qml.data.DatasetDict¶
-
class
DatasetDict
(value=<UnsetType.UNSET: 'UNSET'>, info=None, *, bind=None, parent_and_key=None)[source]¶ Bases:
Generic
[pennylane.data.base.typing_util.T
],pennylane.data.base.attribute.DatasetAttribute
[collections.abc.MutableMapping
,collections.abc.Mapping
[str
,pennylane.data.base.typing_util.T
],collections.abc.Mapping
[str
,pennylane.data.base.typing_util.T
]],collections.abc.MutableMapping
[str
,pennylane.data.base.typing_util.T
],pennylane.data.base.mapper.MapperMixin
Provides a dict-like collection for Dataset attribute types. Keys must be strings.
Attributes
Returns the HDF5 object that contains this attribute’s data.
Returns the
AttributeInfo
for this attribute.Maps type_ids to their DatasetAttribute classes.
Maps types to their default DatasetAttribute
-
bind
: HDF5Group¶ Returns the HDF5 object that contains this attribute’s data.
-
info
¶ Returns the
AttributeInfo
for this attribute.
-
registry
: collections.abc.Mapping[str, Type[DatasetAttribute]] = mappingproxy({'dataset': <class 'pennylane.data.base.dataset._DatasetAttributeType'>, 'array': <class 'pennylane.data.attributes.array.DatasetArray'>, 'dict': <class 'pennylane.data.attributes.dictionary.DatasetDict'>, 'json': <class 'pennylane.data.attributes.json.DatasetJSON'>, 'list': <class 'pennylane.data.attributes.list.DatasetList'>, 'molecule': <class 'pennylane.data.attributes.molecule.DatasetMolecule'>, 'none': <class 'pennylane.data.attributes.none.DatasetNone'>, 'operator': <class 'pennylane.data.attributes.operator.operator.DatasetOperator'>, 'scalar': <class 'pennylane.data.attributes.scalar.DatasetScalar'>, 'sparse_array': <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, 'string': <class 'pennylane.data.attributes.string.DatasetString'>, 'tuple': <class 'pennylane.data.attributes.tuple.DatasetTuple'>, 'pytree': <class 'pennylane.data.attributes.pytree.DatasetPyTree'>})¶ Maps type_ids to their DatasetAttribute classes.
-
type_consumer_registry
: collections.abc.Mapping[type, Type[DatasetAttribute]] = mappingproxy({<class 'pennylane.qchem.molecule.Molecule'>: <class 'pennylane.data.attributes.molecule.DatasetMolecule'>, <class 'NoneType'>: <class 'pennylane.data.attributes.none.DatasetNone'>, <class 'scipy.sparse._bsr.bsr_array'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._coo.coo_array'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._csc.csc_array'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._csr.csr_array'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._dia.dia_array'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._dok.dok_array'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._lil.lil_array'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._csc.csc_matrix'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._csr.csr_matrix'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._bsr.bsr_matrix'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._coo.coo_matrix'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._dia.dia_matrix'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._dok.dok_matrix'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'scipy.sparse._lil.lil_matrix'>: <class 'pennylane.data.attributes.sparse_array.DatasetSparseArray'>, <class 'str'>: <class 'pennylane.data.attributes.string.DatasetString'>, <class 'tuple'>: <class 'pennylane.data.attributes.tuple.DatasetTuple'>})¶ Maps types to their default DatasetAttribute
-
type_id
: ClassVar[str] = 'dict'¶
Methods
clear
()Returns an iterable of types for which this should be the default codec.
copy
()Returns a copy of this mapping as a builtin
dict
, with all elements copied.Deserializes the mapped value from
bind
, and also perform a ‘deep-copy’ of any nested values contained inbind
.Returns a valid default value for this type, or
UNSET
if this type must be initialized with a value.get
(key[, default])Retrieve the corresponding layout by the string key.
Deserializes the mapped value from
bind
.hdf5_to_value
(bind)Parses bind into Python object.
items
()keys
()pop
(k[,d])If key is not found, d is returned if given, otherwise KeyError is raised.
popitem
()as a 2-tuple; but raise KeyError if D is empty.
py_type
(value_type)Determines the
py_type
of an attribute during value initialization, if it was not provided in theinfo
argument.setdefault
(k[,d])update
([E, ]**F)If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
value_to_hdf5
(bind_parent, key, value)Converts value into a HDF5 Array or Group under bind_parent[key].
values
()-
clear
() → None. Remove all items from D.¶
-
classmethod
consumes_types
()¶ Returns an iterable of types for which this should be the default codec. If a value of one of these types is assigned to a Dataset without specifying a type_id, this type will be used.
-
copy_value
()[source]¶ Deserializes the mapped value from
bind
, and also perform a ‘deep-copy’ of any nested values contained inbind
.
-
classmethod
default_value
()[source]¶ Returns a valid default value for this type, or
UNSET
if this type must be initialized with a value.
-
get
(key, default=None)¶ Retrieve the corresponding layout by the string key.
When there isn’t an exact match, all the existing keys in the layout map will be treated as a regex and map against the input key again. The first match will be returned, based on the key insertion order. Return None if there isn’t any match found.
- Parameters
key – the string key as the query for the layout.
- Returns
Corresponding layout based on the query.
-
get_value
()¶ Deserializes the mapped value from
bind
.
-
items
() → a set-like object providing a view on D’s items¶
-
keys
() → a set-like object providing a view on D’s keys¶
-
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.
-
classmethod
py_type
(value_type)¶ Determines the
py_type
of an attribute during value initialization, if it was not provided in theinfo
argument. This method returnsf"{value_type.__module__}.{value_type.__name__}
.
-
setdefault
(k[, d]) → D.get(k,d), also set D[k]=d if k not in D¶
-
update
([E, ]**F) → None. Update D from mapping/iterable E and F.¶ If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
-
value_to_hdf5
(bind_parent, key, value)[source]¶ Converts value into a HDF5 Array or Group under bind_parent[key].
-
values
() → an object providing a view on D’s values¶
-