matplotlib.github.com/2.1.2/api/image_api.html at main · matplotlib/matplotlib.github.com

History

545 lines (483 loc) · 31 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

<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"

"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">

<head>

<title>image — Matplotlib 2.1.2 documentation</title>

type="text/css" />

type="text/css" />

var DOCUMENTATION_OPTIONS = {

URL_ROOT: '../',

VERSION: '2.1.2',

COLLAPSE_INDEX: false,

FILE_SUFFIX: '.html',

HAS_SOURCE: true,

SOURCELINK_SUFFIX: '.txt'

};

</script>

title="Search within Matplotlib 2.1.2 documentation"

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

</head>

<body>

<div id="unreleased-message"> You are reading an old version of the documentation (v2.1.2). For the latest version see <a href="https://matplotlib.org/stable/api/image_api.html">https://matplotlib.org/stable/api/image_api.html</a></div>

<div style="float: left; position: absolute; width: 496px; bottom: 0; padding-bottom: 24px">Version 2.1.2</div>

<div id="forkongithub"><a href="https://github.com/matplotlib/matplotlib">Fork me on GitHub</a></div>

</div>

<h3>Navigation</h3>

<ul>

<a href="../genindex.html" title="General Index"

accesskey="I">index</a></li>

<a href="../py-modindex.html" title="Python Module Index"

>modules</a> |</li>

<a href="legend_api.html" title="legend and legend_handler"

accesskey="N">next</a> |</li>

<a href="_as_gen/matplotlib.gridspec.GridSpecFromSubplotSpec.html" title="matplotlib.gridspec.GridSpecFromSubplotSpec"

accesskey="P">previous</a> |</li>

<li><a href="../gallery/index.html">examples</a>| </li>

<li><a href="../tutorials/index.html">tutorials</a>| </li>

<li><a href="pyplot_summary.html">pyplot</a>| </li>

<li><a href="index.html" accesskey="U">The Matplotlib API</a> »</li>

</ul>

</div>

</a>

</a>

Travis-CI: <a href="https://travis-ci.org/matplotlib/matplotlib">

</a>

<h3><a href="../contents.html">Table Of Contents</a></h3>

<ul>

<li><a class="reference internal" href="#">image</a><ul>

<li><a class="reference internal" href="#module-matplotlib.image"><code class="docutils literal">matplotlib.image</code></a></li>

</ul>

</li>

</ul>

<h3>Related Topics</h3>

<ul>

<li><a href="../contents.html">Documentation overview</a><ul>

<li><a href="index.html">The Matplotlib API</a><ul>

<li>Previous: <a href="_as_gen/matplotlib.gridspec.GridSpecFromSubplotSpec.html" title="previous chapter">matplotlib.gridspec.GridSpecFromSubplotSpec</a></li>

<li>Next: <a href="legend_api.html" title="next chapter">legend and legend_handler</a></li>

</ul></li>

</ul>

</div>

<li><a href="../_sources/api/image_api.rst.txt"

rel="nofollow">Show Source</a></li>

</ul>

</div>

<h3>Quick search</h3>

</form>

</div>

</div>

<h1>image<a class="headerlink" href="#image" title="Permalink to this headline">¶</a></h1>

<h2><a class="reference internal" href="#module-matplotlib.image" title="matplotlib.image"><code class="xref py py-mod docutils literal">matplotlib.image</code></a><a class="headerlink" href="#module-matplotlib.image" title="Permalink to this headline">¶</a></h2>

The image module supports basic image loading, rescaling and display

operations.

class <code class="descclassname">matplotlib.image.</code><code class="descname">AxesImage</code>(ax, cmap=None, norm=None, interpolation=None, origin=None, extent=None, filternorm=1, filterrad=4.0, resample=False, **kwargs)<a class="headerlink" href="#matplotlib.image.AxesImage" title="Permalink to this definition">¶</a></dt>

<dd>Bases: <code class="xref py py-class docutils literal">matplotlib.image._ImageBase</code>

interpolation and cmap default to their rc settings

cmap is a colors.Colormap instance

norm is a colors.Normalize instance to map luminance to 0-1

extent is data axes (left, right, bottom, top) for making image plots

registered with data plots. Default is to label the pixel

centers with the zero-based row and column indices.

Additional kwargs are matplotlib.artist properties

<code class="descname">get_cursor_data</code>(event)<a class="headerlink" href="#matplotlib.image.AxesImage.get_cursor_data" title="Permalink to this definition">¶</a></dt>

<dd>Get the cursor data for a given event

</dd></dl>

<code class="descname">get_extent</code>()<a class="headerlink" href="#matplotlib.image.AxesImage.get_extent" title="Permalink to this definition">¶</a></dt>

<dd>Get the image extent: left, right, bottom, top

</dd></dl>

<code class="descname">get_window_extent</code>(renderer=None)<a class="headerlink" href="#matplotlib.image.AxesImage.get_window_extent" title="Permalink to this definition">¶</a></dt>

<code class="descname">make_image</code>(renderer, magnification=1.0, unsampled=False)<a class="headerlink" href="#matplotlib.image.AxesImage.make_image" title="Permalink to this definition">¶</a></dt>

<code class="descname">set_extent</code>(extent)<a class="headerlink" href="#matplotlib.image.AxesImage.set_extent" title="Permalink to this definition">¶</a></dt>

<dd>extent is data axes (left, right, bottom, top) for making image plots

This updates ax.dataLim, and, if autoscaling, sets viewLim

to tightly fit the image, regardless of dataLim. Autoscaling

state is not changed, so following this with ax.autoscale_view

will redo the autoscaling in accord with dataLim.

</dd></dl>

class <code class="descclassname">matplotlib.image.</code><code class="descname">BboxImage</code>(bbox, cmap=None, norm=None, interpolation=None, origin=None, filternorm=1, filterrad=4.0, resample=False, interp_at_native=True, **kwargs)<a class="headerlink" href="#matplotlib.image.BboxImage" title="Permalink to this definition">¶</a></dt>

<dd>Bases: <code class="xref py py-class docutils literal">matplotlib.image._ImageBase</code>

The Image class whose size is determined by the given bbox.

cmap is a colors.Colormap instance

norm is a colors.Normalize instance to map luminance to 0-1

interp_at_native is a flag that determines whether or not

interpolation should still be applied when the image is

displayed at its native resolution. A common use case for this

is when displaying an image for annotational purposes; it is

treated similarly to Photoshop (interpolation is only used when

displaying the image at non-native resolutions).

kwargs are an optional list of Artist keyword args

<code class="descname">contains</code>(mouseevent)<a class="headerlink" href="#matplotlib.image.BboxImage.contains" title="Permalink to this definition">¶</a></dt>

<dd>Test whether the mouse event occurred within the image.

</dd></dl>

<code class="descname">get_transform</code>()<a class="headerlink" href="#matplotlib.image.BboxImage.get_transform" title="Permalink to this definition">¶</a></dt>

<code class="descname">get_window_extent</code>(renderer=None)<a class="headerlink" href="#matplotlib.image.BboxImage.get_window_extent" title="Permalink to this definition">¶</a></dt>

<code class="descname">make_image</code>(renderer, magnification=1.0, unsampled=False)<a class="headerlink" href="#matplotlib.image.BboxImage.make_image" title="Permalink to this definition">¶</a></dt>

</dd></dl>

class <code class="descclassname">matplotlib.image.</code><code class="descname">FigureImage</code>(fig, cmap=None, norm=None, offsetx=0, offsety=0, origin=None, **kwargs)<a class="headerlink" href="#matplotlib.image.FigureImage" title="Permalink to this definition">¶</a></dt>

<dd>Bases: <code class="xref py py-class docutils literal">matplotlib.image._ImageBase</code>

cmap is a colors.Colormap instance

norm is a colors.Normalize instance to map luminance to 0-1

kwargs are an optional list of Artist keyword args

<code class="descname">get_extent</code>()<a class="headerlink" href="#matplotlib.image.FigureImage.get_extent" title="Permalink to this definition">¶</a></dt>

<dd>Get the image extent: left, right, bottom, top

</dd></dl>

<code class="descname">make_image</code>(renderer, magnification=1.0, unsampled=False)<a class="headerlink" href="#matplotlib.image.FigureImage.make_image" title="Permalink to this definition">¶</a></dt>

<dd>Set the image array.

</dd></dl>

<code class="descname">zorder</code> = 0<a class="headerlink" href="#matplotlib.image.FigureImage.zorder" title="Permalink to this definition">¶</a></dt>

</dd></dl>

class <code class="descclassname">matplotlib.image.</code><code class="descname">NonUniformImage</code>(ax, **kwargs)<a class="headerlink" href="#matplotlib.image.NonUniformImage" title="Permalink to this definition">¶</a></dt>

<dd>Bases: <a class="reference internal" href="#matplotlib.image.AxesImage" title="matplotlib.image.AxesImage"><code class="xref py py-class docutils literal">matplotlib.image.AxesImage</code></a>

kwargs are identical to those for AxesImage, except

that ‘nearest’ and ‘bilinear’ are the only supported ‘interpolation’

options.

<code class="descname">get_extent</code>()<a class="headerlink" href="#matplotlib.image.NonUniformImage.get_extent" title="Permalink to this definition">¶</a></dt>

<code class="descname">make_image</code>(renderer, magnification=1.0, unsampled=False)<a class="headerlink" href="#matplotlib.image.NonUniformImage.make_image" title="Permalink to this definition">¶</a></dt>

<code class="descname">set_array</code>(*args)<a class="headerlink" href="#matplotlib.image.NonUniformImage.set_array" title="Permalink to this definition">¶</a></dt>

<dd>Set the grid for the pixel centers, and the pixel values.

<dt>x and y are monotonic 1-D ndarrays of lengths N and M,</dt>

<dd>respectively, specifying pixel centers</dd>

<dt>A is an (M,N) ndarray or masked array of values to be</dt>

<dd>colormapped, or a (M,N,3) RGB array, or a (M,N,4) RGBA

array.</dd>

</dl>

</div></blockquote>

</dd></dl>

<code class="descname">set_filternorm</code>(s)<a class="headerlink" href="#matplotlib.image.NonUniformImage.set_filternorm" title="Permalink to this definition">¶</a></dt>

<code class="descname">set_filterrad</code>(s)<a class="headerlink" href="#matplotlib.image.NonUniformImage.set_filterrad" title="Permalink to this definition">¶</a></dt>

<code class="descname">set_interpolation</code>(s)<a class="headerlink" href="#matplotlib.image.NonUniformImage.set_interpolation" title="Permalink to this definition">¶</a></dt>

</dd></dl>

class <code class="descclassname">matplotlib.image.</code><code class="descname">PcolorImage</code>(ax, x=None, y=None, A=None, cmap=None, norm=None, **kwargs)<a class="headerlink" href="#matplotlib.image.PcolorImage" title="Permalink to this definition">¶</a></dt>

Make a pcolor-style plot with an irregular rectangular grid.

This uses a variation of the original irregular image code,

and it is used by pcolorfast for the corresponding grid type.

cmap defaults to its rc setting

cmap is a colors.Colormap instance

norm is a colors.Normalize instance to map luminance to 0-1

Additional kwargs are matplotlib.artist properties

<code class="descname">get_cursor_data</code>(event)<a class="headerlink" href="#matplotlib.image.PcolorImage.get_cursor_data" title="Permalink to this definition">¶</a></dt>

<dd>Get the cursor data for a given event

</dd></dl>

<code class="descname">make_image</code>(renderer, magnification=1.0, unsampled=False)<a class="headerlink" href="#matplotlib.image.PcolorImage.make_image" title="Permalink to this definition">¶</a></dt>

<code class="descname">set_array</code>(*args)<a class="headerlink" href="#matplotlib.image.PcolorImage.set_array" title="Permalink to this definition">¶</a></dt>

<dd>Set the grid for the rectangle boundaries, and the data values.

<dt>x and y are monotonic 1-D ndarrays of lengths N+1 and M+1,</dt>

<dd>respectively, specifying rectangle boundaries. If None,

they will be created as uniform arrays from 0 through N

and 0 through M, respectively.</dd>

<dt>A is an (M,N) ndarray or masked array of values to be</dt>

<dd>colormapped, or a (M,N,3) RGB array, or a (M,N,4) RGBA

array.</dd>

</dl>

</div></blockquote>

</dd></dl>

<code class="descclassname">matplotlib.image.</code><code class="descname">composite_images</code>(images, renderer, magnification=1.0)<a class="headerlink" href="#matplotlib.image.composite_images" title="Permalink to this definition">¶</a></dt>

<dd>Composite a number of RGBA images into one. The images are

composited in the order in which they appear in the <code class="xref py py-obj docutils literal">images</code> list.

<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body">images : list of Images

<div>Each must have a <code class="xref py py-obj docutils literal">make_image</code> method. For each image,

<code class="xref py py-obj docutils literal">can_composite</code> should return <a class="reference external" href="https://docs.python.org/3/library/constants.html#True" title="(in Python v3.6)"><code class="xref py py-obj docutils literal">True</code></a>, though this is not

enforced by this function. Each image must have a purely

affine transformation with no shear.

</div></blockquote>

renderer : RendererBase instance

magnification : float

<div>The additional magnification to apply for the renderer in use.

</div></blockquote>

</td>

</tr>

<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">tuple : image, offset_x, offset_y

<div>Returns the tuple:

<li>image: A numpy array of the same type as the input images.</li>

<li>offset_x, offset_y: The offset of the image (left, bottom)

in the output figure.</li>

</ul>

</div></blockquote>

</td>

</tr>

</tbody>

</table>

</dd></dl>

<code class="descclassname">matplotlib.image.</code><code class="descname">imread</code>(fname, format=None)<a class="headerlink" href="#matplotlib.image.imread" title="Permalink to this definition">¶</a></dt>

<dd>Read an image from a file into an array.

fname may be a string path, a valid URL, or a Python

file-like object. If using a file object, it must be opened in binary

mode.

If format is provided, will try to read file of that type,

otherwise the format is deduced from the filename. If nothing can

be deduced, PNG is tried.

Return value is a <code class="xref py py-class docutils literal">numpy.array</code>. For grayscale images, the

return array is MxN. For RGB images, the return value is MxNx3.

For RGBA images the return value is MxNx4.

matplotlib can only read PNGs natively, but if <a class="reference external" href="http://www.pythonware.com/products/pil/">PIL</a> is installed, it will

use it to load the image and return an array (if possible) which

can be used with <a class="reference internal" href="_as_gen/matplotlib.pyplot.imshow.html#matplotlib.pyplot.imshow" title="matplotlib.pyplot.imshow"><code class="xref py py-func docutils literal">imshow()</code></a>. Note, URL strings

may not be compatible with PIL. Check the PIL documentation for more

information.

</dd></dl>

<code class="descclassname">matplotlib.image.</code><code class="descname">imsave</code>(fname, arr, vmin=None, vmax=None, cmap=None, format=None, origin=None, dpi=100)<a class="headerlink" href="#matplotlib.image.imsave" title="Permalink to this definition">¶</a></dt>

<dd>Save an array as in image file.

The output formats available depend on the backend being used.

<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body">fname : str or file-like

<div>Path string to a filename, or a Python file-like object.

If format is None and fname is a string, the output

format is deduced from the extension of the filename.

</div></blockquote>

arr : array-like

<div>An MxN (luminance), MxNx3 (RGB) or MxNx4 (RGBA) array.

</div></blockquote>

vmin, vmax: [ None | scalar ]

<div>vmin and vmax set the color scaling for the image by fixing the

values that map to the colormap color limits. If either vmin

or vmax is None, that limit is determined from the arr

min/max value.

</div></blockquote>

cmap : matplotlib.colors.Colormap, optional

<div>For example, <code class="docutils literal">cm.viridis</code>. If <code class="docutils literal">None</code>, defaults to the

<code class="docutils literal">image.cmap</code> rcParam.

</div></blockquote>

format : str

<div>One of the file extensions supported by the active backend. Most

backends support png, pdf, ps, eps and svg.

</div></blockquote>

origin : [ ‘upper’ | ‘lower’ ]

<div>Indicates whether the <code class="docutils literal">(0, 0)</code> index of the array is in the

upper left or lower left corner of the axes. Defaults to the

<code class="docutils literal">image.origin</code> rcParam.

</div></blockquote>

dpi : int

<div>The DPI to store in the metadata of the file. This does not affect the

resolution of the output image.

</div></blockquote>

</td>

</tr>

</tbody>

</table>

</dd></dl>

<code class="descclassname">matplotlib.image.</code><code class="descname">pil_to_array</code>(pilImage)<a class="headerlink" href="#matplotlib.image.pil_to_array" title="Permalink to this definition">¶</a></dt>

<dd>Load a PIL image and return it as a numpy array.

Grayscale images are returned as <code class="docutils literal">(M, N)</code> arrays. RGB images are

returned as <code class="docutils literal">(M, N, 3)</code> arrays. RGBA images are returned as <code class="docutils literal">(M, N,

4)</code> arrays.

</dd></dl>

<code class="descclassname">matplotlib.image.</code><code class="descname">thumbnail</code>(infile, thumbfile, scale=0.1, interpolation='bilinear', preview=False)<a class="headerlink" href="#matplotlib.image.thumbnail" title="Permalink to this definition">¶</a></dt>

<dd>make a thumbnail of image in infile with output filename

thumbfile.

<dt>infile the image file – must be PNG or Pillow-readable if you</dt>

<dd>have <a class="reference external" href="http://python-pillow.org/">Pillow</a> installed</dd>

<dt>thumbfile</dt>

<dd>the thumbnail filename</dd>

<dt>scale</dt>

<dd>the scale factor for the thumbnail</dd>

<dt>interpolation</dt>

<dd>the interpolation scheme used in the resampling</dd>

<dt>preview</dt>

<dd>if True, the default backend (presumably a user interface

backend) will be used which will cause a figure to be raised

if <a class="reference internal" href="_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show"><code class="xref py py-func docutils literal">show()</code></a> is called. If it is False,

a pure image backend will be used depending on the extension,

‘png’->FigureCanvasAgg, ‘pdf’->FigureCanvasPdf,

‘svg’->FigureCanvasSVG</dd>

</dl>

</div></blockquote>

See examples/misc/image_thumbnail.py.

<a class="reference internal" href="../gallery/misc/image_thumbnail_sgskip.html#sphx-glr-gallery-misc-image-thumbnail-sgskip-py">Image Thumbnail</a>Return value is the figure instance containing the thumbnail

</dd></dl>

</div>

</div>

Last updated on Feb 08, 2018.

Created using <a

href="http://sphinx-doc.org/">Sphinx</a> 1.6.7.

</div>

</body>

</footer>

</html>

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

FilesExpand file tree

image_api.html

Latest commit

History

image_api.html

File metadata and controls