def hemco_to_netCDF( folder, hemco_file_list=None, remake=False ):
"""
Conbine HEMCO diagnostic output files to a single NetCDF file.
Parameters
----------
remake (boolean): overwrite existing NetCDF file
"""
from bpch2netCDF import get_folder
folder = get_folder(folder)
output_file = os.path.join(folder, 'hemco.nc')
# If the hemco netCDF file already exists then quit unless remake=True
if not remake:
if os.path.exists(output_file):
logging.warning( output_file + ' already exists, not remaking')
return
logging.info("Combining hemco diagnostic files")
# By default look for any files that look like hemco diagnostic files:
# Look for all hemco netcdf files then remove the restart files.
if hemco_file_list==None:
hemco_files = glob.glob(folder + '/*HEMCO*.nc')
for filename in hemco_files:
if "restart" in filename:
hemco_files.remove(filename)
else:
file_list = []
for hemco_file in hemco_file_list:
full_path = os.path.join(folder, hemco_file)
if not os.path.exists(full_path):
logging.error(full_path + " could not be found")
raise IOError("{path} could not be found".format(path=full_path))
file_list.append(full_path)
hemco_files = file_list
if len(hemco_files)==0:
logging.warning("No hemco diagnostic files found in {_dir}"\
.format(_dir=folder))
else:
logging.debug( "The following hemco files were found:")
logging.debug( str(hemco_files) )
# Use iris cubes to combine the data into an output file
hemco_data = iris.load(hemco_files)
# Concatanate the times.
hemco_data = hemco_data.concatenate()
iris.save( hemco_data, output_file)
logging.info( str(hemco_data) )
logging.info("Hecmo file created at {file}".format(file=output_file))
return
def bpch_to_netCDF(folder='none', filename='ctm.nc',\
bpch_file_list=None, remake=False, verbose=True):
"""
Converts GEOS-Chem ctm.bpch output file(s) to NetCDF
"""
# Check if file already exists and warn about remaking
from bpch2netCDF import get_folder
folder = get_folder(folder)
output_file = os.path.join(folder, filename)
# If the netCDf file already exists dont overwrite it without remake=True.
if not remake:
if os.path.exists(output_file):
logging.warning(output_file + ' already exists. Not recreating.')
return
# By default look inside the folder for any files
if bpch_file_list == None:
bpch_files = glob.glob(folder + '/*.bpch*')
if len(bpch_files) == 0:
bpch_files = glob.glob(folder + '/*trac_avg*')
if len(bpch_files) == 0:
logging.error("No bpch files found in " + folder)
raise IOError(folder + " contains no bpch files.")
# Confirm the specified bpch files are there.
else:
file_list = []
for bpch_file in bpch_file_list:
full_path = folder + '/' + bpch_file
if not os.path.exists(full_path):
logging.error(full_path + " could not be found")
raise IOError("Full path could not be found")
file_list.append(full_path)
bpch_files = file_list
# Open the bpch files
logging.debug("The following bpch files were found:")
logging.debug(str(bpch_files))
if verbose:
print "Creating a netCDF file. This can take some time..."
bpch_data = datasets.load(bpch_files)
# Save the netCDF file
# iris.fileformats.netcdf.save(data, output_file)
datasets.save(bpch_data, output_file)
logging.info("A netCDF file has been created with the name {ctm}".format(
ctm=output_file))
return
def hemco_to_netCDF(folder, hemco_file_list, remake=False):
from bpch2netCDF import get_folder
folder = get_folder(folder)
output_file = os.path.join(folder, 'hemco.nc')
# If the hemco netCDF file already exists then quit unless remake=True
if not remake:
if os.path.exists(output_file):
logging.warning(output_file + ' already exists, not remaking')
return
logging.info("Combining hemco diagnostic files")
# By default look for any files that look like hemco diagnostic files:
# Look for all hemco netcdf files then remove the restart files.
if hemco_file_list == None:
hemco_files = glob.glob(folder + '/*HEMCO*.nc')
for filename in hemco_files:
if "restart" in filename:
hemco_files.remove(filename)
if len(hemco_files) == 0:
logging.warning("No hemco diagnostic files found in wd")
else:
logging.debug("The following hemco files were found:")
logging.debug(str(hemco_files))
# Use iris cubes to combine the data into an output file
hemco_data = iris.load(hemco_files)
# Concatanate the times.
hemco_data = hemco_data.concatenate()
iris.save(hemco_data, output_file)
logging.info(str(hemco_data))
logging.info("Hecmo file created at {file}".format(file=output_file))
return
def convert_to_netCDF(folder='none', filename='ctm.nc'):
from bpch2netCDF import get_folder
folder = get_folder(folder)
# Get ctm.bpch ( inc. if named *trac_avg* )
import glob
bpch_files = glob.glob(folder + '/*ctm.bpch*')
if len(bpch_files) == 0:
bpch_files = glob.glob(folder + '/*trac_avg*')
# Open the bpch files
try:
from pygchem import datasets
except:
import pygchem.datafields as datasets
data = datasets.load(bpch_files)
# Save the netCDF file
output_file = folder + '/' + filename
import iris
iris.fileformats.netcdf.save(data, output_file)
return
def bpch_to_netCDF(folder=None, filename='ctm.nc', bpch_file_list=None, \
remake=False, filetype="*ctm.bpch*", verbose=False, **kwargs):
"""
Converts GEOS-Chem ctm.bpch output file(s) to NetCDF
Parameters
----------
folder (str): working directory for data files
filename (str): name to give created NetCDF
bpch_file_list (list): list of files to convert
remake (boolean): overwrite existing NetCDF file
filetype (str): string with wildcards to match filenames
( e.g. *ctm.bpch*,*ts*bpch* )
verbose (boolean): print (minor) logging to screen
Returns
-------
(None) saves a NetCDF file to disk
"""
# Check if file already exists and warn about remaking
from bpch2netCDF import get_folder
folder = get_folder(folder)
output_file = os.path.join(folder, filename)
# If the netCDf file already exists dont overwrite it without remake=True.
if not remake:
if os.path.exists(output_file):
logging.warning(output_file + ' already exists. Not recreating.')
return
# Look for files if file list is not provided.
if isinstance( bpch_file_list, type(None) ):
logging.debug("Searching for the following bpch filetype: {filetype}"\
.format(filetype=filetype))
bpch_files = glob.glob( folder + '/' + filetype )
if len(bpch_files) == 0:
logging.error("No bpch files found in "+folder)
raise IOError(folder + " contains no bpch files.")
# use the specified files.
else:
file_list = []
for bpch_file in bpch_file_list:
full_path = folder + '/' + bpch_file
if not os.path.exists(full_path):
logging.error(full_path + " could not be found")
raise IOError("Full path could not be found")
file_list.append(full_path)
bpch_files = file_list
# Open the bpch files
logging.debug( "The following bpch files were found:")
logging.debug( str(bpch_files) )
if verbose:
print "Creating a netCDF file. This can take some time..."
bpch_data = datasets.load(bpch_files)
# Save the netCDF file
# iris.fileformats.netcdf.save(data, output_file)
datasets.save( bpch_data, output_file )
logging.info( "A netCDF file has been created with the name {ctm}".format(ctm=output_file))
return
