public static IDataset interpolate(IDataset oldx, IDataset oldy, IDataset newx) {
// TODO more sanity checks on inputs
DoubleDataset dx = (DoubleDataset) DatasetUtils.cast(oldx, Dataset.FLOAT64);
DoubleDataset dy = (DoubleDataset) DatasetUtils.cast(oldy, Dataset.FLOAT64);
boolean sorted = true;
double maxtest = oldx.getDouble(0);
for (int i = 1; i < ((Dataset) oldx).count(); i++) {
if (maxtest > oldx.getDouble(i)) {
sorted = false;
break;
}
maxtest = dx.getDouble(i);
}
double[] sortedx = null;
double[] sortedy = null;
if (!sorted) {
IntegerDataset sIdx = getIndiciesOfSorted(dx);
sortedx = new double[dx.getData().length];
sortedy = new double[dy.getData().length];
for (int i = 0; i < sIdx.getSize(); i++) {
sortedx[i] = dx.getDouble(sIdx.get(i));
sortedy[i] = dy.getDouble(sIdx.get(i));
}
} else {
sortedx = dx.getData();
sortedy = dy.getData();
}
SplineInterpolator si = new SplineInterpolator();
PolynomialSplineFunction poly = si.interpolate(sortedx, sortedy);
IDataset newy = newx.clone();
newy.setName(oldy.getName() + "_interpolated");
for (int i = 0; i < ((Dataset) newx).count(); i++) {
newy.set(poly.value(newx.getDouble(i)), i);
}
return newy;
}
@Test
public void testFunction() {
AFunction f = new StraightLine();
Assert.assertEquals(2, f.getNoOfParameters());
f.setParameterValues(23., -10.);
Assert.assertArrayEquals(new double[] {23., -10.}, f.getParameterValues(), ABS_TOL);
Assert.assertEquals(23. - 10., f.val(1), ABS_TOL);
DoubleDataset xd = new DoubleDataset(new double[] {-1, 0, 2});
DoubleDataset dx;
dx = f.calculateValues(xd);
Assert.assertArrayEquals(new double[] {-23. - 10, -10, 23. * 2 - 10.}, dx.getData(), ABS_TOL);
dx = f.calculatePartialDerivativeValues(f.getParameter(0), xd);
Assert.assertArrayEquals(new double[] {-1, 0, 2}, dx.getData(), ABS_TOL);
dx = f.calculatePartialDerivativeValues(f.getParameter(1), xd);
Assert.assertArrayEquals(new double[] {1, 1, 1}, dx.getData(), ABS_TOL);
Assert.assertEquals(-1, f.partialDeriv(f.getParameter(0), -1), ABS_TOL);
Assert.assertEquals(1, f.partialDeriv(f.getParameter(1), -1), ABS_TOL);
}
public double absorptionCorrectionCommon(boolean isSampleScatterer, boolean isSampleAttenuator) {
// Make the two components as ComponentGeometries
XPDFComponentGeometry sample = new XPDFComponentCylinder();
XPDFComponentGeometry capillary = new XPDFComponentCylinder();
sample.setDistances(0.0, 0.15);
sample.setStreamality(true, true);
capillary.setDistances(0.15, 0.16);
capillary.setStreamality(true, true);
XPDFComponentGeometry scatterer = (isSampleScatterer) ? sample : capillary;
XPDFComponentGeometry attenuator = (isSampleAttenuator) ? sample : capillary;
// These will be calculated by the Composition class
double quartzAttenuationCoefficient = 0.0529783195963;
double ceriaAttenuationCoefficient = 1.86349597825;
double attenuationCoefficient =
(isSampleAttenuator) ? ceriaAttenuationCoefficient : quartzAttenuationCoefficient;
XPDFBeamData beamData = new XPDFBeamData();
beamData.setBeamEnergy(76.6);
beamData.setBeamHeight(0.07);
beamData.setBeamWidth(0.07);
// Read the target data, and also the angles (in radians) to run
String dataPath = "/home/rkl37156/ceria_dean_data/";
IDataHolder dh = null;
String scattererName, attenuatorName;
scattererName = (isSampleScatterer) ? "sample" : "container";
attenuatorName = (isSampleAttenuator) ? "sample" : "container";
try {
dh = LoaderFactory.getData(dataPath + scattererName + "_" + attenuatorName + "_abs.xy");
} catch (Exception e) {
}
Dataset delta1D = DatasetUtils.convertToDataset(dh.getLazyDataset("Column_1").getSlice());
Dataset delta = new DoubleDataset(delta1D.getSize(), 1);
for (int i = 0; i < delta1D.getSize(); i++) delta.set(delta1D.getDouble(i), i, 0);
Dataset gamma = DoubleDataset.zeros(delta);
Dataset expected = DatasetUtils.convertToDataset(dh.getLazyDataset("Column_2").getSlice());
expected.setShape(expected.getSize(), 1);
Dataset calculated =
scatterer.calculateAbsorptionCorrections(
gamma, delta, attenuator, attenuationCoefficient, beamData, true, true);
// calculated.squeeze();
Dataset difference = Maths.subtract(calculated, expected);
return Math.sqrt((Double) Maths.square(difference).mean());
}
public void testGetUpstreamPathLength() {
XPDFComponentCylinder cap = new XPDFComponentCylinder();
cap.setDistances(0.15, 0.16);
cap.setStreamality(true, true);
final int xSize = 64, ySize = 64;
Dataset pathLengthExp = new DoubleDataset(xSize, ySize);
Dataset pathLength = new DoubleDataset(pathLengthExp);
Dataset r = new DoubleDataset(pathLengthExp);
Dataset xi = new DoubleDataset(pathLengthExp);
// Read the data from file
String fileDirectory = "/home/rkl37156/ceria_dean_data/";
Dataset[] datasets = {pathLengthExp, r, xi};
String[] files = {"incoming", "sample_r", "sample_xi"};
for (int k = 0; k < 3; k++) {
Path filePath = new File(fileDirectory + files[k] + ".txt").toPath();
List<String> filelines = new ArrayList<String>();
try {
filelines = Files.readAllLines(filePath);
} catch (Exception e) {
fail("Error reading " + filePath.toString());
}
for (int i = 0; i < ySize; i++) {
String[] splitline = filelines.get(i).split(" ");
for (int j = 0; j < xSize; j++) {
double assignee = Double.parseDouble(splitline[j]);
datasets[k].set(assignee, i, j);
}
}
}
Dataset x = Maths.multiply(r, Maths.sin(xi));
Dataset z = Maths.multiply(r, Maths.cos(xi));
Dataset y = DoubleDataset.zeros(x);
pathLength = cap.getUpstreamPathLength(x, y, z);
double rmsError =
Math.sqrt((Double) Maths.square(Maths.subtract(pathLength, pathLengthExp)).mean());
assertTrue("Error in upstream path length too large", rmsError < 1e-6);
// fail("Not yet implemented");
}
protected void updateChannelGraphs() {
if (histograms != null && histograms.size() > 1) {
// remove red channel graph
histograms.remove(0);
// remove green channel graph
histograms.remove(0);
// remove blue channel graph
histograms.remove(0);
// remove alpha channel graph
histograms.remove(0);
}
AbstractMapFunction redFunc = GlobalColourMaps.mappingFunctions.get(curRedSelect);
AbstractMapFunction greenFunc = GlobalColourMaps.mappingFunctions.get(curGreenSelect);
AbstractMapFunction blueFunc = GlobalColourMaps.mappingFunctions.get(curBlueSelect);
AbstractMapFunction alphaFunc = GlobalColourMaps.mappingFunctions.get(curAlphaSelect);
double maxValue = histograms.get(0).max().doubleValue();
int currentSize = histograms.get(0).getSize();
DoubleDataset redChannel = new DoubleDataset(currentSize);
DoubleDataset greenChannel = new DoubleDataset(currentSize);
DoubleDataset blueChannel = new DoubleDataset(currentSize);
DoubleDataset alphaChannel = new DoubleDataset(currentSize);
for (int i = 0; i < currentSize; i++) {
double value = i / (double) currentSize;
double redvalue = redFunc.getPoint(value);
if (curRedInverse) redvalue = 1.0 - redvalue;
redvalue *= maxValue;
double greenvalue = greenFunc.getPoint(value);
if (curGreenInverse) greenvalue = 1.0 - greenvalue;
greenvalue *= maxValue;
double bluevalue = blueFunc.getPoint(value);
if (curBlueInverse) bluevalue = 1.0 - bluevalue;
bluevalue *= maxValue;
double alphavalue = alphaFunc.getPoint(value);
if (curAlphaInverse) alphavalue = 1.0 - alphavalue;
alphavalue *= maxValue;
redChannel.set(Math.max(redvalue, 0.0), i);
greenChannel.set(Math.max(greenvalue, 0.0), i);
blueChannel.set(Math.max(bluevalue, 0.0), i);
alphaChannel.set(Math.max(alphavalue, 0.0), i);
}
histograms.add(0, alphaChannel);
histograms.add(0, blueChannel);
histograms.add(0, greenChannel);
histograms.add(0, redChannel);
// Some logging to check on the histograms size
logger.debug("number of histograms stored is {}", histograms.size());
if (histograms.size() > 10) {
logger.warn(
"Number of stored histograms is over expected levels, now at {}", histograms.size());
}
try {
histogramPlotter.replaceAllPlots(histograms);
} catch (PlotException e) {
e.printStackTrace();
}
}
public void testGetDownstreamPathLength() {
XPDFComponentCylinder cap = new XPDFComponentCylinder();
cap.setDistances(0.15, 0.16);
cap.setStreamality(true, true);
final int xSize = 64, ySize = 64;
Dataset pathLengthExp = new DoubleDataset(xSize, ySize);
Dataset pathLength = new DoubleDataset(pathLengthExp);
Dataset r = new DoubleDataset(xSize, ySize);
Dataset xi = new DoubleDataset(r);
String[] angles = {"0.0", "15.0", "28.5", "29.5", "47.0"};
int nAngles = angles.length;
for (String angle : angles) {
// Read the data from file
String fileDirectory = "/home/rkl37156/ceria_dean_data/";
Dataset[] datasets = {pathLengthExp, r, xi};
String[] files = {"outgoing" + angle, "sample_r", "sample_xi"};
for (int k = 0; k < 3; k++) {
Path filePath = new File(fileDirectory + files[k] + ".txt").toPath();
List<String> filelines = new ArrayList<String>();
try {
filelines = Files.readAllLines(filePath);
} catch (Exception e) {
fail("Error reading " + filePath.toString());
}
for (int i = 0; i < ySize; i++) {
String[] splitline = filelines.get(i).split(" ");
for (int j = 0; j < xSize; j++) {
double assignee = Double.parseDouble(splitline[j]);
datasets[k].set(assignee, i, j);
}
}
}
Dataset x = Maths.multiply(r, Maths.sin(xi));
Dataset z = Maths.multiply(r, Maths.cos(xi));
Dataset y = DoubleDataset.zeros(x);
pathLength =
cap.getDownstreamPathLength(x, y, z, 0.0, Math.toRadians(Double.parseDouble(angle)));
// TODO: remove temporary write command
try (Writer fileWriter =
new BufferedWriter(
new OutputStreamWriter(
new FileOutputStream(
"/home/rkl37156/ceria_dean_data/outgoing" + angle + ".java.txt"),
"utf-8"))) {
for (int i = 0; i < ySize; i++) {
for (int j = 0; j < xSize; j++) {
fileWriter.write(((Double) pathLength.getDouble(i, j)).toString() + " ");
}
fileWriter.write(13); // Carriage return
}
} catch (Exception e) {;
}
double rmsError =
Math.sqrt((Double) Maths.square(Maths.subtract(pathLength, pathLengthExp)).mean());
assertTrue(
"Error in downstream path length at " + angle + " too large: " + rmsError,
rmsError < 1e-6);
}
}
