Installation¶
Using Anaconda or Miniconda (recommended)¶
Using conda (latest version recommended), gms_preprocessing is installed as follows:
Create virtual environment for gms_preprocessing (optional but recommended):
$ conda create -c conda-forge --name gms python=3 $ conda activate gms
Then install gms_preprocessing itself:
$ conda install -c conda-forge gms_preprocessing
This is the preferred method to install gms_preprocessing, as it always installs the most recent stable release and automatically resolves all the dependencies.
Using pip (not recommended)¶
There is also a pip installer for gms_preprocessing. However, please note that gms_preprocessing depends on some open source packages that may cause problems when installed with pip. Therefore, we strongly recommend to resolve the following dependencies before the pip installer is run:
gdal
geopandas
ipython
matplotlib
numpy
pyhdf
python-fmask
pyproj
scikit-image
scikit-learn=0.23.2
shapely
scipy
Then, the pip installer can be run by:
$ pip install gms_preprocessing
To enable lock functionality (needed for CPU / memory / disk IO management), install redis-server:
sudo apt-get install redis-server
If you don’t have pip installed, this Python installation guide can guide you through the process.
Note
The gms_preprocessing package has been tested with Python 3.4+. It should be fully compatible to all Python versions from 3.4 onwards.