[VOTE] Releasing Orekit 11.3 from release candidate 1

MaximeJ · October 19, 2022, 8:39am

This is a VOTE in order to release version 11.3 of the Orekit library.
Version 11.3 is a minor release.

Highlights in the 11.3 release are:

The unscented Kalman filter (numerical version),
The semi-analytical unscented Kalman filter (DSST version),
A new PVCoordinatesProvider modelling waypoints on an ellipsoid following a loxodrome (commonly, a rhum bline),
A new method to compute hyperbolic anomaly based on Gooding and Odell algorithm,
A new built-in additional state for covariance propagation (linear method based on the state transition matrix computation),
With a new state covariance object allowing covariance transformation between frames and orbit types,
And the ability to extrapolate a state covariance matrix using a Keplerian model,
A new ExtremumApproachDetector for close encounter computation,
The migration of all JUnit tests from JUnit 4 to JUnit 5,
The ability to estimate measurement parameters (station position or clock biases) from an ephemeris,
New methods to convert from/to Orekit frames and CCSDS frames,
Improvements of CCSDS CDM (Collision Data Message) parsers,
Improvements in date handling and aggregate bounded propagators,
Several bug fixes and documentation improvements.

The release candidate 1 can be found on the GitLab repository as
tag 11.3-RC1 in the release-11.3 branch:

The release notes can be read here:
https://test.orekit.org/site-orekit-development/changes-report.html
(Please note that due to an issue with the website generation, the description and date are not generated. They will for the official release. For more details, see the changes.xml file.)

Maven artifacts are available on Sonatype at: Index of /repositories/orgorekit-1060.

The votes will be tallied in 120 hours for now, on 2022-10-25T09:00:00Z
(this is UTC time).

Serrof · October 19, 2022, 10:41am

Hi Maxime,

A great release ahead!
About the covariance transformation, by orbit type it is meant that one can go from/to Cartesian to/from Keplerian for instance? In that case I am assuming this is done using the Jacobian matrix? If yes then again, like for the propagated case, there needs to be a clear statement in the documentation that this is a linearization-based approximation.
In general, only Cartesian transformations between frames are actually linear, so that the linearization is then exact.

Cheers,
Romain.

bcazabonne · October 19, 2022, 11:27am

+1 for the release

bcazabonne · October 19, 2022, 11:31am

Yes

Yes again

I don’t think we mentioned this in the documentation…
I don’t think we need to amend the RC1 vote for a documentation improvement since it can be done during a patch release. Therefore, could you open an issue with a ‘Documentation’ label in order to add these information during the next patch release?

Best regards,
Bryan

luc · October 19, 2022, 7:09pm

+1 from me, a good release!

petrus.hyvonen · October 19, 2022, 9:28pm

Hi, great work!

I have tried to do a first wrapping for python and it works fine with the exception of the hipparchus class RosenNumberPartitionIterator. I haven’t digged deep into why it fails on this seemingly trivial class, but when excluding it the wrapper seems to build fine. I don’t think this is critical for having in Python, nor part of orekit 11.3 so +1 for me!

If anyone has any insight of the magic in the roses, please share…

github.com

Hipparchus-Math/hipparchus/blob/master/hipparchus-core/src/main/java/org/hipparchus/util/RosenNumberPartitionIterator.java

/* Copyright 2011 Axel Kramer
 * Licensed to the Hipparchus project under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The Hipparchus project licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.hipparchus.util;

import java.util.Iterator;
import java.util.NoSuchElementException;

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paulcefo · October 19, 2022, 10:32pm

+1 for release.

Paul Cefola

frank.dreger · October 20, 2022, 6:07am

+1 from me.

Vincent · October 20, 2022, 6:48am

+1 for the release !

dgondelach · October 20, 2022, 8:24am

Great new features!

+1 from me.

David

Serrof · October 21, 2022, 8:05am

+1 from me as well (assuming there will be a Zenodo release )

Issue about documentation opened. Sorry for my insistence on that, I just do no want people to think that linearization-based covariance transformation/propagation is the only option, or even worse the exact solution.

MaximeJ · October 21, 2022, 9:46am

@petrus.hyvonen I don’t know what happens with this Hipparchus class. At first I thought it was due to the implements Iterator... but there are many other classes in Hipparchus that are built the same.
You should probably open a separate discussion thread on the forum or an issue on Hipparchus about this .

I understand but unfortunately we cannot know before the official release is out on the Github mirror repository.
It worked for Hipparchus so I’m confident!

No problem @Serrof, you are right in wanting a better documentation.

MaximeJ · October 25, 2022, 9:04am

This vote passes with +1 from Bryan, Luc, Petrus, Paul, Frank, Vincent, David, Romain, Pascal, Nicolas, Sébastien and myself (some directly on the thread, some on the voting widget and some on a private PMC thread).

I will proceed with the release right away.