44eded59b7
.. samples(SERIES) will return a vector of all datapoints for the
specified series. e.g. samples(POWER) will return a vector of
3600 elements for a 1hr ride with 1s sampling.
.. to make sure it doesn't go haywire and open all ridefiles if
used in a datafilter or in a naive way by users, it will not
open a ridefile, just return an empty vector.
.. this is safe to use in user metrics; e.g. for average power
you could use value { mean(samples(POWER)); } and this would
work well as the ride is opened before calculation starts.
.. there is an added bonus that this means a datafilter:
length(samples(SECS)) will filter only those rides that are
open. A useful debug tool for memory usage from download or
ride import activity.
GoldenCheetah
About
GoldenCheetah is an open-source data analysis tool primarily written in C++ with Qt for cyclists and triathletes with support for training as well.
GoldenCheetah can connect with indoor trainers and cycling equipment such as cycling computers and power meters to import data.
In addition, GoldenCheetah can connect to cloud services.
It can then manipulate and view the data, as well as analyze it.
Installing
Golden Cheetah install and build instructions are documented for each platform;
INSTALL-WIN32 For building on Microsoft Windows
INSTALL-LINUX For building on Linux
INSTALL-MAC For building on Apple OS X
OSX: 
Windows:
Alternatively, official builds are available from http://www.goldencheetah.org
whilst the latest developer builds are available from https://github.com/GoldenCheetah/GoldenCheetah/releases