freqtrade_origin/freqtrade/data/btanalysis.py

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2019-03-07 20:20:32 +00:00
"""
Helpers when analyzing backtest data
"""
from pathlib import Path
import numpy as np
import pandas as pd
from freqtrade.misc import json_load
# must align with columns in backtest.py
BT_DATA_COLUMNS = ["pair", "profitperc", "open_time", "close_time", "index", "duration",
"open_rate", "close_rate", "open_at_end", "sell_reason"]
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def load_backtest_data(filename) -> pd.DataFrame:
"""
Load backtest data file.
:param filename: pathlib.Path object, or string pointing to the file.
:return a dataframe with the analysis results
"""
if isinstance(filename, str):
filename = Path(filename)
if not filename.is_file():
raise ValueError("File {filename} does not exist.")
with filename.open() as file:
data = json_load(file)
df = pd.DataFrame(data, columns=BT_DATA_COLUMNS)
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df['open_time'] = pd.to_datetime(df['open_time'],
unit='s',
utc=True,
infer_datetime_format=True
)
df['close_time'] = pd.to_datetime(df['close_time'],
unit='s',
utc=True,
infer_datetime_format=True
)
df['profitabs'] = df['close_rate'] - df['open_rate']
df = df.sort_values("open_time").reset_index(drop=True)
return df
def evaluate_result_multi(results: pd.DataFrame, freq: str, max_open_trades: int) -> pd.DataFrame:
"""
Find overlapping trades by expanding each trade once per period it was open
and then counting overlaps
:param results: Results Dataframe - can be loaded
:param freq: Frequency used for the backtest
:param max_open_trades: parameter max_open_trades used during backtest run
:return: dataframe with open-counts per time-period in freq
"""
dates = [pd.Series(pd.date_range(row[1].open_time, row[1].close_time, freq=freq))
for row in results[['open_time', 'close_time']].iterrows()]
deltas = [len(x) for x in dates]
dates = pd.Series(pd.concat(dates).values, name='date')
df2 = pd.DataFrame(np.repeat(results.values, deltas, axis=0), columns=results.columns)
df2 = df2.astype(dtype={"open_time": "datetime64", "close_time": "datetime64"})
df2 = pd.concat([dates, df2], axis=1)
df2 = df2.set_index('date')
df_final = df2.resample(freq)[['pair']].count()
return df_final[df_final['pair'] > max_open_trades]