carbatpy.utils.run_screening_evaluation

Run script to evaluate the fluid screening, together with the compressor model

which are stored in two csv-files. First they are sorted then concatenated. Afterwards, the Paeroto optimal values are selected, plotted and stored.

Created on Mon Feb 12 17:01:22 2024

@author: atakan

Attributes

RUN_NO

f_add

directory

filename1

pareto_file

f_name

filename2

data_screen

keys

fl_all

fl_col

data

eval_dat

keys2

eval_sorted

all_keys

combined_data

what_act

SUCCESS

objectives_act

Module Contents

carbatpy.utils.run_screening_evaluation.RUN_NO = 1[source]
carbatpy.utils.run_screening_evaluation.f_add = '-sort-rlt-4val'[source]
carbatpy.utils.run_screening_evaluation.directory = 'C:\\Users\\atakan\\sciebo\\results\\optimal_hp_fluid\\fluid_select_restricted\\2024-02-12-16-55-...[source]
carbatpy.utils.run_screening_evaluation.filename1 = 'C:\\Users\\atakan\\sciebo\\results\\optimal_hp_fluid\\fluid_select_restricted\\2024-02-12-16-55-...[source]
carbatpy.utils.run_screening_evaluation.pareto_file[source]
carbatpy.utils.run_screening_evaluation.f_name[source]
carbatpy.utils.run_screening_evaluation.filename2 = 'C:\\Users\\atakan\\sciebo\\results\\optimal_hp_fluid\\fluid_select_restricted\\2024-02-12-16-55-...[source]
carbatpy.utils.run_screening_evaluation.data_screen = None[source]
carbatpy.utils.run_screening_evaluation.keys[source]
carbatpy.utils.run_screening_evaluation.fl_all[source]
carbatpy.utils.run_screening_evaluation.fl_col = [][source]
carbatpy.utils.run_screening_evaluation.data[source]
carbatpy.utils.run_screening_evaluation.eval_dat = None[source]
carbatpy.utils.run_screening_evaluation.keys2[source]
carbatpy.utils.run_screening_evaluation.eval_sorted[source]
carbatpy.utils.run_screening_evaluation.all_keys[source]
carbatpy.utils.run_screening_evaluation.combined_data = None[source]
carbatpy.utils.run_screening_evaluation.what_act[source]
carbatpy.utils.run_screening_evaluation.SUCCESS = False[source]
carbatpy.utils.run_screening_evaluation.objectives_act = ['T_glide_h', 'eff_sec_law_r_lowT', 'spec_Volume_sup', 'p_ratio'][source]