def select_seasons(current_english_season, seasons):
"""
Takes the current english season, and a list of seasons available.
Returns a list of seasons selected.
"""
print("\nSeason select")
options = [
"Load current season", "Load all seasons", "Load selected seasons",
"Exit"
]
selection = c.general_menu(options)
if selection == "Load current season":
return [c.get_season_key(current_english_season)]
elif selection == "Load all seasons":
return list(seasons.keys())
elif selection == "Load selected seasons":
selected_seasons = c.multi_pick(list(seasons.keys()))
"""seasons_to_return = []
for sel in selected_seasons:
seasons_to_return.append(seasons[sel])
return seasons_to_return"""
return selected_seasons
elif selection == "Exit":
return "exit"
def generate_predictions(prediction_type, prediction_method):
c.predictions_df = predictive_methods[prediction_type][prediction_method](
c.fixtures)
if type(c.predictions_df) == str:
print("\nNo games were found that met the search requirements")
else:
c.predictions_df["Date"] = pd.to_datetime(c.predictions_df["Date"],
dayfirst=True)
date_range = (c.predictions_df["Date"].min().strftime("%d-%m-%Y") +
" - " +
c.predictions_df["Date"].max().strftime("%d-%m-%Y"))
predictions_file = (prediction_type + " - " + prediction_method +
" - predictions - " + date_range + ".csv")
if ((not os.path.exists(c.unprocessed_predictions_dir +
predictions_file))
and (not os.path.exists(c.old_preprocessed_predictions_dir +
predictions_file))):
print("Would you like to export this to a csv file?")
ans = c.general_menu(["Yes", "No"])
if ans == "Yes":
c.predictions_df.to_csv(c.unprocessed_predictions_dir +
predictions_file)
print("done")
else:
print("These predictions have already been saved.")
print(
"They are in either the unprocessed_predictions or the preprocessed_predictions folder.\n"
)
def display_results():
print("\n Display Results")
selection = c.general_menu([
"Last 1 game", "Last x games", "All results for current season",
"All resulst for defined seasons", "Back"
])
if selection == "Last 1 game":
results_last_1_game()
elif selection == "Last x games":
results_last_x_games()
elif selection == "All results for current season":
results_season()
elif selection == "All results for defined seasons":
results_defined_seasons()
elif selection == "Back":
return
def generate_predictions():
print("\nGenerate Predictions")
print("\nSelect a prediction type.")
prediction_type = c.general_menu(list(pf.predictive_methods.keys()))
print("\nSelect a predictive method.")
prediction_methods = c.multi_pick(
list(pf.predictive_methods[prediction_type].keys()), [])
for prediction_method in prediction_methods:
#TESTING DEBUG
print("\nGenerating predictions for type: ", prediction_type,
"method: ", prediction_method)
#END OF TESTING DEBUG
#Take the selected type and method and pass it to a function to run the
#method and create a scv file.
pf.generate_predictions(prediction_type, prediction_method)
def display_fixtures():
print("\nDisplay Fixtures")
selection = c.general_menu([
"Display all upcoming fixtures", "Display fixtures for specific teams",
"Back"
])
if selection == "Display all upcoming fixtures":
print("\nDisplay all upcoming fixtures")
c.display_fixtures()
elif selection == "Display fixtures for specific teams":
print("\nDisplay fixtures for specific teams")
print("\nSelect teams")
teams = c.multi_pick(c.fixture_team_list)
c.display_fixtures(teams=teams)
return
elif selection == "Back":
return
def main_menu():
while True:
print("\nMain Menu")
selection = c.general_menu([
"Display results", "Display fixtures",
"Generate next game predictions", "Display predictions",
"Prediction analysis options", "Back"
])
if selection == "Display results":
display_results()
elif selection == "Display fixtures":
display_fixtures()
elif selection == "Generate next game predictions":
generate_predictions()
elif selection == "Display predictions":
display_predictions()
elif selection == "Prediction analysis options":
analysis()
elif selection == "Back":
return
def analysis():
print("\nPrediction Analysis Options")
selection = c.general_menu([
"Process prediction files", "Test a predictive function",
"Review tested predictive methods"
])
if selection == "Process prediction files":
files = []
for a, b, filename in os.walk(c.unprocessed_predictions_dir):
files.append(filename)
if len(files) < 1:
print("There are no unprocessed prediction files")
else:
print("\nSelect files to process")
selected_files = c.multi_pick(files[0], [])
#files[0] is the list of files
pa.process_prediction_files(selected_files)
elif selection == "Test a predictive function":
print("\nSelect a prediction type:")
prediction_type = c.general_menu(list(pf.predictive_methods.keys()))
print("\nSelect predictive methods:")
prediction_methods = c.multi_pick(
list(pf.predictive_methods[prediction_type].keys()), [])
predictive_functions = []
for prediction_method in prediction_methods:
predictive_functions.append(
pf.predictive_methods[prediction_type][prediction_method])
print("\nSelect leagues:")
#Empty lists below for no selected items to prevent a bug where an item
#from a previous list is somehow added to the selected items.
leagues = c.multi_pick(list(c.leagues.keys()), [])
print("\nSelect seasons")
#Only allow the selection of seasons where all leagues are available
available_seasons = []
for season in list(c.loaded_seasons.keys()):
if season in c.seasons_with_all_leagues:
available_seasons.append(season)
seasons = c.multi_pick(available_seasons, [])
#Get list of league codes rather than names
league_codes = []
for l in leagues:
league_codes.append(c.leagues[l])
#Get list of season codes rather than names
season_codes = []
for s in seasons:
season_codes.append(c.loaded_seasons[s])
for predictive_function in predictive_functions:
pa.win_draw_test_method(predictive_function,
leagues=league_codes,
seasons=season_codes)
elif selection == "Review tested predictive methods":
pass