diff options
Diffstat (limited to 'data/limbs-avg.py')
| -rwxr-xr-x | data/limbs-avg.py | 15 |
1 files changed, 8 insertions, 7 deletions
diff --git a/data/limbs-avg.py b/data/limbs-avg.py index 135786f..c43deb7 100755 --- a/data/limbs-avg.py +++ b/data/limbs-avg.py @@ -3,6 +3,7 @@ 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] @@ -27,7 +28,7 @@ limbs = (('Head','ShoulderCenter'),\ 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(['name','run','frame','z-value']+list(xlabels)) +print '# '+','.join(['name','run','frame','z-value','z-var']+list(xlabels)) for line in sk_file: @@ -37,7 +38,7 @@ for line in sk_file: frame = int(frame) if frame != pframe and vals != {} and run in flabel and flabel[run] != 'None': out = [] - zv = [] + 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: @@ -46,7 +47,7 @@ for line in sk_file: 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] + #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] @@ -54,16 +55,16 @@ for line in sk_file: #print str(dist) + " " + str(limb) #print str(dist) + "\t" + str(limb) else: - out += ['?'] + out += ['-1'] for l in range(len(dupes)-1,-1,-1): l1, l2 = dupes[l] - if out[l1] != '?' and out[l2] != '?': + if out[l1] != '-1' and out[l2] != '-1': out[l1] = str((float(out[l1])+float(out[l2]))/2) - elif out[l1] == '?' and out[l2] != '?': + elif out[l1] == '-1' and out[l2] != '-1': out[l1] = out[l2] out.pop(l2) if len(zv) >= 1: - print ','.join([flabel[run],str(run),str(frame),str(sum(zv)/len(zv))] + out) + print ','.join([flabel[run],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)] |