@author: rich
'''
from data_loader import DataLoader
import datetime
from datetime import timedelta
from filedata_reader import FileDataReader
if __name__ == '__main__':
# get hostory and future data from coinbase at starttime
ticker = 'BTC-USD'
start_time_str = '2018-10-31 00:00:00.000000'
start_time = datetime.datetime.strptime(start_time_str,
'%Y-%m-%d %H:%M:%S.%f')
livetrade = False
data = DataLoader(ticker, start_time, livetrade)
end_time_str = '2018-10-31 04:30:00.000000'
end_time = datetime.datetime.strptime(end_time_str, '%Y-%m-%d %H:%M:%S.%f')
granularity = 60
history_df = data.getHistoryRange(start_time, end_time, granularity)
print('history', history_df.tail())
filedata = FileDataReader()
print(filedata.data.loc['2018-10-31'].head())
# all_data is read in as minute BTC OHLCV
# starts at 20150801 00:00:00 to close to real time
# run data gatherer to get data from eof till now-5H
# get 6 months at a time
#granularity = 21600 # in seconds; 86400 = 1 Day
#num_points = 728 #728 = 6 mos, w 6H int
granularity = 300 # in seconds; 86400 = 1 Day
num_points = 160000 # try to make it 180 days
duration = granularity * num_points
end_time = start_time + timedelta(seconds=duration)
range_df = all_data.getHistoryRange(start_time, end_time, granularity)
print('num points returned:', len(range_df))
# add time as a column outside of the index for the plotter
#print (range_df.head(20))
print('nan count:', range_df.isna().sum())
#plot = Plotter.showOHLCPlot(range_df)
target_df = pd.DataFrame(index=range_df.index)
target_df['target'] = 0
last_time = range_df.index[-1]
print('last time is:', last_time)
class TestPlotter(unittest.TestCase):
def setUp(self):
ticker = 'BTC-USD'
start_time_str = '2015-01-01 12:00:00.000000'
self.start_time = datetime.datetime.strptime(start_time_str, '%Y-%m-%d %H:%M:%S.%f')
live_data = False
self.data = DataLoader(ticker, self.start_time, live_data)
def tearDown(self):
pass
@unittest.skip("demonstrating skipping")
def testAllPlots(self):
print ("does this even run?")
return(True)
history = {}
history = self.data.getAllHistory(self.start_time)
for granularity in self.data.GRANULARITY:
df = history[granularity]
plot = Plotter.showPlot(df)
assert(True)
@unittest.skip("demonstrating skipping")
def testDayPlot(self):
granularity = 86400
end_time_str = '2016-01-01 12:00:00.000000'
end_time = datetime.datetime.strptime(end_time_str, '%Y-%m-%d %H:%M:%S.%f')
duration = granularity * 300
start_time = end_time - timedelta(seconds=duration)
range_df = self.data.getHistoryRange(start_time, end_time, granularity)
range_df['time'] = range_df.index
print (range_df.head(20))
plot = Plotter.showPlot(range_df)
assert(True)
def testFuturePercentPlot(self):
granularity = 43200
start_time_str = '2016-01-01 12:00:00.000000'
start_time = datetime.datetime.strptime(start_time_str, '%Y-%m-%d %H:%M:%S.%f')
duration = granularity * 60
end_time = start_time + timedelta(seconds=duration)
range_df = self.data.getHistoryRange(start_time, end_time, granularity)
# add time as a column outside of the index for the plotter
#print (range_df.head(20))
new_df = range_df.loc[:,['open']]
#plot = Plotter.showOHLCPlot(range_df)
base_price = new_df['open'].iloc[0]
new_df['open'] = ((new_df['open'] - base_price) / base_price) * 100
print ('base price is:', base_price)
new_df['target'] = 0
new_df.at['2016-01-20 00:00:00','target'] = 1
new_df.at['2016-01-21 00:00:00','target'] = 2
print ('new_df:', new_df.head(20))
plot2 = Plotter.showSinglePlot(new_df)
assert(True)
