dynamo.vf.action
- dynamo.vf.action(n_points, tmax, point_start, point_end, boundary, Function, DiffusionMatrix)[source]
It calculates the minimized action value given an initial path, ODE, and diffusion matrix. The minimization is realized by scipy.optimize.Bounds function in python (without using the gradient of the action function).
- Parameters:
n_points (
int
) – The number of points along the least action path.tmax (
int
) – The value at maximum t.point_start (
ndarray
) – The matrix for storing the coordinates (gene expression configuration) of the start point (initial cell state).point_end (
ndarray
) – The matrix for storing the coordinates (gene expression configuration) of the end point (terminal cell state).boundary (
ndarray
) – Not used.Function (
Callable
) – The (reconstructed) vector field function.DiffusionMatrix (
Callable
) – The function that returns the diffusion matrix which can variable (for example, gene) dependent.
- Returns:
The action value for the learned least action path. output_path: The least action path learned.
- Return type:
fval