Carlos-Francisco Méndez-Cruz / automatic-extraction-growth-conditions

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Estefani Gaytan Nunez
dc5206d9 1 parent 73f0e636

upload

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Showing 4 changed files with 16 additions and 5 deletions
......@@ -68,11 +68,11 @@ if __name__ == '__main__':
for report in reportFileList:
with open(os.path.join(options.inputPath, report), 'r') as File:
string = File.read()
scores[report[7:12].replace('_', ' ')]['CV']=re.findall('best\sCV\sscore\:(\d+\.\d+)', string)[0]
scores[report[7:16]]['CV']=re.findall('best\sCV\sscore\:(\d+\.\d+)', string)[0]
summaryScores = re.findall('avg\s\/\stotal\s+(\d+\.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
scores[report[7:12].replace('_', ' ')]['precision']=summaryScores[0]
scores[report[7:12].replace('_', ' ')]['recall']=summaryScores[1]
scores[report[7:12].replace('_', ' ')]['f1-score']=summaryScores[2]
scores[report[7:16]]['precision']=summaryScores[0]
scores[report[7:16]]['recall']=summaryScores[1]
scores[report[7:16]]['f1-score']=summaryScores[2]
print(DF(scores).T)
scoresTable = DF(scores).T
......@@ -93,5 +93,10 @@ if __name__ == '__main__':
plt.plot(scoresTable['recall'], 'o--', label='recall' , linewidth=3, markersize=15)
plt.plot(scoresTable['CV'], 'o--', label='CV' , linewidth=3, markersize=15)
plt.legend(loc='lower right')
plt.xticks(range(16),['run1', 'run2', 'run3', 'run4', 'run5', 'run6', 'run7', 'run1-NER(9)', 'run2-NER(10)', 'run3-NER(11)', 'run4-NER(12)', 'run5-NER(13)', 'run6-NER(14)', 'run7-NER(15)', 'run8-NER(16)'], rotation=90)
#plt.xticks(range(16),['run1', 'run2', 'run3', 'run4', 'run5', 'run6', 'run7', 'run1-NER(9)', 'run2-NER(10)', 'run3-NER(11)', 'run4-NER(12)', 'run5-NER(13)', 'run6-NER(14)', 'run7-NER(15)', 'run8-NER(16)'], rotation=90)
plt.xticks(range(64),['run1', 'run2', 'run3', 'run4', 'run5', 'run6', 'run7', 'run8',
'run9_v10', 'run10_v10', 'run11_v10', 'run12_v10', 'run13_v10', 'run14_v10', 'run15_v10', 'run16_v10',
'run9_v11', 'run10_v11', 'run11_v11', 'run12_v11', 'run13_v11', 'run14_v11', 'run15_v11', 'run16_v11',
'run9_v12', 'run10_v12', 'run11_v12', 'run12_v12', 'run13_v12', 'run14_v12', 'run15_v12', 'run16_v12',
'run9_v13', 'run10_v13', 'run11_v13', 'run12_v13', 'run13_v13', 'run14_v13', 'run15_v13', 'run16_v13'], rotation=90)
fig.savefig(imageName, bbox_inches='tight', pad_inches = 0.5)
......
#git add FiguresGrid*
cd /home/egaytan/automatic-extraction-growth-conditions/
git add --all .
git commit -m "upload"
#git pull
......
Run10_v10 Run10_v11 Run10_v12 Run10_v13 Run11_v10 Run11_v11 Run11_v12 Run11_v13 Run12_v10 Run12_v11 Run12_v12 Run12_v13 Run13_v10 Run13_v11 Run13_v12 Run13_v13 Run14_v10 Run14_v11 Run14_v12 Run14_v13 Run15_v10 Run15_v11 Run15_v12 Run15_v13 Run16_v10 Run16_v11 Run16_v12 Run16_v13 Run1_v10. Run1_v11. Run1_v12. Run1_v13. Run2_v10. Run2_v11. Run2_v12. Run2_v13. Run3_v10. Run3_v11. Run3_v12. Run3_v13. Run4_v10. Run4_v11. Run4_v12. Run4_v13. Run5_v10. Run5_v11. Run5_v12. Run5_v13. Run6_v10. Run6_v11. Run6_v12. Run6_v13. Run7_v10. Run7_v11. Run7_v12. Run7_v13. Run8_v10. Run8_v11. Run8_v12. Run8_v13. Run9_v10. Run9_v11. Run9_v12. Run9_v13.
CV 0.8426343854107191 0.8375337951545059 0.8344412009392327 0.8342433957330186 0.8106324641347842 0.8200149039218473 0.8256738268677035 0.8222652765189232 0.8369330476694216 0.8324548394172087 0.8305332917162109 0.8269983740799899 0.8308032444965605 0.8337888246126737 0.8317218364725953 0.8295597513348965 0.8497587132907273 0.8514572032055473 0.8529397672009222 0.8530997523170145 0.8354648872990671 0.8438553480543364 0.833488403887471 0.8384402744923658 0.8504521104958047 0.856091701330711 0.8544270978232358 0.8512984764913196 0.818911081696952 0.8117042290979286 0.8211582395746769 0.8166537086281624 0.8263737544180966 0.8265144607685903 0.8266267801413506 0.8209562028933415 0.8153229850631285 0.8170382812294825 0.8214198138509978 0.8200873889763314 0.8200306160186037 0.8201549270256682 0.8172882049457899 0.8192294924716081 0.8315569437055503 0.826756700790382 0.823974602152804 0.830775030715119 0.8514396351676051 0.8443013668504182 0.8434032566660784 0.8577895989909314 0.8376625935961355 0.8381889879918965 0.8349604346257782 0.836408383376389 0.841060076118789 0.843848676674025 0.8426311049791738 0.8433941367984498 0.8189566663670631 0.8186349956286322 0.8193729864282642 0.8163619170548052
f1-score 0.805 0.809 0.804 0.811 0.816 0.802 0.812 0.808 0.816 0.814 0.810 0.804 0.815 0.815 0.817 0.817 0.821 0.820 0.818 0.815 0.817 0.823 0.817 0.814 0.818 0.813 0.823 0.820 0.807 0.801 0.812 0.806 0.804 0.811 0.804 0.806 0.832 0.815 0.808 0.813 0.809 0.801 0.804 0.801 0.814 0.818 0.815 0.817 0.813 0.816 0.815 0.814 0.815 0.813 0.811 0.821 0.816 0.818 0.818 0.823 0.812 0.799 0.807 0.803
precision 0.911 0.853 0.908 0.856 0.922 0.907 0.916 0.852 0.919 0.855 0.912 0.910 0.919 0.915 0.854 0.854 0.864 0.857 0.856 0.922 0.857 0.863 0.857 0.849 0.858 0.905 0.859 0.859 0.850 0.905 0.849 0.848 0.906 0.852 0.906 0.907 0.875 0.906 0.838 0.898 0.855 0.907 0.846 0.907 0.859 0.860 0.856 0.859 0.925 0.857 0.919 0.861 0.850 0.909 0.908 0.860 0.857 0.914 0.858 0.862 0.843 0.827 0.850 0.839
recall 0.746 0.777 0.746 0.781 0.760 0.742 0.750 0.773 0.752 0.783 0.752 0.742 0.754 0.758 0.787 0.787 0.789 0.789 0.787 0.752 0.785 0.791 0.785 0.785 0.785 0.756 0.793 0.789 0.773 0.742 0.781 0.773 0.746 0.779 0.746 0.748 0.802 0.767 0.785 0.764 0.773 0.740 0.771 0.740 0.779 0.785 0.783 0.783 0.750 0.783 0.754 0.777 0.787 0.758 0.756 0.789 0.783 0.760 0.785 0.791 0.787 0.779 0.773 0.773