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 (function) – The (reconstructed) vector field function.

  • DiffusionMatrix (function) – The function that returns the diffusion matrix which can variable (for example, gene) dependent.

Returns:

  • fval (ndarray) – The action value for the learned least action path.

  • output_path (ndarray) – The least action path learned