def list_coins(self, dir):
ret = list()
for dirname, dirnames, filenames in os.walk(dir):
filenames.sort()
# print path to all subdirectories first.
for filename in filenames:
if (filename.endswith('.csv')):
path = os.path.join(dirname, filename)
name = filename[:-4]
c = Coin()
c.path = path
c.name = name
ret.append(c)
return ret
def test_increase_one_hour(self):
cointrain = CoinTrain()
#df=pd.DataFrame(index=['year', 'month','day','hour'],columns=[i],data=)
coin = Coin()
coin.path = "./data/altcoin-1hour/neo.csv"
coin.name = "neo"
coin.ico = "2017-12-31"
coin.read_from_storeage("prepare2")
gtdf = coin.gtdf
idx = gtdf.index
gtdf.index = idx.set_names(['year', 'month', 'day', 'hour'])
print(gtdf['sum_neumulfollower'].tail(27))
gtdf = cointrain.increase_by_one_hour(gtdf)
print(gtdf['sum_neumulfollower'].tail(27))
from coins.coininfo import CoinInfo
from coins.coinprice import CoinPrice
from twitter.statistics import Statistics
from twitter.tweetio import TweetIO
from twitter.sentiment import SentimentAnalyzer
from coins.coin import Coin
import pandas as pd
print('Main starts')
#cinfo=CoinInfo()
#coinlist=cinfo.list_coins('./data/altcoin-1hour')
## choosing first one: neo
#coin=coinlist[19]
coin = Coin()
coin.path = "./data/altcoin-1hour/ada.csv"
coin.name = "ada"
coin.ico = "2017-10-01"
#coin.ico="2016-02-17"
tweetio = TweetIO()
coin.read_from_storeage("prepare1")
print(coin.tweets.columns)
print(coin.retweets.columns)
df = tweetio.sort_and_clip(coin.tweets, coin.ico)
coin.tweets = df
## MULTIPLYING RETWEETS FOLLOWERS
print("multiplying nr. of retweet followers by sentiments.")
sentanalyzer = SentimentAnalyzer()
from datetime import datetime
print('Main starts searching for best model')
pd.set_option("display.max_rows", 100)
pd.set_option("display.max_columns", 100)
cinfo = CoinInfo()
#coinlist=cinfo.list_coins('./data/altcoin-1hour')
## choosing coin
coin = Coin()
#coin.path="./data/altcoin-1hour/neo.csv"
#coin.name="neo"
#coin.ico="2017-05-01"
coin.path = "./data/altcoin-1hour/omg.csv"
coin.name = "omg"
coin.ico = "2017-09-01"
starttime = datetime.now()
print(str(starttime))
coin.read_from_storeage("prepare2")
print(coin.pricehourly.head())
possibleraise = [1.5, 1.1]
possibledeclineratio = [-0.5, -0.667]
possibleoffset = [3, 4]
countphase = 0
for declineratio in possibledeclineratio:
from keras.layers import Dense, Dropout
from keras.layers import Embedding
from sklearn.model_selection import train_test_split
import keras.backend as K
print('Main starts plotting')
pd.set_option("display.max_rows", 100)
pd.set_option("display.max_columns", 100)
cinfo = CoinInfo()
#coinlist=cinfo.list_coins('./data/altcoin-1hour')
## choosing coin
coin = Coin()
coin.path = "./data/altcoin-1hour/neo.csv"
coin.name = "neo"
coin.ico = "2017-05-01"
tweetio = TweetIO()
coin.read_from_storeage("prepare2")
#print(coin.pricehourly.head())
cointrain = CoinTrain()
X = cointrain.create_buy_sig(coin, aimraise=10, declinelimit=-5, offset=12)
X_gtdf = cointrain.increase_by_one_hour(coin.gtdf)
X_grtdf = cointrain.increase_by_one_hour(coin.grtdf)
#Converting X to the same multi index type
times = pd.DatetimeIndex(X.index)
