Java tutorial
/* * Copyright (C) 2013 Dr. John Lindsay <jlindsay@uoguelph.ca> * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see <http://www.gnu.org/licenses/>. */ package plugins; import org.apache.commons.math3.distribution.NormalDistribution; import java.text.DecimalFormat; import whitebox.geospatialfiles.WhiteboxRaster; import whitebox.interfaces.WhiteboxPlugin; import whitebox.interfaces.WhiteboxPluginHost; /** * Spatial autocorrelation describes the extent to which a variable is either dispersed or clustered through space. * * @author Dr. John Lindsay email: jlindsay@uoguelph.ca */ public class ImageAutocorrelation implements WhiteboxPlugin { private WhiteboxPluginHost myHost = null; private String[] args; /** * Used to retrieve the plugin tool's name. This is a short, unique name * containing no spaces. * * @return String containing plugin name. */ @Override public String getName() { return "ImageAutocorrelation"; } /** * Used to retrieve the plugin tool's descriptive name. This can be a longer * name (containing spaces) and is used in the interface to list the tool. * * @return String containing the plugin descriptive name. */ @Override public String getDescriptiveName() { return "Image Autocorrelation"; } /** * Used to retrieve a short description of what the plugin tool does. * * @return String containing the plugin's description. */ @Override public String getToolDescription() { return "Computes the Spatial autocorrelation (Morans' I) of an image."; } /** * Used to identify which toolboxes this plugin tool should be listed in. * * @return Array of Strings. */ @Override public String[] getToolbox() { String[] ret = { "StatisticalTools" }; return ret; } /** * Sets the WhiteboxPluginHost to which the plugin tool is tied. This is the * class that the plugin will send all feedback messages, progress updates, * and return objects. * * @param host The WhiteboxPluginHost that called the plugin tool. */ @Override public void setPluginHost(WhiteboxPluginHost host) { myHost = host; } /** * Used to communicate feedback pop-up messages between a plugin tool and * the main Whitebox user-interface. * * @param feedback String containing the text to display. */ private void showFeedback(String message) { if (myHost != null) { myHost.showFeedback(message); } else { System.out.println(message); } } /** * Used to communicate a return object from a plugin tool to the main * Whitebox user-interface. * * @return Object, such as an output WhiteboxRaster. */ private void returnData(Object ret) { if (myHost != null) { myHost.returnData(ret); } } private int previousProgress = 0; private String previousProgressLabel = ""; /** * Used to communicate a progress update between a plugin tool and the main * Whitebox user interface. * * @param progressLabel A String to use for the progress label. * @param progress Float containing the progress value (between 0 and 100). */ private void updateProgress(String progressLabel, int progress) { if (myHost != null && ((progress != previousProgress) || (!progressLabel.equals(previousProgressLabel)))) { myHost.updateProgress(progressLabel, progress); } previousProgress = progress; previousProgressLabel = progressLabel; } /** * Used to communicate a progress update between a plugin tool and the main * Whitebox user interface. * * @param progress Float containing the progress value (between 0 and 100). */ private void updateProgress(int progress) { if (myHost != null && progress != previousProgress) { myHost.updateProgress(progress); } previousProgress = progress; } /** * Sets the arguments (parameters) used by the plugin. * * @param args An array of string arguments. */ @Override public void setArgs(String[] args) { this.args = args.clone(); } private boolean cancelOp = false; /** * Used to communicate a cancel operation from the Whitebox GUI. * * @param cancel Set to true if the plugin should be canceled. */ @Override public void setCancelOp(boolean cancel) { cancelOp = cancel; } private void cancelOperation() { showFeedback("Operation cancelled."); updateProgress("Progress: ", 0); } private boolean amIActive = false; /** * Used by the Whitebox GUI to tell if this plugin is still running. * * @return a boolean describing whether or not the plugin is actively being * used. */ @Override public boolean isActive() { return amIActive; } /** * Used to execute this plugin tool. */ @Override public void run() { amIActive = true; WhiteboxRaster image; int col, row, numImages, x, y; int cols, rows; int a = 0; double noData; double z, zn; int progress = 0; String progressMessage = ""; String inputFilesString = null; String[] imageFiles; long[] n; double[] mean; String[] shortNames; String[] units; double[] I; double[] stdDev; double totalDeviation; int[] dX; int[] dY; double numerator, W; //double recipRoot2 = 1 / Math.sqrt(2); //double[] wNeighbour = {recipRoot2, 1, recipRoot2, 1, recipRoot2, 1, recipRoot2, 1}; //double[] wNeighbour = {1, 1, 1, 1}; if (args.length <= 0) { showFeedback("Plugin parameters have not been set."); return; } inputFilesString = args[0]; imageFiles = inputFilesString.split(";"); numImages = imageFiles.length; if (args[1].toLowerCase().contains("bishop")) { dX = new int[] { 1, 1, -1, -1 }; dY = new int[] { -1, 1, 1, -1 }; } else if (args[1].toLowerCase().contains("queen") || args[1].toLowerCase().contains("king")) { dX = new int[] { 1, 1, 1, 0, -1, -1, -1, 0 }; dY = new int[] { -1, 0, 1, 1, 1, 0, -1, -1 }; } else { // go with the rook default dX = new int[] { 1, 0, -1, 0 }; dY = new int[] { 0, 1, 0, -1 }; } try { //initialize the image data arrays double sigmaZ; n = new long[numImages]; mean = new double[numImages]; I = new double[numImages]; shortNames = new String[numImages]; units = new String[numImages]; stdDev = new double[numImages]; double[] E_I = new double[numImages]; double[] varNormality = new double[numImages]; double[] varRandomization = new double[numImages]; double[] zN = new double[numImages]; double[] zR = new double[numImages]; double[] pValueN = new double[numImages]; double[] pValueR = new double[numImages]; double[] data; NormalDistribution distribution = new NormalDistribution(0, 1); for (a = 0; a < numImages; a++) { progressMessage = "Image " + (a + 1) + " of " + numImages; image = new WhiteboxRaster(imageFiles[a], "r"); noData = image.getNoDataValue(); rows = image.getNumberRows(); cols = image.getNumberColumns(); shortNames[a] = image.getShortHeaderFile(); if (!image.getZUnits().toLowerCase().equals("not specified")) { units[a] = image.getZUnits(); } else { units[a] = ""; } sigmaZ = 0; for (row = 0; row < rows; row++) { data = image.getRowValues(row); for (col = 0; col < cols; col++) { if (data[col] != noData) { sigmaZ += data[col]; n[a]++; } } if (cancelOp) { cancelOperation(); return; } progress = (int) (row * 100.0 / rows); updateProgress(progressMessage, progress); } mean[a] = sigmaZ / n[a]; E_I[a] = -1.0 / (n[a] - 1); totalDeviation = 0; W = 0; numerator = 0; double S2 = 0; double wij; int numNeighbours = dX.length; double k = 0; for (row = 0; row < rows; row++) { for (col = 0; col < cols; col++) { z = image.getValue(row, col); if (z != noData) { totalDeviation += (z - mean[a]) * (z - mean[a]); k += (z - mean[a]) * (z - mean[a]) * (z - mean[a]) * (z - mean[a]); wij = 0; for (int i = 0; i < numNeighbours; i++) { x = col + dX[i]; y = row + dY[i]; zn = image.getValue(y, x); if (zn != noData) { // two valid neighbour pairs W += 1.0; numerator += (z - mean[a]) * (zn - mean[a]); //* weight of 1.0 wij += 1; } } S2 += wij * wij; } } if (cancelOp) { cancelOperation(); return; } progress = (int) (row * 100.0 / rows); updateProgress(progressMessage, progress); } double S1 = 4 * W; S2 = S2 * 4; stdDev[a] = Math.sqrt(totalDeviation / (n[a] - 1)); I[a] = n[a] * numerator / (totalDeviation * W); varNormality[a] = (n[a] * n[a] * S1 - n[a] * S2 + 3 * W * W) / ((W * W) * (n[a] * n[a] - 1)); zN[a] = (I[a] - E_I[a]) / (Math.sqrt(varNormality[a])); pValueN[a] = 2d * (1.0 - distribution.cumulativeProbability(Math.abs(zN[a]))); k = k / (n[a] * stdDev[a] * stdDev[a] * stdDev[a] * stdDev[a]); varRandomization[a] = (n[a] * ((n[a] * n[a] - 3 * n[a] + 3) * S1 - n[a] * S2 + 3 * W * W) - k * (n[a] * n[a] - n[a]) * S1 - 2 * n[a] * S1 + 6 * W * W) / ((n[a] - 1) * (n[a] - 2) * (n[a] - 3) * W * W); zR[a] = (I[a] - E_I[a]) / (Math.sqrt(varRandomization[a])); pValueR[a] = 2d * (1.0 - distribution.cumulativeProbability(Math.abs(zR[a]))); image.close(); progress = (int) (100f * (a + 1) / numImages); updateProgress(progressMessage, progress); } StringBuilder retstr = new StringBuilder(); DecimalFormat df1 = new DecimalFormat("###,###,###,###"); DecimalFormat df2 = new DecimalFormat("0.0000"); retstr.append("SPATIAL AUTOCORRELATION\n"); for (a = 0; a < numImages; a++) { retstr.append("\n"); retstr.append("Input image:\t\t\t").append(shortNames[a]).append("\n"); retstr.append("Number of cells included:\t\t").append(df1.format(n[a])).append("\n"); if (units[a].equals("")) { retstr.append("Mean of cells included:\t\t").append(df2.format(mean[a])).append("\n"); } else { retstr.append("Mean of cells included:\t\t").append(df2.format(mean[a])).append(" ") .append(units[a]).append("\n"); } retstr.append("Spatial autocorrelation (Moran's I):\t").append(df2.format(I[a])).append("\n"); retstr.append("Expected value:\t\t").append(df2.format(E_I[a])).append("\n"); retstr.append("Variance of I (normality assumption):\t").append(df2.format(varNormality[a])) .append("\n"); retstr.append("z test stat (normality assumption):\t").append(df2.format(zN[a])).append("\n"); retstr.append("p-value (normality assumption):\t").append(df2.format(pValueN[a])).append("\n"); retstr.append("Variance of I (randomization assumption):\t").append(df2.format(varRandomization[a])) .append("\n"); retstr.append("z test stat (randomization assumption):\t").append(df2.format(zR[a])).append("\n"); retstr.append("p-value (randomization assumption):\t").append(df2.format(pValueR[a])).append("\n"); } // System.out.println(retstr.toString()); returnData(retstr.toString()); } 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(); } } // /** // * This method is only used for debugging the tool // * @param args // */ //// this is only used for debugging the tool // public static void main(String[] args) { // ImageAutocorrelation ia = new ImageAutocorrelation(); // args = new String[2]; // //args[0] = "/Users/johnlindsay/Documents/Data/Vermont DEM/Vermont DEM.dep;/Users/johnlindsay/Documents/Data/Change detection/Data/1992 GTA band4.dep"; // // args[0] = "/Users/johnlindsay/Documents/Data/Random fields/random1.dep;/Users/johnlindsay/Documents/Data/Random fields/random2.dep;" // + "/Users/johnlindsay/Documents/Data/Random fields/random3.dep;/Users/johnlindsay/Documents/Data/Random fields/random4.dep;" // + "/Users/johnlindsay/Documents/Data/Random fields/random5.dep;/Users/johnlindsay/Documents/Data/Random fields/random6.dep;" // + "/Users/johnlindsay/Documents/Data/Random fields/random7.dep;/Users/johnlindsay/Documents/Data/Random fields/checker board pattern.dep;" // + "/Users/johnlindsay/Documents/Data/Random fields/random8.dep"; // //// args[0] = "/Users/johnlindsay/Documents/Data/Random fields/random7.dep"; // // args[1] = "rook"; // ia.setArgs(args); // ia.run(); // // } }