def load_data(sim_name, folder_name, dynamic_range_folder_includes, plot_settings):
sim_dir = 'save/{}'.format(sim_name)
attrs_list_each_food_num_all = []
attrs_list_each_food_num_critical = []
attrs_list_each_food_num_sub_critical = []
food_num_list = []
dir_list = all_folders_in_dir_with('{}/repeated_generations'.format(sim_dir), dynamic_range_folder_includes)
for dir in dir_list:
if plot_settings['compress_save_isings']:
isings_list = load_isings_specific_path_decompress(dir)
else:
isings_list = load_isings_specific_path(dir)
if plot_settings['only_copied']:
isings_list = [choose_copied_isings(isings) for isings in isings_list]
if plot_settings['attr'] == 'norm_avg_energy' or plot_settings['attr'] == 'norm_food_and_ts_avg_energy':
settings = load_settings(sim_name)
calc_normalized_fitness(isings_list, plot_settings, settings)
# MERGING INDIVIDUALS OF ALL REPEATS WITH SIMILAR SETTINGS INTO ONE LIST:
isings = make_2d_list_1d(isings_list)
# isings_populations_seperated = seperate_isolated_populations([isings])
# isings_critical = isings_populations_seperated[0][0]
# isings_sub_critical = isings_populations_seperated[1][0]
attrs_list_each_food_num_all.append(attribute_from_isings(isings, plot_settings['attr']))
# attrs_list_each_food_num_critical.append(attribute_from_isings(isings_critical, attr))
# attrs_list_each_food_num_sub_critical.append(attribute_from_isings(isings_sub_critical, attr))
food_num_list.append(get_int_end_of_str(dir))
return attrs_list_each_food_num_all, food_num_list
def load_from_dynamic_range_data_one_sim(sim_name, plot_settings):
dir = 'save/{}/repeated_generations'.format(sim_name)
dir_list = all_folders_in_dir_with(dir, plot_settings['include_name'])
# plot_settings['plot_varying_number']
if plot_settings['plot_largest_varying_number']:
# find largest varying number
plot_settings['plot_varying_number'] = np.max(
[get_int_end_of_str(dir) for dir in dir_list])
elif plot_settings['plot_original_varying_number']:
plot_settings['plot_varying_number'] = plot_settings[
'original_varying_number']
# Find dirs that shall be plotted
dirs_to_plot = []
for dir in dir_list:
if get_int_end_of_str(dir) == plot_settings['plot_varying_number']:
dirs_to_plot.append(dir)
if len(dirs_to_plot) > 1:
print(
'Found more than one simulation in repeated generation folder! Choos ing first detected!'
)
if len(dirs_to_plot) == 0:
print(
'Did not find varying number (time step) {} in {}. Skip plotting this'
.format(plot_settings['plot_varying_number'], sim_name))
return None
else:
# TODO: Change loading all isings in this path as soon as we have more than one ising for speed
if plot_settings['compress_save_isings']:
isings = load_isings_specific_path_decompress(dirs_to_plot[0])[0]
else:
isings = load_isings_specific_path(dirs_to_plot[0])[0]
if plot_settings['only_copied_isings']:
isings = choose_copied_isings(isings)
plot_ind_nums = np.random.randint(0,
len(isings) - 1,
plot_settings['number_individuals'])
return [isings[i] for i in plot_ind_nums]
