Metadata-Version: 2.1
Name: py-aiger-dfa
Version: 0.3.2
Summary: Library for moving between sequential circuits AIGs and DFAs.
Home-page: https://github.com/mvcisback/py-aiger-dfa
License: MIT
Author: Marcell Vazquez-Chanlatte
Author-email: mvc@linux.com
Requires-Python: >=3.9,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.9
Requires-Dist: attrs (>=21.0.0,<22.0.0)
Requires-Dist: bidict (>=0.21.0,<0.22.0)
Requires-Dist: dfa (>=2.0.0,<3.0.0)
Requires-Dist: funcy (>=1.12,<2.0)
Requires-Dist: py-aiger (>=6.0.0,<7.0.0)
Requires-Dist: py-aiger-bv (>=4.0.0,<5.0.0)
Requires-Dist: py-aiger-ptltl (>=3.0.0,<4.0.0)
Requires-Dist: pyrsistent (>=0.18,<0.19)
Project-URL: Repository, https://github.com/mvcisback/py-aiger-dfa
Description-Content-Type: text/markdown

# py-aiger-dfa
Python library for converting between AIG circuits and DFAs.

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<!-- markdown-toc start - Don't edit this section. Run M-x markdown-toc-generate-toc again -->
**Table of Contents**

- [Installation](#installation)
- [Usage](#usage)
    - [DFA to AIG](#dfa-to-aig)
    - [AIG to DFA](#aig-to-dfa)

<!-- markdown-toc end -->


# Installation

If you just need to use `aiger_dfa`, you can just run:

`$ pip install py-aiger-dfa`

For developers, note that this project uses the
[poetry](https://poetry.eustace.io/) python package/dependency
management tool. Please familarize yourself with it and then
run:

`$ poetry install`

# Usage

The main entry points for using this library are the `dfa2aig` and
`aig2dfa` functions. DFAs are represented using the
[dfa](https://github.com/mvcisback/dfa) package. Familiarity with the
`dfa`, `py-aiger`, and `py-aiger-bv` packages is assumed.


## DFA to AIG

An example of going from a `DFA` to an `AIG` object
is shown below.

```python
from dfa import DFA
from aiger_dfa import dfa2aig

my_dfa = DFA(
    start=0,
    inputs={0, 1},
    label=lambda s: (s % 4) == 3,
    transition=lambda s, c: (s + c) % 4,
)
my_aig, relabels, valid = dfa2aig(my_dfa)
```

Now `circ` is an `AIG` and `relabels` is a mapping from the inputs,
states, and outputs of `my_dfa` to their **1-hot** encoded
counterparts in `my_aig`.

`relabels` has the following schema:

```python
relabels = {
    'inputs': .. , #  Mapping from input alphabet -> py-aiger input.
    'outputs': .. , # Mapping from py-aiger output -> output alphabet.
    'states': .. , # Mapping from state space -> py-aiger latches.
}
```

Finally, `valid` is another aiger circuit which tests if all inputs
are 1-hot encoded.

## AIG to DFA

We also support converting a sequential circuit (AIG) to a [Moore
Machine](https://en.wikipedia.org/wiki/Moore_machine) (DFA) using
`aig2dfa`. Using the same example:

```python
from aiger_dfa import aig2dfa

my_dfa2 = aig2dfa(my_aig, relabels=relabels)
```

Note that the output of a sequential circuit (AIG) is dependent on the
state **AND** the action (a [Mealy
Machine](https://en.wikipedia.org/wiki/Mealy_machine)). 

We use the standard Mealy ↦ Moore reduction where one introduces a
1-step delay on the output. The default initial output is `None`, but
can be set using the `initial_label` argument.

