def _parse_parameter_file(self):
self._handle = NetCDF4FileHandler(self.parameter_filename)
with self._handle.open_ds() as ds:
self._read_glo_var()
self.dimensionality = ds.variables["coor_names"].shape[0]
self.parameters["info_records"] = self._load_info_records()
self.unique_identifier = self._get_unique_identifier()
self.num_steps = len(ds.variables["time_whole"])
self.current_time = self._get_current_time()
self.parameters["num_meshes"] = ds.variables["eb_status"].shape[0]
self.parameters["elem_names"] = self._get_elem_names()
self.parameters["nod_names"] = self._get_nod_names()
self.domain_left_edge, self.domain_right_edge = self._load_domain_edge()
self._periodicity = (False, False, False)
# These attributes don't really make sense for unstructured
# mesh data, but yt warns if they are not present, so we set
# them to dummy values here.
self.domain_dimensions = np.ones(3, "int32")
self.cosmological_simulation = 0
self.current_redshift = 0
self.omega_lambda = 0
self.omega_matter = 0
self.hubble_constant = 0
self.refine_by = 0
def __init__(self, ds):
self.filename = ds.index_filename
exodus_ii_handler = NetCDF4FileHandler(self.filename)
self.handler = exodus_ii_handler.dataset
super(IOHandlerExodusII, self).__init__(ds)
self.node_fields = ds._get_nod_names()
self.elem_fields = ds._get_elem_names()
def _get_fluid_types(self):
with NetCDF4FileHandler(self.parameter_filename).open_ds() as ds:
fluid_types = ()
i = 1
while True:
ftype = "connect%d" % i
if ftype in ds.variables:
fluid_types += (ftype,)
i += 1
else:
break
fluid_types += ("all",)
return fluid_types
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 __init__(
self,
filename,
dataset_type="cm1",
storage_filename=None,
units_override=None,
unit_system="mks",
):
self.fluid_types += ("cm1", )
self._handle = NetCDF4FileHandler(filename)
# refinement factor between a grid and its subgrid
self.refine_by = 1
super().__init__(
filename,
dataset_type,
units_override=units_override,
unit_system=unit_system,
)
self.storage_filename = storage_filename
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
def __init__(self, ds):
self.filename = ds.filename
self._handle = NetCDF4FileHandler(self.filename)
super().__init__(ds)
