def main(path1, path2, logfile=None):
from act_parser import ActParser
from act_sample_norm import normalize
print_samples = False
if logfile:
log = open(logfile, "w")
def log_score_enabled(o, s):
print >> log, o, s
global log_score
log_score = log_score_enabled
else:
log = sys.stdout
print_samples = True
print >> log, "# Reading activity data from %s..." % (path1),
p1 = ActParser(path1)
l1 = list(normalize(p1.samples()))
print >> log, "done, read %d samples" % (len(l1))
print >> log, "# Reading activity data from %s..." % (path2),
p2 = ActParser(path2)
l2 = list(normalize(p2.samples()))
print >> log, "done, read %d samples" % (len(l2))
o = int(l1[0].t - l2[0].t)
print >> log, "# Timestamps are offset by %ds" % (o)
if abs(o) > min(len(l1), len(l2)):
print >> log, "# Offset is too big. Assuming clocks out-of-whack..."
o = 0
o, score = find_local_max_correlation_offset(l1, l2, o)
print >> log, "# Minimum score at offset %d is %.2f m" % (o, score)
if print_samples:
for s, t in zip_samples_at_offset(l1, l2, o):
print >> log, "{}\n\t{}\n\t{}".format(geodistance(s, t), s, t)
return 0
def closer(a, b):
"""Return a score that's higher, the closer a and b are to eachother."""
return -geodistance(a, b)
