Open aurore-finco opened 1 month ago
this is uncommon because then each signal data is different for each pixel. What could be done to get back with usual data is to create an axis and interpolate all your signal data on this one (even if it means you'll have to crop a bit the total range). Then you'll be back with an object that you can manipulate easily
OK thanks. This is indeed a solution, although I do not really like interpolating raw data when this is not absolutely needed.
I have the impression that something could also work with a spread data distribution, as we keep the number of microwave frequencies constant, but this is not clear yet, I'll keep thinking about it.
if the number of frequencies is constant and the scaling also then you could just use an axis composed of index and store the scaling and offset as extra attributes of the data object
Yes, I think that it would work. I will try that. Thanks a lot!
Hi! I started trying loading our data from other setups not running with pymodaq using pymodaq_data, and there is something that I do not know how to do. When we do 2D scans measuring the magnetic resonance of the NV center at each pixel, we often change the microwave frequency range at each pixel to track the resonance. So in the end we have a 3D data object with 2 nav axes and one signal axis which is varying. Is there a way to "attach" an Axis object to every pixel in the map in a DataWithAxes? Or is it a weird thing that nobody else would need?
Thanks!