dynamo.vf.alignment

dynamo.vf.alignment(numPaths, numTimeSteps, pot_path, path_tag, attractors_pot, x_path, y_path, grid=100, interpolation_method='linear')[source]

Align potential values so all path-potentials end up at same global min and then generate potential surface with interpolation on a grid.

Parameters:
  • numPaths (int) – Total Number of paths for defined grid spacing.

  • numTimeSteps (int) – A high-enough number for convergence with given dt.

  • pot_path (numpy.ndarray (dimension: numPaths x numTimeSteps)) – Potential along the path.

  • path_tag (numpy.ndarray (dimension: numPaths x 1)) – Tag for given path (to denote basin of attraction).

  • attractors_pot (numpy.ndarray) – Potential value of each identified attractors by the path integral approach.

  • x_path (numpy.ndarray) – x-coord. along path.

  • y_path (numpy.ndarray) – y-coord. along path.

  • grid (int) – No. of grid lines in x- and y- directions

  • interpolation_method (string) –

    Method of interpolation in griddata function. One of

    nearest

    return the value at the data point closest to the point of interpolation. See NearestNDInterpolator for more details.

    linear

    tessellate the input point set to n-dimensional simplices, and interpolate linearly on each simplex. See LinearNDInterpolator for more details.

    cubic (1-D)

    return the value determined from a cubic spline.

    cubic (2-D)

    return the value determined from a piecewise cubic, continuously differentiable (C1), and approximately curvature-minimizing polynomial surface. See CloughTocher2DInterpolator for more details.

Returns:

  • Xgrid (numpy.ndarray) – x-coordinates of the Grid produced from the meshgrid function.

  • Ygrid (numpy.ndarray) – y-coordinates of the Grid produced from the meshgrid function.

  • Zgrid (numpy.ndarray) – z-coordinates or potential at each of the x/y coordinate.