معرفی شرکت ها

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

توضیحات

An efficient algebraic model counter.

ویژگی	مقدار
سیستم عامل	-
نام فایل	aspmc-1.0.9
نام	aspmc
نسخه کتابخانه	1.0.9
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	R. Kiesel
ایمیل نویسنده	rafael.kiesel@tuwien.ac.at
آدرس صفحه اصلی	https://github.com/raki123/aspmc
آدرس اینترنتی	https://pypi.org/project/aspmc/
مجوز	MIT

# aspmc (Algebraic) answer set counter based on a treewidth-aware cycle-breaking for normal answer set programs. For usage on Linux you may also install this software as a pip package via ``` pip install aspmc ``` Documentation for usage as a python module is available [here](https://raki123.github.io/aspmc/). Examples for command line usage are available below. If you have any issues please contact us, or even better create an issue on GitHub. For academic usage cite * Eiter, T., Hecher, M., & Kiesel, R. (2021, September). Treewidth-Aware Cycle Breaking for Algebraic Answer Set Counting. In Proceedings of the International Conference on Principles of Knowledge Representation and Reasoning (Vol. 18, No. 1, pp. 269-279). ## Development setup For developement clone via ``` git clone --single-branch --branch=main git@github.com:raki123/aspmc.git ``` to avoid the download of the experimental results in branch `results`. We include a setup bash script `setup.sh` that should automatically perform all steps below that are required to run our code. (Except for providing the c2d and miniC2D binary.) ### Python * Python >= 3.6 All required modules are listed in `requirements.txt` and can be obtained by running ``` pip install -r requirements.txt ``` ### Tree Decompositions via flow-cutter We use [flow-cutter](https://github.com/kit-algo/flow-cutter-pace17) to obtain treedecompositions that are needed for our treedecomposition guided clark completion, obtaining treewidth upperbounds on the programs, variable order generation and more. It is included as a git submodule. The submodules can be obtained by running ``` git submodule update --init ``` flow-cutter further needs to be compiled via ``` cd aspmc/external/flow-cutter/ bash build.sh ``` ### Knowledge Compilation via d4 or sharpSAT-TD We use [d4](https://github.com/raki123/d4) or [sharpSAT-TD](https://github.com/raki123/sharpsat-td) for knowledge compilation. Note that both of these are forks of the original model counters [here](https://github.com/crillab/d4) and [here](https://github.com/Laakeri/sharpsat-td/), respectively. For d4 we added support for smooth compilation and for sharpSAT-TD we used the nicely thought out addition by Tuukka Korhonen and Matti Järvisalo to enable weighted model counting over semirings in that we added a custom semiring to compile an sd-DNNF. Both are also included as a git submodules. The submodules can be obtained by running ``` git submodule update --init ``` They can then be compiled via ``` cd aspmc/external/sharpsat-td/ mkdir bin bash setupdev.sh cd ../../../ cd aspmc/external/d4/ make -j4 cd ../../../ ``` ## Optionally: c2d and miniC2D We also are able to use c2d to obtain d-DNNF representations. The c2d binary can be provided under `aspmc/external/c2d/bin/` as `c2d_linux` and can be downloaded from [here](http://reasoning.cs.ucla.edu/c2d/). The miniC2D binary (and the hgr2htree binary) can be provided under `aspmc/external/miniC2D/bin/linux/` as `miniC2D` (and `hgr2htree`) and can be downloaded from [here](http://reasoning.cs.ucla.edu/minic2d/). Note that they are only available for research use. ## Usage The basic usage is ``` python main.py [-m .] [-c] [-s .] [-n] [-t] [-ds .] [-dt .] [-k .] [-g .] [-h] [<INPUT-FILES>] --mode -m MODE set input mode to MODE: * asp : take a normal answer set program as input * problog : take a problog program as input * smproblog : take a problog program with negations as input * meuproblog : take a problog program with extra decision and utility atoms as input * mapproblog : take a problog program with extra evidence and map query atoms as input --count -c not only output the equivalent cnf as out.cnf but also performs (algebraic) counting of the answer sets --semiring -s SEMIRING use the semiring specified in the python file aspmc/semirings/SEMIRING.py only useful with -m problog --no_pp -n does not perform cycle breaking and outputs a normalized version of the input program as `out.lp` the result is equivalent, ground and does not contain annotated disjunctions. --treewidth -t print the treewidth of the resulting CNF --decos -ds SOLVER set the solver that computes tree decompositions to SOLVER: * flow-cutter : uses flow_cutter_pace17 (default) --decot -dt SECONDS set the timeout for computing tree decompositions to SECONDS (default: 1) --knowlege -k COMPILER set the knowledge compiler to COMPILER: * sharpsat-td : uses a compilation version of sharpsat-td (default) * d4 : uses the (slightly modified) d4 compiler. * c2d : uses the c2d compiler. * miniC2D : uses the miniC2D compiler. --guide_clark -g GUIDE set the tree decomposition type to use to guide the clark completion to GUIDE: * none : preform the normal clark completion without guidance * ors : guide for or nodes only * both : guide for both `and` and `or` nodes (default) --help -h print this help and exit ``` ### Examples These examples are for when the code is downloaded via GitHub. When using the pip package replace `python main.py` by `aspmc` to obtain the same result. #### ASP example: ``` python main.py -m asp -c -f a :- not b. b :- not a. ``` Reads the program from stdin and counts its models. ``` python main.py -m asp -c -f test/test_cycle.lp ``` Reads the same program from file and counts its models. #### problog example ``` python main.py -m problog -c -f 0.5::a. b :- a. query(b). ``` Evaluates the given simple program over the probability semiring. ``` python main.py -m problog -c -s maxplus -f 0.5::a. b :- a. query(b). ``` Evaluates the given simple program over the MaxPlus semiring.

نیازمندی

مقدار	نام
-	psutil
-	networkx
-	numpy
-	lark
-	clingo
-	matplotlib
-	dataclasses
-	sympy

زبان مورد نیاز

مقدار	نام
>=3.6, <4	Python

نحوه نصب

نصب پکیج whl aspmc-1.0.9:

pip install aspmc-1.0.9.whl

نصب پکیج tar.gz aspmc-1.0.9:

pip install aspmc-1.0.9.tar.gz