yt.frontends.open_pmd.fields module

openPMD-specific fields

class yt.frontends.open_pmd.fields.OpenPMDFieldInfo(ds, field_list)[source]

Bases: yt.fields.field_info_container.FieldInfoContainer

Specifies which fields from the dataset yt should know about.

self.known_other_fields and self.known_particle_fields must be populated. Entries for both of these lists must be tuples of the form

(“name”, (“units”, [“fields”, “to”, “alias”], “display_name”))

These fields will be represented and handled in yt in the way you define them here. The fields defined in both self.known_other_fields and self.known_particle_fields will only be added to a dataset (with units, aliases, etc), if they match any entry in the OpenPMDHierarchy‘s self.field_list.


Contrary to many other frontends, we dynamically obtain the known fields from the simulation output. The openPMD markup is extremely flexible - names, dimensions and the number of individual datasets can (and very likely will) vary.

openPMD states that names of records and their components are only allowed to contain the
characters a-Z, the numbers 0-9 and the underscore _ (equivalently, the regex w).

Since yt widely uses the underscore in field names, openPMD’s underscores (_) are replaced by hyphen (-).

Derived fields will automatically be set up, if names and units of your known on-disk (or manually derived) fields match the ones in [1].


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.

  • 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)
clear() → None. Remove all items from D.
copy() → a shallow copy of D
create_with_fallback(fallback, name='')
extra_union_fields = ()
fallback = None

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.
items() → a set-like object providing a view on D's items
known_other_fields = ()
known_particle_fields = ()
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

Defines which derived mesh fields to create.

If a field can not be calculated, it will simply be skipped.


Defines which derived particle fields to create.

This will be called for every entry in OpenPMDDataset`‘s self.particle_types. If a field can not be calculated, it will simply be skipped.

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
yt.frontends.open_pmd.fields.setup_absolute_positions(self, ptype)[source]
yt.frontends.open_pmd.fields.setup_kinetic_energy(self, ptype)[source]
yt.frontends.open_pmd.fields.setup_velocity(self, ptype)[source]