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49	49	**Slide** listing learning objectives
50	50	)))
51	51
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.
	52	+In this tutorial, we 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.
53	53
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55		-(((
56		-**Slide** listing prerequisites
57		-)))
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58	58
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.
	56	+=== State the learning objectives (In this tutorial, you will learn to do X…) ===
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63		-**Screencast** - terminal
64		-)))
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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.
	60	+=== State prerequisites ===
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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
76		-)))
	64	+=== Description, explanation, and practice ===
77	77
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
84		-)))
	68	+=== Summary (In this tutorial, you have learned to do X…) ===
85	85
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		-\\(% style="color:#000000" %)<< show directory contents; especially lib/python3.9/site-packages >>
92		-)))
	72	+=== Acknowledgements if appropriate ===
93	93
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		-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:
	76	+=== References to websites (For more information, visit us at…) ===
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100		-**Screencast** - terminal
101		-\\(% style="color:#000000" %)source pynn_env/bin/activate
102		-)))
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104		-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.
	80	+=== Contact information (For questions, contact us at…) ===
105	105
106		-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.
107		-
108		-We start here with the installation of Brian2. Brian2 can be installed simply using the pip command.
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112		-**Screencast** - terminal
113		-\\pip install brian2
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115		-
116		-This will install Brian2, 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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120		-**Screencast** - file explorer
121		-\\(% style="color:#000000" %)<< show directory contents lib/python3.9/site-packages >>
122		-)))
123		-
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125		-(((
126		-**Slide** recap of learning objectives
127		-)))
128		-
129		-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.
130		-
131		-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.
132		-
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135		-**Slide** acknowledgements, contact information
136		-)))
137		-
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139		-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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142		-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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146		-[[https:~~/~~/realpython.com/python-virtual-environments-a-primer/>>https://realpython.com/python-virtual-environments-a-primer/]]
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