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test_signals.py
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2305 lines (2239 loc) · 81.8 KB
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from vectorbt.signals.enums import StopType
import vectorbt as vbt
from enum import Enum, IntEnum
from typing import Union
import numpy as np
import pandas as pd
from numba import njit
from datetime import datetime
import pytest
from vectorbt.signals import nb
seed = 42
day_dt = np.timedelta64(86400000000000)
sig = pd.DataFrame([
[True, False, False],
[False, True, False],
[False, False, True],
[True, False, False],
[False, True, False]
], index=pd.Index([
datetime(2020, 1, 1),
datetime(2020, 1, 2),
datetime(2020, 1, 3),
datetime(2020, 1, 4),
datetime(2020, 1, 5)
]), columns=['a', 'b', 'c'])
ts = pd.Series([1., 2., 3., 2., 1.], index=sig.index)
price = pd.DataFrame({
'open': [10, 11, 12, 11, 10],
'high': [11, 12, 13, 12, 11],
'low': [9, 10, 11, 10, 9],
'close': [10, 11, 12, 11, 10]
})
# ############# accessors.py ############# #
class TestAccessors:
def test_freq(self):
assert sig.vbt.signals.wrapper.freq == day_dt
assert sig['a'].vbt.signals.wrapper.freq == day_dt
assert sig.vbt.signals(freq='2D').wrapper.freq == day_dt * 2
assert sig['a'].vbt.signals(freq='2D').wrapper.freq == day_dt * 2
assert pd.Series([False, True]).vbt.signals.wrapper.freq is None
assert pd.Series([False, True]).vbt.signals(freq='3D').wrapper.freq == day_dt * 3
assert pd.Series([False, True]).vbt.signals(freq=np.timedelta64(4, 'D')).wrapper.freq == day_dt * 4
@pytest.mark.parametrize(
"test_n",
[1, 2, 3, 4, 5],
)
def test_fshift(self, test_n):
pd.testing.assert_series_equal(sig['a'].vbt.signals.fshift(test_n), sig['a'].shift(test_n, fill_value=False))
np.testing.assert_array_equal(
sig['a'].vbt.signals.fshift(test_n).values,
nb.fshift_1d_nb(sig['a'].values, test_n)
)
pd.testing.assert_frame_equal(sig.vbt.signals.fshift(test_n), sig.shift(test_n, fill_value=False))
def test_empty(self):
pd.testing.assert_series_equal(
pd.Series.vbt.signals.empty(5, index=np.arange(10, 15), name='a'),
pd.Series(np.full(5, False), index=np.arange(10, 15), name='a')
)
pd.testing.assert_frame_equal(
pd.DataFrame.vbt.signals.empty((5, 3), index=np.arange(10, 15), columns=['a', 'b', 'c']),
pd.DataFrame(np.full((5, 3), False), index=np.arange(10, 15), columns=['a', 'b', 'c'])
)
pd.testing.assert_series_equal(
pd.Series.vbt.signals.empty_like(sig['a']),
pd.Series(np.full(sig['a'].shape, False), index=sig['a'].index, name=sig['a'].name)
)
pd.testing.assert_frame_equal(
pd.DataFrame.vbt.signals.empty_like(sig),
pd.DataFrame(np.full(sig.shape, False), index=sig.index, columns=sig.columns)
)
def test_generate(self):
@njit
def choice_func_nb(from_i, to_i, col, n):
if col == 0:
return np.arange(from_i, to_i)
elif col == 1:
return np.full(1, from_i)
else:
return np.full(1, to_i - n)
pd.testing.assert_series_equal(
pd.Series.vbt.signals.generate(5, choice_func_nb, 1, index=sig['a'].index, name=sig['a'].name),
pd.Series(
np.array([True, True, True, True, True]),
index=sig['a'].index,
name=sig['a'].name
)
)
with pytest.raises(Exception) as e_info:
_ = pd.Series.vbt.signals.generate((5, 2), choice_func_nb, 1)
pd.testing.assert_frame_equal(
pd.DataFrame.vbt.signals.generate((5, 3), choice_func_nb, 1, index=sig.index, columns=sig.columns),
pd.DataFrame(
np.array([
[True, True, False],
[True, False, False],
[True, False, False],
[True, False, False],
[True, False, True]
]),
index=sig.index,
columns=sig.columns
)
)
def test_generate_both(self):
@njit
def entry_func_nb(from_i, to_i, col, temp_int):
temp_int[0] = from_i
return temp_int[:1]
@njit
def exit_func_nb(from_i, to_i, col, temp_int):
temp_int[0] = from_i
return temp_int[:1]
temp_int = np.empty((sig.shape[0],), dtype=np.int_)
en, ex = pd.Series.vbt.signals.generate_both(
5, entry_func_nb, exit_func_nb, (temp_int,), (temp_int,),
index=sig['a'].index, name=sig['a'].name)
pd.testing.assert_series_equal(
en,
pd.Series(
np.array([True, False, True, False, True]),
index=sig['a'].index,
name=sig['a'].name
)
)
pd.testing.assert_series_equal(
ex,
pd.Series(
np.array([False, True, False, True, False]),
index=sig['a'].index,
name=sig['a'].name
)
)
en, ex = pd.DataFrame.vbt.signals.generate_both(
(5, 3), entry_func_nb, exit_func_nb, (temp_int,), (temp_int,),
index=sig.index, columns=sig.columns)
pd.testing.assert_frame_equal(
en,
pd.DataFrame(
np.array([
[True, True, True],
[False, False, False],
[True, True, True],
[False, False, False],
[True, True, True]
]),
index=sig.index,
columns=sig.columns
)
)
pd.testing.assert_frame_equal(
ex,
pd.DataFrame(
np.array([
[False, False, False],
[True, True, True],
[False, False, False],
[True, True, True],
[False, False, False]
]),
index=sig.index,
columns=sig.columns
)
)
en, ex = pd.Series.vbt.signals.generate_both(
(5,), entry_func_nb, exit_func_nb, (temp_int,), (temp_int,),
index=sig['a'].index, name=sig['a'].name, entry_wait=1, exit_wait=0)
pd.testing.assert_series_equal(
en,
pd.Series(
np.array([True, True, True, True, True]),
index=sig['a'].index,
name=sig['a'].name
)
)
pd.testing.assert_series_equal(
ex,
pd.Series(
np.array([True, True, True, True, True]),
index=sig['a'].index,
name=sig['a'].name
)
)
en, ex = pd.Series.vbt.signals.generate_both(
(5,), entry_func_nb, exit_func_nb, (temp_int,), (temp_int,),
index=sig['a'].index, name=sig['a'].name, entry_wait=0, exit_wait=1)
pd.testing.assert_series_equal(
en,
pd.Series(
np.array([True, True, True, True, True]),
index=sig['a'].index,
name=sig['a'].name
)
)
pd.testing.assert_series_equal(
ex,
pd.Series(
np.array([False, True, True, True, True]),
index=sig['a'].index,
name=sig['a'].name
)
)
def test_generate_exits(self):
@njit
def choice_func_nb(from_i, to_i, col, temp_int):
temp_int[0] = from_i
return temp_int[:1]
temp_int = np.empty((sig.shape[0],), dtype=np.int_)
pd.testing.assert_series_equal(
sig['a'].vbt.signals.generate_exits(choice_func_nb, temp_int),
pd.Series(
np.array([False, True, False, False, True]),
index=sig['a'].index,
name=sig['a'].name
)
)
pd.testing.assert_frame_equal(
sig.vbt.signals.generate_exits(choice_func_nb, temp_int),
pd.DataFrame(
np.array([
[False, False, False],
[True, False, False],
[False, True, False],
[False, False, True],
[True, False, False]
]),
index=sig.index,
columns=sig.columns
)
)
pd.testing.assert_frame_equal(
sig.vbt.signals.generate_exits(choice_func_nb, temp_int, wait=0),
pd.DataFrame(
np.array([
[True, False, False],
[False, True, False],
[False, False, True],
[True, False, False],
[False, True, False]
]),
index=sig.index,
columns=sig.columns
)
)
def test_generate_random(self):
pd.testing.assert_series_equal(
pd.Series.vbt.signals.generate_random(
5, n=3, seed=seed, index=sig['a'].index, name=sig['a'].name),
pd.Series(
np.array([False, True, True, False, True]),
index=sig['a'].index,
name=sig['a'].name
)
)
with pytest.raises(Exception) as e_info:
_ = pd.Series.vbt.signals.generate_random((5, 2), n=3)
pd.testing.assert_frame_equal(
pd.DataFrame.vbt.signals.generate_random(
(5, 3), n=3, seed=seed, index=sig.index, columns=sig.columns),
pd.DataFrame(
np.array([
[False, False, True],
[True, True, True],
[True, True, False],
[False, True, True],
[True, False, False]
]),
index=sig.index,
columns=sig.columns
)
)
pd.testing.assert_frame_equal(
pd.DataFrame.vbt.signals.generate_random(
(5, 3), n=[0, 1, 2], seed=seed, index=sig.index, columns=sig.columns),
pd.DataFrame(
np.array([
[False, False, True],
[False, False, True],
[False, False, False],
[False, True, False],
[False, False, False]
]),
index=sig.index,
columns=sig.columns
)
)
pd.testing.assert_series_equal(
pd.Series.vbt.signals.generate_random(
5, prob=0.5, seed=seed, index=sig['a'].index, name=sig['a'].name),
pd.Series(
np.array([True, False, False, False, True]),
index=sig['a'].index,
name=sig['a'].name
)
)
with pytest.raises(Exception) as e_info:
_ = pd.Series.vbt.signals.generate_random((5, 2), prob=3)
pd.testing.assert_frame_equal(
pd.DataFrame.vbt.signals.generate_random(
(5, 3), prob=0.5, seed=seed, index=sig.index, columns=sig.columns),
pd.DataFrame(
np.array([
[True, True, True],
[False, True, False],
[False, False, False],
[False, False, True],
[True, False, True]
]),
index=sig.index,
columns=sig.columns
)
)
pd.testing.assert_frame_equal(
pd.DataFrame.vbt.signals.generate_random(
(5, 3), prob=[0., 0.5, 1.], seed=seed, index=sig.index, columns=sig.columns),
pd.DataFrame(
np.array([
[False, True, True],
[False, True, True],
[False, False, True],
[False, False, True],
[False, False, True]
]),
index=sig.index,
columns=sig.columns
)
)
with pytest.raises(Exception) as e_info:
pd.DataFrame.vbt.signals.generate_random((5, 3))
def test_generate_random_exits(self):
pd.testing.assert_series_equal(
sig['a'].vbt.signals.generate_random_exits(seed=seed),
pd.Series(
np.array([False, False, True, False, True]),
index=sig['a'].index,
name=sig['a'].name
)
)
pd.testing.assert_frame_equal(
sig.vbt.signals.generate_random_exits(seed=seed),
pd.DataFrame(
np.array([
[False, False, False],
[False, False, False],
[True, True, False],
[False, False, False],
[True, False, True]
]),
index=sig.index,
columns=sig.columns
)
)
pd.testing.assert_frame_equal(
sig.vbt.signals.generate_random_exits(seed=seed, wait=0),
pd.DataFrame(
np.array([
[True, False, False],
[False, False, False],
[False, True, False],
[False, False, True],
[True, True, False]
]),
index=sig.index,
columns=sig.columns
)
)
pd.testing.assert_series_equal(
sig['a'].vbt.signals.generate_random_exits(prob=1., seed=seed),
pd.Series(
np.array([False, True, False, False, True]),
index=sig['a'].index,
name=sig['a'].name
)
)
pd.testing.assert_frame_equal(
sig.vbt.signals.generate_random_exits(prob=1., seed=seed),
pd.DataFrame(
np.array([
[False, False, False],
[True, False, False],
[False, True, False],
[False, False, True],
[True, False, False]
]),
index=sig.index,
columns=sig.columns
)
)
pd.testing.assert_frame_equal(
sig.vbt.signals.generate_random_exits(prob=[0., 0.5, 1.], seed=seed),
pd.DataFrame(
np.array([
[False, False, False],
[False, False, False],
[False, False, False],
[False, True, True],
[False, False, False]
]),
index=sig.index,
columns=sig.columns
)
)
pd.testing.assert_frame_equal(
sig.vbt.signals.generate_random_exits(prob=1., wait=0, seed=seed),
pd.DataFrame(
np.array([
[True, False, False],
[False, True, False],
[False, False, True],
[True, False, False],
[False, True, False]
]),
index=sig.index,
columns=sig.columns
)
)
def test_generate_random_both(self):
# n
en, ex = pd.Series.vbt.signals.generate_random_both(
5, n=2, seed=seed, index=sig['a'].index, name=sig['a'].name)
pd.testing.assert_series_equal(
en,
pd.Series(
np.array([True, False, True, False, False]),
index=sig['a'].index,
name=sig['a'].name
)
)
pd.testing.assert_series_equal(
ex,
pd.Series(
np.array([False, True, False, False, True]),
index=sig['a'].index,
name=sig['a'].name
)
)
en, ex = pd.DataFrame.vbt.signals.generate_random_both(
(5, 3), n=2, seed=seed, index=sig.index, columns=sig.columns)
pd.testing.assert_frame_equal(
en,
pd.DataFrame(
np.array([
[True, True, True],
[False, False, False],
[True, True, False],
[False, False, True],
[False, False, False]
]),
index=sig.index,
columns=sig.columns
)
)
pd.testing.assert_frame_equal(
ex,
pd.DataFrame(
np.array([
[False, False, False],
[True, True, True],
[False, False, False],
[False, True, False],
[True, False, True]
]),
index=sig.index,
columns=sig.columns
)
)
en, ex = pd.DataFrame.vbt.signals.generate_random_both(
(5, 3), n=[0, 1, 2], seed=seed, index=sig.index, columns=sig.columns)
pd.testing.assert_frame_equal(
en,
pd.DataFrame(
np.array([
[False, False, True],
[False, True, False],
[False, False, False],
[False, False, True],
[False, False, False]
]),
index=sig.index,
columns=sig.columns
)
)
pd.testing.assert_frame_equal(
ex,
pd.DataFrame(
np.array([
[False, False, False],
[False, False, True],
[False, False, False],
[False, True, False],
[False, False, True]
]),
index=sig.index,
columns=sig.columns
)
)
en, ex = pd.DataFrame.vbt.signals.generate_random_both((2, 3), n=2, seed=seed, entry_wait=1, exit_wait=0)
pd.testing.assert_frame_equal(
en,
pd.DataFrame(
np.array([
[True, True, True],
[True, True, True],
])
)
)
pd.testing.assert_frame_equal(
ex,
pd.DataFrame(
np.array([
[True, True, True],
[True, True, True]
])
)
)
en, ex = pd.DataFrame.vbt.signals.generate_random_both((3, 3), n=2, seed=seed, entry_wait=0, exit_wait=1)
pd.testing.assert_frame_equal(
en,
pd.DataFrame(
np.array([
[True, True, True],
[True, True, True],
[False, False, False]
])
)
)
pd.testing.assert_frame_equal(
ex,
pd.DataFrame(
np.array([
[False, False, False],
[True, True, True],
[True, True, True],
])
)
)
en, ex = pd.DataFrame.vbt.signals.generate_random_both((7, 3), n=2, seed=seed, entry_wait=2, exit_wait=2)
pd.testing.assert_frame_equal(
en,
pd.DataFrame(
np.array([
[True, True, True],
[False, False, False],
[False, False, False],
[False, False, False],
[True, True, True],
[False, False, False],
[False, False, False]
])
)
)
pd.testing.assert_frame_equal(
ex,
pd.DataFrame(
np.array([
[False, False, False],
[False, False, False],
[True, True, True],
[False, False, False],
[False, False, False],
[False, False, False],
[True, True, True]
])
)
)
n = 10
a = np.full(n * 2, 0.)
for i in range(10000):
en, ex = pd.Series.vbt.signals.generate_random_both(1000, n, entry_wait=2, exit_wait=2)
_a = np.empty((n * 2,), dtype=np.int_)
_a[0::2] = np.flatnonzero(en)
_a[1::2] = np.flatnonzero(ex)
a += _a
greater = a > 10000000 / (2 * n + 1) * np.arange(0, 2 * n)
less = a < 10000000 / (2 * n + 1) * np.arange(2, 2 * n + 2)
assert np.all(greater & less)
# probs
en, ex = pd.Series.vbt.signals.generate_random_both(
5, entry_prob=0.5, exit_prob=1., seed=seed, index=sig['a'].index, name=sig['a'].name)
pd.testing.assert_series_equal(
en,
pd.Series(
np.array([True, False, False, False, True]),
index=sig['a'].index,
name=sig['a'].name
)
)
pd.testing.assert_series_equal(
ex,
pd.Series(
np.array([False, True, False, False, False]),
index=sig['a'].index,
name=sig['a'].name
)
)
en, ex = pd.DataFrame.vbt.signals.generate_random_both(
(5, 3), entry_prob=0.5, exit_prob=1., seed=seed, index=sig.index, columns=sig.columns)
pd.testing.assert_frame_equal(
en,
pd.DataFrame(
np.array([
[True, True, True],
[False, False, False],
[False, False, False],
[False, False, True],
[True, False, False]
]),
index=sig.index,
columns=sig.columns
)
)
pd.testing.assert_frame_equal(
ex,
pd.DataFrame(
np.array([
[False, False, False],
[True, True, True],
[False, False, False],
[False, False, False],
[False, False, True]
]),
index=sig.index,
columns=sig.columns
)
)
en, ex = pd.DataFrame.vbt.signals.generate_random_both(
(5, 3), entry_prob=[0., 0.5, 1.], exit_prob=[0., 0.5, 1.],
seed=seed, index=sig.index, columns=sig.columns)
pd.testing.assert_frame_equal(
en,
pd.DataFrame(
np.array([
[False, True, True],
[False, False, False],
[False, False, True],
[False, False, False],
[False, False, True]
]),
index=sig.index,
columns=sig.columns
)
)
pd.testing.assert_frame_equal(
ex,
pd.DataFrame(
np.array([
[False, False, False],
[False, True, True],
[False, False, False],
[False, False, True],
[False, False, False]
]),
index=sig.index,
columns=sig.columns
)
)
en, ex = pd.DataFrame.vbt.signals.generate_random_both(
(5, 3), entry_prob=1., exit_prob=1., exit_wait=0,
seed=seed, index=sig.index, columns=sig.columns)
pd.testing.assert_frame_equal(
en,
pd.DataFrame(
np.array([
[True, True, True],
[True, True, True],
[True, True, True],
[True, True, True],
[True, True, True]
]),
index=sig.index,
columns=sig.columns
)
)
pd.testing.assert_frame_equal(
ex,
pd.DataFrame(
np.array([
[True, True, True],
[True, True, True],
[True, True, True],
[True, True, True],
[True, True, True]
]),
index=sig.index,
columns=sig.columns
)
)
# none
with pytest.raises(Exception) as e_info:
pd.DataFrame.vbt.signals.generate_random((5, 3))
def test_generate_stop_exits(self):
e = pd.Series([True, False, False, False, False, False])
t = pd.Series([2, 3, 4, 3, 2, 1]).astype(np.float64)
# stop loss
pd.testing.assert_series_equal(
e.vbt.signals.generate_stop_exits(t, -0.1),
pd.Series(np.array([False, False, False, False, False, True]))
)
pd.testing.assert_series_equal(
e.vbt.signals.generate_stop_exits(t, -0.1, trailing=True),
pd.Series(np.array([False, False, False, True, False, False]))
)
pd.testing.assert_series_equal(
e.vbt.signals.generate_stop_exits(t, -0.1, trailing=True, first=False),
pd.Series(np.array([False, False, False, True, True, True]))
)
pd.testing.assert_frame_equal(
e.vbt.signals.generate_stop_exits(t.vbt.tile(3), [-0., -0.5, -1.], trailing=True, first=False),
pd.DataFrame(np.array([
[False, False, False],
[False, False, False],
[False, False, False],
[False, False, False],
[False, True, False],
[False, True, False]
]))
)
pd.testing.assert_series_equal(
e.vbt.signals.generate_stop_exits(t, -0.1, trailing=True, exit_wait=3),
pd.Series(np.array([False, False, False, False, True, False]))
)
# take profit
pd.testing.assert_series_equal(
e.vbt.signals.generate_stop_exits(4 - t, 0.1),
pd.Series(np.array([False, False, False, False, False, True]))
)
pd.testing.assert_series_equal(
e.vbt.signals.generate_stop_exits(4 - t, 0.1, trailing=True),
pd.Series(np.array([False, False, False, True, False, False]))
)
pd.testing.assert_series_equal(
e.vbt.signals.generate_stop_exits(4 - t, 0.1, trailing=True, first=False),
pd.Series(np.array([False, False, False, True, True, True]))
)
pd.testing.assert_frame_equal(
e.vbt.signals.generate_stop_exits((4 - t).vbt.tile(3), [0., 0.5, 1.], trailing=True, first=False),
pd.DataFrame(np.array([
[False, False, False],
[False, False, False],
[False, False, False],
[False, True, True],
[False, True, True],
[False, True, True]
]))
)
pd.testing.assert_series_equal(
e.vbt.signals.generate_stop_exits(4 - t, 0.1, trailing=True, exit_wait=3),
pd.Series(np.array([False, False, False, False, True, False]))
)
# iteratively
e = pd.Series([True, True, True, True, True, True])
en, ex = e.vbt.signals.generate_stop_exits(t, -0.1, trailing=True, iteratively=True)
pd.testing.assert_series_equal(
en,
pd.Series(np.array([True, False, False, False, True, False]))
)
pd.testing.assert_series_equal(
ex,
pd.Series(np.array([False, False, False, True, False, True]))
)
en, ex = e.vbt.signals.generate_stop_exits(t, -0.1, trailing=True, entry_wait=2, iteratively=True)
pd.testing.assert_series_equal(
en,
pd.Series(np.array([True, False, False, False, False, True]))
)
pd.testing.assert_series_equal(
ex,
pd.Series(np.array([False, False, False, True, False, False]))
)
en, ex = e.vbt.signals.generate_stop_exits(t, -0.1, trailing=True, exit_wait=2, iteratively=True)
pd.testing.assert_series_equal(
en,
pd.Series(np.array([True, False, False, False, True, False]))
)
pd.testing.assert_series_equal(
ex,
pd.Series(np.array([False, False, False, True, False, False]))
)
def test_generate_ohlc_stop_exits(self):
pd.testing.assert_frame_equal(
sig.vbt.signals.generate_stop_exits(ts, -0.1),
sig.vbt.signals.generate_ohlc_stop_exits(ts, sl_stop=0.1)
)
pd.testing.assert_frame_equal(
sig.vbt.signals.generate_stop_exits(ts, -0.1, trailing=True),
sig.vbt.signals.generate_ohlc_stop_exits(ts, ts_stop=0.1)
)
pd.testing.assert_frame_equal(
sig.vbt.signals.generate_stop_exits(ts, 0.1),
sig.vbt.signals.generate_ohlc_stop_exits(ts, tp_stop=0.1)
)
def _test_ohlc_stop_exits(**kwargs):
out_dict = {'hit_price': np.nan, 'stop_type': -1}
result = sig.vbt.signals.generate_ohlc_stop_exits(
price['open'], price['high'], price['low'], price['close'],
out_dict=out_dict, **kwargs
)
if isinstance(result, tuple):
_, ex = result
else:
ex = result
return result, out_dict['hit_price'], out_dict['stop_type']
ex, hit_price, stop_type = _test_ohlc_stop_exits()
pd.testing.assert_frame_equal(
ex,
pd.DataFrame(np.array([
[False, False, False],
[False, False, False],
[False, False, False],
[False, False, False],
[False, False, False]
]), index=sig.index, columns=sig.columns)
)
pd.testing.assert_frame_equal(
hit_price,
pd.DataFrame(np.array([
[np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan]
]), index=sig.index, columns=sig.columns)
)
pd.testing.assert_frame_equal(
stop_type,
pd.DataFrame(np.array([
[-1, -1, -1],
[-1, -1, -1],
[-1, -1, -1],
[-1, -1, -1],
[-1, -1, -1]
]), index=sig.index, columns=sig.columns)
)
ex, hit_price, stop_type = _test_ohlc_stop_exits(sl_stop=0.1)
pd.testing.assert_frame_equal(
ex,
pd.DataFrame(np.array([
[False, False, False],
[False, False, False],
[False, False, False],
[False, False, True],
[True, False, False]
]), index=sig.index, columns=sig.columns)
)
pd.testing.assert_frame_equal(
hit_price,
pd.DataFrame(np.array([
[np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan],
[np.nan, np.nan, 10.8],
[9.9, np.nan, np.nan]
]), index=sig.index, columns=sig.columns)
)
pd.testing.assert_frame_equal(
stop_type,
pd.DataFrame(np.array([
[-1, -1, -1],
[-1, -1, -1],
[-1, -1, -1],
[-1, -1, 0],
[0, -1, -1]
]), index=sig.index, columns=sig.columns)
)
ex, hit_price, stop_type = _test_ohlc_stop_exits(ts_stop=0.1)
pd.testing.assert_frame_equal(
ex,
pd.DataFrame(np.array([
[False, False, False],
[False, False, False],
[False, False, False],
[False, True, True],
[True, False, False]
]), index=sig.index, columns=sig.columns)
)
pd.testing.assert_frame_equal(
hit_price,
pd.DataFrame(np.array([
[np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan],
[np.nan, 11.7, 10.8],
[9.9, np.nan, np.nan]
]), index=sig.index, columns=sig.columns)
)
pd.testing.assert_frame_equal(
stop_type,
pd.DataFrame(np.array([
[-1, -1, -1],
[-1, -1, -1],
[-1, -1, -1],
[-1, 1, 1],
[1, -1, -1]
]), index=sig.index, columns=sig.columns)
)
ex, hit_price, stop_type = _test_ohlc_stop_exits(tp_stop=0.1)
pd.testing.assert_frame_equal(
ex,
pd.DataFrame(np.array([
[False, False, False],
[True, False, False],
[False, True, False],
[False, False, False],
[False, False, False]
]), index=sig.index, columns=sig.columns)
)
pd.testing.assert_frame_equal(
hit_price,
pd.DataFrame(np.array([
[np.nan, np.nan, np.nan],
[11.0, np.nan, np.nan],
[np.nan, 12.1, np.nan],
[np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan]
]), index=sig.index, columns=sig.columns)
)
pd.testing.assert_frame_equal(
stop_type,
pd.DataFrame(np.array([
[-1, -1, -1],
[2, -1, -1],
[-1, 2, -1],
[-1, -1, -1],
[-1, -1, -1]
]), index=sig.index, columns=sig.columns)
)
ex, hit_price, stop_type = _test_ohlc_stop_exits(sl_stop=0.1, ts_stop=0.1, tp_stop=0.1)
pd.testing.assert_frame_equal(
ex,
pd.DataFrame(np.array([
[False, False, False],
[True, False, False],
[False, True, False],
[False, False, True],
[True, False, False]
]), index=sig.index, columns=sig.columns)
)
pd.testing.assert_frame_equal(
hit_price,
pd.DataFrame(np.array([
[np.nan, np.nan, np.nan],
[11.0, np.nan, np.nan],
[np.nan, 12.1, np.nan],
[np.nan, np.nan, 10.8],
[9.9, np.nan, np.nan]
]), index=sig.index, columns=sig.columns)
)
pd.testing.assert_frame_equal(
stop_type,
pd.DataFrame(np.array([
[-1, -1, -1],
[2, -1, -1],
[-1, 2, -1],
[-1, -1, 0],
[0, -1, -1]
]), index=sig.index, columns=sig.columns)
)
ex, hit_price, stop_type = _test_ohlc_stop_exits(
sl_stop=[0., 0.1, 0.2], ts_stop=[0., 0.1, 0.2], tp_stop=[0., 0.1, 0.2])
pd.testing.assert_frame_equal(
ex,
pd.DataFrame(np.array([
[False, False, False],
[False, False, False],
[False, True, False],
[False, False, False],
[False, False, True]
]), index=sig.index, columns=sig.columns)
)
pd.testing.assert_frame_equal(
hit_price,