Graphical block debugging: Difference between revisions

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{{missingimages}}
{{experimental}}
{{experimental}}


Some progress has been made on this, with the addition of a method in the <tt>system</tt> directory called <tt>system_write_graph</tt>. This method should output the incidence between a filtered set of variables and relations.
Some progress has been made on this, with the addition of a method in the <tt>system</tt> directory called <tt>system_write_graph</tt>. This method should output the incidence between a filtered set of variables and relations. The graph is drawn using [http://www.graphviz.org GraphViz].


<div class="thumb tnone"><div class="thumbinner" style="width:402px;">[[Image:Lotka-graph.png]] <div class="thumbcaption"><div class="magnify">[[File:Lotka-graph.png|<img src="/skins/common/images/magnify-clip.png" width="15" height="11" alt="" />]]</div>Graph of the relationship between variables and relations in the {{src|models/johnpye/lotka.a4c}} example. The graph is drawn using [http://www.graphviz.org GraphViz].</div></div></div>
[[Image:Lotka-graph.png|200px|thumb|none|Graph of the relationship between variables and relations in the {{src|models/johnpye/lotka.a4c}} example.]]


At present this functionality is available from the Python API as shown:
At present this functionality is available from the Python API as shown:
Line 14: Line 13:
M.build()
M.build()
f = file('lotka.png','w')
f = file('lotka.png','w')
M.write(f,&quot;dot&quot;)
M.write(f,"dot")


f.close()</source>
f.close()</source>

Latest revision as of 01:41, 26 November 2017

This page documents an experimental feature. Please tell us if you experience any problems.

Some progress has been made on this, with the addition of a method in the system directory called system_write_graph. This method should output the incidence between a filtered set of variables and relations. The graph is drawn using GraphViz.

Graph of the relationship between variables and relations in the models/johnpye/lotka.a4c example.

At present this functionality is available from the Python API as shown:

L=ascpy.Library()
L.load('johnpye/lotka.a4c')
M = self.L.findType('lotka').getSimulation('sim')

M.build()
f = file('lotka.png','w')
M.write(f,"dot")

f.close()

The file lotka.png can then be viewed in your preferred graphics viewer.

Some preliminary work at integrating these graphics into the PyGTK has been made, see Incidence Graph.