def test_merge():
symToTa = start.get_all_from(
os.path.join(local_path, 'start_test.dir', 'ta'))
df = start.merge(symToTa, '2016-05-02', '2016-05-28')
assert (40, 82) == df.shape
df = start.merge(symToTa, '2016-05-03', '2016-05-28')
assert (38, 82) == df.shape
df = start.merge(symToTa, '2016-05-02', '2016-05-27')
assert (40, 82) == df.shape
df = start.merge(symToTa, '2016-05-02', '2016-05-26')
assert (38, 82) == df.shape
def test_pred():
symToTa = start.get_all_from(
os.path.join(local_path, 'start_test.dir', 'ta'))
df = start.merge(symToTa, '2016-05-02', '2016-05-28')
lLabel = [x for x in df.columns if x.startswith('label')]
for sym in symToTa:
for each in lLabel[4:]:
del symToTa[sym][each]
df = start.pred(symToTa, 3, {}, '2016-01-01', '2016-12-31', '2016-05-27')
assert (2, 77) == df.shape
def test_build_trains2():
symToTa = start.get_all_from(
os.path.join(local_path, 'start_test.dir', 'ta'))
df = start.merge(symToTa, '2016-05-02', '2016-05-28')
lLabel = [x for x in df.columns if x.startswith('label')]
for sym in symToTa:
for each in lLabel[4:]:
del symToTa[sym][each]
df = start.build_trains(symToTa, '2016-05-02', '2016-05-27')
assert (32, 80) == df.shape
def test_train():
symToTa = start.get_all_from(
os.path.join(local_path, 'start_test.dir', 'ta'))
df = start.merge(symToTa, '2016-05-02', '2016-05-28')
lLabel = [x for x in df.columns if x.startswith('label')]
for sym in symToTa:
for each in lLabel[4:]:
del symToTa[sym][each]
#npLabel = df.loc[:,start.get_label_name(df,3)].values.copy()
#npLabel[npLabel != 1.0]
#npLabel[npLabel > 1.0] = 1
#npLabel[npLabel < 1.0] = 0
#print npLabel
#assert False
df = start.train2(symToTa, 3, {}, '2016-01-01', '2016-12-31', '2016-01-01',
'2016-12-31')
assert (32, 81) == df.shape
def test_get_feat_names():
symToTa = start.get_all_from(
os.path.join(local_path, 'start_test.dir', 'ta'))
df = start.merge(symToTa, '2016-05-02', '2016-05-28')
assert 70 == len(start.get_feat_names(df))