3 files changed, 1130 insertions, 21 deletions
diff --git a/data/combined/graphs/face.csv b/data/combined/graphs/face.csv
new file mode 100644
index 0000000..3b0284b
--- /dev/null
+++ b/data/combined/graphs/face.csv
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diff --git a/data/combined/scriptSkeleton.m b/data/combined/scriptSkeleton.m
index 91c724f..0dfbfa0 100644
--- a/data/combined/scriptSkeleton.m
+++ b/data/combined/scriptSkeleton.m
@@ -69,6 +69,8 @@ recall = zeros(numEx, 0);
 for ex = 1 : numEx
   train = trains{ex};
   test = tests{ex};
+  length(train)
+  length(test)
   
   % NB classifier with multivariate Gaussians
   Py = zeros(numClasses, 1);
@@ -116,6 +118,8 @@ for ex = 1 : numEx
   
   % prediction
   [conf, yp] = max(logp, [], 2);
+  size(yp)
+  exit
   
   % sum up all but the highest probability
   norm1 = logp - repmat(conf, 1, numClasses);
diff --git a/data/face-frame-recognition-accuracy.py b/data/face-frame-recognition-accuracy.py
index 0d34cf9..3ff0aa8 100755
--- a/data/face-frame-recognition-accuracy.py
+++ b/data/face-frame-recognition-accuracy.py
@@ -1,4 +1,5 @@
 #!/usr/bin/python
+import numpy as np
 import os
 import sys
 import pickle
@@ -22,8 +23,8 @@ for line in open(sys.argv[1]):
     except:
         continue
     user = line[1]
-    if run not in runs:
-        runs[run] = 0
+    if run not in labels:
+        #runs[run] = 0
         labels[run] = users.index(user) + 1
 
 for line in open(sys.argv[2]):
@@ -41,23 +42,28 @@ for line in open(sys.argv[2]):
     conf[run] = float(line[7])
     prun = run
 
-t=0.0
-tp=0.0
-fp=0.0
-fn=0.0
-for (k,v) in runs.items():
-    #print v,labels[k]
-    if v == 0 or conf[k] < thresh:
-        fn += 1
-    elif v != labels[k]:
-        fp += 1
-    else:
-        tp += 1
-    t += 1
-#print runs[167],labels[167]
-#print tp,fp,fn
-#print("Precision: ",tp/(tp+fp))
-#print("False positives: ",fp/(tp+fp))
-#print("Recall: ",1.0-fn/t)
-print str(tp/(tp+fp))+","+str(1.0-fn/t)
+for i in range(999)+list(np.arange(999,1000,0.01)):
+    thresh = i/10
+    t=0.0
+    tp=0.0
+    fp=0.0
+    fn=0.0
+    for (k,v) in runs.items():
+        #print v,labels[k]
+        if conf[k] < thresh:
+            fn += 1
+        elif v != labels[k]:
+            fp += 1
+        else:
+            tp += 1
+        t += 1
+    #print runs[167],labels[167]
+    #print tp,fp,fn
+    #print("Precision: ",tp/(tp+fp))
+    #print("False positives: ",fp/(tp+fp))
+    #print("Recall: ",1.0-fn/t)
+    try:
+        print str(1.0-fn/t)+","+str(tp/(tp+fp))
+    except:
+        print "0,1"