Wiki source code of 02. Installing PyNN

Version 21.9 by shailesh on 2021/10/06 14:11
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3 tutorials under development for Linux, Mac OS, Windows, Jupyter Lab.
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7 == Learning objectives ==
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9 In this tutorial, you will learn how to install PyNN, together with the NEST, NEURON and Brian2 simulators, on Linux / Mac OS / Windows / in EBRAINS Jupyter Lab.
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13 Note: There will be a separate tutorial for each environment.
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16 == Audience ==
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18 This tutorial is intended for people with at least a basic knowledge of neuroscience (high school level or above) and basic familiarity with the Python programming language. It should also be helpful for people who already have advanced knowledge of neuroscience and neural simulation, who simply wish to learn how to use PyNN, and how it differs from other simulation tools they know.
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20 == Prerequisites ==
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22 To follow this tutorial, you will need a computer with [Linux/Mac OS/Windows] and a good network connection. You will need to know how to open the terminal application for your operating system.
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28 To follow this tutorial, you will need an EBRAINS account. You should know how to create and use Jupyter notebooks in the EBRAINS Jupyter Lab.
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30 == Format ==
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32 These tutorials will be screencasts, in which the presenter runs commands in a terminal (or in a Jupyer notebook), and the viewer is expected to follow along. The intended duration is 10 minutes. For the Jupyter version of the tutorial, the final notebook will also be made available.
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34 == Script ==
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38 **Slide** showing tutorial title, PyNN logo, link to PyNN service page.
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41 Hello, my name is X.
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43 This video is one of a series of tutorials for PyNN, which is Python software for modelling and simulating spiking neural networks.
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45 For a list of the other tutorials in this series, you can visit ebrains.eu/service/pynn, that's p-y-n-n.
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49 **Slide** listing learning objectives
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52 In this tutorial, I will guide you through setting up PyNN, together with the NEST, NEURON and Brian2 simulators, in a Linux  environment. Note that we have a dedicated version of this tutorial for other environments, such as Mac OS, Windows and EBRAINS Jupyter Lab.
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56 **Slide** listing prerequisites
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59 I shall be demonstrating the installation on a computer with Ubuntu 18.04 OS installed. The steps are likely to remain very similar for other versions of Ubuntu OS, and also not expected to vary significantly for other Linux distributions. In the latter case, you will find on the Internet about how to carry out the equivalent of the tasks demonstrated here using Ubuntu OS. Also, the tutorial will focus only on Python 3, as Python 2 has now been deprecated. It is recommended to use Python version 3.6 or higher. I would be using Python 3.9.7 in this tutorial.
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63 **Screencast** - terminal
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66 We shall make use of virtual environments in this tutorial. This allows multiple Python projects to coexist on the same computer, even when they might have different, and even conflicting, requirements. It helps isolate projects and thereby preventing unrequested changes in others, when any one of them is updated.
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68 We begin by creating a directory for our project.
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72 **Screencast** - terminal
73 \\(% style="color:#000000" %)cd ~~
74 mkdir pynn_project
75 cd pynn_project
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78 Next we shall create a virtual environment within this directory. Python 3 provides intrinsic support for creating virtual environments. Since Python 3.6, the recommended method of creating a new virtual environment is as follows:
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82 **Screencast** - terminal
83 \\(% style="color:#000000" %)python -m venv pynn_env
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86 This will create a sub-directory named 'pynn_env' within our project directory, with several files and sub-directories. Let us take a look at the 'site-packages' directory.
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90 **Screencast** - file explorer
91 \\<< show directory contents; especially lib/python3.9/site-packages >>
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94 As you see here, only a limited number of basic packages have currently been installed in this virtual environment. In the steps ahead, we shall install various other packages, and you shall see that these would be reflected here.
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96 Now that we have our project's virtual environment setup, we are now ready to install PyNN and other simulators. In general, it is advisable to install the various simulators (especially NEURON and NEST) prior to installing PyNN, because PyNN will then auto compile NEURON's NMODL fles and NEST's extensions during installation. Alternatively, this would need to be done manually as described on the PyNN website. In this tutorial, we will adopt the easier approach and begin by installing the simulators. For the purposes of this tutorial, we shall demonstrate the installation of Brian2, NEURON and NEST simulators.
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98 We start here with the installation of Brian2.
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102 **Screencast** - current state of editor
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109 **Slide** recap of learning objectives
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112 That is the end of this tutorial, in which I've demonstrated how to install PyNN, and other required simulators, in a Linux system. You are now ready to start modeling! To learn about model development in PyNN, do take a look at our next tutorial.
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114 Als,  we will be releasing a series of tutorials, throughout the rest of 2021 and 2022, to introduce these more advanced features of PyNN, so keep an eye on the EBRAINS website.
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118 **Slide** acknowledgements, contact information
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122 PyNN has been developed by many different people, with financial support from several different organisations. I'd like to mention in particular the CNRS and the European Commission, through the FACETS, BrainScaleS and Human Brain Project grants.
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125 For more information visit neuralensemble.org/PyNN. If you have questions you can contact us through the PyNN Github project, the NeuralEnsemble forum, EBRAINS support, or the EBRAINS Community.
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129 [[https:~~/~~/realpython.com/python-virtual-environments-a-primer/>>https://realpython.com/python-virtual-environments-a-primer/]]