Preprocessing

Preprocessing#

The Preprocessing tab presents an interactive 2D view of the transient-absorption surface, with a crosshair that updates both the ΔA vs. time trace and the ΔA vs. wavelength slice. Users can trim, resample, subtract background/solvent, align time zero, filter, and correct for group-velocity dispersion (“chirp”). Each operation generates a new dataset linked to its immutable raw data, with structured metadata recorded automatically. Exporting to HDF5 preserves the complete raw–dataset hierarchy and metadata, ensuring full provenance and reproducibility.

  • Dataset Widget

    select the dataset to which the processing should be applied.

  • Views Widget

    • Full View

      Plots the full range of the dataset

    • Time Zero View

      Plots the temporal range close to zero. Good for inspection of the chirp.

    • Manual View

      Internally used by TAPAS when data is trimmed.

    • Toolbox above the Canvas

      Additionally, the displayed view can be adjusted by the arrow and magnifying glass tools above the canvas.

  • View Manipulations Widget

    Set a delay-time (eg. 2ps, 2e-12, 2µs) where the delay-time axis should switch from a linear to a logarithmic time-scale.

  • Trim Data Widget

    set a wavelength or delay-time interval. If no value is provided, the minimum/maximum value of the dataset is used. The Canvas will be updated immediately. Pressing Apply will save the new interval to the selected dataset.

  • Resampling Widget

    • Resample:

      Down or upsampe the data grid.

      • Intervall:

        Set the intervall where the resampling should be applied.

      • Factor:

        the sampling factor (eg. 0.1 means downsampling to 10% of datapoints, 3 means subsamling to 3 times the datapoints).

      • Axis:

        the axis (wavelength or delay time) over which the sampling will be applied

      • Method:

        interpolation method: see scipy.interpolate.make_interp_spline for further information on the linear, quadratic and cubic interpolation method, scipy.interpolate.pchip_interpolate for pchip interpolation and scipy.interpolate.Akima1DInterpolator for akima and makima interpolation.

    • Regularize:

      Regularize the grid with equally spaced data points.

  • Chirp Correction Widget

    • Autocorrect:

      automatically find points in the dataset given a preset heuristic (eg. x % rise, x mOD threshold, maximum value).

    • Manually Correct:

      when activated, chirppoints used for fitting can be added by left-click and deleted by right-click in the 2D data canvas.

    • Correct from Project:

      load the chirp fitting coefficients of another project and dataset with a file dialog.

    • Fit:

      fit a 4th order polynomial to the given chirp points. a minimum of 5 points must be provided

    • Show Correction:

      after a successfull fit, the chirp correction can be displayed in the cavas with this button.

    • Apply:

      Apply the fitted chirp line to the dataset via interpolation.

  • Background Correction Widget

    • Subtract Area:

      use an averaged spectrum to subtract from the dataset.

      • Intervall:

        select the delay-time interval which will be used for the averaged background.

      • Subtract up to:

        set the maximum delay-time up to which the background will be subtracted.

      • Method:

        averaging method

    • Subtract from Project:

      load a 2D surface from another project and dataset. Only valid, if both datasets have the same dimensions.

    • Subtract Solvent:

      Subtract the solvent data imported in the Import tab. Only valid, if both datasets have the same dimensions.

  • Time Zero Correction Widget

    • Time-Point:

      Delay time vector will be shifted so that Time-Point equals zero.

  • Averaging and Filtering Widget

    • Savitzky-Golay:

      Apply a Savitzky-Golay filter scipy.signal.savgol_filter

      • Window:

        The length of the filter window.

      • Order:

        Order of the polynomial used to fit the data.

      • Axis:

        the axis (wavelength or delay time) over which the sampling will be applied.

    • Moving Median:

      Apply a median filter scipy.ndimage.median_filter

      • Size:

        Filter subset length.

      • Axis:

        the axis (wavelength or delay time) over which the sampling will be applied.

    • Moving Average:

      Apply a uniform filter scipy.ndimage.uniform_filter

      • Size:

        Filter subset length.

      • Axis:

        the axis (wavelength or delay time) over which the sampling will be applied.