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Hi, I was checking the project and was very hyped for the solver. Good job on the programming!! I'm just having trouble to understand the parameters for the sbc. could u provide any better info how to setup the input?
Sorry for my english.
The text was updated successfully, but these errors were encountered:
First in main.py, I set the name of my club after downloading the club.csv using the chrome extension. After that in preprocess_data_2, I comment/uncomment the appropriate filters. You can even add custom filters like excluding certain players. Some of the filters are necessary, especially the ones on cost != '-- NA --' and loan_players.
Currently the inputs are set to solve this SBC. The main constraints are in optimize.py (L552-588) and the inputs for each constraint are in input.py. So you will have to plug in the inputs for the SBC first in input.py and enable the appropriate constraint by uncommenting the line in optimize.py. Comment out the constraints not required for the SBC.
For this SBC, I've done the following.
3. (a) In input.py, set Formation = 4-2-2-2 and USE_ALTERNATE_POSITIONS = True. There are no duplicates in my dataset. If duplicates were to be prioritized, set any one of the 3 options True and then uncomment model = prioritize_duplicates(df, model, player) in optimize.py.
(b) NUM_UNIQUE_LEAGUE = [4, "Exactly"] # Leagues: Max / Min / Exactly X and then enable model = create_unique_league_constraint(df, model, player, league, map_idx, players_grouped, num_cnts). This handles Leagues: Exactly 4. Similar logic will apply to the requirement Nationalities: Exactly 5.
(c) MAX_NUM_LEAGUE = 4 # Same League Count: Max X and then enable model = create_max_league_constraint(df, model, player, map_idx, players_grouped, num_cnts). This handles Same League Count: Max 4 and the same logic will apply for the requirement Same Nation Count: Max 3.
(d) SQUAD_RATING = 80 # Squad Rating: Min XX and then enable model = create_squad_rating_constraint_3(df, model, player, map_idx, players_grouped, num_cnts) in optimize.py.
(e) CHEMISTRY = 25 # Squad Total Chemistry Points: Min X. If there are no requirements on chemistry, simply set this to 0.
You can refer to the comments under each function to know which input maps to which constraint. Thanks for using the repo, let me know if you have any more questions or if there is a particular SBC you want to solve 🙏 .
Hi, I was checking the project and was very hyped for the solver. Good job on the programming!! I'm just having trouble to understand the parameters for the sbc. could u provide any better info how to setup the input?
Sorry for my english.
The text was updated successfully, but these errors were encountered: