osier.utils

Functions

apply_slack(pareto_front, slack[, sense])	This function applies a specified slack value to a given Pareto front.
check_if_interior(points, par_front, slack_front)	Checks if a point or set of points is inside the N-polytope created by the Pareto front and the slack front (a.k.a the near-optimal front).
distance_matrix(X[, metric])	This function calculates the distance matrix for an MxN matrix and returns the symmetrical square form of the matrix.
farthest_first(X, D, n_points[, start_idx, seed])	This function identifies the farthest first traversal order for an MxN matrix and returns an array of indices (ordered by the distance).
get_dispatchable_names(technology_list)	Returns a list of osier.Technology name strings where dispatchable is True.
get_dispatchable_techs(technology_list)	Returns a list of osier.Technology objects where dispatchable is True.
get_nondispatchable_techs(technology_list)	Returns a list of osier.Technology objects where dispatchable is False.
get_nonstorage_techs(technology_list)	Returns a list of osier.Technology objects that do not have the attribute storage_level.
get_objective_names(res_obj)	This function returns a list of named objectives based on the names of the functions passed to Osier.
get_storage_techs(technology_list)	Returns a list of osier.Technology objects that have the attribute storage_level.
get_tech_names(technology_list)	Returns the a list of osier.Technology name strings.
n_mga(results_obj[, n_points, slack, sense, ...])	N-dimensional modeling-to-generate-alternatives (n-mga) allows users to efficiently search decision space by relaxing the objective function(s) by a specified amount of slack.
synchronize_units(tech_list, unit_power, ...)	This function ensures that all objects in the technology list have units consistent with the model's units.
technology_dataframe(technology_list[, ...])	Returns a pandas.DataFrame with a complete set of data for a given technology list.