Scala compiles either to native, js or jvm - obviously the IO / interface options vary between these envs, but the lang is the same. Recently Scala 3.5 incorporates a simple-to-use CLI which makes it easier to compile to native (or just run a small file as a script, or experiment with a repl), native binaries are small and fast, and there are some simple io libraries. Since you can also compile to jvm to interop with java, that might help with transition.
I now use Scala 3, and very happy with syntactic whitespace (combined with an intelligent compiler)
Well written!
Indeed that’s strange, and the flat slope in 2060 seems inconsistent with declared net-zero policies of China and even India. Russia has no such policy, but still strange to assume continuation of current government concepts there until 2060. (you can see the regional breakdown in supplem Fig 1. )
Regarding the map - an annual average cost is not so meaningful - in higher latitudes solar is not enough in winter - especially where it’s mostly cloudy during the first half of winter. Wind helps the balance but not everywhere, always. Of course, the sophisticated models behind the article know all that, the issue is simplistic presentation. I note “we assume hydrogen is used for seasonal storage” - this may be rather optimistic - how many dark months can that cover?
Scala-js is working on it - as its compiler design may facilitate this.
I haven’t yet tried (on todo list) and am not an expert, but bookmarked in passing:
recent github implementation, some history, following older discussion
I agree. The key symbiosis between coral and microalgae depends on fundamental thermodynamic equilibria of the carbonate chemistry of seawater - which are highly sensitive to temperature and atmospheric CO2, in very predictable ways. When living in coral becomes unprofitable for the algae, they leave. My instinct, from some experience with this system, is that introducing new species won’t do better than nature, nobody can beat thermodynamics. We have to reduce the CO2.
Wonder whether the popularity of the president will follow a similar pattern as in France, trying similar idea … ?
I use vscode as I develop this model in Scala3, whose language-server ‘metals’ integrates well with vscode, and when scala3 was new in mid-21 this was the platform they first targeted. But the scala command-line tools do the clever analysis, vscode provides the layout, colours, git integration, search/regex, web-preview etc… Now considering other options (eg zed) as vscode too dependent on potentially unsafe extensions (of which too much choice), also don’t want M$ scraping my code. Long ago when same model was in java I used netbeans, then eclipse. Would prefer a pure-scala toolset.
Note that Knesset has 120 seats (not obvious from the article). (also, of course, a large fraction of people between the river and the sea don’t get to vote for any of its seats)
“…at a rate of roughly 0.05 percent per day … would take a very long time” … but by my quick calculation 0.9995^3650 is 84% per decade, which is not long. Almost instantaneous on a geological timescale - and think how much the world changed when fungi learned how to digest lignin in wood - ending the era of coal-forming swamps.
Hi, excuse me for replying so late, but i’ve been away from lemmy for.a while.
Well, to summarise, the model calculates the future trajectories, of population, economy, emissions, atmospheric gases, and climate response etc., according to a set of (hundreds of) diverse options and uncertainties which you can adjust - the key feature is that the change shows rapidly enough to let you follow cause -> effect, to understand how the system responds in a quasi-mechanical way.
Indeed you are right, complexity is beautiful, but hard. A challenge with such tools is to adjust gradually from simple to complex. Although SWIM has four complexity levels, they are no longer systematically implemented - also what seems simple or complex varies depending where each person is coming from, so i think to adapt the complexity filter into a topic-focus filter. Much todo …
Hmm, publishing that will really help those Crimean beach hotels get customers for this summer…
I can relate to this, having developed a coupled socio-emissions-carbon-climate model, which evolved for 20 years in java, until recently converted to scala3. You can have a look here. The problem is that “coupling” in such models of complex systems is a ‘good’ thing, as there are feedbacks - for example atmospheric co2 drives climate warming but the latter also changes the carbon cycle, demography drives economic growth but the latter influences fertility and migration, etc… (some feedbacks are solved by extrapolating from the previous timestep - the delay is anyway realistic). There are also policy feedbacks - between top-down climate-stabilisation goals, and bottom up trends and national policies, the choice affects the logical calculation order. All this has to work fast within the browser (now scala.js - originally java applet), responding interactively to parameter adjustments, only recalculating curves which changed - getting all these interactions right is hard.
If restarting in scala3 I’d structure it differently, but having a lot of legacy science code known to work, it’s hard to pull it apart. Wish I’d known such principles at the beginning, but as it grew gradually, one doesn’t anticipate such complexity.
Thankyou for the tool, very useful, but hope they simplify this, so we can make trips across the country.
Being good at passing exams (“majoring”) is just the first stage, continuing in the topic as a career depends more on networking skills.
I began programming java climate model with UK keyboard. When I moved to the continent, switched to swiss then belgian keyboard to better type emails/docs in french, but it was so tedious for code brackets {[()]} and some other punctuation, eventually switched back. Recently converted whole codebase to Scala 3 (here’s the model), now can drop most of those brackets. I speculate whether one motivation for creating scala3 (made in in Lausanne) was swiss/french keyboards.
I like Scala:
Fwiw, here’s my interactive climate system model running in pure scala.
Too true.
I still remember when java5 came out, many new features, great potential for a massive refactoring of my interactive climate model. Within that, I had an idea called “parallel worlds” for comparing scenarios, whereby for efficiency data was shared for parts of the system, and split across parts that varied as user adjusted parameters. So I pulled apart the whole codebase, and joined it back together again… - about two years later, by which time colleagues had given up interest.
[ story simplified to relate to point of OP - not only task in two years! ].
Now I develop a derivative climate system model in scala,
but evidently it’s more interesting to develop some new complex part of the science code, than fix a graphical interface for beginners. But moods vary - some days lacking energy for refactoring, could be satisfied ticking off a few small tasks in a todo list. Yet after some time, brain craving for another big new complex idea…
Indeed to use scala-native you’d need pure-scala libraries, but the core lib re-implements most java lib, and there are now small simple external libs available for common tasks like file management, database, etc. - for example check out the lihaoyi suite.
I mainly use scala-js (to make this) which was formerly a java app - as it compiles to both js and jvm (cross-project) can gradually convert stuff you already wrote. I’ve tried native for stuff like pre-processing data files.