def get_field(self):
gridxy = self.get_gridxy(with_xy_bounds=True)
coords_stacked = gridxy.get_value_stacked()
exact = self.get_exact_field_value(coords_stacked[1], coords_stacked[0])
exact = Variable(name='exact1', value=exact, dimensions=gridxy.dimensions)
dimension_map = {'x': {'variable': 'x', 'bounds': 'xbounds'}, 'y': {'variable': 'y', 'bounds': 'ybounds'}}
field1 = Field.from_variable_collection(gridxy.parent, dimension_map=dimension_map)
field1.add_variable(exact)
field1.set_name('exact1')
field1.append_to_tags(TagName.DATA_VARIABLES, 'exact1')
return field1
def get_field(self):
gridxy = self.get_gridxy(with_xy_bounds=True)
coords_stacked = gridxy.get_value_stacked()
exact = self.get_exact_field_value(coords_stacked[1], coords_stacked[0])
exact = Variable(name='exact1', value=exact, dimensions=gridxy.dimensions)
dimension_map = {'x': {'variable': 'x', 'bounds': 'xbounds'}, 'y': {'variable': 'y', 'bounds': 'ybounds'}}
field1 = Field.from_variable_collection(gridxy.parent, dimension_map=dimension_map)
field1.add_variable(exact)
field1.set_name('exact1')
field1.append_to_tags(TagName.DATA_VARIABLES, 'exact1')
return field1
def get_field(self, *args, **kwargs):
vc = kwargs.pop('vc', None)
format_time = kwargs.pop(KeywordArgument.FORMAT_TIME, True)
if KeywordArgument.GRID_ABSTRACTION in kwargs:
grid_abstraction = kwargs.pop(KeywordArgument.GRID_ABSTRACTION)
else:
grid_abstraction = constants.UNINITIALIZED
if vc is None:
# Get the raw variable collection from source.
new_kwargs = kwargs.copy()
new_kwargs['source_name'] = None
vc = self.get_variable_collection(*args, **new_kwargs)
# Get the appropriate metadata for the collection.
group_metadata = self.get_group_metadata(vc.group, self.metadata_source)
# Always pull the dimension map from the request dataset. This allows it to be overloaded.
dimension_map = self.get_group_metadata(vc.group, self.rd.dimension_map)
# Modify the coordinate system variable. If it is overloaded on the request dataset, then the variable
# collection needs to be updated to hold the variable and any alternative coordinate systems needs to be
# removed.
to_remove = None
to_add = None
crs = self.get_crs(group_metadata)
if self.rd._has_assigned_coordinate_system:
to_add = self.rd._crs
if crs is not None:
to_remove = crs.name
else:
if self.rd._crs is not None and self.rd._crs != 'auto':
to_add = self.rd._crs
if crs is not None:
to_remove = crs.name
elif crs is not None:
to_add = crs
if to_remove is not None:
vc.pop(to_remove, None)
if to_add is not None:
vc.add_variable(to_add, force=True)
# Overload the dimension map with the CRS.
if to_add is not None:
# dimension_map[DimensionMapKey.CRS][DimensionMapKey.VARIABLE] = to_add.name
dimension_map.set_crs(to_add.name)
# Remove the mask variable if present in the raw dimension map and the source dimension map is set to None.
if self.rd.dimension_map.get_spatial_mask() is None and self.dimension_map_raw.get_spatial_mask() is not None:
vc.pop(self.dimension_map_raw.get_spatial_mask())
# Convert the raw variable collection to a field.
kwargs['dimension_map'] = dimension_map
kwargs[KeywordArgument.FORMAT_TIME] = format_time
if grid_abstraction != constants.UNINITIALIZED:
kwargs[KeywordArgument.GRID_ABSTRACTION] = grid_abstraction
field = Field.from_variable_collection(vc, *args, **kwargs)
# If this is a source grid for regridding, ensure the flag is updated.
field.regrid_source = self.rd.regrid_source
# Update the assigned coordinate system flag.
field._has_assigned_coordinate_system = self.rd._has_assigned_coordinate_system
# Apply any requested subsets.
if self.rd.time_range is not None:
field = field.time.get_between(*self.rd.time_range).parent
if self.rd.time_region is not None:
field = field.time.get_time_region(self.rd.time_region).parent
if self.rd.time_subset_func is not None:
field = field.time.get_subset_by_function(self.rd.time_subset_func).parent
if self.rd.level_range is not None:
field = field.level.get_between(*self.rd.level_range).parent
# These variables have all the dimensions needed for a data classification. Use overloaded values from the
# request dataset if they are provided.
try:
data_variable_names = list(get_variable_names(self.rd.rename_variable))
except NoDataVariablesFound:
# It is okay to have no data variables in a field.
data_variable_names = []
pass
for dvn in data_variable_names:
field.append_to_tags(TagName.DATA_VARIABLES, dvn, create=True)
# Load child fields.
for child in list(field.children.values()):
kwargs['vc'] = child
field.children[child.name] = self.get_field(*args, **kwargs)
return field
def create_field(self, *args, **kwargs):
"""
Create a field object. In general, this should not be overloaded by subclasses.
:keyword bool format_time: ``(=True)`` If ``False``, do not convert numeric times to Python date objects.
:keyword str grid_abstraction: ``(='auto')`` If provided, use this grid abstraction.
:keyword raw_field: ``(=None)`` If provided, modify this field instead.
:type raw_field: None | :class:`~ocgis.Field`
:param kwargs: Additional keyword arguments to :meth:`~ocgis.driver.base.AbstractDriver.create_raw_field`.
:return: :class:`ocgis.Field`
"""
kwargs = kwargs.copy()
raw_field = kwargs.pop('raw_field', None)
format_time = kwargs.pop(KeywordArgument.FORMAT_TIME, True)
grid_abstraction = kwargs.pop(KeywordArgument.GRID_ABSTRACTION,
self.rd.grid_abstraction)
grid_is_isomorphic = kwargs.pop('grid_is_isomorphic',
self.rd.grid_is_isomorphic)
if raw_field is None:
# Get the raw variable collection from source.
new_kwargs = kwargs.copy()
new_kwargs['source_name'] = None
raw_field = self.create_raw_field(*args, **new_kwargs)
# Get the appropriate metadata for the collection.
group_metadata = self.get_group_metadata(raw_field.group,
self.metadata_source)
# Always pull the dimension map from the request dataset. This allows it to be overloaded.
dimension_map = self.get_group_metadata(raw_field.group,
self.rd.dimension_map)
# Modify the coordinate system variable. If it is overloaded on the request dataset, then the variable
# collection needs to be updated to hold the variable and any alternative coordinate systems needs to be
# removed.
to_remove = None
to_add = None
crs = self.get_crs(group_metadata)
if self.rd._has_assigned_coordinate_system:
to_add = self.rd._crs
if crs is not None:
to_remove = crs.name
else:
if self.rd._crs is not None and self.rd._crs != 'auto':
to_add = self.rd._crs
if crs is not None:
to_remove = crs.name
elif crs is not None:
to_add = crs
if to_remove is not None:
raw_field.pop(to_remove, None)
if to_add is not None:
raw_field.add_variable(to_add, force=True)
# Overload the dimension map with the CRS.
if to_add is not None:
# dimension_map[DimensionMapKey.CRS][DimensionMapKey.VARIABLE] = to_add.name
dimension_map.set_crs(to_add.name)
# Remove the mask variable if present in the raw dimension map and the source dimension map is set to None.
if self.rd.dimension_map.get_spatial_mask(
) is None and self.dimension_map_raw.get_spatial_mask() is not None:
raw_field.pop(self.dimension_map_raw.get_spatial_mask())
# Convert the raw variable collection to a field.
# TODO: Identify a way to remove this code block; field should be appropriately initialized; format_time and grid_abstraction are part of a dimension map.
kwargs[KeywordArgument.DIMENSION_MAP] = dimension_map
kwargs[KeywordArgument.FORMAT_TIME] = format_time
if grid_abstraction != 'auto':
kwargs[KeywordArgument.GRID_ABSTRACTION] = grid_abstraction
if grid_is_isomorphic != 'auto':
kwargs['grid_is_isomorphic'] = grid_is_isomorphic
field = Field.from_variable_collection(raw_field, *args, **kwargs)
# If this is a source grid for regridding, ensure the flag is updated.
field.regrid_source = self.rd.regrid_source
# Update the assigned coordinate system flag.
field._has_assigned_coordinate_system = self.rd._has_assigned_coordinate_system
# Apply any requested subsets.
if self.rd.time_range is not None:
field = field.time.get_between(*self.rd.time_range).parent
if self.rd.time_region is not None:
field = field.time.get_time_region(self.rd.time_region).parent
if self.rd.time_subset_func is not None:
field = field.time.get_subset_by_function(
self.rd.time_subset_func).parent
if self.rd.level_range is not None:
field = field.level.get_between(*self.rd.level_range).parent
# These variables have all the dimensions needed for a data classification. Use overloaded values from the
# request dataset if they are provided.
try:
data_variable_names = list(
get_variable_names(self.rd.rename_variable))
except NoDataVariablesFound:
# It is okay to have no data variables in a field.
data_variable_names = []
pass
for dvn in data_variable_names:
field.append_to_tags(TagName.DATA_VARIABLES, dvn, create=True)
# Load child fields.
for child in list(field.children.values()):
kwargs['raw_field'] = child
field.children[child.name] = self.create_field(*args, **kwargs)
return field
def create_field(self, *args, **kwargs):
"""
Create a field object. In general, this should not be overloaded by subclasses.
:keyword bool format_time: ``(=True)`` If ``False``, do not convert numeric times to Python date objects.
:keyword str grid_abstraction: ``(='auto')`` If provided, use this grid abstraction.
:keyword raw_field: ``(=None)`` If provided, modify this field instead.
:type raw_field: None | :class:`~ocgis.Field`
:param kwargs: Additional keyword arguments to :meth:`~ocgis.driver.base.AbstractDriver.create_raw_field`.
:return: :class:`ocgis.Field`
"""
kwargs = kwargs.copy()
raw_field = kwargs.pop('raw_field', None)
format_time = kwargs.pop(KeywordArgument.FORMAT_TIME, True)
grid_abstraction = kwargs.pop(KeywordArgument.GRID_ABSTRACTION, self.rd.grid_abstraction)
grid_is_isomorphic = kwargs.pop('grid_is_isomorphic', self.rd.grid_is_isomorphic)
if raw_field is None:
# Get the raw variable collection from source.
new_kwargs = kwargs.copy()
new_kwargs['source_name'] = None
raw_field = self.create_raw_field(*args, **new_kwargs)
# Get the appropriate metadata for the collection.
group_metadata = self.get_group_metadata(raw_field.group, self.metadata_source)
# Always pull the dimension map from the request dataset. This allows it to be overloaded.
dimension_map = self.get_group_metadata(raw_field.group, self.rd.dimension_map)
# Modify the coordinate system variable. If it is overloaded on the request dataset, then the variable
# collection needs to be updated to hold the variable and any alternative coordinate systems needs to be
# removed.
to_remove = None
to_add = None
crs = self.get_crs(group_metadata)
if self.rd._has_assigned_coordinate_system:
to_add = self.rd._crs
if crs is not None:
to_remove = crs.name
else:
if self.rd._crs is not None and self.rd._crs != 'auto':
to_add = self.rd._crs
if crs is not None:
to_remove = crs.name
elif crs is not None:
to_add = crs
if to_remove is not None:
raw_field.pop(to_remove, None)
if to_add is not None:
raw_field.add_variable(to_add, force=True)
# Overload the dimension map with the CRS.
if to_add is not None:
# dimension_map[DimensionMapKey.CRS][DimensionMapKey.VARIABLE] = to_add.name
dimension_map.set_crs(to_add.name)
# Remove the mask variable if present in the raw dimension map and the source dimension map is set to None.
if self.rd.dimension_map.get_spatial_mask() is None and self.dimension_map_raw.get_spatial_mask() is not None:
raw_field.pop(self.dimension_map_raw.get_spatial_mask())
# Convert the raw variable collection to a field.
# TODO: Identify a way to remove this code block; field should be appropriately initialized; format_time and grid_abstraction are part of a dimension map.
kwargs[KeywordArgument.DIMENSION_MAP] = dimension_map
kwargs[KeywordArgument.FORMAT_TIME] = format_time
if grid_abstraction != 'auto':
kwargs[KeywordArgument.GRID_ABSTRACTION] = grid_abstraction
if grid_is_isomorphic != 'auto':
kwargs['grid_is_isomorphic'] = grid_is_isomorphic
field = Field.from_variable_collection(raw_field, *args, **kwargs)
# If this is a source grid for regridding, ensure the flag is updated.
field.regrid_source = self.rd.regrid_source
# Update the assigned coordinate system flag.
field._has_assigned_coordinate_system = self.rd._has_assigned_coordinate_system
# Apply any requested subsets.
if self.rd.time_range is not None:
field = field.time.get_between(*self.rd.time_range).parent
if self.rd.time_region is not None:
field = field.time.get_time_region(self.rd.time_region).parent
if self.rd.time_subset_func is not None:
field = field.time.get_subset_by_function(self.rd.time_subset_func).parent
if self.rd.level_range is not None:
field = field.level.get_between(*self.rd.level_range).parent
# These variables have all the dimensions needed for a data classification. Use overloaded values from the
# request dataset if they are provided.
try:
data_variable_names = list(get_variable_names(self.rd.rename_variable))
except NoDataVariablesFound:
# It is okay to have no data variables in a field.
data_variable_names = []
pass
for dvn in data_variable_names:
field.append_to_tags(TagName.DATA_VARIABLES, dvn, create=True)
# Load child fields.
for child in list(field.children.values()):
kwargs['raw_field'] = child
field.children[child.name] = self.create_field(*args, **kwargs)
return field
