lmlib.utils.beta.mpoly_fit_subspace1#

lmlib.utils.beta.mpoly_fit_subspace1(betas, beta_expo, boundaries, coords, coord_expos, H=None, return_cost=False)#

Fits a multivariate polynomial to polynomial subspace with corresponding coordinates

Parameters
  • betas (array_like of shape (N, Q, ...)) – polynomial coefficients

  • beta_expo (array_like of shape (Q,)) – exponent vector of beta

  • boundaries (array_like of shape (2,)) – integral boundaries (lower, upper)

  • coords (array_like of shape (N, M)) – coordinates of shape (M,) for each beta in betas

  • coord_expos (tuple of shape (M,) of 1D- array_like) – exponent vector for each variable in coordinates

  • H (None, array_like, optional) – output exponent reduction matrix ( max limit )

  • return_cost (bool, optional) – returns additionally the cost for each sample

Returns

  • alphas (array_like) – coefficients of multivariate polynomial fit

  • cost (array_like, optional) – Cost if flag return_cost = True