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);
}
}
