darden1

# -*- coding: utf-8 -*-
import array
import random
import json

import numpy as np
import matplotlib.pyplot as plt

from math import sqrt

darden1

# -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

from tradingrrl import TradingRRL

def main():

    fname = "../data/USDJPY30.csv"

darden1

import random
import numpy

from deap import algorithms
from deap import base
from deap import creator
from deap import tools

creator.create("FitnessMax", base.Fitness, weights=(1.0,))
creator.create("Individual", numpy.ndarray, fitness=creator.FitnessMax)

darden1

import random
import numpy

from deap import algorithms
from deap import base
from deap import creator
from deap import tools

creator.create("FitnessMax", base.Fitness, weights=(1.0,))
creator.create("Individual", numpy.ndarray, fitness=creator.FitnessMax)

darden1

import random

from deap import base
from deap import creator
from deap import tools

creator.create("FitnessMax", base.Fitness, weights=(1.0,))
creator.create("Individual", list, fitness=creator.FitnessMax)

toolbox = base.Toolbox()

darden1

import random
import numpy as np
from operator import attrgetter

def main():
    n_gene   = 100   # The number of genes.
    n_ind    = 300   # The number of individuals in a population.
    CXPB     = 0.5   # The probability of crossover.
    MUTPB    = 0.2   # The probability of individdual mutation.
    MUTINDPB = 0.05  # The probability of gene mutation.

darden1

//+------------------------------------------------------------------+
//|                                                   tradingrrl.mq4 |
//|                        Copyright 2014, MetaQuotes Software Corp. |
//|                                              http://www.mql5.com |
//+------------------------------------------------------------------+
#property copyright "Copyright 2014, MetaQuotes Software Corp."
#property link      "http://www.mql5.com"
#property version   "1.03"
#property strict

darden1

import time
import py_test_sum
import cy_test_sum
import cpp_test_sum

n_iter = 10000000

#--- Python sum
py_ts = py_test_sum.TestSum(n_iter)

darden1

from distutils.core import setup
from distutils.extension import Extension
from Cython.Distutils import build_ext
from Cython.Build import cythonize

setup(
    name = "cpp_test_sum",
    ext_modules = cythonize(
        Extension("cpp_test_sum",
                  sources=["cpp_test_sum.pyx", "cpp_test_sum_.cpp"],

darden1

from libcpp.vector cimport vector

cdef extern from "cpp_test_sum_.h" namespace "cpp_test_sum":
    cdef cppclass cppTestSum:
        cppTestSum(int n_iter) except +
        int n_iter
        vector[double] sum
        
        void calc_sum()