def load_names(type, string_to_token): path = dmtools.get_data_path() + "names/" path += type + "_names.txt" data = [] with open(path, "rb") as f: for line in f: data += [START_TOKEN] + tokenify(line.strip(), string_to_token) + [END_TOKEN] return data
def load_tokens(type): path = dmtools.get_data_path() + "names/" path += type + "_tokens.txt" string_to_token = {">": END_TOKEN, "<": START_TOKEN} token_to_string = {END_TOKEN: ">", START_TOKEN: "<"} with open(path, "rb") as f: for i, line in enumerate(f): string_to_token[line.strip()] = i token_to_string[i] = line.strip() return string_to_token, token_to_string
def generate(water_level=0.15, seed=6, show_france=True): data_path = dmtools.get_data_path() generate_coastline(data_path, water_level, show_france, seed) generate_elevation(data_path, seed) generate_temperature(data_path) generate_wind(data_path, seed) generate_moisture(data_path) generate_biomes(data_path) generate_history(data_path) render_image(data_path)
def generate_notes(moral_alignment, law_alignment): data_path = dmtools.get_data_path() with open(data_path + "npcs/appearance.txt") as f: appearance = random.choice(f.readlines()).strip() with open(data_path + "npcs/mannerisms.txt") as f: mannerism = random.choice(f.readlines()).strip() with open(data_path + "npcs/interaction.txt") as f: interaction = random.choice(f.readlines()).strip() with open(data_path + "npcs/abilities.txt") as f: abilities = f.readlines() ability1 = random.choice(abilities) abilities.remove(ability1) ability1 = ability1.strip() ability2 = random.choice(abilities).strip() with open(data_path + "npcs/talents.txt") as f: talent = random.choice(f.readlines()).strip() with open(data_path + "npcs/ideals_" + alignment_to_string[moral_alignment] + ".txt") as f: moral_ideal = random.choice(f.readlines()).strip() with open(data_path + "npcs/ideals_" + alignment_to_string[law_alignment] + ".txt") as f: law_ideal = random.choice(f.readlines()).strip() with open(data_path + "npcs/bonds.txt") as f: bond = random.choice(f.readlines()).strip() with open(data_path + "npcs/flaws.txt") as f: flaw = random.choice(f.readlines()).strip() return [ appearance, mannerism, interaction, ability1, ability2, talent, "Ideals: " + moral_ideal + ", " + law_ideal.lower(), "Bond: " + bond, "Flaw: " + flaw, ]