- runs all the experiments when considering the disjunction of multiple hypothesis nodes
- generates a csv file that contains information about the inference time for both storm and ace depending on the number of the hypothesis nodes and a plot that visualizes the results
- takes one boolean argument (optional)
- 'true': rerun the experiments, parse the results and plot them (if not set, the existing results will be plotted)
- command to run the script: python3 run_disjunction_experiments.py [true] ([] indicates that the argument is optional)
RUN declare-afolders=("ace_storm_comparison""auxiliary_scripts""bn-mc-transformer""feasibility_analysis""parameter_space_partitioning""psdd_storm_comparison""sensitivity_analysis""storm_evidence")
RUN for f in"${folders[@]}";do mv f /storm_bn/ done
1) Build the target (in ./bn-mc-transformer/build/bin)
mkdir build && cd build && cmake .. && make
For more instructions, check out the documentation found in [Getting Started](http://www.stormchecker.org/getting-started.html).
Benchmarks
----------------------------
Example input files for Storm can be obtained from
https://github.com/moves-rwth/storm-examples.
Various Benchmarks together with example invocations of Storm can be found at the [Quantitative Verification Benchmark Set (QVBS)](http://qcomp.org/benchmarks).
Further examples and benchmarks can be found in the following repositories:
std::stringfolder="/home/hans/Desktop/Storm-bn/bn-mc-transformer/src/storm-bn-robin/TheBestTopologicalOrderings/evidence_tailored/1/";//directory with the bif and jani files
std::cin>>networkName;//name of the network for which the jani file needs to be generated
boolisTailored=true;//indicates whether the transformation is evidence-tailored (if set to true) or agnostic (if set to false)
- runs the experiments using psdd and storm for the networks 'andes' and 'win95pts' and outputs a table containing for each pair of method and network the corresponding construction and inference time
- takes one boolean argument (optional)
- 'true': rerun the experiments, parse the results and output them (if not set, the existing results will be parsed)
- command to run the script: python3 run_psdd_storm_comparison.py [true] ([] indicates that the argument is optional)