def _passed_to(self, datei, point, last_pm=0):
'''
return (True/False:If passed, Int:-1=out to down, 0=on, 1=out to up)
'''
ret = (False, 0)
if point <= 0:
return ret
(open, high, low, close, volume) = self._get_prices(datei, 2)
tp = (high[1]+low[1]+close[1])/3
boxsize = kf.get_bollinger_boxsize(tp)
cmp = tp - point
if abs(cmp) < boxsize:
return ret
if max(high) >= point and min(low) <= point:
if cmp > 0 and last_pm <= 0:
return (True, 1)
elif cmp < 0 and last_pm >= 0:
return (True, -1)
else:
return ret
else:
if cmp > 0:
return (False, 1)
elif cmp < 0:
return (False, -1)
else:
return ret
def _get_nearbys(self, price, points):
points.insert(0, price)
order = np.argsort(points)
bef = []
aft = []
boxsize = kf.get_bollinger_boxsize(price)
for j in range(order):
i = order[j]
if i == 0:
if j > 0:
bef = [order[j-1]]
k=j-2
while k>=0:
if points[order[k]] >= bef - boxsize:
bef.append(order[k])
k -= 1
if j < len(order):
aft = order[j+1]
k=j+2
while k<len(order):
if points[order[k]] <= aft + boxsize:
aft.append(order[k])
k += 1
return bef, aft
def _passed_to(self, datei, point):
'''
return (True/False:If passed, Int:-1=out to down, 0=on, 1=out to up)
'''
(open, high, low, close) = self._get_prices(datei, 2)
tp = (high[1]+low[1]+close[1])/3
boxsize = kf.get_bollinger_boxsize(point)
cpm = tp - point
if abs(cpm) < boxsize:
return (True, 0)
if max(high) >= point and min(low) <= point:
if cmp > 0:
return (True, 1)
elif cmp < 0:
return (True, -1)
else:
return (True, 0)
else:
if cmp > 0:
return (False, 1)
elif cmp < 0:
return (False, -1)
else:
return (False, 0)
def _get_nearest_line_idxs(self, datei, line_points, exclude_idxs, trend):
(open, high, low, close) = self._get_prices(datei, 1)
tp = (high+low+close)/3
line_points.append(tp)
tp_idx = len(line_points)-1
order = np.argsort(line_points)
tp_order = -1
ex_order = [-1]*len(exclude_idxs)
for i in range(len(order)):
if order[i] == tp_idx:
tp_order = i
for j in range(len(exclude_idxs)):
exi = exclude_idxs[j]
if order[i] == exi:
ex_order[j] = i
boxsize = kf.get_bollinger_boxsize(tp)
nearest_line_idxs = []
if tp_order > max(ex_order):
if trend == "up":
if tp_order == len(order)-1:
return [-1]
else:
for i in range(tp_order+1,len(order)):
if len(nearest_line_idxs) == 0:
nearest_line_idxs = [order[i]]
else:
curr_point_idx = order[i]
pre_point_idx = nearest_line_idxs[-1]
if line_points[curr_point_idx] - boxsize <= line_points[pre_point_idx]:
nearest_line_idxs.append(curr_point_idx)
else:
return []
if tp_order < min(ex_order):
if trend == "down":
if tp_order == 0:
return [-1]
else:
r = range(tp_order).sort(reverse=True)
for i in r:
if len(nearest_line_idxs) == 0:
nearest_line_idxs = [order[i]]
else:
curr_point_idx = order[i]
pre_point_idx = nearest_line_idxs[-1]
if line_points[curr_point_idx] + boxsize >= line_points[pre_point_idx]:
nearest_line_idxs.append(curr_point_idx)
else:
return []
return nearest_line_idxs
def _get_touched_line_idxs(self, datei, line_points):
(open, high, low, close) = self._get_prices(datei, 2)
h = max(high)
l = min(low)
touched_line_idxs = []
price = (high[-1]+low[-1]+close[-1])/3
boxsize = kf.get_bollinger_boxsize(price)
i = 0
for i in range(line_points):
lp = line_points[i]
if h+boxsize >= lp and l-boxsize <= lp:
touched_line_idxs.append(i)
return touched_line_idxs
def _get_trend_lines(self, joints, indexes, pmmask):
j = 5
trend_lines = {}
for i in range(5, len(indexes)):
if pmmask[i] != pmmask[i-2] or pmmask[i] != pmmask[i-4]:
continue
df = indexes[i]-indexes[i-4]
if df != 0:
slope = (joints[i]-joints[i-4])*1.0/df
else:
slope = 0
const = joints[i-4]-slope*indexes[i-4]
midrp = joints[i-2]
midlp = self._eq(indexes[i-2], slope, const)
boxsize = kf.get_bollinger_boxsize(midrp)
if midlp - boxsize <= midrp and midlp + boxsize >= midrp:
for d in range(indexes[i], indexes[i] + indexes[i]-indexes[i-4]+1):
if trend_lines.has_key(d) == False:
trend_lines[d] = []
trend_lines[d].append(self._eq(d, slope, const))
j += 1
self.trend_lines = trend_lines