Metadata-Version: 2.4
Name: SpatialMST
Version: 0.0.1
Summary: Spatial Multimodal Self-supervised Transformer
Author-email: Suraj Verma <verma.surajcool@gmail.com>
License: MIT License
Project-URL: Homepage, https://github.com/SurajRepo/SpatialMST
Keywords: SpatialMST
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: AUTHORS.rst
Requires-Dist: NumPy==1.26.4
Requires-Dist: scanpy
Requires-Dist: mudata
Requires-Dist: pandas==2.2.3
Requires-Dist: torch_geometric
Requires-Dist: torch
Requires-Dist: matplotlib
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: beautifulsoup4
Requires-Dist: lightning
Requires-Dist: magic-impute
Provides-Extra: all
Requires-Dist: SpatialMST[extra]; extra == "all"
Provides-Extra: extra
Requires-Dist: pandas; extra == "extra"
Dynamic: license-file

# SpatialMST


[![image](https://img.shields.io/pypi/v/SpatialMST.svg)](https://pypi.python.org/pypi/SpatialMST)
[![image](https://img.shields.io/conda/vn/conda-forge/SpatialMST.svg)](https://anaconda.org/conda-forge/SpatialMST)

[![image](https://pyup.io/repos/github/SurajRepo/SpatialMST/shield.svg)](https://pyup.io/repos/github/SurajRepo/SpatialMST)


**Spatial Multimodal Self-supervised Transformer**


-   Free software: MIT License

## Installation
### Create environment
    `
    conda create -n SpatialMSTEnv python=3.11
    conda activate SpatialMSTEnv
    `
### Install ipykernel
    `
    conda install ipykernel
    python -m ipykernel install --user --name SpatialMSTEnv --display-name "Python(SpatialMSTEnv)"
    `
### Install Pot
    `
    conda install -c conda-forge pot
    `
### Install SpatialMST
PyPI package: https://pypi.org/project/spmetatme/


The source files for spMetaTME can be downloaded from the [Github repo](https://github.com/Angione-Lab/SpatialMST.git).

You can either clone the public repository:

```sh
git clone https://github.com/Angione-Lab/SpatialMST.git
```

Once you have a copy of the source, you can install it with:

```sh
cd spmetatme
uv pip install .
```
