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agomez |
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'''
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Created on 03/01/2012
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@author: R. Valin
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'''
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import matplotlib.pyplot as plt
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import time
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#import os
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import random
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from exp.ea import experiment_type as expt
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from exp.ea import ea_bonfire as ea
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"""############################################
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#Generacion aleatoria de experimentos #
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##############################################"""
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#Lectura de datos del histograma de envio
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#
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dire='/home/cesga/bonfire/workspace/Bonfire/exp/dis'
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print (dire + '/submit_time.csv')
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file1 = open(dire + '/submit_time_norm.csv', 'r')
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#Leemos ficheros estadisticas
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sub_prob = file1.readlines()
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file1.close()
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#Crea una lista con los valores que lee del fichero
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submit_prob = []
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for a in sub_prob:
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submit_prob.append(float(a.split(',')[1]))
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#print(submit_prob)
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#Semilla para random si no pones nada en seed coge el tiempo del sistema
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random.seed()
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print len(sub_prob)
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#Prueba de que la lectura de datos es correcta
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#b=0
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#for a in submit_prob:
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# b=b+a
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#print ('Prob total', b)
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#Asignacion del numero de trabajos cada media hora
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jobs = 0
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i = 0
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#Inicializa prob
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prob = 0
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#Trabajos totales que quieres enviar
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total_jobs = 100
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envio = [0 for x in range(len(submit_prob))]
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for a in range(total_jobs):
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#Probabilidad de envio en una hora dada
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prob_envio = random.random()
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#Con este algoritmo determinamos la hora (o el bin del histograma)
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while (prob < prob_envio and prob_envio > prob + submit_prob[i + 1]):
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i = i + 1
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#print (i)
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prob = prob + submit_prob[i]
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#Vector de trabajos a enviar por hora
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if (i <= len(submit_prob)):
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envio[i] = envio[i] + 1
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else:
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print('Me paso de indice')
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#print prob_envio, prob, prob+submit_prob[i+1]
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#Inicializamos variables para la siguiente iteracion
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i = 0
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prob = submit_prob[0]
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#plt.bar(range(1,49), envio, 1)
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#plt.show()
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file2=open('sub.csv', 'w')
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for sub in envio:
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file2.write(str(sub)+'\n')
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file2.close()
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"""################################################################
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# Envio de experimentos #
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###################################################################"""
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#Descripcion del trabajo en Json
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#exp={'description': 'Experiment description',
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# 'duration': 120,
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# 'name': 'My Experiment',
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# 'resources': [{'compute': {'name': 'JSON-COMPUTE-TEST',
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# 'description': 'A description of the compute.',
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# 'instanceType': 'small',
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# 'locations': ['fr-inria'],
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# 'resources':[{'storage': '@BonFIRE Debian Squeeze v3'},{'network':'@BonFIRE WAN'}]}}]}
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#Indicamos la lista de sites a la que queremos enviar, la duracion de los experimentos
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# y nos devuelve una lista con stings en json con la definicion del experimento
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#locations=['be-ibbt','fr-inria','uk-hplabs','uk-uedin']
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#duration = 120
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#locations = ['uk-uedin']
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#exp, info_instance, info_storage, info_location = expt.json_exp(locations, duration)
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#
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#multi = 10
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#
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#for i in exp:
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# print i
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# m=str(i)
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# for j in range(10):
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# save(locations)
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# location=info_location[m]
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# instance=info_instance[m]
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# store=info_storage[m]
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# ea.ea_bf(i,instance,store,location)
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#time.sleep(float(130))
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