matplotlib.github.com/_modules/matplotlib/cm.html at master · TanShiKai/matplotlib.github.com

History

573 lines (458 loc) · 52.4 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

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

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

<head>

<title>matplotlib.cm — Matplotlib 3.1.1 documentation</title>

type="text/css" />

type="text/css" />

title="Search within Matplotlib 3.1.1 documentation"

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

</head>

<body>

<div style="float: left; position: absolute; width: 496px; bottom: 0; padding-bottom: 24px">Version 3.1.1</div>

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

</div>

<ul>

<li><a href="../../users/installing.html">Installation</a></li>

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

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

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

<li><a href="../../devel/index.html">Contributing</a></li>

</ul>

</nav>

<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>

<li><a href="../../contents.html">contents</a> »</li>

<li><a href="../index.html" >Module code</a> »</li>

<li><a href="../matplotlib.html" accesskey="U">matplotlib</a> »</li>

</ul>

</div>

<h3>Quick search</h3>

</form>

</div>

<h3>Related Topics</h3>

<ul>

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

<li><a href="../index.html">Module code</a><ul>

<li><a href="../matplotlib.html">matplotlib</a><ul>

</ul></li>

</ul>

</div>

<h1>Source code for matplotlib.cm</h1><div class="highlight"><pre>

"""

Builtin colormaps, colormap handling utilities, and the `ScalarMappable` mixin.

.. seealso::

:doc:`/gallery/color/colormap_reference` for a list of builtin

colormaps.

:doc:`/tutorials/colors/colormap-manipulation` for examples of how to

make colormaps and

:doc:`/tutorials/colors/colormaps` an in-depth discussion of

choosing colormaps.

:doc:`/tutorials/colors/colormapnorms` for more details about data

normalization

"""

import functools

import numpy as np

from numpy import ma

import matplotlib as mpl

import matplotlib.colors as colors

import matplotlib.cbook as cbook

from matplotlib._cm import datad

from matplotlib._cm_listed import cmaps as cmaps_listed

cmap_d = {}

# reverse all the colormaps.

# reversed colormaps have '_r' appended to the name.

def _reverser(f, x=None):

"""Helper such that ``_reverser(f)(x) == f(1 - x)``."""

if x is None:

# Returning a partial object keeps it picklable.

return functools.partial(_reverser, f)

return f(1 - x)

<div class="viewcode-block" id="revcmap"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.revcmap">[docs]</a>def revcmap(data):

"""Can only handle specification *data* in dictionary format."""

data_r = {}

for key, val in data.items():

if callable(val):

valnew = _reverser(val)

# This doesn't work: lambda x: val(1-x)

# The same "val" (the first one) is used

# each time, so the colors are identical

# and the result is shades of gray.

else:

# Flip x and exchange the y values facing x = 0 and x = 1.

valnew = [(1.0 - x, y1, y0) for x, y0, y1 in reversed(val)]

data_r[key] = valnew

return data_r</div>

def _reverse_cmap_spec(spec):

"""Reverses cmap specification *spec*, can handle both dict and tuple

type specs."""

if 'listed' in spec:

return {'listed': spec['listed'][::-1]}

if 'red' in spec:

return revcmap(spec)

else:

revspec = list(reversed(spec))

if len(revspec[0]) == 2: # e.g., (1, (1.0, 0.0, 1.0))

revspec = [(1.0 - a, b) for a, b in revspec]

return revspec

def _generate_cmap(name, lutsize):

"""Generates the requested cmap from its *name*. The lut size is

*lutsize*."""

spec = datad[name]

# Generate the colormap object.

if 'red' in spec:

return colors.LinearSegmentedColormap(name, spec, lutsize)

elif 'listed' in spec:

return colors.ListedColormap(spec['listed'], name)

else:

return colors.LinearSegmentedColormap.from_list(name, spec, lutsize)

LUTSIZE = mpl.rcParams['image.lut']

# Generate the reversed specifications (all at once, to avoid

# modify-when-iterating).

datad.update({cmapname + '_r': _reverse_cmap_spec(spec)

for cmapname, spec in datad.items()})

# Precache the cmaps with ``lutsize = LUTSIZE``.

# Also add the reversed ones added in the section above:

for cmapname in datad:

cmap_d[cmapname] = _generate_cmap(cmapname, LUTSIZE)

cmap_d.update(cmaps_listed)

locals().update(cmap_d)

# Continue with definitions ...

<div class="viewcode-block" id="register_cmap"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.register_cmap">[docs]</a>def register_cmap(name=None, cmap=None, data=None, lut=None):

"""

Add a colormap to the set recognized by :func:`get_cmap`.

It can be used in two ways::

register_cmap(name='swirly', cmap=swirly_cmap)

register_cmap(name='choppy', data=choppydata, lut=128)

In the first case, *cmap* must be a :class:`matplotlib.colors.Colormap`

instance. The *name* is optional; if absent, the name will

be the :attr:`~matplotlib.colors.Colormap.name` attribute of the *cmap*.

In the second case, the three arguments are passed to

the :class:`~matplotlib.colors.LinearSegmentedColormap` initializer,

and the resulting colormap is registered.

"""

if name is None:

try:

name = cmap.name

except AttributeError:

raise ValueError("Arguments must include a name or a Colormap")

if not isinstance(name, str):

raise ValueError("Colormap name must be a string")

if isinstance(cmap, colors.Colormap):

cmap_d[name] = cmap

return

# For the remainder, let exceptions propagate.

if lut is None:

lut = mpl.rcParams['image.lut']

cmap = colors.LinearSegmentedColormap(name, data, lut)

cmap_d[name] = cmap</div>

<div class="viewcode-block" id="get_cmap"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.get_cmap">[docs]</a>def get_cmap(name=None, lut=None):

"""

Get a colormap instance, defaulting to rc values if *name* is None.

Colormaps added with :func:`register_cmap` take precedence over

built-in colormaps.

If *name* is a :class:`matplotlib.colors.Colormap` instance, it will be

returned.

If *lut* is not None it must be an integer giving the number of

entries desired in the lookup table, and *name* must be a standard

mpl colormap name.

"""

if name is None:

name = mpl.rcParams['image.cmap']

if isinstance(name, colors.Colormap):

return name

if name in cmap_d:

if lut is None:

return cmap_d[name]

else:

return cmap_d[name]._resample(lut)

else:

raise ValueError(

"Colormap %s is not recognized. Possible values are: %s"

% (name, ', '.join(sorted(cmap_d))))</div>

<div class="viewcode-block" id="ScalarMappable"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.ScalarMappable">[docs]</a>class ScalarMappable(object):

"""

This is a mixin class to support scalar data to RGBA mapping.

The ScalarMappable makes use of data normalization before returning

RGBA colors from the given colormap.

"""

def __init__(self, norm=None, cmap=None):

r"""

Parameters

----------

norm : :class:`matplotlib.colors.Normalize` instance

The normalizing object which scales data, typically into the

interval ``[0, 1]``.

If *None*, *norm* defaults to a *colors.Normalize* object which

initializes its scaling based on the first data processed.

cmap : str or :class:`~matplotlib.colors.Colormap` instance

The colormap used to map normalized data values to RGBA colors.

"""

self.callbacksSM = cbook.CallbackRegistry()

if cmap is None:

cmap = get_cmap()

if norm is None:

norm = colors.Normalize()

self._A = None

#: The Normalization instance of this ScalarMappable.

self.norm = norm

#: The Colormap instance of this ScalarMappable.

self.cmap = get_cmap(cmap)

#: The last colorbar associated with this ScalarMappable. May be None.

self.colorbar = None

self.update_dict = {'array': False}

<div class="viewcode-block" id="ScalarMappable.to_rgba"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.ScalarMappable.to_rgba">[docs]</a> def to_rgba(self, x, alpha=None, bytes=False, norm=True):

"""

Return a normalized rgba array corresponding to *x*.

In the normal case, *x* is a 1-D or 2-D sequence of scalars, and

the corresponding ndarray of rgba values will be returned,

based on the norm and colormap set for this ScalarMappable.

There is one special case, for handling images that are already

rgb or rgba, such as might have been read from an image file.

If *x* is an ndarray with 3 dimensions,

and the last dimension is either 3 or 4, then it will be

treated as an rgb or rgba array, and no mapping will be done.

The array can be uint8, or it can be floating point with

values in the 0-1 range; otherwise a ValueError will be raised.

If it is a masked array, the mask will be ignored.

If the last dimension is 3, the *alpha* kwarg (defaulting to 1)

will be used to fill in the transparency. If the last dimension

is 4, the *alpha* kwarg is ignored; it does not

replace the pre-existing alpha. A ValueError will be raised

if the third dimension is other than 3 or 4.

In either case, if *bytes* is *False* (default), the rgba

array will be floats in the 0-1 range; if it is *True*,

the returned rgba array will be uint8 in the 0 to 255 range.

If norm is False, no normalization of the input data is

performed, and it is assumed to be in the range (0-1).

"""

# First check for special case, image input:

try:

if x.ndim == 3:

if x.shape[2] == 3:

if alpha is None:

alpha = 1

if x.dtype == np.uint8:

alpha = np.uint8(alpha * 255)

m, n = x.shape[:2]

xx = np.empty(shape=(m, n, 4), dtype=x.dtype)

xx[:, :, :3] = x

xx[:, :, 3] = alpha

elif x.shape[2] == 4:

xx = x

else:

raise ValueError("third dimension must be 3 or 4")

if xx.dtype.kind == 'f':

if norm and (xx.max() > 1 or xx.min() < 0):

raise ValueError("Floating point image RGB values "

"must be in the 0..1 range.")

if bytes:

xx = (xx * 255).astype(np.uint8)

elif xx.dtype == np.uint8:

if not bytes:

xx = xx.astype(np.float32) / 255

else:

raise ValueError("Image RGB array must be uint8 or "

"floating point; found %s" % xx.dtype)

return xx

except AttributeError:

# e.g., x is not an ndarray; so try mapping it

pass

# This is the normal case, mapping a scalar array:

x = ma.asarray(x)

if norm:

x = self.norm(x)

rgba = self.cmap(x, alpha=alpha, bytes=bytes)

return rgba</div>

<div class="viewcode-block" id="ScalarMappable.set_array"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.ScalarMappable.set_array">[docs]</a> def set_array(self, A):

"""Set the image array from numpy array *A*.

Parameters

----------

A : ndarray

"""

self._A = A

self.update_dict['array'] = True</div>

<div class="viewcode-block" id="ScalarMappable.get_array"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.ScalarMappable.get_array">[docs]</a> def get_array(self):

'Return the array'

return self._A</div>

<div class="viewcode-block" id="ScalarMappable.get_cmap"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.ScalarMappable.get_cmap">[docs]</a> def get_cmap(self):

'return the colormap'

return self.cmap</div>

<div class="viewcode-block" id="ScalarMappable.get_clim"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.ScalarMappable.get_clim">[docs]</a> def get_clim(self):

'return the min, max of the color limits for image scaling'

return self.norm.vmin, self.norm.vmax</div>

<div class="viewcode-block" id="ScalarMappable.set_clim"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.ScalarMappable.set_clim">[docs]</a> def set_clim(self, vmin=None, vmax=None):

"""

set the norm limits for image scaling; if *vmin* is a length2

sequence, interpret it as ``(vmin, vmax)`` which is used to

support setp

ACCEPTS: a length 2 sequence of floats; may be overridden in methods

that have ``vmin`` and ``vmax`` kwargs.

"""

if vmax is None:

try:

vmin, vmax = vmin

except (TypeError, ValueError):

pass

if vmin is not None:

self.norm.vmin = colors._sanitize_extrema(vmin)

if vmax is not None:

self.norm.vmax = colors._sanitize_extrema(vmax)

self.changed()</div>

<div class="viewcode-block" id="ScalarMappable.get_alpha"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.ScalarMappable.get_alpha">[docs]</a> def get_alpha(self):

"""

Returns

-------

alpha : float

Always returns 1.

"""

# This method is intended to be overridden by Artist sub-classes

return 1.</div>

<div class="viewcode-block" id="ScalarMappable.set_cmap"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.ScalarMappable.set_cmap">[docs]</a> def set_cmap(self, cmap):

"""

set the colormap for luminance data

Parameters

----------

cmap : colormap or registered colormap name

"""

cmap = get_cmap(cmap)

self.cmap = cmap

self.changed()</div>

<div class="viewcode-block" id="ScalarMappable.set_norm"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.ScalarMappable.set_norm">[docs]</a> def set_norm(self, norm):

"""Set the normalization instance.

Parameters

----------

norm : `.Normalize`

Notes

-----

If there are any colorbars using the mappable for this norm, setting

the norm of the mappable will reset the norm, locator, and formatters

on the colorbar to default.

"""

if norm is None:

norm = colors.Normalize()

self.norm = norm

self.changed()</div>

<div class="viewcode-block" id="ScalarMappable.autoscale"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.ScalarMappable.autoscale">[docs]</a> def autoscale(self):

"""

Autoscale the scalar limits on the norm instance using the

current array

"""

if self._A is None:

raise TypeError('You must first set_array for mappable')

self.norm.autoscale(self._A)

self.changed()</div>

<div class="viewcode-block" id="ScalarMappable.autoscale_None"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.ScalarMappable.autoscale_None">[docs]</a> def autoscale_None(self):

"""

Autoscale the scalar limits on the norm instance using the

current array, changing only limits that are None

"""

if self._A is None:

raise TypeError('You must first set_array for mappable')

self.norm.autoscale_None(self._A)

self.changed()</div>

<div class="viewcode-block" id="ScalarMappable.add_checker"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.ScalarMappable.add_checker">[docs]</a> def add_checker(self, checker):

"""

Add an entry to a dictionary of boolean flags

that are set to True when the mappable is changed.

"""

self.update_dict[checker] = False</div>

<div class="viewcode-block" id="ScalarMappable.check_update"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.ScalarMappable.check_update">[docs]</a> def check_update(self, checker):

"""

If mappable has changed since the last check,

return True; else return False

"""

if self.update_dict[checker]:

return True

return False</div>

<div class="viewcode-block" id="ScalarMappable.changed"><a class="viewcode-back" href="../../api/cm_api.html#matplotlib.cm.ScalarMappable.changed">[docs]</a> def changed(self):

"""

Call this whenever the mappable is changed to notify all the

callbackSM listeners to the 'changed' signal

"""

self.callbacksSM.process('changed', self)

for key in self.update_dict:

self.update_dict[key] = True

self.stale = True</div></div>

</pre></div>

</div>

</div>

Last updated on Oct 28, 2019.

Created using

<a href="http://sphinx-doc.org/">Sphinx</a> 1.8.5.

Doc version v3.1.1-53-gb0c4777d3.

</div>

(function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){

(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),

m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)

})(window,document,'script','//www.google-analytics.com/analytics.js','ga');

ga('create', 'UA-55954603-1', 'auto');

ga('send', 'pageview');

</script>

</body>

</footer>

</html>

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

FilesExpand file tree

cm.html

Latest commit

History

cm.html

File metadata and controls