def _is_valid(self, *args, **kwargs):
warn_netcdf(args[0])
try:
from netCDF4 import Dataset
filename = args[0]
with Dataset(filename) as f:
f.variables['connect1']
return True
except:
pass
def _is_valid(self, *args, **kwargs):
warn_netcdf(args[0])
try:
from netCDF4 import Dataset
filename = args[0]
# We use keepweakref here to avoid holding onto the file handle
# which can interfere with other is_valid calls.
with Dataset(filename, keepweakref=True) as f:
f.variables['connect1']
return True
except Exception: pass
def _is_valid(cls, filename, *args, **kwargs):
# This accepts a filename or a set of arguments and returns True or
# False depending on if the file is of the type requested.
warn_netcdf(filename)
try:
nc4_file = NetCDF4FileHandler(filename)
with nc4_file.open_ds(keepweakref=True) as _handle:
is_cm1_lofs = hasattr(_handle, "cm1_lofs_version")
is_cm1 = hasattr(_handle,
"cm1 version") # not a typo, it is a space...
# ensure coordinates of each variable array exists in the dataset
coords = _handle.dimensions # get the dataset wide coordinates
failed_vars = [] # list of failed variables
for var in _handle.variables: # iterate over the variables
vcoords = _handle[
var].dimensions # get the dims for the variable
ncoords = len(vcoords) # number of coordinates in variable
# number of coordinates that pass for a variable
coordspassed = sum(vc in coords for vc in vcoords)
if coordspassed != ncoords:
failed_vars.append(var)
if failed_vars:
mylog.warning(
"Trying to load a cm1_lofs netcdf file but the "
"coordinates of the following fields do not match the "
"coordinates of the dataset: %s",
failed_vars,
)
return False
if not is_cm1_lofs:
if is_cm1:
mylog.warning(
"It looks like you are trying to load a cm1 netcdf file, "
"but at present yt only supports cm1_lofs output. Until"
" support is added, you can likely use"
" yt.load_uniform_grid() to load your cm1 file manually."
)
return False
except (OSError, AttributeError, ImportError):
return False
return True
def _is_valid(cls, filename, *args, **kwargs):
# This accepts a filename or a set of arguments and returns True or
# False depending on if the file is of the type requested.
warn_netcdf(filename)
is_cfrad = False
try:
# note that we use the NetCDF4FileHandler here to avoid some
# issues with xarray opening datasets it cannot handle. Once
# a dataset is as identified as a CFRadialDataset, xarray is used
# for opening. See https://github.com/yt-project/yt/issues/3987
nc4_file = NetCDF4FileHandler(filename)
with nc4_file.open_ds(keepweakref=True) as ds:
con = "Conventions" # the attribute to check for file conventions
cons = "" # the value of the Conventions attribute
for c in [con, con.lower()]:
if hasattr(ds, c):
cons += getattr(ds, c)
is_cfrad = "CF/Radial" in cons
except (OSError, AttributeError, ImportError):
return False
return is_cfrad
