pyeda 0.15.0

Python Electronic Design Automation

PyEDA is a Python library for electronic design automation.

Read the docs!

Features

• Symbolic Boolean algebra with a selection of function representations:

  • Logic expressions

  • Truth tables, with three output states (0, 1, “don’t care”)

  • Reduced, ordered binary decision diagrams (ROBDDs)

  • Fast, disjunctive/conjunctive normal form logic expressions

• SAT solvers:

  • Backtracking

  • DPLL

  • PicoSAT

• Formal equivalence

• Multi-dimensional bit vectors

• DIMACS CNF/SAT parsers

• Logic expression parser

Download

Bleeding edge code:

$ git clone git://github.com/cjdrake/pyeda.git

For release tarballs and zipfiles, visit PyEDA’s page at the Cheese Shop.

Installation

Latest released version using setuptools:

$ easy_install pyeda

Latest release version using pip:

$ pip install pyeda

Installation from the repository:

$ python setup.py install

Getting Started With Logic Expressions

Invoke your favorite Python terminal, and invoke an interactive pyeda session:

>>> from pyeda.inter import *

Create some Boolean expression variables:

>>> a, b, c, d = map(exprvar, "abcd")

Construct Boolean functions using overloaded Python operators: - (NOT), + (OR), * (AND), >> (IMPLIES):

>>> f0 = -a * b + c * -d
>>> f1 = a >> b
>>> f2 = -a * b + a * -b
>>> f3 = -a * -b + a * b
>>> f4 = -a * -b * -c + a * b * c
>>> f5 = a * b + -a * c

Construct Boolean functions using standard function syntax:

>>> f10 = Or(And(Not(a), b), And(c, Not(d)))
>>> f11 = Implies(a, b)
>>> f12 = Xor(a, b)
>>> f13 = Xnor(a, b)
>>> f14 = Equal(a, b, c)
>>> f15 = ITE(a, b, c)

Construct Boolean functions using higher order operators:

>>> f20 = Nor(a, b, c)
>>> f21 = Nand(a, b, c)
>>> f22 = OneHot(a, b, c)
>>> f23 = OneHot0(a, b, c)

Investigate a function’s properties:

>>> f0.support
frozenset([a, b, c, d])
>>> f0.inputs
(a, b, c, d)
>>> f0.top
a
>>> f0.degree
4
>>> f0.cardinality
16
>>> f0.depth
2

Factor complex expressions into only OR/AND and literals:

>>> f11.factor()
a' + b
>>> f12.factor()
a' * b + a * b'
>>> f13.factor()
a' * b' + a * b
>>> f14.factor()
a' * b' * c' + a * b * c
>>> f15.factor()
a * b + a' * c

Restrict a function’s input variables to fixed values, and perform function composition:

>>> f0.restrict({a: 0, c: 1})
b + d'
>>> f0.compose({a: c, b: -d})
c' * d' + c * d'

Test function formal equivalence:

>>> f2.equivalent(f12)
True
>>> f4.equivalent(f14)
True

Investigate Boolean identities:

# Law of double complement
>>> --a
a

# Idempotent laws
>>> a + a
a
>>> a * a
a

# Identity laws
>>> a + 0
a
>>> a * 1
a

# Dominance laws
>>> a + 1
1
>>> a * 0
0

# Commutative laws
>>> (a + b).equivalent(b + a)
True
>>> (a * b).equivalent(b * a)
True

# Associative laws
>>> a + (b + c)
a + b + c
>>> a * (b * c)
a * b * c

# Distributive laws
>>> (a + (b * c)).to_cnf()
(a + b) * (a + c)
>>> (a * (b + c)).to_dnf()
a * b + a * c

# De Morgan's laws
>>> Not(a + b).factor()
a' * b'
>>> Not(a * b).factor()
a' + b'

# Absorption laws
>>> (a + (a * b)).absorb()
a
>>> (a * (a + b)).absorb()
a

Perform Shannon expansions:

>>> a.expand(b)
a * b' + a * b
>>> (a * b).expand([c, d])
a * b * c' * d' + a * b * c' * d + a * b * c * d' + a * b * c * d

Convert a nested expression to disjunctive normal form:

>>> f = a * (b + (c * d))
>>> f.depth
3
>>> g = f.to_dnf()
>>> g
a * b + a * c * d
>>> g.depth
2
>>> f.equivalent(g)
True

Convert between disjunctive and conjunctive normal forms:

>>> f = -a * -b * c + -a * b * -c + a * -b * -c + a * b * c
>>> g = f.to_cnf()
>>> h = g.to_dnf()
>>> g
(a + b + c) * (a + b' + c') * (a' + b + c') * (a' + b' + c)
>>> h
a' * b' * c + a' * b * c' + a * b' * c' + a * b * c

Getting Started With Multi-Dimensional Bit Vectors

Create some four-bit vectors, and use slice operators:

>>> A = bitvec('A', 4)
>>> B = bitvec('B', 4)
>>> A
[A[0], A[1], A[2], A[3]]
>>> A[2:]
[A[2], A[3]]
>>> A[-3:-1]
[A[1], A[2]]

Perform bitwise operations using Python overloaded operators: ~ (NOT), | (OR), & (AND), ^ (XOR):

>>> ~A
[A[0]', A[1]', A[2]', A[3]']
>>> A | B
[A[0] + B[0], A[1] + B[1], A[2] + B[2], A[3] + B[3]]
>>> A & B
[A[0] * B[0], A[1] * B[1], A[2] * B[2], A[3] * B[3]]
>>> A ^ B
[Xor(A[0], B[0]), Xor(A[1], B[1]), Xor(A[2], B[2]), Xor(A[3], B[3])]

Reduce bit vectors using unary OR, AND, XOR:

>>> A.uor()
A[0] + A[1] + A[2] + A[3]
>>> A.uand()
A[0] * A[1] * A[2] * A[3]
>>> A.uxor()
Xor(A[0], A[1], A[2], A[3])

Create and test functions that implement non-trivial logic such as arithmetic:

>>> from pyeda.logic.addition import *
>>> S, C = ripple_carry_add(A, B)
# Note "1110" is LSB first. This says: "7 + 1 = 8".
>>> S.vrestrict({A: "1110", B: "1000"}).to_uint()
8

Other Function Representations

Consult the documentation for information on normal form expressions, truth tables, and binary decision diagrams. Each function representation has different trade-offs, so always use the right one for the job.

Execute Unit Test Suite

If you have Nose installed, run the unit test suite with the following command:

$ make test

If you have Coverage installed, generate a coverage report (including HTML) with the following command:

$ make cover

Perform Static Lint Checks

If you have Pylint installed, perform static lint checks with the following command:

$ make lint

Build the Documentation

If you have Sphinx installed, build the HTML documentation with the following command:

$ make html

Python Versions Supported

PyEDA is developed using Python 3.2+. It is NOT compatible with Python 2.7.

Contact the Authors

• Chris Drake (cjdrake AT gmail DOT com), http://cjdrake.blogspot.com