estimator.gb.gb_cost#
- estimator.gb.gb_cost(n, D, omega=2, prec=None)[source]#
Estimate the complexity of computing a Gröbner basis.
- Parameters:
n – Number of variables n > 0.
D – Tuple of (d,m) pairs where m is number polynomials and d is a degree.
omega – Linear algebra exponent, i.e. matrix-multiplication costs O(n^ω) operations.
prec – Compute power series up to this precision (default: 2n).
EXAMPLE:
>>> from estimator.gb import gb_cost >>> gb_cost(128, [(2, 256)]) rop: ≈2^144.6, dreg: 17, mem: ≈2^144.6