Merge branch 'develop' into timeperiod

2018-01-11 19:45:47 +01:00
parent 94883202b8 3a902289f1
commit 153e11f045
25 changed files with 391 additions and 253 deletions
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -1,19 +1,18 @@
 # pragma pylint: disable=missing-docstring,W0212

-
 import logging
-from typing import Tuple, Dict
+from typing import Dict, Tuple

 import arrow
 from pandas import DataFrame, Series
 from tabulate import tabulate

+import freqtrade.misc as misc
+import freqtrade.optimize as optimize
 from freqtrade import exchange
 from freqtrade.analyze import populate_buy_trend, populate_sell_trend
 from freqtrade.exchange import Bittrex
 from freqtrade.main import min_roi_reached
-import freqtrade.misc as misc
-import freqtrade.optimize as optimize
 from freqtrade.persistence import Trade

 logger = logging.getLogger(__name__)
@@ -121,20 +120,20 @@ def backtest(stake_amount: float, processed: Dict[str, DataFrame],
                if min_roi_reached(trade, row2.close, row2.date) or \
                    (row2.sell == 1 and use_sell_signal) or \
                        current_profit_percent <= stoploss:
-                        current_profit_btc = trade.calc_profit(rate=row2.close)
-                        lock_pair_until = row2.Index
+                    current_profit_btc = trade.calc_profit(rate=row2.close)
+                    lock_pair_until = row2.Index

-                        trades.append(
-                            (
-                                pair,
-                                current_profit_percent,
-                                current_profit_btc,
-                                row2.Index - row.Index,
-                                current_profit_btc > 0,
-                                current_profit_btc < 0
-                            )
+                    trades.append(
+                        (
+                            pair,
+                            current_profit_percent,
+                            current_profit_btc,
+                            row2.Index - row.Index,
+                            current_profit_btc > 0,
+                            current_profit_btc < 0
                        )
-                        break
+                    )
+                    break
    labels = ['currency', 'profit_percent', 'profit_BTC', 'duration', 'profit', 'loss']
    return DataFrame.from_records(trades, columns=labels)

@@ -192,6 +191,6 @@ def start(args):
        use_sell_signal=config.get('experimental', {}).get('use_sell_signal', False)
    )
    logger.info(
-        '\n==================================== BACKTESTING REPORT ====================================\n%s', # noqa
+        '\n==================================== BACKTESTING REPORT ====================================\n%s',  # noqa
        generate_text_table(data, results, config['stake_currency'], args.ticker_interval)
    )
--- a/freqtrade/optimize/hyperopt.py
+++ b/freqtrade/optimize/hyperopt.py
@@ -4,14 +4,18 @@
 import json
 import logging
 import sys
+import pickle
+import signal
+import os
 from functools import reduce
 from math import exp
 from operator import itemgetter

-from hyperopt import fmin, tpe, hp, Trials, STATUS_OK, STATUS_FAIL, space_eval
+from hyperopt import STATUS_FAIL, STATUS_OK, Trials, fmin, hp, space_eval, tpe
 from hyperopt.mongoexp import MongoTrials
 from pandas import DataFrame

+from freqtrade import main  # noqa
 from freqtrade import exchange, optimize
 from freqtrade.exchange import Bittrex
 from freqtrade.misc import load_config
@@ -27,7 +31,7 @@ logger = logging.getLogger(__name__)

 # set TARGET_TRADES to suit your number concurrent trades so its realistic to 20days of data
 TARGET_TRADES = 1100
-TOTAL_TRIES = None
+TOTAL_TRIES = 0
 _CURRENT_TRIES = 0
 CURRENT_BEST_LOSS = 100

@@ -43,6 +47,10 @@ EXPECTED_MAX_PROFIT = 3.85
 PROCESSED = None  # optimize.preprocess(optimize.load_data())
 OPTIMIZE_CONFIG = hyperopt_optimize_conf()

+# Hyperopt Trials
+TRIALS_FILE = os.path.join('freqtrade', 'optimize', 'hyperopt_trials.pickle')
+TRIALS = Trials()
+
 # Monkey patch config
 from freqtrade import main  # noqa
 main._CONF = OPTIMIZE_CONFIG
@@ -99,6 +107,26 @@ SPACE = {
 }


+def save_trials(trials, trials_path=TRIALS_FILE):
+    """Save hyperopt trials to file"""
+    logger.info('Saving Trials to \'{}\''.format(trials_path))
+    pickle.dump(trials, open(trials_path, 'wb'))
+
+
+def read_trials(trials_path=TRIALS_FILE):
+    """Read hyperopt trials file"""
+    logger.info('Reading Trials from \'{}\''.format(trials_path))
+    trials = pickle.load(open(trials_path, 'rb'))
+    os.remove(trials_path)
+    return trials
+
+
+def log_trials_result(trials):
+    vals = json.dumps(trials.best_trial['misc']['vals'], indent=4)
+    results = trials.best_trial['result']['result']
+    logger.info('Best result:\n%s\nwith values:\n%s', results, vals)
+
+
 def log_results(results):
    """ log results if it is better than any previous evaluation """
    global CURRENT_BEST_LOSS
@@ -167,7 +195,7 @@ def format_results(results: DataFrame):
                results.profit_percent.mean() * 100.0,
                results.profit_BTC.sum(),
                results.duration.mean() * 5,
-            )
+    )


 def buy_strategy_generator(params):
@@ -216,7 +244,8 @@ def buy_strategy_generator(params):


 def start(args):
-    global TOTAL_TRIES, PROCESSED, SPACE
+    global TOTAL_TRIES, PROCESSED, SPACE, TRIALS, _CURRENT_TRIES
+
    TOTAL_TRIES = args.epochs

    exchange._API = Bittrex({'key': '', 'secret': ''})
@@ -238,9 +267,19 @@ def start(args):
        logger.info('Start scripts/start-mongodb.sh and start-hyperopt-worker.sh manually!')

        db_name = 'freqtrade_hyperopt'
-        trials = MongoTrials('mongo://127.0.0.1:1234/{}/jobs'.format(db_name), exp_key='exp1')
+        TRIALS = MongoTrials('mongo://127.0.0.1:1234/{}/jobs'.format(db_name), exp_key='exp1')
    else:
-        trials = Trials()
+        logger.info('Preparing Trials..')
+        signal.signal(signal.SIGINT, signal_handler)
+        # read trials file if we have one
+        if os.path.exists(TRIALS_FILE):
+            TRIALS = read_trials()
+
+            _CURRENT_TRIES = len(TRIALS.results)
+            TOTAL_TRIES = TOTAL_TRIES + _CURRENT_TRIES
+            logger.info(
+                'Continuing with trials. Current: {}, Total: {}'
+                .format(_CURRENT_TRIES, TOTAL_TRIES))

    try:
        best_parameters = fmin(
@@ -248,10 +287,10 @@ def start(args):
            space=SPACE,
            algo=tpe.suggest,
            max_evals=TOTAL_TRIES,
-            trials=trials
+            trials=TRIALS
        )

-        results = sorted(trials.results, key=itemgetter('loss'))
+        results = sorted(TRIALS.results, key=itemgetter('loss'))
        best_result = results[0]['result']

    except ValueError:
@@ -265,3 +304,15 @@ def start(args):

    logger.info('Best parameters:\n%s', json.dumps(best_parameters, indent=4))
    logger.info('Best Result:\n%s', best_result)
+
+    # Store trials result to file to resume next time
+    save_trials(TRIALS)
+
+
+def signal_handler(sig, frame):
+    """Hyperopt SIGINT handler"""
+    logger.info('Hyperopt received {}'.format(signal.Signals(sig).name))
+
+    save_trials(TRIALS)
+    log_trials_result(TRIALS)
+    sys.exit(0)
--- a/freqtrade/optimize/hyperopt_conf.py
+++ b/freqtrade/optimize/hyperopt_conf.py
@@ -15,10 +15,10 @@ def hyperopt_optimize_conf() -> dict:
        'stake_currency': 'BTC',
        'stake_amount': 0.01,
        "minimal_roi": {
-            '40':  0.0,
-            '30':  0.01,
-            '20':  0.02,
-            '0':  0.04,
+            '40': 0.0,
+            '30': 0.01,
+            '20': 0.02,
+            '0': 0.04,
        },
        'stoploss': -0.10,
        "bid_strategy": {