MAIVC: Module-based Artificial Intelligence Virtual Cell
Learning atomic operations for virtual cell construction.
Installation
- Create a virtual environment
conda create -n MAIVC python=3.10 scipy numpy pandas scikit-learn && conda activate MAIVC
- Install PyTorch following the official instruction.
pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu126
- Install MAIVC
pip3 install MAIVC
Metadata
Release files for scCoord 1.6.110
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| sccoord-1.6.110.tar.gz | 44.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sccoord-1.6.110-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 95.0 kB
Release files / sccoord-1.6.110.tar.gz
| Download URL | sccoord-1.6.110.tar.gz |
|---|---|
| Size | 44.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.18
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Release files / sccoord-1.6.110-py3-none-any.whl
| Download URL | sccoord-1.6.110-py3-none-any.whl |
|---|---|
| Size | 50.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.18
|