Java DataTable.isNumerical方法代码示例

import com.rapidminer.datatable.DataTable; //导入方法依赖的package包/类
/**
 * Instantiates a new {@link SingleValueValueRange}.
 * 
 * The string representation is created based on the data type of a column in a data table.
 * 
 * @param value
 *            the value of the value range
 * @param dataTable
 *            a data table, from which the data type of the value is extracted
 * @param columnIdx
 *            the column index in data table which is used to extract the data type of the value
 * @throws IllegalArgumentException
 *             if the specified column has an unknown data type (i.e. neither numerical, nominal
 *             nor date).
 */
public SingleValueValueRange(double value, DataTable dataTable, int columnIdx) {
	this.value = value;
	this.columnIdx = columnIdx;
	if (columnIdx >= 0) {
		if (Double.isNaN(value)) {
			valueString = I18N.getGUILabel("plotter.unknown_value_label");
		} else if (dataTable.isNumerical(columnIdx)) {
			valueString = Double.toString(value);
		} else if (dataTable.isNominal(columnIdx)) {
			valueString = dataTable.mapIndex(columnIdx, (int) value);
		} else if (dataTable.isDateTime(columnIdx)) {
			valueString = Tools.formatDateTime(new Date((long) value));
		} else {
			throw new IllegalArgumentException("unknown data type in data table - this should not happen");
		}
	}
}
 

import com.rapidminer.datatable.DataTable; //导入方法依赖的package包/类
/**
 * @brief Creates a new {@link DataTableColumn}.
 * 
 *        name and value type are automatically initialized from the specified column in
 *        dataTable. The DataTableColumn does not keep a reference to dataTable.
 */
public DataTableColumn(DataTable dataTable, int columnIdx) {
	if (columnIdx >= 0 && columnIdx < dataTable.getColumnNumber()) {
		this.columnName = dataTable.getColumnName(columnIdx);
		if (dataTable.isDateTime(columnIdx)) {
			this.valueType = ValueType.DATE_TIME;
		} else if (dataTable.isNominal(columnIdx)) {
			this.valueType = ValueType.NOMINAL;
		} else if (dataTable.isNumerical(columnIdx)) {
			this.valueType = ValueType.NUMERICAL;
		} else {
			this.valueType = ValueType.INVALID;
		}
	} else {
		this.columnName = null;
		this.valueType = ValueType.INVALID;
	}
}
 

import com.rapidminer.datatable.DataTable; //导入方法依赖的package包/类
/**
 * Finds the column index for the column named columnName in dataTable, checks if that column in
 * the data table is compatible with to settings valueType, and updates this.columnIdx.
 * 
 * If the column does not exist or is not compatible, the columnIdx is set to -1.
 */
public static int getColumnIndex(DataTable dataTable, String columnName, ValueType valueType) {
	int columnIdx = dataTable.getColumnIndex(columnName);
	if (columnIdx >= 0) {
		// check value type
		switch (valueType) {
			case NOMINAL:
				if (!dataTable.isNominal(columnIdx)) {
					columnIdx = -1;
				}
				break;
			case NUMERICAL:
				if (!dataTable.isNumerical(columnIdx)) {
					columnIdx = -1;
				}
				break;
			case DATE_TIME:
				if (!dataTable.isDateTime(columnIdx)) {
					columnIdx = -1;
				}
				break;
			case INVALID:
				// do nothing
				break;
		}
	}
	return columnIdx;
}
 

import com.rapidminer.datatable.DataTable; //导入方法依赖的package包/类
@Override
public void doWork() throws OperatorException {
	DataTable table = null;
	if (isParameterSet(PARAMETER_LOG_NAME)) {
		String dataTableName = getParameterAsString(PARAMETER_LOG_NAME);
		table = getProcess().getDataTable(dataTableName);
	} else {
		if (getProcess().getDataTables().size() > 0) {
			table = getProcess().getDataTables().iterator().next();
			logNote("No log name was specified, using first data table found...");
		}
	}

	// check
	if (table == null) {
		throw new UserError(this, 939);
	}

	// create attributes
	List<Attribute> attributes = new ArrayList<Attribute>();
	for (int i = 0; i < table.getNumberOfColumns(); i++) {
		String name = table.getColumnName(i);
		if (table.isDate(i)) {
			attributes.add(AttributeFactory.createAttribute(name, Ontology.DATE));
		} else if (table.isDateTime(i)) {
			attributes.add(AttributeFactory.createAttribute(name, Ontology.DATE_TIME));
		} else if (table.isNumerical(i)) {
			attributes.add(AttributeFactory.createAttribute(name, Ontology.REAL));
		} else {
			attributes.add(AttributeFactory.createAttribute(name, Ontology.NOMINAL));
		}
	}

	// create table
	MemoryExampleTable exampleTable = new MemoryExampleTable(attributes);
	for (int r = 0; r < table.getNumberOfRows(); r++) {
		DataTableRow row = table.getRow(r);
		double[] data = new double[attributes.size()];
		for (int i = 0; i < table.getNumberOfColumns(); i++) {
			if (table.isDate(i)) {
				data[i] = row.getValue(i);
			} else if (table.isDateTime(i)) {
				data[i] = row.getValue(i);
			} else if (table.isNumerical(i)) {
				data[i] = row.getValue(i);
			} else {
				Attribute attribute = attributes.get(i);
				String value = table.getValueAsString(row, i);
				data[i] = attribute.getMapping().mapString(value);
			}
		}
		exampleTable.addDataRow(new DoubleArrayDataRow(data));
	}

	// create and return example set
	exampleSetOutput.deliver(exampleTable.createExampleSet());
	dummyPorts.passDataThrough();
}
 

import com.rapidminer.datatable.DataTable; //导入方法依赖的package包/类
private void populateCategoryMap(DataTable dataTable) {
	this.categoryToColumnListMap.put(HeuristicPlotterConfigurator.NUMERICAL, new ArrayList<String>());
	this.categoryToColumnListMap.put(HeuristicPlotterConfigurator.LABEL, new ArrayList<String>());
	this.categoryToColumnListMap.put(HeuristicPlotterConfigurator.NOMINAL, new ArrayList<String>());
	this.categoryToColumnListMap.put(HeuristicPlotterConfigurator.DATE, new ArrayList<String>());

	for (int i = 0; i < dataTable.getNumberOfColumns(); i++) {
		if (dataTable.isNumerical(i)) {
			this.categoryToColumnListMap.get(HeuristicPlotterConfigurator.NUMERICAL).add(dataTable.getColumnName(i));
		}
		if (dataTable.isNominal(i)) {
			if (dataTable.getNumberOfValues(i) <= MAX_NOMINAL_VALUES) {
				this.categoryToColumnListMap.get(HeuristicPlotterConfigurator.NOMINAL).add(dataTable.getColumnName(i));
			}
		}
		if (dataTable.isDateTime(i)) {
			this.categoryToColumnListMap.get(HeuristicPlotterConfigurator.DATE).add(dataTable.getColumnName(i));
		}
	}

	if (dataTable instanceof DataTableExampleSetAdapter) {
		DataTableExampleSetAdapter mine = (DataTableExampleSetAdapter) dataTable;

		String labelName = mine.getLabelName();
		if (labelName != null) {

			if (mine.isLabelNominal()) {
				// only add nominal labels with less than MAX_NOMINAL_VALUES different values
				if (mine.getNumberOfValues(mine.getColumnIndex(labelName)) <= MAX_NOMINAL_VALUES) {
					this.categoryToColumnListMap.get(HeuristicPlotterConfigurator.NOMINAL).add(labelName);
					this.categoryToColumnListMap.get(HeuristicPlotterConfigurator.LABEL).add(labelName);
				}
			} else {
				this.categoryToColumnListMap.get(HeuristicPlotterConfigurator.LABEL).add(labelName);
			}
			// remove Label from the numerical attribute list
			if (this.categoryToColumnListMap.get(HeuristicPlotterConfigurator.NUMERICAL).contains(labelName)) {
				this.categoryToColumnListMap.get(HeuristicPlotterConfigurator.NUMERICAL).remove(labelName);
			}
		}
		// if there is a cluster attribute it can be handled as an additional label for axis
		// selection:
		if (mine.getClusterName() != null) {
			this.categoryToColumnListMap.get(HeuristicPlotterConfigurator.LABEL).add(mine.getClusterName());
		}

	} else { // set empty values unless Label and Nominal are already set
		if (categoryToColumnListMap.get(HeuristicPlotterConfigurator.LABEL).equals("")) {
			this.categoryToColumnListMap.put(HeuristicPlotterConfigurator.LABEL, new ArrayList<String>());
		}
		if (categoryToColumnListMap.get(HeuristicPlotterConfigurator.NOMINAL).equals("")) {
			this.categoryToColumnListMap.put(HeuristicPlotterConfigurator.NOMINAL, new ArrayList<String>());
		}
	}
}