new combined data

1 files changed, 74 insertions, 0 deletions

diff --git a/data/combined/limbs-avg.py b/data/combined/limbs-avg.py
new file mode 100755
index 0000000..031f80b
--- /dev/null
+++ b/data/combined/limbs-avg.py
@@ -0,0 +1,74 @@
+#!/usr/bin/python
+
+import sys
+import math
+import pickle
+import numpy as np
+
+sk_file = open(sys.argv[1])
+out_dir = sys.argv[1][0:sys.argv[1].rfind('/')+1]
+dirs = ['24-1-2012-16-56-57','27-1-2012-10-45-29']
+names = pickle.load(open(sys.argv[2]))
+labels = []
+for f in sys.argv[3:]:
+    labels += [pickle.load(open(f))]
+flabel = labels[0]
+for label in labels:
+    for run in label:
+        if label[run] != flabel[run] or label[run] == '?' or label[run] == 'None':
+            flabel[run] = 'None'
+
+pframe = 0
+vals = {}
+data = {}
+limbs = (('Head','ShoulderCenter'),\
+        ('ShoulderCenter','ShoulderLeft'),('ShoulderLeft','ElbowLeft'),('ElbowLeft','WristLeft'),\
+        ('ShoulderCenter','ShoulderRight'),('ShoulderRight','ElbowRight'),('ElbowRight','WristRight'),\
+        ('ShoulderCenter','Spine'),('Spine','HipCenter'),\
+        ('HipCenter','HipLeft'),('HipLeft','KneeLeft'),('KneeLeft','AnkleLeft'),\
+        ('HipCenter','HipRight'),('HipRight','KneeRight'),('KneeRight','AnkleRight'))
+dupes = ((1,4),(2,5),(3,6),(9,12),(10,13),(11,14))
+#xlabels = ('h-sc','sc-sl','sl-el','el-wl','sc-sr','sr-er','er-wr','sc-s','s-hc','hc-hl','hl-kl','kl-al','hc-hr','hr-kr','kr-ar')
+xlabels = ('h-sc','sc-sh','sh-el','el-wr','sc-s','s-hc','hc-hi','hi-kn','kn-an')
+print '# '+','.join(['dir','name','run','frame','z-value','z-var']+list(xlabels))
+
+
+for line in sk_file:
+    dir, run, frame, nid, joint, state, x, y, z, X, Y = line.strip().split(',')
+    if frame != 'Frame':
+        run = int(run)
+        frame = int(frame)
+        if frame != pframe and vals != {} and run in flabel and flabel[run] != 'None':
+            out = []
+            zv = map(lambda xyz: xyz[2], vals.values())
+            for l in range(len(limbs)):
+                j1, j2 = limbs[l]
+                if j1 in vals and j2 in vals:
+                    dx = vals[j1][0] - vals[j2][0]
+                    dy = vals[j1][1] - vals[j2][1]
+                    dz = vals[j1][2] - vals[j2][2]
+                    limb = math.sqrt(dx*dx + dy*dy + dz*dz)
+                    out += [str(limb)]
+                    #zv += [(vals[j1][2] + vals[j2][2])/2]
+                    #dist = math.fabs((dz + 2*vals[j2][2])/2)
+                    #if limb < 1000 and limb > 100:
+                    #X += [dist]
+                    #data[name][l] += [limb]
+                    #print str(dist) + " " + str(limb)
+                    #print str(dist) + "\t" + str(limb)
+                else:
+                    out += ['-1']
+            for l in range(len(dupes)-1,-1,-1):
+                l1, l2 = dupes[l]
+                if out[l1] != '-1' and out[l2] != '-1':
+                    out[l1] = str((float(out[l1])+float(out[l2]))/2)
+                elif out[l1] == '-1' and out[l2] != '-1':
+                    out[l1] = out[l2]
+                out.pop(l2)
+            if len(zv) >= 1:
+                print ','.join(str(dirs.index(dir) + 1),str(names.index([flabel[run]) + 1),str(run),str(frame),str(np.average(zv)),str(np.var(zv))] + out)
+            vals = {}
+        if state == 'Tracked':
+            vals[joint] = [float(x), float(y), float(z)]
+        pframe = frame
+