/**
* Returns delta (difference) between model2 and model1. Delta = model2 - model1 .
*
* <p>Both models must have exactly the same number of columns and rows.
*
* @param heatMapModel1
* @param heatMapModel2
* @return
*/
public static BioHeatMapModel delta(
BioHeatMapModel heatMapModel1, BioHeatMapModel heatMapModel2) {
if (heatMapModel2.getColumns().size() != heatMapModel1.getColumns().size()) {
throw new IllegalArgumentException("Number of columns in both models is not the same.");
}
List<HeatMapColumn> columns = new ArrayList<HeatMapColumn>();
for (int columnIndex = 0; columnIndex < heatMapModel2.getColumns().size(); columnIndex++) {
HeatMapColumn model2Column = heatMapModel2.getColumns().get(columnIndex);
HeatMapColumn model1Column = heatMapModel1.getColumns().get(columnIndex);
if (model2Column.getValues().size() != model1Column.getValues().size()) {
throw new IllegalArgumentException(
"Number of values in both columns for both models is not the same.");
}
List<HeatMapValue> values = new ArrayList<HeatMapValue>();
for (int valueIndex = 0; valueIndex < model2Column.getValues().size(); valueIndex++) {
HeatMapValue model2Value = model2Column.getValues().get(valueIndex);
HeatMapValue model1Value = model1Column.getValues().get(valueIndex);
values.add(
new HeatMapValue(
model2Value.getRowValue(),
model2Value.getCellValue() - model1Value.getCellValue()));
}
columns.add(new HeatMapColumn(model2Column.getLabel(), values));
}
BioHeatMapModel delta = new BioHeatMapModel(columns);
return delta;
}
/**
* Returns market traded volume in a form of bio heat map. The range min/max allows to zoom in/out
* inside the market traded volume and to analyse given range of probabilities in more details.
*
* @param marketTradedVolume
* @param min Minimum probability of traded volume that the heat map model is created for. From 0
* to 1
* @param max Maximum probability of traded volume that the heat map model is created for. From 0
* to 1
* @return
*/
public static BioHeatMapModel createHeatMap(BioHeatMapModel ds, double min, double max) {
List<HeatMapColumn> columns = new ArrayList<HeatMapColumn>();
for (int columnIndex = 0; columnIndex < ds.getColumns().size(); columnIndex++) {
HeatMapColumn column = ds.getColumns().get(columnIndex);
/** Create 100 empty values */
List<HeatMapValue> values = new ArrayList<HeatMapValue>();
for (int rowIndex = 0; rowIndex < 101; rowIndex++) {
double rowValue = ((double) rowIndex / 100 * (max - min) + min);
values.add(new HeatMapValue(rowValue, 0));
}
/** Reduce input values. */
for (int rowIndex = 0; rowIndex < column.getValues().size(); rowIndex++) {
double prob = 1 / column.getValues().get(rowIndex).getRowValue();
if (prob >= min && prob <= max) {
double scaledProb = (prob - min) / (max - min);
HeatMapValue value = values.get((int) (scaledProb * 100));
value.setCellValue(
value.getCellValue() + column.getValues().get(rowIndex).getCellValue());
}
}
columns.add(new HeatMapColumn(column.getLabel(), values));
}
BioHeatMapModel heatMapModel = new BioHeatMapModel(columns);
return heatMapModel;
}
