Examples and clean-ups (#1)
- Attempt at implementing an example for DRS - Complete reactions set - New automaton - Formula - Fixed automaton scaling - Proc index in the formula - Benchmark generators - Scripts to reproduce experiments for reaction mining
This commit was merged in pull request #1.
This commit is contained in:
Artur Meski
150
examples/smt/scalable_chain.py
Normal file → Executable file
150
examples/smt/scalable_chain.py
Normal file → Executable file
@@ -31,76 +31,102 @@ from itertools import chain, combinations
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import sys
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import resource
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def generate_system(chainLen, maxConc):
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"""
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This function generates the reaction system with concentrations
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for the scalable chain benchmark
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chainLen is the length of the chain
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maxConc is the maximal concentration
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"""
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r = ReactionSystemWithConcentrations()
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r.add_bg_set_entity(("inc",1))
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r.add_bg_set_entity(("dec",1))
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for i in range(1,chainLen+1):
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r.add_bg_set_entity(("e_" + str(i),maxConc))
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for i in range(1,chainLen+1):
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ent = "e_" + str(i)
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r.add_reaction_inc(ent, "inc", [(ent, 1)],[(ent,maxConc)])
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r.add_reaction_dec(ent, "dec", [(ent, 1)],[])
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if i < chainLen:
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r.add_reaction([(ent,maxConc)],[],[("e_"+str(i+1),1)])
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r.add_reaction([("e_" + str(chainLen),maxConc)],[("dec",1)],[("e_" + str(chainLen),maxConc)])
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r = ReactionSystemWithConcentrations()
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r.add_bg_set_entity(("inc", 1))
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r.add_bg_set_entity(("dec", 1))
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for i in range(1, chainLen + 1):
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r.add_bg_set_entity(("e_" + str(i), maxConc))
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for i in range(1, chainLen + 1):
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ent = "e_" + str(i)
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r.add_reaction_inc(ent, "inc", [(ent, 1)], [(ent, maxConc)])
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r.add_reaction_dec(ent, "dec", [(ent, 1)], [])
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if i < chainLen:
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r.add_reaction([(ent, maxConc)], [], [("e_" + str(i + 1), 1)])
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r.add_reaction(
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[("e_" + str(chainLen), maxConc)],
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[("dec", 1)],
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[("e_" + str(chainLen), maxConc)],
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)
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c = ContextAutomatonWithConcentrations(r)
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c.add_init_state("init")
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c.add_state("working")
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c.add_transition("init", [("e_1",1),("inc",1)], "working")
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c.add_transition("working", [("inc",1)], "working")
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rc = ReactionSystemWithAutomaton(r,c)
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c.add_transition("init", [("e_1", 1), ("inc", 1)], "working")
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c.add_transition("working", [("inc", 1)], "working")
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rc = ReactionSystemWithAutomaton(r, c)
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return rc
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def generate_formula(formula_number, chainLen, maxConc):
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"""
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This function generates the rsLTL formula
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This function generates the rsLTL formula
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corresponding to the formula_number parameter
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"""
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if formula_number == 1:
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ret = Formula_rsLTL.f_F( BagDescription.f_entity("inc") > 0, (BagDescription.f_entity('e_'+str(chainLen)) >= maxConc) )
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ret = Formula_rsLTL.f_F(
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BagDescription.f_entity("inc") > 0,
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(BagDescription.f_entity("e_" + str(chainLen)) >= maxConc),
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)
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elif formula_number == 2:
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f_tmp = Formula_rsLTL.f_F( BagDescription.f_entity("inc") > 0, (BagDescription.f_entity('e_'+str(chainLen)) == maxConc) )
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for i in range(chainLen-1,0,-1):
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f_tmp = Formula_rsLTL.f_F( BagDescription.f_entity("inc") > 0, f_tmp & (BagDescription.f_entity('e_'+str(i)) == maxConc) )
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f_tmp = Formula_rsLTL.f_F(
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BagDescription.f_entity("inc") > 0,
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(BagDescription.f_entity("e_" + str(chainLen)) == maxConc),
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)
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for i in range(chainLen - 1, 0, -1):
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f_tmp = Formula_rsLTL.f_F(
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BagDescription.f_entity("inc") > 0,
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f_tmp & (BagDescription.f_entity("e_" + str(i)) == maxConc),
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)
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ret = f_tmp
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elif formula_number == 3:
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ret = Formula_rsLTL.f_G( BagDescription.f_TRUE(),
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ret = Formula_rsLTL.f_G(
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BagDescription.f_TRUE(),
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Formula_rsLTL.f_Implies(
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(BagDescription.f_entity('e_1') == 1),
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(BagDescription.f_entity("e_1") == 1),
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Formula_rsLTL.f_F(
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BagDescription.f_entity("inc") > 0,
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(BagDescription.f_entity('e_'+str(chainLen)) == maxConc)
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)
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)
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(BagDescription.f_entity("e_" + str(chainLen)) == maxConc),
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),
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),
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)
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elif formula_number == 4:
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ret = Formula_rsLTL.f_F( BagDescription.f_entity("inc") > 0 , BagDescription.f_entity('e_1') == maxConc )
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ret = Formula_rsLTL.f_F(
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BagDescription.f_entity("inc") > 0,
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BagDescription.f_entity("e_1") == maxConc,
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)
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elif formula_number == 5:
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ret = Formula_rsLTL.f_X(BagDescription.f_TRUE(), Formula_rsLTL.f_U( BagDescription.f_entity("inc") > 0 , BagDescription.f_entity('e_1') > 0, BagDescription.f_entity('e_2') > 0 ) )
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ret = Formula_rsLTL.f_X(
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BagDescription.f_TRUE(),
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Formula_rsLTL.f_U(
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BagDescription.f_entity("inc") > 0,
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BagDescription.f_entity("e_1") > 0,
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BagDescription.f_entity("e_2") > 0,
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),
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)
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else:
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ret = None
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assert ret is not None, "Unknown formula"
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return ret
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@@ -110,64 +136,64 @@ def save_statistics(smt_rsc, formula_number, chainLen, maxConc):
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"""
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Saves the statistics fetched from smt_rsc into files
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"""
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time=0
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mem_usage=resource.getrusage(resource.RUSAGE_SELF).ru_maxrss/(1024*1024)
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filename_t="bench_rsc_F" + str(formula_number) + "_time.log"
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filename_m="bench_rsc_F" + str(formula_number) + "_mem.log"
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time=smt_rsc.get_verification_time()
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time = 0
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mem_usage = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss / (1024 * 1024)
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filename_t = "bench_rsc_F" + str(formula_number) + "_time.log"
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filename_m = "bench_rsc_F" + str(formula_number) + "_mem.log"
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time = smt_rsc.get_verification_time()
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f=open(filename_t, 'a')
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log_str="(" + str(chainLen) + "," + str(maxConc) + "," + str(time) + ")\n"
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f = open(filename_t, "a")
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log_str = "(" + str(chainLen) + "," + str(maxConc) + "," + str(time) + ")\n"
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f.write(log_str)
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f.close()
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f=open(filename_m, 'a')
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log_str="(" + str(chainLen) + "," + str(maxConc) + "," + str(mem_usage) + ")\n"
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f = open(filename_m, "a")
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log_str = "(" + str(chainLen) + "," + str(maxConc) + "," + str(mem_usage) + ")\n"
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f.write(log_str)
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f.close()
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def scalable_chain(print_system=False):
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"""
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This is the entry point for the benchmark
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"""
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if len(sys.argv) < 1+3:
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if len(sys.argv) < 1 + 3:
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print("arguments: <chainLen> <maxConc> <formulaNumber>")
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exit(1)
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chainLen=int(sys.argv[1]) # chain length
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maxConc=int(sys.argv[2]) # depth (max concentration)
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formula_number=int(sys.argv[3])
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chainLen = int(sys.argv[1]) # chain length
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maxConc = int(sys.argv[2]) # depth (max concentration)
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formula_number = int(sys.argv[3])
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if chainLen < 1 or maxConc < 1:
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print("be reasonable")
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exit(1)
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if not formula_number in range(1,5+1):
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if not formula_number in range(1, 5 + 1):
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print("formulaNumber must be in 1..5")
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exit(1)
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# Generate the reaction systems with concentrations
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rc = generate_system(chainLen, maxConc)
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# Generate the formula
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form = generate_formula(formula_number, chainLen, maxConc)
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# Optional dump/print of the system
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if print_system:
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rc.show()
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# Create an instance of the SMT checker for RS with concentrations
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smt_rsc = SmtCheckerRSC(rc)
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# Start the verification process
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smt_rsc.check_rsltl(formula=form)
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save_statistics(smt_rsc, formula_number, chainLen, maxConc)
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def main():
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scalable_chain(print_system=True)
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if __name__ == "__main__":
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main()
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