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Merge pull request #2 from SpiNNakerManchester/play
Test notebooks using nbmake
2 parents fe9433c + 2cb2edc commit a84393e

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‎.github/workflows/python_actions.yml

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# Copyright (c) 2020 The University of Manchester
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# This workflow will install Python dependencies, run tests, lint and rat with a variety of Python versions
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# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
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name: Python Actions
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on: [push]
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jobs:
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test:
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runs-on: ubuntu-latest
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timeout-minutes: 10
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strategy:
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matrix:
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python-version: [3.8, 3.9, "3.10", "3.11", "3.12"]
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steps:
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python-version }}
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- name: Checkout
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uses: actions/checkout@v4
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- name: Checkout SupportScripts
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uses: actions/checkout@v4
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with:
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repository: SpiNNakerManchester/SupportScripts
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path: support
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- name: Install pip, etc
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uses: ./support/actions/python-tools
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- name: Install nbmake
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run: pip install pytest nbmake
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- name: Install Spinnaker Dependencies
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uses: ./support/actions/install-spinn-deps
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with:
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repositories: >
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SpiNNUtils SpiNNMachine SpiNNMan PACMAN spalloc
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SpiNNFrontEndCommon sPyNNaker TestBase
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install: true
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- name: Setup
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uses: ./support/actions/run-install
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#- name: Setup PyNN
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# uses: ./support/actions/pynn-setup
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- name: Create a spynnaker.cfg
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uses: ./support/actions/configure-spynnaker
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with:
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virtual: true
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- name: Build test bash
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run: python integration_tests/bash_builder.py
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- name: Test with nbmake
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run: bash integration_tests/pytest.bash
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- name: Lint with flake8
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run: flake8 integration_tests spinnaker_jupyter_examples
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- name: Lint with pylint
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uses: ./support/actions/pylint
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with:
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package: integration_tests spinnaker_jupyter_examples
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exitcheck: 31 # Action fails on any message
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language: en_GB
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‎.gitignore

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/.project
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/.pydevproject
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.ipynb_checkpoints
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.pytest_cache
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.pytest.bash

‎00.Setup/Setup.ipynb

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"source": [
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"import configparser\n",
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"import os\n",
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"from unittest import SkipTest\n",
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"\n",
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"OVERRIDE_EXISTING = False\n",
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"FULL_PATH = os.path.expanduser('~/.spynnaker.cfg')\n",
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" return True\n",
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"\n",
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" # SkipTest as unittest considers this neither a failure nor a success\n",
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" raise SkipTest(f\"{FULL_PATH} already exists. \"\n",
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" \"To replace it change OVERRIDE_EXISTING to True\")\n",
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" print(f\"{FULL_PATH} already exists.\")\n",
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" print(\"To replace it change OVERRIDE_EXISTING to True\")\n",
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" return False\n",
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"\n",
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"\n",
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"check_should_create()\n",
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"\n",
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"# Make sure there is a spynnaker.cfg file\n",
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"with open(FULL_PATH, 'w') as cfg:\n",
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" cfg.write(\"[Machine]\\n\")\n",
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" cfg.write(\"spalloc_server = https://spinnaker.cs.man.ac.uk/spalloc/\\n\")\n",
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" cfg.write(\"\\n\")\n",
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" cfg.write(\"[Java]\\n\")\n",
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" cfg.write(\"use_java=True\\n\")\n",
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" cfg.write(\"\\n\")\n",
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" cfg.write(\"[Reports]\\n\")\n",
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" cfg.write(\"read_provenance_data = False\\n\")\n",
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" print(f\"New {FULL_PATH} created\")\n"
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"if check_should_create():\n",
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" with open(FULL_PATH, 'w') as cfg:\n",
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" cfg.write(\"[Machine]\\n\")\n",
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" cfg.write(\"spalloc_server = https://spinnaker.cs.man.ac.uk/spalloc/\\n\")\n",
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" cfg.write(\"\\n\")\n",
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" cfg.write(\"[Java]\\n\")\n",
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" cfg.write(\"use_java=True\\n\")\n",
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" cfg.write(\"\\n\")\n",
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" cfg.write(\"[Reports]\\n\")\n",
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" cfg.write(\"read_provenance_data = False\\n\")\n",
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" print(f\"New {FULL_PATH} created\")\n"
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]
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},
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{
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "EBRAINS-experimental",
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"language": "python",
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"name": "ebrains-experimental"
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},
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"title": "SpiNNaker Setup"
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},
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎01.RunningPyNNSimulations/RunningPyNNSimulationsOnSpiNNaker.ipynb

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"of the current is added over a number of timesteps, with the current decaying exponentially between each.\n",
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"A longer decay rate will result in more charge being added overall per spike that crosses the synapse.\n",
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"\n",
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"In the above example, the default parameters of the IF_curr_exp are used. These are shown below."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"In the above example, the default parameters of the IF_curr_exp are used. These are shown below.\n",
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"\n",
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"```\n",
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"lif_curr_exp_params = {\n",
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" 'cm': 1.0, # The capacitance of the LIF neuron in nano-Farads\n",
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" 'tau_m': 20.0, # The time-constant of the RC circuit, in milliseconds\n",
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" 'tau_syn_E': 5.0, # The excitatory input current decay time-constant\n",
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" 'tau_syn_I': 5.0, # The inhibitory input current decay time-constant\n",
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" 'i_offset': 0.0, # A base input current to add each timestep\n",
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"}"
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"}\n",
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"```"
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]
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},
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{
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"value of the membrane voltage; the higher the membrane voltage, the more input is required to cause a\n",
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"spike. This is modelled as the reversal potential of the synapse; when the membrane potential equals the\n",
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"reversal potential, no current will flow across the synapse. A conductance-based version of the LIF model\n",
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"is provided, which, in addition to the above parameters, also supports the following."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"is provided, which, in addition to the above parameters, also supports the following.",
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"\n",
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"```\n",
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"lif_cond_exp_extra_params = {\n",
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" 'e_rev_E': 0., # The reversal potential of the excitatory synapse\n",
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" 'e_rev_I': -80.0 # The reversal potential of the inhibitory synapse\n",
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"}"
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"}\n",
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"```"
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]
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},
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{
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"source": [
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"The initial value of the state variables of the neural model can also be set (such as the membrane voltage).\n",
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"This is done via the initialize function of the population, which takes the name of the state variable (e.g. v\n",
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"for the membrane voltage), and the value to be assigned e.g. the initial voltage can be set to -65.0mV as follows."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"pop_1.initialize(v=-65.0)"
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"for the membrane voltage), and the value to be assigned e.g. the initial voltage can be set to -65.0mV as follows.\n",
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"```\n",
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"pop_1.initialize(v=-65.0)\n",
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"```"
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]
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},
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{
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"\n",
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"As well as a connector the Projection must also have a synapse_type which determines how the synapse\n",
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"behaves when spikes are received. For example a StaticSynapse which has fixed weights and delays is\n",
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"specified as shown below."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"specified as shown below.\n",
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"synapse_type=sim.StaticSynapse(weight=0.75, delay=1.0)"
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]
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},
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"### STDP in PyNN\n",
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"The steps for creating a network using STDP are much the same as previously described, with the main\n",
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"difference being that some of the projections use a STDPMechanism to describe the plasticity. Below is an\n",
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"example of the creation of a projection with STDP."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"example of the creation of a projection with STDP.\n",
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"\n",
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"```\n",
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"timing_rule = sim.SpikePairRule(tau_plus=20.0, tau_minus=20.0, A_plus=0.5, A_minus=0.5)\n",
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"weight_rule = sim.AdditiveWeightDependence(w_max=5.0, w_min=0.0)\n",
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"stdp_model = sim.STDPMechanism(timing_dependence=timing_rule, weight_dependence=weight_rule, weight=0.0, delay=5.0)\n",
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"stdp_projection = sim.Projection(input, pop_1, sim.OneToOneConnector(), synapse_type=stdp_model)"
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"stdp_projection = sim.Projection(input, pop_1, sim.OneToOneConnector(), synapse_type=stdp_model)\n",
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"```"
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]
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},
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{
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" - Create an STDP curve graph using a SpikeSourceArray stimulating a LIF population, with varying spike times for the SpikeSourceArray.\n",
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" - See the notebook for further extensions.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "EBRAINS-experimental",
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"language": "python",
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"name": "ebrains-experimental"
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},
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"title": "Running PyNN Simulations on SpiNNaker"
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},
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"nbformat": 4,
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"nbformat_minor": 2

‎01.RunningPyNNSimulations/solutions/task1-solutions.ipynb

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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "EBRAINS-experimental",
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"language": "python",
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"name": "ebrains-experimental"
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},
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"title": "Task 1.1 Solutions"
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},
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"nbformat": 4,
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"nbformat_minor": 2

‎01.RunningPyNNSimulations/solutions/task2-solutions.ipynb

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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "EBRAINS-experimental",
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"language": "python",
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"name": "ebrains-experimental"
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},
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"title": "Task 1.2 Solutions"
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},
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"nbformat": 4,
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"nbformat_minor": 2

‎01.RunningPyNNSimulations/solutions/task3-solutions.ipynb

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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "EBRAINS-experimental",
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"language": "python",
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"name": "ebrains-experimental"
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},
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"title": "Task 1.3 Solutions"
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},
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"nbformat": 4,
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"nbformat_minor": 2

‎01.RunningPyNNSimulations/solutions/task4-solutions.ipynb

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"source": [
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"weights = proj.get([\"weight\"], \"list\")\n",
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"p.end()\n",
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"print weights"
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"print(weights)"
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]
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},
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{
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "EBRAINS-experimental",
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"language": "python",
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"name": "ebrains-experimental"
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},
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"title": "Task 1.4 Solutions"
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},
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"nbformat": 4,
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"nbformat_minor": 2

‎01.RunningPyNNSimulations/solutions/task5-solutions.ipynb

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"metadata": {},
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"outputs": [],
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"source": [
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"weights = proj.get([\"weight\"], \"list\", with_address=False)\n",
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"import numpy\n",
159+
"weights = numpy.array(proj.get(\"weight\", \"list\", with_address=False))\n",
159160
"pre_spikes = pre.get_data(\"spikes\").segments[0].spiketrains\n",
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"post_spikes = post.get_data(\"spikes\").segments[0].spiketrains\n",
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"p.end()"
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177178
"metadata": {},
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"outputs": [],
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"source": [
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"weight_diff = weights[:] - 0.5\n",
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"weight_diff = weights - 0.5\n",
181182
"time_diff = [pre_neuron_spikes[0] - post_neuron_spikes[0] for pre_neuron_spikes, post_neuron_spikes in zip(pre_spikes, post_spikes)]"
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]
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},
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "EBRAINS-experimental",
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"language": "python",
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"name": "ebrains-experimental"
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},
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"title": "Task 1.5 Solutions"
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},
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"nbformat": 4,
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"nbformat_minor": 2

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