Merge pull request freqtrade#79 from gcarq/qtpylib

Include new indicators from qtpylib

freqtrade/analyze.py

@@ -5,6 +5,7 @@
 import arrow
 import talib.abstract as ta
 from pandas import DataFrame
+from qtpylib.indicators import awesome_oscillator, crossed_above
 
 from freqtrade import exchange
 from freqtrade.exchange import Bittrex, get_ticker_history
@@ -41,6 +42,8 @@ def populate_indicators(dataframe: DataFrame) -> DataFrame:
     dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
     dataframe['mfi'] = ta.MFI(dataframe)
     dataframe['cci'] = ta.CCI(dataframe)
+    dataframe['ao'] = awesome_oscillator(dataframe)
+
     return dataframe
 
 

freqtrade/tests/test_analyze.py

@@ -1,36 +1,25 @@
 # pragma pylint: disable=missing-docstring
+import json
 import pytest
 import arrow
 from pandas import DataFrame
 
 from freqtrade.analyze import parse_ticker_dataframe, populate_buy_trend, populate_indicators, \
     get_buy_signal
 
-RESULT_BITTREX = {
-    'success': True,
-    'message': '',
-    'result': [
-        {'O': 0.00065311, 'H': 0.00065311, 'L': 0.00065311, 'C': 0.00065311, 'V': 22.17210568, 'T': '2017-08-30T10:40:00', 'BV': 0.01448082},
-        {'O': 0.00066194, 'H': 0.00066195, 'L': 0.00066194, 'C': 0.00066195, 'V': 33.4727437, 'T': '2017-08-30T10:34:00', 'BV': 0.02215696},
-        {'O': 0.00065311, 'H': 0.00065311, 'L': 0.00065311, 'C': 0.00065311, 'V': 53.85127609, 'T': '2017-08-30T10:37:00', 'BV': 0.0351708},
-        {'O': 0.00066194, 'H': 0.00066194, 'L': 0.00065311, 'C': 0.00065311, 'V': 46.29210665, 'T': '2017-08-30T10:42:00', 'BV': 0.03063118},
-    ]
-}
-
 @pytest.fixture
 def result():
-    return parse_ticker_dataframe(RESULT_BITTREX['result'], arrow.get('2017-08-30T10:00:00'))
+    with open('freqtrade/tests/testdata/btc-eth.json') as data_file:
+        data = json.load(data_file)
+
+    return parse_ticker_dataframe(data['result'], arrow.get('2017-08-30T10:00:00'))
 
 def test_dataframe_has_correct_columns(result):
     assert result.columns.tolist() == \
                         ['close', 'high', 'low', 'open', 'date', 'volume']
 
-def test_orders_by_date(result):
-    assert result['date'].tolist() == \
-                        ['2017-08-30T10:34:00',
-                        '2017-08-30T10:37:00',
-                        '2017-08-30T10:40:00',
-                        '2017-08-30T10:42:00']
+def test_dataframe_has_correct_length(result):
+    assert len(result.index) == 5751
 
 def test_populates_buy_trend(result):
     dataframe = populate_buy_trend(populate_indicators(result))

freqtrade/tests/test_hyperopt.py

@@ -7,6 +7,7 @@
 import pytest
 import arrow
 from pandas import DataFrame
+from qtpylib.indicators import crossed_above
 
 from hyperopt import fmin, tpe, hp
 
@@ -63,6 +64,7 @@ def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
         triggers = {
             'lower_bb': dataframe['tema'] <= dataframe['blower'],
             'faststoch10': (dataframe['fastd'] >= 10) & (prev_fastd < 10),
+            'ao_cross_zero': (crossed_above(dataframe['ao'], 0.0)),
         }
         conditions.append(triggers.get(params['trigger']['type']))
 
@@ -124,7 +126,8 @@ def optimizer(params):
         ]),
         'trigger': hp.choice('trigger', [
             {'type': 'lower_bb'},
-            {'type': 'faststoch10'}
+            {'type': 'faststoch10'},
+            {'type': 'ao_cross_zero'}
         ]),
     }
     print('Best parameters {}'.format(fmin(fn=optimizer, space=space, algo=tpe.suggest, max_evals=40)))