def compute_resistance_support_line(opening, high, low, close):
price_data = db.get_realtime_Data(trading_symbol, frame_size)
print "compute_resistance_support_line"
support_lines, resistance_lines = compute_support_resistance(
opening, high, low, close)
support_end_points = []
good_support = []
support_slope = []
for l in reversed(support_lines[-7:]):
good_support.append(l["line"])
support_slope.append(l["line"].slope)
support_end_points.append(l["line"].get_y(0))
support_end_points.append(l["line"].get_y(frame_size))
good_resisitance = []
resistance_slope = []
resistance_end_points = []
for l in reversed(resistance_lines[-7:]):
good_resisitance.append(l["line"])
resistance_slope.append(l["line"].slope)
resistance_end_points.append(l["line"].get_y(0))
resistance_end_points.append(l["line"].get_y(frame_size))
normalize_slope_val = max(resistance_end_points) - min(support_end_points)
resistance_slope.remove(max(resistance_slope))
resistance_slope.remove(min(resistance_slope))
support_slope.remove(max(support_slope))
support_slope.remove(min(support_slope))
good_lines = []
for index in range(2):
good_lines.append([good_support[index], good_resisitance[index]])
final_support = Line(2, 2, 1, 1)
final_support.slope = (good_lines[0][0].slope + good_lines[1][0].slope) / 2
final_support.intercept = (good_lines[0][0].intercept +
good_lines[1][0].intercept) / 2
final_resistance = Line(2, 2, 1, 1)
final_resistance.slope = (good_lines[0][1].slope +
good_lines[1][1].slope) / 2
final_resistance.intercept = (good_lines[0][1].intercept +
good_lines[1][1].intercept) / 2
return (final_support, final_resistance)
return result
raw_training_data = get_ML_data_for_resistance_support(start_time=20160213,
end_time=20160213)
training_data = []
training_result = []
for chunk in raw_training_data:
unixtime, opening, high, low, close, good_result = chunk
print(len(opening))
for index in range(101, len(opening)):
if good_result[index] != 0.0:
print "good_result"
support_lines, resistance_lines = compute_support_resistance(
opening[index - 26:index - 2], high[index - 26:index - 2],
low[index - 26:index - 2], close[index - 26:index - 2])
support_line, resistance_line = choose_best_line(
resistance_lines, support_lines, 25)
resistance_line_val = resistance_line.get_y(25)
support_line_val = support_line.get_y(25)
print(support_line_val, resistance_line_val,
support_line_val < resistance_line_val)
# time_s = []
# for t in unixtime[index - 101:index]:
# time_s.append(datetime.datetime.fromtimestamp(t))
# Plot.plot_day_candle(time_s, opening[index - 101:index], high[index - 101:index], low[index - 101:index], close[index - 101:index], 26, "EURUSD", lines=[[support_line],[resistance_line]], save=True)
if resistance_line_val > support_line_val:
features_arr = []
if resistance_line.slope > 0:
features_arr.append(0)
import math
from SupportResistance import compute_support_resistance, parse_historical_data
from matplotlib.dates import date2num
db = Database()
currency_data = db.get_range_currency_date("EURUSD", 20160223, 20160523)
for day_data in currency_data:
frame_size = 30
frame = []
support_slope_arr = []
resistance_slope_arr = []
# for frame_size in range(20,30):
frame, opening, high, low, close = parse_historical_data(
day_data["minute_price"], frame_size=frame_size)
resistance_lines, support_lines = compute_support_resistance(
opening[:-1], high[:-1], low[:-1], close[:-1])
support_end_points = []
good_support = []
support_slope = []
for l in reversed(support_lines[-7:]):
good_support.append(l["line"])
support_slope.append(l["line"].slope)
support_end_points.append(l["line"].get_y(0))
support_end_points.append(l["line"].get_y(frame_size))
good_resisitance = []
resistance_slope = []
resistance_end_points = []
for l in reversed(resistance_lines[-7:]):
good_resisitance.append(l["line"])