adelorenzo/stable
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

ensure user defined timerange truncates final backtest so that we arent mismatching data lengths upon return to strategy. Rename DataHandler class to FreqaiDataKitchen

Browse Source
This commit is contained in:
robcaulk 2022-05-06 12:54:49 +02:00
parent 66715c5ba4
commit 00ff0c9b91
2 changed files with 22 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

24
freqtrade/freqai/data_handler.py → freqtrade/freqai/data_kitchen.py
View File

@ -22,7 +22,7 @@ SECONDS_IN_DAY = 86400
logger = logging.getLogger(__name__)
class DataHandler:
class FreqaiDataKitchen:
"""
Class designed to handle all the data for the IFreqaiModel class model.
Functionalities include holding, saving, loading, and analyzing the data.
@ -291,32 +291,48 @@ class DataHandler:
bt_period = bt_split * SECONDS_IN_DAY
full_timerange = TimeRange.parse_timerange(tr)
config_timerange = TimeRange.parse_timerange(self.config["timerange"])
timerange_train = copy.deepcopy(full_timerange)
timerange_backtest = copy.deepcopy(full_timerange)
tr_training_list = []
tr_backtesting_list = []
first = True
# within_config_timerange = True
while True:
if not first:
timerange_train.startts = timerange_train.startts + bt_period
timerange_train.stopts = timerange_train.startts + train_period
# if a full training period doesnt fit, we stop
if timerange_train.stopts > full_timerange.stopts:
break
# make sure we finish with a full backtest
# if timerange_train.stopts > config_timerange.stopts - bt_period:
# within_config_timerange = False
# timerange_train.stopts = config_timerange.stopts - bt_period
# # if a full training period doesnt fit, we stop
# if timerange_train.stopts > full_timerange.stopts:
# break
first = False
start = datetime.datetime.utcfromtimestamp(timerange_train.startts)
stop = datetime.datetime.utcfromtimestamp(timerange_train.stopts)
tr_training_list.append(start.strftime("%Y%m%d") + "-" + stop.strftime("%Y%m%d"))
# associated backtest period
if timerange_backtest.stopts > config_timerange.stopts:
timerange_backtest.stopts = config_timerange.stopts
timerange_backtest.startts = timerange_train.stopts
timerange_backtest.stopts = timerange_backtest.startts + bt_period
start = datetime.datetime.utcfromtimestamp(timerange_backtest.startts)
stop = datetime.datetime.utcfromtimestamp(timerange_backtest.stopts)
tr_backtesting_list.append(start.strftime("%Y%m%d") + "-" + stop.strftime("%Y%m%d"))
# ensure we are predicting on exactly same amount of data as requested by user defined
# --timerange
if timerange_backtest.stopts == config_timerange.stopts:
break
print(tr_training_list, tr_backtesting_list)
return tr_training_list, tr_backtesting_list
def slice_dataframe(self, tr: str, df: DataFrame) -> DataFrame:

4
freqtrade/freqai/freqai_interface.py
View File

@ -8,7 +8,7 @@ import numpy as np
import pandas as pd
from pandas import DataFrame
from freqtrade.freqai.data_handler import DataHandler
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
pd.options.mode.chained_assignment = None
@ -55,7 +55,7 @@ class IFreqaiModel(ABC):
:metadata: pair metadataa coming from strategy.
"""
self.pair = metadata["pair"]
self.dh = DataHandler(self.config, dataframe)
self.dh = FreqaiDataKitchen(self.config, dataframe)
logger.info("going to train %s timeranges", len(self.dh.training_timeranges))