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44	44	**Slide** listing prerequisites
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46	46
47		-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 are 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, because Python 2 has now been deprecated. It is recommended to use Python version 3.6 or higher. I will be using Python 3.8.10 in this tutorial, because it is the default version provided with Ubuntu 20.04.
	47	+I will demonstrate 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 are also not expected to vary significantly for other Linux distributions. In the latter case, you can find information on the Internet about how to carry out the equivalent of the tasks demonstrated here using Ubuntu OS. Also, this tutorial focuses only on Python 3, because Python 2 has now been deprecated. It is recommended to use Python version 3.6 or higher. I will be using Python 3.8.10 in this tutorial, because it is the default version provided with Ubuntu 20.04.
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57	57	**Screencast** - terminal
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59	59
60		-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	+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.
61	61
62		-We begin by creating a directory for our project.
	62	+Let's begin by creating a directory for our project.
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69	69	cd pynn_project
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72		-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.
	72	+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 to create a new virtual environment is as follows.
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92	92	**Note**
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94	94
95		-Observe 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 shall keep things simple and try to work with the bare minimum changes to the system.
	95	+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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98		-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.
	98	+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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103	103	\\(% style="color:#000000" %)<< show directory contents; especially lib/python3.8/site-packages >>
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105	105
106		-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 will be reflected here.
	106	+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.
107	107
108		-To enter into this virtual environment, and thereby use its resources in isolation from other projects on your computer, we have to "activate" it. This is achieved by running the command:
	108	+To enter this virtual environment, and thereby use its resources in isolation from other projects on your computer, we have to "activate" it. This is achieved by running the command:
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120	120	**Note**
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123		-You might be required to run the above command every time you open a new terminal window. Do verify that the terminal command prompt indicates the name of your virtual environment to confirm that you have indeed activated it.
	123	+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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125	125
126		-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. In this tutorial, we will adopt this approach and begin by installing the simulators. For the purposes of this tutorial, we shall demonstrate the installation of Brian2, NEURON and NEST simulators.
	126	+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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140	140	\\(% style="color:#000000" %)pip install brian2
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142	142
143		-This will install Brian 2, along with all its dependencies such as 'cython', 'numpy', and so on. We can now go back into our virtual environment's 'site-packages' directory to see how it is now populated with all these packages.
	143	+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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163		-**Note:**
164		-\\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 shall simply write 'python'. This is possible because, once we have activated our virtual environment, this environment understands that both 'python' and 'python3' are equivalent.
	163	+**Note**
	164	+\\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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167	167	If there are no error messages here, and the import is successful, we have completed the installation of Brian 2.
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169		-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.
	169	+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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171		-At the time of creating this tutorial, the latest 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 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.
	171	+At the time of creating this tutorial, the latest version of NEST is v3.1. This is currently supported by PyNN v0.10, and it is likely that other versions of NEST will 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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201	201	**Note**
202		-\\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.
	202	+\\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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205	205	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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212	212	\\(% style="color:#000000" %)pip install neuron
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215		-This installs the NEURON simulator on your system. To confirm that we have properly installed NEURON, we can test as follows:
	215	+This installs the NEURON simulator on our system. To confirm that we have properly installed NEURON, we can test as follows:
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221	221	\\quit()
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224		-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. Let us next verify that this is indeed accessible via Python.
	224	+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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234	234	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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236		-Now that we have installed all the simulators we intend to use, we move on to installing PyNN itself. As PyNN is a Python package, we can install it easily using the 'pip' command:
	236	+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 using the 'pip' command:
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246	246	**Note**
247		-\\Note that PyNN project is spelt with a captial P, small y, and two captital N. The pip command is case-insensitive, so you may write it differently here. But the Python module, as we shall see later, is case-sensitive and is spelt starting with a small P. This is in line with general Python convention, whereby package names start with small letters. Thus, while importing PyNN module via Python, it needs to be written as 'pyNN'.
	247	+\\Note that PyNN project is spelt with a captial P, small y, and two captital N. The pip command is case-insensitive, so you may write it differently here. But the Python module, as we will see later, is case-sensitive and is spelt starting with a small P. This is in line with general Python convention, whereby package names start with small letters. Thus, while importing PyNN module via Python, it needs to be written as 'pyNN'.
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250	250	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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261	261	(% style="color:#000000" %)sim.end()
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264		-This confirms that PyNN has been properly setup and also that is able to employ Brian 2. To verify similary that PyNN is also able to communicate with NEURON and NEST simulators, we can do the following:
	264	+This confirms that PyNN has been properly setup and also that it is able to employ Brian 2. To verify that PyNN is also able to communicate with NEURON and NEST simulators, we can do the following:
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290	290	**Slide** recap of learning objectives
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293		-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. 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.
	293	+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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