def CubicCurve(positions, t, screen, color, curve_list, green, blue, quad_curve, quad_curve1, quad_curve2):
P0_x = pow((1 - t), 3) * positions[0].x
P0_y = pow((1 - t), 3) * positions[0].y
P1_x = 3 * pow((1-t), 2) * t * positions[1].x
P1_y = 3 * pow((1-t), 2) * t * positions[1].y
P2_x = 3 * (1-t) * pow(t, 2) * positions[2].x
P2_y = 3 * (1-t) * pow(t, 2) * positions[2].y
P3_x = pow(t, 3) * positions[3].x
P3_y = pow(t, 3) * positions[3].y
curve = (P0_x + P1_x + P2_x + P3_x, P0_y + P1_y + P2_y + P3_y)
pygame.draw.line(screen, (0, 0, 0), (positions[0].x, positions[0].y), (positions[1].x, positions[1].y), 1)
pygame.draw.line(screen, (0, 0, 0), (positions[1].x, positions[1].y), (positions[2].x, positions[2].y), 1)
pygame.draw.line(screen, (0, 0, 0), (positions[2].x, positions[2].y), (positions[3].x, positions[3].y), 1)
first_line = [positions[0], positions[1]]
second_line = [positions[1], positions[2]]
third_line = [positions[2], positions[3]]
fourth_line = [positions[0], positions[1], positions[2]]
fifth_line = [positions[1], positions[2], positions[3]]
sixth_line = [positions[0], positions[2], positions[3]]
a = LinearCurve(first_line, t, screen, green, False)
b = LinearCurve(second_line, t, screen, green, False)
c = LinearCurve(third_line, t, screen, green, False)
pygame.draw.line(screen, green, a, b, 2)
pygame.draw.line(screen, green, b, c, 2)
QuadraticCurve(fourth_line, t, screen, (100, 100, 0), quad_curve, green)
QuadraticCurve(fifth_line, t, screen, (100, 100, 0), quad_curve1, green)
QuadraticCurve(sixth_line, t, screen, (100, 100, 0), quad_curve2, green, False)
position_1 = Position(a[0], a[1])
position_2 = Position(b[0], b[1])
position_3 = Position(c[0], c[1])
line1 = [position_1, position_2]
line2 = [position_2, position_3]
start = LinearCurve(line1, t, screen, blue, False)
end = LinearCurve(line2, t, screen, blue, False)
pygame.draw.line(screen, blue, start, end, 2)
pygame.draw.circle(screen, color, (int(curve[0]), int(curve[1])), 8)
curve_list.append((int(curve[0]), int(curve[1])))
def _from_positions_row_to_position(row):
"""
Convert a row into a Position object
"""
quantity = float(row.Quantity.replace(',', ''))
this_position = Position(Code=row.Symbol.replace('+', ''),
Position=quantity)
return this_position
def performAction(self, newPosition, maxRow, maxColumn):
tempPos = PositionManager(self.position.x, self.position.y)
position = Position.factory(newPosition)
tempPos = position.update(tempPos)
if tempPos.validatePosition(maxRow, maxColumn):
return tempPos
else:
return False
def get_position(self, code=None):
if code is None:
code = self.primary_code
position = self.positions.get(code)
if position is None:
# print('2>>>', id(self))
self.positions[code] = Position(code=code, strategy=self)
return self.positions[code]
def umatched_as_positions(self):
"""
Return a PositionList object containing the unmatched trades
"""
result=PositionList()
for code in list(self.keys()):
position=self[code].unmatched.final_position()
result.append(Position(Code=code, Position=position))
return result
class StrategyNeural:
def __init__(self):
self.position = Position()
self.instrument = Instrument()
self.neural_network = NeuralNetwork()
def execute(self):
if not self.position.has_open_position():
params = self.builder_params()
candles = self.instrument.get_candles(params)
open, high, low, close, volume = self.candles2array(candles)
operation = self.neural_network.predict(open, high, low, close, volume)
self.execute_trade(operation)
def builder_params(self):
return {'instrument': 'EUR_USD', 'granularity': 'M5', 'count': 170}
def candles2array(self, candles):
open = []
high = []
low = []
close = []
volume = []
for candle in candles:
mid = candle.mid
open.append(mid.o)
high.append(mid.h)
low.append(mid.l)
close.append(mid.c)
volume.append(candle.volume)
return numpy.array(open, dtype=float), \
numpy.array(high, dtype=float), \
numpy.array(low, dtype=float), \
numpy.array(close, dtype=float), \
numpy.array(volume, dtype=float)
def execute_trade(self, operation):
params = {}
params['instrument'] = 'EUR_USD'
params['take_profit'] = 0.002
params['stop_loss'] = 0.002
if operation == 1:
Buy().execute(params)
elif operation == 2:
Sell().execute(params)
class Player:
view = Position.factory(Positioning.TOP)
def __init__(self, xStart, yStart, id):
self.position = PositionManager(xStart, yStart)
self.id = id
def performAction(self, newPosition, maxRow, maxColumn):
tempPos = PositionManager(self.position.x, self.position.y)
position = Position.factory(newPosition)
tempPos = position.update(tempPos)
if tempPos.validatePosition(maxRow, maxColumn):
return tempPos
else:
return False
def __init__(self):
self.position = Position()
self.instrument = Instrument()
self.neural_network = NeuralNetwork()
fps = 60
font = pygame.font.Font('freesansbold.ttf', 32)
#colors
white = (235, 235, 235)
black = (20, 20, 20)
red = (242, 2, 2)
green = (2, 242, 102)
blue = (2, 146, 242)
purple = (205, 163, 255)
#parameters
t = 0
speed = 0.002
linear_positions = [Position(100, 800, "P0"), Position(300, 200, "P1")]
Quadratic_positions = [
Position(660, 800, "P0"),
Position(880, 450, "P1"),
Position(720, 200, "P2")
]
cubic_positions = [
Position(1050, 800, "P0"),
Position(1280, 200, "P1"),
Position(1420, 800, "P2"),
Position(1800, 200, "P3")
]
quadratic_curve = []
cubic_curve = []
curve1 = []