def test_calc_position_value_nan_exec(self):
quotes = pd.DataFrame(
{
'c': [np.nan, 2, 3, 4, 5, 6],
'exec': [np.nan, 3, 4, 5, 6, np.nan],
},
index=[
pd.Timestamp(d) for d in [
'2018-01-01', '2018-01-02', '2018-01-03', '2018-01-07',
'2018-01-08', '2018-01-09'
]
])
_asset_dict = {
'ticker': 'test_ticker',
'quotes': quotes,
'point_value': 100
}
a = Asset(**_asset_dict)
# Valid case
self.assertEqual(
6 * 100 * 100,
a.calc_position_value(pd.Timestamp('2018-01-09'), 100))
self.assertEqual(
6 * 100 * 100,
a.calc_position_value(pd.Timestamp('2018-01-09'), -100))
# Both are nan raise
self.assertRaises(ValueError, a.calc_position_value,
pd.Timestamp('2018-01-01'), 100)
def test_calc_position_value(self):
_asset_dict = {
'ticker': 'test_ticker',
'quotes': self.quotes,
'point_value': 100
}
a = Asset(**_asset_dict)
# Valid case
self.assertEqual(
2 * 100 * 100,
a.calc_position_value(pd.Timestamp('2018-01-01'), 100))
self.assertEqual(
2 * 100 * 100,
a.calc_position_value(pd.Timestamp('2018-01-01'), -100))