def run_task(self, inputs, context):
'''
Run the TPW Daily binary on a single context
'''
LOG.debug("Running run_task()...")
for key in context.keys():
LOG.debug("run_task() context['{}'] = {}".format(
key, context[key]))
rc = 0
# Link the inputs into the working directory
inputs = symlink_inputs_to_working_dir(inputs)
# Create the TPW daily file for the current day.
rc, tpw_daily_noshift_file = self.create_tpw_daily(inputs,
context,
shifted=False)
rc, tpw_daily_shift_file = self.create_tpw_daily(inputs,
context,
shifted=True)
return {
'noshift': nc_compress(tpw_daily_noshift_file),
'shift': nc_compress(tpw_daily_shift_file)
}
def run_task(self, inputs, context):
LOG.debug("Running run_task()...")
for key in context.keys():
LOG.debug("run_task() context['{}'] = {}".format(
key, context[key]))
rc = 0
# Extract a binary array from a CFSR reanalysis GRIB2 file on a
# global equal angle grid at 0.5 degree resolution. CFSR files
rc, cfsr_files = self.extract_bin_from_cfsr(inputs, context)
# Create the CFSR statistics for the current day.
rc, output_stats_file = self.create_cfsr_statistics(
inputs, context, cfsr_files)
if rc != 0:
LOG.warn('Something went wrong, rc={}...'.format(rc))
return {}
LOG.debug('create_cfsr_statistics() generated {}...'.format(
output_stats_file))
# Create the CFSR means for the current day
rc, output_means_file = self.create_cfsr_means(inputs, context,
output_stats_file)
if rc != 0:
return rc
LOG.debug(
'create_cfsr_means() generated {}...'.format(output_means_file))
LOG.debug('python return value = {}'.format(rc))
extra_attrs = {
'begin_time':
context['granule'],
'end_time':
context['granule'] + timedelta(days=1) - timedelta(seconds=1)
}
LOG.debug('extra_attrs = {}'.format(extra_attrs))
return {
'stats': {
'file': nc_compress(output_stats_file),
'extra_attrs': extra_attrs
},
'means': {
'file': nc_compress(output_means_file),
'extra_attrs': extra_attrs
}
}
def run_task(self, inputs, context):
'''
Run the CTP Orbital binary on a single context
'''
LOG.debug("Running run_task()...")
for key in context.keys():
LOG.debug("run_task() context['{}'] = {}".format(
key, context[key]))
rc = 0
# Extract a binary array from a CFSR reanalysis GRIB2 file on a
# global equal angle grid at 0.5 degree resolution. CFSR files
rc, cfsr_file = self.extract_bin_from_cfsr(inputs, context)
# Link the inputs into the working directory
inputs.pop('CFSR')
inputs = symlink_inputs_to_working_dir(inputs)
inputs['CFSR'] = cfsr_file
# Create the CTP Orbital for the current granule.
rc, ctp_orbital_file = self.create_ctp_orbital(inputs, context)
return {'out': nc_compress(ctp_orbital_file)}
def run_task(self, inputs, context):
'''
Run the TPW Orbital binary on a single context
'''
LOG.debug("Running run_task()...")
for key in context.keys():
LOG.debug("run_task() context['{}'] = {}".format(
key, context[key]))
rc = 0
# Extract a binary array from a CFSR reanalysis GRIB2 file on a
# global equal angle grid at 0.5 degree resolution. CFSR files
rc, cfsr_file = self.extract_bin_from_cfsr(inputs, context)
# Link the inputs into the working directory
inputs.pop('CFSR')
inputs = symlink_inputs_to_working_dir(inputs)
inputs['CFSR'] = cfsr_file
# Link the shifted and nonshifted coefficient files into the current directory
self.link_coeffs(context)
# Create the TPW Orbital for the current granule.
rc, tpw_orbital_noshift_file = self.create_tpw_orbital(inputs,
context,
shifted=False)
rc, tpw_orbital_shift_file = self.create_tpw_orbital(inputs,
context,
shifted=True)
interval = self.hirs_to_time_interval(inputs['HIR1B'])
extra_attrs = {'begin_time': interval.left, 'end_time': interval.right}
return {
'shift': {
'file': nc_compress(tpw_orbital_shift_file),
'extra_attrs': extra_attrs
},
'noshift': {
'file': nc_compress(tpw_orbital_noshift_file),
'extra_attrs': extra_attrs
}
}
def run_task(self, inputs, context):
for key in context.keys():
LOG.debug("run_task() context['{}'] = {}".format(key, context[key]))
rc = 0
# Create the CFSR statistics for the current month.
rc, output_stats_file = self.create_monthly_statistics(inputs, context)
if rc != 0:
return {}
LOG.info('create_monthly_statistics() generated {}...'.format(output_stats_file))
# Create the CFSR zonal means for the current month
rc, output_zonal_means_file = self.create_monthly_zonal_means(output_stats_file, context)
if rc != 0:
return rc
LOG.info('create_zonal_means() generated {}...'.format(output_zonal_means_file))
return {'stats': nc_compress(output_stats_file), 'zonal_means': nc_compress(output_zonal_means_file)}
def run_task(self, inputs, context):
'''
Run the CTP Daily binary on a single context
'''
LOG.debug("Running run_task()...")
for key in context.keys():
LOG.debug("run_task() context['{}'] = {}".format(key, context[key]))
rc = 0
# Link the inputs into the working directory
inputs = symlink_inputs_to_working_dir(inputs)
# Create the CTP daily file for the current day.
rc, ctp_daily_file = self.create_ctp_daily(inputs, context)
return {'out': nc_compress(ctp_daily_file)}
def run_task(self, inputs, context):
LOG.debug("Running run_task()...")
for key in context.keys():
LOG.debug("run_task() context['{}'] = {}".format(
key, context[key]))
granule = context['granule']
satellite = context['satellite']
hirs2nc_delivery_id = context['hirs2nc_delivery_id']
hirs_version = self.satellite_version(context['satellite'],
context['granule'])
# Get the location of the binary package
delivery = delivered_software.lookup('hirs2nc',
delivery_id=hirs2nc_delivery_id)
dist_root = pjoin(delivery.path, 'dist')
envroot = pjoin(dist_root, 'env')
# Get the required environment variables
env = prepare_env([delivery])
LOG.debug(env)
# What is the path of the python interpreter
py_interp = "{}/bin/python".format(envroot)
LOG.debug("py_interp = '{}'".format(py_interp))
# Path of the hirs2nc binary
hirs2nc_bin = pjoin(envroot, 'bin', 'hirs2nc')
# Where are we running the package
work_dir = abspath(curdir)
LOG.debug("working dir = {}".format(work_dir))
input_file = inputs['HIR1B']
output_file = pjoin(work_dir,
basename('{}.nc'.format(inputs['HIR1B'])))
LOG.debug("Input file = {}".format(input_file))
LOG.debug("Output file = {}".format(output_file))
# What are our inputs?
for input in inputs.keys():
inputs_dir = dirname(inputs[input])
LOG.debug("inputs['{}'] = {}".format(input, inputs[input]))
LOG.debug("Inputs dir = {}".format(inputs_dir))
# Convert the flat HIRS file to NetCDF4
cmd = '{} {} {} {} {}'.format(py_interp, hirs2nc_bin, hirs_version,
input_file, output_file)
try:
LOG.debug("cmd = \\\n\t{}".format(cmd.replace(' ', ' \\\n\t')))
rc_hirs2nc = 0
runscript(cmd, requirements=[], env=env)
except CalledProcessError as err:
rc_hirs2nc = err.returncode
LOG.error("hirs2nc binary {} returned a value of {}".format(
hirs2nc_bin, rc_hirs2nc))
return rc_hirs2nc, []
# The staging routine assumes that the output file is located in the work directory
# "tmp******", and that the output path is to be prepended, so return the basename.
output = basename('{}.nc'.format(inputs['HIR1B']))
data_interval = context['data_interval']
extra_attrs = {
'begin_time': data_interval.left,
'end_time': data_interval.right
}
return {
'out': {
'file': nc_compress(output),
'extra_attrs': extra_attrs
}
}