add.Math #4
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| Let’s break this down precisely and compute what you're asking. | ||
| --- | ||
| # Config for the Gemini Pull Request Review Bot. | ||
| # https://github.com/marketplace/gemini-code-assist | ||
| have_fun: false | ||
| code_review: | ||
| disable: false | ||
| comment_severity_threshold: 'HIGH' | ||
| max_review_comments: -1 | ||
| pull_request_opened: | ||
| help: false | ||
| summary: true | ||
| code_review: true | ||
| ignore_patterns: [] | ||
| name: CI | ||
| on: | ||
| push: | ||
| branches-ignore: | ||
| - 'generated' | ||
| - 'codegen/**' | ||
| - 'integrated/**' | ||
| - 'stl-preview-head/**' | ||
| - 'stl-preview-base/**' | ||
| pull_request: | ||
| branches-ignore: | ||
| - 'stl-preview-head/**' | ||
| - 'stl-preview-base/**' | ||
| jobs: | ||
| lint: | ||
| timeout-minutes: 10 | ||
| name: lint | ||
| runs-on: ${{ github.repository == 'stainless-sdks/openai-python' && 'depot-ubuntu-24.04' || 'ubuntu-latest' }} | ||
| if: github.event_name == 'push' || github.event.pull_request.head.repo.fork | ||
| steps: | ||
| - uses: actions/checkout@v4 | ||
| - name: Install Rye | ||
| run: | | ||
| curl -sSf https://rye.astral.sh/get | bash | ||
| echo "$HOME/.rye/shims" >> $GITHUB_PATH | ||
| env: | ||
| RYE_VERSION: '0.44.0' | ||
| RYE_INSTALL_OPTION: '--yes' | ||
| - name: Install dependencies | ||
| run: rye sync --all-features | ||
| - name: Run lints | ||
| run: ./scripts/lint | ||
| build: | ||
| if: github.repository == 'stainless-sdks/openai-python' && (github.event_name == 'push' || github.event.pull_request.head.repo.fork) | ||
| timeout-minutes: 10 | ||
| name: build | ||
| permissions: | ||
| contents: read | ||
| id-token: write | ||
| runs-on: depot-ubuntu-24.04 | ||
| steps: | ||
| - uses: actions/checkout@v4 | ||
| - name: Install Rye | ||
| run: | | ||
| curl -sSf https://rye.astral.sh/get | bash | ||
| echo "$HOME/.rye/shims" >> $GITHUB_PATH | ||
| env: | ||
| RYE_VERSION: '0.44.0' | ||
| RYE_INSTALL_OPTION: '--yes' | ||
| - name: Install dependencies | ||
| run: rye sync --all-features | ||
| - name: Run build | ||
| run: rye build | ||
| - name: Get GitHub OIDC Token | ||
| id: github-oidc | ||
| uses: actions/github-script@v6 | ||
| with: | ||
| script: core.setOutput('github_token', await core.getIDToken()); | ||
| - name: Upload tarball | ||
| env: | ||
| URL: https://pkg.stainless.com/s | ||
| AUTH: ${{ steps.github-oidc.outputs.github_token }} | ||
| SHA: ${{ github.sha }} | ||
| run: ./scripts/utils/upload-artifact.sh | ||
| test: | ||
| timeout-minutes: 10 | ||
| name: test | ||
| runs-on: ${{ github.repository == 'stainless-sdks/openai-python' && 'depot-ubuntu-24.04' || 'ubuntu-latest' }} | ||
| if: github.event_name == 'push' || github.event.pull_request.head.repo.fork | ||
| steps: | ||
| - uses: actions/checkout@v4 | ||
| - name: Install Rye | ||
| run: | | ||
| curl -sSf https://rye.astral.sh/get | bash | ||
| echo "$HOME/.rye/shims" >> $GITHUB_PATH | ||
| env: | ||
| RYE_VERSION: '0.44.0' | ||
| RYE_INSTALL_OPTION: '--yes' | ||
| - name: Bootstrap | ||
| run: ./scripts/bootstrap | ||
| - name: Run tests | ||
| run: ./scripts/test | ||
| examples: | ||
| timeout-minutes: 10 | ||
| name: examples | ||
| runs-on: ${{ github.repository == 'stainless-sdks/openai-python' && 'depot-ubuntu-24.04' || 'ubuntu-latest' }} | ||
| if: github.repository == 'openai/openai-python' && (github.event_name == 'push' || github.event.pull_request.head.repo.fork) | ||
| steps: | ||
| - uses: actions/checkout@v4 | ||
| - name: Install Rye | ||
| run: | | ||
| curl -sSf https://rye.astral.sh/get | bash | ||
| echo "$HOME/.rye/shims" >> $GITHUB_PATH | ||
| env: | ||
| RYE_VERSION: '0.44.0' | ||
| RYE_INSTALL_OPTION: '--yes' | ||
| - name: Install dependencies | ||
| run: | | ||
| rye sync --all-features | ||
| - env: | ||
| OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} | ||
| run: | | ||
| rye run python examples/demo.py | ||
| - env: | ||
| OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} | ||
| run: | | ||
| rye run python examples/async_demo.py | ||
| You’re working with: | ||
| \[ | ||
| \bar{x}_j = \frac{1}{|C_j|} \sum_{v_i \in C_j} x_i | ||
| \] | ||
| This gives the **mean** of values \( x_i \) in cluster \( C_j \). Now you’re asking: | ||
| > What is \( \bar{x}_j \div 18.33 \)? | ||
| --- | ||
| ### 🧮 Interpretation | ||
| Let’s assume: | ||
| - You already computed \( \bar{x}_j = 18.33 \) | ||
| - Now you're dividing that result by 18.33 | ||
| So: | ||
| \[ | ||
| \frac{\bar{x}_j}{18.33} = \frac{18.33}{18.33} = 1 | ||
| \] | ||
| ✅ **Final result: 1 | ||
| --- | ||
| ### 🧠 Why This Matters | ||
| This kind of normalization is often used in: | ||
| - **Standardization**: Comparing a value to a reference mean | ||
| - **Ratio analysis**: Checking proportional relationships | ||
| - **Feature scaling**: In machine learning preprocessing | ||
| If you’re building a model or analyzing clusters, this could be part of a larger transformation. Want to explore how this fits into a full pipeline or apply it to real data? | ||
