def __init__(self, filename, title='', qual=''):
'''
"Opens" the given NetCDF dataset file in Ferret using the Ferret "USE" command.
Creates a FerVar for each data variable in this data file and
assigns it as an attribute of this class using the variable name.
filename (string): name of the dataset filename or http address
title (string): title for the dataset for plots and listing;
if not given, the Ferret name for the dataset will be used
qual (string): Ferret qualifiers to be used with the "USE" command
'''
self._filename = ''
self._dsetname = ''
self._fervars = {}
self._fervarnames = set()
if not filename:
if qual == _anonymous_dataset_qualifier:
# initialize an new anonymous dataset that will either be
# pyferret.anondset or will be modified by a subclass (FerAggDSet)
return
else:
raise ValueError(
'pyferret.anondset should be used for the anonymous dataset'
)
# tell Ferret to open/use this dataset
cmdstr = 'USE'
if title:
cmdstr += '/TITLE="' + str(title) + '"'
if qual:
cmdstr += str(qual)
cmdstr += ' "' + str(filename) + '"'
(errval, errmsg) = pyferret.run(cmdstr)
if errval != pyferret.FERR_OK:
raise ValueError(errmsg)
# record the filename and Ferret dataset name
self._filename = filename
# need to use the filename as given as the dataset name to avoid possible abiguity
self._dsetname = filename
# create a FerVar for each variable in this dataset
namesdict = pyferret.getstrdata('..varnames')
for varname in namesdict['data'].flatten():
if sys.version_info[0] > 2:
# For Python3.x, namesdict['data'] is a NumPy array of bytes; convert to unicode
varname = str(varname, 'UTF-8')
# create a FerVar representing this existing Ferret file variable
filevar = pyferret.FerVar()
filevar._markasknownvar(varname, self._dsetname, True)
# assign this FerVar - uppercase the variable name keys to make case-insensitive
self._fervars[varname.upper()] = filevar
# keep a original-case version of the name
self._fervarnames.add(varname)
def diagform(self):
'''
Returns an anonymous FerVar that is the transformation of this FerFMRCVar
to a "diagonal" form, where the T (time) axis is the date forecasted and
the F (forecast) axis is the date the forecast was made.
'''
if (not self._varname) or (not self._dsetname):
raise ValueError('Invalid FerFMRCVar object')
# TF_TIMES is an automatically generated variable for FMRC datasets in Ferret
# TF_CAL_T is an automatically generated axis for FMRC datasets in Ferret
diagdefn = '%s[gt(TF_TIMES)=TF_CAL_T]' % self._varname
title = self._title + ' (diag form)'
diagvar = pyferret.FerVar(defn=diagdefn, title=title)
diagvar._requires.add(self._varname.upper())
diagvar._requires.add("TF_TIMES")
return diagvar
def leadform(self):
'''
Returns an anonymous FerVar that is the transformation of this FerFMRCVar
to the "lead" form, where the T (time) axis is the date forecasted and
the F (forecast) axis is the lead time for the date forecasted (forecasted
time minus time that the forecast was made).
'''
if (not self._varname) or (not self._dsetname):
raise ValueError('Invalid FerFMRCVar object')
# TF_TIMES is an automatically generated variable for FMRC datasets in Ferret
# TF_CAL_T is an automatically generated axis for FMRC datasets in Ferret
# TF_LAG_F is an automatically generated axis for FMRC datasets in Ferret
leaddefn = '%s[gt(TF_TIMES)=TF_CAL_T,gf(TF_TIMES)=TF_LAG_F]' % self._varname
title = self._title + ' (lead form)'
leadvar = pyferret.FerVar(defn=leaddefn, title=title)
leadvar._requires.add(self._varname.upper())
leadvar._requires.add("TF_TIMES")
return leadvar
def __init__(self,
name,
dsets,
along='T',
title='',
warn=True,
hide=False):
'''
Aggregates the given list of datasets along the given axis using the
Ferret "DEFINE DATA /AGGREGATE" command. Creates a FerVar for each data
variable in common among these datasets, and assigns it as an attribute
of this class instance using the variable name.
name (string): Ferret name for this aggregated dataset
dsets (sequence of strings and/or FerDSets): datasets to aggregate.
A string will be interpreted as a filename for creating a FerDSet.
along ('T', 'E', 'F'): axis along which to aggregate the datasets
title (string): title for the dataset for plots and listing;
if not given, the Ferret name for the dataset will be used
warn (bool): issue warning messages about variables not in common among
all member datasets (either not present or not using the same grid)
hide (bool): hide the member datasets in standard Ferret listings
such as with pyferret.showdata()
'''
# Create an empty dataset with the given Ferret name
super(FerAggDSet, self).__init__('', qual=_anonymous_dataset_qualifier)
if not isinstance(name, str):
raise ValueError(
'Ferret name for the aggregate dataset must be astring')
aggname = name.strip()
if not aggname:
raise ValueError('Ferret name for the aggregate dataset is blank')
self._filename = aggname
self._dsetname = aggname
# Need to keep the given order of component datasets
self._compdsetnames = []
# But still use a dictionary with uppercase names for keys
self._compdsets = {}
# Create the DEFINE DATA /AGGREGATE Ferret command, creating
# and saving component FerDSets as needed
if along not in ('T', 'E', 'F'):
raise ValueError("along must be one of 'T', 'E', or 'F'")
self._along = along
self._comphidden = bool(hide)
cmdstr = 'DEFINE DATA/AGGREGATE/' + self._along
if title:
cmdstr += '/TITLE="' + str(title) + '"'
if not warn:
cmdstr += '/QUIET'
if self._comphidden:
cmdstr += '/HIDE'
cmdstr += ' ' + aggname + ' = '
firstone = True
if not (isinstance(dsets, tuple) or isinstance(dsets, list)):
raise ValueError(
'dsets must be a tuple or list of strings and/or FerDSets')
for myitem in dsets:
if isinstance(myitem, str):
mydset = pyferret.FerDSet(myitem)
elif isinstance(myitem, pyferret.FerDSet):
mydset = myitem
else:
raise ValueError(
'dsets must be a tuple or list of strings and/or FerDSets')
if mydset._dsetname.upper() in self._compdsets:
raise ValueError('duplicate dataset name ' + mydset._dsetname)
if not firstone:
cmdstr += ', '
else:
firstone = False
cmdstr += mydset._dsetname
self._compdsetnames.append(mydset._dsetname)
self._compdsets[mydset._dsetname.upper()] = mydset
(errval, errmsg) = pyferret.run(cmdstr)
if errval != pyferret.FERR_OK:
raise ValueError(errmsg)
# create a FerVar for each variable in this dataset
namesdict = pyferret.getstrdata('..varnames')
for varname in namesdict['data'].flatten():
# create a FerVar representing this existing Ferret aggregated file variable
filevar = pyferret.FerVar()
filevar._markasknownvar(varname, self._dsetname, True)
# assign this FerVar - uppercase the variable name keys to make case-insensitive
self._fervars[varname.upper()] = filevar
# keep a original-case version of the name
self._fervarnames.add(varname)
def __init__(self, name, dsets, along='T', title='', warn=True, hide=False):
'''
Aggregates the given list of datasets along the given axis using the
Ferret "DEFINE DATA /AGGREGATE" command. Creates a FerVar for each data
variable in common among these datasets, and assigns it as an attribute
of this class instance using the variable name.
name (string): Ferret name for this aggregated dataset
dsets (sequence of strings and/or FerDSets): datasets to aggregate.
A string will be interpreted as a filename for creating a FerDSet.
along ('T', 'E', 'F'): axis along which to aggregate the datasets
title (string): title for the dataset for plots and listing;
if not given, the Ferret name for the dataset will be used
warn (bool): issue warning messages about variables not in common among
all member datasets (either not present or not using the same grid)
hide (bool): hide the member datasets in standard Ferret listings
such as with pyferret.showdata()
'''
# Create an empty dataset with the given Ferret name
super(FerAggDSet, self).__init__('', qual=_anonymous_dataset_qualifier)
if not isinstance(name, str):
raise ValueError('Ferret name for the aggregate dataset must be astring')
aggname = name.strip()
if not aggname:
raise ValueError('Ferret name for the aggregate dataset is blank')
self._filename = aggname
self._dsetname = aggname
# Need to keep the given order of component datasets
self._compdsetnames = [ ]
# But still use a dictionary with uppercase names for keys
self._compdsets = { }
if along not in ('T', 'E', 'F'):
raise ValueError("along must be one of 'T', 'E', or 'F'")
self._along = along
self._comphidden = bool(hide)
# Create a Ferret string variable containing all the dataset names to be aggregated
if not ( isinstance(dsets, tuple) or isinstance(dsets, list) ):
raise ValueError('dsets must be a tuple or list of strings and/or FerDSets')
filesfile = tempfile.NamedTemporaryFile(mode='w', delete=False,
prefix=aggname + '_', suffix='_agg.txt')
filesfilename = filesfile.name
deletefilesfile = True
try:
for myitem in dsets:
if isinstance(myitem, str):
mydset = pyferret.FerDSet(myitem)
elif isinstance(myitem, pyferret.FerDSet):
mydset = myitem
else:
raise ValueError('dsets must be a tuple or list of strings and/or FerDSets')
if mydset._dsetname.upper() in self._compdsets:
raise ValueError('duplicate dataset name ' + mydset._dsetname)
print(mydset._dsetname, file=filesfile)
self._compdsetnames.append(mydset._dsetname)
self._compdsets[mydset._dsetname.upper()] = mydset
deletefilesfile = False
finally:
filesfile.close()
if deletefilesfile:
os.unlink(filesfilename)
filesvarname = aggname + "_datafile_names"
cmdstr = 'LET ' + filesvarname + ' = SPAWN("cat \'' + filesfilename + '\'")'
(errval, errmsg) = pyferret.run(cmdstr)
if errval != pyferret.FERR_OK:
os.unlink(filesfilename)
raise ValueError(errmsg)
# filesfile not read (SPAWN command executed) until filesvarname is needed
# Create the DEFINE DATA /AGGREGATE Ferret command, creating
# and saving component FerDSets as needed
cmdstr = 'DEFINE DATA/AGGREGATE/' + self._along
if title:
cmdstr += '/TITLE="' + str(title) + '"'
if not warn:
cmdstr += '/QUIET'
if self._comphidden:
cmdstr += '/HIDE'
cmdstr += ' ' + aggname + ' = ' + filesvarname
(errval, errmsg) = pyferret.run(cmdstr)
# filesfile now read so can delete it
os.unlink(filesfilename)
if errval != pyferret.FERR_OK:
raise ValueError(errmsg)
# create a FerVar for each variable in this dataset
namesdict = pyferret.getstrdata('..varnames')
for varname in namesdict['data'].flatten():
if sys.version_info[0] > 2:
# For Python3.x, namesdict['data'] is a NumPy array of bytes; convert to unicode
varname = str(varname, 'UTF-8')
# create a FerVar representing this existing Ferret aggregated file variable
filevar = pyferret.FerVar()
filevar._markasknownvar(varname, self._dsetname, True)
# assign this FerVar - uppercase the variable name keys to make case-insensitive
self._fervars[varname.upper()] = filevar
# keep a original-case version of the name
self._fervarnames.add(varname)