pySEAS
python Signal Extraction and Segmentation
See the ReadTheDocs page to browse example experiment commands, documentation, and available function help.
Publication describing functionality: Weiser SC, Mullen BR, Ascencio D, Ackman JB (2023) Data-driven segmentation of cortical calcium dynamics. PLOS Computational Biology 19(5): e1011085. https://doi.org/10.1371/journal.pcbi.1011085
Full datasets generated with this code: Weiser, S, Mullen, BR, Ackman, J (2023), Data-driven segmentation of cortical calcium dynamics, Dryad, Dataset, https://doi.org/10.7291/D1N96W
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Release files for seas 0.0.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| seas-0.0.5.tar.gz | 83.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| seas-0.0.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 160.4 kB
Release files / seas-0.0.5.tar.gz
| Download URL | seas-0.0.5.tar.gz |
|---|---|
| Size | 83.9 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/4.0.2 CPython/3.9.16
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Release files / seas-0.0.5-py3-none-any.whl
| Download URL | seas-0.0.5-py3-none-any.whl |
|---|---|
| Size | 76.5 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.16
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