Mark Liversedge a3f42c0746 Horizontal and Vertical Line Annotations on UserChart
.. annotate(hline|vline, "text", style, value) to add a horizontal or
   vertical line to the plot for the current series on a UserChart.

   style is one of solid, dash, dot, dashdot or dashdotdot which are
   the standard Qt pen styles for drawing lines.

   I also took the opportunity to refactor how annotations are passed
   from the datafilter down to the generic plot. This should make it
   far easier to add annotations in the future.

.. fixed a SEGV in the voronoi annotation, which was related to memory
   management and the sqrt_nsites variable (honestly, I am amazed it
   ever worked).

.. labels in Python and R charts are now broken, will fixup shortly when
   worked out how it should work (annotations are related to a series).
2021-10-12 22:13:09 +01:00
2021-10-06 11:01:04 +01:00
2018-06-02 11:01:43 +01:00
2019-03-12 19:16:22 +00:00
2021-10-04 16:04:34 -03:00
2021-10-01 17:29:54 -03:00

GoldenCheetah

About

GoldenCheetah is a desktop application for cyclists and triathletes and coaches, providing a rich set of tools and models to analyse, track and predict performance, optimise aerodynamics and train indoors.

GoldenCheetah integrates with most popular cloud services like Strava and Todays Plan, imports data from bike computers, imports downloads from any website like TrainingPeaks and Garmin and will also connect to smart trainers using ANT+ and Bluetooth.

GoldenCheetah is free for everyone to use and modify, released under the GPL v2 open source license with pre-built binaries for Mac, Windows and Linux.

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

macOS and Linux: Build Status

Windows: Build status

Coverity Status

Official release builds, snapshots and development builds are all available from http://www.goldencheetah.org

Languages
Standard ML 68.3%
C++ 28.1%
C 2.7%
Yacc 0.2%
QMake 0.2%
Other 0.1%