carbatpy.utils.optimize

Scripts for the evaluation of the results of the fluid search, e.g. finding

pareto optimal compositions.

Created on Sun Feb 4 17:38:19 2024

@author: atakan part of carbatpy

Attributes

FILENAME_ACT

Functions

pareto(filename, objectives)

Compute the Pareto (non-dominated) set from the data stored in filename

Module Contents

carbatpy.utils.optimize.pareto(filename, objectives)[source]

Compute the Pareto (non-dominated) set from the data stored in filename

Parameters:

  • filename (string) – directory/file of the csv-file to analyze. The column names will be used to find the objectives.

  • objectives (list of strings, length [2, number_of_objectives]) – the first list in the list are the column names to search for optima. the second list indicates for each optimization, whether a “max” or “min” is searched. Here “diff” can be in a column to indicate a column with categories, which are analyzed separately.

Returns:

results – with the whole pandas dataFrame (key:”all_values”) and a list of booleans if True, this line of the set is pareto optimal (key:”optimal_mask”). Also, the “objectives” are returned.

Return type:

dictionary

carbatpy.utils.optimize.FILENAME_ACT = 'C:\\Users\\atakan\\sciebo\\Python\\carbatpy\\tests\\test_files\\test_data_ProEthPenBut'[source]