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1 parent a8048ed commit 7fcb792326d062ba965b3fdfee6c16240b230d95 MJS committed Mar 30, 2012
Showing with 16 additions and 5 deletions.
  1. +10 −1 code/BA_MJS.tex
  2. +4 −3 code/graphenumerator2.py
  3. +2 −1 code/test.py
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@@ -170,7 +170,16 @@ \subsection{Pattern definition in CTL}
{\tt A(initial\_condition -> EF(AG(gg=}x{\tt )))}.
\end{equation}
In plain language, we require some future paths to exist on which
-eventually the output gene takes on value $x$.
+eventually the output gene takes on value $x$. \\
+
+TODOs:
+\begin{enumerate}
+\item Introduction to CTL (see .pdfs)
+\item The issues with forall eventually forall globally (not expressible in LTL for example)
+\item The issues with forAll states vs. there exists a state (tree with initial state vs. tree where all states are considered initial states).
+Exists is plausible but it only makes sense if there are non-trivial results (e.g. networks that do NOT produce stripes).
+\item Any of these could be evaluated and compared in a big table.
+\end{enumerate}
\subsection{Pattern definition in AL}
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@@ -137,9 +137,10 @@ def filter_disconnected(unique_networks, outfile_tag="_with_morphogene"):
#networks = dict((k, networks[k]) for k in range(500)) # enable for quick check
print "found", len(networks), "networks." # 3^9 = 19683 if unconstrained
#print networks[1]
- check_isomorphism(networks, outfile_tag="_without_morphogene", tag_input_gene=False) # takes 6 hrs
- #check_isomorphism(networks, outfile_tag="_with_morphogene", tag_input_gene=True) # takes 15 hrs
- unique_networks = cPickle.load(file("unique_networks_without_morphogene.db"))
+ #check_isomorphism(networks, outfile_tag="_without_morphogene", tag_input_gene=False) # takes 6 hrs
+ check_isomorphism(networks, outfile_tag="_with_morphogene", tag_input_gene=True) # takes 15 hrs
+ #unique_networks = cPickle.load(file("unique_networks_without_morphogene.db"))
+ unique_networks = cPickle.load(file("unique_networks_with_morphogene.db"))
print "found", len(unique_networks), "unique networks."
filter_disconnected(unique_networks, outfile_tag="_with_morphogene")
connected_unique_networks = cPickle.load(file("connected_unique_networks_with_morphogene.db"))
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@@ -238,7 +238,8 @@ def export_STG(mc, gps, filename, initialRules=None):
2:["((rr=2&bb=0&gg=1)->EF(AG(gg=0)))&((rr=1&bb=0&gg=1)->EF(AG(gg=1)))&((rr=0&bb=0&gg=0)->EF(AG(gg=0)))", "forAll", "CTL"],
# (anterior&medial&posterior), the gg=1 in anterior and medial is from the drawing on page 5
3:["((rr=2&bb=0&gg=1)->EF(AG(gg=0&rr=2)))&((rr=1&bb=0&gg=1)->EF(AG(gg=1&rr=1)))&((rr=0&bb=0&gg=0)->EF(AG(gg=0&rr=0)))", "forAll", "CTL"],
- 4:["((rr=2)&EF(AG(gg=0)))&((rr=1)&EF(AG(gg=1)))&((rr=0)&EF(AG(gg=0))", "forAll", "CTL"]
+ 4:["((rr=2)&EF(AG(gg=0)))&((rr=1)&EF(AG(gg=1)))&((rr=0)&EF(AG(gg=0))", "forAll", "CTL"],
+ 5:["((rr=2)->AF(AG(gg=0)))&((rr=1)->AF(AG(gg=1)))&((rr=0)->AF(AG(gg=0)))", "exists", "CTL"]
}
'''

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