def test_fromfuncs(self):
_vol_ave_int = 2
_sma_window = 4
_skipatstart = _sma_window - 1
_n_sess = 3
_smafunc = pn.expand(pn.tech.sma, 'Adj Close')
_funcs = [
pn.decorate(partial(pn.tech.ratio_to_ave, _vol_ave_int),
title='MyRelVol'),
pn.decorate(partial(_smafunc, window=_sma_window), title='MySMA')]
_features = pn.data.feat.fromfuncs(_funcs, _n_sess, self.equity_data,
skipatstart=_skipatstart)
self.assertEqual(len(_features.index), len(self.equity_data.index) - _n_sess - _skipatstart + 1)
for i in range(len(_features.index)):
self.assertAlmostEqual(_features.iloc[i, 0], 1.)
self.assertEqual(_features.index[i], self.equity_data.index[i + _n_sess + _skipatstart - 1])
for j in range(_n_sess):
# relative volumes all between 1.0 and 2.0
self.assertTrue(_features.iloc[i, j + 1] < 2.)
self.assertTrue(_features.iloc[i, j + 1] > 1.)
# SMAs are means of values like 4, 6, 8, 10
self.assertAlmostEqual(_features.iloc[i, j + _n_sess + 1], 1. + _sma_window + 2. * (i + j))
# properties of relative volumes
if i >= 1:
# strictly decreasing
self.assertTrue(_features.iloc[i, 1] < _features.iloc[i - 1, 1])
# columns match with offset
self.assertAlmostEqual(_features.iloc[i, 1], _features.iloc[i - 1, 2])
self.assertAlmostEqual(_features.iloc[i, 2], _features.iloc[i - 1, 3])
def test_labeledfeatures(self):
_n_featsess = 2
_ave_int = 3
_pred_int = 1
_featfuncs = []
# growth and relative volume functions
_featfuncs.append(
pn.decorate(partial(pn.tech.growth, selection='Adj Close'),
title='G'))
_featfuncs.append(
pn.decorate(partial(pn.tech.ratio_to_ave, _ave_int), title='V'))
_featfunc = pn.decorate(
partial(pn.data.feat.fromfuncs,
_featfuncs,
_n_featsess,
skipatstart=_ave_int), _ave_int + _n_featsess - 1)
_labfunc = pn.decorate(
partial(pn.data.lab.growth, _pred_int, 'Adj Close'), _pred_int)
features, labels = pn.data.labeledfeatures(self.equity_data, _featfunc,
_labfunc)
self.assertEqual(features.values.shape[0], labels.values.shape[0])
self.assertEqual(features.values.shape[1], 5)
for i in range(1, len(features.index)):
self.assertAlmostEqual(features.loc[:, '-1 G'].values[i],
features.loc[:, '0 G'].values[i - 1])
self.assertAlmostEqual(features.loc[:, '-1 V'].values[i],
features.loc[:, '0 V'].values[i - 1])
for i in range(5):
self.assertAlmostEqual(features.loc[:, '0 G'].values[i],
(i + 5.) / (i + 4.))
self.assertAlmostEqual(features.loc[:, '0 V'].values[i],
(2. * i + 9.) / (2. * i + 5.))
self.assertAlmostEqual(labels.values[i], (i + 6.) / (i + 5.))
def test_decorate(self):
def _f():
return 0, 1
self.assertEqual(pn.decorate(_f, 2, 3)(), (0, 1, 2, 3))
self.assertEqual(pn.decorate(lambda x: x * 2, 0)(3), (6, 0))
self.assertEqual(pn.decorate(lambda x: x, 4, 5)('foo'), ('foo', 4, 5))
self.assertEqual(pn.decorate(_f, 'foo')(), (0, 1, 'foo'))
_g = pn.decorate(_f, 2, foo='bar')
self.assertEqual(_g.foo, 'bar')
self.assertFalse(hasattr(_f, 'foo'))
self.assertEqual(_g(), (0, 1, 2))
def test_decorate(self):
def _f():
return 0, 1
self.assertEqual(pn.decorate(_f, 2, 3)(), (0, 1, 2, 3))
self.assertEqual(pn.decorate(lambda x: x * 2, 0)(3), (6, 0))
self.assertEqual(pn.decorate(lambda x: x, 4, 5)('foo'), ('foo', 4, 5))
self.assertEqual(pn.decorate(_f, 'foo')(), (0, 1, 'foo'))
_g = pn.decorate(_f, 2, foo='bar')
self.assertEqual(_g.foo, 'bar')
self.assertFalse(hasattr(_f, 'foo'))
self.assertEqual(_g(), (0, 1, 2))
def test_labeledfeatures(self):
_n_featsess = 2
_ave_int = 3
_pred_int = 1
_featfuncs = []
# growth and relative volume functions
_featfuncs.append(pn.decorate(partial(pn.tech.growth, selection='Adj Close'), title='G'))
_featfuncs.append(pn.decorate(partial(pn.tech.ratio_to_ave, _ave_int), title='V'))
_featfunc = pn.decorate(partial(pn.data.feat.fromfuncs, _featfuncs, _n_featsess, skipatstart=_ave_int),
_ave_int + _n_featsess - 1)
_labfunc = pn.decorate(partial(pn.data.lab.growth, _pred_int, 'Adj Close'), _pred_int)
features, labels = pn.data.labeledfeatures(self.equity_data, _featfunc, _labfunc)
self.assertEqual(features.values.shape[0], labels.values.shape[0])
self.assertEqual(features.values.shape[1], 5)
for i in range(1, len(features.index)):
self.assertAlmostEqual(features.loc[:, '-1 G'].values[i],
features.loc[:, '0 G'].values[i - 1])
self.assertAlmostEqual(features.loc[:, '-1 V'].values[i],
features.loc[:, '0 V'].values[i - 1])
for i in range(5):
self.assertAlmostEqual(features.loc[:, '0 G'].values[i], (i + 5.) / (i + 4.))
self.assertAlmostEqual(features.loc[:, '0 V'].values[i], (2. * i + 9.) / (2. * i + 5.))
self.assertAlmostEqual(labels.values[i], (i + 6.) / (i + 5.))
