src.Refactoring

Attributes

`start_time`
`m_max`
`t_span`
`nu`
`v_e`
`q`
`sol`
`v_grid`
`f_vt`

Functions

reconstruct_fv(f_m_t, v_grid)

Reconstructs the time-evolving function f(v, t) on a velocity grid, given its

Module Contents

src.Refactoring.start_time

src.Refactoring.m_max = 200

src.Refactoring.t_span = None

src.Refactoring.nu = 2

src.Refactoring.v_e

src.Refactoring.q

src.Refactoring.sol

src.Refactoring.reconstruct_fv(f_m_t, v_grid)

Reconstructs the time-evolving function f(v, t) on a velocity grid, given its decomposition in terms of Hermite functions. The reconstruction is performed by computing the Hermite functions for all modes and velocities, normalizing them, and summing over the modes to obtain the desired function.

Parameters:

f_m_t (ndarray or jnp.ndarray) – Coefficients f_m(t) of the Hermite decomposition at each time step. The shape is (T, M), where T is the number of time steps, and M is the number of modes.
v_grid (ndarray or jnp.ndarray) – The velocity grid over which the function is reconstructed. The length of v_grid corresponds to the number of velocity points.

Returns:

The reconstructed function f(v, t) on the velocity grid. The shape of the output is (T, V), where V is the number of velocity points.

Return type:

jnp.ndarray

src.Refactoring.v_grid = None

src.Refactoring.f_vt