Hi Frédéric,
we should separate the bundles and keep the footprint small.
Especially if you'd like to use e.g. PCA on an IoT device to cluster
data / pre-aggregate data, you don't want to install tons of
dependencies. Hence, I would recommend to restrict the dependencies
to a minimum. Each algorithm could be placed in an own bundle, e.g.:
org.eclipse.algorithms.core
org.eclipse.algorithms.svd
org.eclipse.algorithms.nipals
org.eclipse.algorithms.mcr
...
Best,
Philip
Am 20.06.19 um 21:44 schrieb Frédéric
Desbiens:
Hi Philip.
Factoring out algorithms to favor reusability sounds like
a good idea to me. Do you foresee any downsides for the
members of our community that currently leverage them?
Best,
Frédéric Desbiens
Program Manager, IoT and Edge Computing | Eclipse Foundation, Inc.
Eclipse Foundation: The Platform for Open Innovation and Collaboration
![]()
No, on purpose :-). I posted it to
Science and IoT.
Reason: Matrix data processing algorithms might be also
interesting for IoT devices to aggregate/rate data before
sending it to other devices. For that purpose, PCA and other
algorithms could be used. Hence, potentially interesting.
Best,
Philip
Am
20.06.19 um 13:21 schrieb Benjamin Cabé:
Hi Philip,
Wrong mailing list? :)
Benjamin.
Hi folks,
does it make sense to file a new Eclipse Proposals
"Matrix Algorithms"
under the umbrella of the Science working group?
We have dozens of algorithms in ChemClipse/OpenChrom
which we would like
to migrate to a separate project. The goal is, that
they can be reused
more easily in other projects. I assume
Diamond Light Source
Oak Ridge
deeplearning4j
...
are facing the same problem. At the moment, these
algorithms are part of
ChemClipse, DAWNSci, deeplearning4j ... and to use
them, you have to
clone the complete project even if you only need a
certain algorithm. We
could provide the following algorithms
(implementations) in Java:
SVD (Singular Value Decomposition)
NIPALS (Non-linear Iterative Partial Least Squares)
OPLS (Orthogonal Projections to Latent Structures)
Currently, we are working on:
MCR-AR (Multivariate Curve Resolution - Alternating
Regression)
In the future, we are interested to implement:
PARAFAC2 (Parallel Factor Analysis 2)
TCC (Tucker's Congruence Coefficient)
Java isn't that strong in matrix operations, though we
could use matrix
libraries and/or create the algorithms in a way that
different matrix
libraries (Java, C, ...) can be used, e.g.:
ND4J (http://nd4j.org)
Eclipse January (https://www.eclipse.org/january)
EJML (http://ejml.org)
OpenBLAS (https://www.openblas.net)
In my opinion, we should have a dependency to Apache
Commons Math and
setup the project in an encapsulated way, similar as
SWTChart for
plotting charts (it requires only double[] arrays to
plot the data).
https://commons.apache.org/proper/commons-math
https://github.com/eclipse/swtchart
What's your opinion?
Feedback is highly appreciated.
Best,
Philip
--
~~~~~~~~~~~~~~~~~~~~~~~~
OpenChrom - the open source alternative for
chromatography / mass spectrometry
Dr. Philip Wenig » Founder » philip.wenig@xxxxxxxxxxxxx
» http://www.openchrom.net
~~~~~~~~~~~~~~~~~~~~~~~~
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