Metadata-Version: 2.1
Name: ibl-photometry
Version: 1.0.0
Summary: IBL photometry module
Author-email: IBL staff <info@internationalbrainlab.org>
License: MIT License
        
        Copyright (c) 2023 International Brain Laboratory
        
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Project-URL: Homepage, https://github.com/int-brain-lab/iblphotometry
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: ibllib
Requires-Dist: numpy
Requires-Dist: matplotlib
Requires-Dist: pytest
Requires-Dist: scipy
Requires-Dist: pandera
Requires-Dist: pywavelets

# photometry-tools
A collection of methods and tools for experimental photometry data

## under construction
this library is right now undergoing some reorganization and is not yet ready for use
stay tuned!
<!-- ## Note about the preferred formats
A good practice is to keep the raw photometry data in a dataframe with columns:
- times
- raw_isosbestic
- raw_calcium
- (optional) calcium


The preferred interchange format is the parquet format (`.pqt`), which is a binary format that is fast to read and write, compressed and keeps typing information.
You can easily convert a dataframe to parquet `pd.to_parquet('my_file.pqt')` and read it back `pd.read_parquet('my_file.pqt')`.

cf. example [here](./src/examples/csv_preprocessing.py) -->


