matplotlib.github.com/3.7.4/users/explain/performance.html at main · matplotlib/matplotlib.github.com

History

670 lines (478 loc) · 33.9 KB

Raw

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

206

207

208

209

210

211

212

213

214

215

216

217

218

219

220

221

222

223

224

225

226

227

228

229

230

231

232

233

234

235

236

237

238

239

240

241

242

243

244

245

246

247

248

249

250

251

252

253

254

255

256

257

258

259

260

261

262

263

264

265

266

267

268

269

270

271

272

273

274

275

276

277

278

279

280

281

282

283

284

285

286

287

288

289

290

291

292

293

294

295

296

297

298

299

300

301

302

303

304

305

306

307

308

309

310

311

312

313

314

315

316

317

318

319

320

321

322

323

324

325

326

327

328

329

330

331

332

333

334

335

336

337

338

339

340

341

342

343

344

345

346

347

348

349

350

351

352

353

354

355

356

357

358

359

360

361

362

363

364

365

366

367

368

369

370

371

372

373

374

375

376

377

378

379

380

381

382

383

384

385

386

387

388

389

390

391

392

393

394

395

396

397

398

399

400

401

402

403

404

405

406

407

408

409

410

411

412

413

414

415

416

417

418

419

420

421

422

423

424

425

426

427

428

429

430

431

432

433

434

435

436

437

438

439

440

441

442

443

444

445

446

447

448

449

450

451

452

453

454

455

456

457

458

459

460

461

462

463

464

465

466

467

468

469

470

471

472

473

474

475

476

477

478

479

480

481

482

483

484

485

486

487

488

489

490

491

492

493

494

495

496

497

498

499

500

501

502

503

504

505

506

507

508

509

510

511

512

513

514

515

516

517

518

519

520

521

522

523

524

525

526

527

528

529

530

531

532

533

534

535

536

537

538

539

540

541

542

543

544

545

546

547

548

549

550

551

552

553

554

555

556

557

558

559

560

561

562

563

564

565

566

567

568

569

570

571

572

573

574

575

576

577

578

579

580

581

582

583

584

585

586

587

588

589

590

591

592

593

594

595

596

597

598

599

600

601

602

603

604

605

606

607

608

609

610

611

612

613

614

615

616

617

618

619

620

621

622

623

624

625

626

627

628

629

630

631

632

633

634

635

636

637

638

639

640

641

642

643

644

645

646

647

648

649

650

651

652

653

654

655

656

657

658

659

660

661

662

663

664

665

666

667

668

669

670

<!DOCTYPE html>

<head>

<title>Performance — Matplotlib 3.7.4 documentation</title>

document.documentElement.dataset.mode = localStorage.getItem("mode") || "";

document.documentElement.dataset.theme = localStorage.getItem("theme") || "light";

</script>

DOCUMENTATION_OPTIONS.theme_switcher_json_url = 'https://matplotlib.org/devdocs/_static/switcher.json?v3.7.4-2-g03947d07cf';

DOCUMENTATION_OPTIONS.theme_switcher_version_match = '3.7.4';

</script>

title="Search within Matplotlib 3.7.4 documentation"

href="../../_static/opensearch.xml"/>

</head>

<a class="skip-link" href="#main-content">Skip to main content</a>

</form>

</div>

</label>

</a>

</div>

<a class="reference internal nav-link" href="../../plot_types/index.html">Plot types</a>

</li>

<a class="reference internal nav-link" href="../../gallery/index.html">Examples</a>

</li>

<a class="reference internal nav-link" href="../../tutorials/index.html">Tutorials</a>

</li>

<a class="reference internal nav-link" href="../../api/index.html">Reference</a>

</li>

<a class="reference internal nav-link" href="../index.html">User guide</a>

</li>

<a class="reference internal nav-link" href="../../devel/index.html">Develop</a>

</li>

<a class="reference internal nav-link" href="../release_notes.html">Releases</a>

</li>

</ul>

</div>

</button>

</div>

</button>

</div>

stable

</button>

</div>

<label class="sr-only">Gitter</label></a>

</li>

<label class="sr-only">Discourse</label></a>

</li>

<label class="sr-only">GitHub</label></a>

</li>

<label class="sr-only">Twitter</label></a>

</li>

</ul>

</div>

</button>

</div>

</label>

</div>

</nav>

<a class="reference internal nav-link" href="../../plot_types/index.html">Plot types</a>

</li>

<a class="reference internal nav-link" href="../../gallery/index.html">Examples</a>

</li>

<a class="reference internal nav-link" href="../../tutorials/index.html">Tutorials</a>

</li>

<a class="reference internal nav-link" href="../../api/index.html">Reference</a>

</li>

<a class="reference internal nav-link" href="../index.html">User guide</a>

</li>

<a class="reference internal nav-link" href="../../devel/index.html">Develop</a>

</li>

<a class="reference internal nav-link" href="../release_notes.html">Releases</a>

</li>

</ul>

</div>

</button>

</div>

stable

</button>

</div>

<label class="sr-only">Gitter</label></a>

</li>

<label class="sr-only">Discourse</label></a>

</li>

<label class="sr-only">GitHub</label></a>

</li>

<label class="sr-only">Twitter</label></a>

</li>

</ul>

</div>

Section Navigation

</p>

<li class="toctree-l1"><a class="reference internal" href="api_interfaces.html">Matplotlib Application Interfaces (APIs)</a></li>

<li class="toctree-l1"><a class="reference internal" href="figures.html">Creating, viewing, and saving Matplotlib Figures</a></li>

<li class="toctree-l1"><a class="reference internal" href="backends.html">Backends</a></li>

<li class="toctree-l1"><a class="reference internal" href="writing_a_backend_pyplot_interface.html">Writing a backend -- the pyplot interface</a></li>

<li class="toctree-l1"><a class="reference internal" href="interactive.html">Interactive figures</a></li>

<li class="toctree-l1"><a class="reference internal" href="fonts.html">Fonts in Matplotlib</a></li>

<li class="toctree-l1"><a class="reference internal" href="event_handling.html">Event handling and picking</a></li>

<li class="toctree-l1 current active"><a class="current reference internal" href="#">Performance</a></li>

<li class="toctree-l1"><a class="reference internal" href="interactive_guide.html">Interactive figures and asynchronous programming</a></li>

</ul>

</div>

</nav>

</div>

</div>

</div>

</div>

<span id="id1"></span><h1>Performance<a class="headerlink" href="#performance" title="Link to this heading">#</a></h1>

<p>Whether exploring data in interactive mode or programmatically

saving lots of plots, rendering performance can be a challenging

bottleneck in your pipeline. Matplotlib provides multiple

ways to greatly reduce rendering time at the cost of a slight

change (to a settable tolerance) in your plot's appearance.

The methods available to reduce rendering time depend on the

type of plot that is being created.</p>

<h2>Line segment simplification<a class="headerlink" href="#line-segment-simplification" title="Link to this heading">#</a></h2>

<p>For plots that have line segments (e.g. typical line plots, outlines

of polygons, etc.), rendering performance can be controlled by

<code class="docutils literal notranslate"><a class="reference internal" href="../../tutorials/introductory/customizing.html?highlight=path.simplify#matplotlibrc-sample"><span class="std std-ref"><span class="pre">rcParams["path.simplify"]</span></span></a></code> (default: <code class="docutils literal notranslate"><span class="pre">True</span></code>) and <code class="docutils literal notranslate"><a class="reference internal" href="../../tutorials/introductory/customizing.html?highlight=path.simplify_threshold#matplotlibrc-sample"><span class="std std-ref"><span class="pre">rcParams["path.simplify_threshold"]</span></span></a></code> (default: <code class="docutils literal notranslate"><span class="pre">0.111111111111</span></code>), which

can be defined e.g. in the <code class="file docutils literal notranslate"><span class="pre">matplotlibrc</span></code> file (see

<a class="reference internal" href="../../tutorials/introductory/customizing.html"><span class="doc">Customizing Matplotlib with style sheets and rcParams</span></a> for more information about

the <code class="file docutils literal notranslate"><span class="pre">matplotlibrc</span></code> file). <code class="docutils literal notranslate"><a class="reference internal" href="../../tutorials/introductory/customizing.html?highlight=path.simplify#matplotlibrc-sample"><span class="std std-ref"><span class="pre">rcParams["path.simplify"]</span></span></a></code> (default: <code class="docutils literal notranslate"><span class="pre">True</span></code>) is a Boolean

indicating whether or not line segments are simplified at all.

<code class="docutils literal notranslate"><a class="reference internal" href="../../tutorials/introductory/customizing.html?highlight=path.simplify_threshold#matplotlibrc-sample"><span class="std std-ref"><span class="pre">rcParams["path.simplify_threshold"]</span></span></a></code> (default: <code class="docutils literal notranslate"><span class="pre">0.111111111111</span></code>) controls how much line segments are simplified;

higher thresholds result in quicker rendering.</p>

<p>The following script will first display the data without any

simplification, and then display the same data with simplification.

Try interacting with both of them:</p>

<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>

<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>

<span class="kn">import</span> <span class="nn">matplotlib</span> <span class="k">as</span> <span class="nn">mpl</span>

<span class="c1"># Setup, and create the data to plot</span>

<span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">rand</span><span class="p">(</span><span class="mi">100000</span><span class="p">)</span>

<span class="n">y</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">geomspace</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">50000</span><span class="p">,</span> <span class="mi">400</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">int</span><span class="p">)]</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1</span>

<span class="n">mpl</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s1">'path.simplify'</span><span class="p">]</span> <span class="o">=</span> <span class="kc">True</span>

<span class="n">mpl</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s1">'path.simplify_threshold'</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>

</pre></div>

</div>

<p>Matplotlib currently defaults to a conservative simplification

threshold of <code class="docutils literal notranslate"><span class="pre">1/9</span></code>. To change default settings to use a different

value, change the <code class="file docutils literal notranslate"><span class="pre">matplotlibrc</span></code> file. Alternatively, users

can create a new style for interactive plotting (with maximal

simplification) and another style for publication quality plotting

(with minimal simplification) and activate them as necessary. See

<a class="reference internal" href="../../tutorials/introductory/customizing.html"><span class="doc">Customizing Matplotlib with style sheets and rcParams</span></a> for instructions on

how to perform these actions.</p>

<p>The simplification works by iteratively merging line segments

into a single vector until the next line segment's perpendicular

distance to the vector (measured in display-coordinate space)

is greater than the <code class="docutils literal notranslate"><span class="pre">path.simplify_threshold</span></code> parameter.</p>

<p>Changes related to how line segments are simplified were made

in version 2.1. Rendering time will still be improved by these

parameters prior to 2.1, but rendering time for some kinds of

data will be vastly improved in versions 2.1 and greater.</p>

</div>

</section>

<h2>Marker subsampling<a class="headerlink" href="#marker-subsampling" title="Link to this heading">#</a></h2>

<p>Markers can also be simplified, albeit less robustly than line

segments. Marker subsampling is only available to <a class="reference internal" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D" title="matplotlib.lines.Line2D"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Line2D</span></code></a> objects

(through the <code class="docutils literal notranslate"><span class="pre">markevery</span></code> property). Wherever <a class="reference internal" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D" title="matplotlib.lines.Line2D"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Line2D</span></code></a> construction

parameters are passed through, such as <a class="reference internal" href="../../api/_as_gen/matplotlib.pyplot.plot.html#matplotlib.pyplot.plot" title="matplotlib.pyplot.plot"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pyplot.plot</span></code></a> and <a class="reference internal" href="../../api/_as_gen/matplotlib.axes.Axes.plot.html#matplotlib.axes.Axes.plot" title="matplotlib.axes.Axes.plot"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Axes.plot</span></code></a>,

the <code class="docutils literal notranslate"><span class="pre">markevery</span></code> parameter can be used:</p>

<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">markevery</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>

</pre></div>

</div>

<p>The <code class="docutils literal notranslate"><span class="pre">markevery</span></code> argument allows for naive subsampling, or an

attempt at evenly spaced (along the <em>x</em> axis) sampling. See the

<a class="reference internal" href="../../gallery/lines_bars_and_markers/markevery_demo.html"><span class="doc">Markevery Demo</span></a>

for more information.</p>

</section>

<h2>Splitting lines into smaller chunks<a class="headerlink" href="#splitting-lines-into-smaller-chunks" title="Link to this heading">#</a></h2>

<p>If you are using the Agg backend (see <a class="reference internal" href="backends.html#what-is-a-backend"><span class="std std-ref">What is a backend?</span></a>),

then you can make use of <code class="docutils literal notranslate"><a class="reference internal" href="../../tutorials/introductory/customizing.html?highlight=agg.path.chunksize#matplotlibrc-sample"><span class="std std-ref"><span class="pre">rcParams["agg.path.chunksize"]</span></span></a></code> (default: <code class="docutils literal notranslate"><span class="pre">0</span></code>)

This allows users to specify a chunk size, and any lines with

greater than that many vertices will be split into multiple

lines, each of which has no more than <code class="docutils literal notranslate"><span class="pre">agg.path.chunksize</span></code>

many vertices. (Unless <code class="docutils literal notranslate"><span class="pre">agg.path.chunksize</span></code> is zero, in

which case there is no chunking.) For some kind of data,

chunking the line up into reasonable sizes can greatly

decrease rendering time.</p>

<p>The following script will first display the data without any

chunk size restriction, and then display the same data with

a chunk size of 10,000. The difference can best be seen when

the figures are large, try maximizing the GUI and then

interacting with them:</p>

<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>

<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>

<span class="kn">import</span> <span class="nn">matplotlib</span> <span class="k">as</span> <span class="nn">mpl</span>

<span class="c1"># Setup, and create the data to plot</span>

<span class="n">mpl</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s1">'agg.path.chunksize'</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>

</pre></div>

</div>

</section>

<h2>Legends<a class="headerlink" href="#legends" title="Link to this heading">#</a></h2>

<p>The default legend behavior for axes attempts to find the location

that covers the fewest data points (<code class="docutils literal notranslate"><span class="pre">loc='best'</span></code>). This can be a

very expensive computation if there are lots of data points. In

this case, you may want to provide a specific location.</p>

</section>

<h2>Using the <em>fast</em> style<a class="headerlink" href="#using-the-fast-style" title="Link to this heading">#</a></h2>

<p>The <em>fast</em> style can be used to automatically set

simplification and chunking parameters to reasonable

settings to speed up plotting large amounts of data.

The following code runs it:</p>

<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">matplotlib.style</span> <span class="k">as</span> <span class="nn">mplstyle</span>

<span class="n">mplstyle</span><span class="o">.</span><span class="n">use</span><span class="p">(</span><span class="s1">'fast'</span><span class="p">)</span>

</pre></div>

</div>

<p>It is very lightweight, so it works well with other

styles. Be sure the fast style is applied last

so that other styles do not overwrite the settings:</p>

<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">mplstyle</span><span class="o">.</span><span class="n">use</span><span class="p">([</span><span class="s1">'dark_background'</span><span class="p">,</span> <span class="s1">'ggplot'</span><span class="p">,</span> <span class="s1">'fast'</span><span class="p">])</span>

</pre></div>

</div>

</section>

</article>

</div>

<i class="fa-solid fa-list"></i> On this page

</div>

Line segment simplification

</a>

</li>

Marker subsampling

</a>

</li>

Splitting lines into smaller chunks

</a>

</li>

Legends

</a>

</li>

Using the

<em>

fast

</em>

style

</a>

</li>

</ul>

</nav>

</div>

</div>

</footer>

</main>

</div>

</p>

</div>

Created using <a href="http://sphinx-doc.org/">Sphinx</a> 7.2.6.<br>

</p>

</div>

Built from v3.7.4-2-g03947d07cf.

<br/>

</p>

</div>

</footer>

</body>

</html>

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

FilesExpand file tree

performance.html

Latest commit

History

performance.html

File metadata and controls