def test_frdist4(self):
N = 80
P = [[i, i] for i in range(N)]
Q = [[N + i, N + i] for i in range(N)]
res = frdist(P, Q)
ans = 80 * (2**0.5)
self.assertEqual(res, ans)
def test_frdist3(self):
N = 100
P = [[i, i % 10] for i in range(N)]
Q = [[i, (i + 1) % 10] for i in range(N - 1)]
Q.append([N - 1, N % 10])
res = frdist(P, Q)
ans = 9
self.assertEqual(res, ans)
def test_frdist(self):
P = [[1, 1], [2, 1], [2, 2]]
Q = [[2, 2], [0, 1], [2, 4]]
res = frdist(P, Q)
ans = 2.0
self.assertEqual(res, ans)
def test_frdist5(self):
N = 80
for _ in range(5000):
P = [[i, i] for i in range(N)]
Q = [[N + i, N + i] for i in range(N)]
res = frdist(P, Q)
def capture_chart_pattern(cls,
code,
pattern,
db,
threshold=None,
window_size=60,
window_move=None,
group='1',
price_opt='c',
moving_avg=None,
min_diff_ratio=0,
max_diff_ratio=float('inf'),
start_date=None,
end_date=None):
"""
Insert data into this class when chart pattern is found by frechet distance way.
:param code:[str]company code
:param pattern: [(1,) int list] pattern to find out (its length must be window size or less)
:param threshold: [float]chart similarity threshold
:param window_size: [int]chart pattern window size
:param window_move: [int]window moving value in chart
:param group: [str]when inserting, set group value (default '1')
:param price_opt: [str]price option(only close, close+open, ...)
:param moving_avg: [int] moving average
:param min_diff_ratio: [float] minimum chart difference ratio (percent unit)
:param max_diff_ratio: [float] maximum chart difference ratio (percent unit)
:param start_date: [date]chart start date
:param end_date: [date]chart end date
:return: no return, this method insert test data that pattern matched
"""
if window_move is None:
window_move = window_size // 10
with db:
if start_date and end_date:
chart = db.get_range_from_chart(code, start_date, end_date)
else:
chart = db.get_all_from_chart(code)
chart = cls._choose_chart_price(chart, price_opt,
moving_avg) # DataFrame type
fr_pat = cls._trans_pat_to_frpat(pattern, window_size)
max_pat, min_pat = max(pattern), min(pattern)
pat_diff = max_pat - min_pat
if threshold is None:
threshold = (window_size * pat_diff) / 200
days = 0
captured = []
while days < len(chart):
part_chart = chart[days:days + window_size]
if len(part_chart) < window_size:
break
max_val, min_val = max(part_chart), min(part_chart)
cht_diff = max_val - min_val
cht_diff_ratio = cht_diff / min_val * 100 # percent unit
if min_val == 0 or cht_diff == 0:
days += window_move
continue
if min_diff_ratio <= cht_diff_ratio <= max_diff_ratio:
fr_cht = (part_chart - min_val) * (pat_diff /
cht_diff) + min_pat
fr_cht = [[j, data] for j, data in enumerate(fr_cht)
] # convert pd.Series to list
if frdist(fr_cht, fr_pat) < threshold:
date = chart.index[days + window_size - 1]
captured.append([code, date, group])
days += window_size
continue
days += window_move
return captured