Stacked Histogram

We like all things stacked ;)

Stacked histogram support for showing things like time in zone on a PMC is kinda sassy...

Pastels are us too... hail Crockett and the Miami Vice crew

Wireguard setup for dummies

We all know that Dad is the IT infrastructure manager at home, so when it became clear that we needed a VPN for everyone to enjoy that infrastructure (aka access to streaming services) on their phones and laptops when they were away- it became Dad's job to make it happen. My first instinct was to get a Unifi device since I've got lots of them already. Something like the USG or Dream Machine and use the hardware VPN support from there. But then I baulked at the costs for something with enough horsepower, anywhere from £99 to £350. I looked at their Edgerouter X and other devices like the Netgate pfsense and thought, heck, how hard can it be to install a VPN server on my Linux workstation and do it for nothing ? So I started with OpenVPN but couldn't get it to work or work out how to configure clients. So I switched to OpenVPN access server and couldn't even get it to install (I am using Ubuntu 23.04 right now and its not supported). I watched some videos from Cross

W'bal its implementation and optimisation

So, the implementation of W'bal in GoldenCheetah has been a bit of a challenge. The Science I wanted to explain what we've done and how it works in this blog post, but realised that first I need to explain the science behind W'bal, W' and CP. W' and CP How hard can you go, in watts, for half an hour is going to be very different to how hard you can go for say, 20 seconds. And then thinking about how hard you can go for a very long time will be different again. But when it comes to reviewing and tracking changes in your performance and planning future workouts you quickly realise how useful it is to have a good understanding of your own limits. In 1965 two scientists Monod and Scherrer presented a ‘Critical Power Model’ where the Critical Power of a muscle is defined as ‘the maximum rate of work that it can keep up for a very long time without fatigue’. They also proposed an ‘energy store’ (later to be termed W’, pronounced double-ewe-prime) that represente

Implementing the Banister Impulse-Response Model in GoldenCheetah

Over January 2019 I implemented the Banister model in GoldenCheetah, along the way I learned a little about its strengths and weaknesses. This post is about that; explaining the Banister model and how it relates to the PMC , how it has been implemented in GoldenCheetah and what it's limitations are. I've also added a bit at the end covering some of the things I'm looking to do with this next from potential model improvements through to deep learning. In some ways this post is a longer written form of this tutorial I recorded covering Banister and GoldenCheetah. The Banister Impulse Response model In 1975 Eric Banister proposed an impulse-response model that could be used to correlate past training with changes in performance in order to predict future improvements from future training. Originally proposed for working with collegiate swimmers it was reworked in 1990 for working with running and of course also applicable for cycling. Each type of sport needed a w

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