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java.lang.Object uk.ac.leeds.ccg.andyt.grids.utilities.ErrorHandler uk.ac.leeds.ccg.andyt.grids.process.Grid2DSquareCellProcessor uk.ac.leeds.ccg.andyt.grids.process.Grid2DSquareCellProcessorDEM
public class Grid2DSquareCellProcessorDEM
A class of methods relevant to the processing of Digital Elevation Model Data.
Field Summary 

Fields inherited from class uk.ac.leeds.ccg.andyt.grids.process.Grid2DSquareCellProcessor 

grid2DSquareCells, log, logIndentation, startTime, workspace 
Fields inherited from class uk.ac.leeds.ccg.andyt.grids.utilities.ErrorHandler 

handleOutOfMemoryErrorFalse, handleOutOfMemoryErrorTrue, memoryReserve 
Constructor Summary  

Grid2DSquareCellProcessorDEM()
Creates a new Grid2DSquareCellDoubleProcessorDEM 
Method Summary  

Grid2DSquareCellDouble 
doFlowAccumulation(Grid2DSquareCellDouble flowAccumulation,
Grid2DSquareCellDouble grid,
double precipitation,
java.util.HashSet outflowCellIDs,
Grid2DSquareCellDoubleFactory gridFactory)
TODO: docs frictionFactor = 75.0d; constant = 8.0d * 9.81d / frictionFactor; velocity = Math.sqrt( constant * waterDepth * changeInDepth / ChangeInLength ); discharge = velocity * waterDepth 
Grid2DSquareCellDouble 
getFlowAccumulation(Grid2DSquareCellDouble grid,
int iterations,
double precipitation,
java.util.HashSet outflowCellIDs,
Grid2DSquareCellDoubleFactory gridFactory)
There are many estimates of flow that can be generated and many models developed in hydrology. 
Grid2DSquareCellDouble 
getHollowFilledDEM(Grid2DSquareCellDouble grid,
double outflowHeight,
int maxIterations,
java.util.HashSet outflowCellIDsSet,
Grid2DSquareCellDoubleFactory gridFactory)
Returns an Grid2DSquareCellDouble hollowFilledDEM which has cell values as in grid except with any hollows raised so that they are not hollows. 
Grid2DSquareCellDouble 
getInitialFlowAccumulation(Grid2DSquareCellDouble grid,
double precipitation,
java.util.HashSet outflowCellIDs,
Grid2DSquareCellDoubleFactory gridFactory)
TODO: docs frictionFactor = 75.0d; constant = 8.0d * 9.81d / frictionFactor; velocity = Math.sqrt( constant * waterDepth * changeInDepth / ChangeInLength ); discharge = velocity * waterDepth 
java.util.HashSet 
getInitialPeaksHashSetAndSetTheirValue(Grid2DSquareCellDouble grid,
Grid2DSquareCellDouble upSlopeAreaMetrics)
Returns a HashSet containing cellIDs which identifies cells for which neighbouring cells in the immediate 8 cell neighbourhood that are either the same value, lower or noDataValues 
Grid2DSquareCellDouble 
getMaxFlowDirection(Grid2DSquareCellDouble grid,
Grid2DSquareCellDoubleFactory gridFactory)
Returns an Grid2DSquareCellDouble result containing values which indicate the direction of the maximum down slope for the immediate 8 cell neighbourhood. 
Grid2DSquareCellDouble[] 
getMetrics1(Grid2DSquareCellDouble[] metrics1,
Grid2DSquareCellDouble grid,
java.math.BigDecimal[] dimensions,
double distance,
double weightIntersect,
double weightFactor)
Returns an Grid2DSquareCellDouble[] metrics1 where: metrics1[0] = no data count; metrics1[1] = flatness; metrics1[2] = roughness; metrics1[3] = slopyness; metrics1[4] = levelness; metrics1[5] = totalDownness; metrics1[6] = averageDownness; metrics1[7] = totalUpness; metrics1[8] = averageUpness; metrics1[9] = maxd_hhhh [ sum of distance weighted maximum height differences ]; metrics1[10] = mind_hhhh [ sum of distance weighted minimum height differences ]; metrics1[11] = sumd_hhhh [ sum of distance weighted height differences ]; metrics1[12] = aved_hhhh [ sum of distance weighted average height difference ]; metrics1[13] = count_hhhh [ count ]; metrics1[14] = w_hhhh [ sum of distance weights ]; metrics1[15] = mind_hxhx_ai_hhhl [ sum of distance weighted ( minimum difference of cells adjacent to lower cell ) ]; metrics1[16] = maxd_hxhx_ai_hhhl [ sum of distance weighted ( maximum difference of cells adjacent to lower cell ) ]; metrics1[17] = sumd_hxhx_ai_hhhl [ sum of distance weighted ( sum of differences of cells adjacent to lower cell ) ]; metrics1[18] = d_xhxx_ai_hhhl [ sum of distance weighted ( difference of cell opposite lower cell ) ]; metrics1[19] = d_xxxl_ai_hhhl [ sum of distance weighted ( difference of lower cell ) ]; metrics1[20] = sumd_xhxl_ai_hhhl [ sum of distance weighted ( sum of differences of lower cell and cell opposite ) ]; metrics1[21] = mind_abs_xhxl_ai_hhhl [ sum of distance weighted ( minimum difference magnitude of lower cell and cell opposite ) ]; metrics1[22] = maxd_abs_xhxl_ai_hhhl [ sum of distance weighted ( maximum difference magnitude of lower cell and cell opposite ) ]; metrics1[23] = sumd_abs_xhxl_ai_hhhl [ sum of distance weighted ( sum of difference magnitudes of lower cell and cell opposite ) ]; metrics1[24] = count_hhhl [ count ]; metrics1[25] = w_hhhl [ sum of distance weights ]; metrics1[26] = mind_hxhx_ai_hlhl [ sum of distance weighted ( minimum difference of higher cells ) ]; metrics1[27] = maxd_hxhx_ai_hlhl [ sum of distance weighted ( maximum difference of higher cells ) ]; metrics1[28] = sumd_hxhx_ai_hlhl [ sum of distance weighted ( sum differences of higher cells ) ]; metrics1[29] = mind_xlxl_ai_hlhl [ sum of distance weighted ( minimum difference of lower cells ) ]; metrics1[30] = maxd_xlxl_ai_hlhl [ sum of distance weighted ( maximum difference of lower cells ) ]; metrics1[31] = sumd_xlxl_ai_hlhl [ sum of distance weighted ( sum of differences of lower cells ) ]; metrics1[32] = mind_abs_hlhl [ sum of distance weighted ( minimum difference magnitude of cells ) ]; metrics1[33] = maxd_abs_hlhl [ sum of distance weighted ( maximum difference magnitude of cells ) ]; metrics1[34] = sumd_abs_hlhl [ sum of distance weighted ( sum of difference magnitudes of cells ) ]; metrics1[35] = count_hlhl [ count ]; metrics1[36] = w_hlhl [ sum of distance weights ]; metrics1[37] = mind_hhxx_ai_hhll [ sum of distance weighted ( minimum difference of higher cells ) ]; metrics1[38] = maxd_hhxx_ai_hhll [ sum of distance weighted ( maximum difference of higher cells ) ]; metrics1[39] = sumd_hhxx_ai_hhll [ sum of distance weighted ( sum of differences of higher cells ) ]; metrics1[40] = mind_xxll_ai_hhll [ sum of distance weighted ( minimum difference of lower cells ) ]; metrics1[41] = maxd_xxll_ai_hhll [ sum of distance weighted ( maximum difference of lower cells ) ]; metrics1[42] = sumd_xxll_ai_hhll [ sum of distance weighted ( sum of differences of lower cells ) ]; metrics1[43] = mind_abs_hhll [ sum of distance weighted ( minimum difference magnitude of cells ) ]; metrics1[44] = maxd_abs_hhll [ sum of distance weighted ( maximum difference magnitude of cells ) ]; metrics1[45] = sumd_abs_hhll [ sum of distance weighted ( sum of difference magnitudes of cells ) ]; metrics1[46] = count_hhll [ count ]; metrics1[47] = w_hhll [ sum of distance weights ]; metrics1[48] = mind_lxlx_ai_lllh [ sum of distance weighted ( minimum difference of cells adjacent to higher cell ) ]; metrics1[49] = maxd_lxlx_ai_lllh [ sum of distance weighted ( maximum difference of cells adjacent to higher cell ) ]; metrics1[50] = sumd_lxlx_ai_lllh [ sum of distance weighted ( sum of differences of cells adjacent to higher cell ) ]; metrics1[51] = d_xlxx_ai_lllh [ sum of distance weighted ( difference of cell opposite higher cell ) ]; metrics1[52] = d_xxxh_ai_lllh [ sum of distance weighted ( difference of higher cell ) ]; metrics1[53] = sumd_xlxh_ai_lllh [ sum of distance weighted ( sum of differences of higher cell and cell opposite ) ]; metrics1[54] = mind_abs_xlxh_ai_lllh [ sum of distance weighted ( minimum difference magnitude of higher cell and cell opposite ) ]; metrics1[55] = maxd_abs_xlxh_ai_lllh [ sum of distance weighted ( maximum difference magnitude of higher cell and cell opposite ) ]; metrics1[56] = sumd_abs_xlxh_ai_lllh [ sum of distance weighted ( sum of difference magnitudes of higher cell and cell opposite ) ]; metrics1[57] = count_lllh [ count ]; metrics1[58] = w_lllh [ sum of distance weights ]; metrics1[59] = maxd_llll [ sum of distance weighted maximum height differences ]; metrics1[60] = mind_llll [ sum of distance weighted minimum height differences ]; metrics1[61] = sumd_llll [ sum of distance weighted height differences ]; metrics1[62] = aved_llll [ sum of distance weighted average height difference ]; metrics1[63] = count_llll [ count ]; metrics1[64] = w_llll [ sum of distance weights ]; 
Grid2DSquareCellDouble[] 
getMetrics1(Grid2DSquareCellDouble grid,
double distance,
double weightIntersect,
double weightFactor,
Grid2DSquareCellDoubleFactory gridFactory)
Returns an Grid2DSquareCellDouble[] metrics1 where: metrics1[0] = no data count; metrics1[1] = flatness; metrics1[2] = roughness; metrics1[3] = slopyness; metrics1[4] = levelness; metrics1[5] = totalDownness; metrics1[6] = averageDownness; metrics1[7] = totalUpness; metrics1[8] = averageUpness; metrics1[9] = maxd_hhhh [ sum of distance weighted maximum height differences ]; metrics1[10] = mind_hhhh [ sum of distance weighted minimum height differences ]; metrics1[11] = sumd_hhhh [ sum of distance weighted height differences ]; metrics1[12] = aved_hhhh [ sum of distance weighted average height difference ]; metrics1[13] = count_hhhh [ count ]; metrics1[14] = w_hhhh [ sum of distance weights ]; metrics1[15] = mind_hxhx_ai_hhhl [ sum of distance weighted ( minimum difference of cells adjacent to lower cell ) ]; metrics1[16] = maxd_hxhx_ai_hhhl [ sum of distance weighted ( maximum difference of cells adjacent to lower cell ) ]; metrics1[17] = sumd_hxhx_ai_hhhl [ sum of distance weighted ( sum of differences of cells adjacent to lower cell ) ]; metrics1[18] = d_xhxx_ai_hhhl [ sum of distance weighted ( difference of cell opposite lower cell ) ]; metrics1[19] = d_xxxl_ai_hhhl [ sum of distance weighted ( difference of lower cell ) ]; metrics1[20] = sumd_xhxl_ai_hhhl [ sum of distance weighted ( sum of differences of lower cell and cell opposite ) ]; metrics1[21] = mind_abs_xhxl_ai_hhhl [ sum of distance weighted ( minimum difference magnitude of lower cell and cell opposite ) ]; metrics1[22] = maxd_abs_xhxl_ai_hhhl [ sum of distance weighted ( maximum difference magnitude of lower cell and cell opposite ) ]; metrics1[23] = sumd_abs_xhxl_ai_hhhl [ sum of distance weighted ( sum of difference magnitudes of lower cell and cell opposite ) ]; metrics1[24] = count_hhhl [ count ]; metrics1[25] = w_hhhl [ sum of distance weights ]; metrics1[26] = mind_hxhx_ai_hlhl [ sum of distance weighted ( minimum difference of higher cells ) ]; metrics1[27] = maxd_hxhx_ai_hlhl [ sum of distance weighted ( maximum difference of higher cells ) ]; metrics1[28] = sumd_hxhx_ai_hlhl [ sum of distance weighted ( sum differences of higher cells ) ]; metrics1[29] = mind_xlxl_ai_hlhl [ sum of distance weighted ( minimum difference of lower cells ) ]; metrics1[30] = maxd_xlxl_ai_hlhl [ sum of distance weighted ( maximum difference of lower cells ) ]; metrics1[31] = sumd_xlxl_ai_hlhl [ sum of distance weighted ( sum of differences of lower cells ) ]; metrics1[32] = mind_abs_hlhl [ sum of distance weighted ( minimum difference magnitude of cells ) ]; metrics1[33] = maxd_abs_hlhl [ sum of distance weighted ( maximum difference magnitude of cells ) ]; metrics1[34] = sumd_abs_hlhl [ sum of distance weighted ( sum of difference magnitudes of cells ) ]; metrics1[35] = count_hlhl [ count ]; metrics1[36] = w_hlhl [ sum of distance weights ]; metrics1[37] = mind_hhxx_ai_hhll [ sum of distance weighted ( minimum difference of higher cells ) ]; metrics1[38] = maxd_hhxx_ai_hhll [ sum of distance weighted ( maximum difference of higher cells ) ]; metrics1[39] = sumd_hhxx_ai_hhll [ sum of distance weighted ( sum of differences of higher cells ) ]; metrics1[40] = mind_xxll_ai_hhll [ sum of distance weighted ( minimum difference of lower cells ) ]; metrics1[41] = maxd_xxll_ai_hhll [ sum of distance weighted ( maximum difference of lower cells ) ]; metrics1[42] = sumd_xxll_ai_hhll [ sum of distance weighted ( sum of differences of lower cells ) ]; metrics1[43] = mind_abs_hhll [ sum of distance weighted ( minimum difference magnitude of cells ) ]; metrics1[44] = maxd_abs_hhll [ sum of distance weighted ( maximum difference magnitude of cells ) ]; metrics1[45] = sumd_abs_hhll [ sum of distance weighted ( sum of difference magnitudes of cells ) ]; metrics1[46] = count_hhll [ count ]; metrics1[47] = w_hhll [ sum of distance weights ]; metrics1[48] = mind_lxlx_ai_lllh [ sum of distance weighted ( minimum difference of cells adjacent to higher cell ) ]; metrics1[49] = maxd_lxlx_ai_lllh [ sum of distance weighted ( maximum difference of cells adjacent to higher cell ) ]; metrics1[50] = sumd_lxlx_ai_lllh [ sum of distance weighted ( sum of differences of cells adjacent to higher cell ) ]; metrics1[51] = d_xlxx_ai_lllh [ sum of distance weighted ( difference of cell opposite higher cell ) ]; metrics1[52] = d_xxxh_ai_lllh [ sum of distance weighted ( difference of higher cell ) ]; metrics1[53] = sumd_xlxh_ai_lllh [ sum of distance weighted ( sum of differences of higher cell and cell opposite ) ]; metrics1[54] = mind_abs_xlxh_ai_lllh [ sum of distance weighted ( minimum difference magnitude of higher cell and cell opposite ) ]; metrics1[55] = maxd_abs_xlxh_ai_lllh [ sum of distance weighted ( maximum difference magnitude of higher cell and cell opposite ) ]; metrics1[56] = sumd_abs_xlxh_ai_lllh [ sum of distance weighted ( sum of difference magnitudes of higher cell and cell opposite ) ]; metrics1[57] = count_lllh [ count ]; metrics1[58] = w_lllh [ sum of distance weights ]; metrics1[59] = maxd_llll [ sum of distance weighted maximum height differences ]; metrics1[60] = mind_llll [ sum of distance weighted minimum height differences ]; metrics1[61] = sumd_llll [ sum of distance weighted height differences ]; metrics1[62] = aved_llll [ sum of distance weighted average height difference ]; metrics1[63] = count_llll [ count ]; metrics1[64] = w_llll [ sum of distance weights ]; 
Grid2DSquareCellDouble[] 
getMetrics2(Grid2DSquareCellDouble grid,
double distance,
double weightIntersect,
double weightFactor,
int samplingDensity,
Grid2DSquareCellDoubleFactory gridFactory)
Returns an Grid2DSquareCellDouble[] metrics2 where: TODO: metrics2 is a mess. 
protected double[] 
getSlopeAndAspect(Grid2DSquareCellDouble grid,
double x,
double y,
double distance,
double weightIntersect,
double weightFactor)
Returns a double[] slopeAndAspect where: slopeAndAspect[0] is the aggregate slope over the region weighted by distance, weightIntersect and weightFactor; slopeAndAspect[1] is the aggregate aspect over the region weighted by distance, weightIntersect and weightFactor. 
Grid2DSquareCellDouble[] 
getSlopeAndAspect(Grid2DSquareCellDouble grid,
double distance,
double weightIntersect,
double weightFactor,
Grid2DSquareCellDouble slopeAndAspectDimensions,
Grid2DSquareCellDoubleFactory gridFactory)
Returns an Grid2DSquareCellDouble[] slopeAndAspect where: slopeAndAspect[0] is the aggregate slope over the region weighted by distance, weightIntersect and weightFactor; slopeAndAspect[1] is the aggregate aspect over the region weighted by distance, weightIntersect and weightFactor. 
Grid2DSquareCellDouble[] 
getSlopeAndAspect(Grid2DSquareCellDouble grid,
Grid2DSquareCellDoubleFactory gridFactory)
Returns an Grid2DSquareCellDouble[] slopeAndAspect where: slopeAndAspect[0] is the aggregate slope over the region weighted by distance, weightIntersect and weightFactor; slopeAndAspect[1] is the aggregate aspect over the region weighted by distance, weightIntersect and weightFactor. 
protected double[] 
getSlopeAndAspect(Grid2DSquareCellDouble grid,
long rowIndex,
long colIndex,
double distance,
double weightIntersect,
double weightFactor)
Returns a double[] slopeAndAspect where: slopeAndAspect[0] is the aggregate slope over the region weighted by distance, weightIntersect and weightFactor; slopeAndAspect[1] is the aggregate aspect over the region weighted by distance, weightIntersect and weightFactor. 
protected double[] 
getSlopeAndAspect(Grid2DSquareCellDouble grid,
long rowIndex,
long colIndex,
double x,
double y,
double distance,
double weightIntersect,
double weightFactor)
Returns a double[] slopeAndAspect where: slopeAndAspect[0] is the aggregate slope over the region weighted by distance, weightIntersect and weightFactor; slopeAndAspect[1] is the aggregate aspect over the region weighted by distance, weightIntersect and weightFactor. 
Grid2DSquareCellDouble 
getUpSlopeAreaMetrics(Grid2DSquareCellDouble grid,
double distance,
double weightFactor,
double weightIntersect,
Grid2DSquareCellDoubleFactory gridFactory)
Returns an Grid2DSquareCellDouble[] each element of which corresponds to a metrics of up slope cells of grid  a DEM The steeper the slope the higher the runoff? 
Methods inherited from class uk.ac.leeds.ccg.andyt.grids.process.Grid2DSquareCellProcessor 

add, addToGrid, addToGrid, addToGrid, addToGrid, addToGrid, addToGrid, addToGrid, addToGrid, addToGrid, addToGrid, aggregate, aggregate, copyAndSetUpNewLog, distanceToDataValue, divide, freeMemoryOrThrowError, getGrid2DSquareCells, getRowProcessData, getRowProcessInitialData, getTime0, getWorkspace, initWorkspace, linearRescale, linearRescale, log, log, logRescale, logRescale, mask, mask, mask, mask, mask, mask, minus, multiply, replace, setValueALittleBitLarger, setValueALittleBitLarger, setValueALittleBitSmaller, setValueALittleBitSmaller, setWorkspace, setWorkspace 
Methods inherited from class uk.ac.leeds.ccg.andyt.grids.utilities.ErrorHandler 

clearMemoryReserve, initMemoryReserve, initMemoryReserve 
Methods inherited from class java.lang.Object 

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait 
Constructor Detail 

public Grid2DSquareCellProcessorDEM()
Method Detail 

public Grid2DSquareCellDouble[] getSlopeAndAspect(Grid2DSquareCellDouble grid, Grid2DSquareCellDoubleFactory gridFactory)
grid
 the Grid2DSquareCellDouble to be processed.gridFactory
 the factory used for constructing slopeAndAspect.public Grid2DSquareCellDouble[] getSlopeAndAspect(Grid2DSquareCellDouble grid, double distance, double weightIntersect, double weightFactor, Grid2DSquareCellDouble slopeAndAspectDimensions, Grid2DSquareCellDoubleFactory gridFactory)
grid
 the Grid2DSquareCellDouble to be processed.distance
 the distance which defines the aggregate region.weightIntersect
 the kernel weighting weight at centre.weightFactor
 the kernel weighting distance decay.slopeAndAspectDimensions
 is an AbstractGrid2DSquareCellDouble
used for setting the resolutions, dimensions and noDataValue of
slopeAndAspect.gridFactory
 the factory used for generating slopeAndAspect.
(NB. There are various strategies to reduce bias caused by noDataValues.
Here:
If the cell in grid for which slopeAndAspect is being calculated is a
noDataValue then the cells in slopeAndAspect are assigned their
noDataValue.
If one of the cells in the calculation of slope and aspect is a
noDataValue then its height is taken as the nearest cell value.
(Formerly the difference in its height was taken as the average
difference in height for those cells with values.)
)protected double[] getSlopeAndAspect(Grid2DSquareCellDouble grid, long rowIndex, long colIndex, double distance, double weightIntersect, double weightFactor)
grid
 the Grid2DSquareCellDouble to be processed.rowIndex
 the rowIndex where slopeAndAspect is calculated.colIndex
 the colIndex where slopeAndAspect is calculated.distance
 the distance which defines the aggregate region.weightIntersect
 the kernel weighting weight at centre.weightFactor
 the kernel weighting distance decay.protected double[] getSlopeAndAspect(Grid2DSquareCellDouble grid, double x, double y, double distance, double weightIntersect, double weightFactor)
grid
 the Grid2DSquareCellDouble to be processed.x
 the x coordinate from where the aspect is calculatedy
 the y coordinate from where the aspect is calculateddistance
 the distance which defines the aggregate region.weightIntersect
 the kernel weighting weight at centre.weightFactor
 the kernel weighting distance decay.protected double[] getSlopeAndAspect(Grid2DSquareCellDouble grid, long rowIndex, long colIndex, double x, double y, double distance, double weightIntersect, double weightFactor)
grid
  the Grid2DSquareCellDouble to be processedrowIndex
 the rowIndex where the result is calculatedcolIndex
 the colIndex where the result is calculatedx
 the x coordinate from where the aspect is calculatedy
 the y coordinate from where the aspect is calculateddistance
 the distance which defines the regionweightIntersect
 weightFactor
 NB. If grid.getCell( x, y ) == grid.getNoDataValue() then;
result[ 0 ] = grid.getNoDataValue()
result[ 1 ] = grid.getNoDataValue()
TODO:
x and y can be offset from a cell centroid so consider interpolationpublic Grid2DSquareCellDouble getHollowFilledDEM(Grid2DSquareCellDouble grid, double outflowHeight, int maxIterations, java.util.HashSet outflowCellIDsSet, Grid2DSquareCellDoubleFactory gridFactory)
grid
 the Grid2DSquareCellDouble to be processedpublic Grid2DSquareCellDouble[] getMetrics1(Grid2DSquareCellDouble grid, double distance, double weightIntersect, double weightFactor, Grid2DSquareCellDoubleFactory gridFactory)
grid
 the Grid2DSquareCellDouble to be processeddistance
 the distance within which metrics will be calculatedweightIntersect
 kernel parameter ( weight at the centre )weightFactor
 kernel parameter ( distance decay )gridFactory
 the preferred factory for creating gridspublic Grid2DSquareCellDouble[] getMetrics1(Grid2DSquareCellDouble[] metrics1, Grid2DSquareCellDouble grid, java.math.BigDecimal[] dimensions, double distance, double weightIntersect, double weightFactor)
metrics1
 an Grid2DSquareCellDouble[] for storing resultgrid
 the Grid2DSquareCellDouble to be processeddistance
 the distance within which metrics will be calculatedweightIntersect
 kernel parameter ( weight at the centre )weightFactor
 kernel parameter ( distance decay )
Going directly to this method is useful if the initialisation of the
metrics1 is slow and has already been done.public Grid2DSquareCellDouble[] getMetrics2(Grid2DSquareCellDouble grid, double distance, double weightIntersect, double weightFactor, int samplingDensity, Grid2DSquareCellDoubleFactory gridFactory)
public Grid2DSquareCellDouble getMaxFlowDirection(Grid2DSquareCellDouble grid, Grid2DSquareCellDoubleFactory gridFactory)
grid
 the Grid2DSquareCellDouble to be processedgridFactory
 the Grid2DSquareCellDoubleFactory used to create resultpublic Grid2DSquareCellDouble getUpSlopeAreaMetrics(Grid2DSquareCellDouble grid, double distance, double weightFactor, double weightIntersect, Grid2DSquareCellDoubleFactory gridFactory)
public java.util.HashSet getInitialPeaksHashSetAndSetTheirValue(Grid2DSquareCellDouble grid, Grid2DSquareCellDouble upSlopeAreaMetrics)
grid
  the Grid2DSquareCellDouble to be processedpublic Grid2DSquareCellDouble getFlowAccumulation(Grid2DSquareCellDouble grid, int iterations, double precipitation, java.util.HashSet outflowCellIDs, Grid2DSquareCellDoubleFactory gridFactory)
public Grid2DSquareCellDouble getInitialFlowAccumulation(Grid2DSquareCellDouble grid, double precipitation, java.util.HashSet outflowCellIDs, Grid2DSquareCellDoubleFactory gridFactory)
public Grid2DSquareCellDouble doFlowAccumulation(Grid2DSquareCellDouble flowAccumulation, Grid2DSquareCellDouble grid, double precipitation, java.util.HashSet outflowCellIDs, Grid2DSquareCellDoubleFactory gridFactory)


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