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Denis (from ISS beamline) requested a new schema be added to the postprocessing operations for aligning energy grids from multiple spectra. Currently there is a StandardizeGrid UnaryOperator, which operates on single spectrum and standardizes the energy grid to a uniformly spaced values (i.e., new_grid = np.linspace(self.x0, self.xf, self.nx)).
However XAS spectra are often not sampled on uniformly spaced grids because there is more information at different regions of the spectrum.
This new schema will work in the following way:
operates on a group of spectra (MimoOperator)
select one "master energy grid" from the group (this could be the first spectrum passed by default)
align all spectra in group to "master grid" via InterpolatedUnivariateSpline
The text was updated successfully, but these errors were encountered:
@CharlesC30 this is an interesting take but it makes sense. As long as the user is confident that the first (or at least some specified) spectrum contains the "master energy grid" this is a really good idea!
@x94carbone thanks! You are right the user would have to have some confidence about the "master grid", but Denis expressed a strong preference for this method over the current scheme. I already have some code written for this. Would it be okay to commit now or should we wait until #50 is closed?
Denis (from ISS beamline) requested a new schema be added to the postprocessing operations for aligning energy grids from multiple spectra. Currently there is a
StandardizeGrid
UnaryOperator, which operates on single spectrum and standardizes the energy grid to a uniformly spaced values (i.e.,new_grid = np.linspace(self.x0, self.xf, self.nx)
).However XAS spectra are often not sampled on uniformly spaced grids because there is more information at different regions of the spectrum.
This new schema will work in the following way:
MimoOperator
)InterpolatedUnivariateSpline
The text was updated successfully, but these errors were encountered: