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test_labels.py
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from datetime import datetime
import numpy as np
import pandas as pd
import vectorbt as vbt
close_ts = pd.DataFrame({
'a': [1, 2, 1, 2, 3, 2],
'b': [3, 2, 3, 2, 1, 2]
}, index=pd.Index([
datetime(2020, 1, 1),
datetime(2020, 1, 2),
datetime(2020, 1, 3),
datetime(2020, 1, 4),
datetime(2020, 1, 5),
datetime(2020, 1, 6)
]))
pos_ths = [np.array([1, 1 / 2]), np.array([2, 1 / 2]), np.array([3, 1 / 2])]
neg_ths = [np.array([1 / 2, 1 / 3]), np.array([1 / 2, 2 / 3]), np.array([1 / 2, 3 / 4])]
# ############# Global ############# #
def setup_module():
vbt.settings.numba['check_func_suffix'] = True
vbt.settings.caching.enabled = False
vbt.settings.caching.whitelist = []
vbt.settings.caching.blacklist = []
def teardown_module():
vbt.settings.reset()
# ############# generators.py ############# #
class TestGenerators:
def test_FMEAN(self):
pd.testing.assert_frame_equal(
vbt.FMEAN.run(close_ts, window=(2, 3), ewm=False).fmean,
pd.DataFrame(
np.array([
[1.5, 2.5, 1.6666666666666667, 2.3333333333333335],
[1.5, 2.5, 2.0, 2.0],
[2.5, 1.5, 2.3333333333333335, 1.6666666666666667],
[2.5, 1.5, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
(2, False, 'a'),
(2, False, 'b'),
(3, False, 'a'),
(3, False, 'b'),
], names=['fmean_window', 'fmean_ewm', None])
)
)
pd.testing.assert_frame_equal(
vbt.FMEAN.run(close_ts, window=(2, 3), ewm=True).fmean,
pd.DataFrame(
np.array([
[1.8024691358024691, 2.197530864197531, 1.8125, 2.1875],
[1.4074074074074074, 2.5925925925925926, 1.625, 2.375],
[2.2222222222222223, 1.7777777777777777, 2.25, 1.75],
[2.666666666666667, 1.3333333333333335, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
(2, True, 'a'),
(2, True, 'b'),
(3, True, 'a'),
(3, True, 'b'),
], names=['fmean_window', 'fmean_ewm', None])
)
)
def test_FSTD(self):
pd.testing.assert_frame_equal(
vbt.FSTD.run(close_ts, window=(2, 3), ewm=False).fstd,
pd.DataFrame(
np.array([
[0.5, 0.5, 0.4714045207910384, 0.4714045207910183],
[0.5, 0.5, 0.816496580927726, 0.816496580927726],
[0.5, 0.5, 0.4714045207910183, 0.4714045207910384],
[0.5, 0.5, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
(2, False, 'a'),
(2, False, 'b'),
(3, False, 'a'),
(3, False, 'b'),
], names=['fstd_window', 'fstd_ewm', None])
)
)
pd.testing.assert_frame_equal(
vbt.FSTD.run(close_ts, window=(2, 3), ewm=True).fstd,
pd.DataFrame(
np.array([
[0.64486716348143, 0.6448671634814303, 0.6462561866810479, 0.6462561866810479],
[0.8833005039168617, 0.8833005039168604, 0.8591246929842246, 0.8591246929842246],
[0.5916079783099623, 0.5916079783099623, 0.5477225575051662, 0.5477225575051662],
[0.7071067811865476, 0.7071067811865476, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
(2, True, 'a'),
(2, True, 'b'),
(3, True, 'a'),
(3, True, 'b'),
], names=['fstd_window', 'fstd_ewm', None])
)
)
def test_FMIN(self):
pd.testing.assert_frame_equal(
vbt.FMIN.run(close_ts, window=(2, 3)).fmin,
pd.DataFrame(
np.array([
[1.0, 2.0, 1.0, 2.0],
[1.0, 2.0, 1.0, 1.0],
[2.0, 1.0, 2.0, 1.0],
[2.0, 1.0, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
(2, 'a'),
(2, 'b'),
(3, 'a'),
(3, 'b'),
], names=['fmin_window', None])
)
)
def test_FMAX(self):
pd.testing.assert_frame_equal(
vbt.FMAX.run(close_ts, window=(2, 3)).fmax,
pd.DataFrame(
np.array([
[2.0, 3.0, 2.0, 3.0],
[2.0, 3.0, 3.0, 3.0],
[3.0, 2.0, 3.0, 2.0],
[3.0, 2.0, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
(2, 'a'),
(2, 'b'),
(3, 'a'),
(3, 'b'),
], names=['fmax_window', None])
)
)
def test_FIXLB(self):
pd.testing.assert_frame_equal(
vbt.FIXLB.run(close_ts, n=(2, 3)).labels,
pd.DataFrame(
np.array([
[0.0, 0.0, 1.0, -0.3333333333333333],
[0.0, 0.0, 0.5, -0.5],
[2.0, -0.6666666666666666, 1.0, -0.3333333333333333],
[0.0, 0.0, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
(2, 'a'),
(2, 'b'),
(3, 'a'),
(3, 'b'),
], names=['fixlb_n', None])
)
)
def test_MEANLB(self):
pd.testing.assert_frame_equal(
vbt.MEANLB.run(close_ts, window=(2, 3), ewm=False).labels,
pd.DataFrame(
np.array([
[0.5, -0.16666666666666666, 0.6666666666666667, -0.22222222222222218],
[-0.25, 0.25, 0.0, 0.0],
[1.5, -0.5, 1.3333333333333335, -0.4444444444444444],
[0.25, -0.25, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
(2, False, 'a'),
(2, False, 'b'),
(3, False, 'a'),
(3, False, 'b'),
], names=['meanlb_window', 'meanlb_ewm', None])
)
)
pd.testing.assert_frame_equal(
vbt.MEANLB.run(close_ts, window=(2, 3), ewm=True).labels,
pd.DataFrame(
np.array([
[0.8024691358024691, -0.2674897119341564, 0.8125, -0.2708333333333333],
[-0.2962962962962963, 0.2962962962962963, -0.1875, 0.1875],
[1.2222222222222223, -0.40740740740740744, 1.25, -0.4166666666666667],
[0.3333333333333335, -0.33333333333333326, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
(2, True, 'a'),
(2, True, 'b'),
(3, True, 'a'),
(3, True, 'b'),
], names=['meanlb_window', 'meanlb_ewm', None])
)
)
def test_LEXLB(self):
pd.testing.assert_frame_equal(
vbt.LEXLB.run(close_ts, pos_th=pos_ths, neg_th=neg_ths).labels,
pd.DataFrame(
np.array([
[-1, 1, -1, 1, 0, 0],
[1, -1, 0, 0, 0, 0],
[-1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[1, -1, 1, -1, 0, 0],
[0, 1, 0, 1, 0, 0]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
('array_0', 'array_0', 'a'),
('array_0', 'array_0', 'b'),
('array_1', 'array_1', 'a'),
('array_1', 'array_1', 'b'),
('array_2', 'array_2', 'a'),
('array_2', 'array_2', 'b')
], names=['lexlb_pos_th', 'lexlb_neg_th', None])
)
)
def test_TRENDLB(self):
pd.testing.assert_frame_equal(
vbt.TRENDLB.run(close_ts, pos_th=pos_ths, neg_th=neg_ths, mode='Binary').labels,
pd.DataFrame(
np.array([
[1.0, 0.0, 1.0, 0.0, np.nan, np.nan],
[0.0, 1.0, 1.0, 0.0, np.nan, np.nan],
[1.0, 0.0, 1.0, 0.0, np.nan, np.nan],
[1.0, 0.0, 1.0, 0.0, np.nan, np.nan],
[np.nan, 1.0, np.nan, 1.0, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, np.nan, np.nan]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
('array_0', 'array_0', 0, 'a'),
('array_0', 'array_0', 0, 'b'),
('array_1', 'array_1', 0, 'a'),
('array_1', 'array_1', 0, 'b'),
('array_2', 'array_2', 0, 'a'),
('array_2', 'array_2', 0, 'b')
], names=['trendlb_pos_th', 'trendlb_neg_th', 'trendlb_mode', None])
)
)
pd.testing.assert_frame_equal(
vbt.TRENDLB.run(close_ts, pos_th=pos_ths, neg_th=neg_ths, mode='BinaryCont').labels,
pd.DataFrame(
np.array([
[1.0, 0.0, 1.0, 0.0, np.nan, np.nan],
[0.0, 1.0, 0.5, 0.5, np.nan, np.nan],
[1.0, 0.0, 1.0, 0.0, np.nan, np.nan],
[0.5, 0.5, 0.5, 0.5, np.nan, np.nan],
[np.nan, 1.0, np.nan, 1.0, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, np.nan, np.nan]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
('array_0', 'array_0', 1, 'a'),
('array_0', 'array_0', 1, 'b'),
('array_1', 'array_1', 1, 'a'),
('array_1', 'array_1', 1, 'b'),
('array_2', 'array_2', 1, 'a'),
('array_2', 'array_2', 1, 'b')
], names=['trendlb_pos_th', 'trendlb_neg_th', 'trendlb_mode', None])
)
)
pd.testing.assert_frame_equal(
vbt.TRENDLB.run(close_ts, pos_th=pos_ths, neg_th=neg_ths, mode='BinaryContSat').labels,
pd.DataFrame(
np.array([
[1.0, 0.0, 1.0, 0.0, np.nan, np.nan],
[0.0, 1.0, 0.5, 0.4999999999999999, np.nan, np.nan],
[1.0, 0.0, 1.0, 0.0, np.nan, np.nan],
[0.6666666666666667, 0.0, 0.5, 0.4999999999999999, np.nan, np.nan],
[np.nan, 1.0, np.nan, 1.0, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, np.nan, np.nan]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
('array_0', 'array_0', 2, 'a'),
('array_0', 'array_0', 2, 'b'),
('array_1', 'array_1', 2, 'a'),
('array_1', 'array_1', 2, 'b'),
('array_2', 'array_2', 2, 'a'),
('array_2', 'array_2', 2, 'b')
], names=['trendlb_pos_th', 'trendlb_neg_th', 'trendlb_mode', None])
)
)
pd.testing.assert_frame_equal(
vbt.TRENDLB.run(close_ts, pos_th=pos_ths, neg_th=neg_ths, mode='PctChange').labels,
pd.DataFrame(
np.array([
[1.0, -0.3333333333333333, 2.0, -0.6666666666666666, np.nan, np.nan],
[-0.5, 0.5, 0.5, -0.5, np.nan, np.nan],
[2.0, -0.6666666666666666, 2.0, -0.6666666666666666, np.nan, np.nan],
[0.5, -0.5, 0.5, -0.5, np.nan, np.nan],
[np.nan, 1.0, np.nan, 1.0, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, np.nan, np.nan]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
('array_0', 'array_0', 3, 'a'),
('array_0', 'array_0', 3, 'b'),
('array_1', 'array_1', 3, 'a'),
('array_1', 'array_1', 3, 'b'),
('array_2', 'array_2', 3, 'a'),
('array_2', 'array_2', 3, 'b')
], names=['trendlb_pos_th', 'trendlb_neg_th', 'trendlb_mode', None])
)
)
pd.testing.assert_frame_equal(
vbt.TRENDLB.run(close_ts, pos_th=pos_ths, neg_th=neg_ths, mode='PctChangeNorm').labels,
pd.DataFrame(
np.array([
[0.5, -0.3333333333333333, 0.6666666666666666, -0.6666666666666666, np.nan, np.nan],
[-0.5, 0.3333333333333333, 0.3333333333333333, -0.5, np.nan, np.nan],
[0.6666666666666666, -0.6666666666666666, 0.6666666666666666,
-0.6666666666666666, np.nan, np.nan],
[0.3333333333333333, -0.5, 0.3333333333333333, -0.5, np.nan, np.nan],
[np.nan, 0.5, np.nan, 0.5, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, np.nan, np.nan]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
('array_0', 'array_0', 4, 'a'),
('array_0', 'array_0', 4, 'b'),
('array_1', 'array_1', 4, 'a'),
('array_1', 'array_1', 4, 'b'),
('array_2', 'array_2', 4, 'a'),
('array_2', 'array_2', 4, 'b')
], names=['trendlb_pos_th', 'trendlb_neg_th', 'trendlb_mode', None])
)
)
def test_BOLB(self):
pd.testing.assert_frame_equal(
vbt.BOLB.run(close_ts, window=1, pos_th=pos_ths, neg_th=neg_ths).labels,
pd.DataFrame(
np.array([
[1.0, -1.0, 0.0, 0.0, 0.0, 0.0],
[-1.0, 1.0, -1.0, 1.0, -1.0, 1.0],
[1.0, -1.0, 0.0, 0.0, 0.0, 0.0],
[0.0, -1.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 1.0, 0.0, 1.0, 0.0, 1.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
(1, 'array_0', 'array_0', 'a'),
(1, 'array_0', 'array_0', 'b'),
(1, 'array_1', 'array_1', 'a'),
(1, 'array_1', 'array_1', 'b'),
(1, 'array_2', 'array_2', 'a'),
(1, 'array_2', 'array_2', 'b')
], names=['bolb_window', 'bolb_pos_th', 'bolb_neg_th', None])
)
)
pd.testing.assert_frame_equal(
vbt.BOLB.run(close_ts, window=2, pos_th=pos_ths, neg_th=neg_ths).labels,
pd.DataFrame(
np.array([
[1.0, -1.0, 0.0, 0.0, 0.0, 0.0],
[-1.0, 1.0, -1.0, 1.0, -1.0, 1.0],
[1.0, -1.0, 1.0, -1.0, 0.0, 0.0],
[0.0, -1.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 1.0, 0.0, 1.0, 0.0, 1.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
]),
index=close_ts.index,
columns=pd.MultiIndex.from_tuples([
(2, 'array_0', 'array_0', 'a'),
(2, 'array_0', 'array_0', 'b'),
(2, 'array_1', 'array_1', 'a'),
(2, 'array_1', 'array_1', 'b'),
(2, 'array_2', 'array_2', 'a'),
(2, 'array_2', 'array_2', 'b')
], names=['bolb_window', 'bolb_pos_th', 'bolb_neg_th', None])
)
)