单细胞转录组中 UMAP的安装

Installing

UMAP depends upon scikit-learn, and thus scikit-learn's dependencies such as numpy and scipy. UMAP adds a requirement for numba for performance reasons. The original version used Cython, but the improved code clarity, simplicity and performance of Numba made the transition necessary.

Requirements:

(1) numpy

(2) scipy

(3) scikit-learn

(4) numba

Install Options

Conda install, via the excellent work of the conda-forge team:

conda install -c conda-forge umap-learn

The conda-forge packages are available for linux, OS X, and Windows 64 bit.

PyPI install, presuming you have numba and sklearn and all its requirements (numpy and scipy) installed:

pip install umap-learn

If pip is having difficulties pulling the dependencies then we'd suggest installing the dependencies manually using anaconda followed by pulling umap from pip:

conda install numpy scipy

conda install scikit-learn

conda install numba

pip install umap-learn

For a manual install get this package:

wget https://github.com/lmcinnes/umap/archive/master.zip

unzip master.zip

rm master.zip

cd umap-master

Install the requirements

sudo pip install -r requirements.txt

or

conda install scikit-learn numba

Install the package

python setup.py install