Utility functions

This section summarizes various useful functions implemented in LumiSpy.

Join spectra

In case several spectra (or spectral images) where subsequently recorded for different, but overlapping spectral windows, LumiSpy provides a utility join_spectra() to merge these into a single spectrum. The main argument is a list of two or more spectral objects. Spectra are joined at the centre of the overlapping range along the signal axis. To avoid steps in the intensity, several parameters (see docstring: join_spectra()) allow to tune the scaling of the later signals with respect to the previous ones. By default, the scaling parameter is determined as average ratio between the two signals in the range of +/- 50 pixels around the centre of the overlapping region.

>>> import lumispy as lum
>>> s = lum.join_spectra((s1,s2))

Scaling and normalizing signal data

For comparative plotting or a detailed analysis, the intensity of spectra may need to be either scaled by the respective integration times or normalized. The luminescence signal classes provide these functionalities in the methods scale_by_exposure() and normalize().

Both functions can operate directly on the signal (inplace=True), but as default a new signal is returned.

The scaling function can use the integration_time (unit: seconds) provided in the LumiSpy metadata structure (metadata.Acqusition_instrument.Detector.integration_time). Otherwise, the appropriate parameter has to be passed to the function.

>>> scaled = s.scale_by_exposure(integration_time=0.5, inplace=True)

Normalization is performed for the pixel with maximum intensity, Alternatively, the parameter pos in calibrated units of the signal axis can be given to normalize the intensity at this position. Normalization may be convenient for plotting, but should usually not be performed on signals used as input for further analysis (therefore the default is inplace=False).

>>> s.normalize(pos=450)

Replacing negative data values

Log-scale plotting fails in the presence of negative values in the dataset (e.g. introduced after background removal). In this case, the utility function remove_negative() replaces all negative values in the data array by a basevalue (default basevalue=1). The default operational mode is inplace=False (a new signal object is returned).

>>> s.remove_negative(0.1)

Utilities for spectral maps

The function crop_edges() removes the specified number of pixels from all four edges of a spectral map. It is a convenience wrapper for hyperspy.signal.BaseSignal.inav().

>>> s.crop_edges(crop_px=2)

[TODO: add possibility to crop different amounts of pixels on different sides]

Unit conversion

For convenience, LumiSpy provides functions that convert between different units commonly used for the signal axis. Namely,

• nm2eV()

• eV2nm()

• nm2invcm()

• invcm2nm()

For the energy axis, the conversion uses the wavelength-dependent refractive index of air.

Solving the grating equation

The function solve_grating_equation() follows the conventions described in the tutorial from Horiba Scientific.