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56	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. On my system
	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.
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63		-**Screencast** - blank document in editor
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	61	+=== Description, explanation, and practice ===
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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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71		-\\(% style="color:#000000" %)"""install and setup new virtualenv project"""(%%)
72		-\\(% style="color:#000000" %)sudo pip install virtualenv
73		-\\"""if already installed, ensure we have latest package by upgrading"""
74		-\\pip install ~-~-upgrade virtualenv
75		-\\"""create a directory for project"""
76		-\\cd ~~
77		-mkdir pynn_project
78		-cd pynn_project
79		-\\"""create a virtual environment for this project"""
80		-python -m venv pynn_env
81		-\\ls
82		-<< show created directory >>
83		-)))
	65	+=== Summary (In this tutorial, you have learned to do X…) ===
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85		-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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87		-We start here with the installation of Brian2.
	69	+=== Acknowledgements if appropriate ===
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	73	+=== References to websites (For more information, visit us at…) ===
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98		-**Slide** recap of learning objectives
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	77	+=== Contact information (For questions, contact us at…) ===
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	83	+~(~(~(
	84	+~*~*Slide~*~* recap of learning objectives
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101	101	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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103	103	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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106		-(((
107		-**Slide** acknowledgements, contact information
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	96	+~*~*Slide~*~* acknowledgements, contact information
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111	111	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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114	114	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.