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README.md

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### Clone the repo
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```
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git clone --recurse-submodules git@github.com:meelgroup/bn-counting.git
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git clone --recurse-submodules https://github.com/meelgroup/bn-counting.git
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```
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### Dependencies
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```
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## Run ApproxASP
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## Run
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First cd to script: `cd script`
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### Running first task
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### Running first task: C-MTS-1 and C-FIX-1
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`Input`:
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- `Boolean Network`: a Boolean network (.bnet file)
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```
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it should print the count in line: `C-FIX-1:`
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### Running second task
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### Running second task: C-MTS-2 and C-FIX-2
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`Input`:
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- `Boolean network`: a Boolean network (.bnet file)
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- `phenotype`: a phenotype, we specify it in a file. You can see example in file `phen_244.txt`
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```
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it should print the count in line: `C-FIX-2:`
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### Running third task
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### Running third task: C-MTS-3 and C-FIX-3
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`Input`:
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- `Boolean network`: a Boolean network (.bnet file)
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- `phenotype`: a phenotype, we specify it in a file. You can see example in file `phen_244.txt`
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it should print the count in line: `C-FIX-3:`
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## Preprocessing BNs
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We used [tsconj](https://github.com/daemontus/tsconj) and [fASP](https://github.com/giang-trinh/fASP) to process BNs to ASP program, for minimal trap space and fixed points, respectively. The original implementation is modified for our usage.
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We used [tsconj](https://github.com/daemontus/tsconj) and [fASP](https://github.com/giang-trinh/fASP) to encode BNs to ASP program, for minimal trap space and fixed points, respectively. The original implementation is modified for our usage.
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## Benchmark:

build.sh

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cd "$ROOT_DIR/ApproxASP"
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mkdir -p build && cd build
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cmake -DCLINGO_BUILD_SHARED=ON ..
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make -j12
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make -j$(nproc)
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cp approxasp "$ROOT_DIR/script"
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echo "Done. Copied binaries to:"

script/helper.py

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def run(cmd, timeout, ttl = 3, silent = False):
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proc = sp.Popen([cmd], stdout=sp.PIPE, stderr=sp.PIPE, shell=True)
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proc = sp.Popen([cmd], stdout=sp.PIPE, stderr=sp.PIPE, check=True, text=True)
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# print(cmd)
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try:
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(out, err) = proc.communicate(timeout = int(timeout * 1.1) + 1)

script/run_fixed_point.py

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# First, prepare ASP programs for all "normal" networks without any special requirements.
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file_path = "t1_244.bnet"
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def preprocess_bn(bn_path):
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# preprocess BN

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