def create_time_axis(freq, path, name, has_bounds):
global log, start_date_, ref_date_
date_times = cmor_utils.read_time_stamps(path)
if len(date_times) == 0:
log.error("Empty time step list encountered at time axis creation for files %s" % str(path))
return 0, [], []
if has_bounds:
bounds = numpy.empty([len(date_times), 2])
rounded_times = map(lambda time: (cmor_utils.get_rounded_time(freq, time)), date_times)
dt_low = rounded_times
dt_up = rounded_times[1:] + [cmor_utils.get_rounded_time(freq, date_times[-1], 1)]
bounds[:, 0], units = cmor_utils.date2num([t - timeshift for t in dt_low], ref_date_)
bounds[:, 1], units = cmor_utils.date2num([t - timeshift for t in dt_up], ref_date_)
times = bounds[:, 0] + (bounds[:, 1] - bounds[:, 0]) / 2
return cmor.axis(table_entry=str(name), units=units, coord_vals=times, cell_bounds=bounds), dt_low, dt_up
step = cmor_utils.make_cmor_frequency(freq)
if date_times[0] >= start_date_ + step:
date = date_times[0]
extra_dates = []
while date > start_date_:
date = date - step
extra_dates.append(date)
log.warning("The file %s seems to be missing %d time stamps at the beginning, these will be added" %
(path, len(extra_dates)))
date_times = extra_dates[::-1] + date_times
if date_times[0] < start_date_:
date_times = [t for t in date_times if t >= start_date_]
log.warning("The file %s seems to be containing %d too many time stamps at the beginning, these will be "
"removed" % (path, len([t for t in date_times if t >= start_date_])))
times, units = cmor_utils.date2num([t - timeshift for t in date_times], ref_date_)
return cmor.axis(table_entry=str(name), units=units, coord_vals=times), date_times, date_times
def create_time_axis(freq, path, name, has_bounds):
global log, start_date_, ref_date_
command = cdo.Cdo()
times = command.showtimestamp(input=path)[0].split()
datetimes = sorted(
set(
map(lambda s: datetime.datetime.strptime(s, "%Y-%m-%dT%H:%M:%S"),
times)))
if len(datetimes) == 0:
log.error(
"Empty time step list encountered at time axis creation for files %s"
% str(path))
return
refdate = cmor_utils.make_datetime(ref_date_)
if has_bounds:
n = len(datetimes)
bounds = numpy.empty([n, 2])
rounded_times = map(
lambda time:
(cmor_utils.get_rounded_time(freq, time) - refdate).total_seconds(
) / 3600., datetimes)
bounds[:, 0] = rounded_times[:]
bounds[0:n - 1, 1] = rounded_times[1:n]
bounds[n - 1,
1] = (cmor_utils.get_rounded_time(freq, datetimes[n - 1], 1) -
refdate).total_seconds() / 3600.
times[:] = bounds[:, 0] + (bounds[:, 1] - bounds[:, 0]) / 2
return cmor.axis(table_entry=str(name),
units="hours since " + str(ref_date_),
coord_vals=times,
cell_bounds=bounds)
times = numpy.array([(d - refdate).total_seconds() / 3600
for d in datetimes])
return cmor.axis(table_entry=str(name),
units="hours since " + str(ref_date_),
coord_vals=times)