Cleaned up scripts

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@336 ec762483-ff6d-05da-a07a-a48fb63a330f

1 files changed, 118 insertions, 0 deletions

diff --git a/gi/evaluation/confusion_matrix.py b/gi/evaluation/confusion_matrix.py
new file mode 100644
index 00000000..c5e2a379
--- /dev/null
+++ b/gi/evaluation/confusion_matrix.py
@@ -0,0 +1,118 @@
+#!/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:')
+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
+    if False:
+        ptags = []
+        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
+    
+    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)