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cusf-standalone-predictor
kopia lustrzana https://github.com/jonsowman/cusf-standalone-predictor
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Merge pull request #97 from danielrichman/master 

Save GFS files to a temporary directory, then clean up.
pull/98/merge
Adam Greig 2012-12-23 12:07:45 -08:00
rodzic d6aa9b818c 869a4203bb
commit b97f1730fa
1 zmienionych plików z 18 dodań i 8 usunięć
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predict.py
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@ -15,6 +15,9 @@ import calendar
import optparse import optparse
import subprocess import subprocess
import statsd import statsd
import tempfile
import shutil
import bisect
import simplejson as json import simplejson as json
statsd.init_statsd({'STATSD_BUCKET_PREFIX': 'habhub.predictor'}) statsd.init_statsd({'STATSD_BUCKET_PREFIX': 'habhub.predictor'})
@ -91,10 +94,6 @@ def main():
help='search for dataset covering the POSIX timestamp TIME \t[default: now]', help='search for dataset covering the POSIX timestamp TIME \t[default: now]',
metavar='TIME', type='int', metavar='TIME', type='int',
default=calendar.timegm(datetime.datetime.utcnow().timetuple())) default=calendar.timegm(datetime.datetime.utcnow().timetuple()))
parser.add_option('-o', '--output', dest='output',
help='file to write GFS data to with \'%(VAR)\' replaced with the the value of VAR [default: %default]',
metavar='FILE',
default='gfs/gfs_%(time)_%(lat)_%(lon)_%(latdelta)_%(londelta).dat')
parser.add_option('-v', '--verbose', action='count', dest='verbose', parser.add_option('-v', '--verbose', action='count', dest='verbose',
help='be verbose. The more times this is specified the more verbose.', default=False) help='be verbose. The more times this is specified the more verbose.', default=False)
parser.add_option('-p', '--past', dest='past', parser.add_option('-p', '--past', dest='past',
@ -259,7 +258,14 @@ def main():
options.lat, options.latdelta, \ options.lat, options.latdelta, \
options.lon, options.londelta) options.lon, options.londelta)
write_file(options.output, dataset, \ gfs_dir = "/var/www/cusf-standalone-predictor/gfs/"
gfs_dir = tempfile.mkdtemp(dir=gfs_dir)
gfs_filename = "gfs_%(time)_%(lat)_%(lon)_%(latdelta)_%(londelta).dat"
output_format = os.path.join(gfs_dir, gfs_filename)
write_file(output_format, dataset, \
window, \ window, \
time_to_find - datetime.timedelta(hours=options.past), \ time_to_find - datetime.timedelta(hours=options.past), \
time_to_find + datetime.timedelta(hours=options.future)) time_to_find + datetime.timedelta(hours=options.future))
@ -273,7 +279,9 @@ def main():
else: else:
alarm_flags = [] alarm_flags = []
subprocess.call([pred_binary, '-i/var/www/cusf-standalone-predictor/gfs/', '-v', '-o'+uuid_path+'flight_path.csv', uuid_path+'scenario.ini'] + alarm_flags) subprocess.call([pred_binary, '-i' + gfs_dir, '-v', '-o'+uuid_path+'flight_path.csv', uuid_path+'scenario.ini'] + alarm_flags)
shutil.rmtree(gfs_dir)
update_progress(pred_running=False, pred_complete=True) update_progress(pred_running=False, pred_complete=True)
statsd.increment('success') statsd.increment('success')
@ -302,8 +310,10 @@ def write_file(output_format, data, window, mintime, maxtime):
assert(hgtprs_global.dimensions == ('time', 'lev', 'lat', 'lon')) assert(hgtprs_global.dimensions == ('time', 'lev', 'lat', 'lon'))
# Work out what times we want to download # Work out what times we want to download
times = filter(lambda x: (x >= mintime) & (x <= maxtime), times = sorted(map(timestamp_to_datetime, hgtprs_global.maps['time']))
map(timestamp_to_datetime, hgtprs_global.maps['time'])) times_first = max(0, bisect.bisect_right(times, mintime) - 1)
times_last = min(len(times), bisect.bisect_left(times, maxtime) + 1)
times = times[times_first:times_last]
num_times = len(times) num_times = len(times)
current_time = 0 current_time = 0