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Merge pull request #913 from freqtrade/apply-qtpylib-updates

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Apply qtpylib upstream changes
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Matthias 2018-06-13 19:34:02 +02:00 committed by GitHub
commit d7e7ef11f9
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1 changed files with 26 additions and 35 deletions
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61
freqtrade/vendor/qtpylib/indicators.py vendored
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@ -110,10 +110,13 @@ def heikinashi(bars):
bars = bars.copy() bars = bars.copy()
bars['ha_close'] = (bars['open'] + bars['high'] + bars['ha_close'] = (bars['open'] + bars['high'] +
bars['low'] + bars['close']) / 4 bars['low'] + bars['close']) / 4
bars['ha_open'] = (bars['open'].shift(1) + bars['close'].shift(1)) / 2 bars['ha_open'] = (bars['open'].shift(1) + bars['close'].shift(1)) / 2
bars.loc[:1, 'ha_open'] = bars['open'].values[0] bars.loc[:1, 'ha_open'] = bars['open'].values[0]
bars.loc[1:, 'ha_open'] = ( for x in range(2):
(bars['ha_open'].shift(1) + bars['ha_close'].shift(1)) / 2)[1:] bars.loc[1:, 'ha_open'] = (
(bars['ha_open'].shift(1) + bars['ha_close'].shift(1)) / 2)[1:]
bars['ha_high'] = bars.loc[:, ['high', 'ha_open', 'ha_close']].max(axis=1) bars['ha_high'] = bars.loc[:, ['high', 'ha_open', 'ha_close']].max(axis=1)
bars['ha_low'] = bars.loc[:, ['low', 'ha_open', 'ha_close']].min(axis=1) bars['ha_low'] = bars.loc[:, ['low', 'ha_open', 'ha_close']].min(axis=1)
@ -248,45 +251,36 @@ def crossed_below(series1, series2):
def rolling_std(series, window=200, min_periods=None): def rolling_std(series, window=200, min_periods=None):
min_periods = window if min_periods is None else min_periods min_periods = window if min_periods is None else min_periods
try: if min_periods == window and len(series) > window:
if min_periods == window: return numpy_rolling_std(series, window, True)
return numpy_rolling_std(series, window, True) else:
else: try:
try: return series.rolling(window=window, min_periods=min_periods).std()
return series.rolling(window=window, min_periods=min_periods).std() except BaseException:
except BaseException: return pd.Series(series).rolling(window=window, min_periods=min_periods).std()
return pd.Series(series).rolling(window=window, min_periods=min_periods).std()
except BaseException:
return pd.rolling_std(series, window=window, min_periods=min_periods)
# --------------------------------------------- # ---------------------------------------------
def rolling_mean(series, window=200, min_periods=None): def rolling_mean(series, window=200, min_periods=None):
min_periods = window if min_periods is None else min_periods min_periods = window if min_periods is None else min_periods
try: if min_periods == window and len(series) > window:
if min_periods == window: return numpy_rolling_mean(series, window, True)
return numpy_rolling_mean(series, window, True) else:
else: try:
try: return series.rolling(window=window, min_periods=min_periods).mean()
return series.rolling(window=window, min_periods=min_periods).mean() except BaseException:
except BaseException: return pd.Series(series).rolling(window=window, min_periods=min_periods).mean()
return pd.Series(series).rolling(window=window, min_periods=min_periods).mean()
except BaseException:
return pd.rolling_mean(series, window=window, min_periods=min_periods)
# --------------------------------------------- # ---------------------------------------------
def rolling_min(series, window=14, min_periods=None): def rolling_min(series, window=14, min_periods=None):
min_periods = window if min_periods is None else min_periods min_periods = window if min_periods is None else min_periods
try: try:
try: return series.rolling(window=window, min_periods=min_periods).min()
return series.rolling(window=window, min_periods=min_periods).min()
except BaseException:
return pd.Series(series).rolling(window=window, min_periods=min_periods).min()
except BaseException: except BaseException:
return pd.rolling_min(series, window=window, min_periods=min_periods) return pd.Series(series).rolling(window=window, min_periods=min_periods).min()
# --------------------------------------------- # ---------------------------------------------
@ -294,12 +288,9 @@ def rolling_min(series, window=14, min_periods=None):
def rolling_max(series, window=14, min_periods=None): def rolling_max(series, window=14, min_periods=None):
min_periods = window if min_periods is None else min_periods min_periods = window if min_periods is None else min_periods
try: try:
try: return series.rolling(window=window, min_periods=min_periods).min()
return series.rolling(window=window, min_periods=min_periods).min()
except BaseException:
return pd.Series(series).rolling(window=window, min_periods=min_periods).min()
except BaseException: except BaseException:
return pd.rolling_min(series, window=window, min_periods=min_periods) return pd.Series(series).rolling(window=window, min_periods=min_periods).min()
# --------------------------------------------- # ---------------------------------------------
@ -566,9 +557,9 @@ def stoch(df, window=14, d=3, k=3, fast=False):
return pd.DataFrame(index=df.index, data=data) return pd.DataFrame(index=df.index, data=data)
# --------------------------------------------- # ---------------------------------------------
def zscore(bars, window=20, stds=1, col='close'): def zscore(bars, window=20, stds=1, col='close'):
""" get zscore of price """ """ get zscore of price """
std = numpy_rolling_std(bars[col], window) std = numpy_rolling_std(bars[col], window)