org.eclipse.dawnsci.nexus.impl.NXlogImpl Maven / Gradle / Ivy

/*-
 *******************************************************************************
 * Copyright (c) 2015 Diamond Light Source Ltd.
 * All rights reserved. This program and the accompanying materials
 * are made available under the terms of the Eclipse Public License v1.0
 * which accompanies this distribution, and is available at
 * http://www.eclipse.org/legal/epl-v10.html
 *
 * This file was auto-generated from the NXDL XML definition.
 *******************************************************************************/

package org.eclipse.dawnsci.nexus.impl;

import java.util.Date;
import java.util.EnumSet;
import java.util.Set;

import org.eclipse.dawnsci.analysis.api.tree.DataNode;
import org.eclipse.dawnsci.nexus.NXlog;
import org.eclipse.dawnsci.nexus.NXobject;
import org.eclipse.dawnsci.nexus.NexusBaseClass;
import org.eclipse.january.dataset.IDataset;

/**
 * Information recorded as a function of time.
 * Description of information that is recorded against
 * time. There are two common use cases for this:
 * - When logging data such as temperature during a run
 * - When data is taken in streaming mode data acquisition,
 * i.e. just timestamp, value pairs are stored and
 * correlated later in data reduction with other data,
 * In both cases, NXlog contains
 * the logged or streamed values and the times at which they were measured as elapsed time since a starting
 * time recorded in ISO8601 format. The time units are
 * specified in the units attribute. An optional scaling attribute
 * can be used to accomodate non standard clocks.
 * This method of storing logged data helps to distinguish
 * instances in which a variable is a dimension scale of the data, in which case it is stored
 * in an :ref:`NXdata` group, and instances in which it is logged during the
 * run, when it should be stored in an :ref:`NXlog` group.
 * In order to make random access to timestamped data faster there is an optional array pair of
 * ``cue_timestamp_zero`` and ``cue_index``. The ``cue_timestamp_zero`` will
 * contain coarser timestamps than in the time array, say
 * every five minutes. The ``cue_index`` will then contain the
 * index into the time,value pair of arrays for that
 * coarser ``cue_timestamp_zero``.
 * 
 */
public class NXlogImpl extends NXobjectImpl implements NXlog {

	private static final long serialVersionUID = 1L;  // no state in this class, so always compatible


	public static final Set PERMITTED_CHILD_GROUP_CLASSES = EnumSet.noneOf(NexusBaseClass.class);

	public NXlogImpl() {
		super();
	}

	public NXlogImpl(final long oid) {
		super(oid);
	}
	
	@Override
	public Class getNXclass() {
		return NXlog.class;
	}
	
	@Override
	public NexusBaseClass getNexusBaseClass() {
		return NexusBaseClass.NX_LOG;
	}
	
	@Override
	public Set getPermittedChildGroupClasses() {
		return PERMITTED_CHILD_GROUP_CLASSES;
	}
	

	@Override
	public IDataset getTime() {
		return getDataset(NX_TIME);
	}

	@Override
	public Number getTimeScalar() {
		return getNumber(NX_TIME);
	}

	@Override
	public DataNode setTime(IDataset time) {
		return setDataset(NX_TIME, time);
	}

	@Override
	public DataNode setTimeScalar(Number time) {
		return setField(NX_TIME, time);
	}

	@Override
	public Date getTimeAttributeStart() {
		return getAttrDate(NX_TIME, NX_TIME_ATTRIBUTE_START);
	}

	@Override
	public void setTimeAttributeStart(Date start) {
		setAttribute(NX_TIME, NX_TIME_ATTRIBUTE_START, start);
	}

	@Override
	public Number getTimeAttributeScaling_factor() {
		return getAttrNumber(NX_TIME, NX_TIME_ATTRIBUTE_SCALING_FACTOR);
	}

	@Override
	public void setTimeAttributeScaling_factor(Number scaling_factor) {
		setAttribute(NX_TIME, NX_TIME_ATTRIBUTE_SCALING_FACTOR, scaling_factor);
	}

	@Override
	public IDataset getValue() {
		return getDataset(NX_VALUE);
	}

	@Override
	public Number getValueScalar() {
		return getNumber(NX_VALUE);
	}

	@Override
	public DataNode setValue(IDataset value) {
		return setDataset(NX_VALUE, value);
	}

	@Override
	public DataNode setValueScalar(Number value) {
		return setField(NX_VALUE, value);
	}

	@Override
	public IDataset getRaw_value() {
		return getDataset(NX_RAW_VALUE);
	}

	@Override
	public Number getRaw_valueScalar() {
		return getNumber(NX_RAW_VALUE);
	}

	@Override
	public DataNode setRaw_value(IDataset raw_value) {
		return setDataset(NX_RAW_VALUE, raw_value);
	}

	@Override
	public DataNode setRaw_valueScalar(Number raw_value) {
		return setField(NX_RAW_VALUE, raw_value);
	}

	@Override
	public IDataset getDescription() {
		return getDataset(NX_DESCRIPTION);
	}

	@Override
	public String getDescriptionScalar() {
		return getString(NX_DESCRIPTION);
	}

	@Override
	public DataNode setDescription(IDataset description) {
		return setDataset(NX_DESCRIPTION, description);
	}

	@Override
	public DataNode setDescriptionScalar(String description) {
		return setString(NX_DESCRIPTION, description);
	}

	@Override
	public IDataset getAverage_value() {
		return getDataset(NX_AVERAGE_VALUE);
	}

	@Override
	public Double getAverage_valueScalar() {
		return getDouble(NX_AVERAGE_VALUE);
	}

	@Override
	public DataNode setAverage_value(IDataset average_value) {
		return setDataset(NX_AVERAGE_VALUE, average_value);
	}

	@Override
	public DataNode setAverage_valueScalar(Double average_value) {
		return setField(NX_AVERAGE_VALUE, average_value);
	}

	@Override
	public IDataset getAverage_value_error() {
		return getDataset(NX_AVERAGE_VALUE_ERROR);
	}

	@Override
	public Double getAverage_value_errorScalar() {
		return getDouble(NX_AVERAGE_VALUE_ERROR);
	}

	@Override
	public DataNode setAverage_value_error(IDataset average_value_error) {
		return setDataset(NX_AVERAGE_VALUE_ERROR, average_value_error);
	}

	@Override
	public DataNode setAverage_value_errorScalar(Double average_value_error) {
		return setField(NX_AVERAGE_VALUE_ERROR, average_value_error);
	}

	@Override
	public IDataset getMinimum_value() {
		return getDataset(NX_MINIMUM_VALUE);
	}

	@Override
	public Double getMinimum_valueScalar() {
		return getDouble(NX_MINIMUM_VALUE);
	}

	@Override
	public DataNode setMinimum_value(IDataset minimum_value) {
		return setDataset(NX_MINIMUM_VALUE, minimum_value);
	}

	@Override
	public DataNode setMinimum_valueScalar(Double minimum_value) {
		return setField(NX_MINIMUM_VALUE, minimum_value);
	}

	@Override
	public IDataset getMaximum_value() {
		return getDataset(NX_MAXIMUM_VALUE);
	}

	@Override
	public Double getMaximum_valueScalar() {
		return getDouble(NX_MAXIMUM_VALUE);
	}

	@Override
	public DataNode setMaximum_value(IDataset maximum_value) {
		return setDataset(NX_MAXIMUM_VALUE, maximum_value);
	}

	@Override
	public DataNode setMaximum_valueScalar(Double maximum_value) {
		return setField(NX_MAXIMUM_VALUE, maximum_value);
	}

	@Override
	public IDataset getDuration() {
		return getDataset(NX_DURATION);
	}

	@Override
	public Double getDurationScalar() {
		return getDouble(NX_DURATION);
	}

	@Override
	public DataNode setDuration(IDataset duration) {
		return setDataset(NX_DURATION, duration);
	}

	@Override
	public DataNode setDurationScalar(Double duration) {
		return setField(NX_DURATION, duration);
	}

	@Override
	public IDataset getCue_timestamp_zero() {
		return getDataset(NX_CUE_TIMESTAMP_ZERO);
	}

	@Override
	public Number getCue_timestamp_zeroScalar() {
		return getNumber(NX_CUE_TIMESTAMP_ZERO);
	}

	@Override
	public DataNode setCue_timestamp_zero(IDataset cue_timestamp_zero) {
		return setDataset(NX_CUE_TIMESTAMP_ZERO, cue_timestamp_zero);
	}

	@Override
	public DataNode setCue_timestamp_zeroScalar(Number cue_timestamp_zero) {
		return setField(NX_CUE_TIMESTAMP_ZERO, cue_timestamp_zero);
	}

	@Override
	public Date getCue_timestamp_zeroAttributeStart() {
		return getAttrDate(NX_CUE_TIMESTAMP_ZERO, NX_CUE_TIMESTAMP_ZERO_ATTRIBUTE_START);
	}

	@Override
	public void setCue_timestamp_zeroAttributeStart(Date start) {
		setAttribute(NX_CUE_TIMESTAMP_ZERO, NX_CUE_TIMESTAMP_ZERO_ATTRIBUTE_START, start);
	}

	@Override
	public Number getCue_timestamp_zeroAttributeScaling_factor() {
		return getAttrNumber(NX_CUE_TIMESTAMP_ZERO, NX_CUE_TIMESTAMP_ZERO_ATTRIBUTE_SCALING_FACTOR);
	}

	@Override
	public void setCue_timestamp_zeroAttributeScaling_factor(Number scaling_factor) {
		setAttribute(NX_CUE_TIMESTAMP_ZERO, NX_CUE_TIMESTAMP_ZERO_ATTRIBUTE_SCALING_FACTOR, scaling_factor);
	}

	@Override
	public IDataset getCue_index() {
		return getDataset(NX_CUE_INDEX);
	}

	@Override
	public Long getCue_indexScalar() {
		return getLong(NX_CUE_INDEX);
	}

	@Override
	public DataNode setCue_index(IDataset cue_index) {
		return setDataset(NX_CUE_INDEX, cue_index);
	}

	@Override
	public DataNode setCue_indexScalar(Long cue_index) {
		return setField(NX_CUE_INDEX, cue_index);
	}

}