Wiki source code of 02. Installing PyNN

Version 24.1 by shailesh on 2021/10/08 10:11
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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 Brian 2 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 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 Brian 2 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 20.04 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 3.8.10 in this tutorial, as it is the default version provided with Ubuntu 20.04.
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63 **Note:**
64 Having multiple versions of Python on your system can produce issues while installing NEST. The method shown below will install NEST for the default version of Python provided by your Ubuntu OS. E.g. for Ubuntu 18.04 this might be Python 3.6.9 and for Ubuntu 20.04 it will likely be 3.8.10. If you wish to associate the NEST installation with a different Python version installed on your system, please refer the NEST installation instructions to do so on their website.
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69 **Screencast** - terminal
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72 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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74 We begin by creating a directory for our project.
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78 **Screencast** - terminal
79 \\(% style="color:#000000" %)cd ~~
80 mkdir pynn_project
81 cd pynn_project
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84 Next we shall create a virtual environment within this directory. Python 3 provides 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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88 **Note:**
89 For older versions of Python 3, you might require to manually install `python3-venv` package before being able to run the below command. To install, run:
90 \\sudo apt-get install python3-venv
91 \\More recent versions of Python 3 (e.g. v3.9) already have this pre-installed.
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96 **Screencast** - terminal
97 \\(% style="color:#000000" %)python3 -m venv pynn_env
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100 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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104 **Screencast** - file explorer
105 \\(% style="color:#000000" %)<< show directory contents; especially lib/python3.9/site-packages >>
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108 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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110 To enter into this virtual environment, and thereby use its resources in isolation from other projects on your computer, we require to "activate" it. This is achieved by running the command:
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114 **Screencast** - terminal
115 \\(% style="color:#000000" %)source pynn_env/bin/activate
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118 Notice how this changes the command prompt to show the name of your virtual environment. In our case, we had named it 'pynn_env', and this is now reflected as a prefix to the command prompt. This confirms that we are now in our new virtual environment.
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120 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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122 We start here with the installation of Brian 2. Brian 2 can be installed simply using the pip command.
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126 **Screencast** - terminal
127 \\(% style="color:#000000" %)pip install brian2
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130 This will install Brian 2, along with all its dependencies such as 'cython', 'numpy', etc. We can now go back into our virtual environment's 'site-packages' directory to see how it is now populated with all these packages.
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134 **Screencast** - file explorer
135 \\(% style="color:#000000" %)<< show directory contents lib/python3.9/site-packages >>
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138 To confirm that we have properly installed Brian 2 on our computer, we can test as follows:
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142 **Screencast** - terminal
143 \\(% style="color:#000000" %)python3
144 \\import brian2
145 \\exit()
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148 If there are no error messages here, and the import is successful, then we have completed installing Brian 2.
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150 We shall now move on to install the NEST simulator. Unlike Brian 2, NEST is not a Python package and therefore it cannot be installed via the 'pip' command.
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152 At the time of creating this tutorial, the lastest version of NEST is v3.1. This is currently supported by PyNN v0.10, and it is likely that other versions of NEST could potentially be incompatible with this version of PyNN. The installation is done by first adding the PPA repository for NEST and updating apt, followed by the installation of NEST itself.
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156 **Screencast** - terminal
157 \\(% style="color:#000000" %)sudo add-apt-repository ppa:nest-simulator/nest
158 sudo apt-get update
159 \\sudo apt-get install nest
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162 This installs the NEST module along with PyNEST, which is a Python interface for controlling the NEST kernel. This allows us to use NEST via Python. To confirm that we have properly installed Brian 2 on our computer, we can test as follows:
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166 **Screencast** - terminal
167 \\(% style="color:#000000" %)python3
168 \\import nest
169 \\exit()
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172 If there are no error messages here, and the import is successful, then we have completed installing NEST simulator.
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174 We next move on to the third simulation, NEURON. The installation for NEURON is a bit more involved.
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176 << add more >>
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180 **Slide** recap of learning objectives
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183 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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185 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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189 **Slide** acknowledgements, contact information
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193 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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196 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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200 [[https:~~/~~/realpython.com/python-virtual-environments-a-primer/>>https://realpython.com/python-virtual-environments-a-primer/]]
201 [[https:~~/~~/briansimulator.org/install/>>https://briansimulator.org/install/]]
202 [[https:~~/~~/nest-simulator.readthedocs.io/en/v3.1/installation/index.html>>https://nest-simulator.readthedocs.io/en/v3.1/installation/index.html]]