def __evaluate_simulation_results(parameters, logdata_folder, graph_folder, generation_number, plot_name = None): assert logdata_folder, "Please specify where the logdata is located" data = empty_data_matrix(1) #ob_round_based = np.genfromtxt(logdata_folder + 'columnLog_roundBased_orderbook(0,0).csv', names=True, dtype=int, delimiter=',', usecols=(1,2)) #stock_round_based = np.genfromtxt(logdata_folder + 'columnLog_roundBased_stock0.csv', names=True, dtype=int, delimiter=',', usecols=(0,1)) trades = IO.load_trade_log_data(logdata_folder) fas = get_fundamental_after_shock() within_margin = get_number_of_rounds_within_stability_margin(trades['price'], trades['round'], fas) #data['n_simulation_rounds_within_stability_margin'] = within_margin['total_number_of_rounds'] #data['n_seperate_intervals_within_stability_margin'] = within_margin['n_intervals'] if 'longest_interval_within_margin' in data_for_failed_simulation.keys(): data['longest_interval_within_margin'] = within_margin['longest_interval'] if 'stdev' in data_for_failed_simulation.keys(): data['stdev'] = get_tp_std_after_entering_margin(trades['price'], trades['round']) if 'overshoot' in data_for_failed_simulation.keys(): data['overshoot'] = calculate_overshoot(fas, trades['price'], trades['round']) if 'time_to_reach_new_fundamental' in data_for_failed_simulation.keys(): data['time_to_reach_new_fundamental'] = get_first_round_to_reach_new_fundamental(trades['price'], trades['round']) if 'round_stable' in data_for_failed_simulation.keys(): data['round_stable'] = calculate_round_stable(trades['price'], trades['round'], fas) if np.random.random() <= PLOT_SAVE_PROB: data_id = 'gen%s_%s_%s'%(generation_number, get_epoch_time(), str(abs(hash(np.random.random())))) print graph_folder + data_id + '.npz' IO.save_tradeprice_data(trades['round'], trades['price'], data, parameters, graph_folder + data_id + '.npz') plotting.make_pretty_tradeprice_plot(trades['round'], trades['price'], graph_folder + data_id + '.png') #plotting.make_tradeprice_plot(trades['round'], trades['price'], data, parameters, graph_folder + data_id + '.png') else: data_id = None if not KEEP_SIMULATION_DATA: IO.delete_simulation_data(logdata_folder) return data, data_id
def evaluate_simulation_results(graph_folder, generation_number, parameters = {}, reps = [0], autorun = False, plot_name = None):
#print parameters
assert parameters, "Please specify a dictionary with par_name:par_value as key:value sets"
data = empty_data_matrix(len(reps))
saved_simulation_data_ids = list()
simulation_reps_to_run = []
random_path = str(randint(0, 2**64))
log_folders = IO.get_logfolders(parameters, reps, random_path)
for r in reps:
try:
assert IO.check_simulation_complete(log_folders[r]), "Could not calculate data because simulation in folder %s was not finished"%log_folders[r]
except AssertionError:
simulation_reps_to_run.append(r)
if simulation_reps_to_run: run_simulation(parameters, simulation_reps_to_run, random_path)
for r in reps:
data[r], data_id = __evaluate_simulation_results(parameters, log_folders[r], graph_folder, generation_number, plot_name)
if data_id: saved_simulation_data_ids.append(data_id)
return data, saved_simulation_data_ids