Installation and setup
This page provides instructions for setting up the software environment required to do the exercises in the lesson. The following packages are needed:
python=3.9
numpy
matplotlib
jupyterlab
qiskit
qiskit[visualization]
pylatexenc
r-base=3.6
r-tidyverse
rpy2
Local installation
It is strongly recommended to install all dependencies inside a virtual
environment. Here are instructions for using the conda
package manager.
Anaconda/miniconda
If you do not already have an Anaconda or miniconda installation on your computer, download and install miniconda (a smaller distribution than Anaconda) by following the official documentation.
With a working Anaconda/miniconda installation, you can now create a new conda environment with all the required packages by:
$ conda env create -f https://raw.githubusercontent.com/ENCCS/NordIQuEst-workshop/main/environment.yml
Before using the environment you need to activate it:
$ conda activate qcomp
Quito
First clone the repository:
$ git clone https://github.com/Simula-COMPLEX/quito.git
To use Quito one calls directly the script
python quito/Quito_CoverageRunning/quito.py
.
Exercises
All exercises are contained in Jupyter notebooks. You can work in two different ways:
Create a new Jupyter notebook using JupyterLab. Copy-paste code cells from the hands-on episodes of this lesson. Edit as needed and run.
Clone this repository to access the complete notebooks:
$ git clone https://github.com/ENCCS/NordIQuEst-workshop.git $ cd NordIQuEst-workshop/content/notebooks $ jupyter-lab
Running in the cloud
As an alternative to installing packages locally, you can also click the “launch binder” button on the front page. This will spin up a cloud instance on mybinder.org with all dependencies installed.
Exercises
After the Binder image spins up and you see the JupyterLab interface,
navigate to the /content/notebooks
directory in the left-hand file browser
to see the exercise notebooks.
You can also create new notebooks and copy-paste code cells and edit them
as needed.