#Goldencheetah zoom to section full
#Goldencheetah zoom to section registration

The same can be done for the right side, or against total power. It’ll properly plot Stages as a left-only power meter, showing just the left leg against just the left-leg data from a dual-sending unit.

#Goldencheetah zoom to section full

Stages) to a full dual-sending power meter (i.e. This is useful if you want to compare a left-only power meter (i.e. This includes the ability to compare left/right power meters by left/right leg, as well as to compare against left-only power meters. To reset back to the full view, simply double click on the graph.įor power meter data, there are extended types of charts. You can zoom in on a specific section by highlighting a section with your mouse: This value shown is *NOT* the average, but just that exact second in time. This allows you to compare values at any given second. Those points will be shown in the upper right corner of the graph, next to the file names. On each graph you can hover over the section in the graph to look at the various data points. There’s no concept of bike or run, rather, just data (since pace/speed isn’t displayed – only distance). For example, if no heart rate data was recorded then the HR graph won’t show. Here’s what an entire single page looks like (screenshoted below), or, you can just look at the exact same sample here live.Įach set of data set may have different metrics depending on what was recording. Once the page is opened you’ll see various sets of data from the public link that you clicked on. The tool is primarily designed around a desktop experience, and thus at the moment may render a bit odd on some mobile devices. For that there are better tools as part of training logs. Meaning, it’s not designed for comparing a Monday workout to a Tuesday workout on the same course. The tool is not designed for comparing workouts done at different times. This ensures that even if you don’t press start on the devices at the exact same second, it can still align them properly. The analyzer works by comparing the recorded date/timestamps in the files and matching them up. Renaming occurs by going into the edit/view option. You can either edit/view a set, or delete a set. If you’ve already created sets, then when you first login you’ll see a simple listing of all existing sets. As such, please keep copies of all your data files.*** ***Please remember that the Analyzer is *NOT* designed to replace your training log. Note that at present you cannot add files after the fact to a set – so be sure to add everything you want upfront. So if you have three devices, you’ll drag all three files into the window at once (or select them using the file picker). To begin, you’ll start by dragging in a pile of files from a given workout. Additionally, one can apply smoothing dynamically on the fly to allow for easier understanding of data (such as a 30-seconds smoothed chart for noisy power meter data). This gives significant flexibility in comparing products, as one can zoom in on various sections of a workout and dig into any inconsistencies. All that is needed is for those files to record a specific date/time. The tool can consume files from all major fitness devices types (Garmin, Sunuto, Polar, Timex, Apple Watch, etc…), using standard fitness file types (.FIT. H) Running Power (with Polar/COROS/Garmin/Wahoo watches) Right now it allows me to analyze the following types of data: This tool is what I use to compare data from multiple devices at the same time.

#Goldencheetah zoom to section registration

Just wanna register and skip all the chatter? No worries: Registration link at the bottom. It’s merely designed to analyze data from multiple devices at once. TrainingPeaks, Strava, Garmin Connect, SportTracks, etc…). So here we are!įinally note that the tool is NOT designed to replace or be a training log site (i.e. Given I continued to get so many requests for access to the tool, I figured it was time to finally open things up. During that time it’s largely been for my own use, though I have had a handful of folks use it in beta testing since then. So about two years ago I started working with a developer to put together a complete suite to analyze data. But that process would take me 20-40 minutes per set to create/normalize/present all the data, which was an eternity when I wanted to share not just one ride – but perhaps a dozen sets or more. It used to be that I used a combination of Excel and Golden Cheetah to normalize the data. optical HR sensors), and GPS tracks within GPS device reviews.

It’s how I create all of the graphs you see for power meter reviews, heart rate sensor reviews (i.e. This page serves as a quick-start guide for the DCR Analyze tool, which I use for data comparisons between products.