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,
]
