[med-svn] [compclust] 01/01: Take over description from task file

[Andreas Tille]

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tille pushed a commit to branch master
in repository compclust.

commit 008b239a50e65370c28d0a137993ecb3b4165ffd
Author: Andreas Tille <tille at debian.org>
Date:   Fri Dec 1 17:01:30 2017 +0100

    Take over description from task file
---
 debian/control | 19 +++++++++++++++----
 1 file changed, 15 insertions(+), 4 deletions(-)

diff --git a/debian/control b/debian/control
index 2ccc17b..734fcda 100644
--- a/debian/control
+++ b/debian/control
@@ -13,7 +13,18 @@ Package: python-compclust
 Architecture: any
 Depends: ${shlibs:Depends}, python, python-matplotlib, python-numpy
 Recommends: quixote, python-tk
-Description: CompClust bioinformatics analysis tools
- CompClust provides a set of clustering algorithms, scoring tools
- to quantitatively compare various clusterings, and then visualize
- the results.
+Description: explore and quantify relationships between clustering results
+ CompClust is a python package written using the pyMLX and IPlot APIs. It provides
+ software tools to explore and quantify relationships between clustering results. Its
+ development has been largely built around needs of microarray data analysis but could
+ be easily used in other domains.
+ .
+ Briefly pyMLX provides for efficient and convenient execution of many clustering
+ algorithms using a extendable library of algorithms. It also provides many-to-many
+ linkages between data features and annotations (such as cluster labels, gene names,
+ gene ontology information, etc.) These linkages persist through varied data
+ manipulations. IPlot provides an abstraction of the plotting process in which any
+ arbitrary feature or derived feature of the data can be projected onto any feature
+ of the plot, including the X,Y coordinates of points, marker symbol, marker size,
+ maker/line color, etc. These plots are intrinsically linked to the dataset, the
+ View and the Labeling classes found within pyMLX.

-- 
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