Uses of Class
uk.ac.leeds.ccg.andyt.grids.core.Grid2DSquareCellAbstract

Packages that use Grid2DSquareCellAbstract
uk.ac.leeds.ccg.andyt.grids.core   
uk.ac.leeds.ccg.andyt.grids.exchange   
uk.ac.leeds.ccg.andyt.grids.process   
uk.ac.leeds.ccg.andyt.grids.utilities   
 

Uses of Grid2DSquareCellAbstract in uk.ac.leeds.ccg.andyt.grids.core
 

Subclasses of Grid2DSquareCellAbstract in uk.ac.leeds.ccg.andyt.grids.core
 class Grid2DSquareCellDouble
          A class for representing grids of double precision values.
 class Grid2DSquareCellInt
          A class to represent and manipulate int precision Grid2DSquareCellAbstract instances.
 

Fields in uk.ac.leeds.ccg.andyt.grids.core declared as Grid2DSquareCellAbstract
protected  Grid2DSquareCellAbstract Grid2DSquareCellChunkAbstract.grid2DSquareCell
          A reference to the Grid2DSquareCellDoubleAbstract instance.
protected  Grid2DSquareCellAbstract GridStatisticsAbstract.grid2DSquareCell
          A reference to the Grid2DSquareCellAbstract this is for.
 

Methods in uk.ac.leeds.ccg.andyt.grids.core that return Grid2DSquareCellAbstract
 Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create()
          Returns an Grid2DSquareCellAbstract loaded from this.directory.
 Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(java.io.File gridFile)
          Returns a new Grid2DSquareCellAbstract with values obtained from gridFile.
 Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(java.io.File directory, java.io.File gridFile, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex)
          Returns a new Grid2DSquareCellAbstract with values obtained from gridFile.
abstract  Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(java.io.File directory, java.io.File gridFile, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, java.util.HashSet grid2DSquareCells, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellAbstract with values obtained from gridFile.
 Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(java.io.File directory, java.io.File gridFile, java.io.ObjectInputStream ois)
          Returns a new Grid2DSquareCellAbstract with values obtained from gridFile.
abstract  Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(java.io.File directory, java.io.File gridFile, java.io.ObjectInputStream ois, java.util.HashSet grid2DSquareCells, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellAbstract with values obtained from gridFile.
 Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(java.io.File directory, Grid2DSquareCellAbstract grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex)
          Returns a new Grid2DSquareCellAbstract with values obtained from grid2DSquareCell.
abstract  Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(java.io.File directory, Grid2DSquareCellAbstract grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, java.util.HashSet grid2DSquareCells, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellAbstract with values obtained from grid2DSquareCell.
 Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(java.io.File directory, long nrows, long ncols, java.math.BigDecimal[] dimensions)
          Returns an Grid2DSquareCellAbstract with all values as noDataValues.
abstract  Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(java.io.File directory, long nrows, long ncols, java.math.BigDecimal[] dimensions, java.util.HashSet grid2DSquareCells, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellAbstract grid with all values as noDataValues.
 Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(Grid2DSquareCellAbstract grid2DSquareCell)
          Returns a new Grid2DSquareCellAbstract with all values as int values from grid2DSquareCell.
 Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(Grid2DSquareCellAbstract grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex)
          Returns a new Grid2DSquareCellAbstract with values obtained from grid2DSquareCell.
 Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(long nrows, long ncols)
          Returns an Grid2DSquareCellAbstract with all values as noDataValues.
 Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(long nrows, long ncols, java.math.BigDecimal[] dimensions)
          Returns an Grid2DSquareCellAbstract with all values as noDataValues.
 Grid2DSquareCellAbstract Grid2DSquareCellChunkAbstract.getGrid2DSquareCell()
          Returns this.grid2DSquareCell.
 

Methods in uk.ac.leeds.ccg.andyt.grids.core with parameters of type Grid2DSquareCellAbstract
 Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(java.io.File directory, Grid2DSquareCellAbstract grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex)
          Returns a new Grid2DSquareCellAbstract with values obtained from grid2DSquareCell.
abstract  Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(java.io.File directory, Grid2DSquareCellAbstract grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, java.util.HashSet grid2DSquareCells, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellAbstract with values obtained from grid2DSquareCell.
 Grid2DSquareCellDouble Grid2DSquareCellDoubleFactory.create(java.io.File directory, Grid2DSquareCellAbstract grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, java.util.HashSet grid2DSquareCells, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellDouble with all values taken from grid2DSquareCell.
 Grid2DSquareCellInt Grid2DSquareCellIntFactory.create(java.io.File directory, Grid2DSquareCellAbstract grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, java.util.HashSet grid2DSquareCells, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellInt with values obtained from grid2DSquareCell.
 Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(Grid2DSquareCellAbstract grid2DSquareCell)
          Returns a new Grid2DSquareCellAbstract with all values as int values from grid2DSquareCell.
 Grid2DSquareCellAbstract Grid2DSquareCellAbstractFactory.create(Grid2DSquareCellAbstract grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex)
          Returns a new Grid2DSquareCellAbstract with values obtained from grid2DSquareCell.
 Grid2DSquareCellDouble Grid2DSquareCellDoubleFactory.create(GridStatisticsAbstract gridStatistics, java.io.File directory, Grid2DSquareCellAbstract grid2DSquareCell, Grid2DSquareCellDoubleChunkAbstractFactory grid2DSquareCellDoubleChunkFactory, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, java.util.HashSet grid2DSquareCells, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellDouble with all values taken from grid2DSquareCell.
 Grid2DSquareCellInt Grid2DSquareCellIntFactory.create(GridStatisticsAbstract gridStatistics, java.io.File directory, Grid2DSquareCellAbstract grid2DSquareCell, Grid2DSquareCellIntChunkAbstractFactory grid2DSquareCellIntChunkAbstractFactory, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, java.util.HashSet grid2DSquareCells, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellInt with values obtained from grid2DSquareCell.
protected  void GridStatisticsAbstract.init(Grid2DSquareCellAbstract grid2DSquareCell)
          For intitialisation
protected  void Grid2DSquareCellChunkAbstract.initGrid2DSquareCell(Grid2DSquareCellAbstract grid2DSquareCell)
          Initialises grid2DSquareCell.
protected  void Grid2DSquareCellAbstract.initGrid2DSquareCellAbstract(Grid2DSquareCellAbstract grid2DSquareCell)
          Initialises non transient Grid2DSquareCellAbstract fields from grid2DSquareCell
protected  void Grid2DSquareCellInt.initGrid2DSquareCellInt(GridStatisticsAbstract gridStatistics, java.io.File directory, Grid2DSquareCellAbstract grid2DSquareCell, Grid2DSquareCellIntChunkAbstractFactory grid2DSquareCellIntChunkFactory, int chunkNrows, int chunkNcols, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex)
          Initialises this.
protected  void Grid2DSquareCellInt.initGrid2DSquareCellInt(GridStatisticsAbstract gridStatistics, java.io.File directory, Grid2DSquareCellAbstract grid2DSquareCell, Grid2DSquareCellIntChunkAbstractFactory grid2DSquareCellIntChunkFactory, int chunkNrows, int chunkNcols, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, java.util.HashSet grid2DSquareCells, boolean handleOutOfMemoryError)
          Initialise this.
 

Constructors in uk.ac.leeds.ccg.andyt.grids.core with parameters of type Grid2DSquareCellAbstract
Grid2DSquareCellDouble(GridStatisticsAbstract gridStatistics, java.io.File directory, Grid2DSquareCellAbstract grid2DSquareCell, Grid2DSquareCellDoubleChunkAbstractFactory grid2DSquareCellDoubleChunkFactory, int chunkNrows, int chunkNcols, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, double noDataValue, java.util.HashSet grid2DSquareCells, boolean handleOutOfMemoryError)
          Creates a new Grid2DSquareCellDouble based on values in grid2DSquareCell.
Grid2DSquareCellInt(GridStatisticsAbstract gridStatistics, java.io.File directory, Grid2DSquareCellAbstract grid2DSquareCell, Grid2DSquareCellIntChunkAbstractFactory grid2DSquareCellIntChunkFactory, int chunkNrows, int chunkNcols, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, java.util.HashSet grid2DSquareCells, boolean handleOutOfMemoryError)
          Creates a new Grid2DSquareCellInt based on values in grid2DSquareCell.
GridStatistics0(Grid2DSquareCellAbstract grid2DSquareCell)
          Creates a new instance of GridStatistics0
GridStatistics1(Grid2DSquareCellAbstract grid2DSquareCell)
          Creates a new instance of GridStatistics1
 

Uses of Grid2DSquareCellAbstract in uk.ac.leeds.ccg.andyt.grids.exchange
 

Methods in uk.ac.leeds.ccg.andyt.grids.exchange with parameters of type Grid2DSquareCellAbstract
static void IO.gamOutputToGrid(java.io.File gamOutputFile, Grid2DSquareCellAbstract grid, double weight)
           
static void IO.generateGamInput(java.io.File gamInputFile, Grid2DSquareCellAbstract countGrid, Grid2DSquareCellAbstract parGrid)
          Creates gamInputFile from the countFile and parFile.
static void IO.gridArray2CSV(Grid2DSquareCellAbstract[] gridArray, java.lang.String header, java.io.File csvFile)
          Generates CSV file from gridArray
protected  java.io.File ESRIAsciiGridExporter.toAsciiFile(Grid2DSquareCellAbstract grid2DSquareCell)
          Writes grid2DSquareCell out to file in ESRI Asciigrid format and returns a the File to which it was written.
 java.io.File ESRIAsciiGridExporter.toAsciiFile(Grid2DSquareCellAbstract grid2DSquareCell, boolean handleOutOfMemoryError)
          Writes grid2DSquareCell out to file in ESRI Asciigrid format and returns a the File to which it was written.
protected  java.io.File ESRIAsciiGridExporter.toAsciiFile(Grid2DSquareCellAbstract grid2DSquareCell, java.io.File file)
          Writes grid2DSquareCell out to file in ESRI Asciigrid format and returns file.
protected  java.io.File ESRIAsciiGridExporter.toAsciiFile(Grid2DSquareCellAbstract grid2DSquareCell, java.io.File file, java.math.BigDecimal noDataValueBigDecimal)
          Writes grid2DSquareCell out to file in ESRI Asciigrid format and returns file.
 java.io.File ESRIAsciiGridExporter.toAsciiFile(Grid2DSquareCellAbstract grid2DSquareCell, java.io.File file, java.math.BigDecimal noDataValueBigDecimal, boolean handleOutOfMemoryError)
          Writes grid2DSquareCell out to file in ESRI Asciigrid format and returns file.
 java.io.File ESRIAsciiGridExporter.toAsciiFile(Grid2DSquareCellAbstract grid2DSquareCell, java.io.File file, boolean handleOutOfMemoryError)
          Writes grid2DSquareCell out to file in ESRI Asciigrid format and returns file.
 void ImageExporter.toGreyScaleImage(Grid2DSquareCellAbstract grid2DSquareCell, java.io.File file, java.lang.String type, boolean handleOutOfMemoryError)
          Writes this grid as a Grey scale image
 void IO.xyFileToGrid(java.io.File xyFile, Grid2DSquareCellAbstract grid)
           
 

Uses of Grid2DSquareCellAbstract in uk.ac.leeds.ccg.andyt.grids.process
 

Methods in uk.ac.leeds.ccg.andyt.grids.process that return Grid2DSquareCellAbstract
 Grid2DSquareCellAbstract[] Grid2DSquareCellProcessorDEM.getMetrics1(Grid2DSquareCellAbstract[] metrics1, Grid2DSquareCellAbstract grid2DSquareCell, java.math.BigDecimal[] dimensions, double distance, double weightIntersect, double weightFactor, 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 ];
 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 ];
 Grid2DSquareCellAbstract Grid2DSquareCellProcessor.mask(Grid2DSquareCellAbstract grid2DSquareCell, double min, double max, boolean handleOutOfMemoryError)
          Returns grid2DSquareCell with the values of cells in the range [min,max] set to its noDataValue.
 Grid2DSquareCellAbstract Grid2DSquareCellProcessor.mask(Grid2DSquareCellAbstract grid2DSquareCell, double xmin, double ymin, double xmax, double ymax, boolean handleOutOfMemoryError)
          Returns grid with the value of cells that's centroids intersect the rectangle given by (xmin,ymin,xmax,ymax) set to its noDataValue.
 Grid2DSquareCellAbstract Grid2DSquareCellProcessor.mask(Grid2DSquareCellAbstract grid2DSquareCell, Grid2DSquareCellAbstract mask, Grid2DSquareCellAbstractFactory grid2DSquareCellAbstractFactory, boolean handleOutOfMemoryError)
          If grid2DSquareCellAbstractFactory is null then grid2DSquareCell is directly masked and returned, otherwise a new Grid2DSquareCellAbstract result is contructed using grid2DSquareCellAbstractFactory.
 Grid2DSquareCellAbstract Grid2DSquareCellProcessor.mask(Grid2DSquareCellAbstract grid2DSquareCellToMask, Grid2DSquareCellAbstract grid2DSquareCellMask, GridStatisticsAbstract resultGridStatistics, java.io.File resultDirectory, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellAbstract which is of the same type and chunk stucture as grid2DSquareCellMask.
 Grid2DSquareCellAbstract Grid2DSquareCellProcessor.mask(Grid2DSquareCellAbstract grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, boolean handleOutOfMemoryError)
          Returns grid with the value of cells that intersect rectangle given by (startRowIndex,startColIndex,endRowIndex,endColIndex) set to its noDataValue.
 Grid2DSquareCellAbstract Grid2DSquareCellProcessor.mask(Grid2DSquareCellAbstract grid, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, Grid2DSquareCellAbstractFactory grid2DSquareCellFactory, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellDouble that is a copy of grid, but with the value of cells in grid that intersect rectangle given by (startRowIndex,startColIndex,endRowIndex,endColIndex) set to its noDataValue.
 

Methods in uk.ac.leeds.ccg.andyt.grids.process with parameters of type Grid2DSquareCellAbstract
 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.getHollowFilledDEM(Grid2DSquareCellAbstract grid2DSquareCell, double outflowHeight, int maxIterations, java.util.HashSet outflowCellIDsSet, boolean handleOutOfMemoryError)
          Returns an Grid2DSquareCellDouble hollowFilledDEM which has cell values as in grid except with any hollows raised so that they are not hollows.
 Grid2DSquareCellAbstract[] Grid2DSquareCellProcessorDEM.getMetrics1(Grid2DSquareCellAbstract[] metrics1, Grid2DSquareCellAbstract grid2DSquareCell, java.math.BigDecimal[] dimensions, double distance, double weightIntersect, double weightFactor, 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 ];
 Grid2DSquareCellAbstract[] Grid2DSquareCellProcessorDEM.getMetrics1(Grid2DSquareCellAbstract[] metrics1, Grid2DSquareCellAbstract grid2DSquareCell, java.math.BigDecimal[] dimensions, double distance, double weightIntersect, double weightFactor, 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 ];
 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 ];
protected  Grid2DSquareCellDouble[] Grid2DSquareCellProcessorDEM.getSlopeAndAspect(Grid2DSquareCellAbstract grid2DSquareCell)
          Calculates and returns measures of the slope and aspect for the Grid2DSquareCellAbstract grid2DSquareCell passed in.
 Grid2DSquareCellDouble[] Grid2DSquareCellProcessorDEM.getSlopeAndAspect(Grid2DSquareCellAbstract grid2DSquareCell, boolean handleOutOfMemoryError)
          Calculates and returns measures of the slope and aspect for the Grid2DSquareCellAbstract grid2DSquareCell passed in.
protected  double[] Grid2DSquareCellProcessorDEM.getSlopeAndAspect(Grid2DSquareCellAbstract grid2DSquareCell, double x, double y, double distance, double weightIntersect, double weightFactor, boolean handleOutOfMemoryError)
          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  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.
protected  double[] Grid2DSquareCellProcessorDEM.getSlopeAndAspect(Grid2DSquareCellAbstract grid2DSquareCell, long rowIndex, long colIndex, double distance, double weightIntersect, double weightFactor, boolean handleOutOfMemoryError)
          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[] Grid2DSquareCellProcessorDEM.getSlopeAndAspect(Grid2DSquareCellAbstract grid2DSquareCell, long rowIndex, long colIndex, double x, double y, double distance, double weightIntersect, double weightFactor, boolean handleOutOfMemoryError)
          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.
 Grid2DSquareCellAbstract Grid2DSquareCellProcessor.mask(Grid2DSquareCellAbstract grid2DSquareCell, double min, double max, boolean handleOutOfMemoryError)
          Returns grid2DSquareCell with the values of cells in the range [min,max] set to its noDataValue.
 Grid2DSquareCellAbstract Grid2DSquareCellProcessor.mask(Grid2DSquareCellAbstract grid2DSquareCell, double xmin, double ymin, double xmax, double ymax, boolean handleOutOfMemoryError)
          Returns grid with the value of cells that's centroids intersect the rectangle given by (xmin,ymin,xmax,ymax) set to its noDataValue.
 Grid2DSquareCellAbstract Grid2DSquareCellProcessor.mask(Grid2DSquareCellAbstract grid2DSquareCell, Grid2DSquareCellAbstract mask, Grid2DSquareCellAbstractFactory grid2DSquareCellAbstractFactory, boolean handleOutOfMemoryError)
          If grid2DSquareCellAbstractFactory is null then grid2DSquareCell is directly masked and returned, otherwise a new Grid2DSquareCellAbstract result is contructed using grid2DSquareCellAbstractFactory.
 Grid2DSquareCellAbstract Grid2DSquareCellProcessor.mask(Grid2DSquareCellAbstract grid2DSquareCellToMask, Grid2DSquareCellAbstract grid2DSquareCellMask, GridStatisticsAbstract resultGridStatistics, java.io.File resultDirectory, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellAbstract which is of the same type and chunk stucture as grid2DSquareCellMask.
 Grid2DSquareCellAbstract Grid2DSquareCellProcessor.mask(Grid2DSquareCellAbstract grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, boolean handleOutOfMemoryError)
          Returns grid with the value of cells that intersect rectangle given by (startRowIndex,startColIndex,endRowIndex,endColIndex) set to its noDataValue.
 Grid2DSquareCellAbstract Grid2DSquareCellProcessor.mask(Grid2DSquareCellAbstract grid, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, Grid2DSquareCellAbstractFactory grid2DSquareCellFactory, boolean handleOutOfMemoryError)
          Returns a new Grid2DSquareCellDouble that is a copy of grid, but with the value of cells in grid that intersect rectangle given by (startRowIndex,startColIndex,endRowIndex,endColIndex) set to its noDataValue.
 

Uses of Grid2DSquareCellAbstract in uk.ac.leeds.ccg.andyt.grids.utilities
 

Methods in uk.ac.leeds.ccg.andyt.grids.utilities with parameters of type Grid2DSquareCellAbstract
static java.lang.Object[] Utilities.densityPlot(Grid2DSquareCellAbstract xGrid, Grid2DSquareCellAbstract yGrid, int divisions, Grid2DSquareCellDoubleFactory gridFactory)
          Returns a density plot of xGrid values against yGrid values.
static double[] Kernel.getKernelParameters(Grid2DSquareCellAbstract grid2DSquareCell, int cellDistance, double distance, double weightIntersect, double weightFactor)
          Returns double[] result of kernel parameters where: result[0] = The total sum of all the weights for a given kernel; result[1] = The total number of cells thats centroids are within distance of an arbitrary cell centroid of grid2DSquareCell.
static double[][] Kernel.getKernelWeights(Grid2DSquareCellAbstract grid2DSquareCell, double distance, double weightIntersect, double weightFactor)
          Returns a double[] of kernel weights.
static double[] Kernel.getKernelWeights(Grid2DSquareCellAbstract grid2DSquareCell, long rowIndex, long colIndex, double distance, double weightIntersect, double weightFactor, java.awt.geom.Point2D.Double[] points)
          Returns a double[] of kernel weights.