Yet Another TimeSeries Model (YATSM) is written in Python (version 2.7, but 3.5 is soon to be a priority) and utilizes several C libraries, including the Geographic Data Abstraction Library (GDAL). Package dependencies are most easily installed using Conda, but may also be installed using your package manager on Linux (see Ubuntu 14.04 example), Homebrew on Mac OS, or through OSGEO4W on Windows.

However, it is strongly encouraged that you install YATSM into an isolated environment, either using virtualenv for pip installs or a separate environment using conda, to avoid dependency conflicts with other software.


Requirements for YATSM may also be installed using conda, Python’s cross-platform and platform agnostic binary package manager from ContinuumIO. conda makes installation of Python packages, especially scientific packages, a breeze because it includes compiled library dependencies that remove the need for a compiler or pre-installed libraries.

Installation instructions for conda are available on their docs site

Since conda makes installation so easy, installation through conda will install all non-developer dependencies. Install YATSM using conda into an isolated environment by using the environment.yaml file as follows:

# Install
conda env create -n yatsm -f environment.yaml
# Activate
source activate yatsm

And as with pip, you need to install YATSM:

# Install YATSM
pip install .

virtualenv and pip


Python and GDAL are usually installed on most computing environments that handle geographic data (if not, see an example of installing these dependencies on Ubuntu 14.04). If you wish to install YATSM on a system with these two dependencies but you don’t have installation privileges for the Python dependencies, you could install YATSM into a virtualenv.

virtualenv creates isolated Python environments, thus enabling a user without root privileges to install modules. virtualenv has the added benefit of enabling the installation of specific module versions for single piece of software.

To set up a virtualenv, it must first be available. With root access,

sudo pip install virtualenv

Once virtualenv is installed, users may create a virtualenv for YATSM:

virtualenv yatsm_venv

To activate this isolated Python environment from Bash:

source yatsm_venv/bin/activate

Your terminal prompt will change, denoting the switch to this newly created isolated Python environment.


The basic dependencies for YATSM are included in the requirements.txt file which is by pip as follows:

pip install -r requirements.txt

Additional dependencies are required for some timeseries analysis algorithms or for accelerating the computation in YATSM. These requirements are separate from the common base installation requirements so that YATSM may be more modular:

  • Long term mean phenological calculations from Melaas et al., 2013
    • Requires the R statistical software environment and the rpy2 Python to R interface
    • pip install -r requirements/pheno.txt
  • Computation acceleration
    • GLMNET Fortran wrapper for accelerating Elastic Net or Lasso regularized regression
    • Numba for speeding up computation through just in time compilation (JIT)
    • pip install -r requirements/accel.txt

A complete installation of YATSM, including acceleration dependencies and additional timeseries analysis dependencies, may be installed using the requirements/all.txt file:

pip install -r requirements/all.txt

Finally, install YATSM:

# Install YATSM
pip install .

Developer Installation

If you’re interested in helping develop YATSM, you can download the repository using Git and install it in an editable installation:

git clone
cd yatsm/
pip install -e .

Documentation may be built using Sphinx from the docs directory:

cd docs/
make html

Platform Support

YATSM is developed on Linux (CentOS 6, Arch, and Ubuntu 14.04) and has not been tested on any other platforms, though I have seen it working on Mac OS. I am welcome to any help fixing bugs or better supporting Windows, but I will not try to support Windows myself.

Ubuntu 14.04

On Ubuntu 14.04, for example, the GDAL build dependencies may be satisfied by installing the following:

sudo apt-get install python2.7-dev
sudo apt-get install gdal-bin libgdal-dev
sudo apt-get install python-gdal

This installation guide will also utilize the pip utility for installing Python modules. pip may be installed or upgraded following the instructions here, but it is usual preferable to use your package manager:

$ sudo apt-get install python-pip

You will also need two font packages for matplotlib that are not installed with Ubuntu by default:

$ sudo apt-get install libfreetype6-dev libxft-dev

With the GDAL library and pip installed, follow the guide for how to install YATSM below using virtualenv and pip.