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| <h1 id="tutorial-cli-and-profiling">Tutorial: CLI and profiling</h1> |
| <p>The CLI supports five especially useful operational paths:</p> |
| <ul> |
| <li><code>run</code></li> |
| <li><code>batch</code></li> |
| <li><code>profile</code></li> |
| <li><code>schema</code></li> |
| <li><code>recommend</code></li> |
| </ul> |
| <p>All commands below use files that ship with this repository.</p> |
| <h2 id="single-file-run">Single-file run</h2> |
| <pre><code class="language-bash">python -m detime run \ |
| --method SSA \ |
| --series examples/data/example_series.csv \ |
| --col value \ |
| --param window=24 \ |
| --param rank=6 \ |
| --param primary_period=12 \ |
| --out_dir out/ssa \ |
| --output-mode summary \ |
| --plot |
| </code></pre> |
| <p>Published stdout from the current docs build:</p> |
| <pre><code class="language-text">Running SSA on examples/data/example_series.csv... |
| Done. Results saved to out/ssa |
| </code></pre> |
| <p>Published output files:</p> |
| <ul> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/single-file/example_series_summary.json">example_series_summary.json</a></li> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/single-file/example_series_plot.png">example_series_plot.png</a></li> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/single-file/example_series_error.png">example_series_error.png</a></li> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/single-file/command_stdout.txt">command_stdout.txt</a></li> |
| </ul> |
| <p>Representative summary excerpt:</p> |
| <pre><code class="language-json">{ |
| "mode": "summary", |
| "trend": { "shape": [120], "std": 0.6917 }, |
| "season": { "shape": [120], "std": 0.7036 }, |
| "residual": { "shape": [120], "l2_norm": 0.0 }, |
| "meta": { |
| "backend_used": "native", |
| "method": "SSA", |
| "window": 24, |
| "rank": 6 |
| } |
| } |
| </code></pre> |
| <p>Published plots from the same run:</p> |
| <p><img alt="CLI single-file decomposition" src="../../assets/generated/tutorials/cli-and-profiling/single-file/example_series_plot.png" /></p> |
| <p><img alt="CLI single-file residual" src="../../assets/generated/tutorials/cli-and-profiling/single-file/example_series_error.png" /></p> |
| <h2 id="multivariate-run">Multivariate run</h2> |
| <pre><code class="language-bash">python -m detime run \ |
| --method MSSA \ |
| --series examples/data/example_multivariate.csv \ |
| --cols x0,x1 \ |
| --param window=24 \ |
| --param rank=8 \ |
| --param primary_period=12 \ |
| --out_dir out/mssa \ |
| --output-mode summary |
| </code></pre> |
| <p>Published stdout from the current docs build:</p> |
| <pre><code class="language-text">Running MSSA on examples/data/example_multivariate.csv... |
| Done. Results saved to out/mssa |
| </code></pre> |
| <p>Published output files:</p> |
| <ul> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/multivariate/example_multivariate_summary.json">example_multivariate_summary.json</a></li> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/multivariate/command_stdout.txt">command_stdout.txt</a></li> |
| </ul> |
| <p>Representative summary excerpt:</p> |
| <pre><code class="language-json">{ |
| "mode": "summary", |
| "trend": { "shape": [120, 2] }, |
| "season": { "shape": [120, 2] }, |
| "components": { |
| "modes": { "shape": [8, 120, 2] } |
| }, |
| "meta": { |
| "backend_used": "python", |
| "channel_names": ["x0", "x1"] |
| } |
| } |
| </code></pre> |
| <h2 id="batch-processing">Batch processing</h2> |
| <pre><code class="language-bash">python -m detime batch \ |
| --method STD \ |
| --glob "examples/data/batch/*.csv" \ |
| --col value \ |
| --param period=12 \ |
| --out_dir out/std_batch \ |
| --output-mode meta |
| </code></pre> |
| <p>Published stdout from the current docs build:</p> |
| <pre><code class="language-text">Found 2 files. Processing... |
| </code></pre> |
| <p>Published output files:</p> |
| <ul> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/batch/series_a_meta.json">series_a_meta.json</a></li> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/batch/series_b_meta.json">series_b_meta.json</a></li> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/batch/command_stdout.txt">command_stdout.txt</a></li> |
| </ul> |
| <p>Representative <code>meta</code> payload excerpt from <code>series_a_meta.json</code>:</p> |
| <pre><code class="language-json">{ |
| "mode": "meta", |
| "meta": { |
| "method": "STD", |
| "period": 12, |
| "n_cycles": 2, |
| "backend_used": "native", |
| "input_shape": [24] |
| }, |
| "diagnostics": { |
| "component_names": ["dispersion", "seasonal_shape"] |
| } |
| } |
| </code></pre> |
| <h2 id="runtime-profiling">Runtime profiling</h2> |
| <p>Text output now respects <code>--format text</code> on stdout as well as saved reports.</p> |
| <pre><code class="language-bash">python -m detime profile \ |
| --method SSA \ |
| --series examples/data/example_series.csv \ |
| --col value \ |
| --param window=24 \ |
| --param rank=6 \ |
| --param primary_period=12 \ |
| --repeat 5 \ |
| --warmup 1 \ |
| --format text |
| </code></pre> |
| <p>Published stdout from the current docs build:</p> |
| <pre><code class="language-text">method=SSA |
| backend_requested=auto |
| backend_used=native |
| speed_mode=exact |
| repeat=5 |
| warmup=1 |
| ... |
| </code></pre> |
| <p>Raw text report:</p> |
| <ul> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/profile/ssa_profile_text.txt">ssa_profile_text.txt</a></li> |
| </ul> |
| <p>For multivariate JSON profiling:</p> |
| <pre><code class="language-bash">python -m detime profile \ |
| --method MSSA \ |
| --series examples/data/example_multivariate.csv \ |
| --cols x0,x1 \ |
| --param window=24 \ |
| --param primary_period=12 \ |
| --repeat 3 \ |
| --format json |
| </code></pre> |
| <p>Published JSON output:</p> |
| <ul> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/profile/mssa_profile.json">mssa_profile.json</a></li> |
| </ul> |
| <p>Representative excerpt:</p> |
| <pre><code class="language-json">{ |
| "method": "MSSA", |
| "backend_used": "python", |
| "columns": ["x0", "x1"], |
| "repeat": 3, |
| "summary": { |
| "mean_ms": 11.9110, |
| "min_ms": 11.6017, |
| "p95_ms": 12.0886 |
| } |
| } |
| </code></pre> |
| <h2 id="backend-selection-and-saved-reports">Backend selection and saved reports</h2> |
| <pre><code class="language-bash">python -m detime profile \ |
| --method STD \ |
| --series examples/data/example_series.csv \ |
| --col value \ |
| --param period=12 \ |
| --backend native \ |
| --repeat 10 \ |
| --warmup 2 \ |
| --format text \ |
| --output out/profile/std_native.txt |
| </code></pre> |
| <p>Published command stdout:</p> |
| <pre><code class="language-text">Profile report written to out/profile/std_native.txt |
| </code></pre> |
| <p>Published saved report:</p> |
| <ul> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/profile/std_native.txt">std_native.txt</a></li> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/profile/std_native_stdout.txt">std_native_stdout.txt</a></li> |
| </ul> |
| <h2 id="machine-facing-helpers">Machine-facing helpers</h2> |
| <pre><code class="language-bash">python -m detime schema --name method-registry |
| python -m detime recommend --length 192 --channels 3 --prefer accuracy --format text |
| </code></pre> |
| <p>Published outputs:</p> |
| <ul> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/machine/method_registry_schema.json">method_registry_schema.json</a></li> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/machine/recommend_text.txt">recommend_text.txt</a></li> |
| <li><a href="../../assets/generated/tutorials/cli-and-profiling/machine/recommend.json">recommend.json</a></li> |
| </ul> |
| <p>Published recommendation text excerpt:</p> |
| <pre><code class="language-text">1. MSSA (13.50) |
| Multivariate SSA for shared-structure decomposition across channels. |
| 2. STDR (11.75) |
| Robust seasonal-trend decomposition for noisier periodic signals. |
| 3. STD (9.25) |
| Fast seasonal-trend decomposition with dispersion-aware diagnostics. |
| </code></pre></div> |
| </div> |
| </div> |
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