Downloading and launching this workshop’s Jupyter notebooks

During this tutorial, we will be working through a set of Jupyter notebooks. On this page, we will download the notebooks and launch the jupyter notebook application.

Downloading the notebooks

There are two ways to download the notebooks; follow the instructions below for either downloading a .zip file (recommended for beginners) or cloning via git.

Downloading .zip

To download the notebooks as a .zip file, do the following:

1. Navigate your web browser to the workshop’s github repository (for this template, this is napari/napari-workshop-template)

2. Click the green “Code” button to open the download menu and then “Download ZIP”

3. Choose the location you would like to download the .zip into.

4. Open your file browser and double click on the .zip file to uncompress it.

5. You have downloaded the notebooks! Proceed to the “Launching jupyter notebook” section.

Cloning via git

To clone the repository containing the tutorial materials to your computer, open your Terminal and navigate to the folder where you will download the course materials into. We recommend cloning the materials into your Documents folder, but you can choose another suitable location.

cd ~/Documents

Then, clone the repository. This will download all of the files necessary for this tutorial.

git clone https://github.com/napari/napari-workshop-template.git

Launch the jupyter notebook application

Open your terminal and navigate to the notebooks subdirectory of the napari-workshop-template directory you just downloaded.

cd <path to napari-workshop-template>/notebooks

Now activate the napari-tutorial conda environment you created in the installation step.

conda activate napari-tutorial

To start the Jupyter Notebook application, enter

jupyter notebook

Jupyter Notebook will open in a browser window and you will see the following notebooks:

• part_0_viewer_intro.ipynb: in this activity, you will gain familiarity with loading and viewing images in napari.

• part_1_segmenting_and_measuring_nuclei.ipynb: in this notebook, you will use cellpose to segment nuclei and scikit-image to measure them.

• part_2_spot_detection_tutorial_beginner.ipynb: this is the spot detection notebook for people new to image processing with Python

• part_2_spot_detection_tutorial_advanced.ipynb: this is the spot detection notebook for people with experience performing image processing with Python

• part_2_spot_detection_tutorial_solution.ipynb: this is the solution to the spot detection activity.

All of the “part 2” notebooks cover the same activities, with different levels of engagement required to reach the solution. For your convenience, we have rendered the solutions to these notebooks in the following pages.