datacarpentry · JeremyPike · Dec 18, 2023 · Jan 3, 2024 · Jan 3, 2024 · Jan 3, 2024
diff --git a/README.md b/README.md
@@ -12,6 +12,11 @@ This lesson introduces fundamental concepts in image handling and processing. Le
 The lesson assumes a working knowledge of Python and some previous exposure to the Bash shell.
 A detailed list of prerequisites can be found in [`learners/prereqs.md`](learners/prereqs.md).
 
+## Multidimensional Data Episode
+
+There is an extra episode covering analysis of multidimensional data (3D stacks and timelapses) including use of the [Napari](https://napari.org/stable/) image viewer. This additional episode is not part of the official [Carpentries Image Processing with Python lesson](https://datacarpentry.org/image-processing/). It was developed by [Jeremy Pike](https://www.birmingham.ac.uk/research/arc/rsg/staff/jeremy-pike.aspx) from the [Research Software Group](https://www.birmingham.ac.uk/research/arc/rsg/bear-software.aspx) and the
+[Institute for Interdisciplinary Data Science and AI](https://www.birmingham.ac.uk/research/data-science/index.aspx) at the University of Birmingham. 
+
 ## Contribution
 
 - Make a suggestion or correct an error by [raising an Issue](https://github.com/datacarpentry/image-processing/issues).

diff --git a/config.yaml b/config.yaml
@@ -58,7 +58,7 @@ contact: '[email protected]'
 # - another-learner.md
 
 # Order of episodes in your lesson
-episodes: 
+episodes:
 - 01-introduction.md
 - 02-image-basics.md
 - 03-skimage-images.md
@@ -68,15 +68,16 @@ episodes:
 - 07-thresholding.md
 - 08-connected-components.md
 - 09-challenges.md
+- 10-multidimensional-data.md
 
 # Information for Learners
-learners: 
+learners:
 
 # Information for Instructors
-instructors: 
+instructors:
 
 # Learner Profiles
-profiles: 
+profiles:
 
 # Customisation ---------------------------------------------
 #

diff --git a/episodes/10-multidimensional-data.md b/episodes/10-multidimensional-data.md
diff --git a/episodes/fig/cells-napari.png b/episodes/fig/cells-napari.png
diff --git a/episodes/fig/cells-seperate-napari.png b/episodes/fig/cells-seperate-napari.png
diff --git a/episodes/fig/cells-timelapse-mask-napari.png b/episodes/fig/cells-timelapse-mask-napari.png
diff --git a/episodes/fig/cells-timelapse-napari.png b/episodes/fig/cells-timelapse-napari.png
diff --git a/episodes/fig/cells-timelapse-tracking-napari.png b/episodes/fig/cells-timelapse-tracking-napari.png
diff --git a/episodes/fig/cells3d-blurred-napari.png b/episodes/fig/cells3d-blurred-napari.png
diff --git a/episodes/fig/cells3d-labels-napari.png b/episodes/fig/cells3d-labels-napari.png
diff --git a/episodes/fig/cells3d-napari.png b/episodes/fig/cells3d-napari.png
diff --git a/episodes/fig/cells3d-slice-napari.png b/episodes/fig/cells3d-slice-napari.png
diff --git a/episodes/fig/cells3d-volume-napari.png b/episodes/fig/cells3d-volume-napari.png
diff --git a/episodes/fig/cells_timelapse_area_plot.png b/episodes/fig/cells_timelapse_area_plot.png
diff --git a/episodes/fig/cells_timelapse_mean_plot.png b/episodes/fig/cells_timelapse_mean_plot.png
diff --git a/episodes/fig/cells_timelapse_tracking_plot.png b/episodes/fig/cells_timelapse_tracking_plot.png
diff --git a/episodes/fig/colonies-03-napari.png b/episodes/fig/colonies-03-napari.png
diff --git a/episodes/fig/colonies-napari.png b/episodes/fig/colonies-napari.png
diff --git a/episodes/fig/nuc-napari.png b/episodes/fig/nuc-napari.png
diff --git a/episodes/fig/shapes-napari.png b/episodes/fig/shapes-napari.png
diff --git a/learners/setup.md b/learners/setup.md
@@ -3,50 +3,43 @@
 permalink: /setup/
 ---
 
-Before joining the workshop or following the lesson, please complete the data and software setup described in this page.
+Before joining the workshop or following the lesson, please complete the data and software setup
+described in this page.
 
 ## Data
 
-The example images used in this lesson are available on [FigShare](https://figshare.com/).
-To download the data, please visit [the dataset page for this workshop][figshare-data]
-and click the "Download all" button.
-Unzip the downloaded file, and save the contents as a folder  called `data` somewhere you will easily find it again,
+The example images used in this lesson are available for University of Birmingham staff on SharePoint.
+Please follow this [link](https://bham.sharepoint.com/sites/AdvancedResearchComputing-Department/_layouts/15/guestaccess.aspx?share=Eh38JNN264JBv0krIXjdgBcB3bIYFedVU2jRR1hjIQM1pw&e=es0Hsf), 
+log on if required, and click "Download".
+Unzip the downloaded file, and save the contents as a folder called `data` somewhere you will easily
+find it again,
 e.g. your Desktop or a folder you have created for using in this workshop.
-(The name `data` is optional but recommended, as this is the name we will use to refer to the folder throughout the lesson.)
+(The name `data` is optional but recommended, as this is the name we will use to refer to the folder
+throughout the lesson.)
 
 ## Software
 
 1. Download and install the latest [Anaconda
    distribution](https://www.anaconda.com/download/) for your
    operating system. Make sure to choose the Python 3 version (as
-   opposed to the one with Python 2). If you wish to use an existing
-   installation, be sure to upgrade your scikit-image to at least 0.19.
-   You can upgrade to the latest scikit-image using the shell command that follows.
-
-   :::::::::::::::::::::::::::::::::::::::::  callout
-
-   ## Updating scikit-image in an existing Anaconda distribution
-
-   ```shell
-   conda upgrade -y scikit-image
-   ```
-
-   ::::::::::::::::::::::::::::::::::::::::::::::::::
-
-2. This lesson uses Matplotlib features to display images, and some
-   interactive features will be valuable. To enable the interactive
-   tools in JupyterLab, the `ipympl` package is required. The package
-   can be installed with the command
+   opposed to the one with Python 2).
+2. Set up a Conda environment for this Lesson and install the
+   necessary packages. Windows users will need to run these commands within a Anaconda Prompt.
 
    ```shell
-   conda install -c conda-forge ipympl
+   conda create -y -n image-env -c conda-forge python=3.9
+   conda activate image-env
+   conda install -c conda-forge scikit-image ipympl napari pyqt jupyterlab
    ```
 
    :::::::::::::::::::::::::::::::::::::::::  callout
 
    ## Enabling the `ipympl` backend in Jupyter notebooks
 
-   The `ipympl` backend can be enabled with the `%matplotlib` Jupyter
+   This lesson uses Matplotlib features to display images, and some
+   interactive features will be valuable. To enable the interactive
+   tools in JupyterLab, the `ipympl` package is required.The `ipympl` backend can be enabled with
+   the `%matplotlib` Jupyter
    magic. Put the following command in a cell in your notebooks
    (e.g., at the top) and execute the cell before any plotting commands.
 
@@ -65,7 +58,6 @@
    file](https://github.com/matplotlib/ipympl#readme) for the `ipympl`
    package.
 
-
    ::::::::::::::::::::::::::::::::::::::::::::::::::
 
 3. Open a Jupyter notebook:
@@ -74,47 +66,59 @@
 
    ## Instructions for Linux \& Mac
 
-   Open a terminal and type `jupyter lab`.
+   Open a terminal activate your environment and open Jupyter Lab:
 
+   ```shell
+   conda activate image-env
+   jupyter lab
+   ```
 
    :::::::::::::::::::::::::
 
    ::::::::::::::::  spoiler
 
    ## Instructions for Windows
 
-   Launch the Anaconda Prompt program and type `jupyter lab`.
-   (Running this command on the standard Command Prompt will return an error:
+   Launch the Anaconda Prompt program and run your commands within this.
+   (Running conda commands on the standard Command Prompt will return an error:
    `'conda' is not recognized as an internal or external command, operable program or batch file.`)
 
-
    :::::::::::::::::::::::::
 
-   After Jupyter Lab has launched, click the "Python 3" button under "Notebook" in the launcher window,
+   After Jupyter Lab has launched, click the "Python 3" button under "Notebook" in the launcher
+   window,
    or use the "File" menu, to open a new Python 3 notebook.
 
 4. To test your environment, run the following lines in a cell of the notebook:
 
-   ```python
-   import imageio.v3 as iio
-   import matplotlib.pyplot as plt
-   import skimage as ski
+    ```python
+    import imageio.v3 as iio
+    import matplotlib.pyplot as plt
+    import skimage as ski
+    import napari
 
-   %matplotlib widget
+    %matplotlib widget
 
-   # load an image
-   image = iio.imread(uri='data/colonies-01.tif')
+    # load an image
+    image = iio.imread(uri='data/colonies-01.tif')
 
-   # rotate it by 45 degrees
-   rotated = ski.transform.rotate(image=image, angle=45)
+    # rotate it by 45 degrees
+    rotated = ski.transform.rotate(image=image, angle=45)
 
-   # display the original image and its rotated version side by side
-   fig, ax = plt.subplots(1, 2)
-   ax[0].imshow(image)
-   ax[1].imshow(rotated)
-   ```
+    # display the original image and its rotated version side by side
+    fig, ax = plt.subplots(1, 2)
+    ax[0].imshow(image)
+    ax[1].imshow(rotated)
 
-   Upon execution of the cell, a figure with two images should be displayed in an interactive widget. When hovering over the images with the mouse pointer, the pixel coordinates and colour values are displayed below the image.
+    # open the image in Napari
+    viewer = napari.Viewer()
+    viewer.add_image(data=image, name="colonies_01", rgb=True)
+    ```
+
+   Upon execution of the cell, a figure with two images should be displayed in an interactive
+   widget. When hovering over the images with the mouse pointer, the pixel coordinates and colour
+   values are displayed below the image. It will also open a Napari Viewer and display an image
+   within it.
 
    ::::::::::::::::  spoiler
 
@@ -129,11 +133,10 @@
    you can run the cell by selecting "Run" -> "Run selected cell" in the top menu,
    or pressing <kbd>Shift</kbd>\+<kbd>Enter</kbd>.
 
-
    :::::::::::::::::::::::::
 
-5. A small number of exercises will require you to run commands in a terminal. Windows users should 
-use PowerShell for this. PowerShell is probably installed by default but if not you should
-[download and install](https://apps.microsoft.com/detail/9MZ1SNWT0N5D?hl=en-eg&gl=EG) it.
+5. A small number of exercises will require you to run commands in a terminal. Windows users should
+   use PowerShell for this. PowerShell is probably installed by default but if not you
+   should [download and install](https://apps.microsoft.com/detail/9MZ1SNWT0N5D?hl=en-eg&gl=EG) it.
 
 [figshare-data]: https://figshare.com/articles/dataset/Data_Carpentry_Image_Processing_Data_beta_/19260677