def music_function(instrument, mode):
learner = Learn(mode)
learner.loadFromFile()
song = learner.getSong(getStartSequence())
midiPath = getPath(MIDI_BASE_PATH, '.mid')
toMidi(song, midiPath, instrument)
mp3Path = getPath(MP3_BASE_PATH, '.mp3')
generateMP3(midiPath, mp3Path, FONT_PATH)
return mp3Path
def main(_=0, unsupervised=False):
from learn import Learn
endtime = 128
data = Learn().build_with_User_table_for_prog(slicer=endtime)
print(len(data[0]))
data = [(line[0], line[1],
Wisard.retinify([
float(t) - float(t0) + 10
for t, t0 in zip(line[3:endtime], line[2:endtime])
])) for line in data]
print(
"Tabela gerada por rede neural sem peso para derivada segunda do tempo com prognóstico da carla"
)
# bleacher = dict(V=805, S=-6, E=81, F=154)
# 83.36 16.64 v:2165, s:11, f:667, e:422, b:970, a:734, d:10
bleacher = dict(V=1202, S=-15, E=59, F=165) # 199321270259550360019
# bleacher = dict(V=1615, S=-15, E=42, F=169) # 199321270259550360019
# bleacher = dict(V=2531, S=169, E=634, F=856)
# w = Wisard(data, 32 * endtime, bleach=913, mapper=bleacher, enf=609, sup=18, unsupervised=unsupervised)
w = Wisard(data,
32 * endtime,
bleach=913,
mapper=bleacher,
enf=600,
sup=10,
unsupervised=unsupervised)
# bleacher = dict(V=893, S=-304, E=-48, F=25)
# w = Wisard(data, 32 * endtime, bleach=995, mapper=bleacher, enf=452, sup=39, unsupervised=unsupervised)
# bleacher = dict(V=603, S=0, E=81, F=154)
# w = Wisard(data, 32 * endtime, bleach=600, mapper=bleacher, enf=110, sup=20)
w.main()
print(len(data[0][2:]))
print(w.single())
"""
def init(self):
self.colorlib = self.madcow.colorlib
try:
self.learn = Learn(madcow=madcow)
except:
self.learn = None
self.google = Google()
def __init__(self, master=None):
Application_ui.__init__(self, master)
self.logger = MyLogger(log_board=self.log_board,
filename='all.log',
level='debug')
self.learn = Learn(self.logger)
self.t1 = None
def gmain(ch="216501166744497073410"):
from learn import Learn
endtime = 128
data = Learn().build_with_User_table_for_prog(slicer=endtime)
print(len(data[0]))
data = [(line[0], line[1],
Wisard.retinify([
float(t) - float(t0) + 10
for t, t0 in zip(line[3:endtime], line[2:endtime])
])) for line in data]
print(
"Tabela gerada por rede neural sem peso para derivada segunda do tempo com prognóstico da carla"
)
# bleacher = dict(V=805, S=-6, E=81, F=154)
# bleacher = dict(V=1485, S=-359, E=34, F=139) 199321270259550360019
v, s, f, e, b, a, d =\
int(ch[:4]), int(ch[4:7]), int(ch[7:10]), int(ch[10:13]), 0, 600, 10
bleacher = dict(V=v, S=s, E=e, F=f)
w = Wisard(data, 32 * endtime, bleach=b, mapper=bleacher, enf=a, sup=d)
# bleacher = dict(V=893, S=-304, E=-48, F=25)
# w = Wisard(data, 32 * endtime, bleach=995, mapper=bleacher, enf=452, sup=39, unsupervised=unsupervised)
# bleacher = dict(V=603, S=0, E=81, F=154)
# w = Wisard(data, 32 * endtime, bleach=600, mapper=bleacher, enf=110, sup=20)
w.main()
print(len(data[0][2:]))
def __init__(self, tier, room, bot):
self.learn = Learn(room)
self.opponent = {}
self.generation = "generation 6"
self.bot = bot
self.weather = ""
self.statuses = []
self.opponent_pokemon_team = []
self.do_not_switch = False
self.ws = self.bot.ws
self.team = None
self.strongest_move = ""
self.active = ""
self.id = ""
self.tier = tier
self.room = room
self.turn = 0
def init(self):
try:
self.default_location = settings.YELP_DEFAULT_LOCATION
except:
self.default_location = DEFAULT_LOCATION
try:
self.learn = Learn(madcow=self.madcow)
except:
self.learn = None
def run(self):
try:
Learn(files=self.files, update_file=self.file, top=self.top)
except:
traceback.print_exc()
exctype, value = sys.exc_info()[:2]
self.signals.error.emit((exctype, value, traceback.format_exc()))
else:
self.signals.result.emit(None)
finally:
self.signals.finished.emit(True)
def init(self):
opts = {}
for key, default in self.defaults.iteritems():
setting = 'WUNDERGROUND_' + key.upper()
val = getattr(settings, setting, None)
if val is None:
val = default
opts[key] = val
self.api = WeatherUnderground(log=self.madcow.log, **opts)
self.learn = Learn(madcow=self.madcow)
self.method_triggers = [(getattr(self.api, method_name), triggers, pws)
for method_name, triggers, pws in self._method_triggers]
def open_app(app_name, cells, audio, arduino):
current_app = None
app_name = app_name.replace(" ", "")
if app_name == 'riddles':
current_app = Riddles("Riddles", cells, audio, arduino)
elif app_name == 'learn':
current_app = Learn("Learn", cells, audio, arduino)
elif app_name == 'tutor':
current_app = Tutor("Tutor", cells, audio, arduino)
elif app_name == 'headlines':
current_app = Headlines("Headlines", cells, audio, arduino)
elif app_name == 'memory':
current_app = Memory("Memory", cells, audio, arduino)
if current_app is not None:
audio.speak("Opening the application " + app_name)
current_app.on_start()
else:
audio.speak(
"I did not recognize the app. Could you try to open the app again?"
)
def open_app(self, app_name):
current_app = None
app_name = app_name.replace(" ", "")
if app_name == 'riddles':
current_app = Riddles("Riddles")
elif app_name == 'learn':
current_app = Learn("Learn")
elif app_name == 'tutor':
current_app = Tutor("Tutor")
elif app_name == 'headlines':
current_app = Headlines("Headlines")
elif app_name == 'memory':
current_app = Memory("Memory")
if current_app is not None:
glob.mainApp.audio.speak("Opening the application")
glob.mainApp.audio.speak(current_app.name)
current_app.on_start()
else: # shouldn't occur
glob.mainApp.audio.speak(
"I did not recognize the app. Could you try to open the app again?"
)
def init(self):
colorlib = self.madcow.colorlib
self.weather = Weather(colorlib, self.log)
self.learn = Learn(madcow=self.madcow)
import sys from learn import Learn finance_path = 'financetweets.txt' finance_count = '1000' finance_cate = 'finance' finance_args = ['bayes.py', 'learn', finance_cate, finance_path, finance_count] finance_mode = Learn() finance_mode.validate(finance_args) finance_mode.execute() sports_path = 'sportstweets.txt' sports_count = '1000' sports_cate = 'sports' sports_args = ['bayes.py', 'learn', sports_cate, sports_path, sports_count] #['bayes.py', 'learn', 'sports', 'sportstweets.txt', '1000'] sports_mode = Learn() sports_mode.validate(sports_args) sports_mode.execute()
def __init__(self, **kwargs):
Learn.__init__(self, **kwargs)
self.algo = RandomForestClassifier()
def init(self):
self.learn = Learn(madcow=self.madcow)
self.staff = Staff(madcow=self.madcow)
def __init__(self, **kwargs):
Learn.__init__(self, **kwargs)
self.algo = SVC();
def __init__(self, madcow):
self.learn = Learn(madcow)
self.config = madcow.config
class Battle:
pokedex = json.loads(open(os.path.join(os.path.dirname(__file__), "./data/pokedex.json"), "r").read())
pokedex_moves = json.loads(open(os.path.join(os.path.dirname(__file__), "./data/pokedex_moves.json"), "r").read())
pokedex_effectiveness = json.loads(open(os.path.join(os.path.dirname(__file__), "./data/pokedex_effectiveness.json"), "r").read())
teams_for_battle = json.loads(open(os.path.join(os.path.dirname(__file__), "./data/pokemon_teams.json"), "r").read())
moves_that_switch = ["uturn", "voltswitch"]
status_moves = [{"name":"spore", "type":"grass","effect":"sleep"}]
status_moves_names = ["spore"]
def __init__(self, tier, room, bot):
self.learn = Learn(room)
self.opponent = {}
self.generation = "generation 6"
self.bot = bot
self.weather = ""
self.statuses = []
self.opponent_pokemon_team = []
self.do_not_switch = False
self.ws = self.bot.ws
self.team = None
self.strongest_move = ""
self.active = ""
self.id = ""
self.tier = tier
self.room = room
self.turn = 0
def __repr__(self):
return "<Battle: room:{}>".format(self.room)
def __str__(self):
return "<Battle: room:{}>".format(self.room)
def run(self, messages):
try:
if messages[1] == "turn":
return getattr(self, "decide")()
else:
return getattr(self, re.sub(r'[^A-z0-9]', '', messages[1]))(messages)
except (TypeError, AttributeError):
pass
def start(self, message):
self.ws.send("{}|Good Luck, Have Fun".format(self.room))
self.ws.send("{}|/timer")
def turn(self, message):
self.decide()
def weather(self, message):
self.weather = message[2].lower()
# cheesy lines
if self.weather == "hail":
self.ws.send("{}|Oh, it's hailing. It's ok though, because the cold never bothered me anyway.".format(self.room))
elif self.weather == "sandstorm":
pokemon = message[4].split(": ")[1].lower()
self.ws.send("{}|Darude Sandstorm?".format(self.room, pokemon))
elif self.weather == "raindance":
self.ws.send("{}|Shouldn't it be raining men now?".format(self.room))
else:
pass
def move(self, message):
if self.id == "p1":
_id = "p2a"
else:
_id = "p1a"
if _id in message[2]:
move = message[3].replace("-", "").replace(" ", "").lower()
self.learn.write(self.opponent["name"], move)
def update_pokemon_move(self, move, pokemon):
pokemon_move = {}
if "hiddenpower" in move:
pokemon_move["name"] = move[:-2]
pokemon_move["power"] = 60
pokemon_move["type"] = move.split("hiddenpower")[1][:-2]
else:
pokemon_move["name"] = move
pokemon_move["power"] = self.pokedex_moves[move]["power"]
pokemon_move["type"] = self.pokedex_moves[move]["type"]
if move == "return":
pokemon_move["power"] = 102
if move in ["eruption", "waterspout"]:
pokemon_move["power"] = 150 * float(pokemon["hp"])
return pokemon_move
def update_pokemon_team(self, pokemon_team):
json_data = json.loads(pokemon_team)["side"]["pokemon"]
team = []
i = 0
for pokemon in json_data:
pkmn = {}
pkmn["id"] = i + 1
pkmn["name"] = re.sub(r'[^A-z0-9]', '', json_data[i]["ident"].split(": ")[1]).lower()
pkmn["moves"] = json_data[i]["moves"]
pkmn["stats"] = json_data[i]["stats"]
pkmn["active"] = json_data[i]["active"]
pkmn["ability"] = json_data[i]["baseAbility"]
pkmn["type"] = [x.lower() for x in self.pokedex[pkmn["name"]]["types"]]
pkmn["hp"] = json_data[i]["condition"]
if " " in pkmn["hp"]: # condition
pkmn["status"] = pkmn["hp"].split(" ")[1]
pkmn["hp"] = pkmn["hp"].split(" ")[0]
if "/" in pkmn["hp"]: # fraction
pkmn["hp"] = float(Fraction(int(pkmn["hp"].split("/")[0]), int(pkmn["hp"].split("/")[1])))
team.append(pkmn)
i += 1
self.team = team
return team
def teampreview(self, message = None):
self.ws.send("{}|/team {}|1".format(self.room, random.randint(1, 6)))
def player(self, message):
if len(message) > 2:
if self.bot.username == message[3]:
self.id = message[2]
else:
if message[2] == "p1":
self.id = "p2"
else:
self.id = "p1"
def request(self, message):
self.team = self.update_pokemon_team(message[2])
self.id = json.loads(message[2])["side"]["id"]
if "random" in self.tier:
self.teampreview()
def faint(self, message):
if self.id in message[2]:
pokemon = message[2].split(": ")[1].lower()
if len([x for x in self.team if x["name"] == pokemon]) > 0:
self.active["hp"] = 0
self.switch_pokemon()
def switch(self, message):
if self.id == "p1":
_id = "2a"
else:
_id = "1a"
if _id in message[2]:
opponent = re.sub(r'[^A-z0-9]', '', message[3].split(",")[0]).lower()
print("opponent is "+opponent)
self.opponent["hp"] = float(Fraction(int(message[4].split("/")[0]), int(message[4].split("/")[1])))
self.opponent["name"] = opponent
self.do_not_switch = False
def win(self, message):
self.ws.send("{}|Good Game.".format(self.room))
self.ws.send("{}|/part".format(self.room))
def damage(self, message):
pokemon = message[2].split(": ")[1].lower()
if pokemon == self.opponent["name"] and "/" in message[3] and " " not in message[3]:
self.opponent["hp"] = float(Fraction(int(message[3].split("/")[0]), int(message[3].split("/")[1])))
def lose(self, message):
self.win(message)
def tie(self, message):
self.win(message)
def moves_power(self, pokemon = None):
pokemon_moves = []
if pokemon is None:
pokemon = self.active
moves = self.active["moves"]
else:
moves = pokemon["moves"]
pokemon = pokemon
for move in moves:
move = self.update_pokemon_move(move, pokemon)
move["power"] = self.ability_of_pokemon_modifies_power_of_pokemon_move(pokemon, move)
if "multihit" in list(self.pokedex_moves[move["name"]].keys()):
move["power"] *= median(self.pokedex_moves[move["name"]]["multihit"])
pokemon_moves.append(move)
moves_power = []
for move in pokemon_moves:
modifier = self.pokemon_move_modifier(pokemon, move)
moves_power.append({"name": move["name"], "power": move["power"] * modifier, "pokemon": pokemon["name"]})
return moves_power
def pokemon_move_modifier(self, pokemon, pokemon_move):
modifier = 1
if pokemon_move["type"] in pokemon["type"]:
if pokemon["ability"] == "adaptability":
modifier = 2
else:
modifier = 1.5
if self.calculate_effectiveness()["weak"].count(pokemon_move["type"]) == 2:
modifier *= 4
elif self.calculate_effectiveness()["weak"].count(pokemon_move["type"]) == 1:
modifier *= 2
if self.calculate_effectiveness()["resist"].count(pokemon_move["type"]) == 2:
modifier *= 0.25
elif self.calculate_effectiveness()["resist"].count(pokemon_move["type"]) == 1:
modifier *= 0.5
if pokemon_move["type"] in self.calculate_effectiveness()["immune"]:
if pokemon["ability"] == "scrappy" and pokemon_move["type"] in ["fighting", "normal"]:
return modifier
else:
return 0
if pokemon["ability"] in ["teravolt", "moldbreaker"]:
return modifier
opponent_pokemon = [x.lower().replace(" ", "") for x in self.pokedex[self.opponent["name"]]["abilities"]]
if pokemon_move["type"] == "water" and "waterabsorb" in opponent_pokemon:
return 0
elif pokemon_move["type"] == "grass" and "sapsipper" in opponent_pokemon:
return 0
elif pokemon_move["type"] == "fire" and "flashfire" in opponent_pokemon:
return 0
elif pokemon_move["type"] == "electric" and "voltabsorb" in opponent_pokemon:
return 0
elif pokemon_move["type"] == "ground" and "levitate" in opponent_pokemon:
return 0
else:
return modifier
def ability_of_pokemon_modifies_power_of_pokemon_move(self, pokemon, pokemon_move):
ability = pokemon["ability"]
if ability == "aerilate" and pokemon_move["type"] == "normal":
pokemon_move["type"] == "flying"
if ability in ["blaze", "overgrow", "torrent", "swarm"] and float(pokemon["hp"]) <= 0.33:
i = {"blaze": "fire", "overgrow": "grass", "torrent": "water", "swarm": "bug"}
if i[ability] == pokemon_move["type"]:
pokemon_move["power"] *= 1.5
if ability == "darkaura" and pokemon_move["type"] == "dark":
pokemon_move["power"] *= 1.33
if ability == "fairyaura" and pokemon_move["type"] == "fairy":
pokemon_move["power"] *= 1.33
# One Punch Man
if ability == "ironfist" and "punch_move" in list(self.pokedex_moves[pokemon_move["name"]].keys()):
pokemon_move["power"] *= 1.2
if ability == "megalauncher" and "pulse_move" in list(self.pokedex_moves[pokemon_move["name"]].keys()):
pokemon_move["power"] *= 1.5
if ability == "reckless" and "recoil" in list(self.pokedex_moves[pokemon_move["name"]].keys()):
pokemon_move["power"] *= 1.2
if ability == "sandforce" and self.weather == "sandstorm" and pokemon_move["type"] in ["rock", "ground", "steel"]:
pokemon_move["power"] *= 1.3
if ability == "sheerforce" and "secondary_effect" in list(self.pokedex_moves[pokemon_move["name"]].keys()):
pokemon_move["power"] *= 1.3
if ability == "strongjaw" and "bite_move" in list(self.pokedex_moves[pokemon_move["name"]].keys()):
pokemon_move["power"] *= 1.5
if ability == "technician" and pokemon_move["power"] <= 60:
pokemon_move["power"] *= 1.5
if ability == "tintedlens":
opponent_pkmn_resistant_against = self.calculate_effectiveness(self.opponent["name"])["resist"]
if pokemon_move["type"] in opponent_pkmn_resistant_against:
pokemon_move["power"] *= 2
if ability == "toughclaws" and "contact_move" in list(self.pokedex_moves[pokemon_move["name"]].keys()):
pokemon_move["power"] *= 1.3
return pokemon_move["power"]
def switch_pokemon(self):
strongest_moves = [sorted(self.moves_power(pkmn), key=lambda x: x["power"])[::-1][0] for pkmn in self.team if pkmn["active"] != True]
strongest_move_index = strongest_moves.index(sorted(strongest_moves, key=lambda x: x["power"])[::-1][0])
strongest_move = sorted(strongest_moves, key=lambda x: x["power"])[::-1][0]
strongest_pokemon = [x for x in self.team if x["name"] == strongest_move["pokemon"]][0]
strongest_pokemon_id = strongest_pokemon["id"]
current_pokemon_id = 1
strongest_pokemon_index = self.team.index(strongest_pokemon)
current_pokemon_index = self.team.index([i for i in self.team if i["active"] == True][0])
self.team[current_pokemon_index]["id"] = strongest_pokemon_id
self.team[strongest_pokemon_index]["id"] = 1
opponent_pkmn_type = [x.lower() for x in self.pokedex[self.opponent["name"]]["types"]]
weak_against = self.calculate_effectiveness(strongest_pokemon["name"])["weak"]
if len([i for i in weak_against if i in opponent_pkmn_type]) > 0:
self.do_not_switch = True
self.ws.send("{}|/switch {}".format(self.room, strongest_pokemon_id))
def calculate_effectiveness(self, pkmn = None):
effectiveness = {"weak": [], "resist": [], "immune": []}
if pkmn is not None:
pokemon_type = [x.lower() for x in Battle.pokedex[pkmn]["types"]]
else:
pokemon_type = [x.lower() for x in Battle.pokedex[self.opponent["name"]]["types"]]
for pkmn_type in pokemon_type:
effectiveness["weak"].append(Battle.pokedex_effectiveness[pkmn_type]["weak_against"])
effectiveness["resist"].append(Battle.pokedex_effectiveness[pkmn_type]["resistant_against"])
effectiveness["immune"].append(Battle.pokedex_effectiveness[pkmn_type]["immune_against"])
for x in effectiveness:
effectiveness[x] = sorted([z for x in effectiveness[x] for z in x]) # flatten the array
for x in [z for z in effectiveness["weak"] if z in effectiveness["resist"]]:
effectiveness["weak"].remove(x)
effectiveness["resist"].remove(x)
return effectiveness
def can_use_status_move(self):
opponent_pkmn_type = self.pokedex[self.opponent["name"]]["types"]
moves = self.active["moves"]
def decide(self):
self.active = [i for i in self.team if i["active"] == True][0]
opponent_pkmn_type = [x.lower() for x in self.pokedex[self.opponent["name"]]["types"]]
weak_against = self.calculate_effectiveness(self.active["name"])["weak"]
if len([i for i in weak_against if i in opponent_pkmn_type]) > 0 and self.do_not_switch == False: # current pokemon is 2x or 4x weak against opponent.
return self.switch_pokemon()
if self.active["hp"] == "0 fnt":
self.do_not_switch = False
return self.switch_pokemon()
moves_that_heal = [i for i in list(self.pokedex_moves.keys()) if self.pokedex_moves[i].get("heal_move")]
if self.active["hp"] < 0.25 and len([i for i in self.active["moves"] if i in moves_that_heal]) > 0:
move_that_heals = [i for i in self.active["moves"] if i in moves_that_heal][0]
return self.ws.send("{}|/move {}".format(self.room, move_that_heals))
data = sorted(self.moves_power(), key=lambda x: x["power"])[::-1]
self.strongest_move = data[0]
if self.strongest_move["power"] == 0 or self.strongest_move["name"] in self.moves_that_switch:
return self.switch_pokemon()
if len([x for x in self.active["moves"] if x in self.status_moves_names]) > 0:
_move = [x for x in self.active["moves"] if x in self.status_moves_names][0]
move = [x for x in self.status_moves if x["name"] == _move][0]
if move["effect"] not in self.statuses:
self.statuses.append(move["effect"])
return self.ws.send("{}|/move {}".format(self.room, move["name"]))
return self.ws.send("{}|/move {}".format(self.room, data[0]["name"]))
def __init__(self, **kwargs):
Learn.__init__(self, **kwargs)
self.algo = KNeighborsClassifier()
def train_function(mode):
learner = Learn(mode)
learner.train()
learner.saveToFile()
return server()
def init(self):
self.learn = Learn(madcow=self.madcow)
self.staff = Staff(madcow=self.madcow)
self.company = Company(madcow=self.madcow)
self.realname = Realname(madcow=self.madcow)
self.notes = Notes(madcow=self.madcow)
def __init__(self, madcow=None):
self.weather = Weather()
try:
self.learn = Learn(madcow=madcow)
except:
self.learn = None
def __init__(self, **kwargs):
Learn.__init__(self, **kwargs)
self.algo = AdaBoostClassifier(DecisionTreeClassifier(max_depth = 1))
def __init__(self, **kwargs):
Learn.__init__(self, **kwargs)
self.algo = DecisionTreeClassifier()
def init(self):
self.colorlib = self.madcow.colorlib
try:
self.learn = Learn(madcow=self.madcow)
except:
self.learn = None
def __init__(self, madcow):
self.learn = Learn(madcow)
def __init__(self, **kwargs):
Learn.__init__(self, **kwargs)
self.algo =MLPClassifier()
import numpy as np
from learn import Learn
data = np.array([[1, 2], [2, 4], [3, 6], [4, 8], [5, 10], [6, 12], [7, 14],
[8, 16], [9, 18], [10, 20], [23, 46], [54, 108], [77, 154],
[18, 36], [25, 50], [16, 32], [63, 126], [41, 82], [33, 66],
[45, 90], [88, 176], [64, 128], [54, 108], [98, 196],
[14, 28], [34, 68]])
X, y = data[:, :-1], data[:, -1]
test = [85, 17, 457, 991, 13, 68, 19, 85, 36, 1568, 997]
Learn.play(X, y, test)
def __init__(self, args): self.mode = Learn() self.mode.validate(args) self.mode.execute()
def init(self):
self.learn = Learn(self.madcow)
from learn import Learn, Classification
import argparse
import curses
#the only extra argument is "learn" which is used to train the svm
parser = argparse.ArgumentParser(description='Recognize who is typing')
parser.add_argument('--learn',
help='teach the algorithm to recognize the user',
action='store_true')
args = parser.parse_args()
stdscr = curses.initscr()
#need to know the name of the user for predictive purposes
if args.learn:
Learn(stdscr)
else:
Classification(stdscr)
def set_parameters(self, parameters):
for key, value in parameters.iteritems():
setattr(self.algo, key, value)
Learn.set_parameters(self, parameters)
# Scheduler
scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau(optimizer,
mode='min',
factor=0.5,
patience=20,
verbose=False,
threshold=0.0001,
threshold_mode='rel',
cooldown=0,
min_lr=1e-07,
eps=1e-08)
# Learning class
learn = Learn(args,
train_loader=train_loader,
validate_loader=valid_loader,
test_loader=test_loader,
train_set=train_set,
validate_set=valid_set,
test_set=test_set)
# %%
# -----------------------------------------------------------
#
# Losses functions
#
# -----------------------------------------------------------
print('[Creating criterion]')
# Losses
if args.model in ['ae', 'vae', 'wae', 'vae-flow']:
criterion = nn.MSELoss()
if args.num_classes > 1:
class CateBuilder(object): def __init__(self, args): self.mode = Learn() self.mode.validate(args) self.mode.execute()
def __init__(self, **kwargs):
Learn.__init__(self, **kwargs)
self.algo = GradientBoostingClassifier()
from learn import Learn
from decimal import *
from re import findall
learn_path = "./new_train"
learn = Learn(learn_path)
# print(learn.number_of_bad_words, learn.number_of_good_words)
module = learn.number_of_good_words + learn.number_of_bad_words
probably_of_good_examp=Decimal(learn.number_of_good_example / learn.number_of_examles)
probably_of_bad_examp=Decimal(learn.number_of_bad_example / learn.number_of_examles)
CONST_OF_IMPORTANT=3
def probability_b(word):
bad, good = 0, 0
try:
good = learn.good[word]
bad = learn.bad[word]
except:
pass
numb = bad+good
if numb <= CONST_OF_IMPORTANT:
return Decimal(0.5)
return Decimal(bad/numb)
def probability_g(word):
bad, good = 0, 0
try:
good = learn.good[word]
bad = learn.bad[word]
def main():
Game = GameClass()
Svs = Learn(100000)
Game.Play(Svs)
