Joachim Kohlhammer 3e8ddd9f29 Qt6: Preventing crash in stacked LTMPlots (#4483)
In Qt6 the internal handling of QList (now actually a QVector) was
changed compared to Qt5. This results in reallocations / recreations of
the LTMSettings, destroying the objects whose pointers already have been
set to the LTMPlots.
This commit reserves the required space upfront, preventing the
reallocations thus keeping the pointers valid and preventing the crash
2024-05-04 12:59:06 -03:00
2024-03-19 16:36:34 -03:00
2024-04-26 17:03:29 -03:00
2021-10-06 11:01:04 +01:00
2024-01-07 13:46:00 -03:00
2024-04-13 15:58:24 -03:00
2018-06-02 11:01:43 +01:00
2024-03-25 20:46:26 -03:00
2019-03-12 19:16:22 +00:00
2024-03-25 20:46:26 -03:00
2024-03-25 20:46:26 -03:00
2024-03-25 20:46:26 -03:00
2023-10-22 08:54:44 +01:00

GoldenCheetah

About

GoldenCheetah is a desktop application for cyclists and triathletes and coaches

  • Analyse using summary metrics like BikeStress, TRIMP or RPE
  • Extract insight via models like Critical Power and W'bal
  • Track and predict performance using models like Banister and PMC
  • Optimise aerodynamics using Virtual Elevation
  • Train indoors with ANT and BTLE trainers
  • Upload and Download with many cloud services including Strava, Withings and Todays Plan
  • Import and export data to and from a wide range of bike computers and file formats
  • Track body measures, equipment use and setup your own metadata to track

GoldenCheetah provides tools for users to develop their own own metrics, models and charts

  • A high-performance and powerful built-in scripting language
  • Local Python runtime or embedding a user installed runtime
  • Embedded user installed R runtime

GoldenCheetah supports community sharing via the Cloud

  • Upload and download user developed metrics
  • Upload and download user, Python or R charts
  • Import indoor workouts from the ErgDB
  • Share anonymised data with researchers via the OpenData initiative

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 MacOS

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

NOTIO Fork

If you are looking for the NOTIO fork of GoldenCheetah it can be found here: https://github.com/notio-technologies/GCNotio

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