TimedFSData

class typed_lisa_toolkit.types.TimedFSData

Multi-channel frequency series data with time information.

Note

To construct a TimedFSData, use the factory function fsdata().

classmethod from_dict(data_dict: Mapping[str, AnyReps], /, **kwargs: Any) → Self

Create a new instance from a dictionary of channel names to representations.

Warning

This is an expert-level API. Most users should use the top-level factory functions in typed_lisa_toolkit.

classmethod from_entries(*, frequencies: Axis[Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]] | Linspace, ModuleType], entries: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]], channels: tuple[str, ...], name: str | None = None) → Self

Construct from raw frequency-domain entries and explicit channel names.

Warning

This method is considered an expert-level API; for most users, prefer to construct a FSData with the factory function fsdata().

classmethod load(file_path: str | Path, *, legacy: bool = False)

Load the data from an HDF5 file (Deprecated).

Warning

This method is deprecated and will be removed in 0.8.0; use load_data() instead.

drop_times()

Drop the time grid.

get(k[, d]) → D[k] if k in D, else d.  d defaults to None.

get_embedded(embedding_grid: Grid1D[Axis[Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]] | Linspace, ModuleType]], *, known_slices: tuple[slice, ...] | None = None) → Self

Return data embedded on a new 1D grid.

get_kernel() → Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]]

Return kernel entries in conventional shape.

get_subset(*, interval: tuple[float, float] | None = None, slice: slice | None = None) → Self

Return the subset as a new instance.

items() → a set-like object providing a view on D's items

keys() → a set-like object providing a view on D's keys

pick(channels: str | tuple[str, ...]) → Self

Return a new instance containing only the specified channels.

save(file_path: str | Path)

Save the data to an HDF5 file.

The data are saved in the following structure:

• The root level contains the attribute type with the class name.

• Each channel is saved as a group.

• The group contains two datasets:

  • grid for the grid.

  • entries for the entries.

• For TimedFSData, there will be a dataset times at the root level containing the time grid.

set_name(name: str | None) → Self

Set the name of the data container.

The name is only used for labeling the data container in plots.

Note

This method returns self to allow for fluent method chaining.

set_times(times: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]] | Linspace) → Self

set_times(times: Axis[Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]] | Linspace, ModuleType]) → Self

Set the time grid.

Note

This method returns self to allow for fluent method chaining.

to_tsdata(times: ndarray[tuple[Any, ...], dtype[floating[Any]]] | Linspace | None = None, *, tapering: Tapering | None = None)

Return the time series data with times grid (Deprecated).

Warning

This method is deprecated and will be removed in 0.8.0; use freq2time() instead.

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

property channel_names: tuple[str, ...]

Return the channel names.

property df

Return the frequency step.

property domain: Literal['time', 'frequency', 'time-frequency']

Physical domain shared by all channels.

property dt: float

Step size of the associated time grid.

property f_max

Return the maximum frequency.

property f_min

Return the minimum frequency.

property frequencies

Return the frequencies.

property grid

Return the grid.

property kind

Semantic kind of the data.

property times

Associated time grid.

property xp

The underlying array namespace (numpy-like module).