Thanks for the feedback, the web UI does have a gallery link [0] with a few interactive examples [1]. I agree though, a screenshot like this would be a good addition to the homepage.

[0] https://pasteboard.co/IdIaJNo.png [1] https://pasteboard.co/IdIc7dc.png

I don't think that first image helps but that second image is great. That gets me excited and makes it look intuitive. Seriously, put that on the landing page.

Edit: Also that first example (from [1]) doesn't work for me

In[1]:= 1 + 2 - x * 3 x / y

Out[1]= 3 - 3 x ^ 2 / y

Is this a difference in the cli? I also notice I can't get any graphics there. No connection to matplotlib?

In[3]:= Plot[{Sin[x], Cos[x], Tan[x]}, {x, -3Pi, 3Pi}]

Out[3]= -Graphics-

Thanks a lot for your great work! I installed mathics locally and the translate/sierpinski examples from the gallery don't seem to work. Do you have an idea why?

I ran it on my own linux box. Thanks for this work! Suggestions:

1. host those images some where else than on pastebin, it's too slow to see them on your github page. Try anywhere else. 2. your instructions should tell the exact command to run it after installing it with pip on linux too, like you do on windows.

Just renewed it

Just renewed it

Thanks!

Just renewed it (not that it'll survive the HN hug of death). It's been a few years since I've touched that website.

Yes, that's roughly accurate. Jan Pöschko (the creator of Mathics) went to Wolfram in 2012 and I went to Google at the end of 2016. Since then it's been largely unmaintained as I don't have the time to work on it unfortunately

Thanks for the clarification Angus - appreciated.

Nit

> The distribution must be smooth (this method doesn’t work for discrete parameters), but it need not be analytically differentiable

'Smooth' and 'analytic' both have basic technical meanings in the context of differentiability [1], [2].

Glossing over the assumptions in this way is quite misleading

[1] https://en.m.wikipedia.org/wiki/Smoothness [2] https://en.m.wikipedia.org/wiki/Analytic_function

Analytically differentiable (being able to derive a formula for the derivative) is not the same thing at all as analytic functions of complex analysis (which are infinitely differentiable, etc). If anything, the term "analytic function" seems more of a misnomer to me, but "analytically differentiable" is used in its proper sense in the article.

I think you mean 13.468 TB/s per square mile.

Hidden in there (under 1.0) is "new recursive descent parser #416". We've only just finished 1.0 and haven't had a chance to announce it properly yet.

is this limitation in ply?

We previously used ply but ran into a few issues:

The main issue was that generating the tables was extremely slow (~15mins). We solved this by packaging the tables, but when the version of ply changed a table regeneration was forced on our users.

The recursive descent parser was also simpler and significantly more performant.

There's a short write-up on the PR: https://github.com/mathics/Mathics/pull/416

Mathics developer here. Yes, we rewrote it. I better update the docs.

Mathics, a free and open source Mathematica interpreter is looking for its first logo.

We're planning to release a 1.0 in the next few weeks and really need a logo to accompany the release.

http://mathics.github.io/