Wiki source code of 02. Installing PyNN - Linux

Version 46.1 by shailesh on 2021/12/09 11:00

version	line-number	content
4.1	1	== Learning objectives ==
	2
44.1	3	In this tutorial, you will learn how to install PyNN, together with the Brian 2, NEST and NEURON simulators, on Linux.
4.1	4
6.1	5	(% class="box infomessage" %)
	6	(((
	7	Note: There will be a separate tutorial for each environment.
	8	)))
	9
4.1	10	== Audience ==
	11
38.1	12	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.
4.1	13
	14	== Prerequisites ==
	15
24.1	16	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.
4.1	17
	18	== Format ==
	19
27.1	20	These tutorials will be screencasts, in which the presenter runs commands in a terminal, and the viewer is expected to follow along. The intended duration is 10-15 minutes.
4.1	21
	22	== Script ==
5.1	23
11.1	24	(% class="box successmessage" %)
	25	(((
	26	Slide showing tutorial title, PyNN logo, link to PyNN service page.
	27	)))
	28
	29	Hello, my name is X.
	30
12.1	31	This video is one of a series of tutorials for PyNN, which is Python software for modelling and simulating spiking neural networks.
5.1	32
12.1	33	For a list of the other tutorials in this series, you can visit ebrains.eu/service/pynn, that's p-y-n-n.
	34
	35	(% class="box successmessage" %)
	36	(((
	37	Slide listing learning objectives
	38	)))
	39
46.1	40	In this tutorial, I will guide you through setting up PyNN, together with the Brian 2, NEST, and NEURON simulators, on 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.
12.1	41
18.1	42	(% class="box successmessage" %)
	43	(((
	44	Slide listing prerequisites
	45	)))
5.1	46
40.1	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.
18.1	48
22.18	49	(% class="box errormessage" %)
	50	(((
38.1	51	Note
	52	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. For example, 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 to the NEST installation instructions to do so on their website.
22.18	53	)))
	54
21.4	55	(% class="box infomessage" %)
	56	(((
21.8	57	Screencast - terminal
21.4	58	)))
	59
40.1	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.
5.1	61
40.1	62	Let's begin by creating a directory for our project.
21.8	63
21.4	64	(% class="box infomessage" %)
21.2	65	(((
21.8	66	Screencast - terminal
	67	\\(% style="color:#000000" %)cd ~~
21.5	68	mkdir pynn_project
	69	cd pynn_project
21.2	70	)))
5.1	71
41.1	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 for creating a new virtual environment is as follows.
21.8	73
22.8	74	(% class="box errormessage" %)
	75	(((
38.1	76	Note
	77
	78
	79	For older versions of Python 3, you might be required to manually install `python3-venv` package before being able to run the below command. To install, run:
22.8	80	\\sudo apt-get install python3-venv
38.1	81	\\More recent versions of Python 3 (e.g., v3.9) already have this pre-installed.
22.8	82	)))
	83
21.8	84	(% class="box infomessage" %)
	85	(((
	86	Screencast - terminal
22.14	87	\\(% style="color:#000000" %)python3 -m venv pynn_env
21.8	88	)))
	89
27.10	90	(% class="box warningmessage" %)
	91	(((
38.1	92	Note
	93
	94
40.1	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.
27.10	96	)))
	97
40.1	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.
21.8	99
	100	(% class="box infomessage" %)
	101	(((
	102	Screencast - file explorer
37.1	103	\\(% style="color:#000000" %)<< show directory contents; especially lib/python3.8/site-packages >>
21.8	104	)))
	105
40.1	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.
21.8	107
40.1	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:
21.11	109
	110	(% class="box infomessage" %)
	111	(((
	112	Screencast - terminal
	113	\\(% style="color:#000000" %)source pynn_env/bin/activate
	114	)))
	115
38.1	116	Notice how this changes the command prompt to show the name of your virtual environment. In our case, we have 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.
22.1	117
27.4	118	(% class="box warningmessage" %)
	119	(((
38.1	120	Note
	121
	122
40.1	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.
27.4	124	)))
	125
42.1	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, NEST, and NEURON simulators.
21.2	127
27.18	128	(% class="box errormessage" %)
	129	(((
	130	Note:
38.1	131	\\If you have previously installed NEURON or NEST on your system and are installing PyNN now, you will have to compile NEURON's NMODL fles and NEST's extensions manually. For more instructions on this, take a look at:
27.18	132	[[(% style="color:#000000" %)http:~~/~~/neuralensemble.org/docs/PyNN/installation.html>>http://neuralensemble.org/docs/PyNN/installation.html]]
	133	)))
	134
38.1	135	We start here with the installation of Brian 2. Brian 2 can be installed simply by using the pip command.
21.4	136
21.7	137	(% class="box infomessage" %)
	138	(((
21.10	139	Screencast - terminal
22.4	140	\\(% style="color:#000000" %)pip install brian2
21.7	141	)))
	142
40.1	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.
21.7	144
22.6	145	(% class="box infomessage" %)
	146	(((
	147	Screencast - file explorer
37.1	148	\\(% style="color:#000000" %)<< show directory contents lib/python3.8/site-packages >>
22.6	149	)))
	150
22.17	151	To confirm that we have properly installed Brian 2 on our computer, we can test as follows:
22.4	152
22.2	153	(% class="box infomessage" %)
	154	(((
22.4	155	Screencast - terminal
27.10	156	\\(% style="color:#000000" %)python
22.4	157	\\import brian2
22.7	158	\\exit()
22.4	159	)))
	160
27.10	161	(% class="box warningmessage" %)
	162	(((
40.1	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.
27.10	165	)))
	166
38.1	167	If there are no error messages here, and the import is successful, we have completed the installation of Brian 2.
22.5	168
40.1	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.
22.7	170
43.1	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 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.
22.7	172
	173	(% class="box infomessage" %)
	174	(((
	175	Screencast - terminal
	176	\\(% style="color:#000000" %)sudo add-apt-repository ppa:nest-simulator/nest
	177	sudo apt-get update
	178	\\sudo apt-get install nest
	179	)))
	180
27.3	181	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:
22.7	182
22.20	183	(% class="box infomessage" %)
	184	(((
22.21	185	Screencast - terminal
27.2	186	\\(% style="color:#000000" %)nest
45.1	187
	188	(% style="color:#000000" %)exit
27.2	189	)))
	190
43.1	191	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 verify that this is indeed accessible via Python.
27.2	192
	193	(% class="box infomessage" %)
	194	(((
	195	Screencast - terminal
27.10	196	\\(% style="color:#000000" %)python
22.21	197	\\import nest
	198	\\exit()
22.20	199	)))
	200
27.5	201	(% class="box warningmessage" %)
	202	(((
38.1	203	Note
40.1	204	\\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.
27.5	205	)))
	206
38.1	207	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.
22.20	208
38.1	209	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.
22.20	210
27.8	211	(% class="box infomessage" %)
	212	(((
	213	Screencast - terminal
	214	\\(% style="color:#000000" %)pip install neuron
	215	)))
22.20	216
40.1	217	This installs the NEURON simulator on our system. To confirm that we have properly installed NEURON, we can test as follows:
27.8	218
	219	(% class="box infomessage" %)
	220	(((
	221	Screencast - terminal
37.2	222	\\(% style="color:#000000" %)nrniv
37.3	223	\\quit()
27.8	224	)))
	225
40.1	226	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.
27.8	227
	228	(% class="box infomessage" %)
	229	(((
	230	Screencast - terminal
27.10	231	\\(% style="color:#000000" %)python
27.8	232	\\from neuron import h
	233	\\exit()
	234	)))
	235
38.1	236	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.
27.8	237
40.1	238	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:
27.8	239
27.18	240	(% class="box infomessage" %)
	241	(((
	242	Screencast - terminal
35.1	243	\\(% style="color:#000000" %)pip install PyNN
27.18	244	)))
	245
32.2	246	(% class="box warningmessage" %)
	247	(((
38.1	248	Note
40.1	249	\\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'.
32.2	250	)))
	251
38.1	252	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:
27.18	253
27.20	254	(% class="box infomessage" %)
	255	(((
	256	Screencast - terminal
27.18	257
27.20	258	(% style="color:#000000" %)python
	259	\\import pyNN.brian2 as sim
	260
	261	(% style="color:#000000" %)sim.setup()
	262
	263	(% style="color:#000000" %)sim.end()
	264	)))
	265
44.1	266	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 NEST and NEURON simulators, we can do the following:
27.20	267
	268	(% class="box infomessage" %)
	269	(((
	270	Screencast - terminal
	271
	272	(% style="color:#000000" %)python
	273	\\import pyNN.nest as sim
	274
	275	(% style="color:#000000" %)sim.setup()
	276
	277	(% style="color:#000000" %)sim.end()
	278
	279
	280
	281	(% style="color:#000000" %)import pyNN.neuron as sim
	282
	283	(% style="color:#000000" %)sim.setup()
	284
	285	(% style="color:#000000" %)sim.end()
	286	)))
	287
38.1	288	This confirms that all the required software packages have been successfully completed and are functioning as expected.
27.20	289
21.1	290	(% class="box successmessage" %)
	291	(((
	292	Slide recap of learning objectives
	293	)))
5.1	294
40.1	295	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.
20.1	296
21.1	297	(% class="box successmessage" %)
	298	(((
27.12	299	Slide useful links
	300	\\[[(% style="color:#000000" %)https:~~/~~/realpython.com/python-virtual-environments-a-primer/>>https://realpython.com/python-virtual-environments-a-primer/]](%%)
	301	[[(% style="color:#000000" %)https:~~/~~/briansimulator.org/install/>>https://briansimulator.org/install/]](%%)
27.13	302	[[(% 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]](%%)
27.14	303	[[(% style="color:#000000" %)https:~~/~~/neuron.yale.edu/neuron/>>https://neuron.yale.edu/neuron/]]
27.12	304	)))
	305
27.16	306	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.
27.12	307
	308	(% class="box successmessage" %)
	309	(((
21.1	310	Slide acknowledgements, contact information
	311	)))
20.1	312
21.1	313	(% class="wikigeneratedid" %)
38.1	314	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.
20.1	315
21.1	316	(% class="wikigeneratedid" %)
38.1	317	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.

Wiki source code of 02. Installing PyNN - Linux

PyNN: resources