def main(argv=None):
fsc_all = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/Results/Summary.txt",
column=2,
ignore_first_line=False)
fsc_opt = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/Results/Summary.txt",
column=5,
ignore_first_line=False)
fsc_min = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/Results/Summary.txt",
column=10,
ignore_first_line=False)
#
f_scores_b2_all = []
f_scores_b2_all_minval = 1
f_scores_b2_all_maxval = 0
f_scores_b2_all_minlabel = ""
f_scores_b2_all_maxlabel = ""
for d in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGraph/StatsAllFeatures"
):
if isdir(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGraph/StatsAllFeatures/"
+ d):
for f in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGraph/StatsAllFeatures/"
+ d):
if f.endswith(".txt"):
vals = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGraph/StatsAllFeatures/"
+ d + "/" + f,
1,
ignore_first_line=True)
val = vals[len(vals) - 1]
if val < f_scores_b2_all_minval:
f_scores_b2_all_minval = val
f_scores_b2_all_minlabel = d + "/" + f
if val > f_scores_b2_all_maxval:
f_scores_b2_all_maxval = val
f_scores_b2_all_maxlabel = d + "/" + f
f_scores_b2_all.append(val)
#
f_scores_b2_min = []
f_scores_b2_min_minval = 1
f_scores_b2_min_maxval = 0
f_scores_b2_min_minlabel = ""
f_scores_b2_min_maxlabel = ""
for d in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGraph/StatsOptimizedMinimized"
):
if isdir(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGraph/StatsOptimizedMinimized/"
+ d):
for f in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGraph/StatsOptimizedMinimized/"
+ d):
if f.endswith(".txt"):
vals = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGraph/StatsOptimizedMinimized/"
+ d + "/" + f,
1,
ignore_first_line=True)
val = vals[len(vals) - 1]
if val < f_scores_b2_min_minval:
f_scores_b2_min_minval = val
f_scores_b2_min_minlabel = d + "/" + f
if val > f_scores_b2_min_maxval:
f_scores_b2_min_maxval = val
f_scores_b2_min_maxlabel = d + "/" + f
f_scores_b2_min.append(val)
#
f_scores_b3_all = []
f_scores_b3_all_minval = 1
f_scores_b3_all_maxval = 0
f_scores_b3_all_minlabel = ""
f_scores_b3_all_maxlabel = ""
for f in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/Random_43x43/StatsAllFeatures"
):
if f.endswith(".txt"):
vals = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/Random_43x43/StatsAllFeatures/"
+ f,
1,
ignore_first_line=True)
val = vals[len(vals) - 1]
if val < f_scores_b3_all_minval:
f_scores_b3_all_minval = val
f_scores_b3_all_minlabel = f
if val > f_scores_b3_all_maxval:
f_scores_b3_all_maxval = val
f_scores_b3_all_maxlabel = f
f_scores_b3_all.append(val)
#
f_scores_b3_min = []
f_scores_b3_min_minval = 1
f_scores_b3_min_maxval = 0
f_scores_b3_min_minlabel = ""
f_scores_b3_min_maxlabel = ""
for f in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/Random_43x43/StatsOptimizedMinimized"
):
if f.endswith(".txt"):
vals = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/Random_43x43/StatsOptimizedMinimized/"
+ f,
1,
ignore_first_line=True)
val = vals[len(vals) - 1]
if val < f_scores_b3_min_minval:
f_scores_b3_min_minval = val
f_scores_b3_min_minlabel = f
if val > f_scores_b3_min_maxval:
f_scores_b3_min_maxval = val
f_scores_b3_min_maxlabel = f
f_scores_b3_min.append(val)
#
f_scores_b4_all = []
f_scores_b4_all_minval = 1
f_scores_b4_all_maxval = 0
f_scores_b4_all_minlabel = ""
f_scores_b4_all_maxlabel = ""
for d in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGoldRandomClasses/StatsAllFeatures"
):
if isdir(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGoldRandomClasses/StatsAllFeatures/"
+ d):
for f in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGoldRandomClasses/StatsAllFeatures/"
+ d):
if f.endswith(".txt"):
vals = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGoldRandomClasses/StatsAllFeatures/"
+ d + "/" + f,
1,
ignore_first_line=True)
val = vals[len(vals) - 1]
if val < f_scores_b4_all_minval:
f_scores_b4_all_minval = val
f_scores_b4_all_minlabel = d + "/" + f
if val > f_scores_b4_all_maxval:
f_scores_b4_all_maxval = val
f_scores_b4_all_maxlabel = d + "/" + f
f_scores_b4_all.append(val)
#
f_scores_b4_min = []
f_scores_b4_min_minval = 1
f_scores_b4_min_maxval = 0
f_scores_b4_min_minlabel = ""
f_scores_b4_min_maxlabel = ""
for d in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGoldRandomClasses/StatsOptimizedMinimized"
):
if isdir(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGoldRandomClasses/StatsOptimizedMinimized/"
+ d):
for f in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGoldRandomClasses/StatsOptimizedMinimized/"
+ d):
if f.endswith(".txt"):
vals = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/RandomGoldRandomClasses/StatsOptimizedMinimized/"
+ d + "/" + f,
1,
ignore_first_line=True)
val = vals[len(vals) - 1]
if val < f_scores_b4_min_minval:
f_scores_b4_min_minval = val
f_scores_b4_min_minlabel = d + "/" + f
if val > f_scores_b4_min_maxval:
f_scores_b4_min_maxval = val
f_scores_b4_min_maxlabel = d + "/" + f
f_scores_b4_min.append(val)
fsc_all_boxplot = BoxPlot(fsc_all, "fsc_all_boxplot")
fsc_opt_boxplot = BoxPlot(fsc_opt, "fsc_opt")
fsc_min_boxplot = BoxPlot(fsc_min, "fsc_min")
f_scores_b2_all_boxplot = BoxPlot(f_scores_b2_all,
"f_scores_b2_all",
minlabel=f_scores_b2_all_minlabel,
maxlabel=f_scores_b2_all_maxlabel)
f_scores_b2_min_boxplot = BoxPlot(f_scores_b2_min,
"f_scores_b2_min",
minlabel=f_scores_b2_min_minlabel,
maxlabel=f_scores_b2_min_maxlabel)
f_scores_b3_all_boxplot = BoxPlot(f_scores_b3_all,
"f_scores_b3_all",
minlabel=f_scores_b3_all_minlabel,
maxlabel=f_scores_b3_all_maxlabel)
f_scores_b3_min_boxplot = BoxPlot(f_scores_b3_min,
"f_scores_b3_min",
minlabel=f_scores_b3_min_minlabel,
maxlabel=f_scores_b3_min_maxlabel)
f_scores_b4_all_boxplot = BoxPlot(f_scores_b4_all,
"f_scores_b4_all",
minlabel=f_scores_b4_all_minlabel,
maxlabel=f_scores_b4_all_maxlabel)
f_scores_b4_min_boxplot = BoxPlot(f_scores_b4_min,
"f_scores_b4_min",
minlabel=f_scores_b4_min_minlabel,
maxlabel=f_scores_b4_min_maxlabel)
print(fsc_all_boxplot.get_tikz())
print(fsc_opt_boxplot.get_tikz())
print(fsc_min_boxplot.get_tikz())
print(f_scores_b2_all_boxplot.get_tikz())
print(f_scores_b2_min_boxplot.get_tikz())
print(f_scores_b3_all_boxplot.get_tikz())
print(f_scores_b3_min_boxplot.get_tikz())
print(f_scores_b4_all_boxplot.get_tikz())
print(f_scores_b4_min_boxplot.get_tikz())
def ddcplots(argv=None):
fsc_all = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/DDCResults/Summary.txt",
column=3,
ignore_first_line=False)
fsc_opt = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/Results/Summary.txt",
column=6,
ignore_first_line=False)
fsc_min = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/SimilarityGraph/Results/Summary.txt",
column=11,
ignore_first_line=False)
#
f_scores_b3_all = []
for f in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/Random_43x98/StatsAllFeatures"
):
if f.endswith(".txt"):
vals = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/Random_43x98/StatsAllFeatures/"
+ f,
1,
ignore_first_line=True)
f_scores_b3_all.append(vals[len(vals) - 1])
#
f_scores_b3_min = []
for f in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/Random_43x98/StatsOptimizedMinimized"
):
if f.endswith(".txt"):
vals = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/Random_43x98/StatsOptimizedMinimized/"
+ f,
1,
ignore_first_line=True)
f_scores_b3_min.append(vals[len(vals) - 1])
#
f_scores_b4_all = []
for d in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/DDCRandomGoldRandomClasses/StatsAllFeatures"
):
if isdir(
"k:/Wiki/StadtWikis/DDC/Classification/DDCRandomGoldRandomClasses/StatsAllFeatures/"
+ d):
for f in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/DDCRandomGoldRandomClasses/StatsAllFeatures/"
+ d):
if f.endswith(".txt"):
vals = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/DDCRandomGoldRandomClasses/StatsAllFeatures/"
+ d + "/" + f,
1,
ignore_first_line=True)
f_scores_b4_all.append(vals[len(vals) - 1])
#
f_scores_b4_min = []
for d in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/DDCRandomGoldRandomClasses/StatsOptimizedMinimized"
):
if isdir(
"k:/Wiki/StadtWikis/DDC/Classification/DDCRandomGoldRandomClasses/StatsOptimizedMinimized/"
+ d):
for f in listdir(
"k:/Wiki/StadtWikis/DDC/Classification/DDCRandomGoldRandomClasses/StatsOptimizedMinimized/"
+ d):
if f.endswith(".txt"):
vals = IOUtil.get_float_column(
"k:/Wiki/StadtWikis/DDC/Classification/DDCRandomGoldRandomClasses/StatsOptimizedMinimized/"
+ d + "/" + f,
1,
ignore_first_line=True)
f_scores_b4_min.append(vals[len(vals) - 1])
fsc_all_boxplot = BoxPlot(fsc_all, "fsc_all_boxplot")
fsc_opt_boxplot = BoxPlot(fsc_opt, "fsc_opt")
fsc_min_boxplot = BoxPlot(fsc_min, "fsc_min")
f_scores_b3_all_boxplot = BoxPlot(f_scores_b3_all, "f_scores_b3_all")
f_scores_b3_min_boxplot = BoxPlot(f_scores_b3_min, "f_scores_b3_min")
f_scores_b4_all_boxplot = BoxPlot(f_scores_b4_all, "f_scores_b4_all")
f_scores_b4_min_boxplot = BoxPlot(f_scores_b4_min, "f_scores_b4_min")
print(fsc_all_boxplot.get_tikz())
print(fsc_opt_boxplot.get_tikz())
print(fsc_min_boxplot.get_tikz())
print(f_scores_b3_all_boxplot.get_tikz())
print(f_scores_b3_min_boxplot.get_tikz())
print(f_scores_b4_all_boxplot.get_tikz())
print(f_scores_b4_min_boxplot.get_tikz())