Codestin Search App

History

2163 lines (1838 loc) · 277 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

744

745

746

747

748

749

750

751

752

753

754

755

756

757

758

759

760

761

762

763

764

765

766

767

768

769

770

771

772

773

774

775

776

777

778

779

780

781

782

783

784

785

786

787

788

789

790

791

792

793

794

795

796

797

798

799

800

801

802

803

804

805

806

807

808

809

810

811

812

813

814

815

816

817

818

819

820

821

822

823

824

825

826

827

828

829

830

831

832

833

834

835

836

837

838

839

840

841

842

843

844

845

846

847

848

849

850

851

852

853

854

855

856

857

858

859

860

861

862

863

864

865

866

867

868

869

870

871

872

873

874

875

876

877

878

879

880

881

882

883

884

885

886

887

888

889

890

891

892

893

894

895

896

897

898

899

900

901

902

903

904

905

906

907

908

909

910

911

912

913

914

915

916

917

918

919

920

921

922

923

924

925

926

927

928

929

930

931

932

933

934

935

936

937

938

939

940

941

942

943

944

945

946

947

948

949

950

951

952

953

954

955

956

957

958

959

960

961

962

963

964

965

966

967

968

969

970

971

972

973

974

975

976

977

978

979

980

981

982

983

984

985

986

987

988

989

990

991

992

993

994

995

996

997

998

999

1000

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

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

<head>

<title>matplotlib.colors — 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.colors</h1><div class="highlight"><pre>

"""

A module for converting numbers or color arguments to *RGB* or *RGBA*

*RGB* and *RGBA* are sequences of, respectively, 3 or 4 floats in the

range 0-1.

This module includes functions and classes for color specification

conversions, and for mapping numbers to colors in a 1-D array of colors called

a colormap. Colormapping typically involves two steps: a data array is first

mapped onto the range 0-1 using an instance of :class:`Normalize` or of a

subclass; then this number in the 0-1 range is mapped to a color using an

instance of a subclass of :class:`Colormap`. Two are provided here:

:class:`LinearSegmentedColormap`, which is used to generate all the built-in

colormap instances, but is also useful for making custom colormaps, and

:class:`ListedColormap`, which is used for generating a custom colormap from a

list of color specifications.

The module also provides functions for checking whether an object can be

interpreted as a color (:func:`is_color_like`), for converting such an object

to an RGBA tuple (:func:`to_rgba`) or to an HTML-like hex string in the

`#rrggbb` format (:func:`to_hex`), and a sequence of colors to an `(n, 4)`

RGBA array (:func:`to_rgba_array`). Caching is used for efficiency.

Matplotlib recognizes the following formats to specify a color:

* an RGB or RGBA tuple of float values in ``[0, 1]`` (e.g., ``(0.1, 0.2, 0.5)``

or ``(0.1, 0.2, 0.5, 0.3)``);

* a hex RGB or RGBA string (e.g., ``'#0F0F0F'`` or ``'#0F0F0F0F'``);

* a string representation of a float value in ``[0, 1]`` inclusive for gray

level (e.g., ``'0.5'``);

* one of ``{'b', 'g', 'r', 'c', 'm', 'y', 'k', 'w'}``;

* a X11/CSS4 color name;

* a name from the `xkcd color survey <https://xkcd.com/color/rgb/>`__;

prefixed with ``'xkcd:'`` (e.g., ``'xkcd:sky blue'``);

* one of ``{'tab:blue', 'tab:orange', 'tab:green',

'tab:red', 'tab:purple', 'tab:brown', 'tab:pink',

'tab:gray', 'tab:olive', 'tab:cyan'}`` which are the Tableau Colors from the

'T10' categorical palette (which is the default color cycle);

* a "CN" color spec, i.e. `'C'` followed by a single digit, which is an index

into the default property cycle (``matplotlib.rcParams['axes.prop_cycle']``);

the indexing occurs at artist creation time and defaults to black if the

cycle does not include color.

All string specifications of color, other than "CN", are case-insensitive.

"""

from __future__ import (absolute_import, division, print_function,

unicode_literals)

import six

from six.moves import zip

from collections import Sized

import itertools

import re

import warnings

import numpy as np

import matplotlib.cbook as cbook

from ._color_data import BASE_COLORS, TABLEAU_COLORS, CSS4_COLORS, XKCD_COLORS

class _ColorMapping(dict):

def __init__(self, mapping):

super(_ColorMapping, self).__init__(mapping)

self.cache = {}

def __setitem__(self, key, value):

super(_ColorMapping, self).__setitem__(key, value)

self.cache.clear()

def __delitem__(self, key):

super(_ColorMapping, self).__delitem__(key)

self.cache.clear()

_colors_full_map = {}

# Set by reverse priority order.

_colors_full_map.update(XKCD_COLORS)

_colors_full_map.update({k.replace('grey', 'gray'): v

for k, v in XKCD_COLORS.items()

if 'grey' in k})

_colors_full_map.update(CSS4_COLORS)

_colors_full_map.update(TABLEAU_COLORS)

_colors_full_map.update({k.replace('gray', 'grey'): v

for k, v in TABLEAU_COLORS.items()

if 'gray' in k})

_colors_full_map.update(BASE_COLORS)

_colors_full_map = _ColorMapping(_colors_full_map)

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

"""Return the global mapping of names to named colors."""

return _colors_full_map</div>

def _sanitize_extrema(ex):

if ex is None:

return ex

try:

ret = np.asscalar(ex)

except AttributeError:

ret = float(ex)

return ret

def _is_nth_color(c):

"""Return whether *c* can be interpreted as an item in the color cycle."""

return isinstance(c, six.string_types) and re.match(r"\AC[0-9]\Z", c)

<div class="viewcode-block" id="is_color_like"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.is_color_like.html#matplotlib.colors.is_color_like">[docs]</a>def is_color_like(c):

"""Return whether *c* can be interpreted as an RGB(A) color."""

# Special-case nth color syntax because it cannot be parsed during

# setup.

if _is_nth_color(c):

return True

try:

to_rgba(c)

except ValueError:

return False

else:

return True</div>

def same_color(c1, c2):

"""

Compare two colors to see if they are the same.

Parameters

----------

c1, c2 : Matplotlib colors

Returns

-------

bool

``True`` if *c1* and *c2* are the same color, otherwise ``False``.

"""

return (to_rgba_array(c1) == to_rgba_array(c2)).all()

<div class="viewcode-block" id="to_rgba"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.to_rgba.html#matplotlib.colors.to_rgba">[docs]</a>def to_rgba(c, alpha=None):

"""

Convert *c* to an RGBA color.

Parameters

----------

c : Matplotlib color

alpha : scalar, optional

If *alpha* is not ``None``, it forces the alpha value, except if *c* is

``"none"`` (case-insensitive), which always maps to ``(0, 0, 0, 0)``.

Returns

-------

tuple

Tuple of ``(r, g, b, a)`` scalars.

"""

# Special-case nth color syntax because it should not be cached.

if _is_nth_color(c):

from matplotlib import rcParams

prop_cycler = rcParams['axes.prop_cycle']

colors = prop_cycler.by_key().get('color', ['k'])

c = colors[int(c[1]) % len(colors)]

try:

rgba = _colors_full_map.cache[c, alpha]

except (KeyError, TypeError): # Not in cache, or unhashable.

rgba = _to_rgba_no_colorcycle(c, alpha)

try:

_colors_full_map.cache[c, alpha] = rgba

except TypeError:

pass

return rgba</div>

def _to_rgba_no_colorcycle(c, alpha=None):

"""Convert *c* to an RGBA color, with no support for color-cycle syntax.

If *alpha* is not ``None``, it forces the alpha value, except if *c* is

``"none"`` (case-insensitive), which always maps to ``(0, 0, 0, 0)``.

"""

orig_c = c

if c.lower() == "none":

return (0., 0., 0., 0.)

# Named color.

try:

# This may turn c into a non-string, so we check again below.

c = _colors_full_map[c.lower()]

except KeyError:

pass

# hex color with no alpha.

match = re.match(r"\A#[a-fA-F0-9]{6}\Z", c)

if match:

return (tuple(int(n, 16) / 255

for n in [c[1:3], c[3:5], c[5:7]])

+ (alpha if alpha is not None else 1.,))

# hex color with alpha.

match = re.match(r"\A#[a-fA-F0-9]{8}\Z", c)

if match:

color = [int(n, 16) / 255

if alpha is not None:

color[-1] = alpha

return tuple(color)

# string gray.

try:

return (float(c),) * 3 + (alpha if alpha is not None else 1.,)

except ValueError:

pass

raise ValueError("Invalid RGBA argument: {!r}".format(orig_c))

# tuple color.

c = np.array(c)

if not np.can_cast(c.dtype, float, "same_kind") or c.ndim != 1:

# Test the dtype explicitly as `map(float, ...)`, `np.array(...,

# float)` and `np.array(...).astype(float)` all convert "0.5" to 0.5.

# Test dimensionality to reject single floats.

# Return a tuple to prevent the cached value from being modified.

c = tuple(c.astype(float))

if len(c) not in [3, 4]:

raise ValueError("RGBA sequence should have length 3 or 4")

if len(c) == 3 and alpha is None:

alpha = 1

if alpha is not None:

c = c[:3] + (alpha,)

if any(elem < 0 or elem > 1 for elem in c):

raise ValueError("RGBA values should be within 0-1 range")

return c

<div class="viewcode-block" id="to_rgba_array"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.to_rgba_array.html#matplotlib.colors.to_rgba_array">[docs]</a>def to_rgba_array(c, alpha=None):

"""Convert *c* to a (n, 4) array of RGBA colors.

If *alpha* is not ``None``, it forces the alpha value. If *c* is

``"none"`` (case-insensitive) or an empty list, an empty array is returned.

"""

# Special-case inputs that are already arrays, for performance. (If the

# array has the wrong kind or shape, raise the error during one-at-a-time

# conversion.)

if (isinstance(c, np.ndarray) and c.dtype.kind in "if"

and c.ndim == 2 and c.shape[1] in [3, 4]):

if c.shape[1] == 3:

result = np.column_stack([c, np.zeros(len(c))])

result[:, -1] = alpha if alpha is not None else 1.

elif c.shape[1] == 4:

result = c.copy()

if alpha is not None:

result[:, -1] = alpha

if np.any((result < 0) | (result > 1)):

raise ValueError("RGBA values should be within 0-1 range")

return result

# Handle single values.

# Note that this occurs *after* handling inputs that are already arrays, as

# `to_rgba(c, alpha)` (below) is expensive for such inputs, due to the need

# to format the array in the ValueError message(!).

if isinstance(c, six.string_types) and c.lower() == "none":

return np.zeros((0, 4), float)

try:

return np.array([to_rgba(c, alpha)], float)

except (ValueError, TypeError):

pass

# Convert one at a time.

result = np.empty((len(c), 4), float)

for i, cc in enumerate(c):

result[i] = to_rgba(cc, alpha)

return result</div>

<div class="viewcode-block" id="to_rgb"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.to_rgb.html#matplotlib.colors.to_rgb">[docs]</a>def to_rgb(c):

"""Convert *c* to an RGB color, silently dropping the alpha channel."""

return to_rgba(c)[:3]</div>

<div class="viewcode-block" id="to_hex"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.to_hex.html#matplotlib.colors.to_hex">[docs]</a>def to_hex(c, keep_alpha=False):

"""Convert *c* to a hex color.

Uses the ``#rrggbb`` format if *keep_alpha* is False (the default),

``#rrggbbaa`` otherwise.

"""

c = to_rgba(c)

if not keep_alpha:

c = c[:3]

return "#" + "".join(format(int(np.round(val * 255)), "02x")

for val in c)</div>

### Backwards-compatible color-conversion API

cnames = CSS4_COLORS

hexColorPattern = re.compile(r"\A#[a-fA-F0-9]{6}\Z")

rgb2hex = to_hex

hex2color = to_rgb

class ColorConverter(object):

"""

Provides methods for converting color specifications to *RGB* or *RGBA*

Caching is used for more efficient conversion upon repeated calls

with the same argument.

Ordinarily only the single instance instantiated in this module,

*colorConverter*, is needed.

"""

colors = _colors_full_map

cache = _colors_full_map.cache

@staticmethod

def to_rgb(arg):

"""

Returns an *RGB* tuple of three floats from 0-1.

*arg* can be an *RGB* or *RGBA* sequence or a string in any of

several forms:

1) a letter from the set 'rgbcmykw'

2) a hex color string, like '#00FFFF'

3) a standard name, like 'aqua'

4) a string representation of a float, like '0.4',

indicating gray on a 0-1 scale

if *arg* is *RGBA*, the *A* will simply be discarded.

"""

return to_rgb(arg)

@staticmethod

def to_rgba(arg, alpha=None):

"""

Returns an *RGBA* tuple of four floats from 0-1.

For acceptable values of *arg*, see :meth:`to_rgb`.

In addition, if *arg* is "none" (case-insensitive),

then (0,0,0,0) will be returned.

If *arg* is an *RGBA* sequence and *alpha* is not *None*,

*alpha* will replace the original *A*.

"""

return to_rgba(arg, alpha)

@staticmethod

def to_rgba_array(arg, alpha=None):

"""

Returns a numpy array of *RGBA* tuples.

Accepts a single mpl color spec or a sequence of specs.

Special case to handle "no color": if *c* is "none" (case-insensitive),

then an empty array will be returned. Same for an empty list.

"""

return to_rgba_array(arg, alpha)

colorConverter = ColorConverter()

### End of backwards-compatible color-conversion API

<div class="viewcode-block" id="makeMappingArray"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.makeMappingArray.html#matplotlib.colors.makeMappingArray">[docs]</a>def makeMappingArray(N, data, gamma=1.0):

"""Create an *N* -element 1-d lookup table

*data* represented by a list of x,y0,y1 mapping correspondences.

Each element in this list represents how a value between 0 and 1

(inclusive) represented by x is mapped to a corresponding value

between 0 and 1 (inclusive). The two values of y are to allow

for discontinuous mapping functions (say as might be found in a

sawtooth) where y0 represents the value of y for values of x

<= to that given, and y1 is the value to be used for x > than

that given). The list must start with x=0, end with x=1, and

all values of x must be in increasing order. Values between

the given mapping points are determined by simple linear interpolation.

Alternatively, data can be a function mapping values between 0 - 1

to 0 - 1.

The function returns an array "result" where ``result[x*(N-1)]``

gives the closest value for values of x between 0 and 1.

"""

if callable(data):

xind = np.linspace(0, 1, N) ** gamma

lut = np.clip(np.array(data(xind), dtype=float), 0, 1)

return lut

try:

adata = np.array(data)

except Exception:

raise TypeError("data must be convertible to an array")

shape = adata.shape

if len(shape) != 2 or shape[1] != 3:

raise ValueError("data must be nx3 format")

x = adata[:, 0]

y0 = adata[:, 1]

y1 = adata[:, 2]

if x[0] != 0. or x[-1] != 1.0:

raise ValueError(

"data mapping points must start with x=0 and end with x=1")

if (np.diff(x) < 0).any():

raise ValueError("data mapping points must have x in increasing order")

# begin generation of lookup table

x = x * (N - 1)

lut = np.zeros((N,), float)

xind = (N - 1) * np.linspace(0, 1, N) ** gamma

ind = np.searchsorted(x, xind)[1:-1]

distance = (xind[1:-1] - x[ind - 1]) / (x[ind] - x[ind - 1])

lut[1:-1] = distance * (y0[ind] - y1[ind - 1]) + y1[ind - 1]

lut[0] = y1[0]

lut[-1] = y0[-1]

# ensure that the lut is confined to values between 0 and 1 by clipping it

return np.clip(lut, 0.0, 1.0)</div>

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

"""

Baseclass for all scalar to RGBA mappings.

Typically Colormap instances are used to convert data values (floats) from

the interval ``[0, 1]`` to the RGBA color that the respective Colormap

represents. For scaling of data into the ``[0, 1]`` interval see

:class:`matplotlib.colors.Normalize`. It is worth noting that

:class:`matplotlib.cm.ScalarMappable` subclasses make heavy use of this

``data->normalize->map-to-color`` processing chain.

"""

"""

Parameters

----------

name : str

The name of the colormap.

N : int

The number of rgb quantization levels.

"""

self.name = name

self.N = int(N) # ensure that N is always int

self._rgba_bad = (0.0, 0.0, 0.0, 0.0) # If bad, don't paint anything.

self._rgba_under = None

self._rgba_over = None

self._i_under = self.N

self._i_over = self.N + 1

self._i_bad = self.N + 2

self._isinit = False

#: When this colormap exists on a scalar mappable and colorbar_extend

#: is not False, colorbar creation will pick up ``colorbar_extend`` as

#: the default value for the ``extend`` keyword in the

#: :class:`matplotlib.colorbar.Colorbar` constructor.

self.colorbar_extend = False

def __call__(self, X, alpha=None, bytes=False):

"""

Parameters

----------

X : scalar, ndarray

The data value(s) to convert to RGBA.

For floats, X should be in the interval ``[0.0, 1.0]`` to

return the RGBA values ``X*100`` percent along the Colormap line.

For integers, X should be in the interval ``[0, Colormap.N)`` to

return RGBA values *indexed* from the Colormap with index ``X``.

alpha : float, None

Alpha must be a scalar between 0 and 1, or None.

bytes : bool

If False (default), the returned RGBA values will be floats in the

interval ``[0, 1]`` otherwise they will be uint8s in the interval

``[0, 255]``.

Returns

-------

Tuple of RGBA values if X is scalar, otherwise an array of

RGBA values with a shape of ``X.shape + (4, )``.

"""

# See class docstring for arg/kwarg documentation.

if not self._isinit:

self._init()

mask_bad = None

if not cbook.iterable(X):

vtype = 'scalar'

xa = np.array([X])

else:

vtype = 'array'

xma = np.ma.array(X, copy=True) # Copy here to avoid side effects.

mask_bad = xma.mask # Mask will be used below.

xa = xma.filled() # Fill to avoid infs, etc.

del xma

# Calculations with native byteorder are faster, and avoid a

# bug that otherwise can occur with putmask when the last

# argument is a numpy scalar.

if not xa.dtype.isnative:

xa = xa.byteswap().newbyteorder()

if xa.dtype.kind == "f":

xa *= self.N

# Negative values are out of range, but astype(int) would truncate

# them towards zero.

xa[xa < 0] = -1

# xa == 1 (== N after multiplication) is not out of range.

xa[xa == self.N] = self.N - 1

# Avoid converting large positive values to negative integers.

np.clip(xa, -1, self.N, out=xa)

xa = xa.astype(int)

# Set the over-range indices before the under-range;

# otherwise the under-range values get converted to over-range.

xa[xa > self.N - 1] = self._i_over

if mask_bad is not None:

if mask_bad.shape == xa.shape:

np.copyto(xa, self._i_bad, where=mask_bad)

elif mask_bad:

xa.fill(self._i_bad)

if bytes:

lut = (self._lut * 255).astype(np.uint8)

else:

lut = self._lut.copy() # Don't let alpha modify original _lut.

if alpha is not None:

alpha = min(alpha, 1.0) # alpha must be between 0 and 1

alpha = max(alpha, 0.0)

if bytes:

alpha = int(alpha * 255)

if (lut[-1] == 0).all():

lut[:-1, -1] = alpha

# All zeros is taken as a flag for the default bad

# color, which is no color--fully transparent. We

# don't want to override this.

else:

lut[:, -1] = alpha

# If the bad value is set to have a color, then we

# override its alpha just as for any other value.

rgba = np.empty(shape=xa.shape + (4,), dtype=lut.dtype)

lut.take(xa, axis=0, mode='clip', out=rgba)

if vtype == 'scalar':

rgba = tuple(rgba[0, :])

return rgba

def __copy__(self):

"""Create new object with the same class, update attributes

"""

cls = self.__class__

cmapobject = cls.__new__(cls)

cmapobject.__dict__.update(self.__dict__)

if self._isinit:

cmapobject._lut = np.copy(self._lut)

return cmapobject

<div class="viewcode-block" id="Colormap.set_bad"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.Colormap.html#matplotlib.colors.Colormap.set_bad">[docs]</a> def set_bad(self, color='k', alpha=None):

"""Set color to be used for masked values.

"""

self._rgba_bad = colorConverter.to_rgba(color, alpha)

if self._isinit:

self._set_extremes()</div>

<div class="viewcode-block" id="Colormap.set_under"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.Colormap.html#matplotlib.colors.Colormap.set_under">[docs]</a> def set_under(self, color='k', alpha=None):

"""Set color to be used for low out-of-range values.

Requires norm.clip = False

"""

self._rgba_under = colorConverter.to_rgba(color, alpha)

if self._isinit:

self._set_extremes()</div>

<div class="viewcode-block" id="Colormap.set_over"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.Colormap.html#matplotlib.colors.Colormap.set_over">[docs]</a> def set_over(self, color='k', alpha=None):

"""Set color to be used for high out-of-range values.

Requires norm.clip = False

"""

self._rgba_over = colorConverter.to_rgba(color, alpha)

if self._isinit:

self._set_extremes()</div>

def _set_extremes(self):

if self._rgba_under:

else:

self._lut[self._i_under] = self._lut[0]

if self._rgba_over:

else:

self._lut[self._i_over] = self._lut[self.N - 1]

def _init(self):

"""Generate the lookup table, self._lut"""

raise NotImplementedError("Abstract class only")

<div class="viewcode-block" id="Colormap.is_gray"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.Colormap.html#matplotlib.colors.Colormap.is_gray">[docs]</a> def is_gray(self):

if not self._isinit:

self._init()

return (np.all(self._lut[:, 0] == self._lut[:, 1]) and

np.all(self._lut[:, 0] == self._lut[:, 2]))</div>

def _resample(self, lutsize):

"""

Return a new color map with *lutsize* entries.

"""

raise NotImplementedError()

<div class="viewcode-block" id="Colormap.reversed"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.Colormap.html#matplotlib.colors.Colormap.reversed">[docs]</a> def reversed(self, name=None):

"""

Make a reversed instance of the Colormap.

.. note :: Function not implemented for base class.

Parameters

----------

name : str, optional

The name for the reversed colormap. If it's None the

name will be the name of the parent colormap + "_r".

Notes

-----

See :meth:`LinearSegmentedColormap.reversed` and

:meth:`ListedColormap.reversed`

"""

raise NotImplementedError()</div></div>

<div class="viewcode-block" id="LinearSegmentedColormap"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.LinearSegmentedColormap.html#matplotlib.colors.LinearSegmentedColormap">[docs]</a>class LinearSegmentedColormap(Colormap):

"""Colormap objects based on lookup tables using linear segments.

The lookup table is generated using linear interpolation for each

primary color, with the 0-1 domain divided into any number of

segments.

"""

def __init__(self, name, segmentdata, N=256, gamma=1.0):

"""Create color map from linear mapping segments

segmentdata argument is a dictionary with a red, green and blue

entries. Each entry should be a list of *x*, *y0*, *y1* tuples,

forming rows in a table. Entries for alpha are optional.

Example: suppose you want red to increase from 0 to 1 over

the bottom half, green to do the same over the middle half,

and blue over the top half. Then you would use::

cdict = {'red': [(0.0, 0.0, 0.0),

(0.5, 1.0, 1.0),

(1.0, 1.0, 1.0)],

'green': [(0.0, 0.0, 0.0),

(0.25, 0.0, 0.0),

(0.75, 1.0, 1.0),

(1.0, 1.0, 1.0)],

'blue': [(0.0, 0.0, 0.0),

(0.5, 0.0, 0.0),

(1.0, 1.0, 1.0)]}

Each row in the table for a given color is a sequence of

*x*, *y0*, *y1* tuples. In each sequence, *x* must increase

monotonically from 0 to 1. For any input value *z* falling

between *x[i]* and *x[i+1]*, the output value of a given color

will be linearly interpolated between *y1[i]* and *y0[i+1]*::

row i: x y0 y1

/

row i+1: x y0 y1

Hence y0 in the first row and y1 in the last row are never used.

.. seealso::

:meth:`LinearSegmentedColormap.from_list`

Static method; factory function for generating a

smoothly-varying LinearSegmentedColormap.

:func:`makeMappingArray`

For information about making a mapping array.

"""

# True only if all colors in map are identical; needed for contouring.

self.monochrome = False

Colormap.__init__(self, name, N)

self._segmentdata = segmentdata

self._gamma = gamma

def _init(self):

self._lut = np.ones((self.N + 3, 4), float)

self._lut[:-3, 0] = makeMappingArray(

self.N, self._segmentdata['red'], self._gamma)

self._lut[:-3, 1] = makeMappingArray(

self.N, self._segmentdata['green'], self._gamma)

self._lut[:-3, 2] = makeMappingArray(

self.N, self._segmentdata['blue'], self._gamma)

if 'alpha' in self._segmentdata:

self._lut[:-3, 3] = makeMappingArray(

self.N, self._segmentdata['alpha'], 1)

self._isinit = True

self._set_extremes()

<div class="viewcode-block" id="LinearSegmentedColormap.set_gamma"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.LinearSegmentedColormap.html#matplotlib.colors.LinearSegmentedColormap.set_gamma">[docs]</a> def set_gamma(self, gamma):

"""

Set a new gamma value and regenerate color map.

"""

self._gamma = gamma

self._init()</div>

<div class="viewcode-block" id="LinearSegmentedColormap.from_list"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.LinearSegmentedColormap.html#matplotlib.colors.LinearSegmentedColormap.from_list">[docs]</a> @staticmethod

def from_list(name, colors, N=256, gamma=1.0):

"""

Make a linear segmented colormap with *name* from a sequence

of *colors* which evenly transitions from colors[0] at val=0

to colors[-1] at val=1. *N* is the number of rgb quantization

levels.

Alternatively, a list of (value, color) tuples can be given

to divide the range unevenly.

"""

raise ValueError('colors must be iterable')

if (isinstance(colors[0], Sized) and len(colors[0]) == 2

and not isinstance(colors[0], six.string_types)):

# List of value, color pairs

vals, colors = zip(*colors)

else:

vals = np.linspace(0, 1, len(colors))

cdict = dict(red=[], green=[], blue=[], alpha=[])

for val, color in zip(vals, colors):

r, g, b, a = colorConverter.to_rgba(color)

cdict['red'].append((val, r, r))

cdict['green'].append((val, g, g))

cdict['blue'].append((val, b, b))

cdict['alpha'].append((val, a, a))

return LinearSegmentedColormap(name, cdict, N, gamma)</div>

def _resample(self, lutsize):

"""

Return a new color map with *lutsize* entries.

"""

return LinearSegmentedColormap(self.name, self._segmentdata, lutsize)

<div class="viewcode-block" id="LinearSegmentedColormap.reversed"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.LinearSegmentedColormap.html#matplotlib.colors.LinearSegmentedColormap.reversed">[docs]</a> def reversed(self, name=None):

"""

Make a reversed instance of the Colormap.

Parameters

----------

name : str, optional

The name for the reversed colormap. If it's None the

name will be the name of the parent colormap + "_r".

Returns

-------

LinearSegmentedColormap

The reversed colormap.

"""

if name is None:

name = self.name + "_r"

# Function factory needed to deal with 'late binding' issue.

def factory(dat):

def func_r(x):

return dat(1.0 - x)

return func_r

data_r = dict()

for key, data in six.iteritems(self._segmentdata):

if callable(data):

data_r[key] = factory(data)

else:

new_data = [(1.0 - x, y1, y0) for x, y0, y1 in reversed(data)]

data_r[key] = new_data

return LinearSegmentedColormap(name, data_r, self.N, self._gamma)</div></div>

<div class="viewcode-block" id="ListedColormap"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.ListedColormap.html#matplotlib.colors.ListedColormap">[docs]</a>class ListedColormap(Colormap):

"""Colormap object generated from a list of colors.

This may be most useful when indexing directly into a colormap,

but it can also be used to generate special colormaps for ordinary

mapping.

"""

def __init__(self, colors, name='from_list', N=None):

"""

Make a colormap from a list of colors.

*colors*

a list of matplotlib color specifications,

or an equivalent Nx3 or Nx4 floating point array

(*N* rgb or rgba values)

*name*

a string to identify the colormap

*N*

the number of entries in the map. The default is *None*,

in which case there is one colormap entry for each

element in the list of colors. If::

N < len(colors)

the list will be truncated at *N*. If::

N > len(colors)

the list will be extended by repetition.

"""

self.monochrome = False # True only if all colors in map are

# identical; needed for contouring.

if N is None:

self.colors = colors

N = len(colors)

else:

if isinstance(colors, six.string_types):

self.colors = [colors] * N

self.monochrome = True

elif cbook.iterable(colors):

if len(colors) == 1:

self.monochrome = True

self.colors = list(

itertools.islice(itertools.cycle(colors), N))

else:

try:

gray = float(colors)

except TypeError:

pass

else:

self.colors = [gray] * N

self.monochrome = True

def _init(self):

rgba = colorConverter.to_rgba_array(self.colors)

self._lut = np.zeros((self.N + 3, 4), float)

self._lut[:-3] = rgba

self._isinit = True

self._set_extremes()

def _resample(self, lutsize):

"""

Return a new color map with *lutsize* entries.

"""

colors = self(np.linspace(0, 1, lutsize))

return ListedColormap(colors, name=self.name)

<div class="viewcode-block" id="ListedColormap.reversed"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.ListedColormap.html#matplotlib.colors.ListedColormap.reversed">[docs]</a> def reversed(self, name=None):

"""

Make a reversed instance of the Colormap.

Parameters

----------

name : str, optional

The name for the reversed colormap. If it's None the

name will be the name of the parent colormap + "_r".

Returns

-------

ListedColormap

A reversed instance of the colormap.

"""

if name is None:

name = self.name + "_r"

colors_r = list(reversed(self.colors))

return ListedColormap(colors_r, name=name, N=self.N)</div></div>

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

"""

A class which, when called, can normalize data into

the ``[0.0, 1.0]`` interval.

"""

def __init__(self, vmin=None, vmax=None, clip=False):

"""

If *vmin* or *vmax* is not given, they are initialized from the

minimum and maximum value respectively of the first input

processed. That is, *__call__(A)* calls *autoscale_None(A)*.

If *clip* is *True* and the given value falls outside the range,

the returned value will be 0 or 1, whichever is closer.

Returns 0 if::

vmin==vmax

Works with scalars or arrays, including masked arrays. If

View remainder of file in raw view

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

FilesExpand file tree

colors.html

Latest commit

History

colors.html

File metadata and controls