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#!/usr/bin/python
import sys
import numpy as np
sk_file = open(sys.argv[1])
try:
div = float(sys.argv[2])
except:
div = 2.0
labels = sk_file.readline().strip().split(',')
beg = labels.index('h-sc')
data = {}
#print ','.join(['#name'] + labels[beg:])
for i in range(1,40):
data[str(i)] = {}
for l in labels[beg:]:
data[str(i)][l] = []
for line in sk_file:
line = line.strip().split(',')
#limbs = line[beg:]
if "-1" not in line and 2 < float(line[labels.index('z-value')]) < 3:
id = line[labels.index('name')]
for x in labels[beg:]: data[id][x] += [float(line[labels.index(x)])]
var = []
for i in data:
out = [i]
for l in labels[beg:]:
if len(data[i][l]) > 1:
var += [np.var(data[i][l])]
data[i][l] = np.average(data[i][l])
out += [str(np.average(data[i][l]))]
#if len(out) > 1:
# print ','.join(out)
sys.stderr.write(str(div**0.5)+'\n')
sys.stderr.write(str(np.average(var))+'\n')
sk_file.seek(0)
print sk_file.readline().strip()
for line in sk_file:
line = line.strip().split(',')
id = line[labels.index('name')]
for l in labels[beg:]:
obs = float(line[labels.index(l)])
if obs > 0:
diff = obs-data[id][l]
line[labels.index(l)] = str(data[id][l] + diff/(div**0.5))
print ','.join(line)
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