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fix timestamping, move imports, add words to doc

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This commit is contained in:
robcaulk
2022-09-06 19:46:58 +02:00
parent fa8d5b9834
commit 4b28d0495f
4 changed files with 25 additions and 30 deletions
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26
freqtrade/freqai/data_kitchen.py
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@@ -2,12 +2,14 @@ import copy
import logging
import shutil
from datetime import datetime, timezone
from math import cos, sin
from pathlib import Path
from typing import Any, Dict, List, Tuple
import numpy as np
import numpy.typing as npt
import pandas as pd
import scipy.stats as stats
from pandas import DataFrame
from sklearn import linear_model
from sklearn.cluster import DBSCAN
@@ -401,8 +403,8 @@ class FreqaiDataKitchen:
timerange_train.stopts = timerange_train.startts + train_period_days
first = False
start = datetime.utcfromtimestamp(timerange_train.startts)
stop = datetime.utcfromtimestamp(timerange_train.stopts)
start = datetime.fromtimestamp(timerange_train.startts, tz=timezone.utc)
stop = datetime.fromtimestamp(timerange_train.stopts, tz=timezone.utc)
tr_training_list.append(start.strftime("%Y%m%d") + "-" + stop.strftime("%Y%m%d"))
tr_training_list_timerange.append(copy.deepcopy(timerange_train))
@@ -415,8 +417,8 @@ class FreqaiDataKitchen:
if timerange_backtest.stopts > config_timerange.stopts:
timerange_backtest.stopts = config_timerange.stopts
start = datetime.utcfromtimestamp(timerange_backtest.startts)
stop = datetime.utcfromtimestamp(timerange_backtest.stopts)
start = datetime.fromtimestamp(timerange_backtest.startts, tz=timezone.utc)
stop = datetime.fromtimestamp(timerange_backtest.stopts, tz=timezone.utc)
tr_backtesting_list.append(start.strftime("%Y%m%d") + "-" + stop.strftime("%Y%m%d"))
tr_backtesting_list_timerange.append(copy.deepcopy(timerange_backtest))
@@ -630,8 +632,6 @@ class FreqaiDataKitchen:
is an outlier.
"""
from math import cos, sin
if predict:
if not self.data['DBSCAN_eps']:
return
@@ -732,8 +732,6 @@ class FreqaiDataKitchen:
into previous timepoints.
"""
import scipy.stats as ss
no_prev_pts = self.freqai_config["feature_parameters"]["inlier_metric_window"]
if set_ == 'train':
@@ -778,8 +776,8 @@ class FreqaiDataKitchen:
inliers = pd.DataFrame(index=distances.index)
for key in distances.keys():
current_distances = distances[key].dropna()
fit_params = ss.weibull_min.fit(current_distances)
quantiles = ss.weibull_min.cdf(current_distances, *fit_params)
fit_params = stats.weibull_min.fit(current_distances)
quantiles = stats.weibull_min.cdf(current_distances, *fit_params)
df_inlier = pd.DataFrame(
{key: quantiles}, index=distances.index
@@ -794,8 +792,8 @@ class FreqaiDataKitchen:
index=compute_df.index
)
inlier_metric = 2 * (inlier_metric - inlier_metric.min()) / \
(inlier_metric.max() - inlier_metric.min()) - 1
inlier_metric = (2 * (inlier_metric - inlier_metric.min()) /
(inlier_metric.max() - inlier_metric.min()) - 1)
if set_ in ('train', 'test'):
inlier_metric = inlier_metric.iloc[no_prev_pts:]
@@ -956,8 +954,8 @@ class FreqaiDataKitchen:
backtest_timerange.startts = (
backtest_timerange.startts - backtest_period_days * SECONDS_IN_DAY
)
start = datetime.utcfromtimestamp(backtest_timerange.startts)
stop = datetime.utcfromtimestamp(backtest_timerange.stopts)
start = datetime.fromtimestamp(backtest_timerange.startts, tz=timezone.utc)
stop = datetime.fromtimestamp(backtest_timerange.stopts, tz=timezone.utc)
full_timerange = start.strftime("%Y%m%d") + "-" + stop.strftime("%Y%m%d")
self.full_path = Path(

15
freqtrade/freqai/freqai_interface.py
View File

@@ -1,10 +1,9 @@
# import contextlib
import logging
import shutil
import threading
import time
from abc import ABC, abstractmethod
from datetime import datetime
from datetime import datetime, timezone
from pathlib import Path
from threading import Lock
from typing import Any, Dict, Tuple
@@ -214,12 +213,12 @@ class IFreqaiModel(ABC):
dataframe_backtest = dk.slice_dataframe(tr_backtest, dataframe)
trained_timestamp = tr_train
tr_train_startts_str = datetime.utcfromtimestamp(tr_train.startts).strftime(
"%Y-%m-%d %H:%M:%S"
)
tr_train_stopts_str = datetime.utcfromtimestamp(tr_train.stopts).strftime(
"%Y-%m-%d %H:%M:%S"
)
tr_train_startts_str = datetime.fromtimestamp(
tr_train.startts,
tz=timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
tr_train_stopts_str = datetime.fromtimestamp(
tr_train.stopts,
tz=timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
logger.info(
f"Training {metadata['pair']}, {self.pair_it}/{self.total_pairs} pairs"
f" from {tr_train_startts_str} to {tr_train_stopts_str}, {train_it}/{total_trains} "