arpes.analysis.derivative.dn_along_axis

arpes.analysis.derivative.dn_along_axis(arr, dim='', smooth_fn=None, *, order=2)

Like curvature, performs a second derivative.

You can pass a function to use for smoothing through the parameter smooth_fn, otherwise no smoothing will be performed.

You can specify the dimension (by dim) to take the derivative along with the axis param, which expects a string. If no axis is provided the axis will be chosen from among the available ones according to the preference for axes here, the first available being taken:

[‘eV’, ‘kp’, ‘kx’, ‘kz’, ‘ky’, ‘phi’, ‘beta’, ‘theta]

Parameters:

• arr (xr.DataArray) – ARPES data

• dim (str) – dimension for derivative (default is the first item in dims)

• smooth_fn (Callable | None) –

  smoothing function. Define like as:

  def warpped_filter(arr: xr.DataArray):

  return gaussian_filtter_arr(arr, {“eV”: 0.05, “phi”: np.pi/180}, repeat_n=5)

• order – Specifies how many derivatives to take

Returns:

The nth derivative data.