private void calculateRaster() { amIActive = true; String inputHeader = null; String outputHeader = null; int col; int row; int numCols; int numRows; int a, i; float progress; int minValue, maxValue, range; boolean blnTextOutput = false; boolean zeroAsBackground = false; if (args.length <= 0) { showFeedback("Plugin parameters have not been set."); return; } inputHeader = args[0]; outputHeader = args[1]; blnTextOutput = Boolean.parseBoolean(args[2]); zeroAsBackground = Boolean.parseBoolean(args[3]); // check to see that the inputHeader and outputHeader are not null. if ((inputHeader == null) || (outputHeader == null)) { showFeedback("One or more of the input parameters have not been set properly."); return; } try { WhiteboxRaster image = new WhiteboxRaster(inputHeader, "r"); numRows = image.getNumberRows(); numCols = image.getNumberColumns(); double noData = image.getNoDataValue(); WhiteboxRaster output = new WhiteboxRaster( outputHeader, "rw", inputHeader, WhiteboxRaster.DataType.FLOAT, noData); output.setPreferredPalette("spectrum.pal"); output.setDataScale(WhiteboxRaster.DataScale.CONTINUOUS); minValue = (int) (image.getMinimumValue()); maxValue = (int) (image.getMaximumValue()); range = maxValue - minValue; double[] data; // find the axis-aligned minimum bounding box. updateProgress("Loop 1 of 2:", 0); double[][] boundingBox = new double[6][range + 1]; for (a = 0; a <= range; a++) { boundingBox[0][a] = Integer.MAX_VALUE; // west boundingBox[1][a] = Integer.MIN_VALUE; // east boundingBox[2][a] = Integer.MAX_VALUE; // north boundingBox[3][a] = Integer.MIN_VALUE; // south } for (row = 0; row < numRows; row++) { data = image.getRowValues(row); for (col = 0; col < numCols; col++) { if (data[col] != noData) { a = (int) (data[col] - minValue); if (col < boundingBox[0][a]) { boundingBox[0][a] = col; } if (col > boundingBox[1][a]) { boundingBox[1][a] = col; } if (row < boundingBox[2][a]) { boundingBox[2][a] = row; } if (row > boundingBox[3][a]) { boundingBox[3][a] = row; } boundingBox[5][a]++; } } if (cancelOp) { cancelOperation(); return; } progress = (float) (100f * row / (numRows - 1)); updateProgress("Loop 1 of 2:", (int) progress); } updateProgress("Loop 2 of 2:", 0); double radius; for (a = 0; a <= range; a++) { if ((boundingBox[1][a] - boundingBox[0][a] + 1) > (boundingBox[3][a] - boundingBox[2][a] + 1)) { radius = (boundingBox[1][a] - boundingBox[0][a] + 1) / 2; } else { radius = (boundingBox[3][a] - boundingBox[2][a] + 1) / 2; } boundingBox[4][a] = Math.PI * radius * radius; } if (zeroAsBackground) { boundingBox[0 - minValue][4] = 0d; // sum the column numbers and row numbers of each patch cell // along with the total number of cells. for (row = 0; row < numRows; row++) { data = image.getRowValues(row); for (col = 0; col < numCols; col++) { if (data[col] > 0) { a = (int) (data[col] - minValue); output.setValue(row, col, 1 - boundingBox[5][a] / boundingBox[4][a]); } } if (cancelOp) { cancelOperation(); return; } progress = (float) (100f * row / (numRows - 1)); updateProgress("Loop 2 of 2:", (int) progress); } } else { // sum the column numbers and row numbers of each patch cell // along with the total number of cells. for (row = 0; row < numRows; row++) { data = image.getRowValues(row); for (col = 0; col < numCols; col++) { if (data[col] != noData) { a = (int) (data[col] - minValue); output.setValue(row, col, 1 - boundingBox[5][a] / boundingBox[4][a]); } } if (cancelOp) { cancelOperation(); return; } progress = (float) (100f * row / (numRows - 1)); updateProgress("Loop 2 of 2:", (int) progress); } } output.addMetadataEntry("Created by the " + getDescriptiveName() + " tool."); output.addMetadataEntry("Created on " + new Date()); image.close(); output.close(); if (blnTextOutput) { DecimalFormat df; df = new DecimalFormat("0.0000"); String retstr = "Related Circumscribing Circle\nPatch ID\tValue"; for (a = 0; a <= range; a++) { if (boundingBox[4][a] > 0) { retstr = retstr + "\n" + (a + minValue) + "\t" + df.format(1 - boundingBox[5][a] / boundingBox[4][a]); } } returnData(retstr); } // returning a header file string displays the image. returnData(outputHeader); } catch (OutOfMemoryError oe) { myHost.showFeedback("An out-of-memory error has occurred during operation."); } catch (Exception e) { myHost.showFeedback("An error has occurred during operation. See log file for details."); myHost.logException("Error in " + getDescriptiveName(), e); } finally { updateProgress("Progress: ", 0); // tells the main application that this process is completed. amIActive = false; myHost.pluginComplete(); } }
private void histogramMatching(String inputHeader1, String inputHeader2, String outputHeader) { // check to see that the inputHeader and outputHeader are not null. if (inputHeader1.isEmpty() || outputHeader.isEmpty() || inputHeader2.isEmpty()) { showFeedback("One or more of the input parameters have not been set properly."); return; } try { int row, col; double z; int progress = 0; int numCells1 = 0; int numCells2 = 0; int i = 0; WhiteboxRasterInfo inputFile1 = new WhiteboxRasterInfo(inputHeader1); int rows1 = inputFile1.getNumberRows(); int cols1 = inputFile1.getNumberColumns(); double noData1 = inputFile1.getNoDataValue(); WhiteboxRasterInfo inputFile2 = new WhiteboxRasterInfo(inputHeader2); int rows2 = inputFile2.getNumberRows(); int cols2 = inputFile2.getNumberColumns(); double noData2 = inputFile2.getNoDataValue(); WhiteboxRaster outputFile = new WhiteboxRaster( outputHeader, "rw", inputHeader1, WhiteboxRaster.DataType.FLOAT, noData1); outputFile.setPreferredPalette(inputFile1.getPreferredPalette()); double minValue1 = inputFile1.getMinimumValue(); double maxValue1 = inputFile1.getMaximumValue(); int numBins1 = Math.max( 2 * (int) Math.ceil(maxValue1 - minValue1 + 1), (int) Math.ceil(Math.pow(rows1 * cols1, 1.0 / 3))); double binSize = (maxValue1 - minValue1) / numBins1; long[] histogram = new long[numBins1]; int binNum; int numBinsLessOne1 = numBins1 - 1; double[] data; updateProgress("Histogram matching: ", 0); for (row = 0; row < rows1; row++) { data = inputFile1.getRowValues(row); for (col = 0; col < cols1; col++) { z = data[col]; if (z != noData1) { numCells1++; binNum = (int) ((z - minValue1) / binSize); if (binNum > numBinsLessOne1) { binNum = numBinsLessOne1; } histogram[binNum]++; } } if (cancelOp) { cancelOperation(); return; } progress = (int) (100f * row / (rows1 - 1)); updateProgress("Histogram matching: ", progress); } updateProgress("Histogram matching: ", 0); double[] cdf = new double[numBins1]; cdf[0] = histogram[0]; for (i = 1; i < numBins1; i++) { cdf[i] = cdf[i - 1] + histogram[i]; } for (i = 0; i < numBins1; i++) { cdf[i] = cdf[i] / numCells1; } double minValue2 = inputFile2.getMinimumValue(); double maxValue2 = inputFile2.getMaximumValue(); int numBins2 = Math.max( 2 * (int) Math.ceil(maxValue2 - minValue2 + 1), (int) Math.ceil(Math.pow(rows2 * cols2, 1.0 / 3))); int numBinsLessOne2 = numBins2 - 1; long[] histogram2 = new long[numBins2]; double[][] referenceCDF = new double[numBins2][2]; for (row = 0; row < rows2; row++) { data = inputFile2.getRowValues(row); for (col = 0; col < cols2; col++) { z = data[col]; if (z != noData2) { numCells2++; binNum = (int) ((z - minValue2) / binSize); if (binNum > numBinsLessOne2) { binNum = numBinsLessOne2; } histogram2[binNum]++; } } if (cancelOp) { cancelOperation(); return; } progress = (int) (100f * row / (rows1 - 1)); updateProgress("Histogram matching: ", progress); } // convert the reference histogram to a cdf. referenceCDF[0][1] = histogram2[0]; for (i = 1; i < numBins2; i++) { referenceCDF[i][1] = referenceCDF[i - 1][1] + histogram2[i]; } for (i = 0; i < numBins2; i++) { referenceCDF[i][0] = minValue2 + (i / (float) numBins2) * (maxValue2 - minValue2); referenceCDF[i][1] = referenceCDF[i][1] / numCells2; } int[] startingVals = new int[11]; double pVal = 0; for (i = 0; i < numBins2; i++) { pVal = referenceCDF[i][1]; if (pVal < 0.1) { startingVals[1] = i; } if (pVal < 0.2) { startingVals[2] = i; } if (pVal < 0.3) { startingVals[3] = i; } if (pVal < 0.4) { startingVals[4] = i; } if (pVal < 0.5) { startingVals[5] = i; } if (pVal < 0.6) { startingVals[6] = i; } if (pVal < 0.7) { startingVals[7] = i; } if (pVal < 0.8) { startingVals[8] = i; } if (pVal < 0.9) { startingVals[9] = i; } if (pVal <= 1) { startingVals[10] = i; } } updateProgress("Histogram matching: ", 0); int j = 0; double xVal = 0; double x1, x2, p1, p2; for (row = 0; row < rows1; row++) { data = inputFile1.getRowValues(row); for (col = 0; col < cols1; col++) { z = data[col]; if (z != noData1) { binNum = (int) ((z - minValue1) / binSize); if (binNum > numBinsLessOne1) { binNum = numBinsLessOne1; } pVal = cdf[binNum]; j = (int) (Math.floor(pVal * 10)); for (i = startingVals[j]; i < numBins2; i++) { if (referenceCDF[i][1] > pVal) { if (i > 0) { x1 = referenceCDF[i - 1][0]; x2 = referenceCDF[i][0]; p1 = referenceCDF[i - 1][1]; p2 = referenceCDF[i][1]; if (p1 != p2) { xVal = x1 + ((x2 - x1) * ((pVal - p1) / (p2 - p1))); } else { xVal = x1; } } else { xVal = referenceCDF[i][0]; } break; } } outputFile.setValue(row, col, xVal); } } if (cancelOp) { cancelOperation(); return; } progress = (int) (100f * row / (rows1 - 1)); updateProgress("Histogram matching: ", progress); } inputFile1.close(); outputFile.close(); } catch (OutOfMemoryError oe) { myHost.showFeedback("An out-of-memory error has occurred during operation."); } catch (Exception e) { myHost.showFeedback("An error has occurred during operation. See log file for details."); myHost.logException("Error in " + getDescriptiveName(), e); } finally { updateProgress("Progress: ", 0); } }