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Force cast to float for np.isinf, fixes #204 #207

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Nov 20, 2023
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Force cast to float for np.isinf, fixes #204 #207

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2 changes: 1 addition & 1 deletion ffn/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1567,7 +1567,7 @@ def calc_inv_vol_weights(returns):
Series {col_name: weight}
"""
# calc vols
vol = np.divide(1.0, np.std(returns, ddof=1))
vol = np.divide(1.0, np.std(returns, ddof=1)).astype(float)
vol[np.isinf(vol)] = np.NaN
volsum = vol.sum()
return np.divide(vol, volsum)
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20 changes: 14 additions & 6 deletions tests/test_core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -267,6 +267,15 @@ def test_calc_inv_vol_weights(df):
aae(actual["MSFT"], 0.464, 3)
aae(actual["C"], 0.318, 3)

def test_calc_inv_vol_weights_object_regression_204(df):
prc = df.iloc[0:11]
rets = prc.to_returns().dropna().astype(object)
actual = ffn.core.calc_inv_vol_weights(rets)

aae(actual["AAPL"], 0.218, 3)
aae(actual["MSFT"], 0.464, 3)
aae(actual["C"], 0.318, 3)


def test_calc_mean_var_weights(df):
prc = df.iloc[0:11]
Expand Down Expand Up @@ -958,17 +967,17 @@ def test_infer_nperiods():
index = pd.date_range(start='2018-01-01', periods = 10, freq = 'T'))
secondly = pd.DataFrame(np.random.randn(10),
index = pd.date_range(start='2018-01-01', periods = 10, freq = 'S'))

minutely_30 = pd.DataFrame(np.random.randn(10),
index = pd.date_range(start='2018-01-01', periods = 10, freq = '30T'))


not_known_vals = np.concatenate((pd.date_range(start='2018-01-01', periods = 5, freq = '1H').values,
pd.date_range(start='2018-01-02', periods = 5, freq = '5H').values))

not_known = pd.DataFrame(np.random.randn(10),
index = pd.DatetimeIndex(not_known_vals))

assert ffn.core.infer_nperiods(daily) == ffn.core.TRADING_DAYS_PER_YEAR
assert ffn.core.infer_nperiods(hourly) == ffn.core.TRADING_DAYS_PER_YEAR * 24
assert ffn.core.infer_nperiods(minutely) == ffn.core.TRADING_DAYS_PER_YEAR * 24 * 60
Expand All @@ -977,4 +986,3 @@ def test_infer_nperiods():
assert ffn.core.infer_nperiods(yearly) == 1
assert ffn.core.infer_nperiods(minutely_30) == ffn.core.TRADING_DAYS_PER_YEAR * 24 * 60 * 30
assert ffn.core.infer_nperiods(not_known) is None