rpi-rgb-led-matrix VS sysidentpy

Hzeller - https://github.com/hzeller/rpi-rgb-led-matrix/blob/a93acf26990ad6794184ed8c9487ab2a5c39cd28/bindings/python/README.md

I installed https://github.com/hzeller/rpi-rgb-led-matrix

Anyway I used this library on a Raspberry Pi Zero https://github.com/hzeller/rpi-rgb-led-matrix I only displayed static images but the "image-example" shows how to handle animated gifs.

Adafruit makes a hat that you can plug right onto the GPIO port. I'm using rpi-rgb-led-matrix, I also have a guide you can watch on YT here https://www.youtube.com/watch?v=ssyTWpVEl0E

Use a rgb matrix hat, a raspberry pi, and this library.

To control the matrix, a loop is ran and inside things are displayed to the matrix. (I'm using this library https://github.com/hzeller/rpi-rgb-led-matrix)

I found this https://github.com/hzeller/rpi-rgb-led-matrix, this provides python scripts. Please read through them, and then ask specific questions at each step. If python just looks like gobldegock, I suggest you go through some basic python tutorials docs.python.org has a tutorial page, and no you don't have to complete the whole think just read everything about built-ins and basic syntax (for, if, def, else, etc).

If you then follow this forward to the code they originally forked theirs from from (here) and scroll down a fair way you find the entry Improving Flicker that states (in part):

Link para o site da documentação: SysIdentPy - SysIdentPy

I'm the only maintainer, but I keep including new features (some exclusives, like the algorithm I've developed in my thesis to create NARMAX models), improving the code and documentation, and fixing bugs.

benchmark codes: Welcome to SysIdentPy’s documentation! — NARMAX models

github: wilsonrljr/sysidentpy: A Python Package For System Identification Using NARMAX Models (github.com)

I built a package where you can build polynomial NARMAX models using the most used method for model selection of this class of models in the beckend. In addition, you can built NARX Neural Networks for forecasting problems (this is built on top of Pytorch) and you can use any model that have a fit/predict method (Catboost, any estimator from sklearn) in a NARX configuration to perform infinity-steps-ahead prediction. Maybe its worth a try. Here is the link of the package: GitHub - wilsonrljr/sysidentpy: A Python Package For System Identification Using NARMAX Models