`pygsti.baseobjs.opcalc.slowopcalc`

Python implementations of common polynomial operations

Module Contents

`abs_sum_bulk_eval_compact_polynomials_complex`(vtape, ...)	Equivalent to np.sum(np.abs(bulk_eval_compact_polynomials_complex(.)))
`compact_deriv`(vtape, ctape, wrt_params)	Take the derivative of one or more compact Polynomials with respect
`float_product`(ar)

`bulk_eval_compact_polynomials_real`
`bulk_eval_compact_polynomials_complex`
`bulk_eval_compact_polynomials_derivs_real`
`bulk_eval_compact_polynomials_derivs_complex`

pygsti.baseobjs.opcalc.slowopcalc.bulk_eval_compact_polynomials_derivs_real

pygsti.baseobjs.opcalc.slowopcalc.bulk_eval_compact_polynomials_derivs_complex

pygsti.baseobjs.opcalc.slowopcalc.abs_sum_bulk_eval_compact_polynomials_complex(vtape, ctape, paramvec, dest_size, **kwargs): Equivalent to np.sum(np.abs(bulk_eval_compact_polynomials_complex(.)))

pygsti.baseobjs.opcalc.slowopcalc.compact_deriv(vtape, ctape, wrt_params)

Take the derivative of one or more compact Polynomials with respect to one or more variables/parameters.

vtape, ctapenumpy.ndarray: Specifies “variable” and “coefficient” 1D numpy arrays to differentiate. These “tapes” can be generated by concatenating the tapes of individual complact-polynomial tuples returned by Polynomial.compact().
wrt_paramslist: The variable indices to differentiate with respect to. They must be sorted in ascending order. E.g. “[0,3]” means separatey differentiate w.r.t x_0 and x_3 (concatenated first by wrt_param then by poly).

vtape, ctape : numpy.ndarray