Inheritance diagram for javawrapper::DisperseBehaviors:
Public Member Functions | |
DisperseBehaviors (GUIManager oManager) | |
Constructor. | |
void | DoSetup (TreePopulation oPop) throws ModelException |
Does setup. | |
void | ValidateData (TreePopulation oPop) throws ModelException |
Validates the data in preparation for parameter file writing or some such. | |
Static Public Attributes | |
static final int | WEIBULL = 0 |
Weibull disperse function. | |
static final int | LOGNORMAL = 1 |
Lognormal disperse function. | |
static final int | CANOPY = 0 |
Canopy forest cover status for cells. | |
static final int | GAP = 1 |
Gap forest cover status for cells. | |
static final int | NUMBER_OF_DISPERSE_FUNCTIONS = 2 |
Total number of disperse functions. | |
static final int | NUMBER_OF_FOREST_COVERS = 2 |
Total number of forest cover statuses. | |
Private Attributes | |
ModelVector[][] | mp_fSTR |
STR for disperse function. | |
ModelVector[][] | mp_fBeta |
Beta for disperse function. | |
ModelVector[][] | mp_fThetaOrXb |
Theta (if weibull) or Xb (if lognormal) for disperse function. | |
ModelVector[][] | mp_fDispOrX0 |
Dispersal (if weibull) or X0 (if lognormal) for disperse function. | |
ModelVector[] | mp_iWhichFunctionUsed |
Which disperse function to use under each forest cover - valid values are WEIBULL and LOGNORMAL - this is a vector of ModelEnums. | |
ModelVector | mp_fSlopeOfLambda |
Slope of lambda for non spatial dispersal for each species. | |
ModelVector | mp_fInterceptOfLambda |
Intercept of lambda for non spatial dispersal for each species. | |
ModelVector | mp_fMinDbhForReproduction |
Minimum DBH for reproduction for each species. | |
ModelVector | mp_fStumpSTR |
STR for stump dispersal for each species. | |
ModelVector | mp_fStumpBeta |
Beta for stump dispersal for each species. | |
ModelVector | mp_fDirectionMaxDispersal |
Azimuth direction of maximum dispersal distance, in radians. | |
ModelVector | mp_fAnisotropicAmplitude |
Amplitude of anisotropic effect. | |
ModelVector | mp_fStandardDeviation |
Standard deviation if seed distribution method is normal or lognormal. | |
ModelVector | mp_fClumpingParameter |
Clumping parameter if seed distribution is negative binomial. | |
ModelEnum | m_iSeedDistributionMethod |
Seed distribution. | |
ModelFloat | m_fMaxSearchRadius |
Maximum search radius, in meters, for neighbors for isotropic and anisotropic disperse. | |
ModelInt | m_iMaxGapDensity |
Max number of parent trees that can be in a grid cell for it to still be marked as gap. |
Copyright: Copyright (c) Charles D. Canham 2003
Company: Institute of Ecosystem Studies
javawrapper::DisperseBehaviors::DisperseBehaviors | ( | GUIManager | oManager | ) | [inline] |
Constructor.
oManager | GUIManager object. |
void javawrapper::DisperseBehaviors::DoSetup | ( | TreePopulation | oPop | ) | throws ModelException [inline, virtual] |
Does setup.
Sets up the substrate favorability grid.
oPop | TreePopulation object. |
ModelException | if there's a problem setting behavior use data. |
Implements javawrapper::WorkerBase.
void javawrapper::DisperseBehaviors::ValidateData | ( | TreePopulation | oPop | ) | throws ModelException [inline, virtual] |
Validates the data in preparation for parameter file writing or some such.
oPop | TreePopulation object. |
ModelException | if:
|
Implements javawrapper::WorkerBase.
Initial value:
new ModelFloat(0, "Maximum Search Distance for Neighbor Parents, in m", "di_maxSearchRadius")
Initial value:
new ModelInt(0, "Maximum Parent Trees Allowed in Gap Cell", "di_maxGapDensity")
Initial value:
new ModelEnum(new int[] {0, 1, 2, 3, 4} , new String[] {"Deterministic", "Poisson", "Lognormal", "Normal", "Negative binomial"} , "Seed Distribution", "di_seedDistributionMethod")
Initial value:
new ModelVector( "Amplitude of Anisotropic Effect", "di_anisotropicAmplitude", "di_aaVal", 0, ModelVector.FLOAT)
ModelVector [][] javawrapper::DisperseBehaviors::mp_fBeta [private] |
Beta for disperse function.
Array is 3D - first index is which disperse function is used - weibull or lognormal. The second index is cover - canopy or gap. The third index is species.
Initial value:
new ModelVector( "Seed Dist. Clumping Parameter (Neg. Binomial)", "di_clumpingParameter", "di_cpVal", 0, ModelVector.FLOAT)
Initial value:
new ModelVector( "Azimuth Direction of Max Dispersal Distance, in rad", "di_directionMaxDispersal", "di_dmdVal", 0, ModelVector.FLOAT)
ModelVector [][] javawrapper::DisperseBehaviors::mp_fDispOrX0 [private] |
Dispersal (if weibull) or X0 (if lognormal) for disperse function.
Array is 3D - first index is which disperse function is used - weibull or lognormal. The second index is cover - canopy or gap. The third index is species.
Initial value:
new ModelVector( "Intercept of Mean Non-Spatial Seed Rain, seeds/m2/yr", "di_nonSpatialInterceptOfLambda", "di_nsiolVal", 0, ModelVector.FLOAT)
Initial value:
new ModelVector( "Slope Mean Non-Spatial Seed Rain, seeds/m2/ha of BA/yr", "di_nonSpatialSlopeOfLambda", "di_nssolVal", 0, ModelVector.FLOAT)
Initial value:
new ModelVector( "Seed Dist. Std. Deviation (Normal or Lognormal)", "di_standardDeviation", "di_sdVal", 0, ModelVector.FLOAT)
ModelVector [][] javawrapper::DisperseBehaviors::mp_fSTR [private] |
STR for disperse function.
Array is 3D - first index is which disperse function is used - weibull or lognormal. The second index is cover - canopy or gap. The third index is species.
ModelVector [][] javawrapper::DisperseBehaviors::mp_fThetaOrXb [private] |
Theta (if weibull) or Xb (if lognormal) for disperse function.
Array is 3D - first index is which disperse function is used - weibull or lognormal. The second index is cover - canopy or gap. The third index is species.