|
|
@@ -8,20 +8,13 @@ There are two tools: `hercules` and `labours.py`. The first is the program
|
|
|
written in Go which takes a Git repository and runs a Directed Acyclic Graph (DAG) of [analysis tasks](doc/PIPELINE_ITEMS.md).
|
|
|
The second is the Python script which draws some predefined plots. These two tools are normally used together through
|
|
|
a pipe. It is possible to write custom analyses using the plugin system. It is also possible
|
|
|
-to merge several analysis results together.
|
|
|
+to merge several analysis results together. There is a [presentation](http://vmarkovtsev.github.io/techtalks-2017-moscow-lightning/) available.
|
|
|
|
|
|
|
|
|
<p align="center">The DAG of burndown and couples analyses with UAST diff refining. Generated with <code>hercules --burndown --burndown-people --couples --feature=uast --dry-run --dump-dag doc/dag.dot https://github.com/src-d/hercules</code></p>
|
|
|
|
|
|
|
|
|
-<p align="center">torvalds/linux line burndown (granularity 30, sampling 30, resampled by year)</p>
|
|
|
-
|
|
|
-There is an option to resample the bands inside `labours.py`, so that you can
|
|
|
-define a very precise distribution and visualize it different ways. Besides,
|
|
|
-resampling aligns the bands across periodic boundaries, e.g. months or years.
|
|
|
-Unresampled bands are apparently not aligned and start from the project's birth date.
|
|
|
-
|
|
|
-There is a [presentation](http://vmarkovtsev.github.io/techtalks-2017-moscow-lightning/) available.
|
|
|
+<p align="center">torvalds/linux line burndown (granularity 30, sampling 30, resampled by year). Generated with <code>hercules --burndown --pb https://github.com/torvalds/linux | python3 labours.py -f pb -m project</code></p>
|
|
|
|
|
|
### Installation
|
|
|
You are going to need Go (>= v1.8) and Python 2 or 3.
|
|
|
@@ -107,6 +100,11 @@ Granularity is the number of days each band in the stack consists of. Sampling
|
|
|
is the frequency with which the burnout state is snapshotted. The smaller the
|
|
|
value, the more smooth is the plot but the more work is done.
|
|
|
|
|
|
+There is an option to resample the bands inside `labours.py`, so that you can
|
|
|
+define a very precise distribution and visualize it different ways. Besides,
|
|
|
+resampling aligns the bands across periodic boundaries, e.g. months or years.
|
|
|
+Unresampled bands are apparently not aligned and start from the project's birth date.
|
|
|
+
|
|
|
#### Files
|
|
|
|
|
|
```
|
Vadim Markovtsev