Examples of org.aavso.tools.vstar.data.ValidObservation

org.aavso.tools.vstar.data.ValidObservation

This class corresponds to a single valid variable star observation. Depending upon the source, some fields may be null. Some are not permitted to be null however and these are documented below.

For reference, here are the fields in the order they appear in the AAVSO download format:

JD(0), MAGNITUDE(1), UNCERTAINTY(2), HQ_UNCERTAINTY(3), BAND(4), OBSERVER_CODE(5), COMMENT_CODE(6), COMP_STAR_1(7), COMP_STAR_2(8), CHARTS(9), COMMENTS(10), TRANSFORMED(11), AIRMASS(12), VALFLAG(13), CMAG(14), KMAG(15), HJD(16), NAME(17), AFFILIATION(18), MTYPE(19), GROUP(20)

The simple format file has these fields:

JD MAGNITUDE [UNCERTAINTY] [OBSERVER_CODE] [VALFLAG]

When VStar was first developed, observation source plugins were not anticipated, but should have been. The additional details members permit other string-based information to be stored for an observation.

  protected Listener<ObservationSelectionMessage> createObservationSelectionListener() {
    final JPanel parent = this;
    return new Listener<ObservationSelectionMessage>() {
      public void update(ObservationSelectionMessage message) {
        if (message.getSource() != parent) {
          ValidObservation ob = message.getObservation();
          Integer rowIndex = validDataModel
              .getRowIndexFromObservation(ob);
          if (rowIndex != null && rowIndex >= 0) {
            try {
              // Convert to view index!

View Full Code Here

      if (rows.length > 1) {
        // This is a multiple observation selection.
        List<ValidObservation> obs = new ArrayList<ValidObservation>();
        for (int row : rows) {
          row = validDataTable.convertRowIndexToModel(row);
          ValidObservation ob = validDataModel.getObservations().get(
              row);
          obs.add(ob);
        }
        MultipleObservationSelectionMessage message = new MultipleObservationSelectionMessage(
            obs, this);


        Mediator.getInstance()
            .getMultipleObservationSelectionNotifier()
            .notifyListeners(message);


        selectedObs.clear();
        selectedObs.addAll(obs);
        createFilterButton.setEnabled(true);
      } else {
        // This is a single observation selection.
        int row = validDataTable.getSelectedRow();


        if (row >= 0) {
          row = validDataTable.convertRowIndexToModel(row);
          ValidObservation ob = validDataModel.getObservations().get(
              row);
          lastObSelected = ob;
          ObservationSelectionMessage message = new ObservationSelectionMessage(
              ob, this);
          Mediator.getInstance().getObservationSelectionNotifier()

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   * @see javax.swing.table.TableModel#getValueAt(int, int)
   */
  public Object getValueAt(int rowIndex, int columnIndex) {
    assert columnIndex < COLUMN_COUNT;


    ValidObservation ob = obs.get(rowIndex);


    Object value = null;


    switch (columnIndex) {
    case PHASE_COLUMN:
      if (rowIndex < obs.size() / 2) {
        value = NumericPrecisionPrefs.formatTime(ob
            .getPreviousCyclePhase());
      } else {
        value = NumericPrecisionPrefs.formatTime(ob.getStandardPhase());
      }
      break;
    case MEAN_COLUMN:
      // The mean magnitude.
      value = NumericPrecisionPrefs.formatMag(ob.getMagnitude()
          .getMagValue());
      break;
    case STDERR_COLUMN:
      // The standard error of the average.
      value = NumericPrecisionPrefs.formatMag(ob.getMagnitude()
          .getUncertainty());
      break;
    }


    return value;

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        // so add a ValidObservation containing mean and error value
        // to the list.
        Bin bin = createMeanObservationForRange(observations,
            timeElementEntity, i + 1, maxIndex);


        ValidObservation ob = bin.getMeanObservation();


        // If the mean magnitude value is NaN (e.g. because
        // there was no valid data in the range in question),
        // it doesn't make sense to include this bin.
        if (!Double.isNaN(ob.getMag())) {
          // Notice that we add to the start of the list
          // to avoid having to reverse the list since we
          // are moving from right to left along the original
          // list.
          binnedObs.add(0, ob);

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        // so add a ValidObservation containing mean and error value
        // to the list.
        Bin bin = createMeanObservationForRange(observations,
            timeElementEntity, minIndex, i - 1);


        ValidObservation ob = bin.getMeanObservation();


        // If the mean magnitude value is NaN (e.g. because
        // there was no valid data in the range in question),
        // it doesn't make sense to include this bin.
        if (!Double.isNaN(ob.getMag())) {
          binnedObs.add(ob);
          bins.add(bin.getMagnitudes());
        }


        if (i < observations.size()) {

View Full Code Here

   */
  public void retrieveObservations() throws ObservationReadError,
      InterruptedException {
    try {
      while (!wasInterrupted() && source.next()) {
        ValidObservation validOb = null;


        // If there's an error in an SQL row, create an invalid
        // observation for it.
        try {
          validOb = getNextObservation();
        } catch (SQLException e) {
          int uniqueId = source.getInt("unique_id");
          InvalidObservation invalidOb = new InvalidObservation(
              "Row with unique ID " + uniqueId, e
                  .getLocalizedMessage());
          invalidOb.setRecordNumber(source.getRow());
          invalidObservations.add(invalidOb);
          continue;
        }


        // TODO: When we do more field validation here,
        // we should do these checks in getNextObservation()
        // and just throw an exception; something like ValidationError?
        // May need to modify some validators to take types other than
        // string. Actually, another approach is to read all fields as
        // strings and then do *exactly* the same validation as for file
        // sourced data.


        if (validOb.getMagnitude().isBrighterThan()) {
          InvalidObservation invalidOb = new InvalidObservation("JD "
              + validOb.getJD(),
              "A \"Brighter Than\" observation.");
          invalidObservations.add(invalidOb);
        } else if (validOb.getHqUncertainty() != null
            && !uncertaintyRangePredicate.holds(validOb
                .getHqUncertainty())) {
          InvalidObservation invalidOb = new InvalidObservation("JD "
              + validOb.getJD(),
              "HQ uncertainty value out of range "
                  + uncertaintyRangePredicate.toString());
          invalidObservations.add(invalidOb);
        } else {
          // Okay. Accept this as a valid observation, but
          // ignore non-standard magnitude type observations.
          if (validOb.getMType() == MTypeType.STD) {
            addValidObservation(validOb);
            categoriseValidObservation(validOb);
          }
        }
        // TODO: Why am I not updating progress bar here? Need count(*).

View Full Code Here

   * the ResultSet getter methods instead of strings. We use the string
   * versions for clarity. We can change this to use named constants if it
   * proves to be too inefficient.
   */
  private ValidObservation getNextObservation() throws SQLException {
    ValidObservation ob = new ValidObservation();


    int recordNum = source.getInt("unique_id");
    if (!source.wasNull())
      ob.setRecordNumber(recordNum);


    ob.setDateInfo(new DateInfo(source.getDouble("jd")));
    ob.setMagnitude(getNextMagnitude());
    ob.setHqUncertainty(getNextPossiblyNullDouble("hq_uncertainty"));
    SeriesType band = SeriesType.Unspecified;
    String bandNum = getNextPossiblyNullString("band");
    if (bandNum != null && !"".equals(bandNum)) {
      int num = Integer.parseInt(bandNum);
      band = SeriesType.getSeriesFromIndex(num);
    }
    ob.setBand(band);
    ob.setObsCode(getNextPossiblyNullString("observer_code"));
    ob.setCommentCode(getNextPossiblyNullString("comment_code"));
    ob.setCompStar1(getNextPossiblyNullString("comp_star_1"));
    ob.setCompStar2(getNextPossiblyNullString("comp_star_2"));
    ob.setCharts(getNextPossiblyNullString("charts"));
    ob.setComments(getNextPossiblyNullString("comments"));


    ob.setTransformed("yes"
        .equals(getNextPossiblyNullString("transformed")) ? true
        : false);


    ob.setAirmass(getNextPossiblyNullString("airmass"));
    ob.setValidationType(getNextValidationType());
    ob.setCMag(getNextPossiblyNullString("cmag"));
    ob.setKMag(getNextPossiblyNullString("kmag"));


    Double hjd = getNextPossiblyNullDouble("hjd");
    ob.setHJD(hjd != null ? new DateInfo(hjd) : null);


    ob.setName(getNextPossiblyNullString("name"));


    // If mtype is null or 0, we use the ValidObservation's
    // constructed default (standard magnitude type).
    Integer mtype = getNextPossiblyNullInteger("mtype");
    if (mtype != null && mtype != 0) {
      if (mtype == 1) {
        ob.setMType(MTypeType.DIFF);
      } else if (mtype == 2) {
        ob.setMType(MTypeType.STEP);
      }
    }


    ob.setObsType(ObsType
        .getObsTypeFromAIDIndex(getNextPossiblyNullInteger("obstype")));


    String pubref = getNextPossiblyNullString("pubref");
    if (pubref != null) {
      ob.setADSRef(pubref);
    }


    String digitizer = getNextPossiblyNullString("digitizer");
    if (digitizer != null) {
      ob.setDigitizer(digitizer);
    }


    return ob;
  }

View Full Code Here


          double jd = Double.parseDouble(fields[0]);
          double mag = Double.parseDouble(fields[1]);
          double error = Double.parseDouble(fields[2]);


          ValidObservation ob = new ValidObservation();
          ob.setDateInfo(new DateInfo(jd));
          ob.setMagnitude(new Magnitude(mag, error));
          ob.setBand(series);
          ob.setRecordNumber(reader.getLineNumber());
          collectObservation(ob);
        }


        line = reader.readLine();
      }

View Full Code Here

        // if (rfil=='y') then {
        // write(9,250) tt+dt0,resid,obs(n),xvec(n),xm


        // Create model and residual "observations".


        ValidObservation modelOb = new ValidObservation();
        modelOb.setDateInfo(new DateInfo(tt + dt0));
        modelOb.setMagnitude(new Magnitude(xm, 0));
        modelOb.setComments(model.getDescription());
        modelOb.setBand(SeriesType.Model);
        modelObs.add(modelOb);


        ValidObservation residualOb = new ValidObservation();
        residualOb.setDateInfo(new DateInfo(tt + dt0));
        residualOb.setMagnitude(new Magnitude(resid, 0));
        residualOb.setComments(model.getDescription());
        residualOb.setBand(SeriesType.Residuals);
        residualObs.add(residualOb);


        // }
        ttl = tt;
        xml = xm;

View Full Code Here

    // Note: this is only necessary of a recipient of filtered observations
    // needs to perform lookups.
    Set<ValidObservation> matchingObs = new LinkedHashSet<ValidObservation>();


    for (int i = 0; i < obs.size(); i++) {
      ValidObservation ob = obs.get(i);


      boolean does_match = matches(ob);


      if (does_match) {
        // Use logical implication (p => q which is the same as !p or q,
        // where p is the observation's property and q is the inclusion
        // property relating to p) to check that our inclusion criteria
        // still permit a match for this observation. For example, taking
        // fainter-thans we have this truth table:
        //
        // observation is-fainter-than | include is-fainter-thans | result
        // ----------------------------+--------------------------+--------
        //                       False |                    False | True
        //                       False |                    True  | True
        //                       True  |                    False | False
        //                       True  |                    True  | True
        does_match &= !ob.getMagnitude().isFainterThan()
            || includeFainterThan;
        does_match &= !ob.isDiscrepant() || includeDiscrepant;
        does_match &= !ob.isExcluded() || includeExcluded;


        if (does_match) {
          matchingObs.add(ob);
        }
      }

View Full Code Here

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