comparison evaluation.py @ 2:b8e32e577597 draft

planemo upload for repository https://github.com/eteriSokhoyan/galaxytools/tree/branchForIterations/tools/GraphClust/CollectResults commit 9bc3c9b613d106098a78e16534897c88a3738c07

1:ed8c7191b322

import glob
from os import system
import re

def sh(script):
    system("bash -c '%s'" % script)

dataNames = "FASTA/data.names"

toWrite = ""
for i in range(len(listOfClusters)):
    toWrite += listOfClasses[i] + "\t" + listOfClusters[i] + '\n'
with open("RESULTS/fullTab.tabular", "w") as full:
    full.write(toWrite)

2:b8e32e577597

import glob
from os import system
import re
from sklearn import metrics

def sh(script):
    system("bash -c '%s'" % script)

dataNames = "FASTA/data.names"

toWrite = ""
for i in range(len(listOfClusters)):
    toWrite += listOfClasses[i] + "\t" + listOfClusters[i] + '\n'
with open("RESULTS/fullTab.tabular", "w") as full:
    full.write(toWrite)


listOfClasses = []
listOfClusters = []
pattern = re.compile("^RF.*$")


if len(listOfClasses) > 0 and  pattern.match(str(listOfClasses[0])):
    with open("RESULTS/fullTab.tabular", "r") as tabF:
        for line in tabF.readlines():
            listOfClasses.append(line.split()[0])
            listOfClusters.append(line.split()[1])

    completeness_score = metrics.completeness_score(listOfClasses, listOfClusters)
    homogeneity_score = metrics.homogeneity_score(listOfClasses, listOfClusters)
    adjusted_rand_score = metrics.adjusted_rand_score(listOfClasses, listOfClusters)
    adjusted_mutual_info_score = metrics.adjusted_mutual_info_score(listOfClasses, listOfClusters)
    v_measure_score = metrics.v_measure_score(listOfClasses, listOfClusters)

    toWrite = "completeness_score : " + str(completeness_score) + "\n" + "homogeneity_score : " + str(homogeneity_score) + "\n" + "adjusted_rand_score : " +str(adjusted_rand_score)  + "\n" + "adjusted_mutual_info_score : " + str(adjusted_mutual_info_score)+ "\n" + "v_measure_score : " + str(v_measure_score)

else:
    toWrite = "completeness_score : NA \nhomogeneity_score : NA \nadjusted_rand_score : NA \nadjusted_mutual_info_score : NA \nv_measure_score : NA"

with open("RESULTS/evaluation.txt", "w") as fOut:
    fOut.write(toWrite)