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11 changes: 11 additions & 0 deletions episodes/files/environment.yml
Original file line number Diff line number Diff line change
@@ -0,0 +1,11 @@
name: dc-image
channels:
- conda-forge
dependencies:
- python>=3.11
- jupyterlab
- numpy
- matplotlib
- scikit-image
- ipympl
- imageio
37 changes: 14 additions & 23 deletions learners/setup.md
Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@ Before joining the workshop or following the lesson, please complete the data an

## Data

The example images used in this lesson are available on [FigShare](https://figshare.com/).
The example images and a description of the Python environment 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,
Expand All @@ -16,30 +16,21 @@ e.g. your Desktop or a folder you have created for using in this workshop.

## 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.
1. Download and install the latest [MiniForge distribution of Python](https://conda-forge.org/download/) for your operating system.
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I'm not sure it's obvious that, on Unix-like platforms, you need to run

bash Miniforge3-$(uname)-$(uname -m).sh

from the terminal to install Miniforge... I would add a line about this. Is it obvious on Windows? I guess so, if you need to double-click what you just downloaded.

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Yes - on Windows it's an .exe file, so you just double-click the downloaded file.

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I added a link to the central instructions, which are more detailed, in 9c8345e.

If you already have a Python 3 setup that you are happy with, you can continue to use that (we recommend that you make sure your Python version is current).
The next step assumes that `conda` is available to manage your Python environment.
2. Setup an environment to work in during the lesson.
In a terminal (Linux/Mac) or the MiniForge Prompt application (Windows), navigate to the location where you saved the unzipped data for the lesson and run the following command:

::::::::::::::::::::::::::::::::::::::::: callout

## Updating scikit-image in an existing Anaconda distribution

```shell
conda upgrade -y scikit-image
```bash
conda env create -f environment.yml
```

::::::::::::::::::::::::::::::::::::::::::::::::::

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
If prompted, allow `conda` to install the required libraries.
3. Activate the new environment you just created:

```shell
conda install -c conda-forge ipympl
```bash
conda activate dc-image
```

::::::::::::::::::::::::::::::::::::::::: callout
Expand Down Expand Up @@ -83,9 +74,9 @@ e.g. your Desktop or a folder you have created for using in this workshop.

## Instructions for Windows

Launch the Anaconda Prompt program and type `jupyter lab`.
Launch the MiniForge Prompt program and type `jupyter lab`.
(Running this command on the standard Command Prompt will return an error:
`'conda' is not recognized as an internal or external command, operable program or batch file.`)
`'jupyter' is not recognized as an internal or external command, operable program or batch file.`)


:::::::::::::::::::::::::
Expand Down