import sys, math

from pyevolve import G1DList, GSimpleGA, Selectors, Scaling, DBAdapters

#------------------------------------------------------------------

# 从文件中读取数据

ifile = open( 'mydata.txt', 'r')


linedata = ()


mypoints = []



for line in ifile:

  pair = line.split()   

  linedata = (float(pair[0]), float(pair[1]))

  mypoints.append(linedata) 


#------------------------------------------------------------------

#定义你要拟合的曲线方程，例如 y = a*x + b

def eval_curve(concentration, a, b):

  activity = a*concentration + b 

    return activity


# 定义适应度函数

def generate_fitness_function(mypoints):

    def fitness_function(chromosome):

    score = 0.0

        for point in mypoints:

      delta = abs(eval_curve(point[0], *chromosome) - point[1])

      score += delta


    score = -score
    

    return score

  return fitness_function

#------------------------------------------------------------------      

# Create the population

genome = G1DList.G1DList(2)

genome.evaluator.set(generate_fitness_function(mypoints))

genome.setParams(rangemin=-50, rangemax=50)

# Set up the engine

ga = GSimpleGA.GSimpleGA(genome)
ga.setPopulationSize(1000)

ga.selector.set(Selectors.GRouletteWheel)

# Change the scaling method

pop = ga.getPopulation()
pop.scaleMethod.set(Scaling.SigmaTruncScaling)

#------------------------------------------------------------------

# Start the algorithm, and print the results.

ga.evolve(freq_stats=10)

print(ga.bestIndividual())

print("Mypoints: " + repr(mypoints))

ifile.close