Python Electronic Design Automation
Project description
PyEDA is a Python library for electronic design automation.
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)
SAT solvers:
Backtracking
DPLL
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
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), ^ (XOR), & (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() Or(~a, b) >>> f12.factor() Or(And(~a, b), And(a, ~b)) >>> f13.factor() Or(And(~a, ~b), And(a, b)) >>> f14.factor() Or(And(~a, ~b, ~c), And(a, b, c)) >>> f15.factor() Or(And(a, b), And(~a, c))
Restrict a function’s input variables to fixed values, and perform function composition:
>>> f0.restrict({a: 0, c: 1}) Or(b, ~d) >>> f0.compose({a: c, b: ~d}) Or(And(~c, ~d), And(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) Or(a, b, c) >>> a & (b & c) And(a, b, c) # Distributive laws >>> (a | (b & c)).to_cnf() And(Or(a, b), Or(a, c)) >>> (a & (b | c)).to_dnf() Or(And(a, b), And(a, c)) # De Morgan's laws >>> Not(a | b).factor() And(~a, ~b) >>> Not(a & b).factor() Or(~a, ~b) # Absorption laws >>> (a | (a & b)).absorb() a >>> (a & (a | b)).absorb() a
Perform Shannon expansions:
>>> a.expand(b) Or(And(a, ~b), And(a, b)) >>> (a & b).expand([c, d]) Or(And(a, b, ~c, ~d), And(a, b, ~c, d), And(a, b, c, ~d), And(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 Or(And(a, b), And(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 And(Or(a, b, c), Or(a, ~b, ~c), Or(~a, b, ~c), Or(~a, ~b, c)) >>> h Or(And(~a, ~b, c), And(~a, b, ~c), And(a, ~b, ~c), And(a, b, c))
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 [Or(A[0], B[0]), Or(A[1], B[1]), Or(A[2], B[2]), Or(A[3], B[3])] >>> A & B [And(A[0], B[0]), And(A[1], B[1]), And(A[2], B[2]), And(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() Or(A[0], A[1], A[2], A[3]) >>> A.uxor() Xor(A[0], A[1], A[2], A[3]) >>> A.uand() And(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 about truth tables, and binary decision diagrams. Each function representation has different trade-offs, so always use the right one for the job.
PicoSAT SAT Solver C Extension
PyEDA includes an extension to the industrial-strength PicoSAT SAT solving engine.
Use the satisfy_one method to finding a single satisfying input point:
>>> f = OneHot(a, b, c) >>> f.satisfy_one() {a: 0, b: 0, c: 1}
Use the satisfy_all method to iterate through all satisfying input points:
>>> list(f.satisfy_all()) [{a: 0, b: 0, c: 1}, {a: 0, b: 1, c: 0}, {a: 1, b: 0, c: 0}]
For more interesting examples, see the following documentation chapters:
Espresso Logic Minimization C Extension
PyEDA includes an extension to the famous Espresso library for the minimization of two-level covers of Boolean functions.
Use the espresso_exprs function to minimize multiple expressions:
>>> f1 = ~a & ~b & ~c | ~a & ~b & c | a & ~b & c | a & b & c | a & b & ~c >>> f2 = ~a & ~b & c | a & ~b & c >>> f1m, f2m = espresso_exprs(f1, f2) >>> f1m Or(And(~a, ~b), And(a, b), And(~b, c)) >>> f2m And(~b, c)
Use the espresso_tts function to minimize multiple truth tables:
>>> X = bitvec('x', 4) >>> f1 = truthtable(X, "0000011111------") >>> f2 = truthtable(X, "0001111100------") >>> f1m, f2m = espresso_tts(f) >>> f1m Or(x[3], And(x[0], x[2]), And(x[1], x[2])) >>> f2m Or(x[2], And(x[0], x[1]))
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.
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