Working with streak images

LumiSpy has implemented handling of streak camera images, which are a special subclass of hyperspy.api.signals.Signal2D as the two signal axes have different units: Namely, wavelength (or energy) and time. The signal class is LumiTransientSpectrum. An important feature is that also for streak camera images (or linescans/maps of these), the wavelength axis can be transformed to e.g. a The energy axis.

Note

For streak images, not all tools available for hyperspy.api.signals.Signal2D will work. However, in particular Peak finding can be helpful to identify local maxima in the images.

Transition to one-dimensional signals

When transitioning from a streak image to a one-dimensional signal, LumiSpy uses the axes units of the new signal (whether it is time units or not) to assign the correct 1D signal class: Either LumiSpectrum or LumiTransient. Such a reduction of the signal dimensionality can be done for example by slicing the signal with numpy-style indexing or by using functions such as sum() and integrate1D()

In the following image, the spectrum summed over all times is obtained from the streak image by:

>>> import lumispy as lum
>>> import numpy as np
...
>>> data = np.arange(10*20).reshape(10, 20)
...
>>> s = lum.signals.LumiTransientSpectrum(data)
>>> s.axes_manager[-1].name = "Time"
>>> s.axes_manager[-1].units = "ns"
>>> s.axes_manager[-2].name = "Wavelength"
>>> s.axes_manager[-2].units = "nm"
>>> s.sum(axis='Time')
>>> # Or alternatively:
>>> s.sum(axis=-1)

Similarly, the transient summed over all wavelengths is obtained by:

>>> s.sum(axis='Wavelength')
>>> # Or alternatively:
>>> s.sum(axis=-2)