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dbenn merged 2 commits into from
May 6, 2026
Merged

579 coverage decimal precision #593

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af05f39
#579: test remaining GUI-bucket table models
dbenn May 4, 2026
23431c0
#579: use one-decimal precision for GUI/combined coverage figures
dbenn May 6, 2026
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14 changes: 8 additions & 6 deletions script/coverage_metrics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -225,15 +225,17 @@ def emit_github_output(
the original combined number for continuity if anyone wants it.
"""
pairs = [
# Non-GUI headline: integer precision keeps badge text stable.
("line_cov", non_gui.line.percent_int()),
("branch_cov", non_gui.branch.percent_int()),
("method_cov", non_gui.method.percent_int()),
("gui_line_cov", gui.line.percent_int()),
("gui_branch_cov", gui.branch.percent_int()),
("gui_method_cov", gui.method.percent_int()),
("all_line_cov", total.line.percent_int()),
("all_branch_cov", total.branch.percent_int()),
("all_method_cov", total.method.percent_int()),
# GUI and combined: one-decimal so small test additions are visible.
("gui_line_cov", gui.line.percent()),
("gui_branch_cov", gui.branch.percent()),
("gui_method_cov", gui.method.percent()),
("all_line_cov", total.line.percent()),
("all_branch_cov", total.branch.percent()),
("all_method_cov", total.method.percent()),
("non_gui_lines_total", str(non_gui.line.total)),
("gui_lines_total", str(gui.line.total)),
("all_lines_total", str(total.line.total)),
Expand Down
6 changes: 6 additions & 0 deletions test/AllTests.java
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Original file line number Diff line number Diff line change
Expand Up @@ -60,7 +60,10 @@
import org.aavso.tools.vstar.ui.dialog.DateToJdDialogTest;
import org.aavso.tools.vstar.ui.dialog.DoubleFieldTest;
import org.aavso.tools.vstar.ui.dialog.TextDialogTest;
import org.aavso.tools.vstar.ui.model.list.AbstractSyntheticObservationTableModelTest;
import org.aavso.tools.vstar.ui.model.list.PeriodAnalysisDataTableModelTest;
import org.aavso.tools.vstar.ui.model.list.ValidObservationTableModelTest;
import org.aavso.tools.vstar.ui.model.list.WWZDataTableModelTest;
import org.aavso.tools.vstar.ui.pane.list.VisibleSeriesRowFilterTest;
import org.aavso.tools.vstar.vela.VeLaTest;

Expand Down Expand Up @@ -125,6 +128,9 @@ public static Test suite() {

// GUI-coverage tests (issue #579, prong C).
suite.addTestSuite(ValidObservationTableModelTest.class);
suite.addTestSuite(PeriodAnalysisDataTableModelTest.class);
suite.addTestSuite(WWZDataTableModelTest.class);
suite.addTestSuite(AbstractSyntheticObservationTableModelTest.class);
suite.addTestSuite(VisibleSeriesRowFilterTest.class);
suite.addTestSuite(DateToJdDialogTest.class);
suite.addTestSuite(TextDialogTest.class);
Expand Down
322 changes: 322 additions & 0 deletions test/org/aavso/tools/vstar/ui/model/list/AbstractSyntheticObservationTableModelTest.java
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Original file line number Diff line number Diff line change
@@ -0,0 +1,322 @@
/**
* VStar: a statistical analysis tool for variable star data.
* Copyright (C) 2009 AAVSO (http://www.aavso.org/)
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero General Public License as
* published by the Free Software Foundation, either version 3 of the
* License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
package org.aavso.tools.vstar.ui.model.list;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.Locale;

import org.aavso.tools.vstar.data.DateInfo;
import org.aavso.tools.vstar.data.Magnitude;
import org.aavso.tools.vstar.data.SeriesType;
import org.aavso.tools.vstar.data.ValidObservation;
import org.aavso.tools.vstar.util.prefs.NumericPrecisionPrefs;
import org.aavso.tools.vstar.util.stats.BinningResult;

import junit.framework.TestCase;

// Uses SeriesType.Visual as an arbitrary series for BinningResult construction.

/**
* Tests for the four concrete subclasses of
* {@link AbstractSyntheticObservationTableModel}:
* <ul>
* <li>{@link RawDataMeanObservationTableModel}</li>
* <li>{@link PhasePlotMeanObservationTableModel}</li>
* <li>{@link RawDataModelObservationTableModel}</li>
* <li>{@link PhasePlotModelObservationTableModel}</li>
* </ul>
*
* These exercise the abstract base-class machinery (observation storage,
* row-index mapping, reverse lookup) through real production classes
* rather than an artificial stub.
*
* Part of issue #579 (GUI code coverage).
*/
public class AbstractSyntheticObservationTableModelTest extends TestCase {

private ValidObservation ob1;
private ValidObservation ob2;
private List<ValidObservation> observations;

@Override
protected void setUp() {
Locale.setDefault(Locale.ENGLISH);

ob1 = new ValidObservation();
ob1.setDateInfo(new DateInfo(2451545.0));
ob1.setMagnitude(new Magnitude(5.5, 0.01));
ob1.setStandardPhase(0.25);

ob2 = new ValidObservation();
ob2.setDateInfo(new DateInfo(2451546.0));
ob2.setMagnitude(new Magnitude(6.0, 0.02));
ob2.setStandardPhase(0.75);

observations = new ArrayList<>(Arrays.asList(ob1, ob2));
}

// -----------------------------------------------------------
// RawDataMeanObservationTableModel
// -----------------------------------------------------------

public void testRawMeanColumnCount() {
RawDataMeanObservationTableModel m =
new RawDataMeanObservationTableModel(observations);
assertEquals(4, m.getColumnCount());
}

public void testRawMeanRowCount() {
RawDataMeanObservationTableModel m =
new RawDataMeanObservationTableModel(observations);
assertEquals(2, m.getRowCount());
}

public void testRawMeanColumnNames() {
RawDataMeanObservationTableModel m =
new RawDataMeanObservationTableModel(observations);
assertEquals("Julian Day", m.getColumnName(0));
assertEquals("Calendar Date", m.getColumnName(1));
assertEquals("Mean Magnitude", m.getColumnName(2));
assertEquals("Standard Error of the Average", m.getColumnName(3));
}

public void testRawMeanColumnClasses() {
RawDataMeanObservationTableModel m =
new RawDataMeanObservationTableModel(observations);
for (int col = 0; col < 4; col++) {
assertEquals(String.class, m.getColumnClass(col));
}
}

public void testRawMeanGetValueAtJD() {
RawDataMeanObservationTableModel m =
new RawDataMeanObservationTableModel(observations);
String expected = NumericPrecisionPrefs.formatTime(2451545.0);
assertEquals(expected, m.getValueAt(0, 0));
}

public void testRawMeanGetValueAtMagnitude() {
RawDataMeanObservationTableModel m =
new RawDataMeanObservationTableModel(observations);
String expected = NumericPrecisionPrefs.formatMag(5.5);
assertEquals(expected, m.getValueAt(0, 2));
}

public void testRawMeanGetValueAtStdErr() {
RawDataMeanObservationTableModel m =
new RawDataMeanObservationTableModel(observations);
String expected = NumericPrecisionPrefs.formatMag(0.01);
assertEquals(expected, m.getValueAt(0, 3));
}

// -----------------------------------------------------------
// PhasePlotMeanObservationTableModel
// -----------------------------------------------------------

public void testPhaseMeanColumnCount() {
PhasePlotMeanObservationTableModel m =
new PhasePlotMeanObservationTableModel(observations);
assertEquals(3, m.getColumnCount());
}

public void testPhaseMeanRowCount() {
PhasePlotMeanObservationTableModel m =
new PhasePlotMeanObservationTableModel(observations);
assertEquals(2, m.getRowCount());
}

public void testPhaseMeanColumnNames() {
PhasePlotMeanObservationTableModel m =
new PhasePlotMeanObservationTableModel(observations);
assertEquals("Phase", m.getColumnName(0));
assertEquals("Mean Magnitude", m.getColumnName(1));
assertEquals("Standard Error of the Average", m.getColumnName(2));
}

public void testPhaseMeanGetValueAtPhase() {
PhasePlotMeanObservationTableModel m =
new PhasePlotMeanObservationTableModel(observations);
String expected = NumericPrecisionPrefs.formatTime(0.25);
assertEquals(expected, m.getValueAt(0, 0));
}

public void testPhaseMeanGetValueAtMag() {
PhasePlotMeanObservationTableModel m =
new PhasePlotMeanObservationTableModel(observations);
String expected = NumericPrecisionPrefs.formatMag(5.5);
assertEquals(expected, m.getValueAt(0, 1));
}

// -----------------------------------------------------------
// RawDataModelObservationTableModel
// -----------------------------------------------------------

public void testRawModelColumnCount() {
RawDataModelObservationTableModel m =
new RawDataModelObservationTableModel(observations,
SeriesType.Model);
assertEquals(3, m.getColumnCount());
}

public void testRawModelRowCount() {
RawDataModelObservationTableModel m =
new RawDataModelObservationTableModel(observations,
SeriesType.Model);
assertEquals(2, m.getRowCount());
}

public void testRawModelColumnNames() {
RawDataModelObservationTableModel m =
new RawDataModelObservationTableModel(observations,
SeriesType.Model);
assertEquals("Julian Day", m.getColumnName(0));
assertEquals("Calendar Date", m.getColumnName(1));
assertEquals("Magnitude", m.getColumnName(2));
}

public void testRawModelGetValueAtJD() {
RawDataModelObservationTableModel m =
new RawDataModelObservationTableModel(observations,
SeriesType.Model);
String expected = NumericPrecisionPrefs.formatTime(2451545.0);
assertEquals(expected, m.getValueAt(0, 0));
}

public void testRawModelGetValueAtMag() {
RawDataModelObservationTableModel m =
new RawDataModelObservationTableModel(observations,
SeriesType.Model);
String expected = NumericPrecisionPrefs.formatMag(5.5);
assertEquals(expected, m.getValueAt(0, 2));
}

public void testRawModelWithResidualsSeries() {
RawDataModelObservationTableModel m =
new RawDataModelObservationTableModel(observations,
SeriesType.Residuals);
assertEquals(2, m.getRowCount());
}

// -----------------------------------------------------------
// PhasePlotModelObservationTableModel
// -----------------------------------------------------------

public void testPhaseModelColumnCount() {
PhasePlotModelObservationTableModel m =
new PhasePlotModelObservationTableModel(observations,
SeriesType.Model);
assertEquals(2, m.getColumnCount());
}

public void testPhaseModelRowCountIsDoubled() {
PhasePlotModelObservationTableModel m =
new PhasePlotModelObservationTableModel(observations,
SeriesType.Model);
assertEquals(4, m.getRowCount());
}

public void testPhaseModelColumnNames() {
PhasePlotModelObservationTableModel m =
new PhasePlotModelObservationTableModel(observations,
SeriesType.Model);
assertEquals("Phase", m.getColumnName(0));
assertEquals("Magnitude", m.getColumnName(1));
}

public void testPhaseModelGetValueAtPhase() {
PhasePlotModelObservationTableModel m =
new PhasePlotModelObservationTableModel(observations,
SeriesType.Model);
String expected = NumericPrecisionPrefs.formatTime(0.25);
assertEquals(expected, m.getValueAt(0, 0));
}

public void testPhaseModelWrapsAroundForDoubledRows() {
PhasePlotModelObservationTableModel m =
new PhasePlotModelObservationTableModel(observations,
SeriesType.Model);
assertEquals(m.getValueAt(0, 0), m.getValueAt(2, 0));
assertEquals(m.getValueAt(1, 0), m.getValueAt(3, 0));
}

// -----------------------------------------------------------
// Base-class features via RawDataMeanObservationTableModel
// -----------------------------------------------------------

public void testGetObs() {
RawDataMeanObservationTableModel m =
new RawDataMeanObservationTableModel(observations);
assertSame(ob1, m.getObs().get(0));
assertSame(ob2, m.getObs().get(1));
}

public void testGetRowIndexFromObservation() {
RawDataMeanObservationTableModel m =
new RawDataMeanObservationTableModel(observations);
assertEquals(Integer.valueOf(0), m.getRowIndexFromObservation(ob1));
assertEquals(Integer.valueOf(1), m.getRowIndexFromObservation(ob2));
}

public void testGetRowIndexFromUnknownObservationReturnsNull() {
RawDataMeanObservationTableModel m =
new RawDataMeanObservationTableModel(observations);
ValidObservation unknown = new ValidObservation();
assertNull(m.getRowIndexFromObservation(unknown));
}

public void testEmptyModel() {
RawDataMeanObservationTableModel m =
new RawDataMeanObservationTableModel(new ArrayList<>());
assertEquals(0, m.getRowCount());
assertTrue(m.getObs().isEmpty());
}

public void testMeanModelUpdateViaListener() {
RawDataMeanObservationTableModel m =
new RawDataMeanObservationTableModel(observations);
assertEquals(2, m.getRowCount());

ValidObservation ob3 = new ValidObservation();
ob3.setDateInfo(new DateInfo(2451547.0));
ob3.setMagnitude(new Magnitude(7.0, 0.03));
List<ValidObservation> newObs = Arrays.asList(ob3);

BinningResult result = new BinningResult(
SeriesType.Visual, 1, newObs, null);
m.update(result);

assertEquals(1, m.getRowCount());
assertSame(ob3, m.getObs().get(0));
assertEquals(Integer.valueOf(0), m.getRowIndexFromObservation(ob3));
}

public void testCanBeRemovedMean() {
RawDataMeanObservationTableModel m =
new RawDataMeanObservationTableModel(observations);
assertTrue(m.canBeRemoved());
}

public void testCanBeRemovedModel() {
RawDataModelObservationTableModel m =
new RawDataModelObservationTableModel(observations,
SeriesType.Model);
assertTrue(m.canBeRemoved());
}
}
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