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Made some small changes to the README etc. for setup
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surabhisnath authored Jun 14, 2023
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214 changes: 214 additions & 0 deletions .gitignore
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## PYTHON IGNORES (from github/gitignore/python.gitignore)

# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class

# C extensions
*.so

# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST

# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec

# Installer logs
pip-log.txt
pip-delete-this-directory.txt

# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/

# Translations
*.mo
*.pot

# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal

# Flask stuff:
instance/
.webassets-cache

# Scrapy stuff:
.scrapy

# Sphinx documentation
docs/_build/

# PyBuilder
.pybuilder/
target/

# Jupyter Notebook
.ipynb_checkpoints

# IPython
profile_default/
ipython_config.py

# pyenv
# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
# .python-version

# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
#Pipfile.lock

# poetry
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock

# pdm
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
# in version control.
# https://pdm.fming.dev/#use-with-ide
.pdm.toml

# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/

# Celery stuff
celerybeat-schedule
celerybeat.pid

# SageMath parsed files
*.sage.py

# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/

# Spyder project settings
.spyderproject
.spyproject

# Rope project settings
.ropeproject

# mkdocs documentation
/site

# mypy
.mypy_cache/
.dmypy.json
dmypy.json

# Pyre type checker
.pyre/

# pytype static type analyzer
.pytype/

# Cython debug symbols
cython_debug/

# PyCharm
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/

## R IGNORES (from github/gitignore/R.gitignore)

# History files
.Rhistory
.Rapp.history

# Session Data files
.RData
.RDataTmp

# User-specific files
.Ruserdata

# Example code in package build process
*-Ex.R

# Output files from R CMD build
/*.tar.gz

# Output files from R CMD check
/*.Rcheck/

# RStudio files
.Rproj.user/

# produced vignettes
vignettes/*.html
vignettes/*.pdf

# OAuth2 token, see https://github.com/hadley/httr/releases/tag/v0.3
.httr-oauth

# knitr and R markdown default cache directories
*_cache/
/cache/

# Temporary files created by R markdown
*.utf8.md
*.knit.md

# R Environment Variables
.Renviron

# pkgdown site
docs/

# translation temp files
po/*~

# RStudio Connect folder
rsconnect/
24 changes: 21 additions & 3 deletions README.md
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Expand Up @@ -31,13 +31,31 @@ We recommend setting up a python virtual environment and installing all the requ
git clone https://github.com/surabhisnath/Relating_ObjectiveComplexity_SubjectiveComplexity_Beauty_BinaryPixelPatterns.git
cd Relating_ObjectiveComplexity_SubjectiveComplexity_Beauty_BinaryPixelPatterns

python3 -m venv ./env
python3 -m venv .env

# On macOS/Linux
source env/bin/activate
# On Windows
.env\Scripts\activate

pip install -r requirements.txt`
pip install -r requirements.txt
```

To reproduce the plots and results from the paper, simply run `DescriptiveAnalysis.ipynb` and `MixedEffectsModelling.R`.
To reproduce the plots from the paper, run
```bash
jupyter-lab
```
and open the file `scripts/DescriptiveAnalysis.ipynb`.

To reproduce the model fits from the paper
- Ensure you have a working R installation
- Install the required libraries
- *E.g.*, `install.packages(c("lme4", "ggplot2", "interactions", "dplyr", "mediation"))` from an R console
- Run `MixedEffectsModelling.R`
```R
setwd('/path/to/Relating_ObjectiveComplexity_SubjectiveComplexity_Beauty_BinaryPixelPatterns/scripts')
source("MixedEffectsModelling.R")
```

## Citation

Expand Down
3 changes: 1 addition & 2 deletions requirements.txt
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Expand Up @@ -2,9 +2,8 @@ imageio==2.19.3
matplotlib==3.5.2
numpy==1.21.5
pybdm==0.1.0
re
pandas
statsmodels
seaborn
scipy
pickle
jupyterlab

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