yt.frontends.ytdata.fields module

YTData-specific fields

class yt.frontends.ytdata.fields.YTDataContainerFieldInfo(ds, field_list)[source]

Bases: yt.fields.field_info_container.FieldInfoContainer

add_fake_grid_fields()[source]

Add cell volume and mass fields that use the dx, dy, and dz fields that come with the dataset instead of the index fields which correspond to the oct tree. We need to do this for now since we’re treating the grid data like particles until we implement exporting AMR hierarchies.

add_field(name, sampling_type, function=None, **kwargs)

Add a new field, along with supplemental metadata, to the list of available fields. This respects a number of arguments, all of which are passed on to the constructor for DerivedField.

Parameters:
  • name (str) – is the name of the field.
  • function (callable) – A function handle that defines the field. Should accept arguments (field, data)
  • units (str) – A plain text string encoding the unit. Powers must be in python syntax (** instead of ^). If set to “auto” the units will be inferred from the return value of the field function.
  • take_log (bool) – Describes whether the field should be logged
  • validators (list) – A list of FieldValidator objects
  • particle_type (bool) – Is this a particle (1D) field?
  • vector_field (bool) – Describes the dimensionality of the field. Currently unused.
  • display_name (str) – A name used in the plots
add_output_field(name, sampling_type, **kwargs)
alias(alias_name, original_name, units=None)
check_derived_fields(fields_to_check=None)
clear() → None. Remove all items from D.
copy() → a shallow copy of D
create_with_fallback(fallback, name='')
extra_union_fields = ()
fallback = None
find_dependencies(loaded)
fromkeys()

Returns a new dict with keys from iterable and values equal to value.

get(k[, d]) → D[k] if k in D, else d. d defaults to None.
has_key(key)
items() → a set-like object providing a view on D's items
keys()
known_other_fields = ()
known_particle_fields = ()
load_all_plugins(ftype='gas')
load_plugin(plugin_name, ftype='gas', skip_check=False)
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised

popitem() → (k, v), remove and return some (key, value) pair as a

2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
setup_extra_union_fields(ptype='all')
setup_fluid_aliases(ftype='gas')
setup_fluid_fields()
setup_fluid_index_fields()
setup_particle_fields(ptype, ftype='gas', num_neighbors=64)
setup_smoothed_fields(ptype, num_neighbors=64, ftype='gas')
update([E, ]**F) → None. Update D from dict/iterable E and F.

If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values() → an object providing a view on D's values
class yt.frontends.ytdata.fields.YTGridFieldInfo(ds, field_list, slice_info=None)[source]

Bases: yt.fields.field_info_container.FieldInfoContainer

add_field(name, sampling_type, function=None, **kwargs)

Add a new field, along with supplemental metadata, to the list of available fields. This respects a number of arguments, all of which are passed on to the constructor for DerivedField.

Parameters:
  • name (str) – is the name of the field.
  • function (callable) – A function handle that defines the field. Should accept arguments (field, data)
  • units (str) – A plain text string encoding the unit. Powers must be in python syntax (** instead of ^). If set to “auto” the units will be inferred from the return value of the field function.
  • take_log (bool) – Describes whether the field should be logged
  • validators (list) – A list of FieldValidator objects
  • particle_type (bool) – Is this a particle (1D) field?
  • vector_field (bool) – Describes the dimensionality of the field. Currently unused.
  • display_name (str) – A name used in the plots
add_output_field(name, sampling_type, **kwargs)
alias(alias_name, original_name, units=None)
check_derived_fields(fields_to_check=None)
clear() → None. Remove all items from D.
copy() → a shallow copy of D
create_with_fallback(fallback, name='')
extra_union_fields = ()
fallback = None
find_dependencies(loaded)
fromkeys()

Returns a new dict with keys from iterable and values equal to value.

get(k[, d]) → D[k] if k in D, else d. d defaults to None.
has_key(key)
items() → a set-like object providing a view on D's items
keys()
known_other_fields = ()
known_particle_fields = ()
load_all_plugins(ftype='gas')
load_plugin(plugin_name, ftype='gas', skip_check=False)
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised

popitem() → (k, v), remove and return some (key, value) pair as a

2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
setup_extra_union_fields(ptype='all')
setup_fluid_aliases(ftype='gas')
setup_fluid_fields()
setup_fluid_index_fields()
setup_particle_fields(ptype, ftype='gas', num_neighbors=64)
setup_smoothed_fields(ptype, num_neighbors=64, ftype='gas')
update([E, ]**F) → None. Update D from dict/iterable E and F.

If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values() → an object providing a view on D's values