ce_update_vinv

pyoptex.doe.cost_optimal.codex.formulas.ce_update_vinv(Vinv, Zi, b, ratios)[source]

Computes the update to Vinv based on the iterative application of the required operations in b.

Parameters

Vinvnp.array(3d): The current inverses of the observation covariance matrix.
Zinp.array(1d): The current grouping matrix
blist(tuple(row_start, row_stop, group_from, group_to)): A list of operations to apply changing the groups of certain rows.
ratiosnp.array(1d): The variance ratios of this column.

Returns

Zinp.array(1d): The new grouping matrix (non-ascending)
Vinvnp.array(3d): The updated inverses observation covariance matrix.