Mark Liversedge 4b4d86f413 Datafilter bug fixes
.. annotate - didn't validate parameters - seemingly inocuous but there
   are multiple validators that update leaf->seriesType. When this did
   not happen a) syntax errors were ignored (and caused a crash) and
   b) functions like samples(POWER) returned the wrong data.

.. annotate - assumed parameters were numeric or string but did not
   support vectors.

.. lots of use of 'it' as a variable, overriding the scope of the
   DataFilter::eval() function parameter which in a couple of cases
   led to SEGV ('it' is used when indexing vectors).
2020-05-13 14:53:25 +01:00
2015-09-18 08:49:39 +01:00
2020-02-24 09:22:48 +00:00
2020-05-13 14:53:25 +01:00
2019-02-10 16:18:51 +01:00
2020-05-06 21:19:24 -03:00
2020-05-07 16:25:45 -03:00
2018-06-02 11:01:43 +01:00
2019-03-12 19:16:22 +00:00
2019-11-29 14:26:17 -03:00
2020-05-09 13:39:02 -03:00
2020-03-27 13:38:45 -03:00

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

macOS and Linux: Build Status

Windows: Build status

Coverity Status

Alternatively, official builds are available from http://www.goldencheetah.org

whilst the latest developer builds are available from https://github.com/GoldenCheetah/GoldenCheetah/releases

Languages
Standard ML 68.2%
C++ 28.2%
C 2.7%
Yacc 0.2%
QMake 0.2%
Other 0.1%