A Quick and Dirty Guide to PyQt5
So far I have seen a lot of guides that introduce the PyQt5 as the saviour of humanity, the holy hand grenade of all the GUIs out there, but I have not yet seen a guide where… well, you start with a basic stuff. Where you abuse the notation at first, make errors, just to get things going.
So here you go – a totally wrong, dirty guide to how not to write in PyQt5! With examples! And NO QML.
It works. Just remember about forwarding with a proper xhci host.
So yesterday I wanted to post my notes from around October on how to install ROS Melodic on a Slackware 64bit system – yes, I’m boring, but honestly I like compiling ROS. It’s like an unhealthy, nerve-wrecking, time-consuming addiction that makes you smile in the end just for this one minute and it’s all worth it. Kinda like golf.
During my recent works with SEA (Series Elastic Actuators) I was using motors with gearboxes and was happy – as happy as a researcher can be in that scenario. So not very much.
All my gearboxes are scrapped from different servos, be it small 9g 1$ blue servo (SG-90) or a “slightly” more expensive Dynamixel MX-64. But what if… I design my own?
This is one of the older things I did, but did not have enough time to make it into a post. So: the aim is to get a working stream of data from OptiTrack system into ROS Kinetic. A small catch: get individual points as well as rigid bodies.
A bit of honesty – I made this project by accident. True story.
Just notes on installing jekyll, because I keep forgetting how.
assume that 192.168.0.100 is the server and 192.168.0.153 is the client with Matlab
console on the server:
(and same with rosrun turtlesim turtlesim_node on another console)
robotctrl = rospublisher( ‘/turtle1/cmd_vel’ )
robotpose = rossubscriber( ‘/turtle1/pose’ )
twist = rosmessage(robotctrl.MessageType)
twist.Linear.X = 1
state = receive( robotpose, 1 )
(RAW, unedited dump of my notes that ends in a glorious failure) Goals for today:
- IOMMU groups on Zbook 14 G1 + Slackware 14.2
- GPU passthrough for a second graphics card (some kind of a Radeon)
- (maybe) Looking Glass to copy framebuffer to the Intel GPU
I almost forgot, while discussing libpam last time, that the top reason for Matlab R2017b crashing in flames and destruction on Slackware 14.2 is actually MATLABWindow (and the Chromium underneath) that are causing problems. Solution? As always, cheat with libraries.