Nowadays, python is ruling the world. This very humble language that was once the realm of enlighted developers that loved to create the most beautiful scripting language is now becoming the programming language of the world, and particularly of the data deluge.
This repository allows you to install all the necesary stuff to start working with python on scientific applications, and particularly, to work with sensor data and neuroscience time-series. It allows you to install everything you need and start coding with NumPy, SciPy, OpenAI and MNE.
If you don't know anything at all about python, and you want to know something that will help you to do what you need, this is one place to be.
Install Git Bash
Download Anaconda 3.7 for your platform and install it.
Install Visual Studio Code
Download and install it from https://code.visualstudio.com/download
- Clone this repository
From the Git Bash console, run
git clone https://github.com/faturita/python-scientific.git
- Run an Anaconda Prompt
- Move with "cd" to the directory that you just downloaded ("cd python-scientific")
- Create the environment with:
conda env update --name mne3 --file environmentw.yml
(or this one if any error occurs
conda env update --prefix ./env --file environmentw.yml
- Activate the newly created environment
conda activate mne3
NOTE: if you receive an error about 'umap package missing' or similar, just edit your local file environmentw.yaml and erase the umap line from the file. You can later install this package directly from an Anaconda prompt by doing:
conda config --add channels conda-forge conda config --set channel_priority strict
- Install umap (or any package that you want)
conda install -n mne3 umap
conda install -n mne3 umap-learn