- #Goldencheetah weather data mac os x#
- #Goldencheetah weather data series#
- #Goldencheetah weather data free#
To access activity data the Python script uses the GC activity API, which in the context of a custom data processor is augmented with the ability to modify the objects returned by GC.series and GC.xdataSeries by assignment to object, as shown in the example, since they implement _setitem_.Īdditionally the objects returned by xdataSeries support append and remove methods, and the Python-API was extended with the following methods available for custom data processors: This is handy since it allows to preview the data, both standard and XData, run the data processor using Run button and immediately see the script effects on the selected activity, undo them if needed and run again, until you are satisfied enough to save and close to create a new Python Fix (or edit an existing one) with the provided name and script. Script output is shown in the lower left panel, which behaves like an standard Python interpreter REPL. The following dialog window allows to create a new Python Fix (or edit an existing one) editing the name and script on the upper left panel, and test its behaviour on the selected activity, which is shown in the Editor on the right panel. Managing Existing Python FixesĮdit > Python fixes > Manage Python Fixes menu allows to see existing custom data processors, and select one to edit or delete:Įditing a Python Fix is similar to creating a new one but prefilled with the name and script for the selected Python Fix.
These changes are subject to Undo/Redo in Editor until they are made permanent via Save or discarded via Revert to Saved Version or Exit without saving.
#Goldencheetah weather data series#
Running Existing Python FixesĮxisting Python fixes can be executed directly from Edit > Python Fixes menu and they behave like builtin Data Processors: they are able to add, modify and delete standard or XData series for the currently selected activity in Activities View. to manage existing custom data processors (edit and delete) and to create new custom data processors in Python. It allows to run existing custom data processors (Fix Missing Initial Temperature and Add Weather Data, in this example). This menu item is automatically available when Python embedding is enabled in GoldenCheetah, see Working with Python for details. The lead developer isa 47 year old hack that cut his teeth on C in the 80s.The ability to create custom data processors in Python, called Python fixes, is a new GoldenCheetah v3.5 feature accessible via Edit > Python fixes menu:
#Goldencheetah weather data mac os x#
It supports Mac OS X (including Yosemite), Linux, OpenBSD and Windows.
#Goldencheetah weather data free#
You can even analyse subsets of data using free text search and advanced data filtering. You can record and plot data as you ride indoors including support for video, ANT+ power, virtual power and computer controlled trainers from Racermate, Wahoo and Tacx.Īdvanced analysis features include time series, histogram, scatter, 3d, pedal force/velocity, aerobic and anaerobic stress, power duration, personal bests and supports over 100 metrics including altitude power, LR balance, TSS, BikeScore, NP and xPower. You can share and export data to popular online services like Strava and TrainingPeaks. You can analyse and compare performance data across different rides, intervals, seasons and even compare athletes. GoldenCheetah supports all current power meters including SRM, PowerTap and Vector and all of the most popular application file formats.
GoldenCheetah is a program for cyclists, especially those with power meters.ĭownload and import activities from most popular bike computers from CycleOps, SRM, Polar, Garmin and others Analyse, track and review performance data and metrics Train indoors with realtime monitoring supporting trainers from Racermate, Tacx and any ANT+ device.
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