Uses of Class
uk.ac.leeds.ccg.andyt.grids.core.Grid2DSquareCellDoubleFactory

Packages that use Grid2DSquareCellDoubleFactory
uk.ac.leeds.ccg.andyt.grids.examples   
uk.ac.leeds.ccg.andyt.grids.process   
uk.ac.leeds.ccg.andyt.grids.utilities   
 

Uses of Grid2DSquareCellDoubleFactory in uk.ac.leeds.ccg.andyt.grids.examples
 

Methods in uk.ac.leeds.ccg.andyt.grids.examples with parameters of type Grid2DSquareCellDoubleFactory
 void Example.doSlopeAndAspect(Grid2DSquareCellDoubleFactory grid2DSquareCellDoubleFactory, Grid2DSquareCellAbstract grid2DSquareCell)
          Calculates the slope and aspect of dem and writes results as asciigrid files
 

Uses of Grid2DSquareCellDoubleFactory in uk.ac.leeds.ccg.andyt.grids.process
 

Fields in uk.ac.leeds.ccg.andyt.grids.process declared as Grid2DSquareCellDoubleFactory
 Grid2DSquareCellDoubleFactory Grid2DSquareCellProcessor.grid2DSquareCellDoubleFactory
          Grid2DSquareCellDoubleFactory
 

Methods in uk.ac.leeds.ccg.andyt.grids.process with parameters of type Grid2DSquareCellDoubleFactory
 Grid2DSquareCellDouble Grid2DSquareCellProcessor.addToGrid(Grid2DSquareCellDouble grid, double value, Grid2DSquareCellDoubleFactory gridFactory, boolean handleOutOfMemoryError)
          Returns a copy of grid with value added to every cell via AbstractGrid2DSquareCellDouble.addToCell(value)
 Grid2DSquareCellDouble Grid2DSquareCellProcessor.addToGrid(Grid2DSquareCellDouble grid, java.util.HashSet cellIDs, double value, Grid2DSquareCellDoubleFactory gridFactory, boolean handleOutOfMemoryError)
          Returns a copy of grid with value added to all cells with IDs as Integer keys in cellIDKeys
 Grid2DSquareCellDouble Grid2DSquareCellProcessor.aggregate(Grid2DSquareCellAbstract grid2DSquareCell, int cellFactor, java.lang.String statistic, int rowOffset, int colOffset, Grid2DSquareCellDoubleFactory gridFactory, boolean handleOutOfMemoryError)
          Returns an Grid2DSquareCellDouble at a lower level of resolution than grid.
 Grid2DSquareCellDouble Grid2DSquareCellProcessor.aggregate(Grid2DSquareCellAbstract grid2DSquareCell, java.lang.String statistic, java.math.BigDecimal[] resultDimensions, Grid2DSquareCellDoubleFactory gridFactory, boolean handleOutOfMemoryError)
          Returns an Grid2DSquareCellDouble at a lower level of resolution than grid.
 Grid2DSquareCellDouble Grid2DSquareCellProcessorDEM.doFlowAccumulation(Grid2DSquareCellDouble flowAccumulation, Grid2DSquareCellDouble grid, double precipitation, java.util.HashSet outflowCellIDs, Grid2DSquareCellDoubleFactory gridFactory, boolean handleOutOfMemoryError)
          TODO: docs frictionFactor = 75.0d; constant = 8.0d * 9.81d / frictionFactor; velocity = Math.sqrt( constant * waterDepth * changeInDepth / ChangeInLength ); discharge = velocity * waterDepth
 Grid2DSquareCellDouble[] Grid2DSquareCellProcessorGWS.geometricDensity(Grid2DSquareCellDouble grid, double distance, Grid2DSquareCellDoubleFactory gridFactory)
          Returns an Grid2DSquareCellDouble[] containing geometric density surfaces at a range of scales: result[ 0 ] - is the result at the first scale ( double the cellsize of grid ) result[ 1 ] - if it exists is the result at the second scale ( double the cellsize of result[ 0 ] ) result[ n ] - if it exists is the result at the ( n + 1 )th scale ( double the cellsize of result[ n - 1 ] ) The algorithm used for generating a geometric density surface is described in: Turner A (2000) Density Data Generation for Spatial Data Mining Applications.
 Grid2DSquareCellDouble Grid2DSquareCellProcessorDEM.getFlowAccumulation(Grid2DSquareCellDouble grid, int iterations, double precipitation, java.util.HashSet outflowCellIDs, Grid2DSquareCellDoubleFactory gridFactory, boolean handleOutOfMemoryError)
          There are many estimates of flow that can be generated and many models developed in hydrology.
 Grid2DSquareCellDouble Grid2DSquareCellProcessorDEM.getInitialFlowAccumulation(Grid2DSquareCellDouble grid, double precipitation, java.util.HashSet outflowCellIDs, Grid2DSquareCellDoubleFactory gridFactory, boolean handleOutOfMemoryError)
          TODO: docs frictionFactor = 75.0d; constant = 8.0d * 9.81d / frictionFactor; velocity = Math.sqrt( constant * waterDepth * changeInDepth / ChangeInLength ); discharge = velocity * waterDepth
 Grid2DSquareCellDouble Grid2DSquareCellProcessorDEM.getMaxFlowDirection(Grid2DSquareCellDouble grid, Grid2DSquareCellDoubleFactory gridFactory, boolean handleOutOfMemoryError)
          Returns an Grid2DSquareCellDouble result containing values which indicate the direction of the maximum down slope for the immediate 8 cell neighbourhood.
 Grid2DSquareCellAbstract[] Grid2DSquareCellProcessorDEM.getMetrics1(Grid2DSquareCellAbstract grid2DSquareCell, double distance, double weightIntersect, double weightFactor, Grid2DSquareCellDoubleFactory grid2DSquareCellDoubleFactory, Grid2DSquareCellIntFactory grid2DSquareCellIntFactory, boolean handleOutOfMemoryError)
          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[] Grid2DSquareCellProcessorDEM.getMetrics2(Grid2DSquareCellDouble grid, double distance, double weightIntersect, double weightFactor, int samplingDensity, Grid2DSquareCellDoubleFactory gridFactory, boolean handleOutOfMemoryError)
          Returns an Grid2DSquareCellDouble[] metrics2 where: TODO: metrics2 is a mess.
protected  Grid2DSquareCellDouble[] Grid2DSquareCellProcessorDEM.getSlopeAndAspect(Grid2DSquareCellAbstract grid2DSquareCell, double distance, double weightIntersect, double weightFactor, Grid2DSquareCellDoubleFactory grid2DSquareCellDoubleFactory)
          Returns a Grid2DSquareCellDouble[] slopeAndAspect where: slopeAndAspect[0] is the distance weighted aggregate slope over the region slopeAndAspect[1] is the distance weighted aggregate aspect over the region.
 Grid2DSquareCellDouble[] Grid2DSquareCellProcessorDEM.getSlopeAndAspect(Grid2DSquareCellAbstract grid2DSquareCell, double distance, double weightIntersect, double weightFactor, Grid2DSquareCellDoubleFactory grid2DSquareCellDoubleFactory, boolean handleOutOfMemoryError)
          Returns a Grid2DSquareCellDouble[] slopeAndAspect where: slopeAndAspect[0] is the distance weighted aggregate slope over the region slopeAndAspect[1] is the distance weighted aggregate aspect over the region.
 Grid2DSquareCellDouble Grid2DSquareCellProcessorDEM.getUpSlopeAreaMetrics(Grid2DSquareCellDouble grid, double distance, double weightFactor, double weightIntersect, Grid2DSquareCellDoubleFactory gridFactory, boolean handleOutOfMemoryError)
          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?
 Grid2DSquareCellDouble Grid2DSquareCellProcessor.linearRescale(Grid2DSquareCellDouble grid, double min, double max, Grid2DSquareCellDoubleFactory gridFactory, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellDouble that is a copy of grid, but with values linearly rescaled into the range [min,max].
 Grid2DSquareCellDouble Grid2DSquareCellProcessor.logRescale(Grid2DSquareCellDouble grid, double min, double max, Grid2DSquareCellDoubleFactory gridFactory, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellDouble that is a copy of grid, but with values linearly scaled to range [1.0d,1000000.0d] then logged using Math.log(double) and then linearly scaled into the range [min,max]
 Grid2DSquareCellDouble[] Grid2DSquareCellProcessorGWS.regionBivariateStatistics(Grid2DSquareCellDouble grid0, Grid2DSquareCellDouble grid1, java.util.Vector statistics, double distance, double weightIntersect, double weightFactor, Grid2DSquareCellDoubleFactory gridFactory)
          Returns an Grid2DSquareCellDouble[] result with elements based on statistics and values based on bivariate comparison of grid0 and grid1, distance, weightIntersect and weightFactor.
 java.util.Vector Grid2DSquareCellProcessorGWS.regionUnivariateStatistics(Grid2DSquareCellDouble grid, java.util.Vector statistics, double distance, double weightIntersect, double weightFactor, Grid2DSquareCellDoubleFactory gridFactory)
          Returns a Vector containing Grid2DSquareCellDoubles.
 java.util.Vector Grid2DSquareCellProcessorGWS.regionUnivariateStatisticsCrossScale(Grid2DSquareCellDouble grid, java.util.Vector statistics, double distance, double weightIntersept, double weightFactor, double scaleIntersept, double scaleFactor, Grid2DSquareCellDoubleFactory gridFactory)
          TODO
 java.util.Vector Grid2DSquareCellProcessorGWS.regionUnivariateStatisticsSlow(Grid2DSquareCellDouble grid, java.util.Vector statistics, double distance, double weightIntersect, double weightFactor, Grid2DSquareCellDoubleFactory gridFactory)
          Returns a Vector containing Grid2DSquareCellDoubles
 Grid2DSquareCellDouble Grid2DSquareCellProcessor.setValueALittleBitLarger(Grid2DSquareCellDouble grid, java.util.HashSet cellIDs, Grid2DSquareCellDoubleFactory gridFactory, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellDouble that is a copy of grid, but with value of cells with keys in cellKeys set to a value a little bit larger.
 Grid2DSquareCellDouble Grid2DSquareCellProcessor.setValueALittleBitSmaller(Grid2DSquareCellDouble grid, java.util.HashSet cellIDs, Grid2DSquareCellDoubleFactory gridFactory, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellDouble that is a copy of grid, but with value of cells with keys in cellKeys set to a value a little bit smaller.
 

Uses of Grid2DSquareCellDoubleFactory in uk.ac.leeds.ccg.andyt.grids.utilities
 

Methods in uk.ac.leeds.ccg.andyt.grids.utilities with parameters of type Grid2DSquareCellDoubleFactory
static java.lang.Object[] Utilities.densityPlot(Grid2DSquareCellAbstract xGrid, Grid2DSquareCellAbstract yGrid, int divisions, Grid2DSquareCellDoubleFactory gridFactory)
          Returns a density plot of xGrid values against yGrid values.