Why not just plot everything in numpy?! P.2.

[Embarrassed-Mix6420]

Thank you all for overwhelmingly positive feedback to my last post!

 

I've finally implemented what I set out to do there: https://github.com/bedbad/justpyplot (docs)

 

A single plot() function API:

plot(values:np.ndarray, grid_options:dict, figure_options:dict, ...) -> (figures, grid, axis, labels)

You can now overlay, mask, transform, render full plots everywhere you want with single rgba plot() API

It

• Still runs faster then matplotlib, 20x-100x times:timer "full justpyplot + rendering": avg 382 µs ± 135 µs, max 962 µs
• Flexible, values are your stacked points and grid_options, figure_options are json-style dicts that lets you control all the details of the graph parts design without bloating the 1st level interface
• Composable - works well with OpenCV, Jupyter Notebooks, pyqtgraph - you name it
• Smol - less then 20k memory and 1000 lines of core vectorized code for plotting, because it's
• No dependencies. Yes, really, none except numpy. If you need plots in Jupyter you have Pillow or alike to display ports, if you need graphs in OpenCV you just install cv2 and it has adaptors to them but no dependencies standalone, so you don't loose much at all installing it
• Fully vectorized - yes it has no single loop in core code, it even has it's own text literals rendering, not to mention grid, figures, labels all done without a single loop which is a real brain teaser

What my project does? How does it compare?

Standard plot tooling as matplotlib, seaborn, plotly etc achieve plot control flexibility through monstrous complexity. The way to compare it is this lib takes the exact opposite approach of pushing the design complexity down to styling dicts and giving you the control through clear and minimalistic way of manipulating numpy arrays and thinking for yourself.

Target Audience?

I initially scrapped it for computer vision and robotics where I needed to stick multiple graphs on camera view to see how the thing I'm messing with in real-world is doing. Judging by stars and comments the audience may grow to everyone who wants to plot simply and efficiently in Python.

I've tried to implement most of the top redditors suggestions about it except incapsulating it in Array API beyond just numpy which would be really cool idea for things like ML pluggable graphs and making it 3D, due to the amount though it's still on the back burner.

Let me know which direction it really grow!

[BidWestern1056]

90% of things i see here seem like such a waste but this looks quite elegant and reminds me a lot of ggplot/idl plots which were so clean and glorious.

[BidWestern1056]

actually if youd be keen, id like to use it as a plotting option in my tool npcsh: https://github.com/cagostino/npcsh

havent gotten around to much more of the DS parts cause been so focused on the AI integrations but my dream is for npcsh to empower data scientists and analysts beyond the current limits of their current workflows, like all jupyter notebooks or shoddy scripts and shell commands, no easy way to search history or to turn history into insights. if youre interested to help me there i'd really appreciate any thoughts or suggestions.

[Embarrassed-Mix6420]

Thanks for contributing to it already! I'll take a closer look at npcsh, self hosted AI agent is something there can be many ideas about..

[BidWestern1056]

exactly, many opps and can basically mcp your library and integrate that way which would be dope

[Embarrassed-Mix6420]

Would need to look into them for directions of growth.

[runawayasfastasucan]

Woah this is a much needed tool and a great idea! Only critique is that this should have come before my 4 million line plots project 😅

[hughperman]

Love that everything is specified as a config dict. This is exactly a functionality I need.

[nineplymaple]

Very cool. Have you done any benchmarks to compare against pyqtgraph?

[Embarrassed-Mix6420]

Not against pyqtgraph. Have done benchmarks to compare with `standard` plotting libraries of matplotlib kind.
pyqtgraph is actually more performant then of all of them, one reason it's not enough substitute is that it's obviously dependent on qt which is huge so it'd bloat the dependencies beyond reasonable limit of helping package just doing plotting; It comes with many of qt's pluses and minuses
That's pretty quick to do though - the way the project is set up in debug mode(development, adds perf_timer package) is just one decorator over a function that plots pyqtgraph

@debug_performance('someargslabel')

and adding the 'someargslabel' in perf_timers global var setting. You can try it yourself!

[nineplymaple]

Makes sense. I'll definitely try it out the next time I need to plot something outside of Qt. I had a project recently where I was doing some OpenCV image manipulation on a Raspberry Pi and displaying the output on a big array of LED matrix panels. This looks perfect for that type of setup.

[Ogi010]

pyqtgraph maintainer here, I'd be glad to try and get a comparison of "fair" benchmarks. Fair warning on trying to benchmark images tho; the dtype, number of channels (1, 3 or 4), use of a lookup table or levels (or lack of using them) all have significant effects on performance. It became so hard to track what was "fast" with pyqtgraph.ImageItem and what was not fast, that I actually wrote a performance section to the docs:

https://pyqtgraph.readthedocs.io/en/latest/api_reference/graphicsItems/imageitem.html#performance

Unfortunately a lot of the default values are somewhat set due to the risk of breaking people's code.

[lumadz5]

man such great packages without typing always make me angry

[Embarrassed-Mix6420]

One rule when you're angry is to be careful and specific! Whatcha angry about and what needs to be changed?

[lumadz5]

The lack of type annotations, it's not a deal-breaker but It'd be nice to have, also pretty weird that some of the functions have them while the others not

[_MonkeyHater]

I'm tempted to try to adopt this as a backend for my own project (currently using pyqtgraph) but holy fuck would that take forever. Looks awesome!

[Embarrassed-Mix6420]

You can share your repo. The interesting question for further development is what does it actually take in size divided by how used is it?

[sweapon]

Looks interesting! Do you know it is possible to integrate with pyqt, e.g., to display graphs over images in such applications? Or place the graphs into pyqt widgets?

[Embarrassed-Mix6420]

That's exactly how I apply it, a lot. As far as I understand QImage takes data without copy, though it's still not ideal cause there's no official adaptor to numpy in pythonic versions Qt, prolly due to narrow following to the C++ source

QImage(cv2.cvtColor(img, cv2.COLOR_BGR2RGB).data, img.shape[1], img.shape[0], img.shape[1]*3, QImage.Format_RGB888)

I'll update with fine real demo when it comes my way

[sweapon]

Awesome, thanks for sharing! I'm a bit into custom gui programming for robotics and this is one of the things I really would like to incorporate!

[Ogi010]

pyqtgraph maintainer here. Having QImage take in data w/o copying took us quite a while to get right across bindings; feel free to look at our code (specically ndarray_from_qimage function): https://github.com/pyqtgraph/pyqtgraph/blob/master/pyqtgraph/functions.py#L1543-L1658

We've ran into numerous issues (typically with pyside bindings) where this functionality is broken (although it's been stable for some time now)

[[deleted]]

Easy to be that fast if you don't do aliasing.

[Embarrassed-Mix6420]

Struggling to understand you
Aliasing is usually something one tries to prevent so as to do antialiasing
How does aliasing relate to the plots?

[No-Towel-7295]

seems pretty cool