antonlopezr
Joined 5 years ago
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87
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18
Member since
Jan 7
Recent submissions
Comment · 4 years ago
Comment · 5 years ago
I've been working on MPL Plotter for some time now. I shared it back in the day, but it's gone through significant improvements to the point I'm using it as my main plotting software, so I figured I might as well share it in its adult form :)
I'm eyeing network graphs in the not so distant future, perhaps moving away from Matplotlib. Any feedback is appreciated!
Comment · 5 years ago
Hey everyone.
Huracan is an open source, 0-dimensional, object-oriented airbreathing engine modelling package for preliminary analysis and design of airbreathing engines, divulgation and educational purposes.
The aerospace industry is notoriously closed source. Huracan being open source means that anyone is free to not only use it to experiment with engine designs, but also investigate the physical principles behind how each component affects a flow of gas. I think that makes it a precious learning opportunity for the interested layman, as well as giving more knowledgeable people the opportunity to contribute to the improvement of the tool if they can and so desire.
0-dimensional engine simulation consists in taking an engine architecture and simulating the state of the gas flowing through it after each component. This is, simulating the state of the flow in a discrete way. 0-dimensional engine modelling programs such as GasTurb and NLR's GSP are used in academia and the industry for preliminary design and analysis of engines.
At the moment Huracan is capable of modelling engines with an arbitrary number of components connected by an arbitrary number of shafts. It allows for a single combustion chamber per stream and reheating. Multiple-stream systems can be modelled, as well as splitting (such as the bypass flow of a turbofan) and mixing streams (such as in the nozzle of a mixed exhaust turbofan). The thrust, specific fuel consumption and propulsive efficiency of an engine can be obtained. Further verification and validation of the model are currently the main objectives of the project, as well as further performance analysis features.
For the curious, there's turbofan, turboprop and turbojet simulation examples in the repository.
The API reference is available here[1].
Comment · 5 years ago
Hey everyone,
Anchorage is a Python library & CLI with to retrieve and bulk archive your bookmark collection online in the Internet Archive or locally using ArchiveBox, all directly from your shell.
As all of you probably know link rot is a significant problem for most content in the internet. I quite appreciate my bookmark collection, so loosing part or most of it to link rot would be a pity. After doing some search I wasn't able to find a tool to suit my needs, and so I got to programming Anchorage.
Through its CLI, Anchorage can: - Retrieve your bookmarks from the JSON (Chromium) or JSONLZ4 (Firefox) bookmarks file of your browser. - Apply filters to your collection, namely: dropping local files, and dropping bookmark directories, URLs or bookmark names if they match a given string (or any in a list), contain a given substring (idem) or match a regex formula. - Archive the resulting collection online (IA) or locally (ArchiveBox)
Further details are in the README of the repo, and all implementations are documented in detail at http://anchorage-docs.github.io/
All feedback is appreciated! Still got much to learn :)
Thanks for hopping by and have a nice day!
Comment · 5 years ago
Oh and also check the MPL Plotter custom preset functions! Editing your plots from a dictionary with all modifiable parameters visible for you to uncomment and tune is one of the nicer things the library has to offer.
Comment · 5 years ago
Hey! Thanks a lot for checking it out! TL;DR:
1. Between Seaborn and MPL Plotter, I believe it comes to taste more than anything, and (somewhat arguably), I think MPL Plotter is a bit more concise. I really like how you can expand its functionality with Matplotlib, but that applies to both!
2. I recommend Datashader (https://datashader.org/) (HoloViz is super cool) and Vispy (https://vispy.org/). I found Vispy's documentation a bit lacking some time ago, but they probably have improved it since then, and it's very capable. Lastly, check Taichi (https://taichi.graphics/), might not be a conventional data representation library (or rather, not only), but it's amazing and worth a look.
To add some more depth to the Seaborn comparison, and not being an expert Seaborn user, I'd say:
1. MPL Plotter is lighter (but also with less wide-ranging plot options) 2. In my experience, MPL Plotter's presets (most importantly, the defaults from which you build your plots up) are more suitable for technical papers than Seaborn's.
And perhaps a bit more arguably (again, I'm not a Seaborn expert, please do correct me if you think otherwise):
3. I believe MPL Plotter gives you more fine-grained control over your plot. That's is for you to plot and customize as far as Matplotlib will take you in one line, while most Seaborn examples I've seen use pyplot snippets. 4. And following with the above, I believe the syntax is a little more concise.
Personally I like that MPL Plotter is fundamentally Matplotlib, so I can use any Matplotlib customization I might need seamlessly, and, if useful enough, add it later on as a method in MPL Plotter itself, which would be a bit harder on such an established project as Seaborn. It's just tastes at that point, and the flexibility of being a small project.
Cheers!
Comment · 5 years ago
Thanks for checking the library and for the heads up! I'll be correcting that asap :)
Comment · 5 years ago
Hey! Thanks a lot for checking it out! I meant it as in learning Python myself while I was making it :)
As to the API, I've added "stability" indicators for every plotting method in the README, and the most unstable features (panes) have warnings.
I'm not sure how to deal with breaking changes if I make any (again, probably only to the 'panes' functions). I think I'll create a new release (so 3.n.n to 4.0.0 for example) and state it as clearly as possible in the commits. Of course my priority during development is avoiding such changes. Please let me know any thoughts on how to do better!
1. Giving you complete control over the Pandoc call 2. Allowing you to post-process the Pandoc output with tailored Markup Packs.
You can see a test OneNote note and its Emacs Org Mode and Pandoc Markdown exports here https://github.com/alopezrivera/owo#results
Markup Packs are markup-format-specific functions containing search and replace queries executed at runtime against the text output by Pandoc. If search and replace doesn't cut it, you can add a postprocessing scriptblock to increase your freedom. They effectively give you control over how all is rendered, including
- Headers - Metadata (eg: note creation date) - Other markup elements such as horizontal lines, custom indentations and formatting, and whatever else you might be able to conjure up with the text in your notes
OneWayOut is built on the foundation of ConvertOneNote2Markdown (https://github.com/theohbrothers/ConvertOneNote2Markdown), by SjoerdV (https://github.com/SjoerdV), and improved by nixsee (https://github.com/nixsee/) and theohbrothers (https://github.com/theohbrothers).
Got a lot to learn so all feedback or suggestions are welcome! Thanks for checking it out :)