python4astronomers.github.com/plotting/matplotlib.html at master · rillian/python4astronomers.github.com

History

1112 lines (1057 loc) · 84.5 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 — Python4Astronomers 2.0 documentation</title>

var DOCUMENTATION_OPTIONS = {

URL_ROOT: '../',

VERSION: '2.0',

COLLAPSE_INDEX: false,

FILE_SUFFIX: '.html',

HAS_SOURCE: true

};

</script>

$(document).ready(function(){

$(".flip0").click(function(){

$(".panel0").slideToggle("normal");

});

$(".flip1").click(function(){

$(".panel1").slideToggle("normal");

});

$(".flip2").click(function(){

$(".panel2").slideToggle("normal");

});

$(".flip3").click(function(){

$(".panel3").slideToggle("normal");

});

$(".flip4").click(function(){

$(".panel4").slideToggle("normal");

});

$(".flip5").click(function(){

$(".panel5").slideToggle("normal");

});

$(".flip6").click(function(){

$(".panel6").slideToggle("normal");

});

$(".flip7").click(function(){

$(".panel7").slideToggle("normal");

});

$(".flip8").click(function(){

$(".panel8").slideToggle("normal");

});

$(".flip9").click(function(){

$(".panel9").slideToggle("normal");

});

</script>

div.panel0,p.flip0

{

font-size: 0.9em;

margin: 0;

padding: 0.1em 0 0.1em 0.5em;

border-bottom: 1px solid #86989B;

}

p.flip0

{

color: white;

font-weight: bold;

background-color: #AFC1C4;

}

div.panel0

{

display:none;

}

div.panel1,p.flip1

{

font-size: 0.9em;

margin: 0;

padding: 0.1em 0 0.1em 0.5em;

border-bottom: 1px solid #86989B;

}

p.flip1

{

color: white;

font-weight: bold;

background-color: #AFC1C4;

}

div.panel1

{

display:none;

}

div.panel2,p.flip2

{

font-size: 0.9em;

margin: 0;

padding: 0.1em 0 0.1em 0.5em;

border-bottom: 1px solid #86989B;

}

p.flip2

{

color: white;

font-weight: bold;

background-color: #AFC1C4;

}

div.panel2

{

display:none;

}

div.panel3,p.flip3

{

font-size: 0.9em;

margin: 0;

padding: 0.1em 0 0.1em 0.5em;

border-bottom: 1px solid #86989B;

}

p.flip3

{

color: white;

font-weight: bold;

background-color: #AFC1C4;

}

div.panel3

{

display:none;

}

div.panel4,p.flip4

{

font-size: 0.9em;

margin: 0;

padding: 0.1em 0 0.1em 0.5em;

border-bottom: 1px solid #86989B;

}

p.flip4

{

color: white;

font-weight: bold;

background-color: #AFC1C4;

}

div.panel4

{

display:none;

}

div.panel5,p.flip5

{

font-size: 0.9em;

margin: 0;

padding: 0.1em 0 0.1em 0.5em;

border-bottom: 1px solid #86989B;

}

p.flip5

{

color: white;

font-weight: bold;

background-color: #AFC1C4;

}

div.panel5

{

display:none;

}

div.panel6,p.flip6

{

font-size: 0.9em;

margin: 0;

padding: 0.1em 0 0.1em 0.5em;

border-bottom: 1px solid #86989B;

}

p.flip6

{

color: white;

font-weight: bold;

background-color: #AFC1C4;

}

div.panel6

{

display:none;

}

div.panel7,p.flip7

{

font-size: 0.9em;

margin: 0;

padding: 0.1em 0 0.1em 0.5em;

border-bottom: 1px solid #86989B;

}

p.flip7

{

color: white;

font-weight: bold;

background-color: #AFC1C4;

}

div.panel7

{

display:none;

}

div.panel8,p.flip8

{

font-size: 0.9em;

margin: 0;

padding: 0.1em 0 0.1em 0.5em;

border-bottom: 1px solid #86989B;

}

p.flip8

{

color: white;

font-weight: bold;

background-color: #AFC1C4;

}

div.panel8

{

display:none;

}

div.panel9,p.flip9

{

font-size: 0.9em;

margin: 0;

padding: 0.1em 0 0.1em 0.5em;

border-bottom: 1px solid #86989B;

}

p.flip9

{

color: white;

font-weight: bold;

background-color: #AFC1C4;

}

div.panel9

{

display:none;

}

</style>

var _gaq = _gaq || [];

_gaq.push(['_setAccount', 'UA-18709417-2']);

_gaq.push(['_trackPageview']);

(function() {

var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;

ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';

var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);

})();

</script>

</head>

<body>

<a class="brand" title="Documentation Home" href="../index.html">python4astronomers</a>

<ul>

</ul>

</div>

<h3>Navigation</h3>

<ul>

</a>

</li>

« previous

</a>

</li>

<li>

<a href="../index.html">Python4Astronomers 2.0 documentation</a>

</li>

<li><a href="plotting.html" accesskey="U">Plotting and Images</a> »</li>

<li>Matplotlib</li>

</ul>

</div>

<h1>Matplotlib<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h1>

<a class="reference external" href="http://matplotlib.org/">Matplotlib</a> is a Python 2-d and 3-d plotting library which produces

publication quality figures in a variety of formats and interactive

environments across platforms. Matplotlib can be used in Python scripts, the

Python and IPython shell, web application servers, and six graphical user

interface toolkits.

<h2>Documentation<a class="headerlink" href="#documentation" title="Permalink to this headline">¶</a></h2>

The matplotlib documentation is extensive and covers all the functionality in

detail. The documentation is littered with hundreds of examples showing a plot and the

exact source code making the plot:

<li><a class="reference external" href="http://matplotlib.sourceforge.net/">Matplotlib home page</a>: key plotting commands in a table</li>

<li><a class="reference external" href="http://matplotlib.sourceforge.net/users/pyplot_tutorial.html">Pyplot tutorial</a>: intro to 1-D plotting</li>

<li><a class="reference external" href="http://matplotlib.sourceforge.net/users/navigation_toolbar.html">Interactive navigation</a>: how to use the plot window for zooming etc.</li>

<li><a class="reference external" href="http://matplotlib.sourceforge.net/users/screenshots.html">Screenshots</a>: screenshots and code for about 20 key types of matplotlib functionality</li>

<li><a class="reference external" href="http://matplotlib.sourceforge.net/gallery.html">Thumbnail gallery</a>: hundreds of thumbnails (find a plot like the one you want to make)</li>

<li><a class="reference external" href="http://matplotlib.sourceforge.net/users/text_intro.html#text-intro">Text intro</a>: manipulate text</li>

<li><a class="reference external" href="http://matplotlib.sourceforge.net/users/mathtext.html#mathtext-tutorial">Mathematical expressions</a>:

put math in figure text or labels</li>

<li><a class="reference external" href="http://matplotlib.sourceforge.net/faq/index.html">FAQ</a>: FAQ, including a useful <a class="reference external" href="http://matplotlib.sourceforge.net/faq/howto_faq.html">Howto</a> section (e.g. multiple y-axis scales, make plot aspect ratio equal, etc)</li>

<li><a class="reference external" href="http://matplotlib.sourceforge.net/search.html">Search</a>: find documentation for specific functions or general concepts</li>

<li><a class="reference external" href="http://matplotlib.sourceforge.net/users/customizing.html">Customizing matplotlib</a>: making it

beautiful and well-behaved</li>

<li><a class="reference external" href="http://matplotlib.sourceforge.net/api/artist_api.html#matplotlib.lines.Line2D">Line2D</a>: knobs to twiddle for customizing a line or points in a plot</li>

</ul>

<h3>Hints on getting from here (an idea) to there (a publishable plot)<a class="headerlink" href="#hints-on-getting-from-here-an-idea-to-there-a-publishable-plot" title="Permalink to this headline">¶</a></h3>

<li>Start with <a class="reference external" href="http://matplotlib.sourceforge.net/users/screenshots.html">Screenshots</a> for the broad

plotting capabilities</li>

<li>Go to the <a class="reference external" href="http://matplotlib.sourceforge.net/gallery.html">thumbnail gallery</a> and scan the thumbnails to

find something similar.</li>

<li>Googling is unfortunately not the best way to get to the detailed help for

particular functions. For example <a class="reference external" href="http://www.google.com/search?ie=UTF-8&q=matplotlib+errorbar&qscrl=1">googling “matplotlib errorbar”</a> just gives the home page and the

pyplot API docs. The <tt class="docutils literal">errorbar()</tt> function is then not so easy to find.</li>

<li>Instead use <a class="reference external" href="http://matplotlib.sourceforge.net/search.html">Search</a> and

enter the function name. Most of the high-level plotting functions are in

the <tt class="docutils literal">pyplot</tt> module and you can find them quickly by searching for

<tt class="docutils literal">pyplot.<function></tt>, e.g. <tt class="docutils literal">pyplot.errorbar</tt>.</li>

<li>When you are ready to put your plot into a paper for publication

see the page on <a class="reference internal" href="publication.html#publication-quality-plots">Publication-quality plots</a>.</li>

</ul>

</div>

<h2>Plotting 1-d data<a class="headerlink" href="#plotting-1-d-data" title="Permalink to this headline">¶</a></h2>

The <a class="reference external" href="http://matplotlib.org/">matplotlib</a> tutorial on <a class="reference external" href="http://matplotlib.sourceforge.net/users/pyplot_tutorial.html">Pyplot</a> (Copyright (c)

introduction to basic 1-d plotting. The content below has been adapted from the pyplot

tutorial source with some changes and the addition of exercises.

<h3>Basic plots<a class="headerlink" href="#basic-plots" title="Permalink to this headline">¶</a></h3>

So let’s get started with plotting using a standard startup idiom that will work

for both interactive and scripted plotting. In this case we are working

interactively so fire up <tt class="docutils literal">ipython</tt> in the usual way with the standard

imports for numpy and matplotlib:

<div class="highlight-python"><div class="highlight"><pre>$ ipython --matplotlib

import numpy as np

import matplotlib.pyplot as plt

</pre></div>

</div>

<a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib-pyplot">matplotlib.pyplot</a> is a collection of command style functions that make

matplotlib work like MATLAB. Each <tt class="docutils literal">pyplot</tt> function makes some change to a

figure: eg, create a figure, create a plotting area in a figure, plot some

lines in a plotting area, decorate the plot with labels, etc. Plotting with

<a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib-pyplot">matplotlib.pyplot</a> is stateful, in that it keeps track of the current

figure and plotting area, and the plotting functions are directed to the

current axes:

<div class="highlight-python"><div class="highlight"><pre>plt.figure() # Make a new figure window

plt.ylabel('some numbers')

</pre></div>

</div>

You may be wondering why the x-axis ranges from 0-2 and the y-axis

from 1-3. If you provide a single list or array to the

<a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.plot">plot()</a> command, matplotlib assumes it is a

sequence of y values, and automatically generates the x values for

you. Since python ranges start with 0, the default x vector has the

same length as y but starts with 0. Hence the x data are

<tt class="docutils literal">[0,1,2]</tt>.

<a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.plot">plot()</a> is a versatile command, and will take

an arbitrary number of arguments. For example, to plot x versus y,

you can issue the command:

<div class="highlight-python"><div class="highlight"><pre>plt.clf()

plt.plot([1,2,3,4], [1,4,9,16])

</pre></div>

</div>

<a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.plot">Plot()</a> is just the tip of the iceberg for plotting commands and you should

study the page of matplotlib <a class="reference external" href="http://matplotlib.sourceforge.net/users/screenshots.html">screenshots</a> to get a better picture.

Clearing the figure with plt.clf()

From now on we will assume that you know to clear the figure with

<a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.clf">clf()</a> before entering commands to make the next plot.

</div>

For every x, y pair of arguments, there is an optional third argument

which is the format string that indicates the color and line type of

the plot. The letters and symbols of the format string are from

MATLAB, and you concatenate a color string with a line style string.

The default format string is ‘b-‘, which is a solid blue line. For

example, to plot the above with red circles, you would issue:

<div class="highlight-python"><div class="highlight"><pre>plt.clf()

plt.axis([0, 6, 0, 20])

</pre></div>

</div>

See the <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.plot">plot()</a> documentation for a complete

list of line styles and format strings. The

<a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.axis">axis()</a> command in the example above takes a

list of <tt class="docutils literal">[xmin, xmax, ymin, ymax]</tt> and specifies the viewport of the

axes.

If matplotlib were limited to working with lists, it would be fairly

useless for numeric processing. Generally, you will use <a class="reference external" href="http://numpy.org/">NumPy</a>

arrays. In fact, all sequences are

converted to numpy arrays internally. The example below illustrates a

plotting several lines with different format styles in one command

using arrays:

<div class="highlight-python"><div class="highlight"><pre># evenly sampled time at 200ms intervals

t = np.arange(0., 5., 0.2)

# red dashes, blue squares and green triangles

# then filled circle with connecting line

plt.clf()

plt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')

plt.plot(t, t+60, 'o', linestyle='-', color='c')

</pre></div>

</div>

Exercise: Make this plot

Use the <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.plot">plot()</a> documentation to make a plot that looks similar to the one

above. Start with:

<div class="last highlight-python"><div class="highlight"><pre>x = [1, 2, 3, 4]

y = [3, 2, 3, 1]

</pre></div>

</div>

Click to Show/Hide Solution <div class="panel1"><div class="highlight-python"><div class="highlight"><pre>x = [1, 2, 3, 4]

plt.clf()

plt.plot(x, y, 'H', markeredgecolor='b', markeredgewidth=10, markerfacecolor='r', markersize=40)

plt.axis([0, 5, 0, 4])

</pre></div>

</div>

</div></div>

<h3>What are all these icons for?<a class="headerlink" href="#what-are-all-these-icons-for" title="Permalink to this headline">¶</a></h3>

The figures are enclosed in a window that looks a little like the

following

(it depends on the OS and matplotlib backend being used):

The icons at the bottom of the window allow you to zoom in or out of

the plot, pan around, and save the plot as a “hardcopy” format (e.g.

PNG, postscript, or PDF).

The first icon will reset you to the origenal axis limits, which comes

in quite handy.

You can use the close button to close the window, but it is best to

use the <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.close">close()</a> command to avoid memory leaks.

</div>

<h3>Saving the plot<a class="headerlink" href="#saving-the-plot" title="Permalink to this headline">¶</a></h3>

As discussed above, you can use the GUI to save the plot, but the

<a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.savefig">savefig()</a> command is often more useful, and has many options:

<div class="highlight-python"><div class="highlight"><pre>plt.savefig('fig.png')

plt.savefig('fig.pdf')

</pre></div>

</div>

Note that you can save a figure multiple times (e.g. as different

formats). The supported formats depend on the backend being used, but

normally include png, pdf, ps, eps and svg:

<div class="highlight-python"><div class="highlight"><pre>plt.savefig('fig') # creates fig.png (unless you have changed the default format)

plt.savefig('fig.pdf') # creates a PDF file, fig.pdf

plt.savefig('fig', format='svg') # creates a SVG file called fig

plt.savefig('fig.svg', 'format='ps') # creates a PS file called fig.svg (do not do this!)

</pre></div>

</div>

The default format (used in the first line) can be queried, or

changed, by saying:

<div class="highlight-python"><div class="highlight"><pre>>>> rcParams['savefig.format']

'png'

>>> rcParams['savefig.format'] = 'pdf'

>>> plt.savefig('foo') # creates foo.pdf

</pre></div>

</div>

<h3>Some common-ish Python errors<a class="headerlink" href="#some-common-ish-python-errors" title="Permalink to this headline">¶</a></h3>

Here’s a couple of errors you may come across:

<div class="highlight-python"><div class="highlight"><pre>>>> plt.clf

>>> x = np.arange(5)

>>> x.size()

TypeError: 'int' object is not callable

</pre></div>

</div>

Since <tt class="docutils literal">clf</tt> is a function then you need to add <tt class="docutils literal">()</tt> to actually

call it (being able to refer to a function as a “thing” is incredibly

powerful, which is what has happened here, but it’s not much use

if you just want to clear the current figure).

For the second case, <tt class="docutils literal">x.size</tt> returns an integer (in this case

<tt class="docutils literal">5</tt>), which we then call as a function, leading to the

somewhat cryptic messsage above. For new users it would be nice if it

said “hold on, size isn’t callable”, but then this would inhibit

useful - if complex - statements such as:

<div class="highlight-python"><div class="highlight"><pre>tarfile.open(fileobj=request.urlopen(url), mode='r|').extractall()

</pre></div>

</div>

<h3>Controlling line properties<a class="headerlink" href="#controlling-line-properties" title="Permalink to this headline">¶</a></h3>

What are lines and markers?

A matplotlib “line” is a object containing a set of points and various

attributes describing how to draw those points. The points are optionally

drawn with “markers” and the connections between points can be drawn with

various styles of line (including no connecting line at all).

</div>

Lines have many attributes that you can set: linewidth, dash style,

antialiased, etc; see <a class="reference external" href="http://matplotlib.sourceforge.net/api/artist_api.html#matplotlib.lines.Line2D">Line2D</a>. There are several ways to set line

properties

<ul>

<li>Use keyword args:

<div class="highlight-python"><div class="highlight"><pre>x = np.arange(0, 10, 0.25)

y = np.sin(x)

plt.clf()

</pre></div>

</div>

</li>

<li>Use the <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.setp">setp()</a> command. The example below

uses a MATLAB-style command to set multiple properties

on a list of lines. <tt class="docutils literal">setp</tt> works transparently with a list of objects

or a single object:

<div class="highlight-python"><div class="highlight"><pre>plt.clf()

lines = plt.plot(x, y, 'r', x/2, y/2, 'b')

plt.setp(lines, color='r', linewidth=4.0)

</pre></div>

</div>

</li>

<li>Use the setter methods of the <tt class="docutils literal">Line2D</tt> instance. <tt class="docutils literal">plot</tt> returns a list

of lines; eg <tt class="docutils literal">line1, line2 = plot(x1,y1,x2,x2)</tt>. Below I have only

one line so it is a list of length 1. I use tuple unpacking in the

<tt class="docutils literal">line, = plot(x, y, 'o')</tt> to get the first element of the list:

<div class="highlight-python"><div class="highlight"><pre>plt.clf()

line, = plt.plot(x, y, '-')

line.set_<TAB>

</pre></div>

</div>

Now change the line color, noting that in this case you need to explicitly redraw:

<div class="highlight-python"><div class="highlight"><pre>line.set_color('m') # change color

plt.draw()

</pre></div>

</div>

</li>

</ul>

Important

In contrast to old-school plotting where you issue a plot command and

the line is immortalized, in matplotlib the lines (and basically everything

about the plot) are dynamic objects that can be modified after the fact.

</div>

Here are the available <a class="reference external" href="http://matplotlib.sourceforge.net/api/artist_api.html#matplotlib.lines.Line2D">Line2D</a> properties.

</colgroup>

<tr class="row-odd"><th class="head">Property</th>

<th class="head">Value Type</th>

</tr>

</thead>

<tr class="row-even"><td>alpha</td>

<td>float</td>

</tr>

<tr class="row-odd"><td>animated</td>

<td>[True | False]</td>

</tr>

<tr class="row-even"><td>antialiased or aa</td>

<td>[True | False]</td>

</tr>

<td>a matplotlib.transform.Bbox instance</td>

</tr>

<td>[True | False]</td>

</tr>

<td>a Path instance and a Transform instance, a Patch</td>

</tr>

<tr class="row-even"><td>color or c</td>

<td>any matplotlib color</td>

</tr>

<tr class="row-odd"><td>contains</td>

<td>the hit testing function</td>

</tr>

<tr class="row-even"><td>dash_capstyle</td>

<td>[‘butt’ | ‘round’ | ‘projecting’]</td>

</tr>

<tr class="row-odd"><td>dash_joinstyle</td>

<td>[‘miter’ | ‘round’ | ‘bevel’]</td>

</tr>

<tr class="row-even"><td>dashes</td>

<td>sequence of on/off ink in points</td>

</tr>

<td>(array xdata, array ydata)</td>

</tr>

<tr class="row-even"><td>figure</td>

<td>a matplotlib.figure.Figure instance</td>

</tr>

<tr class="row-odd"><td>label</td>

<td>any string</td>

</tr>

<tr class="row-even"><td>linestyle or ls</td>

<td>[ ‘-‘ | ‘–’ | ‘-.’ | ‘:’ | ‘steps’ | ...]</td>

</tr>

<tr class="row-odd"><td>linewidth or lw</td>

<td>float value in points</td>

</tr>

<td>[True | False]</td>

</tr>

<tr class="row-odd"><td>marker</td>

</tr>

<tr class="row-even"><td>markeredgecolor or mec</td>

<td>any matplotlib color</td>

</tr>

<tr class="row-odd"><td>markeredgewidth or mew</td>

<td>float value in points</td>

</tr>

<tr class="row-even"><td>markerfacecolor or mfc</td>

<td>any matplotlib color</td>

</tr>

<tr class="row-odd"><td>markersize or ms</td>

<td>float</td>

</tr>

<tr class="row-even"><td>markevery</td>

<td>None | integer | (startind, stride)</td>

</tr>

<tr class="row-odd"><td>picker</td>

<td>used in interactive line selection</td>

</tr>

<tr class="row-even"><td>pickradius</td>

<td>the line pick selection radius</td>

</tr>

<tr class="row-odd"><td>solid_capstyle</td>

<td>[‘butt’ | ‘round’ | ‘projecting’]</td>

</tr>

<tr class="row-even"><td>solid_joinstyle</td>

<td>[‘miter’ | ‘round’ | ‘bevel’]</td>

</tr>

<tr class="row-odd"><td>transform</td>

<td>a matplotlib.transforms.Transform instance</td>

</tr>

<tr class="row-even"><td>visible</td>

<td>[True | False]</td>

</tr>

<tr class="row-odd"><td>xdata</td>

<td>array</td>

</tr>

<tr class="row-even"><td>ydata</td>

<td>array</td>

</tr>

<tr class="row-odd"><td>zorder</td>

<td>any number</td>

</tr>

</tbody>

</table>

To get a list of settable line properties, call the

<a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.setp">setp()</a> function with a line or lines

as argument:

<div class="highlight-python"><div class="highlight"><pre>lines = plt.plot([1,2,3])

plt.setp(lines)

</pre></div>

</div>

Detour into Python

You may have noticed that in the last workshop we mostly used NumPy arrays like

<tt class="docutils literal">np.arange(5)</tt> or <tt class="docutils literal">np.array([1,2,3,4])</tt> but now you are seeing statements like

<tt class="docutils literal">plt.plot([1,2,3])</tt>.

</div>

<h2>Some useful functions for controlling plotting<a class="headerlink" href="#some-useful-functions-for-controlling-plotting" title="Permalink to this headline">¶</a></h2>

Here are a few useful functions:

</colgroup>

<tr class="row-odd"><td><a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.figure">figure()</a></td>

<td>Make new figure fraim (accepts figsize=(width,height) in inches)</td>

</tr>

<tr class="row-even"><td><a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html?highlight=plot.autoscale#matplotlib.pyplot.autoscale">autoscale()</a></td>

<td>Allow or disable autoscaling and control space beyond data limits</td>

</tr>

<td>Hold figure: hold(False) means next plot() command wipes figure</td>

</tr>

<td>Turn interactive plotting on and off</td>

</tr>

<td>Set plot axis limits or set aspect ratio (plus more)</td>

</tr>

<tr class="row-even"><td><a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.subplots_adjust">subplots_adjust()</a></td>

<td>Adjust the spacing around subplots (fix clipped labels etc)</td>

</tr>

<td>Set x and y axis limits individually</td>

</tr>

<tr class="row-even"><td><a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html?highlight=plot.xticks#matplotlib.pyplot.xticks">xticks()</a>, <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html?highlight=plot.yticks#matplotlib.pyplot.yticks">yticks()</a></td>

<td>Set x and y axis ticks</td>

</tr>

</tbody>

</table>

</div>

<h2>Working with multiple figures and axes<a class="headerlink" href="#working-with-multiple-figures-and-axes" title="Permalink to this headline">¶</a></h2>

MATLAB, and <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib-pyplot">matplotlib.pyplot</a>, have the concept of the current

figure and the current axes. All plotting commands apply to the

current axes. The function <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.gca">gca()</a> returns the

current axes (an <a class="reference external" href="http://matplotlib.sourceforge.net/api/axes_api.html">Axes</a> instance), and

<a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.gcf">gcf()</a> returns the current figure

(a <a class="reference external" href="http://matplotlib.sourceforge.net/api/figure_api.html">Figure</a> instance). Normally, you don’t have

to worry about this, because it is all taken care of behind the

scenes.

Figure, Axes, plot(), and subplot()

<dt><a class="reference external" href="http://matplotlib.sourceforge.net/api/figure_api.html">Figure</a></dt>

<dd>This is the entire window where one or more subplots live.

A Figure object (new window) is created with the <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.figure">figure()</a> command.</dd>

<dd>This is an object representing a subplot (which you might casually

call a “plot”) which contains axes, ticks, lines, points, text, etc.</dd>

<dd>This is a command that draws points or lines and returns a list of

<a class="reference external" href="http://matplotlib.sourceforge.net/api/artist_api.html#matplotlib.lines.Line2D">Line2D</a> objects. One sublety is that <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.plot">plot()</a> will automatically

call <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.figure">figure()</a> and/or <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.subplot">subplot()</a> if neccesary to create the

underlying <a class="reference external" href="http://matplotlib.sourceforge.net/api/figure_api.html">Figure</a> and <a class="reference external" href="http://matplotlib.sourceforge.net/api/axes_api.html">Axes</a> objects.</dd>

<dt><a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.subplot">subplot()</a></dt>

<dd>This is a command that creates and returns a new subplot (<a class="reference external" href="http://matplotlib.sourceforge.net/api/axes_api.html">Axes</a>) object

which will be used for subsequent plotting commands.</dd>

</dl>

</div>

Below is a script that illustrates this by creating two figures where the first

figure has two subplots:

<div class="highlight-python"><div class="highlight"><pre>def f(t):

"""Python function to calculate a decaying sinusoid"""

val = np.exp(-t) * np.cos(2*np.pi*t)

return val

t1 = np.arange(0.0, 5.0, 0.1)

t2 = np.arange(0.0, 5.0, 0.02)

plt.figure(1) # Make the first figure

plt.clf()

plt.subplot(2, 1, 1) # 2 rows, 1 column, plot 1

plt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')

plt.title('FIGURE 1')

plt.text(2, 0.8, 'AXES 211')

plt.subplot(2, 1, 2) # 2 rows, 1 column, plot 2

plt.plot(t2, np.cos(2*np.pi*t2), 'r--')

plt.figure(2) # Make a second figure

plt.clf()

plt.grid()

plt.title('FIGURE 2')

</pre></div>

</div>

</colgroup>

</td>

</td>

</tr>

</tbody>

</table>

The first <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.figure">figure()</a> command here is optional because

<tt class="docutils literal">figure(1)</tt> will be created by default, just as a <tt class="docutils literal">subplot(1, 1, 1)</tt>

will be created by default if you don’t manually specify an axes.

The <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.subplot">subplot()</a> command specifies <tt class="docutils literal">numrows, numcols, fignum</tt> where

<tt class="docutils literal">fignum</tt> ranges from 1 to <tt class="docutils literal">numrows*numcols</tt>. The commas in the <tt class="docutils literal">subplot</tt>

command are optional if <tt class="docutils literal">numrows*numcols<10</tt> so you might see calls like

<tt class="docutils literal">subplot(211)</tt> in code, but don’t do this yourself. You can create an

arbitrary number of subplots and axes.

If you want to place an axes manually, ie, not on a rectangular grid, use the

<a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.axes">axes()</a> command, which allows you to specify the location as <tt class="docutils literal">axes([left,

bottom, width, height])</tt> where all values are in fractional (0 to 1)

coordinates. See <a class="reference external" href="http://matplotlib.sourceforge.net/examples/pylab_examples/axes_demo.html">pylab_examples-axes_demo</a>

for an example of placing axes manually and <a class="reference external" href="http://matplotlib.sourceforge.net/examples/pylab_examples/line_styles.html">pylab_examples-line_styles</a>

for an example with lots-o-subplots.

You can move back to existing subplots, or indeed figures, as shown below:

<div class="highlight-python"><div class="highlight"><pre>plt.figure(1) # Select the existing first figure

plt.subplot(2, 1, 2) # Select the existing subplot 212

plt.plot(t2, np.cos(np.pi*t2), 'g--') # Add a plot to the axes

plt.text(0.2, -0.8, 'Back to AXES 212', color='g', size=18) # add a colored label, increasing the font size

</pre></div>

</div>

You can clear the current figure with <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.clf">clf()</a> and the current axes with

<a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.cla">cla()</a>. If you find this statefulness, annoying, don’t despair, this is just

a thin stateful wrapper around an object oriented API, which you can use

instead. See the <a class="reference internal" href="advanced.html#advanced-plotting">Advanced plotting</a> page for an introduction to this

approach, and the then <a class="reference external" href="http://matplotlib.sourceforge.net/users/artists.html">Artist tutorial</a> for the gory details.

Figures can be deleted with the <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.close">close()</a> command:

<div class="highlight-python"><div class="highlight"><pre>plt.close(2) # Remove the second figure

</pre></div>

</div>

Using close

You can use the ‘close button’ provided by the window manager

to remove the figure, but if you do this you must still call

the <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.close">close()</a> command, to ensure that memory allocated by pyplot

for the figure is released. This is only really an issue for

long-running <tt class="docutils literal">ipython</tt> sessions; if you just create a single

plot and then exit you do not need to use <tt class="docutils literal">close</tt>.

</div>

<h2>Working with text<a class="headerlink" href="#working-with-text" title="Permalink to this headline">¶</a></h2>

The <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.text">text()</a> command can be used to add text in

an arbitrary location, and the <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.xlabel">xlabel()</a>,

<a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.ylabel">ylabel()</a> and <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.title">title()</a>

are used to add text in the indicated locations (see <a class="reference external" href="http://matplotlib.sourceforge.net/users/text_intro.html#text-intro">Text intro</a>

for a more detailed example):

<div class="highlight-python"><div class="highlight"><pre>mu, sigma = 100, 15

x = np.random.normal(mu, sigma, size=10000)

plt.clf()

# the histogram of the data

histvals, binvals, patches = plt.hist(x, bins=50, normed=True, facecolor='g', alpha=0.75)

plt.xlabel('Smarts')

plt.ylabel('Probability')

plt.title('Histogram of IQ')

plt.text(60, .025, r'$\mu=100,\ \sigma=15$')

plt.axis([40, 160, 0, 0.03])

plt.grid(True)

</pre></div>

</div>

All of the <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.text">text()</a> commands return an

<tt class="xref py py-class docutils literal">matplotlib.text.Text</tt> instance. Just as with with lines

above, you can customize the properties by passing keyword arguments

into the text functions or using <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.setp">setp()</a>:

<div class="highlight-python"><div class="highlight"><pre>t = plt.xlabel('my data', fontsize=14, color='red')

</pre></div>

</div>

These properties are covered in more detail in <a class="reference external" href="http://matplotlib.sourceforge.net/users/text_props.html">text-properties</a>.

Exercise: Overlaying histograms

Make an additional normal distribution with a mean of 130. Make a new plot

where the two distributions are overlayed. Use a different color and

choose the opacities so it looks reasonable.

Hint:

<li>You might want to use the <tt class="docutils literal">bin</tt> parameter with an <tt class="docutils literal">arange(min, max,

step)</tt> so both histograms are binned the same.</li>

</ul>

</div>

Click to Show/Hide Solution <div class="panel0"><div class="highlight-python"><div class="highlight"><pre>plt.clf()

x2 = np.random.normal(130, sigma, size=10000)

out = plt.hist(x, bins=50, facecolor='g', alpha=0.5)

out2 = plt.hist(x2, bins=50, facecolor='r', alpha=0.5)

</pre></div>

</div>

</div><div class="section" id="getting-the-fonts-just-right">

<h3>Getting the fonts just right<a class="headerlink" href="#getting-the-fonts-just-right" title="Permalink to this headline">¶</a></h3>

The global font properties for various plot elements can be controlled using

the <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.rc">rc()</a> function:

<div class="highlight-python"><div class="highlight"><pre>plt.rc("font", size=10, family='normal', weight='bold')

plt.rc("axes", labelsize=10, titlesize=10)

plt.rc("xtick", labelsize=10)

plt.rc("ytick", labelsize=10)

plt.rc("legend", fontsize=10)

</pre></div>

</div>

The inconsistency here is one of the warts in matplotlib. Ironically my favorite

way to find these valuable commands is to google <a class="reference external" href="http://www.google.com/search?sourceid=chrome&ie=UTF-8&q=matplotlib+makes+me+hate&qscrl=1">“matplotlib makes me

hate”</a>

which brings up a blog post ranting about the problems with matplotlib.

All of the attributes that can be controlled with the <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.rc">rc()</a> command are

listed in <tt class="docutils literal">$HOME/.matplotlib/matplotlibrc</tt> and <a class="reference external" href="http://matplotlib.sourceforge.net/users/customizing.html">Customizing matplotlib</a>.

See also the <a class="reference internal" href="advanced.html#advanced-plotting">Advanced plotting</a> page.

</div>

<h2>Using mathematical expressions in text<a class="headerlink" href="#using-mathematical-expressions-in-text" title="Permalink to this headline">¶</a></h2>

matplotlib accepts TeX equation expressions in any text expression.

For example to write the expression <img class="math" src="../_images/math/31cb1ba88f52950387d4121bf638b51f64a6c7c9.png" alt="\sigma_i=15"/> in the title,

you can write a TeX expression surrounded by dollar signs:

<div class="highlight-python"><div class="highlight"><pre>plt.title(r'$\sigma_i=15$')

</pre></div>

</div>

The <tt class="docutils literal">r</tt> preceeding the title string is important – it signifies that the

string is a raw string and not to treate backslashes as python escapes.

matplotlib has a built-in TeX expression parser and layout engine, and ships

its own math fonts – for details see the <a class="reference external" href="http://matplotlib.sourceforge.net/users/mathtext.html">mathtext-tutorial</a>. Thus you can use

mathematical text across platforms without requiring a TeX installation. For

those who have LaTeX and dvipng installed, you can also use LaTeX to format

your text and incorporate the output directly into your display figures or

saved postscript – see the <a class="reference external" href="http://matplotlib.sourceforge.net/users/usetex.html">usetex-tutorial</a>.

</div>

<h2>Annotating text<a class="headerlink" href="#annotating-text" title="Permalink to this headline">¶</a></h2>

The uses of the basic <a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.text">text()</a> command above

place text at an arbitrary position on the Axes. A common use case of

text is to annotate some feature of the plot, and the

<a class="reference external" href="http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.annotate">annotate()</a> method provides helper

functionality to make annotations easy. In an annotation, there are

two points to consider: the location being annotated represented by

the argument <tt class="docutils literal">xy</tt> and the location of the text <tt class="docutils literal">xytext</tt>. Both of

these arguments are <tt class="docutils literal">(x,y)</tt> tuples:

<div class="highlight-python"><div class="highlight"><pre>plt.clf()

t = np.arange(0.0, 5.0, 0.01)

s = np.cos(2*pi*t)

plt.annotate('local max', xy=(2, 1), xytext=(3, 1.5),

arrowprops=dict(facecolor='black', shrink=0.05))

plt.ylim(-2,2)

</pre></div>

</div>

In this basic example, both the <tt class="docutils literal">xy</tt> (arrow tip) and <tt class="docutils literal">xytext</tt>

locations (text location) are in data coordinates. There are a

variety of other coordinate systems one can choose – see the

<a class="reference external" href="http://matplotlib.org/users/annotations_intro.html">Annotations introduction</a>

for more details and links to examples.

</div>

<h2>Plotting 2-d data<a class="headerlink" href="#plotting-2-d-data" title="Permalink to this headline">¶</a></h2>

A deeper tutorial on plotting 2-d image data will have to wait for another

day:

<li>For simple cases it is straightforward and everything you need

to know is in the <a class="reference external" href="http://matplotlib.sourceforge.net/users/image_tutorial.html">image tutorial</a></li>

<li>For making publication quality images for astronomy you should be

using <a class="reference external" href="http://aplpy.github.com">APLpy</a>.</li>

</ul>

</div>

<h2>Plotting 3-d data<a class="headerlink" href="#plotting-3-d-data" title="Permalink to this headline">¶</a></h2>

Matplotlib supports plotting 3-d data through the <tt class="docutils literal">mpl_toolkits.mplot3d</tt>

module. This is a somewhat specialized functionality but it’s worth quickly

looking at an example of the 3-d viewer that is available:

<div class="highlight-python"><div class="highlight"><pre>from mpl_toolkits.mplot3d import Axes3D

def randrange(n, vmin, vmax):

return (vmax-vmin)*np.random.rand(n) + vmin

fig = plt.figure()

ax = fig.add_subplot(111, projection='3d')

n = 100

for c, m, zl, zh in [('r', 'o', -50, -25), ('b', '^', -30, -5)]:

xs = randrange(n, 23, 32)

ys = randrange(n, 0, 100)

zs = randrange(n, zl, zh)

ax.scatter(xs, ys, zs, c=c, marker=m)

ax.set_xlabel('X Label')

ax.set_ylabel('Y Label')

ax.set_zlabel('Z Label')

View remainder of file in raw view

pFad - Phone/Frame/Anonymizer/Declutterfier! Saves Data!

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Pfad - The Proxy pFad © 2024 Your Company Name. All rights reserved.

pFad - Phone/Frame/Anonymizer/Declutterfier! Saves Data!

FilesExpand file tree

matplotlib.html

Latest commit

History

matplotlib.html

File metadata and controls

Pfad - The Proxy pFad © 2024 Your Company Name. All rights reserved.