arpes.plotting.ui.smoothing.DifferentiateApp#

class arpes.plotting.ui.smoothing.DifferentiateApp(data, **kwargs)[source]#

An interactive differentiation UI for xarray DataArray using Panel and HoloViews.

After smoothing, Differentiate, Maximum curvaure (1D, 2D) and Minimum gradient techniques applied to find the peak position.

__init__(data, **kwargs)[source]#

Initialize the DifferentiationApp with data and parameters.

Parameters:

  • data (xr.DataArray) – Input data to be differentiated.

  • **kwargs – Additional parameters for the UI, such as pane_kwargs.

Methods

__init__(data, **kwargs)

Initialize the DifferentiationApp with data and parameters.

_boxcar_smoothing(data, **kwargs)

_build()

Build the differentiation UI components.

_derivative(data, **kwargs)

_gaussian_smoothing(data, **kwargs)

_get_current_derivative_params()

Retrieve current values from parameter widgets.

_get_current_params()

Retrieve current values from parameter widgets.

_maximum_curvature_1d(data, **kwargs)

_maximum_curvature_2d(data, **kwargs)

_minimum_gradient(data, **kwargs)

_n_th_derivative_with_SG(data, **kwargs)

Apply second derivative using Savitzky-Golay filter.

_on_apply(_)

Callback when Apply button is clicked.ArithmeticError.

_savitzky_golay_smoothing(data, **kwargs)

_update_derivative_param_widgets(*_)

Update the parameter widgets based on the selected smoothing function.

_update_plot()

Update the HoloViews plot with the current (smoothed) data.

_update_plot0()

Update the HoloViews plot with the current (smoothed) data.

_update_smooth_param_widgets(*_)

Update the parameter widgets based on the selected smoothing function.

log_message(message)

Append a message to the log and update the message pane.

panel()

Return the Panel layout for the smoothing application.

Attributes

_abc_impl