78 lines
No EOL
3.8 KiB
Python
Executable file
78 lines
No EOL
3.8 KiB
Python
Executable file
#!/usr/bin/env python3
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import sys
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import os
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import numpy as np
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import matplotlib.pyplot as plt
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#cmd eg : python3 ./dist_op_random.py ./fastga_results_all/fastga_results_random/ ./hist_and_csv/
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#get the distribution of operators variants recommended by 15 random algo for each maxEv
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#pc and pm 10 possibilities : [0-0.1[ [0.1-0.2[ [0.2-0.3[ [0.3-0.4[ [0-0.5[ [0.5-0.6[ ...[0.9-1[
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#pop-size and offspring-size 10 possibilities : 0-5 5-10, 10-15 15-20 20-25 25-30 30-35- 35-40 40-45 45-50
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path=sys.argv[1] # directory of a result of one experiment
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#eg : ./fastga_results_all/fastga_results_random/
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figdir=sys.argv[2] #directory of where you want to store the data
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if("random" in path):
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#column : [operator : nbpossibilities]
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distdir=figdir+"/distribution_random"
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try:
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os.makedirs(distdir)
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except FileExistsError:
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pass
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nbparam=9 #-1 car il y a le pb
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res=[]
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for maxEvdir in os.listdir(path):
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res.append({"crossover-rate":["pc" , np.zeros(10, dtype=int)],
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"cross-selector":["SelectC", np.zeros(7, dtype=int)],
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"crossover":["Crossover" , np.zeros(10, dtype=int)],
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"mutation-rate":["pm",np.zeros(10, dtype=int)],
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"mut-selector":["SelectM",np.zeros(10, dtype=int)],
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"mutation":["Mutation", np.zeros(11, dtype=int)],
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"replacement":["Replacement" , np.zeros(11, dtype=int)],
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"pop-size":["pop-size", np.zeros(10, dtype=int)],
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"offspring-size":["offspring-size" , np.zeros(10, dtype=int)]})
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for algodir in os.listdir(os.path.join(path,maxEvdir)): #fastgadir : directory of 50 runs of an elite configuration
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algo=algodir.split("_")
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for param in algo:
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name,val=param.split("=")[0],float(param.split("=")[1])
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if(name in {"pop-size" ,"offspring-size"}):
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if(val%5==0):
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res[-1][name][1][int(val//5) -1]+=1
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else:
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#print(res[-1][name][1],val//5)
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res[-1][name][1][int(val//5)]+=1
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elif(name in {"crossover-rate","mutation-rate"} ):
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if(int(val*10)==10): #case of val=1
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res[-1][name][1][-1]+=1
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else :
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#print(int(float(val)*10), name,pb,val)
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res[-1][name][1][int(val*10)]+=1
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else :
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res[-1][name][1][int(val)]+=1
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ind=0
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for maxEvdir in os.listdir(path):
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name="distribution_random_"+maxEvdir.split("_")[0]+".csv" #the end of the path must be /
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with open(os.path.join(distdir,name),"w+") as csvfile:
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csvfile.write("Op index, "+",".join(map(str,range(0,11)))+"\n")
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with open(os.path.join(distdir,name),"a") as csvfile:
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for param_name in res[ind].keys():
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#print(map(str,res[ind]),res[ind], ",".join(map(str,res[ind])))
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csvfile.write(res[ind][param_name][0]+","+ ",".join(map(str,res[ind][param_name][1]))+",-"*(11-len(res[ind][param_name][1])) +"\n")
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#print(str(i)+",",",".join(map(str,np.mean(aucs[i],1))))
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ind+=1
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#all problems
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name ="distribution_all_random_"+path.split("/")[-1]+".csv"
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with open(os.path.join(distdir,name),'w+') as csvfile:
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csvfile.write("Op index, "+",".join(map(str,range(0,11)))+"\n")
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with open(os.path.join(distdir,name),'a') as csvfile:
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for param_name in res[0].keys():
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#print(map(str,res[ind]),res[ind], ",".join(map(str,res[ind])))
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csvfile.write(res[0][param_name][0]+","+ ",".join(map(str,np.sum([res[i][param_name][1] for i in range(ind-1)],0)))+",-"*(11-len(res[0][param_name][1])) +"\n") #res[0] only for getting the name of parameters
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#print(str(i)+",",",".join(map(str,np.mean(aucs[i],1)))) |