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Fixed future deprecating warning and divide by zero warning #35

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Fixed future deprecating warning and divide by zero warning #35

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596cb56
Bokeh fix future deprecating
ryanwcyin Jan 4, 2022
f0ffc3f
avoid divide by zero error
ryanwcyin Jan 4, 2022
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31 changes: 19 additions & 12 deletions gemini/empyrical/stats.py
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Original file line number Diff line number Diff line change
Expand Up @@ -378,7 +378,7 @@ def max_drawdown(returns, out=None):
cumulative = np.empty(
(returns.shape[0] + 1,) + returns.shape[1:],
dtype='float64',
)
)
cumulative[0] = start = 100
cum_returns(returns_array, starting_value=start, out=cumulative[1:])

Expand Down Expand Up @@ -627,7 +627,7 @@ def omega_ratio(returns, risk_free=0.0, required_return=0.0,
return np.nan
else:
return_threshold = (1 + required_return) ** \
(1. / annualization) - 1
(1. / annualization) - 1

returns_less_thresh = returns - risk_free - return_threshold

Expand Down Expand Up @@ -697,15 +697,19 @@ def sharpe_ratio(returns,
returns_risk_adj = np.asanyarray(_adjust_returns(returns, risk_free))
ann_factor = annualization_factor(period, annualization)

np.multiply(
np.divide(
nanmean(returns_risk_adj, axis=0),
nanstd(returns_risk_adj, ddof=1, axis=0),
# handle 0.
if nanstd(returns_risk_adj, ddof=1, axis=0) == 0.0:
out = np.zeros_like(out)
else:
np.multiply(
np.divide(
nanmean(returns_risk_adj, axis=0),
nanstd(returns_risk_adj, ddof=1, axis=0),
out=out,
),
np.sqrt(ann_factor),
out=out,
),
np.sqrt(ann_factor),
out=out,
)
)
if return_1d:
out = out.item()

Expand Down Expand Up @@ -787,7 +791,10 @@ def sortino_ratio(returns,
if _downside_risk is not None else
downside_risk(returns, required_return, period, annualization)
)
np.divide(average_annual_return, annualized_downside_risk, out=out)
if annualized_downside_risk == 0.0:
out = np.zeros_like(out)
else:
np.divide(average_annual_return, annualized_downside_risk, out=out)
if return_1d:
out = out.item()
elif isinstance(returns, pd.DataFrame):
Expand Down Expand Up @@ -1508,7 +1515,7 @@ def tail_ratio(returns):
return np.nan

return np.abs(np.percentile(returns, 95)) / \
np.abs(np.percentile(returns, 5))
np.abs(np.percentile(returns, 5))


def capture(returns, factor_returns, period=DAILY):
Expand Down
10 changes: 5 additions & 5 deletions gemini/helpers/analyze.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ def analyze_bokeh(algo, title=None, show_trades=False):
continue

p.line(records['date'], records[c], color='grey',
legend=c, y_range_name="Records")
legend_label=c, y_range_name="Records")

# print(algo.data[['date', 'close', 'sma50', 'sma150']])

Expand All @@ -54,12 +54,12 @@ def analyze_bokeh(algo, title=None, show_trades=False):

p.line(algo.data.index, algo.data['base_equity'],
color='#CAD8DE',
legend='Buy and Hold')
# ,y_range_name="equity_y_axis")
legend_label='Buy and Hold')
# ,y_range_name="equity_y_axis")
p.line(algo.data.index, algo.data['equity'],
color='#49516F',
legend='Strategy')
#,y_range_name="equity_y_axis")
legend_label='Strategy')
#,y_range_name="equity_y_axis")

cmo_above_50 = bokeh.models.Span(location=50,
dimension="width",
Expand Down