almost done with my fraction collector controller

@Arthur What kind of multi-dimensional analysis do you do?

Currently listening to a remote software meeting on BM@N experiment. They are talking about super-computers and grid computing system. The same was on IAXO meeting yesterday. People are more inclined to buy more powerfull computers than to work on better software that requires fewer resources. I hope that kotlin scientific community will be able to change that.

I've finished first iteration of Table API. Current version is here: https://github.com/mipt-npm/dataforge-core/tree/dev/dataforge-tables/src/commonMain/kotlin/hep/dataforge/tables. It features reasonable (not full) type safety for table building and reading. Also it is basically an interface, so it could be binded to different table implementations. For now there is no documentation and a single IO test here: https://github.com/mipt-npm/dataforge-core/blob/dev/dataforge-tables/src/jvmTest/kotlin/hep/dataforge/tables/io/TextRowsTest.kt.

a jfx lab gui. opengl "Fractal GUI"

There is a new article on GraalVM performance in kotlin: https://medium.com/@ramtop/graal-vs-c2-who-runs-kotlin-faster-82f03f1b11dd. Tests are rather synthetic, but it looks even more promising than before.

Do we have a fast (using SSE and all if possible) FFT available for kotlin (or java)?

Hello! The Kotlin stdlib has

Duration

, in experimental API. Did anyone think about continuing the six remaining measures from the SI (International System of units, aka. Système International)? I'd add

Distance

,

Mass

, etc, along with most common derived units, and functions to allow operations.

was this recorded?

Hi

📈 We've just published a new development version of plotly.kt (0.2.0-dev-13, it is available from the bintray). There is a plot drawing tutorial: https://github.com/mipt-npm/plotly.kt/blob/dev/docs/tutorials/HowToDrawASinus.md It even can do krangl: https://github.com/mipt-npm/plotly.kt/blob/dev/examples/src/main/kotlin/violin/GroupedViolinPlot.kt (cheers, @holgerbrandl) The most of layouting and tutorials are done by Ekaterina Smorodova, our intern from JetBrains Research. Jupyter support is functioning, but is yet bugged and requires more work.

We've released next stable version of `gdml.kt`: https://github.com/mipt-npm/gdml.kt/releases/tag/v0.1.8 Probably it is interesting only for particle physics (💥). Also we are planning a first release of dataforge-vis (probably with different name) and a big name change (scientifik -> kscience).

We are releasing new version of Plotly.kt. It comes with almos full API capabilities and Jupyter-kotlin support (experimental yet). Feel free to join our announce seminar: https://research.jetbrains.org/news/plotlykt-release-announce

Hey @altavir! We’ve been talking a little bit about on discourse about DataForge

i have heard that python is best for scientific work

@breandan looking at https://github.com/breandan/kaliningraph (again). Looks superb and documentation is the best as always.

We really need to start some kind of PR project for those scientific resources. I will think about that.

Hi all, I'm just throwing in here that I'm actually using Kotlin in my research (quantum physics, quantum computer). I basically rewrote the Qutip package (Python) in Kotlin to solve the von Neuman equation including noise. Initially I wrote it in Python but the performance was abysmal. Since I know Java and Kotlin well, I rewrote it there (using the Hipparchus math labrary; former Apache Math). Enormous performance gain, very easy multi-threading (using coroutines) - all I wanted. Unfortunately Hipparchus is missing a lot of complex functions, and some real-valued functions (Fresnel integrals e.g.) so I hit a roadblock just a few days ago and I had to resort to - guess what - Mathematica (offered by the university) 😞 Just sayin, Kotlin for science is awesome!

I really love kotlin. A hour of work, fifty lines of code and we have dynamic visualization of fully parallel and reactive stream-based simulation of terrestrial gamma-flashes (reactor model). The code is not yet publication-ready, but you can look at it here. Flows are really great for Monte-Carlo simulations (cc @elizarov).

I am going to make an open seminar this Friday evening about MC simulations with kotlin and coroutines. If anyone wants to attend, I can make it in English.

By the way, plotlykt 0.3.0-rc is out: https://github.com/mipt-npm/plotly.kt/releases/tag/v0.3.0-dev-rc. Sadly, no new features. Full migration of JS part to IR though.

Kotlin is doing openscience: I made our wikidata bot in Kotlin: https://twitter.com/cenaptech/status/1334558159827046404 (bot page on wikidata https://www.wikidata.org/wiki/User:NPImporterBot)

it is a pain to do bitwise operations currently

https://blog.jetbrains.com/kotlin/2020/12/lets-plot-in-kotlin/ @Maria Khalusova post on lets-plot. Eagerly waiting for more kotlinish API.

I am not sure I will be able to make a release this year as I expected, still. Have a nice kotlin with a demo. The full (JVM!) code to create the demo: https://github.com/mipt-npm/visionforge/blob/new-properties/playground/src/jvmMain/kotlin/hep/dataforge/vision/solid/stars.kt

JBR annual highlights are out: https://research.jetbrains.org/annual-report/2020/. Some of it is about Kotlin.

what do you know about tensorflow kotlin? tfk.dev

Next tuesday at 18:00 Moscow time, there will be an open laboratory seminar in English seminar about using kotlin, jupyter and our libraries for real-life neutrino mass experiment analysis. The calendar link Meet link: https://meet.google.com/fzy-buqp-srg

Due to comming demise of Jcenter we all have to think about moving to MavenCentral. I am still not sure about that decision, but I bought a kscience.space domain (kscience.science is also free, but the name looks ugly). We can use it as a community resource for kotlin scientific knowlege. I personally do not have time to work on the site, but if anyone else wants to work on it, I willing to help and provide the hosting.