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estimator.gb.gb_cost

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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
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