Dear developers,
Thank you for your work on this project.
I noticed that this line of code in lifetime_cal.py can cause memory issues when loading somewhat large .ptu files.
The issue is that the code tries to load all data on the T, Y, X, and H axes before integrate over the T axis. For large files, this can be very memory-intensive. The time binning feature does not address this issue, since it happens afterward.
The recommended way to do this would be using the decode_image function or using slice notation to integrate along the T axis while decoding (see the ptufile examples). This is also how the phasorpy library does it.
Would you consider updating the implementation accordingly? I believe this would make the code more robust for .ptu files with high resolution and/or long acquisition time.
Dear developers,
Thank you for your work on this project.
I noticed that this line of code in
lifetime_cal.pycan cause memory issues when loading somewhat large .ptu files.The issue is that the code tries to load all data on the T, Y, X, and H axes before integrate over the T axis. For large files, this can be very memory-intensive. The time binning feature does not address this issue, since it happens afterward.
The recommended way to do this would be using the
decode_imagefunction or using slice notation to integrate along the T axis while decoding (see the ptufile examples). This is also how the phasorpy library does it.Would you consider updating the implementation accordingly? I believe this would make the code more robust for .ptu files with high resolution and/or long acquisition time.