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nel-lab / mesmerize-core

High level pandas-based API for batch analysis of Calcium Imaging data using CaImAn
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No matching distribution found for LazyTiff #292

Closed lea-danics closed 5 months ago

lea-danics commented 5 months ago

Dear Kushal,

I cannot overcome at the following point of cnmfe demo workbook: a = LazyTiff(df.iloc[0].caiman.get_input_movie_path()) 2 a.shape

NameError: name 'LazyTiff' is not defined

I couldn't import neither install LazyTiff.

When I tried to install I got ERROR: Could not find a version that satisfies the requirement lazytiff (from versions: none) ERROR: No matching distribution found for lazytiff

For installation I tried this code in (mescore) PS C: C:\Users\danic git clone https://github.com/plimkilde/lazytiff.git cd lazytiff pip install lazytiff

Thanks for the help in advance!!

kushalkolar commented 5 months ago

LazyTiff is a mescore loader but I'd really just recommend using tiffit by @EricThomson (check his repo) to convert your tiff files so that they're memmapable (I'm assuming you don't have memmapable tiff files right now), which makes them much nicer to deal with.

lea-danics commented 5 months ago

Thank You! I installed tiffit as well. Than should I only modify the code? e.g. a = tiffit(df.iloc[0].caiman.get_input_movie_path()) 2 a.shape

Thanks for the help!

EricThomson commented 5 months ago

tiffit is a command line interface so at the command line you can convert your movies to a "good" format before you start your analysis, before you do anything in jupyter. So in your anaconda prompt (or whatever command line you initially use to run jupyter from), you activate your virtual environment. Then, if you have a "bad" tiff file named bad.tiff, create a good tiff file with:

tiffit convert bad.tiff good.tiff

That creates a new tiff file named good.tiff which behaves better for Caiman and mesmerize etc. Then you do your analysis on good.tiff within jupyter as usual.

kushalkolar commented 5 months ago

Thank You! I installed tiffit as well. Than should I only modify the code? e.g. a = tiffit(df.iloc[0].caiman.get_input_movie_path()) 2 a.shape

Thanks for the help!

Can you please tell us what you're trying to do, the full context.

kushalkolar commented 5 months ago

Hi, I'm guessing you solved this, if not feel free to re-open :)