def hist_number_of_words(nfvs):
total = len(nfvs)
nwords = [x['note_words'] for x in nfvs.values()]
stats = s(nwords)
cap.hist2(
nwords,
breaks=[
0, 1, 5, 10, 20, 30, 40, 50, 100, 200, 500, 1000, 2000, 5000, 10000
],
filename="/var/www/listit-study/n-words.png",
xlab="number of words",
title=
"words per note [df:%d] (min:0, max:%g, mean:%g, median:%g, var:%g)" %
(total - 1, stats[1], stats[2], stats[3], stats[4]),
ylab="Notes (out of %d)" % total)
cap.loghist(
nwords,
breaks=[
0, 1, 5, 10, 20, 30, 40, 50, 100, 200, 500, 1000, 2000, 5000, 10000
],
filename="/var/www/listit-study/n-logwords.png",
xlab="number of words",
title=
"words per note [df:%d] (min:0, max:%g, mean:%g, median:%g, var:%g)" %
(total - 1, stats[1], stats[2], stats[3], stats[4]),
ylab="Notes (out of %d)" % total)
def hist_edit_distance(nfs):
total = len(nfs)
ndist = [n["edit_distance"] for n in nfs.values()]
stats = s(ndist)
cap.loghist( ndist,
breaks=[0,1,5,10,20,30,40,50,100,200,500,1000,10000],
filename="/var/www/listit-study/edit-distances.png",
xlab="edit distance (chars)",
title="edit distance[%d] (min:0, max:%g, mean:%g, median:%g, var:%g)" % (total-1,stats[1],stats[2],stats[3],stats[4]),
ylab="edits (out of %d)" % total )
def hist_edit_distance(nfs):
total = len(nfs)
ndist = [n["edit_distance"] for n in nfs.values()]
stats = s(ndist)
cap.loghist(
ndist,
breaks=[0, 1, 5, 10, 20, 30, 40, 50, 100, 200, 500, 1000, 10000],
filename="/var/www/listit-study/edit-distances.png",
xlab="edit distance (chars)",
title="edit distance[%d] (min:0, max:%g, mean:%g, median:%g, var:%g)" %
(total - 1, stats[1], stats[2], stats[3], stats[4]),
ylab="edits (out of %d)" % total)
def hist_capped_number_of_words(nfvs,cap=300):
total = len(nfvs)
nwords = [x['note_words'] for x in nfvs.values() if x['note_words'] < cap]
stats = s(nwords)
cap.hist2( nwords,
breaks=[0,1,5,10,20,30,40,50,100,200,300],
filename="/var/www/listit-study/n-words.png",
xlab="number of words",
title="words per note [df:%d] (min:0, max:%g, mean:%g, median:%g, var:%g)" % (total-1,stats[1],stats[2],stats[3],stats[4]),
ylab="Notes (out of %d)" % total )
cap.loghist( nwords,
breaks=[0,1,5,10,20,30,40,50,100,200,500,1000,2000,5000,10000],
filename="/var/www/listit-study/n-logwords.png",
xlab="number of words",
title="words per note [df:%d] (min:0, max:%g, mean:%g, median:%g, var:%g)" % (total-1,stats[1],stats[2],stats[3],stats[4]),
ylab="Notes (out of %d)" % total )