def update(timestamp, cu, ratios, rolling_pos, rolling_dev, channel_pos,
channel_dev, correlation):
# Update currency and ratios
a, b = get_universe_singular(currencies, granularity)
cu.loc[timestamp] = a
ratios.loc[timestamp] = b
# Update rolling based on new currencies
r_p, r_d = get_rolling(cu.tail(windows[-1] + 10), currencies, windows)
rolling_pos = rolling_pos.append(r_p.loc[r_p.timestamp == timestamp],
ignore_index=True)
rolling_dev = rolling_dev.append(r_d.loc[r_d.timestamp == timestamp],
ignore_index=True)
# Update Correlation ased on new currencies
c = get_correlation(cu.tail(windows[-1] + 10), currencies, windows)
correlation = correlation.append(c.loc[c.timestamp == timestamp],
ignore_index=True)
# Update channels based on new currencies
ch_p, ch_d = get_channels(cu.tail(windows[-1] + 10), currencies,
windows)
channel_pos = channel_pos.append(ch_p.loc[ch_p.timestamp == timestamp],
ignore_index=True)
channel_dev = channel_dev.append(ch_d.loc[ch_d.timestamp == timestamp],
ignore_index=True)
# Append csv Files for update
pd.DataFrame(cu.loc[pd.to_datetime(timestamp)]).T\
.to_csv('/Users/user/Desktop/test.csv',
mode='a', header=False, index=True)
pd.DataFrame(ratios.loc[pd.to_datetime(timestamp)]).T\
.to_csv('/Users/user/Desktop/test.csv',
mode='a', header=False, index=True)
rolling_pos.loc[rolling_pos.timestamp == timestamp]\
.to_csv(path + 'rolling_pos.csv', index=False,
header=False, mode='a')
rolling_dev.loc[rolling_dev.timestamp == timestamp]\
.to_csv(path + 'rolling_dev.csv', index=False,
header=False, mode='a')
channel_pos.loc[channel_pos.timestamp == timestamp]\
.to_csv(path + 'channel_pos.csv', index=False,
header=False, mode='a')
channel_dev.loc[channel_dev.timestamp == timestamp]\
.to_csv(path + 'channel_dev.csv', index=False,
header=False, mode='a')
correlation.loc[correlation.timestamp == timestamp]\
.to_csv(path + 'correlation.csv', index=False,
header=False, mode='a')
return {
'cu': cu,
'ratios': ratios,
'rolling_pos': rolling_pos,
'rolling_dev': rolling_dev,
'correlation': correlation,
'channel_pos': channel_pos,
'channel_dev': channel_dev
}
def update(timestamp):
# Update currency and ratios
a, b = get_universe_singular(currencies, granularity)
cu.loc[timestamp] = a
ratios.loc[timestamp] = b
# Update rolling based on new currencies
r = get_rolling(cu.tail(windows[-1] + 10), currencies, windows)
rolling.loc[timestamp] = r.loc[r.last_valid_index()]
# Update Correlation ased on new currencies
c = get_correlation(cu.tail(windows[-1] + 10), currencies, windows)
correlation.loc[timestamp] = c.loc[c.last_valid_index()]
# Update channels based on new currencies
ch = get_channels(cu.tail(windows[-1] + 10), currencies, windows)
channels.loc[timestamp] = ch.loc[ch.last_valid_index()]
# Export
cu.to_csv(path + 'currencies.csv')
ratios.to_csv(path + 'ratio.csv')
correlation.to_csv(path + 'correlation.csv')
rolling.to_csv(path + 'rolling.csv')
channels.to_csv(path + 'channels.csv')
###############################################################################
if 1:
cu.to_pickle(file)
timestamp = cu.loc[cu.last_valid_index(), 'timestamp']
# Look for new candle every _x_ seconds. Update all info when found
while True:
# Do we have new information ?
new_time = get_time(granularity)
if new_time > timestamp:
try:
sleep(2)
timestamp = new_time
print('Candle Found at:\t' + str(timestamp))
# Update ratios and cu with new data
a, b = get_universe_singular(currencies, granularity)
# Add line to cur
a['timestamp'] = timestamp
cu = cu.append(a, ignore_index=True, verify_integrity=True)
# Export currencies
cu.to_pickle(file)
# Print Data
print()
for k, v in sorted(a.items()):
print(v)
print()
# Print Spread
spreads = get_multiple_candles_spread(instrument_list,
granularity)
for k, v in sorted(spreads.items()):
print(v)
###############################################################################
if 1:
timestamp = get_time(granularities[0])
# Look for new candle every _x_ seconds. Update all info when found
while True:
# Do we have new information ?
new_time = get_time(update_granularity)
if new_time > timestamp:
timestamp = new_time
# Update ratios and cu with new data
a, b = get_universe_singular(currencies, update_granularity)
a['timestamp'] = timestamp
b['timestamp'] = timestamp
# Currencies
cu = pd.read_pickle(path + str(update_granularity) + '.pkl')
cu = cu.append(a, ignore_index=True, verify_integrity=True)
cu.to_pickle(path + str(update_granularity) + '.pkl')
# Ratios
rat = pd.read_pickle(ratios_path + str(update_granularity) +
'.pkl')
rat = rat.append(b, ignore_index=True, verify_integrity=True)
rat.to_pickle(ratios_path + str(update_granularity) + '.pkl')
# Print update
def update(timestamp, rolling_pos, rolling_dev, channel_pos,
channel_dev, correlation):
# Update currency and ratios
a, b = get_universe_singular(currencies, granularity)
cu.loc[timestamp] = a
ratios.loc[timestamp] = b
# Update rolling based on new currencies
r_p, r_d = get_rolling(cu.tail(windows[-1] + 10), currencies, windows)
rolling_pos = rolling_pos.append(r_p.loc[r_p.timestamp == timestamp],
ignore_index=True)
rolling_dev = rolling_dev.append(r_d.loc[r_d.timestamp == timestamp],
ignore_index=True)
# Update Correlation ased on new currencies
c = get_correlation(cu.tail(windows[-1] + 10), currencies, windows)
correlation = correlation.append(c.loc[c.timestamp == timestamp],
ignore_index=True)
# Update channels based on new currencies
ch_p, ch_d = get_channels(cu.tail(windows[-1] + 10), currencies, windows)
channel_pos = channel_pos.append(ch_p.loc[ch_p.timestamp == timestamp],
ignore_index=True)
channel_dev = channel_dev.append(ch_d.loc[ch_d.timestamp == timestamp],
ignore_index=True)
# Export cu and ratios
c = cu.stack().reset_index()
r = ratios.stack().reset_index()
c.columns = ['timestamp', 'currency', 'currency_values']
r.columns = ['timestamp', 'instrument', 'instrument_values']
c.to_csv(path + 'currencies.csv', index=False)
r.to_csv(path + 'ratios.csv', index=False)
# Export indicators
rolling_pos.to_csv(path + 'rolling_pos.csv', index=False)
rolling_dev.to_csv(path + 'rolling_dev.csv', index=False)
correlation.to_csv(path + 'correlation.csv', index=False)
channel_pos.to_csv(path + 'channel_pos.csv', index=False)
channel_dev.to_csv(path + 'channel_dev.csv', index=False)
# Export Differences
# rolling_pos_diff.to_csv(path + 'rolling_pos_diff.csv')
# rolling_dev_diff.to_csv(path + 'rolling_dev_diff.csv')
# channel_pos_diff.to_csv(path + 'channel_pos_diff.csv')
# channel_dev_diff.to_csv(path + 'channel_dev_diff.csv')
# # Get Differences
# rpd = get_diff(rolling_pos.tail(windows[-1] + 10), windows, instrument_list)
# rdd = get_diff(rolling_dev.tail(windows[-1] + 10), windows, instrument_list)
# cpd = get_diff(channel_pos.tail(windows[-1] + 10), windows, instrument_list)
# cdd = get_diff(channel_dev.tail(windows[-1] + 10), windows, instrument_list)
#
return {
'rolling_pos': rolling_pos,
'rolling_dev': rolling_dev,
'correlation': correlation,
'channel_pos': channel_pos,
'channel_dev': channel_dev
}