dynamo.vf.gen_gradient

dynamo.vf.gen_gradient(dim, N, Function, DiffusionMatrix)[source]

Calculate the gradient of the (learned) vector field function for the least action path (LAP) symbolically

Parameters:

  • dim ('int') – The number of dimension of the system

  • N ('int') – The number of the points on the discretized path of the LAP

  • Function ('function') – The function of the (learned) vector field function that is needed to calculate the Jacobian matrix

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

Returns:

  • ret (‘np.ndarray’) – The symbolic function that calculates the gradient of the LAP based on the Jacobian of the vector field function

  • V (‘np.ndarray’) – A matrix consists of the coordinates of the unstable steady state