Installing Tisane
Requirements
Tisane requires Python 3.8+ and also an installation of R.
You will need to install the R packages lme4
, lmerTest
, and emmeans
, and also lazyeval
. (You can do this either by copying the below code into a file and running it using R, run it in RStudio, or you open an R shell and copy and paste the code.)
install.packages(c('lme4','lmerTest','emmeans','lazyeval'));
If you have issues with installing all 4 at once, for convenience, here they are individually:
install.packages('lme4');
install.packages('lmerTest');
install.packages('emmeans');
install.packages('lazyeval');
Installing with pip
We recommend using a virtualenv with pip
to keep your dependencies clean.
Here’s how you create and activate a virtualenv.
# create and activate your virtual environment, if you haven't already
# replace <MY-ENV-NAME> with the name of your env
python3 -m venv <MY-ENV-NAME>
# activate the virtual environment
source <MY-ENV-NAME>/bin/activate
Once you have activated the virtualenv, you install Tisane using pip
.
# install tisane
pip install tisane
As long as your virtualenv is activated, you will be able to run Python scripts that use Tisane with no problems!
Installing with poetry
Equivalently, you could also use poetry
, and add Tisane to your dependencies for your data analysis:
poetry add tisane
Installing with conda
conda install tisane
Installing R
For convenience, here are several ways you can install R:
Conda
Anaconda is a popular Python data science package manager, that can also be used to install R. This will also install the required R packages.
conda install -c conda-forge r r-base r-lmertest r-emmeans rpy2
Caution: using conda
together with poetry
may cause problems with running
models. In that case, you may want to install R in one of the following alternative ways.
Homebrew
brew install r
Download
Visit this page and select the version for your operating system.
RStudio
RStudio is a popular IDE for developing R scripts. You can download it here. Once you have installed RStudio, you can run the code in Requirements in the R shell in RStudio.