64 lines
2.6 KiB
Python
64 lines
2.6 KiB
Python
from state.devstate import DevState
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from api.od import ODAPI
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from concrete_syntax.textual_od.renderer import render_od
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# from concrete_syntax.textual_od.renderer_jinja2 import render_od_jinja2
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from bootstrap.scd import bootstrap_scd
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from util import loader
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from transformation.rule import RuleMatcherRewriter, ActionGenerator
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from transformation.ramify import ramify
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from examples.semantics.operational import simulator
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from examples.petrinet.renderer import show_petri_net
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if __name__ == "__main__":
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import os
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THIS_DIR = os.path.dirname(__file__)
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# get file contents as string
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def read_file(filename):
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with open(THIS_DIR+'/'+filename) as file:
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return file.read()
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state = DevState()
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scd_mmm = bootstrap_scd(state)
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# Read models from their files
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mm_cs = read_file('metamodels/mm_design.od')
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mm_rt_cs = mm_cs + read_file('metamodels/mm_runtime.od')
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# m_cs = read_file('models/m_example_simple.od')
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# m_rt_initial_cs = m_cs + read_file('models/m_example_simple_rt_initial.od')
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# m_cs = read_file('models/m_example_mutex.od')
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# m_rt_initial_cs = m_cs + read_file('models/m_example_mutex_rt_initial.od')
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m_cs = read_file('models/m_example_inharc.od')
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m_rt_initial_cs = m_cs + read_file('models/m_example_inharc_rt_initial.od')
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# Parse them
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mm = loader.parse_and_check(state, mm_cs, scd_mmm, "Petri-Net Design meta-model")
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mm_rt = loader.parse_and_check(state, mm_rt_cs, scd_mmm, "Petri-Net Runtime meta-model")
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m = loader.parse_and_check(state, m_cs, mm, "Example model")
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m_rt_initial = loader.parse_and_check(state, m_rt_initial_cs, mm_rt, "Example model initial state")
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mm_rt_ramified = ramify(state, mm_rt)
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rules = loader.load_rules(state,
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lambda rule_name, kind: f"{THIS_DIR}/operational_semantics/r_{rule_name}_{kind}.od",
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mm_rt_ramified,
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["fire_transition"]) # only 1 rule :(
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matcher_rewriter = RuleMatcherRewriter(state, mm_rt, mm_rt_ramified)
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action_generator = ActionGenerator(matcher_rewriter, rules)
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def render_callback(od):
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show_petri_net(od)
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return render_od(state, od.m, od.mm)
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sim = simulator.Simulator(
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action_generator=action_generator,
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decision_maker=simulator.InteractiveDecisionMaker(auto_proceed=False),
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# decision_maker=simulator.RandomDecisionMaker(seed=0),
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renderer=render_callback,
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# renderer=lambda od: render_od(state, od.m, od.mm),
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)
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sim.run(ODAPI(state, m_rt_initial, mm_rt))
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