Package org.aavso.tools.vstar.ui.model.list

Examples of org.aavso.tools.vstar.ui.model.list.InvalidObservationTableModel


    Map<SeriesType, List<ValidObservation>> validObservationCategoryMap = starInfo
        .getRetriever().getValidObservationCategoryMap();

    // Table models.
    ValidObservationTableModel validObsTableModel = null;
    InvalidObservationTableModel invalidObsTableModel = null;
    RawDataMeanObservationTableModel meanObsTableModel = null;

    // Plot models.
    obsAndMeanPlotModel = null;

    // GUI table and chart components.
    ObservationListPane obsListPane = null;
    SyntheticObservationListPane<AbstractMeanObservationTableModel> meansListPane = null;
    ObservationAndMeanPlotPane obsAndMeanChartPane = null;

    if (!validObsList.isEmpty()) {

      freeListeners();

      // Create a message to notify whoever is listening that a new star
      // has been loaded.
      NewStarMessage newStarMsg = new NewStarMessage(newStarType,
          starInfo, validObsList, validObservationCategoryMap,
          starInfo.getRetriever().getMinMag(), starInfo
              .getRetriever().getMaxMag(), starInfo
              .getRetriever().getSourceName());

      if (!addObs) {
        newStarMessageList.clear();
      }

      newStarMessageList.add(newStarMsg);

      // This is a specific fix for tracker 3007948.
      this.discrepantObservationNotifier = new Notifier<DiscrepantObservationMessage>();

      // Observation table and plot.
      validObsTableModel = new ValidObservationTableModel(validObsList,
          newStarType.getRawDataTableColumnInfoSource());

      // Observation-and-mean table and plot.
      obsAndMeanPlotModel = new ObservationAndMeanPlotModel(
          validObservationCategoryMap, JDCoordSource.instance,
          JDComparator.instance, JDTimeElementEntity.instance, null);

      // Record initial ANOVA information and make the document manager
      // listen to changes to ANOVA via new binning results.
      documentManager.updateAnovaInfo(obsAndMeanPlotModel
          .getBinningResult());

      obsAndMeanPlotModel.getMeansChangeNotifier().addListener(
          documentManager.createBinChangeListener());

      documentManager
          .addStatsInfo("Confidence Interval",
              "Mean error bars denote 95% Confidence Interval (twice Standard Error)");

      obsAndMeanChartPane = createObservationAndMeanPlotPane(LocaleProps
          .get("LIGHT_CURVE")
          + " "
          + LocaleProps.get("FOR")
          + " "
          + starInfo.getDesignation(), null, obsAndMeanPlotModel,
          starInfo.getRetriever());

      obsAndMeanPlotModel.getMeansChangeNotifier().addListener(
          createMeanObsChangeListener(obsAndMeanPlotModel
              .getMeanSourceSeriesNum()));

      // The mean observation table model must listen to the plot
      // model to know when the means data has changed. We also pass
      // the initial means data obtained from the plot model to
      // the mean observation table model.
      meanObsTableModel = new RawDataMeanObservationTableModel(
          obsAndMeanPlotModel.getMeanObsList());

      obsAndMeanPlotModel.getMeansChangeNotifier().addListener(
          meanObsTableModel);

      if (obsArtefactProgressAmount > 0) {
        // Update progress.
        getProgressNotifier().notifyListeners(
            new ProgressInfo(ProgressType.INCREMENT_PROGRESS,
                obsArtefactProgressAmount));
      }
    }

    if (!invalidObsList.isEmpty()) {
      invalidObsTableModel = new InvalidObservationTableModel(
          invalidObsList);
    }

    // The observation table pane contains valid and potentially
    // invalid data components. Tell the valid data table to have
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