def regression_series(sx: pd.Series, sy: pd.Series, window: int):
new = [sx, sy]
df = pd.concat(new, axis=1, join='outer',)
values = df.values
index = df.index.values
x = values[:, 0]
y = values[:, 1]
x1 = array_windows(x, window=window)
y1 = array_windows(y, window=window)
m, b, r = regression(x1, y1)
m = append_nan(m, window)
b = append_nan(b, window)
r = append_nan(r, window)
return m, b, r, index
def test_intervals():
def _time_days_int_intervals(times, window_size):
"""Test WITHOUT NUMBA. Construct time intervals for windowing."""
tnum = len(times) - window_size
intervals = []
for ii in range(tnum):
interval = times[ii:ii + window_size]
intervals.append(interval)
return intervals
times = np.linspace(1, 100, 10000)
window_size = 20
_ = array_windows(times, window_size)
def test1():
return array_windows(times, window_size)
def test2():
return _time_days_int_intervals(times, window_size)
def test3():
return _array_windows(times, window_size)
time1 = timeit.timeit(test1, number=400)
time2 = timeit.timeit(test2, number=400)
time3 = timeit.timeit(test3, number=400)
print('Numba interval speed = ', time1)
print('Python interval speed = ', time2)
print('Numba 2 interval speed = ', time3)
assert time1 < time2
def __init__(self, sx: pd.Series, sy: pd.Series, window: int):
new = [sx, sy]
df = pd.concat(new, axis=1, join='outer',)
values = df.values
index = df.index.values
x = values[:, 0]
y = values[:, 1]
x1 = array_windows(x, window=window)
y1 = array_windows(y, window=window)
m, b, r = regression(x1, y1)
m = append_nan(m, window)
b = append_nan(b, window)
r = append_nan(r, window)
self.index = index
self.x = x
self.y = y
self.m = m
self.b = b
self.r = r
def test1():
return array_windows(times, window_size)
# -*- coding: utf-8 -*-
from numba import njit
from backtester.exceptions import NotEnoughDataError
import numpy as np
from backtester.indicators import array_windows
if __name__ == '__main__':
x = np.arange(5)
try:
y = array_windows(x, 40)
except NotEnoughDataError:
y = 'bob'