wdm

typed_lisa_toolkit.wdm(frequencies: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]] | Linspace, times: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]] | Linspace, entries: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]], *, sparse_indices: None = None) → WilsonDaubechiesMeyer[Grid2DCartesian[Axis[Linspace, ModuleType], Axis[Linspace, ModuleType]]]

typed_lisa_toolkit.wdm(frequencies: AxisT, times: AxisT, entries: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]], *, sparse_indices: None = None) → WDM[Grid2DCartesian[AxisT, AxisT]]

typed_lisa_toolkit.wdm(frequencies: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]] | Linspace, times: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]] | Linspace, entries: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]], *, sparse_indices: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]]) → WilsonDaubechiesMeyer[Grid2DSparse[Axis[Linspace, ModuleType], Axis[Linspace, ModuleType]]]

typed_lisa_toolkit.wdm(frequencies: AxisT, times: AxisT, entries: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]], *, sparse_indices: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]]) → WDM[Grid2DSparse[AxisT, AxisT]]

Build a WilsonDaubechiesMeyer.

Parameters:

• frequencies (AnyAxis) – Evenly-spaced frequencies with separation ΔF and size Nf+1.

• times (AnyAxis) – Evenly-spaced times with separation ΔT and size Nt.

• entries (Array) – For dense grid: an array of shape (n_batch, 1, 1, 1, Nf+1, Nt). For sparse grid: an array of shape (n_batch, 1, 1, 1, num_sparse_points) where num_sparse_points is the number of rows in sparse_indices.

Note

See the general description of the shape convention for entries.