Mercurial > repos > sybila > ebcsgen_simulation

comparison ebcsgen_simulate.py @ 0:179d32e79968 draft

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planemo upload for repository https://github.com/sybila/galaxytools/tree/master/tools/ebcsgen commit 33b83dc8c71401922b087400fa1f4080e9abe170
author sybila
date Tue, 04 Oct 2022 13:15:48 +0000
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-1:000000000000 0:179d32e79968
1 import argparse
2
3 from eBCSgen.Errors import UnspecifiedParsingError
4 from eBCSgen.Errors.InvalidInputError import InvalidInputError
5 from eBCSgen.Errors.ModelParsingError import ModelParsingError
6 from eBCSgen.Errors.RatesNotSpecifiedError import RatesNotSpecifiedError
7 from eBCSgen.Parsing.ParseBCSL import Parser
8
9
10 args_parser = argparse.ArgumentParser(description='Simulation')
11
12 args_parser._action_groups.pop()
13 required = args_parser.add_argument_group('required arguments')
14
15 required.add_argument('--model', type=str, required=True)
16 required.add_argument('--output', type=str, required=True)
17 required.add_argument('--deterministic', required=True)
18 required.add_argument('--direct', required=True)
19 required.add_argument('--runs', type=int, required=True)
20 required.add_argument('--max_time', type=float, required=True)
21 required.add_argument('--volume', type=float, required=True)
22 required.add_argument('--step', type=float, required=True)
23
24 args = args_parser.parse_args()
25
26 model_parser = Parser("model")
27 model_str = open(args.model, "r").read()
28
29 model = model_parser.parse(model_str)
30
31 if model.success:
32 if len(model.data.params) != 0:
33 raise InvalidInputError("Provided model is parametrised - simulation cannot be executed.")
34 if not model.data.all_rates:
35 raise RatesNotSpecifiedError("Some rules do not have rates specified - simulation cannot be executed.")
36
37 if eval(args.deterministic):
38 vm = model.data.to_vector_model()
39 df = vm.deterministic_simulation(args.max_time, args.volume, args.step)
40 else:
41 if eval(args.direct):
42 df = model.data.network_free_simulation(args.max_time)
43 else:
44 vm = model.data.to_vector_model()
45 df = vm.stochastic_simulation(args.max_time, args.runs)
46
47 df.to_csv(args.output, index=None, header=True)
48 else:
49 if "error" in model.data:
50 raise UnspecifiedParsingError(model.data["error"])
51 raise ModelParsingError(model.data, model_str)