[Blends-commit] [SCM] science branch, master, updated. 7d2cd8f89aa60f3de0352ad48fb6aa36c0a08c09

[Sébastien Villemot]

The following commit has been merged in the master branch:
commit 7d2cd8f89aa60f3de0352ad48fb6aa36c0a08c09
Author: Sébastien Villemot <sebastien at debian.org>
Date:   Wed Jan 31 10:44:30 2018 +0100

    Add repast-symphony, repast-hpc and python-pandasdmx to economics task.

diff --git a/tasks/economics b/tasks/economics
index f5a6b7e..6f6bb7e 100644
--- a/tasks/economics
+++ b/tasks/economics
@@ -225,6 +225,51 @@ Pkg-Description: R package to simulate Post-Keynesian Stock-Flow Consistent Mode
  Stephen and O’Shea, Terence, Solution and Simulation of Large Stock Flow
  Consistent Monetary Production Models Via the Gauss Seidel Algorithm.
 
+Depends: repast-symphony
+Homepage: https://repast.github.io/repast_simphony.html
+License: BSD-3-clause
+Pkg-Description: platform for extremely flexible models of interacting agents
+ Repast Simphony is a tightly integrated, richly interactive, cross platform
+ Java-based modeling system. It supports the development of extremely flexible
+ models of interacting agents for use on workstations and computing clusters.
+ .
+ Repast Simphony models can be developed in several different forms including
+ the ReLogo dialect of Logo, point-and-click statecharts, Groovy, or Java, all
+ of which can be fluidly interleaved.
+ .
+ Repast Simphony has been successfully used in many application domains
+ including social science, consumer products, supply chains, possible future
+ hydrogen infrastructures, and ancient pedestrian traffic to name a few.
+
+Depends: repast-hpc
+Homepage: https://repast.github.io/repast_hpc.html
+License: BSD-3-clause
+Pkg-Description: agent-based modeling for large-scale distributed computing platforms
+ Repast for High Performance Computing (Repast HPC) is a next generation
+ agent-based modeling system intended for large-scale distributed computing
+ platforms. It implements the core Repast Simphony concepts (e.g. contexts and
+ projections), modifying them to work in a parallel distributed environment.
+ .
+ Repast HPC is written in cross-platform C++. It can be used on workstations,
+ clusters, and supercomputers running Apple macOS, Linux, or Unix. Portable
+ models can be written in either standard or Logo-style C++.
+ .
+ Repast HPC has been successfully tested for scalability on Argonne National
+ Laboratory's Blue Gene/P.
+
+Depends: python-pandasdmx
+Homepage: https://pypi.python.org/pypi/pandaSDMX
+License: Apache-2.0
+Pkg-Description: python- and pandas-powered client for statistical data and metadata exchange
+ pandaSDMX is SDMX software that facilitates the acquisition and analysis of
+ SDMX-2.1 compliant data and metadata. These can be rendered in various
+ formats:
+  - as a hierarchical data structure following closely the SDMX 2.1 information
+    model. Technically, the model is a layer on top of the XML structure
+    rendered by SDMX web services.
+  - as arbitrary output generated by dedicated writers. Currently, there is only
+    one writer rendering data as pandas Series and DataFrames.
+
 Suggests: ess
 
 Suggests: dynare-matlab

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