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Updated behav course prerequisites (#62)
* Updated behav course prerequisites * Apply suggestions from code review Co-authored-by: Chang Huan Lo <[email protected]> --------- Co-authored-by: Chang Huan Lo <[email protected]>
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@@ -24,12 +24,49 @@ This will cover how to run pose estimation at scale, using the GPUs of the SWC H | |
* [Sofía Miñano](https://github.com/sfmig) | ||
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## Prerequisites | ||
Make sure to follow the [steps outlined here](https://github.com/neuroinformatics-unit/course-behavioural-analysis#prerequisites) which will guide you through | ||
setting up your laptop, installing the required software, and downloading the sample data. | ||
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If you encounter issues with any of these steps please contact | ||
<a href="mailto:[email protected]?subject=SWC/GCNU Software Skills">Niko Sirmpilatze</a> | ||
in advance of the course. | ||
### Hardware Requirements | ||
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This is a hands-on course, so **please bring your own laptop and charger**. A mouse is recommended but not essential. A dedicated GPU is not required but will be helpful. | ||
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### General Software Requirements | ||
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:::{note} | ||
If you are an incoming PhD student attending the full [General Software Skills for Systems Neuroscience](general-software-skills) course and have already installed the general software requirements on Day 1, you may skip this section. | ||
::: | ||
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- An IDE for Python programming. We recommend one of the following: | ||
- [Visual Studio Code](https://code.visualstudio.com/) with the [Python extension](https://marketplace.visualstudio.com/items?itemName=ms-python.python) | ||
- [PyCharm](https://www.jetbrains.com/pycharm/) | ||
- [JupyterLab](https://jupyter.org/install) | ||
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- A working `conda` (or `mamba`) installation. If you don't have it, install via [Miniforge](https://github.com/conda-forge/miniforge). | ||
- A working [Git](https://git-scm.com/) installation. | ||
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### Specific Software Requirements | ||
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:::{note} | ||
Only proceed with this section after fulfilling the general software requirements above. | ||
::: | ||
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You will need to pre-install two different `conda` environments for the practical exercises. Create them as follows: | ||
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1. [**SLEAP**](https://sleap.ai/): Use the [conda package method](https://sleap.ai/installation.html#conda-package) from the SLEAP installation guide. You may use either `conda` or `mamba` in the installation command. An NVIDIA GPU is not required for this course as you will only use the SLEAP GUI (launched using `sleap-label`). | ||
2. [**Keypoint-MoSeq**](https://keypoint-moseq.readthedocs.io): Use the recommended [conda installation method](https://keypoint-moseq.readthedocs.io/en/latest/install.html#install-using-conda). | ||
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You should now have two new conda environments called `sleap` and `keypoint_moseq`. To view all your conda environments, run `conda env list`. | ||
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### Sample Data | ||
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Download the sample data for this course from [Dropbox](https://www.dropbox.com/scl/fo/ey7b6yrqax2olqyv1th7j/h?rlkey=u4wh2gxtbbn4g5o3s55zbx6pp&st=zolupk4i&dl=0). Click "Download" to get the `behav-analysis-course.zip` archive, then unzip it. | ||
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Alternatively, if you are connected to the SWC network and have access to the SWC's `ceph` filesystem, the dataset is available at `/ceph/scratch/neuroinformatics-dropoff/behav-analysis-course`. | ||
Ensure you copy the data to a convenient location on your laptop. | ||
The instructions to mount `ceph` on your laptop can be found on the [SWC wiki](https://wiki.ucl.ac.uk/display/SSC/Storage%3A+Ceph). | ||
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:::{note} | ||
If you encounter any issues with these steps, please contact [Niko Sirmpilatze](mailto:[email protected]?subject=SWC/GCNU%20Software%20Skills) in advance of the course. | ||
::: | ||
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## Materials | ||
- [GitHub repository](https://github.com/neuroinformatics-unit/course-behavioural-analysis) | ||
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