Last modified by shailesh on 2021/10/20 09:58
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shailesh 41.1 3 **Under development! Awaiting EBRAINS JupyterLab SPACK implementation.**
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adavison 5.1 5
adavison 4.1 6 == Learning objectives ==
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annedevismes 39.1 8 In this tutorial, you will learn how to install PyNN, together with the  Brian 2, NEST, and NEURON simulators, in EBRAINS Jupyter Lab.
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12 Note: There will be a separate tutorial for each environment.
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adavison 4.1 15 == Audience ==
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adavison 5.1 17 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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19 == Prerequisites ==
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shailesh 30.1 21 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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23 == Format ==
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shailesh 31.1 25 These tutorials will be screencasts, in which the presenter runs commands in a Jupyer notebook, and the viewer is expected to follow along. The intended duration is 10-15 minutes.
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27 == Script ==
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31 **Slide** showing tutorial title, PyNN logo, link to PyNN service page.
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34 Hello, my name is X.
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shailesh 12.1 36 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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shailesh 12.1 38 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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42 **Slide** listing learning objectives
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annedevismes 38.1 45 In this tutorial, I will guide you through setting up PyNN, together with the Brian 2, NEST, and NEURON simulators, in the EBRAINS Collaboratory's JupyterLab. Note that we have a dedicated version of this tutorial for other environments, such as Linux, Mac OS, and Windows.
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49 **Slide** listing prerequisites
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shailesh 32.3 52 To follow this tutorial, you will need an EBRAINS account. Interested users with a current affiliation to an academic institution can directly create an account at [[https:~~/~~/ebrains.eu/register/>>https://ebrains.eu/register/]]. Users without such an affiliation may submit a request for an account.
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annedevismes 38.1 54 EBRAINS JupyterLab only supports Python3, with the current default version being Python 3.6.9. This tutorial presents the steps for such an environment, but changes required to the steps below following upgrades to more recent versions of Python are expected to be minimal.
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shailesh 21.8 58 **Screencast** - terminal
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annedevismes 38.1 61 In this tutorial, we will make use of virtual environments. 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, thereby preventing unrequested changes in others, when any one of them is updated.
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shailesh 21.8 63 We begin by creating a directory for our project.
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shailesh 21.8 67 **Screencast** - terminal
68 \\(% style="color:#000000" %)cd ~~
shailesh 21.5 69 mkdir pynn_project
70 cd pynn_project
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annedevismes 38.1 73 Next, we will create a virtual environment within this directory. Python 3 provides support for creating virtual environments. Since Python 3.6, the recommended method for creating a new virtual environment is as follows:
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annedevismes 38.1 77 **Note**
78 For older versions of Python 3, you be might required to manually install `python3-venv` package before being able to run the below command. To install, run:
shailesh 22.8 79 \\sudo apt-get install python3-venv
80 \\More recent versions of Python 3 (e.g. v3.9) already have this pre-installed.
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85 **Screencast** - terminal
shailesh 22.14 86 \\(% style="color:#000000" %)python3 -m venv pynn_env
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annedevismes 38.1 91 **Note**
92 \\Note that this command is 'python3' and not simply 'python'. This is because Ubuntu 20, by default, understands only the former. You can find on the Internet various ways to have 'python' also refer to 'python3', but for the purposes of this tutorial, we keep things simple and try to work with the bare minimum changes to the system.
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annedevismes 38.1 95 This will create a sub-directory named 'pynn_env' within our project directory, with several files and sub-directories. Let's take a look at the 'site-packages' directory.
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99 **Screencast** - file explorer
shailesh 21.11 100 \\(% style="color:#000000" %)<< show directory contents; especially lib/python3.9/site-packages >>
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annedevismes 38.1 103 As you see here, only a limited number of basic packages have currently been installed in this virtual environment. In the steps ahead, we will install various other packages, which you will be able to see here.
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annedevismes 38.1 105 To enter 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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109 **Screencast** - terminal
110 \\(% style="color:#000000" %)source pynn_env/bin/activate
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annedevismes 38.1 113 Notice how this changes the command prompt to show the name of your virtual environment. In our case, we 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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annedevismes 38.1 117 **Note**
118 \\You might be required to run the above command every time you open a new terminal window. Check that the terminal command prompt indicates the name of your virtual environment to confirm that you have indeed activated it.
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annedevismes 38.1 121 Now that we have our project's virtual environment setup, we are 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. In this tutorial, we will adopt this approach and begin by installing the simulators. For the purposes of this tutorial, we will demonstrate the installation of Brian2, NEURON, and NEST simulators.
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125 **Note:**
126 \\If you have previously already installed NEURON or NEST on your system and are installing PyNN now, then you would require to compile NEURON's NMODL fles and NEST's extensions manually. For more instructions on this, take a look at:
127 [[(% style="color:#000000" %)http:~~/~~/neuralensemble.org/docs/PyNN/installation.html>>http://neuralensemble.org/docs/PyNN/installation.html]]
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annedevismes 38.1 130 We start here with the installation of Brian 2. Brian 2 can be installed simply by using the pip command.
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shailesh 21.10 134 **Screencast** - terminal
shailesh 22.4 135 \\(% style="color:#000000" %)pip install brian2
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annedevismes 38.1 138 This will install Brian 2, along with all its dependencies such as 'cython', 'numpy', and so on. We can now go back to our virtual environment's 'site-packages' directory to see how it is populated with all these packages.
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142 **Screencast** - file explorer
143 \\(% style="color:#000000" %)<< show directory contents lib/python3.9/site-packages >>
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shailesh 22.17 146 To confirm that we have properly installed Brian 2 on our computer, we can test as follows:
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shailesh 22.4 150 **Screencast** - terminal
shailesh 27.10 151 \\(% style="color:#000000" %)python
shailesh 22.4 152 \\import brian2
shailesh 22.7 153 \\exit()
shailesh 22.4 154 )))
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annedevismes 38.1 158 **Note:**
159 \\You might remember that, earlier in this tutorial, we had to use the term 'python3' to run Python on our system. But here, as in the rest of this tutorial, we will simply write 'python'. This is possible because once we have activated our virtual environment, this environment understands that both 'python' and 'python3' are equivalent.
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annedevismes 38.1 162 If there are no error messages here, and the import is successful, we have completed installing Brian 2.
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annedevismes 38.1 164 We will 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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annedevismes 38.1 166 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 are potentially 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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170 **Screencast** - terminal
171 \\(% style="color:#000000" %)sudo add-apt-repository ppa:nest-simulator/nest
172 sudo apt-get update
173 \\sudo apt-get install nest
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shailesh 27.3 176 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 NEST on our computer, we can test as follows:
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shailesh 22.21 180 **Screencast** - terminal
shailesh 27.2 181 \\(% style="color:#000000" %)nest
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annedevismes 38.1 184 This will display the NEST banner, which mentions the version amongst other info. Here, as we can see, we have now installed NEST v3.1 on our system. Next, let's next verify that this is indeed accessible via Python.
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188 **Screencast** - terminal
shailesh 27.10 189 \\(% style="color:#000000" %)python
shailesh 22.21 190 \\import nest
191 \\exit()
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annedevismes 38.1 196 **Note**
197 \\I find that I receive a "no module named nest" error, when trying this right after installing NEST. But it succeeds after a restart. So, if you do observe an error, close all programs, restart your computer, and try again. This time, it should execute as expected.
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annedevismes 38.1 200 If there are no error messages here, and the import is successful, we have completed installing NEST simulator and are able to load it via Python.
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annedevismes 38.1 202 We next move on to the third simulator, NEURON. The installation for NEURON used to be more complex but can now be easily completed by using the 'pip' command:
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206 **Screencast** - terminal
207 \\(% style="color:#000000" %)pip install neuron
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shailesh 27.8 210 This installs the NEURON simulator on your system. To confirm that we have properly installed NEURON, we can test as follows:
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214 **Screencast** - terminal
215 \\(% style="color:#000000" %)nrngui
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annedevismes 38.1 218 This will display the NEURON banner, which mentions the version amongst other info. Here, as we can see, we have now installed NEURON v8.0.0 on our system. Next, let's verify that this is indeed accessible via Python.
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222 **Screencast** - terminal
shailesh 27.10 223 \\(% style="color:#000000" %)python
shailesh 27.8 224 \\from neuron import h
225 \\exit()
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annedevismes 38.1 228 If there are no error messages here, and the import is successful, we have completed installing NEURON simulator, and are able to load it via Python.
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annedevismes 38.1 230 Now that we have installed all the simulators we intend to use, we move on to installing PyNN itself. Because PyNN is a Python package, we can install it easily by using the 'pip' command:
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234 **Screencast** - terminal
shailesh 27.20 235 \\(% style="color:#000000" %)pip install pyNN
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annedevismes 38.1 240 **Note**
shailesh 35.1 241 \\Note that PyNN project is spelt with a captial P, small y, and two captital N. But the Python module, as seen here, is spelt starting with a small P. This is in line with general Python convention, where package names start with small alphabets.
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shailesh 27.18 244 To verify that PyNN has been successfully installed on our system, and that it is indeed able to communicate with the other simulators that we installed earlier, we can try running:
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248 **Screencast** - terminal
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shailesh 27.20 250 (% style="color:#000000" %)python
251 \\import pyNN.brian2 as sim
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253 (% style="color:#000000" %)sim.setup()
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255 (% style="color:#000000" %)sim.end()
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annedevismes 39.1 258 This confirms that PyNN has been properly setup, and also that is able to employ Brian 2. To verify that PyNN is also able to communicate with NEST and NEURON simulators, we can do the following:
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262 **Screencast** - terminal
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264 (% style="color:#000000" %)python
265 \\import pyNN.nest as sim
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267 (% style="color:#000000" %)sim.setup()
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269 (% style="color:#000000" %)sim.end()
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273 (% style="color:#000000" %)import pyNN.neuron as sim
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275 (% style="color:#000000" %)sim.setup()
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annedevismes 38.1 280 This confirms that all the required software packages have been successfully completed and are functioning as expected.
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284 **Slide** recap of learning objectives
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adavison 5.1 286
annedevismes 38.1 287 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, take a look at our next tutorial. Also, we will be releasing a series of tutorials, throughout the rest of 2021 and 2022, to introduce more advanced features of PyNN, so keep an eye on the EBRAINS website.
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shailesh 27.12 291 **Slide** useful links
292 \\[[(% style="color:#000000" %)https:~~/~~/realpython.com/python-virtual-environments-a-primer/>>https://realpython.com/python-virtual-environments-a-primer/]](%%)
293 [[(% style="color:#000000" %)https:~~/~~/briansimulator.org/install/>>https://briansimulator.org/install/]](%%)
shailesh 27.13 294 [[(% style="color:#000000" %)https:~~/~~/nest-simulator.readthedocs.io/en/v3.1/installation/index.html>>https://nest-simulator.readthedocs.io/en/v3.1/installation/index.html]](%%)
shailesh 27.14 295 [[(% style="color:#000000" %)https:~~/~~/neuron.yale.edu/neuron/>>https://neuron.yale.edu/neuron/]]
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shailesh 27.16 298 We have listed here some links that might be of interest to users who wish to find more details about the various softwares employed in this tutorial.
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shailesh 21.1 302 **Slide** acknowledgements, contact information
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annedevismes 38.1 306 PyNN has been developed by many different people, with financial support from several 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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annedevismes 38.1 309 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.