https://github.com/daeh/comosoco-env
PPL environment for the course "Computational Models of Social Cognition"
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Low similarity (11.2%) to scientific vocabulary
Repository
PPL environment for the course "Computational Models of Social Cognition"
Basic Info
Statistics
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- Forks: 3
- Open Issues: 0
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Metadata Files
README.md
Computational Models of Social Cognition (CoMoSoCo) - Python Environment
This repository contains a starter Python environment for running Jupyter notebooks used in the Computational Models of Social Cognition course.
Environment Setup
For this course, you need a Python environment that lets you run Jupyter Notebooks with memo models. While this guide suggests creating an environment that matches the one I'll be using for the tutorials, you can also use a more minimal setup. As long as you can successfully run notebooks like comosoco/installation-test.ipynb, your setup should be sufficient.
Install Homebrew (MacOS only)
Homebrew is a package manager for MacOS that simplifies software installation and management.
Follow the installation instructions on https://brew.sh
Verify the installation:
bash
brew --version
I can't or don't want to use homebrew!
No problem, it just makes it easier to install and remove things on MacOS.Install git
git is a version control system that helps manage code. Here's how to install it:
With Homebrew:
bash
brew install git
Without Homebrew:
Follow the installation instructions on https://git-scm.com/download/win
Verify the installation:
bash
git --version
I can't or don't want to use git!
But git is great! Ok, though, you can skip it for now and download the repository directly as a ZIP file (see "Getting the Repository" section below).Install uv
Astral uv is a fast Python package installer that we'll use to set up the environment.
With Homebrew:
bash
brew install uv
Without Homebrew:
Follow the install instructions on https://docs.astral.sh/uv/getting-started/installation/
Verify the installation:
bash
uv --version
I can't or don't want to use uv!
Ok, we can work around that.Install Task (MacOS only)
Task is a task runner that simplifies common commands. While Task is not specific to MacOS, at the moment this repository only supports Task on MacOS.
With Homebrew:
bash
brew install go-task
Without Homebrew:
Follow the installation instructions on https://taskfile.dev/installation/
Verify the installation:
bash
task --version
I can't or don't want to use Task!
No problem, it's just for convenience.
Install Visual Studio Code
VS Code is the recommended editor for this course:
- Download VS Code from https://code.visualstudio.com
- Install the downloaded file
I can't or don't want to use VS Code!
You can use any editor that supports Jupyter notebooks, but this README only gives instructions for VS Code.Clone this repository
Choose one of these methods:
Option 1: Fork and Clone (Recommended)
1. Create a GitHub account if you don't have one
2. Go to this repository https://github.com/daeh/comosoco-env
3. Click the "Fork" button in the top-right corner
4. Clone your fork:
bash
git clone https://github.com/YOUR-USERNAME/comosoco-env.git
cd comosoco-env
Option 2: Direct Clone
bash
git clone https://github.com/daeh/comosoco-env.git
cd comosoco-env
Option 3: Direct Download
- Visit https://github.com/daeh/comosoco-env
- Click the green "Code" button
- Select "Download ZIP"
- Extract the ZIP file
- Navigate to the
comosoco-envfolder in your terminal
Installing the Environment
Make sure you're in the comosoco-env directory, then choose one method:
Option 1: Using Task (Easiest, MacOS)
bash
task install
Option 2: Using uv
bash
uv sync
Option 3: Using pip
1, Make a virtual environment:
```bash
python -m venv .venv
```
2. Activate the environment:
MacOS/Linux:
```bash
source .venv/bin/activate
```
Windows (Command Prompt):
```cmd
.venv\Scripts\activate.bat
```
Windows (PowerShell):
```powershell
.venv\Scripts\Activate.ps1
```
3. Install packages:
```bash
pip install -r requirements-standard.txt
```
If you encounter issues, try using `requirements-minimal.txt` instead:
```bash
pip install -r requirements-minimal.txt
```
Setting up VS Code
Open the VS Code application
Open
VSCProject.code-workspace
You should see that the window name is "comosoco"

- When prompted, install recommended extensions

Troubleshooting: If you don't see a prompt to install the recommended extensions, make sure you've correctly open the
VSCProject.code-workspacefile. You should see "comosoco" as the window name.Troubleshooting: If you're sure you have the workspace open, you can manually install the extensions by searching for
@recommendedin the Extension Pane
Open
comosoco/installation-test.ipynbSet the Jupyter notebook to use the
.venvpython incomosoco-env- See below for screen shots.
Run all cells in the notebook - if they complete without error, your setup is working!




Owner
- Name: Dae
- Login: daeh
- Kind: user
- Location: Cambridge, MA
- Company: MIT
- Website: https://daeh.info
- Twitter: daehoulihan
- Repositories: 2
- Profile: https://github.com/daeh
Neukom Computational Science Postdoc Fellow at Dartmouth. PhD from MIT Brain and Cognitive Sciences.
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Dependencies
- graphviz >=0.20.3
- ipykernel >=6.29.5
- jax >=0.4.36
- jupyterlab >=4.3.4
- matplotlib >=3.10.0
- memo-lang >=0.4.5
- numpy >=2.0.2
- optype [numpy]>=0.7.3
- pandas >=2.2.3
- pandas-stubs >=2.2.3.241126
- pydantic >=2.10.4
- python-dotenv >=1.0.1
- pyyaml >=6.0.2
- ruff >=0.8.6
- scikit-learn >=1.6.0
- scipy >=1.15.0
- scipy-stubs >=1.15.0.0
- seaborn >=0.13.2
- toml >=0.10.2
- tqdm >=4.67.1
- xarray >=2025.1.0
- ipykernel ==6.29.5
- matplotlib ==3.10.0
- memo-lang ==0.5.1
- pandas ==2.2.3
- scikit-learn ==1.6.0
- scipy ==1.15.0
- seaborn ==0.13.2
- xarray ==2025.1.1
- graphviz ==0.20.3
- ipykernel ==6.29.5
- jax ==0.4.38
- jupyterlab ==4.3.4
- matplotlib ==3.10.0
- memo-lang ==0.5.1
- numpy ==2.2.1
- optype ==0.8.0
- pandas ==2.2.3
- pandas-stubs ==2.2.3.241126
- pydantic ==2.10.5
- python-dotenv ==1.0.1
- pyyaml ==6.0.2
- ruff ==0.9.0
- scikit-learn ==1.6.0
- scipy ==1.15.0
- scipy-stubs ==1.15.0.0
- seaborn ==0.13.2
- toml ==0.10.2
- tqdm ==4.67.1
- xarray ==2025.1.1