time_series§

typed_lisa_toolkit.time_series(times: Linspace, entries: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]]) → UniformTimeSeries[source]§
typed_lisa_toolkit.time_series(times: Axis[Linspace, ModuleType], entries: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]]) → UniformTimeSeries
typed_lisa_toolkit.time_series(times: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]], entries: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]]) → TimeSeries[Axis[Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]], ModuleType]]
typed_lisa_toolkit.time_series(times: AxisT, entries: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]]) → TimeSeries[AxisT]

Build a TimeSeries or a UniformTimeSeries.

Parameters:

  • times – Either a Linspace or a 1D array of time points.

  • entries (Array) – An array of shape (n_batch, 1, 1, 1, Nt) where Nt is the size of times.

Note

See the general description of the shape convention for entries.

Example

import jax.numpy as jnp
import typed_lisa_toolkit as tlt

ts1 = tlt.time_series(
    tlt.linspace(0, 1, 10), jnp.ones((1, 1, 1, 1, 10))
)  # UniformTimeSeries
ts2 = tlt.time_series(
    jnp.array([0, 0.1, 0.3, 0.6, 1]), jnp.ones((1, 1, 1, 1, 5))
)  # TimeSeries[Array]