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Merge pull request #1948 from ArmDeveloperEcosystem/main
Production update
2 parents 1c7d65a + c3bba36 commit cb13ecc

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‎.github/workflows/roadmap-update.yml‎

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name: Update Roadmap Date
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on:
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pull_request_target:
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types: [labeled]
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jobs:
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update-roadmap-dates:
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runs-on: ubuntu-latest
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if: |
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github.event.label.name == 'awaiting_tech_review' ||
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github.event.label.name == 'publish'
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permissions:
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contents: read
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pull-requests: read
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repository-projects: write
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steps:
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- name: Checkout repository
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uses: actions/checkout@v3
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- name: Setup Node.js
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uses: actions/setup-node@v3
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with:
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node-version: '18.x'
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- name: Install Octokit
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run: npm install @octokit/rest
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- name: Update Project Board Dates
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uses: actions/github-script@v6
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with:
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github-token: ${{ secrets.PROJECT_TOKEN }}
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script: |
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const octokit = github;
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const projectNumber = 4;
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const orgLogin = 'ArmDeveloperEcosystem';
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const prNumber = context.payload.pull_request.number;
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const labelName = context.payload.label.name;
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async function getProjectItemForPR() {
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const projectQuery = `
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query {
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organization(login: "${orgLogin}") {
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projectV2(number: ${projectNumber}) {
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id
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}
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}
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}
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`;
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const projectResponse = await octokit.graphql(projectQuery);
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const project = projectResponse.organization?.projectV2;
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if (!project) throw new Error("Project not found for organization.");
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const projectId = project.id;
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let cursor = null;
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let itemId = null;
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do {
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const prQuery = `
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query($after: String) {
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organization(login: "${orgLogin}") {
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projectV2(number: ${projectNumber}) {
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items(first: 100, after: $after) {
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nodes {
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id
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content {
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... on PullRequest {
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number
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repository {
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name
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}
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}
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}
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}
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pageInfo {
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hasNextPage
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endCursor
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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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const prResponse = await octokit.graphql(prQuery, { after: cursor });
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const items = prResponse.organization.projectV2.items.nodes;
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const foundItem = items.find(item =>
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item.content &&
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item.content.number === prNumber &&
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item.content.repository.name === context.repo.repo
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);
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if (foundItem) {
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itemId = foundItem.id;
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break;
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}
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cursor = prResponse.organization.projectV2.items.pageInfo.endCursor;
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} while (cursor);
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return { projectId, itemId };
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}
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async function getFieldId(projectId, fieldName) {
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const fieldsQuery = `
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query {
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node(id: "${projectId}") {
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... on ProjectV2 {
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fields(first: 50) {
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nodes {
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... on ProjectV2Field {
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id
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name
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dataType
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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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`;
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const fieldsResponse = await octokit.graphql(fieldsQuery);
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const fields = fieldsResponse.node?.fields?.nodes || [];
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const field = fields.find(f => f.name === fieldName && f.dataType === 'DATE');
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return field ? field.id : null;
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}
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async function updateDateField(projectId, itemId, fieldId, date) {
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const mutation = `
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mutation {
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updateProjectV2ItemFieldValue(
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input: {
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projectId: "${projectId}"
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itemId: "${itemId}"
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fieldId: "${fieldId}"
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value: { date: "${date}" }
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}
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) {
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projectV2Item {
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id
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}
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}
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}
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`;
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const result = await octokit.graphql(mutation);
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console.log('Mutation result:', result);
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return result;
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}
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async function main() {
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try {
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const { projectId, itemId } = await getProjectItemForPR();
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if (!itemId) {
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console.log('PR not found in project board');
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return;
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}
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const today = new Date().toISOString().split('T')[0];
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if (labelName === 'awaiting_tech_review') {
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const startDateFieldId = await getFieldId(projectId, 'Start Date');
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if (startDateFieldId) {
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await updateDateField(projectId, itemId, startDateFieldId, today);
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console.log('Updated Start Date to', today);
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} else {
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console.log('Start Date field not found');
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}
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} else if (labelName === 'publish') {
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const endDateFieldId = await getFieldId(projectId, 'Publish Date');
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if (endDateFieldId) {
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await updateDateField(projectId, itemId, endDateFieldId, today);
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console.log('Updated Publish Date to', today);
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} else {
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console.log('Publish Date field not found');
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}
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} else {
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console.log('No action taken for label:', labelName);
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}
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} catch (error) {
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console.error('Error updating project board:', error);
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core.setFailed(`Error updating project board: ${error.message}`);
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}
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}
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main();

‎.wordlist.txt‎

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@@ -4080,4 +4080,42 @@ DB's
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FFT's
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IoT's
40824082
NumPy's
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SendGrid's
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SendGrid's
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AEMv
4085+
AEx
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BusyBox
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CTX
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FastMCP
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HW
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LLVM's
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LiveHDR
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PCI
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PSCI
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Pixmap
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PyPi
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Qixiang
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REGS
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RevC
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SMMU
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SMP
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Strided
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TTS
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Wix’s
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Xu
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aemfvp
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convolve
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deps
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dotenv
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fastmcp
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ipykernel
4111+
jlowin
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libomp
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lockfile
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lockfiles
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mk
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multimodal
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ngrok’s
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precomputed
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pyproject
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toml
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virtualenv

‎content/learning-paths/embedded-and-microcontrollers/_index.md‎

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operatingsystems_filter:
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- Android: 1
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- Baremetal: 29
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- Linux: 26
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- Linux: 27
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- macOS: 6
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- RTOS: 9
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- Windows: 4
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subjects_filter:
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- CI-CD: 5
2020
- Containers and Virtualization: 6
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- Embedded Linux: 3
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- Embedded Linux: 4
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- Libraries: 3
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- ML: 12
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- Performance and Architecture: 21
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- Arm Compiler for Embedded: 7
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- Arm Compiler for Linux: 1
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- Arm Compute Library: 1
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- Arm Development Studio: 7
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- Arm Development Studio: 8
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- Arm Fast Models: 4
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- Arm Virtual Hardware: 10
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- Assembly: 1
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- AVH: 1
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- C: 2
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- C: 3
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- C/C++: 1
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- ChatGPT: 1
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- Clang: 1
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- MPS3: 1
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- MXNet: 1
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- Neon: 1
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- NumPy: 1
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- Paddle: 1
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- Porcupine: 1
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- Python: 5
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- TrustZone: 2
8991
- TVMC: 1
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- vcpkg: 1
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- VS Code: 1
9293
- Yocto Linux: 1
9394
- Zephyr: 1
9495
weight: 5

‎content/learning-paths/embedded-and-microcontrollers/cmsisdsp-dev-with-python/_index.md‎

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---
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title: Getting Started with CMSIS-DSP Using Python
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title: Getting started with CMSIS-DSP using Python
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minutes_to_complete: 30
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minutes_to_complete: 45
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draft: true
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cascade:
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draft: true
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who_is_this_for: This is an advanced topic for developers looking to integrate the CMSIS-DSP library into their applications using Python.
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who_is_this_for: Developers who want to learn how the CMSIS-DSP package can be integrated into their applications
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learning_objectives:
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- Understand how to use the CMSIS-DSP Python package
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- Understand how the Python implementation maps to the C implementation
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- Develop a complex application using CMSIS-DSP
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- Use the CMSIS-DSP Python package to prototype DSP algorithms.
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- Understand how the Python API maps to the C implementation.
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- Build and port a complex DSP application using CMSIS-DSP.
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prerequisites:
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- Some familiarity with Python and DSP programming
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- Knowledge of C
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- Some familiarity with CMSIS-DSP
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- Python installed on your system
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- Familiarity with Python and digital signal processing concepts.
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- Working knowledge of C.
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- Prior exposure to CMSIS-DSP.
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- Python installed on your machine.
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author: Christophe Favergeon
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- Python
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- C
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- Jupyter Notebook
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- numpy
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- NumPy
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operatingsystems:
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- Linux
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- Windows
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- macOS
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further_reading:
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- resource:
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title: Biquad filters with CMSIS-DSP Python package
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title: Biquad Filters with CMSIS-DSP Python Package
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link: https://developer.arm.com/documentation/102463/latest/
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type: documentation
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- resource:
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title: CMSIS-DSP library
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title: CMSIS-DSP Library (GitHub)
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link: https://github.com/ARM-software/CMSIS-DSP
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type: Open-source project
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- resource:
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title: CMSIS-DSP python package
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title: CMSIS-DSP Python Package (PyPi)
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link: https://pypi.org/project/cmsisdsp/
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type: Open-source project
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- resource:
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title: CMSIS-DSP Python package examples and tests
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title: CMSIS-DSP Python Package Examples and Tests
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link: https://github.com/ARM-software/CMSIS-DSP/tree/main/PythonWrapper/examples
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type: Open-source project
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- resource:

‎content/learning-paths/embedded-and-microcontrollers/cmsisdsp-dev-with-python/how-to-1.md‎

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## What is CMSIS-DSP?
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CMSIS-DSP is a general-purpose compute library with a focus on DSP. It was initially developed for Cortex-M processors and has recently been upgraded to also support Cortex-A.
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CMSIS-DSP is a general-purpose computation library focused on digital signal processing (DSP).
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On each processor, CMSIS-DSP is optimized for the architecture: DSP extensions on M4 and M7; Helium on M55 and M85; Neon on A55, etc.
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Originally developed for Cortex-M processors, it now also supports Cortex-A.
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## What is the CMSIS-DSP Python package?
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The library is optimized for each architecture:
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- DSP extensions on Cortex-M4 and M7.
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- Helium on M55 and M85.
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- Neon on Cortex-A55 and other Cortex-A cores.
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The CMSIS-DSP Python package is a Python API for CMSIS-DSP. Its goal is to make it easier to develop a C solution using CMSIS-DSP by decreasing the gap between a design environment like Python and the final C implementation.
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## What is the CMSIS-DSP Python package?
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The CMSIS-DSP Python package provides a Python API for CMSIS-DSP. Its goal is to make it easier to develop a C solution using CMSIS-DSP by bridging the gap between a Python-based design environment and a final C implementation.
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For this reason, the Python API is as close as possible to the C one.
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The API is designed to closely mirror the C version in both function and structure.
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Fixed-point arithmetic is rarely provided by Python packages, which generally focus on floating-point operations. The CMSIS-DSP Python package provides the same fixed-point arithmetic functions as the C version: Q31, Q15 and Q7. The package also provides floating-point functions and will also support half-precision floats in the future, like the C API.
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Fixed-point arithmetic is rarely supported by Python libraries, which generally focus on floating-point operations. The CMSIS-DSP Python package includes the same fixed-point arithmetic functions as the C version: Q31, Q15 and Q7. Support for half-precision floats will be added in a future release, matching the C API.
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Finally, the CMSIS-DSP Python package is compatible with NumPy and can be used with all other scientific and AI Python packages such as SciPy and PyTorch.
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The package is compatible with NumPy and integrates well with scientific and AI libraries such as SciPy and PyTorch.
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