matplotlib.github.com/2.2.2/_modules/matplotlib/scale.html at main · matplotlib/matplotlib.github.com

History

743 lines (593 loc) · 86 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

671

672

673

674

675

676

677

678

679

680

681

682

683

684

685

686

687

688

689

690

691

692

693

694

695

696

697

698

699

700

701

702

703

704

705

706

707

708

709

710

711

712

713

714

715

716

717

718

719

720

721

722

723

724

725

726

727

728

729

730

731

732

733

734

735

736

737

738

739

740

741

742

743

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

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

<head>

<title>matplotlib.scale — Matplotlib 2.2.2 documentation</title>

type="text/css" />

type="text/css" />

var DOCUMENTATION_OPTIONS = {

URL_ROOT: '../../',

VERSION: '2.2.2',

COLLAPSE_INDEX: false,

FILE_SUFFIX: '.html',

HAS_SOURCE: true,

SOURCELINK_SUFFIX: '.txt'

};

</script>

title="Search within Matplotlib 2.2.2 documentation"

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

</head>

<body>

<div id="unreleased-message"> You are reading an old version of the documentation (v2.2.2). For the latest version see <a href="/stable/">https://matplotlib.org/stable/</a> </div>

<div style="float: left; position: absolute; width: 496px; bottom: 0; padding-bottom: 24px">Version 2.2.2</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>

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

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

<li><a href="../../api/pyplot_summary.html">pyplot</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.scale</h1><div class="highlight"><pre>

from __future__ import (absolute_import, division, print_function,

unicode_literals)

import six

import numpy as np

from numpy import ma

from matplotlib import cbook, docstring, rcParams

from matplotlib.ticker import (

NullFormatter, ScalarFormatter, LogFormatterSciNotation, LogitFormatter,

NullLocator, LogLocator, AutoLocator, AutoMinorLocator,

SymmetricalLogLocator, LogitLocator)

from matplotlib.transforms import Transform, IdentityTransform

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

"""

The base class for all scales.

Scales are separable transformations, working on a single dimension.

Any subclasses will want to override:

- :attr:`name`

- :meth:`get_transform`

- :meth:`set_default_locators_and_formatters`

And optionally:

- :meth:`limit_range_for_scale`

"""

<div class="viewcode-block" id="ScaleBase.get_transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.ScaleBase.get_transform">[docs]</a> def get_transform(self):

"""

Return the :class:`~matplotlib.transforms.Transform` object

associated with this scale.

"""

raise NotImplementedError()</div>

<div class="viewcode-block" id="ScaleBase.set_default_locators_and_formatters"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.ScaleBase.set_default_locators_and_formatters">[docs]</a> def set_default_locators_and_formatters(self, axis):

"""

Set the :class:`~matplotlib.ticker.Locator` and

:class:`~matplotlib.ticker.Formatter` objects on the given

axis to match this scale.

"""

raise NotImplementedError()</div>

<div class="viewcode-block" id="ScaleBase.limit_range_for_scale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.ScaleBase.limit_range_for_scale">[docs]</a> def limit_range_for_scale(self, vmin, vmax, minpos):

"""

Returns the range *vmin*, *vmax*, possibly limited to the

domain supported by this scale.

*minpos* should be the minimum positive value in the data.

This is used by log scales to determine a minimum value.

"""

return vmin, vmax</div></div>

<div class="viewcode-block" id="LinearScale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LinearScale">[docs]</a>class LinearScale(ScaleBase):

"""

The default linear scale.

"""

name = 'linear'

def __init__(self, axis, **kwargs):

pass

<div class="viewcode-block" id="LinearScale.set_default_locators_and_formatters"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LinearScale.set_default_locators_and_formatters">[docs]</a> def set_default_locators_and_formatters(self, axis):

"""

Set the locators and formatters to reasonable defaults for

linear scaling.

"""

axis.set_major_locator(AutoLocator())

axis.set_major_formatter(ScalarFormatter())

axis.set_minor_formatter(NullFormatter())

# update the minor locator for x and y axis based on rcParams

if rcParams['xtick.minor.visible']:

axis.set_minor_locator(AutoMinorLocator())

else:

axis.set_minor_locator(NullLocator())</div>

<div class="viewcode-block" id="LinearScale.get_transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LinearScale.get_transform">[docs]</a> def get_transform(self):

"""

The transform for linear scaling is just the

:class:`~matplotlib.transforms.IdentityTransform`.

"""

return IdentityTransform()</div></div>

<div class="viewcode-block" id="LogTransformBase"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogTransformBase">[docs]</a>class LogTransformBase(Transform):

input_dims = 1

output_dims = 1

is_separable = True

has_inverse = True

def __init__(self, nonpos='clip'):

Transform.__init__(self)

self._clip = {"clip": True, "mask": False}[nonpos]

<div class="viewcode-block" id="LogTransformBase.transform_non_affine"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogTransformBase.transform_non_affine">[docs]</a> def transform_non_affine(self, a):

# Ignore invalid values due to nans being passed to the transform

with np.errstate(divide="ignore", invalid="ignore"):

out = np.log(a)

out /= np.log(self.base)

if self._clip:

# SVG spec says that conforming viewers must support values up

# to 3.4e38 (C float); however experiments suggest that

# Inkscape (which uses cairo for rendering) runs into cairo's

# 24-bit limit (which is apparently shared by Agg).

# Ghostscript (used for pdf rendering appears to overflow even

# earlier, with the max value around 2 ** 15 for the tests to

# pass. On the other hand, in practice, we want to clip beyond

# np.log10(np.nextafter(0, 1)) ~ -323

# so 1000 seems safe.

out[a <= 0] = -1000

return out</div>

def __str__(self):

type(self).__name__, "clip" if self._clip else "mask")</div>

<div class="viewcode-block" id="InvertedLogTransformBase"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLogTransformBase">[docs]</a>class InvertedLogTransformBase(Transform):

input_dims = 1

output_dims = 1

is_separable = True

has_inverse = True

<div class="viewcode-block" id="InvertedLogTransformBase.transform_non_affine"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLogTransformBase.transform_non_affine">[docs]</a> def transform_non_affine(self, a):

return ma.power(self.base, a)</div>

def __str__(self):

return "{}()".format(type(self).__name__)</div>

<div class="viewcode-block" id="Log10Transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.Log10Transform">[docs]</a>class Log10Transform(LogTransformBase):

base = 10.0

<div class="viewcode-block" id="Log10Transform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.Log10Transform.inverted">[docs]</a> def inverted(self):

return InvertedLog10Transform()</div></div>

<div class="viewcode-block" id="InvertedLog10Transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLog10Transform">[docs]</a>class InvertedLog10Transform(InvertedLogTransformBase):

base = 10.0

<div class="viewcode-block" id="InvertedLog10Transform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLog10Transform.inverted">[docs]</a> def inverted(self):

return Log10Transform()</div></div>

<div class="viewcode-block" id="Log2Transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.Log2Transform">[docs]</a>class Log2Transform(LogTransformBase):

base = 2.0

<div class="viewcode-block" id="Log2Transform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.Log2Transform.inverted">[docs]</a> def inverted(self):

return InvertedLog2Transform()</div></div>

<div class="viewcode-block" id="InvertedLog2Transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLog2Transform">[docs]</a>class InvertedLog2Transform(InvertedLogTransformBase):

base = 2.0

<div class="viewcode-block" id="InvertedLog2Transform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLog2Transform.inverted">[docs]</a> def inverted(self):

return Log2Transform()</div></div>

<div class="viewcode-block" id="NaturalLogTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.NaturalLogTransform">[docs]</a>class NaturalLogTransform(LogTransformBase):

base = np.e

<div class="viewcode-block" id="NaturalLogTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.NaturalLogTransform.inverted">[docs]</a> def inverted(self):

return InvertedNaturalLogTransform()</div></div>

<div class="viewcode-block" id="InvertedNaturalLogTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedNaturalLogTransform">[docs]</a>class InvertedNaturalLogTransform(InvertedLogTransformBase):

base = np.e

<div class="viewcode-block" id="InvertedNaturalLogTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedNaturalLogTransform.inverted">[docs]</a> def inverted(self):

return NaturalLogTransform()</div></div>

<div class="viewcode-block" id="LogTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogTransform">[docs]</a>class LogTransform(LogTransformBase):

def __init__(self, base, nonpos='clip'):

LogTransformBase.__init__(self, nonpos)

self.base = base

<div class="viewcode-block" id="LogTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogTransform.inverted">[docs]</a> def inverted(self):

return InvertedLogTransform(self.base)</div></div>

<div class="viewcode-block" id="InvertedLogTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLogTransform">[docs]</a>class InvertedLogTransform(InvertedLogTransformBase):

def __init__(self, base):

InvertedLogTransformBase.__init__(self)

self.base = base

<div class="viewcode-block" id="InvertedLogTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLogTransform.inverted">[docs]</a> def inverted(self):

return LogTransform(self.base)</div></div>

<div class="viewcode-block" id="LogScale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogScale">[docs]</a>class LogScale(ScaleBase):

"""

A standard logarithmic scale. Care is taken so non-positive

values are not plotted.

For computational efficiency (to push as much as possible to Numpy

C code in the common cases), this scale provides different

transforms depending on the base of the logarithm:

- base 10 (:class:`Log10Transform`)

- base 2 (:class:`Log2Transform`)

- base e (:class:`NaturalLogTransform`)

- arbitrary base (:class:`LogTransform`)

"""

name = 'log'

# compatibility shim

LogTransformBase = LogTransformBase

Log10Transform = Log10Transform

InvertedLog10Transform = InvertedLog10Transform

Log2Transform = Log2Transform

InvertedLog2Transform = InvertedLog2Transform

NaturalLogTransform = NaturalLogTransform

InvertedNaturalLogTransform = InvertedNaturalLogTransform

LogTransform = LogTransform

InvertedLogTransform = InvertedLogTransform

"""

*basex*/*basey*:

The base of the logarithm

*nonposx*/*nonposy*: ['mask' | 'clip' ]

non-positive values in *x* or *y* can be masked as

invalid, or clipped to a very small positive number

*subsx*/*subsy*:

Where to place the subticks between each major tick.

Should be a sequence of integers. For example, in a log10

scale: ``[2, 3, 4, 5, 6, 7, 8, 9]``

will place 8 logarithmically spaced minor ticks between

each major tick.

"""

if axis.axis_name == 'x':

base = kwargs.pop('basex', 10.0)

subs = kwargs.pop('subsx', None)

nonpos = kwargs.pop('nonposx', 'clip')

else:

base = kwargs.pop('basey', 10.0)

subs = kwargs.pop('subsy', None)

nonpos = kwargs.pop('nonposy', 'clip')

if len(kwargs):

raise ValueError(("provided too many kwargs, can only pass "

"{'basex', 'subsx', nonposx'} or "

"{'basey', 'subsy', nonposy'}. You passed ") +

"{!r}".format(kwargs))

if nonpos not in ['mask', 'clip']:

raise ValueError("nonposx, nonposy kwarg must be 'mask' or 'clip'")

if base <= 0 or base == 1:

raise ValueError('The log base cannot be <= 0 or == 1')

if base == 10.0:

self._transform = self.Log10Transform(nonpos)

elif base == 2.0:

self._transform = self.Log2Transform(nonpos)

elif base == np.e:

self._transform = self.NaturalLogTransform(nonpos)

else:

self._transform = self.LogTransform(base, nonpos)

self.base = base

self.subs = subs

<div class="viewcode-block" id="LogScale.set_default_locators_and_formatters"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogScale.set_default_locators_and_formatters">[docs]</a> def set_default_locators_and_formatters(self, axis):

"""

Set the locators and formatters to specialized versions for

log scaling.

"""

axis.set_major_locator(LogLocator(self.base))

axis.set_major_formatter(LogFormatterSciNotation(self.base))

axis.set_minor_locator(LogLocator(self.base, self.subs))

axis.set_minor_formatter(

LogFormatterSciNotation(self.base,

labelOnlyBase=(self.subs is not None)))</div>

<div class="viewcode-block" id="LogScale.get_transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogScale.get_transform">[docs]</a> def get_transform(self):

"""

Return a :class:`~matplotlib.transforms.Transform` instance

appropriate for the given logarithm base.

"""

return self._transform</div>

<div class="viewcode-block" id="LogScale.limit_range_for_scale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogScale.limit_range_for_scale">[docs]</a> def limit_range_for_scale(self, vmin, vmax, minpos):

"""

Limit the domain to positive values.

"""

if not np.isfinite(minpos):

minpos = 1e-300 # This value should rarely if ever

# end up with a visible effect.

return (minpos if vmin <= 0 else vmin,

minpos if vmax <= 0 else vmax)</div></div>

<div class="viewcode-block" id="SymmetricalLogTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.SymmetricalLogTransform">[docs]</a>class SymmetricalLogTransform(Transform):

input_dims = 1

output_dims = 1

is_separable = True

has_inverse = True

def __init__(self, base, linthresh, linscale):

Transform.__init__(self)

self.base = base

self.linthresh = linthresh

self.linscale = linscale

self._linscale_adj = (linscale / (1.0 - self.base ** -1))

self._log_base = np.log(base)

<div class="viewcode-block" id="SymmetricalLogTransform.transform_non_affine"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.SymmetricalLogTransform.transform_non_affine">[docs]</a> def transform_non_affine(self, a):

sign = np.sign(a)

-self.linthresh,

self.linthresh,

copy=False)

log = sign * self.linthresh * (

self._linscale_adj +

ma.log(np.abs(masked) / self.linthresh) / self._log_base)

if masked.mask.any():

return ma.where(masked.mask, a * self._linscale_adj, log)

else:

return log</div>

<div class="viewcode-block" id="SymmetricalLogTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.SymmetricalLogTransform.inverted">[docs]</a> def inverted(self):

return InvertedSymmetricalLogTransform(self.base, self.linthresh,

self.linscale)</div></div>

<div class="viewcode-block" id="InvertedSymmetricalLogTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedSymmetricalLogTransform">[docs]</a>class InvertedSymmetricalLogTransform(Transform):

input_dims = 1

output_dims = 1

is_separable = True

has_inverse = True

def __init__(self, base, linthresh, linscale):

Transform.__init__(self)

symlog = SymmetricalLogTransform(base, linthresh, linscale)

self.base = base

self.linthresh = linthresh

self.invlinthresh = symlog.transform(linthresh)

self.linscale = linscale

<div class="viewcode-block" id="InvertedSymmetricalLogTransform.transform_non_affine"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedSymmetricalLogTransform.transform_non_affine">[docs]</a> def transform_non_affine(self, a):

masked = ma.masked_inside(a, -self.invlinthresh,

self.invlinthresh, copy=False)

exp = sign * self.linthresh * (

ma.power(self.base, (sign * (masked / self.linthresh))

- self._linscale_adj))

if masked.mask.any():

return ma.where(masked.mask, a / self._linscale_adj, exp)

else:

return exp</div>

<div class="viewcode-block" id="InvertedSymmetricalLogTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedSymmetricalLogTransform.inverted">[docs]</a> def inverted(self):

return SymmetricalLogTransform(self.base,

self.linthresh, self.linscale)</div></div>

<div class="viewcode-block" id="SymmetricalLogScale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.SymmetricalLogScale">[docs]</a>class SymmetricalLogScale(ScaleBase):

"""

The symmetrical logarithmic scale is logarithmic in both the

positive and negative directions from the origin.

Since the values close to zero tend toward infinity, there is a

need to have a range around zero that is linear. The parameter

*linthresh* allows the user to specify the size of this range

(-*linthresh*, *linthresh*).

"""

name = 'symlog'

# compatibility shim

SymmetricalLogTransform = SymmetricalLogTransform

InvertedSymmetricalLogTransform = InvertedSymmetricalLogTransform

"""

*basex*/*basey*:

The base of the logarithm

*linthreshx*/*linthreshy*:

A single float which defines the range (-*x*, *x*), within

which the plot is linear. This avoids having the plot go to

infinity around zero.

*subsx*/*subsy*:

Where to place the subticks between each major tick.

Should be a sequence of integers. For example, in a log10

scale: ``[2, 3, 4, 5, 6, 7, 8, 9]``

will place 8 logarithmically spaced minor ticks between

each major tick.

*linscalex*/*linscaley*:

This allows the linear range (-*linthresh* to *linthresh*)

to be stretched relative to the logarithmic range. Its

value is the number of decades to use for each half of the

linear range. For example, when *linscale* == 1.0 (the

default), the space used for the positive and negative

halves of the linear range will be equal to one decade in

the logarithmic range.

"""

if axis.axis_name == 'x':

linthresh = kwargs.pop('linthreshx', 2.0)

linscale = kwargs.pop('linscalex', 1.0)

else:

base = kwargs.pop('basey', 10.0)

linthresh = kwargs.pop('linthreshy', 2.0)

subs = kwargs.pop('subsy', None)

linscale = kwargs.pop('linscaley', 1.0)

if base <= 1.0:

raise ValueError("'basex/basey' must be larger than 1")

if linthresh <= 0.0:

raise ValueError("'linthreshx/linthreshy' must be positive")

if linscale <= 0.0:

raise ValueError("'linscalex/linthreshy' must be positive")

self._transform = self.SymmetricalLogTransform(base,

linthresh,

linscale)

self.base = base

self.linthresh = linthresh

self.linscale = linscale

self.subs = subs

<div class="viewcode-block" id="SymmetricalLogScale.set_default_locators_and_formatters"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.SymmetricalLogScale.set_default_locators_and_formatters">[docs]</a> def set_default_locators_and_formatters(self, axis):

"""

Set the locators and formatters to specialized versions for

symmetrical log scaling.

"""

axis.set_major_locator(SymmetricalLogLocator(self.get_transform()))

axis.set_minor_locator(SymmetricalLogLocator(self.get_transform(),

self.subs))

axis.set_minor_formatter(NullFormatter())</div>

<div class="viewcode-block" id="SymmetricalLogScale.get_transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.SymmetricalLogScale.get_transform">[docs]</a> def get_transform(self):

"""

Return a :class:`SymmetricalLogTransform` instance.

"""

return self._transform</div></div>

<div class="viewcode-block" id="LogitTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogitTransform">[docs]</a>class LogitTransform(Transform):

input_dims = 1

output_dims = 1

is_separable = True

has_inverse = True

Transform.__init__(self)

self._nonpos = nonpos

<div class="viewcode-block" id="LogitTransform.transform_non_affine"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogitTransform.transform_non_affine">[docs]</a> def transform_non_affine(self, a):

"""logit transform (base 10), masked or clipped"""

out = np.log10(a / (1 - a))

if self._clip: # See LogTransform for choice of clip value.

out[1 <= a] = 1000

return out</div>

<div class="viewcode-block" id="LogitTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogitTransform.inverted">[docs]</a> def inverted(self):

return LogisticTransform(self._nonpos)</div>

def __str__(self):

return "{}({!r})".format(type(self).__name__,

"clip" if self._clip else "mask")</div>

<div class="viewcode-block" id="LogisticTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogisticTransform">[docs]</a>class LogisticTransform(Transform):

input_dims = 1

output_dims = 1

is_separable = True

has_inverse = True

Transform.__init__(self)

self._nonpos = nonpos

<div class="viewcode-block" id="LogisticTransform.transform_non_affine"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogisticTransform.transform_non_affine">[docs]</a> def transform_non_affine(self, a):

"""logistic transform (base 10)"""

return 1.0 / (1 + 10**(-a))</div>

<div class="viewcode-block" id="LogisticTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogisticTransform.inverted">[docs]</a> def inverted(self):

return LogitTransform(self._nonpos)</div>

def __str__(self):

<div class="viewcode-block" id="LogitScale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogitScale">[docs]</a>class LogitScale(ScaleBase):

"""

Logit scale for data between zero and one, both excluded.

This scale is similar to a log scale close to zero and to one, and almost

linear around 0.5. It maps the interval ]0, 1[ onto ]-infty, +infty[.

"""

name = 'logit'

def __init__(self, axis, nonpos='mask'):

"""

*nonpos*: ['mask' | 'clip' ]

values beyond ]0, 1[ can be masked as invalid, or clipped to a number

very close to 0 or 1

"""

raise ValueError("nonposx, nonposy kwarg must be 'mask' or 'clip'")

self._transform = LogitTransform(nonpos)

<div class="viewcode-block" id="LogitScale.get_transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogitScale.get_transform">[docs]</a> def get_transform(self):

"""

Return a :class:`LogitTransform` instance.

"""

return self._transform</div>

<div class="viewcode-block" id="LogitScale.set_default_locators_and_formatters"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogitScale.set_default_locators_and_formatters">[docs]</a> def set_default_locators_and_formatters(self, axis):

# ..., 0.01, 0.1, 0.5, 0.9, 0.99, ...

axis.set_major_locator(LogitLocator())

axis.set_major_formatter(LogitFormatter())

axis.set_minor_locator(LogitLocator(minor=True))

axis.set_minor_formatter(LogitFormatter())</div>

<div class="viewcode-block" id="LogitScale.limit_range_for_scale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogitScale.limit_range_for_scale">[docs]</a> def limit_range_for_scale(self, vmin, vmax, minpos):

"""

Limit the domain to values between 0 and 1 (excluded).

"""

minpos = 1e-7 # This value should rarely if ever

# end up with a visible effect.

1 - minpos if vmax >= 1 else vmax)</div></div>

_scale_mapping = {

'linear': LinearScale,

'log': LogScale,

'symlog': SymmetricalLogScale,

'logit': LogitScale,

}

<div class="viewcode-block" id="get_scale_names"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.get_scale_names">[docs]</a>def get_scale_names():

return sorted(_scale_mapping)</div>

<div class="viewcode-block" id="scale_factory"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.scale_factory">[docs]</a>def scale_factory(scale, axis, **kwargs):

"""

Return a scale class by name.

ACCEPTS: [ %(names)s ]

"""

scale = scale.lower()

if scale is None:

scale = 'linear'

if scale not in _scale_mapping:

raise ValueError("Unknown scale type '%s'" % scale)

return _scale_mapping[scale](axis, **kwargs)</div>

scale_factory.__doc__ = cbook.dedent(scale_factory.__doc__) % \

{'names': " | ".join(get_scale_names())}

<div class="viewcode-block" id="register_scale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.register_scale">[docs]</a>def register_scale(scale_class):

"""

Register a new kind of scale.

*scale_class* must be a subclass of :class:`ScaleBase`.

"""

_scale_mapping[scale_class.name] = scale_class</div>

<div class="viewcode-block" id="get_scale_docs"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.get_scale_docs">[docs]</a>def get_scale_docs():

"""

Helper function for generating docstrings related to scales.

"""

docs = []

for name in get_scale_names():

scale_class = _scale_mapping[name]

docs.append(" '%s'" % name)

docs.append("")

class_docs = cbook.dedent(scale_class.__init__.__doc__)

class_docs = "".join([" %s\n" %

x for x in class_docs.split("\n")])

docs.append(class_docs)

docs.append("")

return "\n".join(docs)</div>

docstring.interpd.update(

scale=' | '.join([repr(x) for x in get_scale_names()]),

scale_docs=get_scale_docs().rstrip(),

)

</pre></div>

</div>

</div>

Last updated on Jun 28, 2018.

Created using

<ahref="http://sphinx-doc.org/">Sphinx</a> 1.7.5.

Doc version v2.2.2-101-g15e1eadd0.

</div>

</body>

</footer>

</html>

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

FilesExpand file tree

scale.html

Latest commit

History

scale.html

File metadata and controls