speasy.core.data_containers module

class speasy.core.data_containers.DataContainer(values: array, meta: Dict = None, name: str = None, is_time_dependent: bool = True)[source]

Bases: DataContainerProtocol[DataContainer]

astype(dtype) → DataContainer[source]

copy(name=None)[source]

property dtype

static empty_like(other: DataContainer) → DataContainer[source]

static from_dictionary(dictionary: ~typing.Dict[str, str | ~typing.Dict[str, str] | ~typing.List], dtype=<class 'numpy.float64'>) → DataContainer[source]

property is_time_dependent: bool

property meta

property name

property nbytes: int

property ndim

static ones_like(other: DataContainer) → DataContainer[source]

static reserve_like(other: DataContainer, length: int = 0) → DataContainer[source]

reshape(new_shape) → DataContainer[source]

select(indices, inplace=False) → DataContainer[source]

property shape

to_dictionary(array_to_list=False) → Dict[str, object][source]

property unit: str

unit_applied(unit: str = None) → DataContainer[source]

property values: array

view(index_range: slice | ndarray)[source]

static zeros_like(other: DataContainer) → DataContainer[source]

class speasy.core.data_containers.DataContainerProtocol(*args, **kwargs)[source]

Bases: Protocol[T]

astype(dtype) → T[source]

property dtype: dtype

static from_dictionary(dictionary: ~typing.Dict[str, str | ~typing.Dict[str, str] | ~typing.List], dtype=<class 'numpy.float64'>) → T[source]

property is_time_dependent: bool

property name: str

property nbytes: int

static reserve_like(other: T, length: int = 0) → T[source]

select(indices, inplace=False) → T[source]

property shape

to_dictionary(array_to_list=False) → Dict[str, object][source]

property unit: str

property values: array

view(index_range: slice | ndarray) → T[source]

class speasy.core.data_containers.VariableAxis(values: array = None, meta: Dict = None, name: str = '', is_time_dependent: bool = False, data: DataContainer = None)[source]

Bases: DataContainerProtocol[VariableAxis]

astype(dtype) → VariableAxis[source]

property data_container: DataContainer

property dtype: dtype

empty_like() → VariableAxis[source]

static from_dictionary(dictionary: Dict[str, str | Dict[str, str] | List], time=None) → VariableAxis[source]

property is_time_dependent: bool

property meta: Dict

property name: str

property nbytes: int

ones_like() → VariableAxis[source]

static reserve_like(other: VariableAxis, length: int = 0) → VariableAxis[source]

select(indices, inplace=False) → VariableAxis[source]

property shape

to_dictionary(array_to_list=False) → Dict[str, object][source]

property unit: str

property values: array

view(index_range: slice | ndarray) → VariableAxis[source]

zeros_like() → VariableAxis[source]

class speasy.core.data_containers.VariableTimeAxis(values: array = None, meta: Dict = None, name: str = 'time', data: DataContainer = None)[source]

Bases: DataContainerProtocol[VariableTimeAxis]

astype(dtype) → VariableTimeAxis[source]

property data_container: DataContainer

property dtype: dtype

empty_like() → VariableTimeAxis[source]

static from_dictionary(dictionary: Dict[str, str | Dict[str, str] | List], time=None) → VariableTimeAxis[source]

property is_time_dependent: bool

property meta: Dict

property name: str

property nbytes: int

ones_like() → VariableTimeAxis[source]

static reserve_like(other: VariableTimeAxis, length: int = 0) → VariableTimeAxis[source]

select(indices, inplace=False) → VariableTimeAxis[source]

property shape

to_dictionary(array_to_list=False) → Dict[str, object][source]

property unit: str

property values: array

view(index_range: slice | ndarray) → VariableTimeAxis[source]

zeros_like() → VariableTimeAxis[source]

speasy.core.data_containers.fill_value_mask(values: ndarray, meta: Dict) → ndarray | None[source]

Returns a boolean mask of the entries equal to the ISTP FILLVAL, or None when no mask can be computed at all.

None means undecidable, not “nothing matched”: either FILLVAL is absent, or it is a string while the data is numeric, which warns. That second case is a real ISTP pattern rather than a hypothetical – CDAWeb mis-declares some numeric variables’ FILLVAL with a TT2000/EPOCH attribute type, which the data codec stringifies (e.g. ela_att_solution_date), and there is no reliable way to recover the intended numeric sentinel from that mismatch.

A NaN FILLVAL needs no special case: NaN != NaN, so it simply matches nothing, which is right because such data already carries NaN where it means fill.

speasy.core.data_containers.np_build_result_name(func, *args, **kwargs)[source]

speasy.core.data_containers.numpy_supported(cls)[source]

speasy.core.data_containers.scalar_meta(meta: Dict, key: str) → Any[source]: Returns a metadata entry, unwrapped from the single-element list CDF attributes arrive in.