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Javier Vegas-Regidor
committed
import shutil
import threading
import uuid
from datetime import datetime
import netCDF4
import numpy as np
import os
from autosubmit.date.chunk_date_lib import parse_date, chunk_start_date, chunk_end_date, previous_day, add_months, \
date2str
def __init__(self, institution, model, expid, datafolder, frequency, chunk_size, experiment_name, num_chunks,
scratch_dir, nfrp, member_digits, calendar='standard'):
"""
:param institution:
:param model:
:param expid:
:param datafolder:
:param frequency:
:param chunk_size:
:param experiment_name:
:param num_chunks:
:param calendar:
"""
self.initialization_method = 'to be filled'
self.initialization_description = 'to be filled'
self.physics_version = 'to be filled'
self.physics_description = 'to be filled'
self.associated_model = 'to be filled'
self.source = 'to be filled'
self.associated_experiment = 'to be filled'
self.institution = institution
self.model = model
self.expid = expid
self.data_dir = datafolder
self.frequency = frequency
self.chunk_size = chunk_size
self.experiment_name = experiment_name
self.add_startdate = True
self.add_name = True
self.num_chunks = num_chunks
self.calendar = calendar
self.scratch_dir = scratch_dir
self.nfrp = nfrp
self.member_digits = member_digits
# noinspection PyPep8Naming
def prepare_CMOR_files(self, startdates, members, force_rebuild):
"""
Prepares the data to be used by the diagnostic.
If CMOR data is not created, it show a warning and closes. In the future, an automatic cmorization procedure
will be launched
If CMOR data is available but packed, the procedure will unpack it.
:param force_rebuild: if True, forces the creation of the CMOR files
:type force_rebuild: bool
:param startdates: list of startdates that will be used by the diagnostics
:type startdates: list[str]
:param members: lists of members that will be used by the diagnostics
:type members: list[int]
:return:
"""
if force_rebuild or not os.path.exists(os.path.join(self.data_dir, self.expid, 'cmorfiles')):
for startdate in startdates:
for member in members:
Log.info('Untaring member S{0} {1}', startdate, self.get_member_str(member))
for tarfile in glob.glob(os.path.join(self.data_dir, self.expid, 'original_files', startdate,
self.get_member_str(member),
self._unpack_tar(member, startdate, tarfile)
grb_path = os.path.join(self.data_dir, self.expid, 'original_files', startdate,
self.get_member_str(member), 'outputs', '*.grb')
gribfiles = glob.glob(grb_path)
if len(gribfiles) == 0:
for tarfile in glob.glob(os.path.join(self.data_dir, self.expid, 'original_files', startdate,
self.get_member_str(member),
'outputs', 'MMA*')):
self._unpack_tar(member, startdate, tarfile)
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else:
gribfiles.sort()
copied_gribfiles = list()
for gribfile in gribfiles:
shutil.copy(gribfile, os.path.join(self.scratch_dir, os.path.basename(gribfile)))
copied_gribfiles.append(os.path.join(self.scratch_dir, os.path.basename(gribfile)))
for gribfile in copied_gribfiles:
cdo = Utils.cdo
start = parse_date(gribfile[-10:-4])
month = '{0:02}'.format(start.month)
times = cdo.showtimestamp(input=gribfile)
times = times[0].split()[0:2]
time_diff = datetime.strptime(times[1], '%Y-%m-%dT%H:%M:%S') - datetime.strptime(times[0],
'%Y-%m-%dT%H:%M:%S')
NFRP = (time_diff.seconds // 3600)
param_6hr = (151, 167, 168, 164, 165, 166, 129,)
param_day = (167, 165, 166, 151, 164, 168, 169, 177, 179, 228, 201, 202, 130)
param_mon = (167, 201, 202, 165, 166, 151, 144, 228, 205, 182, 164, 146, 147, 176, 169,
177, 175, 212, 141, 180, 181, 179, 168, 243, 129, 130, 131, 132, 133)
grid = os.path.basename(gribfile)[3:5]
if os.path.exists('ICM{0}{1}+{2.year}{2.month:02}.grb'.format(grid, self.expid,
add_months(start, -1,
'standard'))):
fd = open('rules_files', 'w')
fd.write('if (dataDate >= {0.year}{0.month:02}01) {{ write ; }}\n'.format(start))
fd.close()
# get first timestep for each month from previous file (if possible)
if os.path.exists('ICM'):
os.remove('ICM')
Utils.execute_shell_command('grib_filter -o ICM rules_files '
'ICM{0}{1}+{2.year}{2.month:02}.grb '
'{3}'.format(grid, self.expid,
add_months(start, -1, 'standard'),
gribfile))
os.remove('rules_files')
else:
shutil.copy(gribfile, 'ICM')
# remap on regular Gauss grid
if grid == 'SH':
Utils.cdo.splitparam(input='-sp2gpl ICM', output=gribfile + '_')
else:
Utils.cdo.splitparam(input='ICM', output=gribfile + '_', options='-R')
# total precipitation (remove negative values)
Utils.cdo.setcode(228, input='-setmisstoc,0 -setvrange,0,Inf -add '
'{0}_{{142,143}}.128.grb'.format(gribfile),
output='{0}_228.128.grb'.format(gribfile))
os.remove('ICM')
cdo_reftime = parse_date(startdate).strftime('%Y-%m-%d,00:00')
# daily variables
for param in param_day:
if not os.path.exists('{0}_{1}.128.grb'.format(gribfile, param)):
continue
new_units = None
if param in (169, 177, 179):
# radiation
new_units = "W m-2"
cdo_operator = "-divc,{0} -daymean -selmon,{2} " \
"-shifttime,-{1}hours".format(NFRP * 3600, NFRP, month)
elif param == 228:
# precipitation
new_units = "kg m-2 -s"
cdo_operator = "-mulc,1000 -divc,{0} -daymean -selmon,{2} " \
"-shifttime,-{1}hours".format(NFRP * 3600, NFRP, month)
elif param == 201:
# maximum
cdo_operator = "-daymax -selmon,{1} -shifttime,-{0}hours".format(NFRP, month)
elif param == 202:
# minmimum
cdo_operator = "-daymin -selmon,{1} -shifttime,-{0}hours".format(NFRP, month)
elif param == 130:
# 850 hPa
cdo_operator = "-daymean -sellevel,85000 -selmon,{0}".format(month)
else:
# default, plain daily mean
cdo_operator = "-daymean -selmon,{0}".format(month)
Utils.execute_shell_command('cdo -f nc -t ecmwf setreftime,{0} '
'{1} {2}_{3}.128.grb '
'{2}_{3}_day.nc'.format(cdo_reftime, cdo_operator,
gribfile, param))
if new_units:
handler = Utils.openCdf('{0}_{1}_day.nc'.format(gribfile, param))
for var in handler.variables.values():
if 'code' in var.ncattrs() and var.code == param:
var.units = new_units
break
handler.close()
# concat all vars in one file for day
Utils.nco.ncks(input='{0}_{1}_day.nc'.format(gribfile, param),
output='{0}_day.nc'.format(gribfile), options='-A')
os.remove('{0}_{1}_day.nc'.format(gribfile, param))
# monthly variables
for param in param_mon:
if not os.path.exists('{0}_{1}.128.grb'.format(gribfile, param)):
continue
new_units = None
if param in (146, 147, 176, 169, 177, 175, 179, 212):
# radiation/heat
new_units = "W m-2"
cdo_operator = "-divc,{0} -monmean -selmon,{2} " \
"-shifttime,-{1}hours".format(NFRP * 3600, NFRP, month)
elif param in (180, 181):
# momentum flux
new_units = "N m-2"
cdo_operator = "-divc,{0} -monmean -selmon,{2} " \
"-shifttime,-{1}hours".format(NFRP * 3600, NFRP, month)
elif param in (144, 228, 205, 182):
# precipitation/evaporation/runoff
new_units = "kg m-2 s-1"
cdo_operator = "-mulc,1000 -divc,{0} -monmean -selmon,{2} " \
"-shifttime,-{1}hours".format(NFRP * 3600, NFRP, month)
elif param == 201:
# mean daily maximum
cdo_operator = "-monmean -daymax -selmon,{1} " \
"-shifttime,-{0}hours".format(NFRP, month)
elif param == 202:
# mean daily minmimum
cdo_operator = "-monmean -daymin -selmon,{1} " \
"-shifttime,-{0}hours".format(NFRP, month)
elif param in (130, 131, 132, 133):
# upper-air
cdo_operator = "-monmean -sellevel,5000,20000,50000,85000 " \
"-selmon,{0}".format(month)
elif param == 129:
# upper-air geopotential
new_units = "m"
cdo_operator = "-divc,9.81 -timmean -sellevel,5000,20000,50000,85000 " \
"-selmon,{0}".format(month)
else:
# default, plain monthly mean
cdo_operator = "-monmean -selmon,{0}".format(month)
Utils.execute_shell_command('cdo -f nc -t ecmwf setreftime,{0} '
'{1} {2}_{3}.128.grb '
'{2}_{3}_mon.nc'.format(cdo_reftime, cdo_operator,
gribfile, param))
handler = Utils.openCdf('{0}_{1}_mon.nc'.format(gribfile, param))
if new_units:
for var in handler.variables.values():
if 'code' in var.ncattrs() and var.code == param:
var.units = new_units
break
var_name = None
for key in handler.variables.keys():
if key + '_2' in handler.variables and key not in handler.dimensions:
var_name = key
handler.close()
if var_name is not None:
Utils.nco.ncks(input='{0}_{1}_mon.nc'.format(gribfile, param),
output='{0}_{1}_mon.nc'.format(gribfile, param),
options='-O -v {0}'.format(var_name))
# concat all vars in one file for mon
Utils.nco.ncks(input='{0}_{1}_mon.nc'.format(gribfile, param),
output='{0}_mon.nc'.format(gribfile), options='-A')
os.remove('{0}_{1}_mon.nc'.format(gribfile, param))
# 6-hourly variables
for param in param_6hr:
if not os.path.exists('{0}_{1}.128.grb'.format(gribfile, param)):
continue
new_units = None
if param == 129:
# geopotential
new_units = "m"
cdo_operator = "-divc,9.81 -sellevel,50000 -selmon,{0}".format(month)
else:
# default, plain monthly mean
cdo_operator = "-selmon,{0}".format(month)
Utils.execute_shell_command('cdo -f nc -t ecmwf setreftime,{0} '
'{1} {2}_{3}.128.grb '
'{2}_{3}_6hr.nc'.format(cdo_reftime, cdo_operator,
gribfile, param))
if new_units:
handler = Utils.openCdf('{0}_{1}_6hr.nc'.format(gribfile, param))
for var in handler.variables.values():
if 'code' in var.ncattrs() and var.code == param:
var.units = new_units
break
handler.close()
# concat all vars in one file for 6hr
Utils.nco.ncks(input='{0}_{1}_6hr.nc'.format(gribfile, param),
output='{0}_6hr.nc'.format(gribfile), options='-A')
os.remove('{0}_{1}_6hr.nc'.format(gribfile, param))
for splited_file in glob.glob('{0}_???.128.grb'.format(gribfile)):
os.remove(splited_file)
chunk_start = parse_date(startdate)
while os.path.exists(os.path.join(self.scratch_dir,
'ICMGG{0}+{1}.grb'.format(self.expid,
date2str(chunk_start)[:-2]))):
chunk_end = chunk_end_date(chunk_start, self.chunk_size, 'month', 'standard')
chunk_end = previous_day(chunk_end, 'standard')
chunk_files_gg_mon = list()
chunk_files_gg_day = list()
chunk_files_gg_6h = list()
chunk_files_sh_mon = list()
chunk_files_sh_day = list()
chunk_files_sh_6h = list()
for month in range(0, self.chunk_size):
chunk_file = 'ICMGG{0}+{1}.grb'.format(self.expid,
date2str(add_months(chunk_start, month,
'standard'))[:-2])
os.remove(chunk_file)
os.remove('ICMSH' + chunk_file[5:])
chunk_files_gg_mon.append(chunk_file + '_mon.nc')
chunk_files_gg_day.append(chunk_file + '_day.nc')
chunk_files_gg_6h.append(chunk_file + '_6hr.nc')
chunk_files_sh_mon.append('ICMSH' + chunk_file[5:] + '_mon.nc')
chunk_files_sh_day.append('ICMSH' + chunk_file[5:] + '_day.nc')
chunk_files_sh_6h.append('ICMSH' + chunk_file[5:] + '_6hr.nc')
self._merge_and_cmorize_atmos(startdate, member, chunk_start, chunk_end, chunk_files_sh_mon,
'SH', '1m')
self._merge_and_cmorize_atmos(startdate, member, chunk_start, chunk_end, chunk_files_sh_day,
'SH', '1d')
self._merge_and_cmorize_atmos(startdate, member, chunk_start, chunk_end, chunk_files_sh_6h,
'SH', '6hr')
self._merge_and_cmorize_atmos(startdate, member, chunk_start, chunk_end, chunk_files_gg_mon,
'GG', '1m')
self._merge_and_cmorize_atmos(startdate, member, chunk_start, chunk_end, chunk_files_gg_day,
'GG', '1d')
self._merge_and_cmorize_atmos(startdate, member, chunk_start, chunk_end, chunk_files_gg_6h,
'GG', '6hr')
chunk_start = chunk_end_date(chunk_start, self.chunk_size, 'month', 'standard')
return
for startdate in startdates:
for member in members:
Javier Vegas-Regidor
committed
member_path = os.path.join(self.data_dir, self.expid, 'cmorfiles', startdate,
self.get_member_str(member), 'outputs')
Log.info('Preparing CMOR files for startdate {0} and member {1}'.format(startdate, member))
filepaths = glob.glob(os.path.join(member_path, '*.gz'))
if len(filepaths) == 0:
continue
self._unpack_cmorfiles(filepaths, member_path)
def _merge_and_cmorize_atmos(self, startdate, member, chunk_start, chunk_end, chunk_files, grid, frequency):
merged_file = 'MMA_{0}_{1}_{2}_{3}.nc'.format(frequency, date2str(chunk_start), date2str(chunk_end), grid)
for x in range(0, len(chunk_files)):
chunk_files[x] = os.path.join(self.scratch_dir, chunk_files[x])
Utils.cdo.mergetime(input=' '.join(chunk_files), output=merged_file, options='-O')
for filepath in chunk_files:
os.remove(filepath)
self._cmorize_nc_file(merged_file, member, startdate)
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def _unpack_cmorfiles(self, filepaths, member_path):
threads = list()
numthreads = Utils.available_cpu_count()
for numthread in range(0, numthreads):
t = threading.Thread(target=DataManager._unzip,
args=([filepaths[numthread::numthreads]]))
threads.append(t)
t.start()
for t in threads:
t.join()
filepaths = glob.glob(os.path.join(member_path, '*.tar'))
for numthread in range(0, numthreads):
t = threading.Thread(target=DataManager._untar,
args=(filepaths[numthread::numthreads], member_path))
threads.append(t)
t.start()
for t in threads:
t.join()
if self.experiment_name != self.model:
bad_path = os.path.join(member_path, 'output', self.institution, self.model, self.model)
for (dirpath, dirnames, filenames) in os.walk(bad_path, False):
for filename in filenames:
filepath = os.path.join(dirpath, filename)
good = filepath.replace('_{0}_output_'.format(self.model),
'_{0}_{1}_'.format(self.model, self.experiment_name))
good = good.replace('/{0}/{0}'.format(self.model),
'/{0}/{1}'.format(self.model,
self.experiment_name))
Utils.move_file(filepath, good)
os.rmdir(dirpath)
good_dir = os.path.join(member_path, 'output', self.institution, self.model, self.experiment_name)
for sdate in os.listdir(good_dir):
for (dirpath, dirnames, filenames) in os.walk(os.path.join(good_dir, sdate), False):
for filename in filenames:
filepath = os.path.join(dirpath, filename)
good = filepath.replace('_{0}_{1}_r'.format(self.model, self.experiment_name, sdate),
'_{0}_{1}_{2}_r'.format(self.model, self.experiment_name, sdate))
if good != filepath:
Log.info('Moving {0} to {1}'.format(filename, good))
Utils.move_file(filepath, good)
def _unpack_tar(self, member, startdate, tarfile):
scratch_dir = os.path.join(self.scratch_dir, 'CMOR')
os.makedirs(scratch_dir)
self._untar((tarfile,), scratch_dir)
self._unzip(glob.glob(os.path.join(scratch_dir, '*.gz')))
if os.path.basename(tarfile).startswith('MMA'):
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for filename in glob.glob(os.path.join(scratch_dir, 'MMA_*_SH_*.nc')):
Utils.cdo.sp2gpl(options='-O', input=filename, output=temp)
shutil.move(temp, filename)
sh_files = glob.glob(os.path.join(scratch_dir, 'MMA_*_SH_*.nc'))
Utils.cdo.mergetime(input=sh_files, output=os.path.join(scratch_dir, 'sh.nc'))
gg_files = glob.glob(os.path.join(scratch_dir, 'MMA_*_GG_*.nc'))
Utils.cdo.mergetime(input=gg_files, output=os.path.join(scratch_dir, 'gg.nc'))
for filename in sh_files + gg_files:
os.remove(filename)
Utils.nco.ncks(input=os.path.join(scratch_dir, 'sh.nc'),
output=os.path.join(scratch_dir, 'gg.nc'), options='-A')
os.remove(os.path.join(scratch_dir, 'sh.nc'))
tar_startdate = tarfile[0:-4].split('_')[5].split('-')
new_name = 'MMA_1m_{0[0]}_{0[1]}.nc'.format(tar_startdate)
shutil.move(os.path.join(scratch_dir, 'gg.nc'), os.path.join(scratch_dir, new_name))
for filename in glob.glob(os.path.join(scratch_dir, '*.nc')):
self._cmorize_nc_file(filename, member, startdate)
def _cmorize_nc_file(self, filename, member, startdate):
Log.info('Processing file {0}', filename)
file_parts = os.path.basename(filename).split('_')
frequency = file_parts[1][1].lower()
variables = dict()
variables['time_counter'] = 'time'
variables['time_counter_bnds'] = 'time_bnds'
# variables['time_counter_bounds'] = 'time_bnds'
variables['tbnds'] = 'bnds'
# variables['axis_nbounds'] = 'bnds'
variables['nav_lat'] = 'lat'
variables['nav_lon'] = 'lon'
variables['x'] = 'i'
variables['y'] = 'j'
Utils.rename_variables(filename, variables, False, True)
handler = Utils.openCdf(filename)
self._add_common_attributes(frequency, handler, member, startdate)
self._update_time_variables(handler, startdate)
handler.sync()
temp = TempFile.get()
Log.info('Splitting file {0}', filename)
for variable in handler.variables.keys():
if variable in ('lon', 'lat', 'time', 'time_bnds', 'leadtime', 'lev', 'icethi',
'deptht', 'depthu', 'depthw', 'depthv', 'time_centered', 'time_centered_bounds',
'deptht_bounds', 'depthu_bounds', 'depthv_bounds', 'depthw_bounds',
'time_counter_bounds', 'ncatice',
'nav_lat_grid_V', 'nav_lat_grid_U', 'nav_lat_grid_T',
'nav_lon_grid_V', 'nav_lon_grid_U', 'nav_lon_grid_T',):
continue
self.extract_variable(file_parts, filename, frequency, handler, member, startdate, temp,
variable)
Log.result('File {0} cmorized!', filename)
handler.close()
os.remove(filename)
def extract_variable(self, file_parts, filename, frequency, handler, member, startdate, temp, variable):
var_cmor = Variable.get_variable(variable)
if var_cmor is None:
return
Utils.nco.ncks(input=filename, output=temp, options='-v {0}'.format(variable))
Utils.rename_variables(temp, {'deptht': 'lev', 'depthu': 'lev', 'depthw': 'lev', 'depthv': 'lev'}, False, True)
handler_cmor = Utils.openCdf(temp)
Utils.copy_variable(handler, handler_cmor, 'lon', False)
Utils.copy_variable(handler, handler_cmor, 'lat', False)
if 'time' in handler_cmor.dimensions.keys():
Utils.copy_variable(handler, handler_cmor, 'leadtime', False)
handler_cmor.modeling_realm = var_cmor.domain
handler_cmor.table_id = 'SPECS_' + self.domain_abbreviation(var_cmor.domain, frequency)
var_handler = handler_cmor.variables[variable]
var_handler.short_name = var_cmor.short_name
var_handler.standard_name = var_cmor.standard_name
var_handler.long_name = var_cmor.long_name
handler_cmor.close()
if frequency == 'd':
frequency = 'day'
elif frequency == 'm':
frequency = 'mon'
elif frequency == 'h':
frequency = '6hr'
else:
raise Exception('Frequency {0} not supported'.format(frequency))
if var_cmor.basin is None:
region = None
else:
region = var_cmor.basin.fullname
self.send_file(temp, var_cmor.domain, var_cmor.short_name, startdate, member,
frequency=frequency, rename_var=variable,
date_str='{0}-{1}'.format(file_parts[2][0:6], file_parts[3][0:6]),
region=region)
@staticmethod
def _update_time_variables(handler, startdate):
time_var = handler.variables['time']
times = netCDF4.num2date(time_var[:], time_var.units, time_var.calendar)
if type(times[0]) is not datetime:
for x in range(0, times.shape[0]):
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# noinspection PyProtectedMember
times[x] = times[x]._to_real_datetime()
time_var[:] = netCDF4.date2num(times, 'days since 1850-01-01', 'standard')
if 'axis_nbounds' in handler.dimensions:
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handler.renameDimension('axis_nbounds', 'bnds')
if 'time_counter_bounds' in handler.variables:
handler.renameVariable('time_counter_bounds', 'time_bnds')
handler.sync()
if 'time_bnds' in handler.variables:
time_bounds_var = handler.variables['time_bnds']
time_var.bounds = "time_bnds"
time_bounds = netCDF4.num2date(time_bounds_var[:], time_var.units, time_var.calendar)
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if type(time_bounds[0, 0]) is not datetime:
for x in range(0, time_bounds.shape[0]):
for y in range(0, time_bounds.shape[1]):
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# noinspection PyProtectedMember
time_bounds[x, y] = time_bounds[x, y]._to_real_datetime()
time_bounds_var[:] = netCDF4.date2num(time_bounds, 'days since 1850-01-01', 'standard')
time_var.units = 'days since 1850-01-01'
time_var.time_origin = "1850-01-01"
time_var.calendar = 'standard'
time_var.long_name = "Verification time of the forecast"
time_var.standard_name = "time"
time_var.axis = "T"
if 'leadtime' in handler.variables:
var = handler.variables['leadtime']
else:
var = handler.createVariable('leadtime', float, 'time')
var.units = "days"
var.long_name = "Time elapsed since the start of the forecast"
var.standard_name = "forecast_period"
leadtime = (netCDF4.num2date(time_var[:], time_var.units, time_var.calendar) - parse_date(startdate))
for lt in range(0, leadtime.shape[0]):
var[lt] = leadtime[lt].days
def _add_common_attributes(self, frequency, handler, member, startdate):
handler.associated_experiment = self.associated_experiment
handler.batch = '{0}{1}'.format(self.institution, datetime.now().strftime('%Y-%m-%dT%H:%M:%SZ'))
handler.contact = 'Pierre-Antoine Bretonnire, pierre-antoine.bretonniere@bsc.es , ' \
'Javier Vegas-Regidor, javier.vegas@bsc.es '
handler.conventions = 'CF-1.6'
handler.creation_date = datetime.now().strftime('%Y-%m-%dT%H:%M:%SZ')
handler.experiment_id = self.experiment_name
handler.forecast_reference_time = datetime.now().strftime('%Y-%m-%dT%H:%M:%SZ')
if frequency == 'd':
handler.frequency = 'daily'
elif frequency == 'm':
handler.frequency = 'monthly'
handler.institute_id = self.institution
handler.institution = self.institution
handler.initialization_method = self.initialization_method
handler.initialization_description = self.initialization_description
handler.physics_version = self.physics_version
handler.physics_description = self.physics_description
handler.associated_model = self.associated_model
handler.project_id = 'SPECS'
handler.realization = member
handler.source = self.source
handler.startdate = 'S{0}'.format(startdate)
handler.tracking_id = str(uuid.uuid1())
handler.title = "{0} model output prepared for SPECS {1}".format(self.model, self.experiment_name)
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@staticmethod
def _unzip(files):
for filepath in files:
Log.debug('Unzipping {0}', filepath)
Utils.execute_shell_command('gunzip {0}'.format(filepath))
@staticmethod
def _untar(files, member_path):
for filepath in files:
Log.debug('Unpacking {0}', filepath)
Utils.execute_shell_command('tar -xvf {0} -C {1}'.format(filepath, member_path))
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def get_files(self, startdate, member, chunk, domain, variables, grid=None):
"""
Returns a list of filenames for different variables
:param startdate: startdate to retrieve
:type startdate: str
:param member: member to retrieve
:type member: int
:param chunk: chunk to retrieve
:type chunk: int
:param domain: variable's CMOR domain
:type domain:str
:param variables: variables list
:type variables: list[str], tuple[str]
:param grid: specifies if the variable must be in a interpolated grid
:type grid: str
:return:
"""
domain_abreviattion = self.domain_abbreviation(domain, self.frequency)
start = parse_date(startdate)
member_plus = str(member + 1)
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member_path = os.path.join(self.data_dir, self.expid, 'cmorfiles', startdate, self.get_member_str(member),
'outputs', 'output', self.institution, self.model, self.experiment_name,
'S' + startdate, self.frequency, domain)
chunk_start = chunk_start_date(start, chunk, self.chunk_size, 'month', 'standard')
chunk_end = chunk_end_date(chunk_start, self.chunk_size, 'month', 'standard')
chunk_end = previous_day(chunk_end, 'standard')
var_file = list()
for var in variables:
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if grid:
var_path = os.path.join(member_path, var, grid, 'r{0}i1p1'.format(member_plus))
else:
var_path = os.path.join(member_path, var, 'r{0}i1p1'.format(member_plus))
var_file.append(os.path.join(var_path,
'{7}-{8}.nc'.format(var, domain_abreviattion,
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self.frequency, self.model, self.experiment_name,
startdate, member_plus,
"{0:04}{1:02}".format(chunk_start.year,
chunk_start.month),
"{0:04}{1:02}".format(chunk_end.year,
chunk_end.month))))
file_names.append(var_file)
return file_names
def get_file(self, domain, var, startdate, member, chunk, grid=None, box=None, frequency=None):
"""
Copies a given file from the CMOR repository to the scratch folder and returns the path to the scratch's copy
:param domain: CMOR domain
:type domain: str
:param var: variable name
:type var: str
:param startdate: file's startdate
:type startdate: str
:param member: file's member
:type member: int
:param chunk: file's chunk
:type chunk: int
:param grid: file's grid (only needed if it is not the original)
:type grid: str
:param box: file's box (only needed to retrieve sections or averages)
:type box: Box
:param frequency: file's frequency (only needed if it is different from the default)
:type frequency: str
:return: path to the copy created on the scratch folder
:rtype: str
"""
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if not frequency:
frequency = self.frequency
domain_abbreviation = self.domain_abbreviation(domain, frequency)
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start = parse_date(startdate)
member_plus = str(member + 1)
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member_path = os.path.join(self.data_dir, self.expid, 'cmorfiles', startdate, self.get_member_str(member),
'outputs', 'output', self.institution, self.model, self.experiment_name,
'S' + startdate, frequency, domain)
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chunk_start = chunk_start_date(start, chunk, self.chunk_size, 'month', 'standard')
chunk_end = chunk_end_date(chunk_start, self.chunk_size, 'month', 'standard')
chunk_end = previous_day(chunk_end, 'standard')
if box:
var += box.get_lon_str() + box.get_lat_str() + box.get_depth_str()
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if grid:
var_path = os.path.join(member_path, var, grid, 'r{0}i1p1'.format(member_plus))
else:
var_path = os.path.join(member_path, var, 'r{0}i1p1'.format(member_plus))
filepath = os.path.join(var_path, '{0}_{1}_{3}_{4}_S{5}_r{6}i1p1_'
'{7}-{8}.nc'.format(var, domain_abbreviation, frequency, self.model,
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self.experiment_name, startdate, member_plus,
"{0:04}{1:02}".format(chunk_start.year,
chunk_start.month),
"{0:04}{1:02}".format(chunk_end.year,
chunk_end.month)))
temp_path = TempFile.get()
shutil.copyfile(filepath, temp_path)
return temp_path
def send_file(self, filetosend, domain, var, startdate, member, chunk=None, grid=None, region=None, box=None,
rename_var=None, frequency=None, year=None, date_str=None):
"""
Copies a given file to the CMOR repository. It also automatically converts to netCDF 4 if needed and can merge
with already existing ones as needed
711
712
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719
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723
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732
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735
736
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:param year: if frequency is yearly, this parameter is used to give the corresponding year
:type year: int
:param rename_var: if exists, the given variable will be renamed to the one given by var
:type rename_var: str
:param filetosend: path to the file to send to the CMOR repository
:type filetosend: str
:param region: specifies the region represented by the file. If it is defined, the data will be appended to the
CMOR repository as a new region in the file or will overwrite if region was already present
:type region: str
:param domain: CMOR domain
:type domain: str
:param var: variable name
:type var: str
:param startdate: file's startdate
:type startdate: str
:param member: file's member
:type member: int
:param chunk: file's chunk
:type chunk: int
:param grid: file's grid (only needed if it is not the original)
:type grid: str
:param box: file's box (only needed to retrieve sections or averages)
:type box: Box
:param frequency: file's frequency (only needed if it is different from the default)
:type frequency: str
:return: path to the copy created on the scratch folder
:rtype: str
"""
if box:
var += box.get_lon_str() + box.get_lat_str() + box.get_depth_str()
if rename_var:
Utils.rename_variable(filetosend, rename_var, var)
if not frequency:
frequency = self.frequency
domain_abreviattion = self.domain_abbreviation(domain, frequency)
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start = parse_date(startdate)
member_plus = str(member + 1)
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member_path = os.path.join(self.data_dir, self.expid, 'cmorfiles', startdate, self.get_member_str(member),
'outputs', 'output', self.institution, self.model, self.experiment_name,
'S' + startdate,
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if chunk is not None:
chunk_start = chunk_start_date(start, chunk, self.chunk_size, 'month', 'standard')
chunk_end = chunk_end_date(chunk_start, self.chunk_size, 'month', 'standard')
chunk_end = previous_day(chunk_end, 'standard')
time_bound = "{0:04}{1:02}-{2:04}{3:02}".format(chunk_start.year, chunk_start.month, chunk_end.year,
chunk_end.month)
elif year is not None:
if frequency is not 'yr':
raise ValueError('Year may be provided instead of chunk only if frequency is "yr"')
time_bound = str(year)
elif date_str is not None:
time_bound = date_str
else:
raise ValueError('Chunk and year can not be None at the same time')
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if grid:
var_path = os.path.join(member_path, var, grid, 'r{0}i1p1'.format(member_plus))
else:
var_path = os.path.join(member_path, var, 'r{0}i1p1'.format(member_plus))
filepath = os.path.join(var_path, '{0}_{1}_{2}_{3}_S{4}_r{5}i1p1_'
'{6}.nc'.format(var, domain_abreviattion, self.model,
self.experiment_name, startdate, member_plus, time_bound))
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if region:
if not os.path.exists(filepath):
handler = Utils.openCdf(filetosend)
handler.createDimension('region')
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var_region = handler.createVariable('region', str, 'region')
var_region[0] = region
original_var = handler.variables[var]
new_var = handler.createVariable('new_var', original_var.datatype,
original_var.dimensions + ('region',))
new_var.setncatts({k: original_var.getncattr(k) for k in original_var.ncattrs()})
value = original_var[:]
new_var[..., 0] = value
handler.close()
Utils.nco.ncks(input=filetosend, output=filetosend, options='-O -x -v {0}'.format(var))
Utils.rename_variable(filetosend, 'new_var', var)
else:
temp = TempFile.get()
shutil.copyfile(filepath, temp)
Utils.nco.ncks(input=temp, output=temp, options='-O --mk_rec_dmn region')
handler = Utils.openCdf(temp)
handler_send = Utils.openCdf(filetosend)
value = handler_send.variables[var][:]
var_region = handler.variables['region']
basin_index = np.where(var_region[:] == region)
if len(basin_index[0]) == 0:
var_region[var_region.shape[0]] = region
basin_index = var_region.shape[0] - 1
else:
basin_index = basin_index[0][0]
handler.variables[var][..., basin_index] = value
handler.close()
handler_send.close()
Utils.move_file(temp, filetosend)
Utils.nco.ncks(input=filetosend, output=filetosend, options='-O --fix_rec_dmn region')
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temp = TempFile.get()
Utils.execute_shell_command(["nccopy", "-4", "-d4", "-s", filetosend, temp])
shutil.move(temp, filetosend)
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Utils.move_file(filetosend, filepath)
if frequency in ('d', 'daily', 'day'):
freq_str = 'daily_mean'
else:
freq_str = 'monthly_mean'
if domain in ['ocean', 'seaIce']:
link_path = os.path.join(self.data_dir, self.expid, freq_str, '{0}_f6h'.format(var))
else:
link_path = os.path.join(self.data_dir, self.expid, freq_str, '{0}_f{1}h'.format(var, self.nfrp))
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if not os.path.exists(link_path):
# This can be a race condition
# noinspection PyBroadException
try:
os.makedirs(link_path)
except Exception:
pass
link_path = os.path.join(link_path, os.path.basename(filepath))
if os.path.lexists(link_path):
os.remove(link_path)
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os.symlink(filepath, link_path)
@staticmethod
def domain_abbreviation(domain, frequency):
if frequency == 'mon':
if domain == 'seaIce':
domain_abreviattion = 'OImon'
else:
domain_abreviattion = domain[0].upper() + 'mon'
elif frequency == '6hr':
domain_abreviattion = '6hrPlev'
else:
domain_abreviattion = 'day'
return domain_abreviattion
def get_year(self, domain, var, startdate, member, year, grid=None, box=None):
Gets all the data corresponding to a given year from the CMOR repository to the scratch folder as one file and
returns the path to the scratch's copy.
:param year: year to retrieve
:type year: int
:param domain: CMOR domain
:type domain: str
:param var: variable name
:type var: str
:param startdate: file's startdate
:type startdate: str
:param member: file's member
:type member: int
:param grid: file's grid (only needed if it is not the original)
:type grid: str
:param box: file's box (only needed to retrieve sections or averages)
:type box: Box
:return: path to the copy created on the scratch folder
:rtype: str
"""
chunk_files = list()
for chunk in self.get_year_chunks(startdate, year):
chunk_files.append(self.get_file(domain, var, startdate, member, chunk, grid=grid, box=box))
if len(chunk_files) > 1:
temp = TempFile.get()
Utils.nco.ncrcat(input=' '.join(chunk_files), output=temp)
for chunk_file in chunk_files:
os.remove(chunk_file)
else:
temp = chunk_files[0]
temp2 = TempFile.get()
handler = Utils.openCdf(temp)
time = Utils.get_datetime_from_netcdf(handler)
handler.close()
start = None
end = None
for x in range(0, len(time)):
date = time[x]
if date.year == year:
if date.month == 1:
start = x
elif date.month == 12:
end = x
Utils.nco.ncks(input=temp, output=temp2, options='-O -d time,{0},{1}'.format(start, end))
os.remove(temp)
return temp2
def get_year_chunks(self, startdate, year):
"""
Get the list of chunks containing timesteps from the given year
:param startdate: startdate to use
:type startdate: str
:param year: reference year
:type year: int
:return: list of chunks containing data from the given year
:rtype: list[int]
date = parse_date(startdate)
chunks = list()
for chunk in range(1, self.num_chunks + 1):
chunk_start = chunk_start_date(date, chunk, self.chunk_size, 'month', self.calendar)
if chunk_start.year > year:
break
elif chunk_start.year == year or chunk_end_date(chunk_start, self.chunk_size, 'month',
self.calendar).year == year:
return chunks
def get_full_years(self, startdate):
"""
Returns the list of full years that are in the given startdate
:param startdate: startdate to use
:type startdate: str
:return: list of full years
:rtype: list[int]
"""
chunks_per_year = 12 / self.chunk_size
date = parse_date(startdate)
first_january = 0
first_year = date.year
if date.month != 1:
month = date.month
first_year += 1
while month + self.chunk_size < 12:
month += self.chunk_size
first_january += 1
years = list()
for chunk in range(first_january, self.num_chunks - chunks_per_year, chunks_per_year):
years.append(first_year)
first_year += 1
return years
def get_member_str(self, member):
return 'fc{0}'.format(str(member).zfill(self.member_digits))
class Variable(object):
def __init__(self, line):
self.short_name = line[1]
self.standard_name = line[2]
self.long_name = line[3]
self.domain = line[4]
self.basin = Basins.parse(line[5])
@classmethod
def get_variable(cls, original_name):
try:
return Variable._dict_variables[original_name.lower()]
except AttributeError:
Variable._dict_variables = dict()
with open(os.path.join(os.path.dirname(os.path.realpath(__file__)), 'cmor_table.csv'), 'rb') as csvfile:
reader = csv.reader(csvfile, dialect='excel')
for line in reader:
if line[0] == 'variable':
continue
for old_name in line[0].split(':'):
Variable._dict_variables[old_name] = var
Variable._dict_variables[var.short_name] = var
return Variable.get_variable(original_name)
except KeyError:
Log.error('Variable {0} is not defined'.format(original_name))
return None