get_phasor_image is not working?

[fluorescence-tools]

get_phasor_image is not working?

[tpeulen]

I have only very limited testing data. Can you provide me with a PTU file? Then I can make sure your data is going to work on the next release (ETA 1-2 month).

[Ozcifci]

Here are the PTU file and the short python script I wrote:
https://drive.google.com/file/d/1WFfUVMoAuF7sfyKUyhD5y-KtnOhm5iHe/view?usp=sharing
Please let me know if you need more data or information about the measurement.
Thank you a lot for your help.

[tpeulen]

Thanks, a lot. I will let you know on my progress via this issue.

[Ozcifci]

Since Monday I have used get_fluorescence_decay_image and analyzed the data with fourier transformation and IRF deconvolution with my script.
I have realized that my data has per pixel too few photons to perform proper phasor analysis. But I have to work with low concentrations.
get_fluorescence_decay_image bins the data in 16384 channels even though the data requires only 3214 channels after the time calibration. After increasing the micro_time_coarsening to 10 or so, I could get reasonable binning of the data. But, the get_phasor_image function does not have micro_time_coarsening, which is probably why the function cannot fourier transform the flat decay curve. I think the problem lies there. It may be good if you can implement micro_time_coarsening to get_phasor_image, too.

However, even binning the photons with lower resolution did not yield a good phasor plot, the data points are still too close to zero lifetime, which is not true.
I will now increase the photon count per pixel by decreasing the pixel size of 512x512 to e.g. 50x50.
Is there a possibility to do that while creating the tttrlib.CLSMImage Image?

[Ozcifci]

Update:
I found the problem and could perform a phasor plot without micro_time_coarsening and the need to reduce the image size.

The problem is that get_fluorescence_decay_image is binning the data in ~20% of the whole bins and filling the rest with zeros.
Thus the whole decay curve is squeezed to 20% of the whole macro resolution. I have deleted the unnecessary bins and now everything is working:
img_decays = np.delete(img_decays, np.s_[int(642/3276*img_decays.shape[3]):], axis=3)

Anyway it may be good if you could correct it in your next release since my script is quite slow.

Best wishes,
Özcifci