Ref to paper (ToDo - complete)
Retrodiction as Delayed Recurrence: the Case of Adjectives in Italian and English
This code has only been tested in Linux Mint 19+, with the Python library versions specified in environment.yml, and R version 4.0.4.
The quick recipe:
- Install Miniconda3 (or Conda if preferred):
https://docs.conda.io/en/latest/miniconda.html
- Create an environment using the provided environment.yml file:
conda env create -f environment.yml
- You may need to install PyTorch and the Spacy models separately:
conda install --name learningadjs pytorch==1.5.0 torchvision==0.6.0 -c pytorch
Alternatively, use pip from within your activated (virtual) Python environment:
cat requirements.txt | xargs -n 1 pip install
pip install torch==1.5.0+cu101 torchvision==0.6.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html
The reported simulations used Spacy v. 2.0.12.
conda install -c conda-forge spacy
python -m spacy download en_core_news_sm
python -m spacy download it_core_news_sm
The following packages are required for AoA analyses:
sudo apt-get -y install r-cran-rmysql libcurl4-gnutls-dev libxml2-dev libssl-dev libmysql++-dev gfortran liblapack-dev liblapack3 libopenblas-base libopenblas-dev
As well as:
install.packages("magrittr")
install.packages("dplyr")
install.packages('devtools', repos='http://cran.rstudio.com/')
install.packages("stringr") #required for wordbankr
install.packages("wordbankr")
install.packages("optparse")
For using R from Bash scripts and command line:
sudo apt-get install littler
To reproduce the analyses in the paper, :
- Data Preparation
- Analyses TPs
- Analyses AoA
- Train and test RNNs (see src/scripts)
- Analyze predictions of RNNs