for this stock
double LeafMass = PlantModel.CalculateEquilibriumLeafMass(_CellEnvironment, functionalGroups.GetTraitNames("leaf strategy", FunctionalGroup) == "deciduous");
// Initialise the new stock with the relevant properties
NewStock = new Stock((byte)FunctionalGroup, IndividualMass[FunctionalGroup], LeafMass);
// Add the new stock to the list of grid cell stocks
_GridCellStocks[FunctionalGroup].Add(NewStock);
// Increment the variable tracking the total number of stocks in the model
globalDiagnostics["NumberOfStocksInModel"]++;
}
else if (FunctionalGroupsToUse.Contains(FunctionalGroup))
{
// Initialise the new stock with the relevant properties
NewStock = new Stock((byte)FunctionalGroup, IndividualMass[FunctionalGroup], 1e12);
// Add the new stock to the list of grid cell stocks
_GridCellStocks[FunctionalGroup].Add(NewStock);
// Increment the variable tracking the total number of stocks in the model
globalDiagnostics["NumberOfStocksInModel"]++;
}
else
{
}
}
}
}
/// <summary>
/// Constructor for a grid cell; creates cell and reads in environmental data
/// </summary>
/// <param name="latitude">The latitude of the grid cell</param>
/// <param name="latIndex">The latitudinal index of the grid cell</param>
/// <param name="longitude">The longitude of the grid cell</param>
/// <param name="lonIndex">The longitudinal index of the grid cell</param>
/// <param name="latCellSize">The latitudinal dimension of the grid cell</param>
/// <param name="lonCellSize">The longitudinal dimension of the grid cell</param>
/// <param name="dataLayers">A list of environmental data variables in the model</param>
/// <param name="missingValue">The missing value to be applied to all data in the grid cell</param>
/// <param name="cohortFunctionalGroups">The definitions for cohort functional groups in the model</param>
/// <param name="stockFunctionalGroups">The definitions for stock functional groups in the model</param>
/// <param name="globalDiagnostics">A list of global diagnostic variables for the model grid</param>
/// <param name="tracking">Whether process-tracking is enabled</param>
/// <param name="specificLocations">Whether the model is being run for specific locations</param>
public GridCell(float latitude, uint latIndex, float longitude, uint lonIndex, float latCellSize, float lonCellSize,
SortedList<string, EnviroData> dataLayers, double missingValue, FunctionalGroupDefinitions cohortFunctionalGroups,
FunctionalGroupDefinitions stockFunctionalGroups, SortedList<string, double> globalDiagnostics,Boolean tracking,
bool specificLocations)
{
// Boolean to track when environmental data are missing
Boolean EnviroMissingValue;
// Initialise the utility functions
Utilities = new UtilityFunctions();
// Temporary vector for holding initial values of grid cell properties
double[] tempVector;
// Initialise deltas sorted list
_Deltas = new Dictionary<string, Dictionary<string, double>>();
// Initialize delta abundance sorted list with appropriate processes
Dictionary<string, double> DeltaAbundance = new Dictionary<string, double>();
DeltaAbundance.Add("mortality", 0.0);
// Add delta abundance sorted list to deltas sorted list
_Deltas.Add("abundance", DeltaAbundance);
// Initialize delta biomass sorted list with appropriate processes
Dictionary<string, double> DeltaBiomass = new Dictionary<string, double>();
DeltaBiomass.Add("metabolism", 0.0);
DeltaBiomass.Add("predation", 0.0);
DeltaBiomass.Add("herbivory", 0.0);
DeltaBiomass.Add("reproduction", 0.0);
// Add delta biomass sorted list to deltas sorted list
_Deltas.Add("biomass", DeltaBiomass);
// Initialize delta reproductive biomass vector with appropriate processes
Dictionary<string, double> DeltaReproductiveBiomass = new Dictionary<string, double>();
DeltaReproductiveBiomass.Add("reproduction", 0.0);
// Add delta reproduction sorted list to deltas sorted list
_Deltas.Add("reproductivebiomass", DeltaReproductiveBiomass);
// Initialize organic pool delta vector with appropriate processes
Dictionary<string, double> DeltaOrganicPool = new Dictionary<string, double>();
DeltaOrganicPool.Add("herbivory", 0.0);
DeltaOrganicPool.Add("predation", 0.0);
DeltaOrganicPool.Add("mortality", 0.0);
// Add delta organic pool sorted list to deltas sorted list
_Deltas.Add("organicpool", DeltaOrganicPool);
// Initialize respiratory CO2 pool delta vector with appropriate processes
Dictionary<string, double> DeltaRespiratoryCO2Pool = new Dictionary<string, double>();
DeltaRespiratoryCO2Pool.Add("metabolism", 0.0);
// Add delta respiratory CO2 pool to deltas sorted list
_Deltas.Add("respiratoryCO2pool", DeltaRespiratoryCO2Pool);
// Set the grid cell values of latitude, longitude and missing value as specified
_Latitude = latitude;
_Longitude = longitude;
// Initialise list of environmental data layer values
_CellEnvironment = new SortedList<string, double[]>();
//Add the latitude and longitude
tempVector = new double[1];
tempVector[0] = latitude;
_CellEnvironment.Add("Latitude", tempVector);
tempVector = new double[1];
tempVector[0] = longitude;
_CellEnvironment.Add("Longitude", tempVector);
// Add an organic matter pool to the cell environment to track organic biomass not held by animals or plants with an initial value of 0
tempVector = new double[1];
tempVector[0] = 0.0;
_CellEnvironment.Add("Organic Pool", tempVector);
// Add a repsiratory CO2 pool to the cell environment with an initial value of 0
tempVector = new double[1];
tempVector[0] = 0.0;
_CellEnvironment.Add("Respiratory CO2 Pool", tempVector);
// Add the grid cell area (in km2) to the cell environment with an initial value of 0
tempVector = new double[1];
// Calculate the area of this grid cell
tempVector[0] = Utilities.CalculateGridCellArea(latitude, lonCellSize, latCellSize);
// Add it to the cell environment
_CellEnvironment.Add("Cell Area", tempVector);
//Add the latitude and longitude indices
tempVector = new double[1];
tempVector[0] = latIndex;
_CellEnvironment.Add("LatIndex", tempVector);
tempVector = new double[1];
tempVector[0] = lonIndex;
_CellEnvironment.Add("LonIndex", tempVector);
// Add the missing value of data in the grid cell to the cell environment
tempVector = new double[1];
tempVector[0] = missingValue;
_CellEnvironment.Add("Missing Value", tempVector);
// Loop through environmental data layers and extract values for this grid cell
// Also standardise missing values
// Loop over variables in the list of environmental data
foreach (string LayerName in dataLayers.Keys)
{
// Initiliase the temporary vector of values to be equal to the number of time intervals in the environmental variable
tempVector = new double[dataLayers[LayerName].NumTimes];
// Loop over the time intervals in the environmental variable
for (int hh = 0; hh < dataLayers[LayerName].NumTimes; hh++)
{
// Add the value of the environmental variable at this time interval to the temporary vector
tempVector[hh] = dataLayers[LayerName].GetValue(_Latitude, _Longitude, (uint)hh, out EnviroMissingValue,latCellSize,lonCellSize);
// If the environmental variable is a missing value, then change the value to equal the standard missing value for this cell
if (EnviroMissingValue)
tempVector[hh] = missingValue;
}
// Add the values of the environmental variables to the cell environment, with the name of the variable as the key
_CellEnvironment.Add(LayerName, tempVector);
}
if (_CellEnvironment.ContainsKey("LandSeaMask"))
{
if (_CellEnvironment["LandSeaMask"][0].CompareTo(0.0) == 0)
{
if (ContainsData(_CellEnvironment["OceanTemp"], _CellEnvironment["Missing Value"][0]))
{
//This is a marine cell
tempVector = new double[1];
tempVector[0] = 2.0;
_CellEnvironment.Add("Realm", tempVector);
_CellEnvironment.Add("NPP", _CellEnvironment["OceanNPP"]);
_CellEnvironment.Add("DiurnalTemperatureRange", _CellEnvironment["OceanDTR"]);
if (_CellEnvironment.ContainsKey("Temperature"))
{
if(_CellEnvironment.ContainsKey("SST"))
{
_CellEnvironment["Temperature"] = _CellEnvironment["SST"];
}
else
{
}
}
else
{
_CellEnvironment.Add("Temperature", _CellEnvironment["SST"]);
}
}
else
{
//This is a freshwater cell and in this model formulation is characterised as belonging to the terrestrial realm
tempVector = new double[1];
tempVector[0] = 2.0;
_CellEnvironment.Add("Realm", tempVector);
_CellEnvironment.Add("NPP", _CellEnvironment["LandNPP"]);
_CellEnvironment.Add("DiurnalTemperatureRange", _CellEnvironment["LandDTR"]);
}
}
else
{
//This is a land cell
tempVector = new double[1];
tempVector[0] = 1.0;
_CellEnvironment.Add("Realm", tempVector);
_CellEnvironment.Add("NPP", _CellEnvironment["LandNPP"]);
_CellEnvironment.Add("DiurnalTemperatureRange", _CellEnvironment["LandDTR"]);
}
}
else
{
Debug.Fail("No land sea mask defined - a mask is required to initialise appropriate ecology");
}
//Calculate and add the standard deviation of monthly temperature as a measure of seasonality
//Also calculate and add the annual mean temperature for this cell
tempVector = new double[12];
double[] sdtemp = new double[12];
double[] meantemp = new double[12];
tempVector = _CellEnvironment["Temperature"];
double Average = tempVector.Average();
meantemp[0] = Average;
double SumOfSquaresDifferences = tempVector.Select(val => (val - Average) * (val - Average)).Sum();
sdtemp[0] = Math.Sqrt(SumOfSquaresDifferences / tempVector.Length);
_CellEnvironment.Add("SDTemperature", sdtemp);
_CellEnvironment.Add("AnnualTemperature", meantemp);
//Remove unrequired cell environment layers
if (_CellEnvironment.ContainsKey("LandNPP")) _CellEnvironment.Remove("LandNPP");
if (_CellEnvironment.ContainsKey("LandDTR")) _CellEnvironment.Remove("LandDTR");
if (_CellEnvironment.ContainsKey("OceanNPP")) _CellEnvironment.Remove("OceanNPP");
if (_CellEnvironment.ContainsKey("OceanDTR")) _CellEnvironment.Remove("OceanDTR");
if (_CellEnvironment.ContainsKey("SST")) _CellEnvironment.Remove("SST");
// CREATE NPP SEASONALITY LAYER
_CellEnvironment.Add("Seasonality", CalculateNPPSeasonality(_CellEnvironment["NPP"], _CellEnvironment["Missing Value"][0]));
// Calculate other climate variables from temperature and precipitation
// Declare an instance of the climate variables calculator
ClimateVariablesCalculator CVC = new ClimateVariablesCalculator();
// Calculate the fraction of the year that experiences frost
double[] NDF = new double[1];
NDF[0] = CVC.GetNDF(_CellEnvironment["FrostDays"], _CellEnvironment["Temperature"],_CellEnvironment["Missing Value"][0]);
_CellEnvironment.Add("Fraction Year Frost", NDF);
double[] frostMonthly = new double[12];
frostMonthly[0] = Math.Min(_CellEnvironment["FrostDays"][0] / 31.0, 1.0);
frostMonthly[1] = Math.Min(_CellEnvironment["FrostDays"][1] / 28.0, 1.0);
frostMonthly[2] = Math.Min(_CellEnvironment["FrostDays"][2] / 31.0, 1.0);
frostMonthly[3] = Math.Min(_CellEnvironment["FrostDays"][3] / 30.0, 1.0);
frostMonthly[4] = Math.Min(_CellEnvironment["FrostDays"][4] / 31.0, 1.0);
frostMonthly[5] = Math.Min(_CellEnvironment["FrostDays"][5] / 30.0, 1.0);
frostMonthly[6] = Math.Min(_CellEnvironment["FrostDays"][6] / 31.0, 1.0);
frostMonthly[7] = Math.Min(_CellEnvironment["FrostDays"][7] / 31.0, 1.0);
frostMonthly[8] = Math.Min(_CellEnvironment["FrostDays"][8] / 30.0, 1.0);
frostMonthly[9] = Math.Min(_CellEnvironment["FrostDays"][9] / 31.0, 1.0);
frostMonthly[10] = Math.Min(_CellEnvironment["FrostDays"][10] / 30.0, 1.0);
frostMonthly[11] = Math.Min(_CellEnvironment["FrostDays"][11] / 31.0, 1.0);
_CellEnvironment.Add("Fraction Month Frost", frostMonthly);
_CellEnvironment.Remove("FrostDays");
// Calculate AET and the fractional length of the fire season
Tuple<double[], double, double> TempTuple = new Tuple<double[], double, double>(new double[12], new double(), new double());
TempTuple = CVC.MonthlyActualEvapotranspirationSoilMoisture(_CellEnvironment["AWC"][0], _CellEnvironment["Precipitation"], _CellEnvironment["Temperature"]);
_CellEnvironment.Add("AET", TempTuple.Item1);
_CellEnvironment.Add("Fraction Year Fire", new double[1] { TempTuple.Item3 / 360 });
// Designate a breeding season for this grid cell, where a month is considered to be part of the breeding season if its NPP is at
// least 80% of the maximum NPP throughout the whole year
double[] BreedingSeason = new double[12];
for (int i = 0; i < 12; i++)
{
if ((_CellEnvironment["Seasonality"][i] / _CellEnvironment["Seasonality"].Max()) > 0.5)
{
BreedingSeason[i] = 1.0;
}
else
{
BreedingSeason[i] = 0.0;
}
}
_CellEnvironment.Add("Breeding Season", BreedingSeason);
// Initialise the grid cell cohort and stock handlers
_GridCellCohorts = new GridCellCohortHandler(cohortFunctionalGroups.GetNumberOfFunctionalGroups());
_GridCellStocks = new GridCellStockHandler(stockFunctionalGroups.GetNumberOfFunctionalGroups());
}
/// <summary>
/// Seed grid cell with cohorts, as specified in the model input files
/// </summary>
/// <param name="functionalGroups">The functional group definitions for cohorts in the grid cell</param>
/// <param name="cellEnvironment">The environment in the grid cell</param>
/// <param name="globalDiagnostics">A list of global diagnostic variables</param>
/// <param name="nextCohortID">YThe unique ID to assign to the next cohort produced</param>
/// <param name="tracking">boolean to indicate if cohorts are to be tracked in this model</param>
/// <param name="totalCellTerrestrialCohorts">The total number of cohorts to be seeded in each terrestrial grid cell</param>
/// <param name="totalCellMarineCohorts">The total number of cohorts to be seeded in each marine grid cell</param>
/// <param name="DrawRandomly">Whether the model is set to use random draws</param>
/// <param name="ZeroAbundance">Set this parameter to 'true' if you want to seed the cohorts with zero abundance</param>
private void SeedGridCellCohorts(ref FunctionalGroupDefinitions functionalGroups, ref SortedList<string, double[]>
cellEnvironment, SortedList<string, double> globalDiagnostics, Int64 nextCohortID, Boolean tracking, double totalCellTerrestrialCohorts,
double totalCellMarineCohorts, Boolean DrawRandomly, Boolean ZeroAbundance)
{
// Set the seed for the random number generator from the system time
RandomNumberGenerator.SetSeedFromSystemTime();
// StreamWriter tempsw = new StreamWriter("C://Temp//adult_juvenile_masses.txt");
// tempsw.WriteLine("adult mass\tjuvenilemass");
// Define local variables
double CohortJuvenileMass;
double CohortAdultMassRatio;
double CohortAdultMass;
double ExpectedLnAdultMassRatio;
int[] FunctionalGroupsToUse;
double NumCohortsThisCell;
double TotalNewBiomass =0.0;
// Get the minimum and maximum possible body masses for organisms in each functional group
double[] MassMinima = functionalGroups.GetBiologicalPropertyAllFunctionalGroups("minimum mass");
double[] MassMaxima = functionalGroups.GetBiologicalPropertyAllFunctionalGroups("maximum mass");
string[] NutritionSource = functionalGroups.GetTraitValuesAllFunctionalGroups("nutrition source");
double[] ProportionTimeActive = functionalGroups.GetBiologicalPropertyAllFunctionalGroups("proportion suitable time active");
//Variable for altering the juvenile to adult mass ratio for marine cells when handling certain functional groups eg baleen whales
double Scaling = 0.0;
Int64 CohortIDIncrementer = nextCohortID;
// Check which realm the cell is in
if (cellEnvironment["Realm"][0] == 1.0)
{
// Get the indices of all terrestrial functional groups
FunctionalGroupsToUse = functionalGroups.GetFunctionalGroupIndex("realm", "terrestrial", true);
NumCohortsThisCell = totalCellTerrestrialCohorts;
}
else
{
// Get the indices of all marine functional groups
FunctionalGroupsToUse = functionalGroups.GetFunctionalGroupIndex("realm", "marine", true);
NumCohortsThisCell = totalCellMarineCohorts;
}
Debug.Assert(cellEnvironment["Realm"][0] > 0.0, "Missing realm for grid cell");
if (NumCohortsThisCell > 0)
{
// Loop over all functional groups in the model
for (int FunctionalGroup = 0; FunctionalGroup < functionalGroups.GetNumberOfFunctionalGroups(); FunctionalGroup++)
{
// Create a new list to hold the cohorts in the grid cell
_GridCellCohorts[FunctionalGroup] = new List<Cohort>();
// If it is a functional group that corresponds to the current realm, then seed cohorts
if (FunctionalGroupsToUse.Contains(FunctionalGroup))
{
// Loop over the initial number of cohorts
double NumberOfCohortsInThisFunctionalGroup = 1.0;
if (!ZeroAbundance)
{
NumberOfCohortsInThisFunctionalGroup = functionalGroups.GetBiologicalPropertyOneFunctionalGroup("initial number of gridcellcohorts", FunctionalGroup);
}
for (int jj = 0; jj < NumberOfCohortsInThisFunctionalGroup; jj++)
{
// Check whether the model is set to randomly draw the body masses of new cohorts
if (DrawRandomly)
{
// Draw adult mass from a log-normal distribution with mean -6.9 and standard deviation 10.0,
// within the bounds of the minimum and maximum body masses for the functional group
CohortAdultMass = Math.Pow(10, (RandomNumberGenerator.GetUniform() * (Math.Log10(MassMaxima[FunctionalGroup]) - Math.Log10(50 * MassMinima[FunctionalGroup])) + Math.Log10(50 * MassMinima[FunctionalGroup])));
// Terrestrial and marine organisms have different optimal prey/predator body mass ratios
if (cellEnvironment["Realm"][0] == 1.0)
// Optimal prey body size 10%
OptimalPreyBodySizeRatio = Math.Max(0.01, RandomNumberGenerator.GetNormal(0.1, 0.02));
else
{
if (functionalGroups.GetTraitNames("Diet", FunctionalGroup) == "allspecial")
{
// Note that for this group
// it is actually (despite the name) not an optimal prey body size ratio, but an actual body size.
// This is because it is invariant as the predator (filter-feeding baleen whale) grows.
// See also the predation classes.
OptimalPreyBodySizeRatio = Math.Max(0.00001, RandomNumberGenerator.GetNormal(0.0001, 0.1));
}
else
{
// Optimal prey body size or marine organisms is 10%
OptimalPreyBodySizeRatio = Math.Max(0.01, RandomNumberGenerator.GetNormal(0.1, 0.02));
}
}
// Draw from a log-normal distribution with mean 10.0 and standard deviation 5.0, then add one to obtain
// the ratio of adult to juvenile body mass, and then calculate juvenile mass based on this ratio and within the
// bounds of the minimum and maximum body masses for this functional group
if (cellEnvironment["Realm"][0] == 1.0)
{
do
{
ExpectedLnAdultMassRatio = 2.24 + 0.13 * Math.Log(CohortAdultMass);
CohortAdultMassRatio = 1.0 + RandomNumberGenerator.GetLogNormal(ExpectedLnAdultMassRatio, 0.5);
CohortJuvenileMass = CohortAdultMass * 1.0 / CohortAdultMassRatio;
} while (CohortAdultMass <= CohortJuvenileMass || CohortJuvenileMass < MassMinima[FunctionalGroup]);
}
// In the marine realm, have a greater difference between the adult and juvenile body masses, on average
else
{
uint Counter = 0;
Scaling = 0.2;
// Use the scaling to deal with baleen whales not having such a great difference
do
{
ExpectedLnAdultMassRatio = 2.5 + Scaling * Math.Log(CohortAdultMass);
CohortAdultMassRatio = 1.0 + 10 * RandomNumberGenerator.GetLogNormal(ExpectedLnAdultMassRatio, 0.5);
CohortJuvenileMass = CohortAdultMass * 1.0 / CohortAdultMassRatio;
Counter++;
if (Counter > 10)
{
Scaling -= 0.01;
Counter = 0;
}
} while (CohortAdultMass <= CohortJuvenileMass || CohortJuvenileMass < MassMinima[FunctionalGroup]);
}
}
else
{
// Use the same seed for the random number generator every time
RandomNumberGenerator.SetSeed((uint)(jj + 1), (uint)((jj + 1) * 3));
// Draw adult mass from a log-normal distribution with mean -6.9 and standard deviation 10.0,
// within the bounds of the minimum and maximum body masses for the functional group
CohortAdultMass = Math.Pow(10, (RandomNumberGenerator.GetUniform() * (Math.Log10(MassMaxima[FunctionalGroup]) - Math.Log10(50 * MassMinima[FunctionalGroup])) + Math.Log10(50 * MassMinima[FunctionalGroup])));
OptimalPreyBodySizeRatio = Math.Max(0.01, RandomNumberGenerator.GetNormal(0.1, 0.02));
// Draw from a log-normal distribution with mean 10.0 and standard deviation 5.0, then add one to obtain
// the ratio of adult to juvenile body mass, and then calculate juvenile mass based on this ratio and within the
// bounds of the minimum and maximum body masses for this functional group
if (cellEnvironment["Realm"][0] == 1.0)
{
do
{
ExpectedLnAdultMassRatio = 2.24 + 0.13 * Math.Log(CohortAdultMass);
CohortAdultMassRatio = 1.0 + RandomNumberGenerator.GetLogNormal(ExpectedLnAdultMassRatio, 0.5);
CohortJuvenileMass = CohortAdultMass * 1.0 / CohortAdultMassRatio;
} while (CohortAdultMass <= CohortJuvenileMass || CohortJuvenileMass < MassMinima[FunctionalGroup]);
}
// In the marine realm, have a greater difference between the adult and juvenile body masses, on average
else
{
do
{
ExpectedLnAdultMassRatio = 2.24 + 0.13 * Math.Log(CohortAdultMass);
CohortAdultMassRatio = 1.0 + 10 * RandomNumberGenerator.GetLogNormal(ExpectedLnAdultMassRatio, 0.5);
CohortJuvenileMass = CohortAdultMass * 1.0 / CohortAdultMassRatio;
} while (CohortAdultMass <= CohortJuvenileMass || CohortJuvenileMass < MassMinima[FunctionalGroup]);
}
}
// An instance of Cohort to hold the new cohort
Cohort NewCohort;
//double NewBiomass = Math.Pow(0.2, (Math.Log10(CohortAdultMass))) * (1.0E9 * _CellEnvironment["Cell Area"][0]) / NumCohortsThisCell;
// 3000*(0.6^log(mass)) gives individual cohort biomass density in g ha-1
// * 100 to give g km-2
// * cell area to give g grid cell
//*3300/NumCohortsThisCell scales total initial biomass in the cell to some approximately reasonable mass
double NewBiomass = (3300 / NumCohortsThisCell) * 100 * 3000 *
Math.Pow(0.6, (Math.Log10(CohortJuvenileMass))) * (_CellEnvironment["Cell Area"][0]);
TotalNewBiomass += NewBiomass;
double NewAbund = 0.0;
if (!ZeroAbundance)
{
NewAbund = NewBiomass / CohortJuvenileMass;
}
/*
// TEMPORARILY MARINE ONLY
if (cellEnvironment["Realm"][0] == 1)
{
NewAbund = 0.0;
}
*/
double TrophicIndex;
switch (NutritionSource[FunctionalGroup])
{
case "herbivore":
TrophicIndex = 2;
break;
case "omnivore":
TrophicIndex = 2.5;
break;
case "carnivore":
TrophicIndex = 3;
break;
default:
Debug.Fail("Unexpected nutrition source trait value when assigning trophic index");
TrophicIndex = 0.0;
break;
}
// Initialise the new cohort with the relevant properties
NewCohort = new Cohort((byte)FunctionalGroup, CohortJuvenileMass, CohortAdultMass, CohortJuvenileMass, NewAbund,
OptimalPreyBodySizeRatio, (ushort)0, ProportionTimeActive[FunctionalGroup], ref CohortIDIncrementer,TrophicIndex, tracking);
// Add the new cohort to the list of grid cell cohorts
_GridCellCohorts[FunctionalGroup].Add(NewCohort);
// TEMPORARY
/*
// Check whether the model is set to randomly draw the body masses of new cohorts
if ((Longitude % 4 == 0) && (Latitude % 4 == 0))
{
if (DrawRandomly)
{
CohortAdultMass = 100000;
CohortJuvenileMass = 100000;
}
else
{
CohortAdultMass = 100000;
CohortJuvenileMass = 100000;
}
// An instance of Cohort to hold the new cohort
Cohort NewCohort;
double NewBiomass = (1.0E7 * _CellEnvironment["Cell Area"][0]) / NumCohortsThisCell;
double NewAbund = 0.0;
NewAbund = 3000;
// Initialise the new cohort with the relevant properties
NewCohort = new Cohort((byte)FunctionalGroup, CohortJuvenileMass, CohortAdultMass, CohortJuvenileMass, NewAbund,
(ushort)0, ref nextCohortID, tracking);
// Add the new cohort to the list of grid cell cohorts
_GridCellCohorts[FunctionalGroup].Add(NewCohort);
}
*/
// Incrememt the variable tracking the total number of cohorts in the model
globalDiagnostics["NumberOfCohortsInModel"]++;
}
}
}
}
else
{
// Loop over all functional groups in the model
for (int FunctionalGroup = 0; FunctionalGroup < functionalGroups.GetNumberOfFunctionalGroups(); FunctionalGroup++)
{
// Create a new list to hold the cohorts in the grid cell
_GridCellCohorts[FunctionalGroup] = new List<Cohort>();
}
}
// tempsw.Dispose();
}
public void OutputCurrentModelState(ModelGrid currentModelGrid, FunctionalGroupDefinitions functionalGroupHandler, List<uint[]> cellIndices, uint currentTimestep, int maximumNumberOfCohorts, string filename)
{
float[] Latitude = currentModelGrid.Lats;
float[] Longitude = currentModelGrid.Lons;
float[] CohortFunctionalGroup = new float[functionalGroupHandler.GetNumberOfFunctionalGroups()];
for (int fg = 0; fg < CohortFunctionalGroup.Length; fg++)
{
CohortFunctionalGroup[fg] = fg;
}
int CellCohortNumber = 0;
GridCellCohortHandler CellCohorts;
for (int cellIndex = 0; cellIndex < cellIndices.Count; cellIndex++)
{
CellCohorts = currentModelGrid.GetGridCellCohorts(cellIndices[cellIndex][0], cellIndices[cellIndex][1]);
for (int i = 0; i < CellCohorts.Count; i++)
{
if (CellCohorts[i].Count > CellCohortNumber) CellCohortNumber = CellCohorts[i].Count;
}
}
int MaxNumberCohorts = Math.Max(CellCohortNumber, maximumNumberOfCohorts);
float[] Cohort = new float[MaxNumberCohorts];
for (int c = 0; c < Cohort.Length; c++)
{
Cohort[c] = c;
}
//Define an array for stock functional group - there are only three currently
float[] StockFunctionalGroup = new float[] { 1, 2, 3 };
//Define an array for index of stocks - there is only one currently
float[] Stock = new float[] { 1 };
string Filename = filename + "_" + currentTimestep.ToString() + Simulation.ToString();
StateOutput = SDSCreator.CreateSDS("netCDF", Filename, _OutputPath);
//Define the cohort properties for output
string[] CohortProperties = new string[]
{"JuvenileMass", "AdultMass", "IndividualBodyMass", "CohortAbundance",
"BirthTimeStep", "MaturityTimeStep", "LogOptimalPreyBodySizeRatio",
"MaximumAchievedBodyMass","Merged","TrophicIndex","ProportionTimeActive"};
//define the dimensions for cohort outputs
string[] dims = new string[] { "Latitude", "Longitude", "Cohort Functional Group", "Cohort" };
// Add the variables for each cohort property
// Then calculate the state for this property and put the data to this variable
foreach (string v in CohortProperties)
{
DataConverter.AddVariable(StateOutput, "Cohort" + v, 4,
dims, currentModelGrid.GlobalMissingValue, Latitude,
Longitude, CohortFunctionalGroup, Cohort);
StateOutput.PutData<double[, , ,]>("Cohort" + v,
CalculateCurrentCohortState(currentModelGrid, v, Latitude.Length, Longitude.Length, CohortFunctionalGroup.Length, Cohort.Length, cellIndices));
StateOutput.Commit();
}
//Define the stock properties for output
string[] StockProperties = new string[] { "IndividualBodyMass", "TotalBiomass" };
//define the dimensions for cohort outputs
dims = new string[] { "Latitude", "Longitude", "Stock Functional Group", "Stock" };
// Add the variables for each stock property
// Then calculate the state for this property and put the data to this variable
foreach (string v in StockProperties)
{
DataConverter.AddVariable(StateOutput, "Stock" + v, 4,
dims, currentModelGrid.GlobalMissingValue, Latitude,
Longitude, StockFunctionalGroup, Stock);
StateOutput.PutData<double[, , ,]>("Stock" + v,
CalculateCurrentStockState(currentModelGrid, v, Latitude.Length, Longitude.Length, StockFunctionalGroup.Length, Stock.Length, cellIndices));
StateOutput.Commit();
}
//Close this data set
StateOutput.Dispose();
}
public void OutputCurrentModelState(ModelGrid currentModelGrid, FunctionalGroupDefinitions functionalGroupHandler, List <uint[]> cellIndices, uint currentTimestep, int maximumNumberOfCohorts, string filename)
{
float[] Latitude = currentModelGrid.Lats;
float[] Longitude = currentModelGrid.Lons;
float[] CohortFunctionalGroup = new float[functionalGroupHandler.GetNumberOfFunctionalGroups()];
for (int fg = 0; fg < CohortFunctionalGroup.Length; fg++)
{
CohortFunctionalGroup[fg] = fg;
}
int CellCohortNumber = 0;
GridCellCohortHandler CellCohorts;
for (int cellIndex = 0; cellIndex < cellIndices.Count; cellIndex++)
{
CellCohorts = currentModelGrid.GetGridCellCohorts(cellIndices[cellIndex][0], cellIndices[cellIndex][1]);
for (int i = 0; i < CellCohorts.Count; i++)
{
if (CellCohorts[i].Count > CellCohortNumber)
{
CellCohortNumber = CellCohorts[i].Count;
}
}
}
int MaxNumberCohorts = Math.Max(CellCohortNumber, maximumNumberOfCohorts);
float[] Cohort = new float[MaxNumberCohorts];
for (int c = 0; c < Cohort.Length; c++)
{
Cohort[c] = c;
}
//Define an array for stock functional group - there are only three currently
float[] StockFunctionalGroup = new float[] { 1, 2, 3 };
//Define an array for index of stocks - there is only one currently
float[] Stock = new float[] { 1 };
string Filename = filename + "_" + currentTimestep.ToString() + Simulation.ToString();
StateOutput = SDSCreator.CreateSDS("netCDF", Filename, _OutputPath);
//Define the cohort properties for output
string[] CohortProperties = new string[]
{ "JuvenileMass", "AdultMass", "IndividualBodyMass", "IndividualReproductivePotentialMass", "CohortAbundance",
"BirthTimeStep", "MaturityTimeStep", "LogOptimalPreyBodySizeRatio",
"MaximumAchievedBodyMass", "Merged", "TrophicIndex", "ProportionTimeActive" };
//define the dimensions for cohort outputs
string[] dims = new string[] { "Latitude", "Longitude", "Cohort Functional Group", "Cohort" };
// Add the variables for each cohort property
// Then calculate the state for this property and put the data to this variable
foreach (string v in CohortProperties)
{
DataConverter.AddVariable(StateOutput, "Cohort" + v, 4,
dims, currentModelGrid.GlobalMissingValue, Latitude,
Longitude, CohortFunctionalGroup, Cohort);
StateOutput.PutData <double[, , , ]>("Cohort" + v,
CalculateCurrentCohortState(currentModelGrid, v, Latitude.Length, Longitude.Length, CohortFunctionalGroup.Length, Cohort.Length, cellIndices));
StateOutput.Commit();
}
//Define the stock properties for output
string[] StockProperties = new string[] { "IndividualBodyMass", "TotalBiomass" };
//define the dimensions for cohort outputs
dims = new string[] { "Latitude", "Longitude", "Stock Functional Group", "Stock" };
// Add the variables for each stock property
// Then calculate the state for this property and put the data to this variable
foreach (string v in StockProperties)
{
DataConverter.AddVariable(StateOutput, "Stock" + v, 4,
dims, currentModelGrid.GlobalMissingValue, Latitude,
Longitude, StockFunctionalGroup, Stock);
StateOutput.PutData <double[, , , ]>("Stock" + v,
CalculateCurrentStockState(currentModelGrid, v, Latitude.Length, Longitude.Length, StockFunctionalGroup.Length, Stock.Length, cellIndices));
StateOutput.Commit();
}
//Close this data set
StateOutput.Dispose();
}
/// <summary>
/// Seed the stocks and cohorts from output from a previous simulation
/// </summary>
/// <param name="cellIndices">A list of the active cells in the model grid</param>
/// <param name="cohortFunctionalGroupDefinitions">The functional group definitions for cohorts in the model</param>
/// <param name="stockFunctionalGroupDefinitions">The functional group definitions for stocks in the model</param>
/// <param name="globalDiagnostics">A list of global diagnostic variables</param>
/// <param name="nextCohortID">The ID number to be assigned to the next produced cohort</param>
/// <param name="tracking">Whether process-tracking is enabled</param>
/// <param name="DrawRandomly">Whether the model is set to use a random draw</param>
/// <param name="dispersalOnly">Whether to run dispersal only (i.e. to turn off all other ecological processes</param>
/// <param name="processTrackers">An instance of the ecological process tracker</param>
public void SeedGridCellStocksAndCohorts(List<uint[]> cellIndices,
InputModelState inputModelState,
FunctionalGroupDefinitions cohortFunctionalGroupDefinitions,
FunctionalGroupDefinitions stockFunctionalGroupDefinitions)
{
int ii = 1;
Console.WriteLine("Seeding grid cell stocks and cohorts:");
//Check to see if the correct number of functional groups exist in the definitions file and in the input state
if (cohortFunctionalGroupDefinitions.GetNumberOfFunctionalGroups() != inputModelState.GridCellCohorts[
cellIndices[0][0],cellIndices[0][1]].Count)
{
Console.WriteLine("Mismatch in the number of functional groups defined in CohortFunctionalGroupDefinitions.csv set-up file and the Model State being read in");
Environment.Exit(0);
}
int[] TerrestrialStockFunctionalIndices = stockFunctionalGroupDefinitions.GetFunctionalGroupIndex("Realm", "Terrestrial", false);
int[] MarineStockFunctionalIndices = stockFunctionalGroupDefinitions.GetFunctionalGroupIndex("Realm", "Marine", false);
int[] TerrestrialCohortFunctionalIndices = cohortFunctionalGroupDefinitions.GetFunctionalGroupIndex("Realm", "Terrestrial", false);
int[] MarineCohortFunctionalIndices = cohortFunctionalGroupDefinitions.GetFunctionalGroupIndex("Realm", "Marine", false);
foreach (uint[] cellIndexPair in cellIndices)
{
for (int i = 0; i < inputModelState.GridCellCohorts[cellIndexPair[0], cellIndexPair[1]].Count; i++)
{
InternalGrid[cellIndexPair[0], cellIndexPair[1]].GridCellCohorts[i] = new List<Cohort>();
}
//Check which cohorts should be initialised for each cell
if (InternalGrid[cellIndexPair[0], cellIndexPair[1]].CellEnvironment["Realm"][0] == 1)
{
//This is a terrestrial cell so only add the terrestrial stocks
foreach (int fg in TerrestrialCohortFunctionalIndices)
{
//Cohort[] tempGridCellCohorts = (Cohort[])inputModelState.GridCellCohorts[cellIndexPair[0], cellIndexPair[1]][fg].ToArray().Clone();
//Cohort[] tempGridCellCohorts = (Cohort[])Array.ConvertAll(inputModelState.GridCellCohorts[cellIndexPair[0], cellIndexPair[1]][fg].ToArray(),
// element => (Cohort)element.Clone());
Cohort[] tempGridCellCohorts = inputModelState.GridCellCohorts[cellIndexPair[0], cellIndexPair[1]][fg].ToArray().Select(cohort => new Cohort(cohort)).ToArray();
InternalGrid[cellIndexPair[0], cellIndexPair[1]].GridCellCohorts[fg] = tempGridCellCohorts.ToList();
}
}
else
{
// this is a marine cell so only add the marine stocks
foreach (int fg in MarineCohortFunctionalIndices)
{
//Cohort[] tempGridCellCohorts = (Cohort[])inputModelState.GridCellCohorts[cellIndexPair[0], cellIndexPair[1]][fg].ToArray().Clone();
//Cohort[] tempGridCellCohorts = (Cohort[])Array.ConvertAll(inputModelState.GridCellCohorts[cellIndexPair[0], cellIndexPair[1]][fg].ToArray(),
// element => (Cohort)element.Clone());
Cohort[] tempGridCellCohorts = inputModelState.GridCellCohorts[cellIndexPair[0], cellIndexPair[1]][fg].ToArray().Select(cohort => new Cohort(cohort)).ToArray();
InternalGrid[cellIndexPair[0], cellIndexPair[1]].GridCellCohorts[fg] = tempGridCellCohorts.ToList();
}
}
for (int i = 0; i < inputModelState.GridCellStocks[cellIndexPair[0], cellIndexPair[1]].Count; i++)
{
InternalGrid[cellIndexPair[0], cellIndexPair[1]].GridCellStocks[i] = new List<Stock>();
}
//Check which stocks should be initialised for each cell
if (InternalGrid[cellIndexPair[0], cellIndexPair[1]].CellEnvironment["Realm"][0] == 1)
{
//This is a terrestrial cell so only add the terrestrial stocks
foreach (int fg in TerrestrialStockFunctionalIndices)
{
//Stock[] tempGridCellStocks = (Stock[])inputModelState.GridCellStocks[cellIndexPair[0], cellIndexPair[1]][fg].ToArray().Clone();
//Stock[] tempGridCellStocks = (Stock[])Array.ConvertAll(inputModelState.GridCellStocks[cellIndexPair[0], cellIndexPair[1]][fg].ToArray(),
// element => (Stock)element.Clone());
Stock[] tempGridCellStocks = inputModelState.GridCellStocks[cellIndexPair[0], cellIndexPair[1]][fg].ToArray().Select(stock => new Stock(stock)).ToArray();
InternalGrid[cellIndexPair[0], cellIndexPair[1]].GridCellStocks[fg] = tempGridCellStocks.ToList();
}
}
else
{
// this is a marine cell so only add the marine stocks
foreach (int fg in MarineStockFunctionalIndices)
{
//Stock[] tempGridCellStocks = (Stock[])inputModelState.GridCellStocks[cellIndexPair[0], cellIndexPair[1]][fg].ToArray().Clone();
//Stock[] tempGridCellStocks = (Stock[])Array.ConvertAll(inputModelState.GridCellStocks[cellIndexPair[0], cellIndexPair[1]][fg].ToArray(),
// element => (Stock)element.Clone());
Stock[] tempGridCellStocks = inputModelState.GridCellStocks[cellIndexPair[0], cellIndexPair[1]][fg].ToArray().Select(stock => new Stock(stock)).ToArray();
InternalGrid[cellIndexPair[0], cellIndexPair[1]].GridCellStocks[fg] = tempGridCellStocks.ToList();
}
}
Console.Write("\rGrid Cell: {0} of {1}", ii++, cellIndices.Count);
}
Console.WriteLine("");
Console.WriteLine("");
}
public void SaveTimestep(int currentTimestep)
{
UInt32 hh = this.CurrentTimeStep;
MadingleyModelInitialisation initialisation = this.ModelInitialisation;
// Temporary variables
Boolean varExists;
// For runs with specific locations and where track processes has been specified, write out mass flows data and reset the mass flow tracker
// for the next time step
if (SpecificLocations)
{
for (var cellIndex = 0; cellIndex < _CellList.Count; cellIndex++)
{
if (ProcessTrackers[cellIndex].TrackProcesses)
{
ProcessTrackers[cellIndex].EndTimeStepPredationTracking(CurrentTimeStep);
ProcessTrackers[cellIndex].EndTimeStepHerbvioryTracking(CurrentTimeStep);
}
}
}
if (TrackGlobalProcesses.TrackProcesses)
{
for (uint ii = 0; ii < StockFunctionalGroupDefinitions.GetNumberOfFunctionalGroups(); ii++)
{
TrackGlobalProcesses.StoreNPPGrid(hh, ii);
TrackGlobalProcesses.StoreHANPPGrid(hh, ii);
}
}
#endif
OutputTimer.Start();
// Write the global outputs for this time step
GlobalOutputs.TimeStepOutputs(EcosystemModelGrid, CurrentTimeStep, CurrentMonth, TimeStepTimer, CohortFunctionalGroupDefinitions,
StockFunctionalGroupDefinitions, _CellList, GlobalDiagnosticVariables, initialisation);
OutputTimer.Stop();
Console.WriteLine("Global Outputs took: {0}", OutputTimer.GetElapsedTimeSecs());
OutputTimer.Start();
if (SpecificLocations)
{
// Loop over grid cells and write (a) time step outputs, and (b) trophic flow data (if process tracking is on)
for (int i = 0; i < _CellList.Count; i++)
{
// Write out the grid cell outputs for this time step
CellOutputs[i].TimeStepOutputs(EcosystemModelGrid, CohortFunctionalGroupDefinitions, StockFunctionalGroupDefinitions,
_CellList, i, GlobalDiagnosticVariables, TimeStepTimer, NumTimeSteps, CurrentTimeStep, initialisation, CurrentMonth, EcosystemModelGrid.GetEnviroLayer("Realm", 0, _CellList[i][0], _CellList[i][1], out varExists) == 2.0);
// Write out trophic flow data for this time step
if (ProcessTrackers[i].TrackProcesses) ProcessTrackers[i].WriteTimeStepTrophicFlows(CurrentTimeStep, EcosystemModelGrid.NumLatCells, EcosystemModelGrid.NumLonCells, initialisation,
EcosystemModelGrid.GetEnviroLayer("Realm", 0, _CellList[i][0], _CellList[i][1], out varExists) == 2.0);
}
}
else
{
// Write out grid outputs for this time step
GridOutputs.TimeStepOutputs(EcosystemModelGrid, CohortFunctionalGroupDefinitions, StockFunctionalGroupDefinitions, _CellList,
CurrentTimeStep, initialisation);
}
OutputTimer.Stop();
Console.WriteLine("Cell/Grid Outputs took: {0}", OutputTimer.GetElapsedTimeSecs());
// Write the results of dispersal to the console
Console.ForegroundColor = ConsoleColor.Green;
Console.WriteLine("Number of cohorts that dispersed this time step: {0}\n", Dispersals);
Console.ForegroundColor = ConsoleColor.White;
Dispersals = 0;
if (OutputModelStateTimestep.Contains(hh))
{
OutputTimer.Start();
Console.WriteLine("Outputting model state");
//Writing to text based output
WriteModelState.OutputCurrentModelState(EcosystemModelGrid, _CellList, hh);
WriteModelState.OutputCurrentModelState(EcosystemModelGrid, CohortFunctionalGroupDefinitions, _CellList, CurrentTimeStep, initialisation.MaxNumberOfCohorts, "ModelState");
OutputTimer.Stop();
// Write the results of dispersal to the console
Console.ForegroundColor = ConsoleColor.Green;
Console.WriteLine("Writing model state took: {0}", OutputTimer.GetElapsedTimeSecs());
Console.ForegroundColor = ConsoleColor.White;
/*ReadModelState = new InputModelState(
initialisation.OutputPath,
"ModelState0");*/
}
}