# -*- coding: utf-8 -*-
from setuptools import setup

packages = \
['scimap',
 'scimap.cli',
 'scimap.helpers',
 'scimap.plotting',
 'scimap.preprocessing',
 'scimap.tests',
 'scimap.tools']

package_data = \
{'': ['*'], 'scimap.tests': ['_data/*']}

install_requires = \
['PhenoGraph>=1.5.7,<2.0.0',
 'TiffFile>=2020.11.18,<2021.0.0',
 'anndata>=0.7.4,<0.8.0',
 'dask[array]>=2.30.0,<3.0.0',
 'gensim>=3.8.3,<4.0.0',
 'llvmlite<=0.34.0',
 'matplotlib>=3.2.1,<4.0.0',
 'mkdocs-material>=7.1.1,<8.0.0',
 'mkdocs>=1.1.2,<2.0.0',
 'napari>=0.4.2,<0.5.0',
 'numba<=0.51.2',
 'numpy>=1.18.5,<2.0.0',
 'pandas>=1.0.4,<2.0.0',
 'plotly>=4.12.0,<5.0.0',
 'pytest-xvfb>=2.0.0,<3.0.0',
 'pytest>=5.4.3,<6.0.0',
 'scanpy>=1.6.0,<2.0.0',
 'scipy>=1.4.1,<2.0.0',
 'seaborn>=0.11.0,<0.12.0',
 'shapely>=1.7.1,<2.0.0',
 'sklearn>=0.0,<0.1',
 'tifffile>=2020.6.3,<2021.0.0',
 'zarr>=2.5.0,<3.0.0']

entry_points = \
{'console_scripts': ['scimap-clustering = '
                     'scimap.cli._scimap_mcmicro:clustering',
                     'scimap-mcmicro = scimap.cli._scimap_mcmicro:mcmicro_wrap',
                     'scimap-merge-h5ad = scimap.cli._scimap_mcmicro:merge']}

setup_kwargs = {
    'name': 'scimap',
    'version': '0.17.8',
    'description': 'Spatial Single-Cell Analysis Toolkit',
    'long_description': '# Single-Cell Image Analysis Package\n<br>\n\n[![build: Unix-Mac-Win](https://github.com/ajitjohnson/scimap/actions/workflows/build-unix-mac-win.yml/badge.svg)](https://github.com/ajitjohnson/scimap/actions/workflows/build-unix-mac-win.yml)\n[![Docs](https://github.com/ajitjohnson/scimap/actions/workflows/docs.yml/badge.svg)](https://github.com/ajitjohnson/scimap/actions/workflows/docs.yml)\n[![Downloads](https://pepy.tech/badge/scimap)](https://pepy.tech/project/scimap)\n[![PyPI Version](https://img.shields.io/pypi/v/scimap.svg)](https://pypi.org/project/scimap)\n[![PyPI License](https://img.shields.io/pypi/l/scimap.svg)](https://pypi.org/project/scimap)\n[![Gitter chat](https://badges.gitter.im/scimap_io/community.png)](https://gitter.im/scimap_io/community)\n\n<br>\n\n<img src="./docs/assets/scimap_logo.png" style="max-width:700px;width:100%" >\n\n<br> \n\nScimap is a scalable toolkit for analyzing spatial molecular data. The underlying framework is generalizable to spatial datasets mapped to XY coordinates. The package uses the [anndata](https://anndata.readthedocs.io/en/stable/anndata.AnnData.html) framework making it easy to integrate with other popular single-cell analysis toolkits. It includes preprocessing, phenotyping, visualization, clustering, spatial analysis and differential spatial testing. The Python-based implementation efficiently deals with large datasets of millions of cells.\n\n## Installation\n\nWe strongly recommend installing `scimap` in a fresh virtual environment.\n\n```\n# If you have conda installed\nconda create --name scimap python=3.7\nconda activate scimap\n```\n\nInstall `scimap` directly into an activated virtual environment:\n\n```python\n$ pip install scimap\n```\n\nAfter installation, the package can be imported as:\n\n```python\n$ python\n>>> import scimap as sm\n```\n\n## Get Started\n\n\n#### Detailed documentation of `scimap` functions and tutorials are available [here](http://scimap.xyz/).\n\n*SCIMAP* development is led by [Ajit Johnson Nirmal](https://ajitjohnson.com/) at the Laboratory of Systems Pharmacology, Harvard Medical School.\n\n## Funding\nThis work is supported by the following NIH grant K99-CA256497\n\n',
    'author': 'Ajit Johnson Nirmal',
    'author_email': 'ajitjohnson.n@gmail.com',
    'maintainer': None,
    'maintainer_email': None,
    'url': 'https://pypi.org/project/scimap/',
    'packages': packages,
    'package_data': package_data,
    'install_requires': install_requires,
    'entry_points': entry_points,
    'python_requires': '>=3.7,<4.0',
}


setup(**setup_kwargs)
