Uses of Class
uk.ac.leeds.ccg.andyt.grids.core.AbstractGrid2DSquareCell

Packages that use AbstractGrid2DSquareCell
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 AbstractGrid2DSquareCell in uk.ac.leeds.ccg.andyt.grids.core
 

Subclasses of AbstractGrid2DSquareCell 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 AbstractGrid2DSquareCell instances.
 

Fields in uk.ac.leeds.ccg.andyt.grids.core declared as AbstractGrid2DSquareCell
protected  AbstractGrid2DSquareCell AbstractGrid2DSquareCellChunk._Grid2DSquareCell
          A reference to the Grid2DSquareCellDoubleAbstract instance.
protected  AbstractGrid2DSquareCell AbstractGridStatistics._Grid2DSquareCell
          A reference to the AbstractGrid2DSquareCell this is for.
 

Methods in uk.ac.leeds.ccg.andyt.grids.core that return AbstractGrid2DSquareCell
 AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create()
           
 AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(AbstractGrid2DSquareCell _Grid2DSquareCell)
           
 AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(AbstractGrid2DSquareCell grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex)
           
 AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(java.io.File gridFile)
           
 AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(java.io.File _Directory, AbstractGrid2DSquareCell grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex)
           
abstract  AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(java.io.File _Directory, AbstractGrid2DSquareCell grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, java.util.HashSet _Grid2DSquareCells, boolean _HandleOutOfMemoryError)
           
 AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(java.io.File _Directory, java.io.File gridFile, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex)
           
abstract  AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(java.io.File _Directory, java.io.File gridFile, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, java.util.HashSet _Grid2DSquareCells, boolean _HandleOutOfMemoryError)
           
 AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(java.io.File _Directory, java.io.File gridFile, java.io.ObjectInputStream ois)
           
abstract  AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(java.io.File _Directory, java.io.File gridFile, java.io.ObjectInputStream ois, java.util.HashSet _Grid2DSquareCells, boolean _HandleOutOfMemoryError)
           
 AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(java.io.File _Directory, long _NRows, long _NCols, java.math.BigDecimal[] _Dimensions)
           
abstract  AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(java.io.File _Directory, long _NRows, long _NCols, java.math.BigDecimal[] dimensions, java.util.HashSet _Grid2DSquareCells, boolean _HandleOutOfMemoryError)
           
 AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(long _NRows, long _NCols)
           
 AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(long _NRows, long _NCols, java.math.BigDecimal[] _Dimensions)
           
protected  AbstractGrid2DSquareCell AbstractGrid2DSquareCellChunk.getGrid2DSquareCell()
          Returns this._Grid2DSquareCell.
 AbstractGrid2DSquareCell AbstractGrid2DSquareCellChunk.getGrid2DSquareCell(boolean _HandleOutOfMemoryError)
          Returns this._Grid2DSquareCell.
 

Methods in uk.ac.leeds.ccg.andyt.grids.core with parameters of type AbstractGrid2DSquareCell
protected  java.util.HashMap OutOfMemoryErrorHandler._SwapToFileGrid2DSquareCellChunkExcept(AbstractGrid2DSquareCell _Grid2DSquareCell)
           
protected  java.util.HashMap OutOfMemoryErrorHandler._SwapToFileGrid2DSquareCellChunkExcept(AbstractGrid2DSquareCell _Grid2DSquareCell, AbstractGrid2DSquareCell.ChunkID _ChunkID)
           
 java.util.HashMap OutOfMemoryErrorHandler._SwapToFileGrid2DSquareCellChunkExcept(AbstractGrid2DSquareCell _Grid2DSquareCell, AbstractGrid2DSquareCell.ChunkID _ChunkID, boolean _HandleOutOfMemoryError)
           
 java.util.HashMap OutOfMemoryErrorHandler._SwapToFileGrid2DSquareCellChunkExcept(AbstractGrid2DSquareCell _Grid2DSquareCell, boolean _HandleOutOfMemoryError)
           
protected  java.util.HashMap OutOfMemoryErrorHandler._SwapToFileGrid2DSquareCellChunkExcept(AbstractGrid2DSquareCell _Grid2DSquareCell, java.util.HashSet _ChunkIDs)
           
 java.util.HashMap OutOfMemoryErrorHandler._SwapToFileGrid2DSquareCellChunkExcept(AbstractGrid2DSquareCell _Grid2DSquareCell, java.util.HashSet _ChunkIDHashSet, boolean _HandleOutOfMemoryError)
           
protected  java.util.HashMap OutOfMemoryErrorHandler._SwapToFileGrid2DSquareCellChunksExcept(AbstractGrid2DSquareCell _Grid2DSquareCell)
          Attempts to Swap all AbstractGrid2DSquareCell.ChunkIDs in this._Grid2DSquareCells except those with AbstractGrid2DSquareCell.ChunkID _ChunkID.
protected  java.util.HashMap OutOfMemoryErrorHandler._SwapToFileGrid2DSquareCellChunksExcept(AbstractGrid2DSquareCell _Grid2DSquareCell, AbstractGrid2DSquareCell.ChunkID _ChunkID)
          Attempts to Swap all AbstractGrid2DSquareCell.ChunkIDs in this._Grid2DSquareCells except those with AbstractGrid2DSquareCell.ChunkID _ChunkID.
 java.util.HashMap OutOfMemoryErrorHandler._SwapToFileGrid2DSquareCellChunksExcept(AbstractGrid2DSquareCell _Grid2DSquareCell, AbstractGrid2DSquareCell.ChunkID _ChunkID, boolean _HandleOutOfMemoryError)
          Attempts to Swap all AbstractGrid2DSquareCell.ChunkIDs in this._Grid2DSquareCells except those with AbstractGrid2DSquareCell.ChunkID _ChunkID.
 java.util.HashMap OutOfMemoryErrorHandler._SwapToFileGrid2DSquareCellChunksExcept(AbstractGrid2DSquareCell _Grid2DSquareCell, boolean _HandleOutOfMemoryError)
          Attempts to Swap all AbstractGrid2DSquareCell.ChunkIDs in this._Grid2DSquareCells except those with AbstractGrid2DSquareCell.ChunkID _ChunkID.
protected  java.util.HashMap OutOfMemoryErrorHandler._SwapToFileGrid2DSquareCellChunksExcept(AbstractGrid2DSquareCell _Grid2DSquareCell, java.util.HashSet _ChunkIDs)
          Attempts to Swap all AbstractGrid2DSquareCell.ChunkIDs in this._Grid2DSquareCells except those with AbstractGrid2DSquareCell.ChunkIDs in _ChunkIDs.
 AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(AbstractGrid2DSquareCell _Grid2DSquareCell)
           
 AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(AbstractGrid2DSquareCell grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex)
           
 Grid2DSquareCellDouble Grid2DSquareCellDoubleFactory.create(AbstractGridStatistics _GridStatistics, java.io.File _Directory, AbstractGrid2DSquareCell _Grid2DSquareCell, AbstractGrid2DSquareCellDoubleChunkFactory _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(AbstractGridStatistics gridStatistics, java.io.File _Directory, AbstractGrid2DSquareCell grid2DSquareCell, AbstractGrid2DSquareCellIntChunkFactory grid2DSquareCellIntChunkAbstractFactory, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, java.util.HashSet _Grid2DSquareCells, boolean _HandleOutOfMemoryError)
          Returns a new Grid2DSquareCellInt with values obtained from grid2DSquareCell.
 AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(java.io.File _Directory, AbstractGrid2DSquareCell grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex)
           
abstract  AbstractGrid2DSquareCell AbstractGrid2DSquareCellFactory.create(java.io.File _Directory, AbstractGrid2DSquareCell grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, java.util.HashSet _Grid2DSquareCells, boolean _HandleOutOfMemoryError)
           
 Grid2DSquareCellDouble Grid2DSquareCellDoubleFactory.create(java.io.File _Directory, AbstractGrid2DSquareCell _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, AbstractGrid2DSquareCell grid2DSquareCell, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, java.util.HashSet _Grid2DSquareCells, boolean _HandleOutOfMemoryError)
          Returns a new Grid2DSquareCellInt with values obtained from grid2DSquareCell.
 double[][] OutOfMemoryErrorHandler.getNormalDistributionKernelWeights(AbstractGrid2DSquareCell _Grid2DSquareCell, double _Distance, boolean _HandleOutOfMemoryError)
           
 void OutOfMemoryErrorHandler.init_MemoryReserve(AbstractGrid2DSquareCell _Grid2DSquareCell, AbstractGrid2DSquareCell.ChunkID _ChunkID, boolean _HandleOutOfMemoryError)
          Initialises _MemoryReserve.
 void OutOfMemoryErrorHandler.init_MemoryReserve(AbstractGrid2DSquareCell _Grid2DSquareCell, boolean _HandleOutOfMemoryError)
          Initialises _MemoryReserve.
 void OutOfMemoryErrorHandler.init_MemoryReserve(AbstractGrid2DSquareCell _Grid2DSquareCell, java.util.HashSet _ChunkIDs, boolean _HandleOutOfMemoryError)
          Initialises _MemoryReserve.
protected  void AbstractGridStatistics.init(AbstractGrid2DSquareCell grid2DSquareCell)
          For intitialisation
protected  void AbstractGrid2DSquareCell.initGrid2DSquareCell(AbstractGrid2DSquareCell _Grid2DSquareCell)
          Initialises non transient AbstractGrid2DSquareCell fields from _Grid2DSquareCell.
protected  void AbstractGrid2DSquareCellChunk.initGrid2DSquareCell(AbstractGrid2DSquareCell _Grid2DSquareCell)
          Initialises _Grid2DSquareCell.
protected  void Grid2DSquareCellInt.initGrid2DSquareCellInt(AbstractGridStatistics _GridStatistics, java.io.File _Directory, AbstractGrid2DSquareCell _Grid2DSquareCell, AbstractGrid2DSquareCellIntChunkFactory _Grid2DSquareCellIntChunkFactory, int _ChunkNRows, int _ChunkNCols, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, java.util.HashSet _Grid2DSquareCells, boolean _HandleOutOfMemoryError)
          Initialise this.
 double AbstractGrid2DSquareCell.setCell(long _CellRowIndex, long _CellColIndex, double valueToSet, boolean _HandleOutOfMemoryError, AbstractGrid2DSquareCell _Grid2DSquareCell)
           
 

Constructors in uk.ac.leeds.ccg.andyt.grids.core with parameters of type AbstractGrid2DSquareCell
Grid2DSquareCellDouble(AbstractGridStatistics _GridStatistics, java.io.File _Directory, AbstractGrid2DSquareCell _Grid2DSquareCell, AbstractGrid2DSquareCellDoubleChunkFactory 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(AbstractGridStatistics _GridStatistics, java.io.File _Directory, AbstractGrid2DSquareCell _Grid2DSquareCell, AbstractGrid2DSquareCellIntChunkFactory _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(AbstractGrid2DSquareCell _Grid2DSquareCell)
          Creates a new instance of GridStatistics0
GridStatistics1(AbstractGrid2DSquareCell _Grid2DSquareCell)
          Creates a new instance of GridStatistics1
 

Uses of AbstractGrid2DSquareCell in uk.ac.leeds.ccg.andyt.grids.exchange
 

Methods in uk.ac.leeds.ccg.andyt.grids.exchange with parameters of type AbstractGrid2DSquareCell
static void IO.gamOutputToGrid(java.io.File gamOutputFile, AbstractGrid2DSquareCell grid, double weight)
           
static void IO.generateGamInput(java.io.File gamInputFile, AbstractGrid2DSquareCell countGrid, AbstractGrid2DSquareCell parGrid)
          Creates gamInputFile from the countFile and parFile.
static void IO.gridArray2CSV(AbstractGrid2DSquareCell[] gridArray, java.lang.String header, java.io.File csvFile)
          Generates CSV file from gridArray
protected  java.io.File ESRIAsciiGridExporter.toAsciiFile(AbstractGrid2DSquareCell 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(AbstractGrid2DSquareCell _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(AbstractGrid2DSquareCell _Grid2DSquareCell, java.io.File file)
          Writes _Grid2DSquareCell out to file in ESRI Asciigrid format and returns file.
protected  java.io.File ESRIAsciiGridExporter.toAsciiFile(AbstractGrid2DSquareCell _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(AbstractGrid2DSquareCell _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(AbstractGrid2DSquareCell _Grid2DSquareCell, java.io.File file, boolean _HandleOutOfMemoryError)
          Writes _Grid2DSquareCell out to file in ESRI Asciigrid format and returns file.
protected  void ImageExporter.toGreyScaleImage(AbstractGrid2DSquareCell _Grid2DSquareCell, java.io.File file, java.lang.String type)
          Writes this grid as a Grey scale image
 void ImageExporter.toGreyScaleImage(AbstractGrid2DSquareCell _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, AbstractGrid2DSquareCell grid)
           
 

Uses of AbstractGrid2DSquareCell in uk.ac.leeds.ccg.andyt.grids.process
 

Methods in uk.ac.leeds.ccg.andyt.grids.process that return AbstractGrid2DSquareCell
protected  AbstractGrid2DSquareCell Grid2DSquareCellProcessor.getGrid2DSquareCell()
          Returns a AbstractGrid2DSquareCell from this._Grid2DSquareCells.
 AbstractGrid2DSquareCell Grid2DSquareCellProcessor.getGrid2DSquareCell(boolean _HandleOutOfMemoryError)
          Returns a AbstractGrid2DSquareCell from this._Grid2DSquareCells.
 AbstractGrid2DSquareCell[] Grid2DSquareCellProcessorDEM.getMetrics1(AbstractGrid2DSquareCell[] metrics1, AbstractGrid2DSquareCell _Grid2DSquareCell, java.math.BigDecimal[] dimensions, double distance, double weightIntersect, double weightFactor, boolean _HandleOutOfMemoryError)
          Returns an Grid2DSquareCellDouble[] metrics1 where: \n metrics1[0] = no data count; \n metrics1[1] = flatness; \n metrics1[2] = roughness; \n metrics1[3] = slopyness; \n metrics1[4] = levelness; \n metrics1[5] = totalDownness; \n metrics1[6] = averageDownness; \n metrics1[7] = totalUpness; \n metrics1[8] = averageUpness; \n metrics1[9] = maxd_hhhh [ sum of distance weighted maximum height differences ]; \n metrics1[10] = mind_hhhh [ sum of distance weighted minimum height differences ]; \n metrics1[11] = sumd_hhhh [ sum of distance weighted height differences ]; \n metrics1[12] = aved_hhhh [ sum of distance weighted average height difference ]; \n metrics1[13] = count_hhhh [ count ]; \n metrics1[14] = w_hhhh [ sum of distance weights ]; \n metrics1[15] = mind_hxhx_ai_hhhl [ sum of distance weighted ( minimum difference of cells adjacent to lower cell ) ]; \n metrics1[16] = maxd_hxhx_ai_hhhl [ sum of distance weighted ( maximum difference of cells adjacent to lower cell ) ]; \n metrics1[17] = sumd_hxhx_ai_hhhl [ sum of distance weighted ( sum of differences of cells adjacent to lower cell ) ]; \n metrics1[18] = d_xhxx_ai_hhhl [ sum of distance weighted ( difference of cell opposite lower cell ) ]; \n metrics1[19] = d_xxxl_ai_hhhl [ sum of distance weighted ( difference of lower cell ) ]; \n metrics1[20] = sumd_xhxl_ai_hhhl [ sum of distance weighted ( sum of differences of lower cell and cell opposite ) ]; \n metrics1[21] = mind_abs_xhxl_ai_hhhl [ sum of distance weighted ( minimum difference magnitude of lower cell and cell opposite ) ]; \n metrics1[22] = maxd_abs_xhxl_ai_hhhl [ sum of distance weighted ( maximum difference magnitude of lower cell and cell opposite ) ]; \n metrics1[23] = sumd_abs_xhxl_ai_hhhl [ sum of distance weighted ( sum of difference magnitudes of lower cell and cell opposite ) ]; \n metrics1[24] = count_hhhl [ count ]; \n metrics1[25] = w_hhhl [ sum of distance weights ]; \n metrics1[26] = mind_hxhx_ai_hlhl [ sum of distance weighted ( minimum difference of higher cells ) ]; \n metrics1[27] = maxd_hxhx_ai_hlhl [ sum of distance weighted ( maximum difference of higher cells ) ]; \n metrics1[28] = sumd_hxhx_ai_hlhl [ sum of distance weighted ( sum differences of higher cells ) ]; \n metrics1[29] = mind_xlxl_ai_hlhl [ sum of distance weighted ( minimum difference of lower cells ) ]; \n metrics1[30] = maxd_xlxl_ai_hlhl [ sum of distance weighted ( maximum difference of lower cells ) ]; \n metrics1[31] = sumd_xlxl_ai_hlhl [ sum of distance weighted ( sum of differences of lower cells ) ]; \n metrics1[32] = mind_abs_hlhl [ sum of distance weighted ( minimum difference magnitude of cells ) ]; \n metrics1[33] = maxd_abs_hlhl [ sum of distance weighted ( maximum difference magnitude of cells ) ]; \n metrics1[34] = sumd_abs_hlhl [ sum of distance weighted ( sum of difference magnitudes of cells ) ]; \n metrics1[35] = count_hlhl [ count ]; \n metrics1[36] = w_hlhl [ sum of distance weights ]; \n metrics1[37] = mind_hhxx_ai_hhll [ sum of distance weighted ( minimum difference of higher cells ) ]; \n metrics1[38] = maxd_hhxx_ai_hhll [ sum of distance weighted ( maximum difference of higher cells ) ]; \n metrics1[39] = sumd_hhxx_ai_hhll [ sum of distance weighted ( sum of differences of higher cells ) ]; \n metrics1[40] = mind_xxll_ai_hhll [ sum of distance weighted ( minimum difference of lower cells ) ]; \n metrics1[41] = maxd_xxll_ai_hhll [ sum of distance weighted ( maximum difference of lower cells ) ]; \n metrics1[42] = sumd_xxll_ai_hhll [ sum of distance weighted ( sum of differences of lower cells ) ]; \n metrics1[43] = mind_abs_hhll [ sum of distance weighted ( minimum difference magnitude of cells ) ]; \n metrics1[44] = maxd_abs_hhll [ sum of distance weighted ( maximum difference magnitude of cells ) ]; \n metrics1[45] = sumd_abs_hhll [ sum of distance weighted ( sum of difference magnitudes of cells ) ]; \n metrics1[46] = count_hhll [ count ]; \n metrics1[47] = w_hhll [ sum of distance weights ]; \n metrics1[48] = mind_lxlx_ai_lllh [ sum of distance weighted ( minimum difference of cells adjacent to higher cell ) ]; \n metrics1[49] = maxd_lxlx_ai_lllh [ sum of distance weighted ( maximum difference of cells adjacent to higher cell ) ]; \n metrics1[50] = sumd_lxlx_ai_lllh [ sum of distance weighted ( sum of differences of cells adjacent to higher cell ) ]; \n metrics1[51] = d_xlxx_ai_lllh [ sum of distance weighted ( difference of cell opposite higher cell ) ]; \n metrics1[52] = d_xxxh_ai_lllh [ sum of distance weighted ( difference of higher cell ) ]; \n metrics1[53] = sumd_xlxh_ai_lllh [ sum of distance weighted ( sum of differences of higher cell and cell opposite ) ]; \n metrics1[54] = mind_abs_xlxh_ai_lllh [ sum of distance weighted ( minimum difference magnitude of higher cell and cell opposite ) ]; \n metrics1[55] = maxd_abs_xlxh_ai_lllh [ sum of distance weighted ( maximum difference magnitude of higher cell and cell opposite ) ]; \n metrics1[56] = sumd_abs_xlxh_ai_lllh [ sum of distance weighted ( sum of difference magnitudes of higher cell and cell opposite ) ]; \n metrics1[57] = count_lllh [ count ]; \n metrics1[58] = w_lllh [ sum of distance weights ]; \n metrics1[59] = maxd_llll [ sum of distance weighted maximum height differences ]; \n metrics1[60] = mind_llll [ sum of distance weighted minimum height differences ]; \n metrics1[61] = sumd_llll [ sum of distance weighted height differences ]; \n metrics1[62] = aved_llll [ sum of distance weighted average height difference ]; \n metrics1[63] = count_llll [ count ]; \n metrics1[64] = w_llll [ sum of distance weights ]; \n
 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 ];
 

Methods in uk.ac.leeds.ccg.andyt.grids.process with parameters of type AbstractGrid2DSquareCell
 void Grid2DSquareCellProcessor._Output(AbstractGrid2DSquareCell _Grid2DSquareCell, java.io.File _Output_Directory, ImageExporter _ImageExporter, java.lang.String[] _ImageTypes, ESRIAsciiGridExporter _ESRIAsciiGridExporter, boolean _HandleOutOfMemoryError)
           For outputting _Grid2DSquareCell to various formats of file.
 void Grid2DSquareCellProcessor._OutputESRIAsciiGrid(AbstractGrid2DSquareCell _Grid2DSquareCell, java.io.File _Output_Directory, ESRIAsciiGridExporter _ESRIAsciiGridExporter, boolean _HandleOutOfMemoryError)
           
 void Grid2DSquareCellProcessor._OutputImage(AbstractGrid2DSquareCell _Grid2DSquareCell, java.io.File _Output_Directory, ImageExporter _ImageExporter, java.lang.String[] _ImageTypes, boolean _HandleOutOfMemoryError)
           
 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 Grid2DSquareCellProcessorDEM.getHollowFilledDEM(AbstractGrid2DSquareCell _Grid2DSquareCell, Grid2DSquareCellDoubleFactory _Grid2DSquareCellDoubleFactory, double outflowHeight, int maxIterations, java.util.HashSet outflowCellIDsSet, boolean _TreatNoDataValueAsOutflow, boolean _HandleOutOfMemoryError)
           
 AbstractGrid2DSquareCell[] Grid2DSquareCellProcessorDEM.getMetrics1(AbstractGrid2DSquareCell[] metrics1, AbstractGrid2DSquareCell _Grid2DSquareCell, java.math.BigDecimal[] dimensions, double distance, double weightIntersect, double weightFactor, boolean _HandleOutOfMemoryError)
          Returns an Grid2DSquareCellDouble[] metrics1 where: \n metrics1[0] = no data count; \n metrics1[1] = flatness; \n metrics1[2] = roughness; \n metrics1[3] = slopyness; \n metrics1[4] = levelness; \n metrics1[5] = totalDownness; \n metrics1[6] = averageDownness; \n metrics1[7] = totalUpness; \n metrics1[8] = averageUpness; \n metrics1[9] = maxd_hhhh [ sum of distance weighted maximum height differences ]; \n metrics1[10] = mind_hhhh [ sum of distance weighted minimum height differences ]; \n metrics1[11] = sumd_hhhh [ sum of distance weighted height differences ]; \n metrics1[12] = aved_hhhh [ sum of distance weighted average height difference ]; \n metrics1[13] = count_hhhh [ count ]; \n metrics1[14] = w_hhhh [ sum of distance weights ]; \n metrics1[15] = mind_hxhx_ai_hhhl [ sum of distance weighted ( minimum difference of cells adjacent to lower cell ) ]; \n metrics1[16] = maxd_hxhx_ai_hhhl [ sum of distance weighted ( maximum difference of cells adjacent to lower cell ) ]; \n metrics1[17] = sumd_hxhx_ai_hhhl [ sum of distance weighted ( sum of differences of cells adjacent to lower cell ) ]; \n metrics1[18] = d_xhxx_ai_hhhl [ sum of distance weighted ( difference of cell opposite lower cell ) ]; \n metrics1[19] = d_xxxl_ai_hhhl [ sum of distance weighted ( difference of lower cell ) ]; \n metrics1[20] = sumd_xhxl_ai_hhhl [ sum of distance weighted ( sum of differences of lower cell and cell opposite ) ]; \n metrics1[21] = mind_abs_xhxl_ai_hhhl [ sum of distance weighted ( minimum difference magnitude of lower cell and cell opposite ) ]; \n metrics1[22] = maxd_abs_xhxl_ai_hhhl [ sum of distance weighted ( maximum difference magnitude of lower cell and cell opposite ) ]; \n metrics1[23] = sumd_abs_xhxl_ai_hhhl [ sum of distance weighted ( sum of difference magnitudes of lower cell and cell opposite ) ]; \n metrics1[24] = count_hhhl [ count ]; \n metrics1[25] = w_hhhl [ sum of distance weights ]; \n metrics1[26] = mind_hxhx_ai_hlhl [ sum of distance weighted ( minimum difference of higher cells ) ]; \n metrics1[27] = maxd_hxhx_ai_hlhl [ sum of distance weighted ( maximum difference of higher cells ) ]; \n metrics1[28] = sumd_hxhx_ai_hlhl [ sum of distance weighted ( sum differences of higher cells ) ]; \n metrics1[29] = mind_xlxl_ai_hlhl [ sum of distance weighted ( minimum difference of lower cells ) ]; \n metrics1[30] = maxd_xlxl_ai_hlhl [ sum of distance weighted ( maximum difference of lower cells ) ]; \n metrics1[31] = sumd_xlxl_ai_hlhl [ sum of distance weighted ( sum of differences of lower cells ) ]; \n metrics1[32] = mind_abs_hlhl [ sum of distance weighted ( minimum difference magnitude of cells ) ]; \n metrics1[33] = maxd_abs_hlhl [ sum of distance weighted ( maximum difference magnitude of cells ) ]; \n metrics1[34] = sumd_abs_hlhl [ sum of distance weighted ( sum of difference magnitudes of cells ) ]; \n metrics1[35] = count_hlhl [ count ]; \n metrics1[36] = w_hlhl [ sum of distance weights ]; \n metrics1[37] = mind_hhxx_ai_hhll [ sum of distance weighted ( minimum difference of higher cells ) ]; \n metrics1[38] = maxd_hhxx_ai_hhll [ sum of distance weighted ( maximum difference of higher cells ) ]; \n metrics1[39] = sumd_hhxx_ai_hhll [ sum of distance weighted ( sum of differences of higher cells ) ]; \n metrics1[40] = mind_xxll_ai_hhll [ sum of distance weighted ( minimum difference of lower cells ) ]; \n metrics1[41] = maxd_xxll_ai_hhll [ sum of distance weighted ( maximum difference of lower cells ) ]; \n metrics1[42] = sumd_xxll_ai_hhll [ sum of distance weighted ( sum of differences of lower cells ) ]; \n metrics1[43] = mind_abs_hhll [ sum of distance weighted ( minimum difference magnitude of cells ) ]; \n metrics1[44] = maxd_abs_hhll [ sum of distance weighted ( maximum difference magnitude of cells ) ]; \n metrics1[45] = sumd_abs_hhll [ sum of distance weighted ( sum of difference magnitudes of cells ) ]; \n metrics1[46] = count_hhll [ count ]; \n metrics1[47] = w_hhll [ sum of distance weights ]; \n metrics1[48] = mind_lxlx_ai_lllh [ sum of distance weighted ( minimum difference of cells adjacent to higher cell ) ]; \n metrics1[49] = maxd_lxlx_ai_lllh [ sum of distance weighted ( maximum difference of cells adjacent to higher cell ) ]; \n metrics1[50] = sumd_lxlx_ai_lllh [ sum of distance weighted ( sum of differences of cells adjacent to higher cell ) ]; \n metrics1[51] = d_xlxx_ai_lllh [ sum of distance weighted ( difference of cell opposite higher cell ) ]; \n metrics1[52] = d_xxxh_ai_lllh [ sum of distance weighted ( difference of higher cell ) ]; \n metrics1[53] = sumd_xlxh_ai_lllh [ sum of distance weighted ( sum of differences of higher cell and cell opposite ) ]; \n metrics1[54] = mind_abs_xlxh_ai_lllh [ sum of distance weighted ( minimum difference magnitude of higher cell and cell opposite ) ]; \n metrics1[55] = maxd_abs_xlxh_ai_lllh [ sum of distance weighted ( maximum difference magnitude of higher cell and cell opposite ) ]; \n metrics1[56] = sumd_abs_xlxh_ai_lllh [ sum of distance weighted ( sum of difference magnitudes of higher cell and cell opposite ) ]; \n metrics1[57] = count_lllh [ count ]; \n metrics1[58] = w_lllh [ sum of distance weights ]; \n metrics1[59] = maxd_llll [ sum of distance weighted maximum height differences ]; \n metrics1[60] = mind_llll [ sum of distance weighted minimum height differences ]; \n metrics1[61] = sumd_llll [ sum of distance weighted height differences ]; \n metrics1[62] = aved_llll [ sum of distance weighted average height difference ]; \n metrics1[63] = count_llll [ count ]; \n metrics1[64] = w_llll [ sum of distance weights ]; \n
 AbstractGrid2DSquareCell[] Grid2DSquareCellProcessorDEM.getMetrics1(AbstractGrid2DSquareCell[] metrics1, AbstractGrid2DSquareCell _Grid2DSquareCell, java.math.BigDecimal[] dimensions, double distance, double weightIntersect, double weightFactor, boolean _HandleOutOfMemoryError)
          Returns an Grid2DSquareCellDouble[] metrics1 where: \n metrics1[0] = no data count; \n metrics1[1] = flatness; \n metrics1[2] = roughness; \n metrics1[3] = slopyness; \n metrics1[4] = levelness; \n metrics1[5] = totalDownness; \n metrics1[6] = averageDownness; \n metrics1[7] = totalUpness; \n metrics1[8] = averageUpness; \n metrics1[9] = maxd_hhhh [ sum of distance weighted maximum height differences ]; \n metrics1[10] = mind_hhhh [ sum of distance weighted minimum height differences ]; \n metrics1[11] = sumd_hhhh [ sum of distance weighted height differences ]; \n metrics1[12] = aved_hhhh [ sum of distance weighted average height difference ]; \n metrics1[13] = count_hhhh [ count ]; \n metrics1[14] = w_hhhh [ sum of distance weights ]; \n metrics1[15] = mind_hxhx_ai_hhhl [ sum of distance weighted ( minimum difference of cells adjacent to lower cell ) ]; \n metrics1[16] = maxd_hxhx_ai_hhhl [ sum of distance weighted ( maximum difference of cells adjacent to lower cell ) ]; \n metrics1[17] = sumd_hxhx_ai_hhhl [ sum of distance weighted ( sum of differences of cells adjacent to lower cell ) ]; \n metrics1[18] = d_xhxx_ai_hhhl [ sum of distance weighted ( difference of cell opposite lower cell ) ]; \n metrics1[19] = d_xxxl_ai_hhhl [ sum of distance weighted ( difference of lower cell ) ]; \n metrics1[20] = sumd_xhxl_ai_hhhl [ sum of distance weighted ( sum of differences of lower cell and cell opposite ) ]; \n metrics1[21] = mind_abs_xhxl_ai_hhhl [ sum of distance weighted ( minimum difference magnitude of lower cell and cell opposite ) ]; \n metrics1[22] = maxd_abs_xhxl_ai_hhhl [ sum of distance weighted ( maximum difference magnitude of lower cell and cell opposite ) ]; \n metrics1[23] = sumd_abs_xhxl_ai_hhhl [ sum of distance weighted ( sum of difference magnitudes of lower cell and cell opposite ) ]; \n metrics1[24] = count_hhhl [ count ]; \n metrics1[25] = w_hhhl [ sum of distance weights ]; \n metrics1[26] = mind_hxhx_ai_hlhl [ sum of distance weighted ( minimum difference of higher cells ) ]; \n metrics1[27] = maxd_hxhx_ai_hlhl [ sum of distance weighted ( maximum difference of higher cells ) ]; \n metrics1[28] = sumd_hxhx_ai_hlhl [ sum of distance weighted ( sum differences of higher cells ) ]; \n metrics1[29] = mind_xlxl_ai_hlhl [ sum of distance weighted ( minimum difference of lower cells ) ]; \n metrics1[30] = maxd_xlxl_ai_hlhl [ sum of distance weighted ( maximum difference of lower cells ) ]; \n metrics1[31] = sumd_xlxl_ai_hlhl [ sum of distance weighted ( sum of differences of lower cells ) ]; \n metrics1[32] = mind_abs_hlhl [ sum of distance weighted ( minimum difference magnitude of cells ) ]; \n metrics1[33] = maxd_abs_hlhl [ sum of distance weighted ( maximum difference magnitude of cells ) ]; \n metrics1[34] = sumd_abs_hlhl [ sum of distance weighted ( sum of difference magnitudes of cells ) ]; \n metrics1[35] = count_hlhl [ count ]; \n metrics1[36] = w_hlhl [ sum of distance weights ]; \n metrics1[37] = mind_hhxx_ai_hhll [ sum of distance weighted ( minimum difference of higher cells ) ]; \n metrics1[38] = maxd_hhxx_ai_hhll [ sum of distance weighted ( maximum difference of higher cells ) ]; \n metrics1[39] = sumd_hhxx_ai_hhll [ sum of distance weighted ( sum of differences of higher cells ) ]; \n metrics1[40] = mind_xxll_ai_hhll [ sum of distance weighted ( minimum difference of lower cells ) ]; \n metrics1[41] = maxd_xxll_ai_hhll [ sum of distance weighted ( maximum difference of lower cells ) ]; \n metrics1[42] = sumd_xxll_ai_hhll [ sum of distance weighted ( sum of differences of lower cells ) ]; \n metrics1[43] = mind_abs_hhll [ sum of distance weighted ( minimum difference magnitude of cells ) ]; \n metrics1[44] = maxd_abs_hhll [ sum of distance weighted ( maximum difference magnitude of cells ) ]; \n metrics1[45] = sumd_abs_hhll [ sum of distance weighted ( sum of difference magnitudes of cells ) ]; \n metrics1[46] = count_hhll [ count ]; \n metrics1[47] = w_hhll [ sum of distance weights ]; \n metrics1[48] = mind_lxlx_ai_lllh [ sum of distance weighted ( minimum difference of cells adjacent to higher cell ) ]; \n metrics1[49] = maxd_lxlx_ai_lllh [ sum of distance weighted ( maximum difference of cells adjacent to higher cell ) ]; \n metrics1[50] = sumd_lxlx_ai_lllh [ sum of distance weighted ( sum of differences of cells adjacent to higher cell ) ]; \n metrics1[51] = d_xlxx_ai_lllh [ sum of distance weighted ( difference of cell opposite higher cell ) ]; \n metrics1[52] = d_xxxh_ai_lllh [ sum of distance weighted ( difference of higher cell ) ]; \n metrics1[53] = sumd_xlxh_ai_lllh [ sum of distance weighted ( sum of differences of higher cell and cell opposite ) ]; \n metrics1[54] = mind_abs_xlxh_ai_lllh [ sum of distance weighted ( minimum difference magnitude of higher cell and cell opposite ) ]; \n metrics1[55] = maxd_abs_xlxh_ai_lllh [ sum of distance weighted ( maximum difference magnitude of higher cell and cell opposite ) ]; \n metrics1[56] = sumd_abs_xlxh_ai_lllh [ sum of distance weighted ( sum of difference magnitudes of higher cell and cell opposite ) ]; \n metrics1[57] = count_lllh [ count ]; \n metrics1[58] = w_lllh [ sum of distance weights ]; \n metrics1[59] = maxd_llll [ sum of distance weighted maximum height differences ]; \n metrics1[60] = mind_llll [ sum of distance weighted minimum height differences ]; \n metrics1[61] = sumd_llll [ sum of distance weighted height differences ]; \n metrics1[62] = aved_llll [ sum of distance weighted average height difference ]; \n metrics1[63] = count_llll [ count ]; \n metrics1[64] = w_llll [ sum of distance weights ]; \n
 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 ];
protected  Grid2DSquareCellDouble[] Grid2DSquareCellProcessorDEM.getSlopeAspect(AbstractGrid2DSquareCell _Grid2DSquareCell)
          Calculates and returns measures of the slope and aspect for the AbstractGrid2DSquareCell _Grid2DSquareCell passed in.
 Grid2DSquareCellDouble[] Grid2DSquareCellProcessorDEM.getSlopeAspect(AbstractGrid2DSquareCell _Grid2DSquareCell, boolean _HandleOutOfMemoryError)
          Calculates and returns measures of the slope and aspect for the AbstractGrid2DSquareCell _Grid2DSquareCell passed in.
 Grid2DSquareCellDouble[] Grid2DSquareCellProcessorDEM.getSlopeAspect(AbstractGrid2DSquareCell _Grid2DSquareCell, double distance, double weightIntersect, double weightFactor, boolean _HandleOutOfMemoryError)
           
protected  double[] Grid2DSquareCellProcessorDEM.getSlopeAspect(AbstractGrid2DSquareCell _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  double[] Grid2DSquareCellProcessorDEM.getSlopeAspect(AbstractGrid2DSquareCell _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.getSlopeAspect(AbstractGrid2DSquareCell _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.
 void Grid2DSquareCellProcessor.mask(AbstractGrid2DSquareCell grid, AbstractGrid2DSquareCell mask, boolean _HandleOutOfMemoryError)
          Modifies grid by setting to grid.noDataValue those cells coincident with mask.noDataValue cells.
 void Grid2DSquareCellProcessor.mask(AbstractGrid2DSquareCell grid, double min, double max, boolean _HandleOutOfMemoryError)
          Modifies grid with the values of cells in the range [min,max] set to its noDataValue.
 void Grid2DSquareCellProcessor.mask(AbstractGrid2DSquareCell grid, double xmin, double ymin, double xmax, double ymax, boolean _HandleOutOfMemoryError)
          Modifies grid by setting to grid.noDataValue those cells that's centroids intersect the rectangle given by: (xmin,ymin,xmax,ymax).
 void Grid2DSquareCellProcessor.mask(AbstractGrid2DSquareCell grid, long startRowIndex, long startColIndex, long endRowIndex, long endColIndex, boolean _HandleOutOfMemoryError)
          Modifies grid by setting to grid.noDataValue those cells that intersect the rectangle given by: (startRowIndex,startColIndex,endRowIndex,endColIndex).
 

Uses of AbstractGrid2DSquareCell in uk.ac.leeds.ccg.andyt.grids.utilities
 

Methods in uk.ac.leeds.ccg.andyt.grids.utilities with parameters of type AbstractGrid2DSquareCell
static java.lang.Object[] Utilities.densityPlot(AbstractGrid2DSquareCell xGrid, AbstractGrid2DSquareCell yGrid, int divisions, Grid2DSquareCellDoubleFactory gridFactory)
          Returns a density plot of xGrid values against yGrid values.
static double[] Kernel.getKernelParameters(AbstractGrid2DSquareCell 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(AbstractGrid2DSquareCell grid2DSquareCell, double distance, double weightIntersect, double weightFactor)
          Returns a double[] of kernel weights.
static double[] Kernel.getKernelWeights(AbstractGrid2DSquareCell grid2DSquareCell, long rowIndex, long colIndex, double distance, double weightIntersect, double weightFactor, java.awt.geom.Point2D.Double[] points)
          Returns a double[] of kernel weights.
static double[][] Kernel.getNormalDistributionKernelWeights(AbstractGrid2DSquareCell _Grid2DSquareCell, double _Distance)