# take log
if 0:
mval = min(valsl) - 0.0001
print 'Min: %f' % mval
# Prevent negative current issues
valsl = [math.log(x - mval) for x in valsl]
# Limit numbers that are more than a few std dev away
# this messes up way that hist eq currently works
# although not entirely sure why
# helped a lot
if 1:
print valsl[0:10]
sd = statistics.stdev(valsl)
u = statistics.mean(valsl)
sds = 2
print 'Mean: %f' % u
print 'SD: %f' % sd
keep_min = u - sd * sds
keep_max = u + sd * sds
print 'Keeping'
print ' Min: %f' % keep_min
print ' Max: %f' % keep_max
valsl = [min(keep_max, x) for x in valsl]
valsl = [max(keep_min, x) for x in valsl]
if 1:
print 'Equalizing...'
valsl = histeq(valsl)
# Account for second derrivitive
val = opened[i + 2] - opened[0]
valsl.append(val)
print 'Cols: %d' % cols
print 'Rows: %d' % rows
# Limit numbers that are more than a few std dev away
# this messes up way that hist eq currently works
# although not entirely sure why
# helped a lot
if 1:
print valsl[0:10]
sd = statistics.stdev(valsl)
u = statistics.mean(valsl)
sds = 2
print 'Mean: %f' % u
print 'SD: %f' % sd
keep_min = u - sd * sds
keep_max = u + sd * sds
print 'Keeping'
print ' Min: %f' % keep_min
print ' Max: %f' % keep_max
valsl = [min(keep_max, x) for x in valsl]
valsl = [max(keep_min, x) for x in valsl]
if 0:
print 'Equalizing...'
valsl = histeq(valsl)
while True:
this = gp.get()
ig, a, b = this
igstr = gp307.fmt(ig)
astr = gp307.fmt(a)
bstr = gp307.fmt(b)
t = time.time()
print '%s: IG %s, A %s, B %s' % (time.strftime('%F %T'), igstr, astr, bstr)
if args.diff and lasts:
last = lasts[0]
diff = [x - y for x, y in zip(this, last)]
print ' D IG %s, A %s, B %s' % (fmts(diff[0]), fmts(diff[1]), fmts(diff[2]))
if f:
f.write('%s, %s, %s, %s\n' % (t, igstr, astr, bstr))
f.flush()
lasts = [this] + lasts[0:args.trend_n - 1]
if args.stat and len(lasts) > 1:
s = ''
for chan in zip(*lasts):
chanl = [math.log(x, 10) for x in chan]
sd = statistics.stdev(chanl)
u = statistics.mean(chanl)
s += '(%s, %s) ' % (fmte(u), fmte(sd))
print ' % 3u %s' % (len(lasts), s)
ig, a, b = this
igstr = gp307.fmt(ig)
astr = gp307.fmt(a)
bstr = gp307.fmt(b)
t = time.time()
print '%s: IG %s, A %s, B %s' % (time.strftime('%F %T'), igstr, astr,
bstr)
if args.diff and lasts:
last = lasts[0]
diff = [x - y for x, y in zip(this, last)]
print ' D IG %s, A %s, B %s' % (fmts(diff[0]), fmts(
diff[1]), fmts(diff[2]))
if f:
f.write('%s, %s, %s, %s\n' % (t, igstr, astr, bstr))
f.flush()
lasts = [this] + lasts[0:args.trend_n - 1]
if args.stat and len(lasts) > 1:
s = ''
for chan in zip(*lasts):
chanl = [math.log(x, 10) for x in chan]
sd = statistics.stdev(chanl)
u = statistics.mean(chanl)
s += '(%s, %s) ' % (fmte(u), fmte(sd))
print ' % 3u %s' % (len(lasts), s)