time2wdm§

typed_lisa_toolkit.shop.time2wdm(tdata: TSData, /, *, Nt: int, Nf: int) → WDMData[Grid2DCartesian[Axis[Linspace, ModuleType], Axis[Linspace, ModuleType]]][source]§
typed_lisa_toolkit.shop.time2wdm(tseries: TimeSeries[Axis[Linspace, ModuleType]], /, *, Nt: int, Nf: int) → WilsonDaubechiesMeyer[Grid2DCartesian[Axis[Linspace, ModuleType], Axis[Linspace, ModuleType]]]

Transform a time series to WDM.

Note

The convention for signal duration in WDM is Nt*ΔT = N*Δt. This is not equivalent to the convention grid[-1] - grid[0], more useful for nonuniform grids, that you may be assuming elsewhere.

Parameters:

  • tseries (TimeSeries) – Regularly-sampled time series of length at least Nf*Nt.

  • Nt (int) – Length of WDM time grid.

  • Nf (int) – Nf+1 is the length of the WDM frequency grid.

Returns:

Transform of the first Nf*Nt points of the time series.

Return type:

WDM

Raises:

ValueError – If the time series is too small for the chosen values of Nf and Nt.