Merge remote branch 'upstream/master'

Conflicts:
	Jamroot
	bjam
	decoder/Jamfile
	decoder/cdec.cc
	dpmert/Jamfile
	jam-files/sanity.jam
	klm/lm/Jamfile
	klm/util/Jamfile
	mira/Jamfile

1 files changed, 0 insertions, 123 deletions

diff --git a/gi/evaluation/confusion_matrix.py b/gi/evaluation/confusion_matrix.py
deleted file mode 100644
index 2dd7aa47..00000000
--- a/gi/evaluation/confusion_matrix.py
+++ /dev/null
@@ -1,123 +0,0 @@
-#!/usr/bin/env python
-
-import sys, math, itertools, getopt
-
-def usage():
-    print >>sys.stderr, 'Usage:', sys.argv[0], '[-s slash_threshold] [-p output] [-m] input-1 input-2'
-    sys.exit(0)
-
-optlist, args = getopt.getopt(sys.argv[1:], 'hs:mp:')
-slash_threshold = None
-output_fname = None
-show_matrix = False
-for opt, arg in optlist:
-    if opt == '-s':
-        slash_threshold = int(arg)
-    elif opt == '-p':
-        output_fname = arg
-    elif opt == '-m':
-        show_matrix = True
-    else:
-        usage()
-if len(args) != 2 or (not show_matrix and not output_fname):
-    usage()
-
-ginfile = open(args[0])
-pinfile = open(args[1])
-
-if output_fname:
-    try:
-        import Image, ImageDraw
-    except ImportError:
-        print >>sys.stderr, "Error: Python Image Library not available. Did you forget to set your PYTHONPATH environment variable?" 
-        sys.exit(1)
-
-N = 0
-gold_frequencies = {}
-predict_frequencies = {}
-joint_frequencies = {}
-
-for gline, pline in itertools.izip(ginfile, pinfile):
-    gparts = gline.split('||| ')[1].split()
-    pparts = pline.split('||| ')[1].split()
-    assert len(gparts) == len(pparts)
-
-    for gpart, ppart in zip(gparts, pparts):
-        gtag = gpart.split(':',1)[1]
-        ptag = ppart.split(':',1)[1]
-
-        if slash_threshold == None or gtag.count('/') + gtag.count('\\') <= slash_threshold:
-            joint_frequencies.setdefault((gtag, ptag), 0)
-            joint_frequencies[gtag,ptag] += 1
-
-            predict_frequencies.setdefault(ptag, 0)
-            predict_frequencies[ptag] += 1
-
-            gold_frequencies.setdefault(gtag, 0)
-            gold_frequencies[gtag] += 1
-
-            N += 1
-
-# find top tags
-gtags = gold_frequencies.items()
-gtags.sort(lambda x,y: x[1]-y[1])
-gtags.reverse()
-#gtags = gtags[:50]
-
-preds = predict_frequencies.items()
-preds.sort(lambda x,y: x[1]-y[1])
-preds.reverse()
-
-if show_matrix:
-    print '%7s %7s' % ('pred', 'cnt'),
-    for gtag, gcount in gtags: print '%7s' % gtag,
-    print
-    print '=' * 80
-
-    for ptag, pcount in preds:
-        print '%7s %7d' % (ptag, pcount),
-        for gtag, gcount in gtags:
-            print '%7d' % joint_frequencies.get((gtag, ptag), 0),
-        print
-
-    print '%7s %7d' % ('total', N),
-    for gtag, gcount in gtags: print '%7d' % gcount,
-    print
-
-if output_fname:
-    offset=10
-
-    image = Image.new("RGB", (len(preds), len(gtags)), (255, 255, 255))
-    #hsl(hue, saturation%, lightness%)
-
-    # re-sort preds to get a better diagonal
-    ptags=[]
-    if True:
-        ptags = map(lambda (p,c): p, preds)
-    else:
-        remaining = set(predict_frequencies.keys())
-        for y, (gtag, gcount) in enumerate(gtags):
-            best = (None, 0)
-            for ptag in remaining:
-                #pcount = predict_frequencies[ptag]
-                p = joint_frequencies.get((gtag, ptag), 0)# / float(pcount)
-                if p > best[1]: best = (ptag, p)
-            ptags.append(ptag)
-            remaining.remove(ptag)
-            if not remaining: break
-
-    print 'Predicted tag ordering:', ' '.join(ptags)
-    print 'Gold tag ordering:', ' '.join(map(lambda (t,c): t, gtags))
-    
-    draw = ImageDraw.Draw(image)
-    for x, ptag in enumerate(ptags):
-        pcount = predict_frequencies[ptag]
-        minval = math.log(offset)
-        maxval = math.log(pcount + offset)
-        for y, (gtag, gcount) in enumerate(gtags):
-            f = math.log(offset + joint_frequencies.get((gtag, ptag), 0))
-            z = int(240. * (maxval - f) / float(maxval - minval))
-            #print x, y, z, f, maxval
-            draw.point([(x,y)], fill='hsl(%d, 100%%, 50%%)' % z)
-    del draw
-    image.save(output_fname)