frequency_series§

typed_lisa_toolkit.frequency_series(frequencies: Linspace, entries: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]]) → UniformFrequencySeries[source]§
typed_lisa_toolkit.frequency_series(frequencies: Axis[Linspace, ModuleType], entries: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]]) → UniformFrequencySeries
typed_lisa_toolkit.frequency_series(frequencies: AxisT, entries: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]]) → FrequencySeries[AxisT]
typed_lisa_toolkit.frequency_series(frequencies: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]], entries: Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]]) → FrequencySeries[Axis[Array[Any, ModuleType] | ndarray[tuple[Any, ...], dtype[Any]], ModuleType]]

Build an FrequencySeries or a UniformFrequencySeries.

Parameters:

  • frequencies – Either a Linspace or a 1D array of positive frequencies.

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

Note

See the general description of the shape convention for entries.

Example

import jax.numpy as jnp
import typed_lisa_toolkit as tlt

fs1 = tlt.frequency_series(
    tlt.linspace(0, 1, 10), jnp.ones((1, 1, 1, 1, 10))
)  # UniformFrequencySeries
fs2 = tlt.frequency_series(
    jnp.array([0, 0.1, 0.3, 0.6, 1]), jnp.ones((1, 1, 1, 1, 5))
)  # FrequencySeries[Array[Any]]