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

Packages that use Grid2DSquareCellDoubleFactory

uk.ac.leeds.ccg.andyt.grids.process
uk.ac.leeds.ccg.andyt.grids.utilities

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.aggregate(AbstractGrid2DSquareCell grid, 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(AbstractGrid2DSquareCell grid, java.lang.String statistic, java.math.BigDecimal[] resultDimensions, Grid2DSquareCellDoubleFactory gridFactory, boolean handleOutOfMemoryError) Returns an Grid2DSquareCellDouble at a lower level of resolution than grid.
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.getHollowFilledDEM(AbstractGrid2DSquareCell _Grid2DSquareCell, Grid2DSquareCellDoubleFactory _Grid2DSquareCellDoubleFactory, double outflowHeight, int maxIterations, java.util.HashSet outflowCellIDsSet, boolean _TreatNoDataValueAsOutflow, boolean handleOutOfMemoryError)
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.
AbstractGrid2DSquareCell[]	Grid2DSquareCellProcessorDEM.getMetrics1(AbstractGrid2DSquareCell _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.
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[]	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.List<AbstractGrid2DSquareCell>	Grid2DSquareCellProcessorGWS.regionUnivariateStatistics(Grid2DSquareCellDouble grid, java.util.List<java.lang.String> 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.List<AbstractGrid2DSquareCell>	Grid2DSquareCellProcessorGWS.regionUnivariateStatisticsSlow(Grid2DSquareCellDouble grid, java.util.List<java.lang.String> statistics, double distance, double weightIntersect, double weightFactor, Grid2DSquareCellDoubleFactory gridFactory) Returns a Vector containing Grid2DSquareCellDoubles

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(AbstractGrid2DSquareCell xGrid, AbstractGrid2DSquareCell yGrid, int divisions, Grid2DSquareCellDoubleFactory gridFactory) Returns a density plot of xGrid values against yGrid values.