1# http://pyrocko.org - GPLv3 

2# 

3# The Pyrocko Developers, 21st Century 

4# ---|P------/S----------~Lg---------- 

5 

6''' 

7Utility functions and defintions for a common plot style throughout Pyrocko. 

8 

9Functions with name prefix ``mpl_`` are Matplotlib specific. All others should 

10be toolkit-agnostic. 

11 

12The following skeleton can be used to produce nice PDF figures, with absolute 

13sizes derived from paper and font sizes 

14(file :file:`/../../examples/plot_skeleton.py` 

15in the Pyrocko source directory):: 

16 

17 from matplotlib import pyplot as plt 

18 

19 from pyrocko.plot import mpl_init, mpl_margins, mpl_papersize 

20 # from pyrocko.plot import mpl_labelspace 

21 

22 fontsize = 9. # in points 

23 

24 # set some Pyrocko style defaults 

25 mpl_init(fontsize=fontsize) 

26 

27 fig = plt.figure(figsize=mpl_papersize('a4', 'landscape')) 

28 

29 # let margins be proportional to selected font size, e.g. top and bottom 

30 # margin are set to be 5*fontsize = 45 [points] 

31 labelpos = mpl_margins(fig, w=7., h=5., units=fontsize) 

32 

33 axes = fig.add_subplot(1, 1, 1) 

34 

35 # positioning of axis labels 

36 # mpl_labelspace(axes) # either: relative to axis tick labels 

37 labelpos(axes, 2., 1.5) # or: relative to left/bottom paper edge 

38 

39 axes.plot([0, 1], [0, 9]) 

40 

41 axes.set_xlabel('Time [s]') 

42 axes.set_ylabel('Amplitude [m]') 

43 

44 fig.savefig('plot_skeleton.pdf') 

45 

46 plt.show() 

47 

48''' 

49 

50import math 

51import random 

52import time 

53import calendar 

54import numpy as num 

55 

56from pyrocko.util import parse_md, time_to_str, arange2, to_time_float 

57from pyrocko.guts import StringChoice, Float, Int, Bool, Tuple, Object 

58 

59 

60__doc__ += parse_md(__file__) 

61 

62 

63guts_prefix = 'pf' 

64 

65point = 1. 

66inch = 72. 

67cm = 28.3465 

68 

69units_dict = { 

70 'point': point, 

71 'inch': inch, 

72 'cm': cm, 

73} 

74 

75_doc_units = "``'point'``, ``'inch'``, or ``'cm'``" 

76 

77 

78def apply_units(x, units): 

79 if isinstance(units, str): 

80 units = units_dict[units] 

81 

82 if isinstance(x, (int, float)): 

83 return x / units 

84 else: 

85 if isinstance(x, tuple): 

86 return tuple(v / units for v in x) 

87 else: 

88 return list(v / units for v in x) 

89 

90 

91tango_colors = { 

92 'butter1': (252, 233, 79), 

93 'butter2': (237, 212, 0), 

94 'butter3': (196, 160, 0), 

95 'chameleon1': (138, 226, 52), 

96 'chameleon2': (115, 210, 22), 

97 'chameleon3': (78, 154, 6), 

98 'orange1': (252, 175, 62), 

99 'orange2': (245, 121, 0), 

100 'orange3': (206, 92, 0), 

101 'skyblue1': (114, 159, 207), 

102 'skyblue2': (52, 101, 164), 

103 'skyblue3': (32, 74, 135), 

104 'plum1': (173, 127, 168), 

105 'plum2': (117, 80, 123), 

106 'plum3': (92, 53, 102), 

107 'chocolate1': (233, 185, 110), 

108 'chocolate2': (193, 125, 17), 

109 'chocolate3': (143, 89, 2), 

110 'scarletred1': (239, 41, 41), 

111 'scarletred2': (204, 0, 0), 

112 'scarletred3': (164, 0, 0), 

113 'aluminium1': (238, 238, 236), 

114 'aluminium2': (211, 215, 207), 

115 'aluminium3': (186, 189, 182), 

116 'aluminium4': (136, 138, 133), 

117 'aluminium5': (85, 87, 83), 

118 'aluminium6': (46, 52, 54)} 

119 

120 

121graph_colors = [ 

122 tango_colors[_x] for _x in ( 

123 'scarletred2', 

124 'skyblue3', 

125 'chameleon3', 

126 'orange2', 

127 'plum2', 

128 'chocolate2', 

129 'butter2')] 

130 

131 

132def color(x=None): 

133 if x is None: 

134 return tuple([random.randint(0, 255) for _x in 'rgb']) 

135 

136 if isinstance(x, int): 

137 if 0 <= x < len(graph_colors): 

138 return graph_colors[x] 

139 else: 

140 return (0, 0, 0) 

141 

142 elif isinstance(x, str): 

143 if x in tango_colors: 

144 return tango_colors[x] 

145 

146 elif isinstance(x, tuple): 

147 return x 

148 

149 assert False, "Don't know what to do with this color definition: %s" % x 

150 

151 

152def to01(c): 

153 return tuple(x/255. for x in c) 

154 

155 

156def nice_value(x): 

157 ''' 

158 Round x to nice value. 

159 ''' 

160 

161 if x == 0.0: 

162 return 0.0 

163 

164 exp = 1.0 

165 sign = 1 

166 if x < 0.0: 

167 x = -x 

168 sign = -1 

169 while x >= 1.0: 

170 x /= 10.0 

171 exp *= 10.0 

172 while x < 0.1: 

173 x *= 10.0 

174 exp /= 10.0 

175 

176 if x >= 0.75: 

177 return sign * 1.0 * exp 

178 if x >= 0.35: 

179 return sign * 0.5 * exp 

180 if x >= 0.15: 

181 return sign * 0.2 * exp 

182 

183 return sign * 0.1 * exp 

184 

185 

186_papersizes_list = [ 

187 ('a0', (2380., 3368.)), 

188 ('a1', (1684., 2380.)), 

189 ('a2', (1190., 1684.)), 

190 ('a3', (842., 1190.)), 

191 ('a4', (595., 842.)), 

192 ('a5', (421., 595.)), 

193 ('a6', (297., 421.)), 

194 ('a7', (210., 297.)), 

195 ('a8', (148., 210.)), 

196 ('a9', (105., 148.)), 

197 ('a10', (74., 105.)), 

198 ('b0', (2836., 4008.)), 

199 ('b1', (2004., 2836.)), 

200 ('b2', (1418., 2004.)), 

201 ('b3', (1002., 1418.)), 

202 ('b4', (709., 1002.)), 

203 ('b5', (501., 709.)), 

204 ('archa', (648., 864.)), 

205 ('archb', (864., 1296.)), 

206 ('archc', (1296., 1728.)), 

207 ('archd', (1728., 2592.)), 

208 ('arche', (2592., 3456.)), 

209 ('flsa', (612., 936.)), 

210 ('halfletter', (396., 612.)), 

211 ('note', (540., 720.)), 

212 ('letter', (612., 792.)), 

213 ('legal', (612., 1008.)), 

214 ('11x17', (792., 1224.)), 

215 ('ledger', (1224., 792.))] 

216 

217papersizes = dict(_papersizes_list) 

218 

219_doc_papersizes = ', '.join("``'%s'``" % k for (k, _) in _papersizes_list) 

220 

221 

222def papersize(paper, orientation='landscape', units='point'): 

223 

224 ''' 

225 Get paper size from string. 

226 

227 :param paper: string selecting paper size. Choices: %s 

228 :param orientation: ``'landscape'``, or ``'portrait'`` 

229 :param units: Units to be returned. Choices: %s 

230 

231 :returns: ``(width, height)`` 

232 ''' 

233 

234 assert orientation in ('landscape', 'portrait') 

235 

236 w, h = papersizes[paper.lower()] 

237 if orientation == 'landscape': 

238 w, h = h, w 

239 

240 return apply_units((w, h), units) 

241 

242 

243papersize.__doc__ %= (_doc_papersizes, _doc_units) 

244 

245 

246class AutoScaleMode(StringChoice): 

247 ''' 

248 Mode of operation for auto-scaling. 

249 

250 ================ ================================================== 

251 mode description 

252 ================ ================================================== 

253 ``'auto'``: Look at data range and choose one of the choices 

254 below. 

255 ``'min-max'``: Output range is selected to include data range. 

256 ``'0-max'``: Output range shall start at zero and end at data 

257 max. 

258 ``'min-0'``: Output range shall start at data min and end at 

259 zero. 

260 ``'symmetric'``: Output range shall by symmetric by zero. 

261 ``'off'``: Similar to ``'min-max'``, but snap and space are 

262 disabled, such that the output range always 

263 exactly matches the data range. 

264 ================ ================================================== 

265 ''' 

266 choices = ['auto', 'min-max', '0-max', 'min-0', 'symmetric', 'off'] 

267 

268 

269class AutoScaler(Object): 

270 

271 ''' 

272 Tunable 1D autoscaling based on data range. 

273 

274 Instances of this class may be used to determine nice minima, maxima and 

275 increments for ax annotations, as well as suitable common exponents for 

276 notation. 

277 

278 The autoscaling process is guided by the following public attributes: 

279 ''' 

280 

281 approx_ticks = Float.T( 

282 default=7.0, 

283 help='Approximate number of increment steps (tickmarks) to generate.') 

284 

285 mode = AutoScaleMode.T( 

286 default='auto', 

287 help='''Mode of operation for auto-scaling.''') 

288 

289 exp = Int.T( 

290 optional=True, 

291 help='If defined, override automatically determined exponent for ' 

292 'notation by the given value.') 

293 

294 snap = Bool.T( 

295 default=False, 

296 help='If set to True, snap output range to multiples of increment. ' 

297 "This parameter has no effect, if mode is set to ``'off'``.") 

298 

299 inc = Float.T( 

300 optional=True, 

301 help='If defined, override automatically determined tick increment by ' 

302 'the given value.') 

303 

304 space = Float.T( 

305 default=0.0, 

306 help='Add some padding to the range. The value given, is the fraction ' 

307 'by which the output range is increased on each side. If mode is ' 

308 "``'0-max'`` or ``'min-0'``, the end at zero is kept fixed " 

309 'at zero. This parameter has no effect if mode is set to ' 

310 "``'off'``.") 

311 

312 exp_factor = Int.T( 

313 default=3, 

314 help='Exponent of notation is chosen to be a multiple of this value.') 

315 

316 no_exp_interval = Tuple.T( 

317 2, Int.T(), 

318 default=(-3, 5), 

319 help='Range of exponent, for which no exponential notation is a' 

320 'allowed.') 

321 

322 def __init__( 

323 self, 

324 approx_ticks=7.0, 

325 mode='auto', 

326 exp=None, 

327 snap=False, 

328 inc=None, 

329 space=0.0, 

330 exp_factor=3, 

331 no_exp_interval=(-3, 5)): 

332 

333 ''' 

334 Create new AutoScaler instance. 

335 

336 The parameters are described in the AutoScaler documentation. 

337 ''' 

338 

339 Object.__init__( 

340 self, 

341 approx_ticks=approx_ticks, 

342 mode=mode, 

343 exp=exp, 

344 snap=snap, 

345 inc=inc, 

346 space=space, 

347 exp_factor=exp_factor, 

348 no_exp_interval=no_exp_interval) 

349 

350 def make_scale(self, data_range, override_mode=None): 

351 

352 ''' 

353 Get nice minimum, maximum and increment for given data range. 

354 

355 Returns ``(minimum, maximum, increment)`` or ``(maximum, minimum, 

356 -increment)``, depending on whether data_range is ``(data_min, 

357 data_max)`` or ``(data_max, data_min)``. If ``override_mode`` is 

358 defined, the mode attribute is temporarily overridden by the given 

359 value. 

360 ''' 

361 

362 data_min = min(data_range) 

363 data_max = max(data_range) 

364 

365 is_reverse = (data_range[0] > data_range[1]) 

366 

367 a = self.mode 

368 if self.mode == 'auto': 

369 a = self.guess_autoscale_mode(data_min, data_max) 

370 

371 if override_mode is not None: 

372 a = override_mode 

373 

374 mi, ma = 0, 0 

375 if a == 'off': 

376 mi, ma = data_min, data_max 

377 elif a == '0-max': 

378 mi = 0.0 

379 if data_max > 0.0: 

380 ma = data_max 

381 else: 

382 ma = 1.0 

383 elif a == 'min-0': 

384 ma = 0.0 

385 if data_min < 0.0: 

386 mi = data_min 

387 else: 

388 mi = -1.0 

389 elif a == 'min-max': 

390 mi, ma = data_min, data_max 

391 elif a == 'symmetric': 

392 m = max(abs(data_min), abs(data_max)) 

393 mi = -m 

394 ma = m 

395 

396 nmi = mi 

397 if (mi != 0. or a == 'min-max') and a != 'off': 

398 nmi = mi - self.space*(ma-mi) 

399 

400 nma = ma 

401 if (ma != 0. or a == 'min-max') and a != 'off': 

402 nma = ma + self.space*(ma-mi) 

403 

404 mi, ma = nmi, nma 

405 

406 if mi == ma and a != 'off': 

407 mi -= 1.0 

408 ma += 1.0 

409 

410 # make nice tick increment 

411 if self.inc is not None: 

412 inc = self.inc 

413 else: 

414 if self.approx_ticks > 0.: 

415 inc = nice_value((ma-mi) / self.approx_ticks) 

416 else: 

417 inc = nice_value((ma-mi)*10.) 

418 

419 if inc == 0.0: 

420 inc = 1.0 

421 

422 # snap min and max to ticks if this is wanted 

423 if self.snap and a != 'off': 

424 ma = inc * math.ceil(ma/inc) 

425 mi = inc * math.floor(mi/inc) 

426 

427 if is_reverse: 

428 return ma, mi, -inc 

429 else: 

430 return mi, ma, inc 

431 

432 def make_exp(self, x): 

433 ''' 

434 Get nice exponent for notation of ``x``. 

435 

436 For ax annotations, give tick increment as ``x``. 

437 ''' 

438 

439 if self.exp is not None: 

440 return self.exp 

441 

442 x = abs(x) 

443 if x == 0.0: 

444 return 0 

445 

446 if 10**self.no_exp_interval[0] <= x <= 10**self.no_exp_interval[1]: 

447 return 0 

448 

449 return math.floor(math.log10(x)/self.exp_factor)*self.exp_factor 

450 

451 def guess_autoscale_mode(self, data_min, data_max): 

452 ''' 

453 Guess mode of operation, based on data range. 

454 

455 Used to map ``'auto'`` mode to ``'0-max'``, ``'min-0'``, ``'min-max'`` 

456 or ``'symmetric'``. 

457 ''' 

458 

459 a = 'min-max' 

460 if data_min >= 0.0: 

461 if data_min < data_max/2.: 

462 a = '0-max' 

463 else: 

464 a = 'min-max' 

465 if data_max <= 0.0: 

466 if data_max > data_min/2.: 

467 a = 'min-0' 

468 else: 

469 a = 'min-max' 

470 if data_min < 0.0 and data_max > 0.0: 

471 if abs((abs(data_max)-abs(data_min)) / 

472 (abs(data_max)+abs(data_min))) < 0.5: 

473 a = 'symmetric' 

474 else: 

475 a = 'min-max' 

476 return a 

477 

478 

479# below, some convenience functions for matplotlib plotting 

480 

481def mpl_init(fontsize=10): 

482 ''' 

483 Initialize Matplotlib rc parameters Pyrocko style. 

484 

485 Returns the matplotlib.pyplot module for convenience. 

486 ''' 

487 

488 import matplotlib 

489 

490 matplotlib.rcdefaults() 

491 matplotlib.rc('font', size=fontsize) 

492 matplotlib.rc('axes', linewidth=1.5) 

493 matplotlib.rc('xtick', direction='out') 

494 matplotlib.rc('ytick', direction='out') 

495 ts = fontsize * 0.7071 

496 matplotlib.rc('xtick.major', size=ts, width=0.5, pad=ts) 

497 matplotlib.rc('ytick.major', size=ts, width=0.5, pad=ts) 

498 matplotlib.rc('figure', facecolor='white') 

499 

500 try: 

501 from cycler import cycler 

502 matplotlib.rc( 

503 'axes', prop_cycle=cycler( 

504 'color', [to01(x) for x in graph_colors])) 

505 except (ImportError, KeyError): 

506 try: 

507 matplotlib.rc('axes', color_cycle=[to01(x) for x in graph_colors]) 

508 except KeyError: 

509 pass 

510 

511 from matplotlib import pyplot as plt 

512 return plt 

513 

514 

515def mpl_margins( 

516 fig, 

517 left=1.0, top=1.0, right=1.0, bottom=1.0, 

518 wspace=None, hspace=None, 

519 w=None, h=None, 

520 nw=None, nh=None, 

521 all=None, 

522 units='inch'): 

523 

524 ''' 

525 Adjust Matplotlib subplot params with absolute values in user units. 

526 

527 Calls :py:meth:`matplotlib.figure.Figure.subplots_adjust` on ``fig`` with 

528 absolute margin widths/heights rather than relative values. If ``wspace`` 

529 or ``hspace`` are given, the number of subplots must be given in ``nw`` 

530 and ``nh`` because ``subplots_adjust()`` treats the spacing parameters 

531 relative to the subplot width and height. 

532 

533 :param units: Unit multiplier or unit as string: %s 

534 :param left,right,top,bottom: margin space 

535 :param w: set ``left`` and ``right`` at once 

536 :param h: set ``top`` and ``bottom`` at once 

537 :param all: set ``left``, ``top``, ``right``, and ``bottom`` at once 

538 :param nw: number of subplots horizontally 

539 :param nh: number of subplots vertically 

540 :param wspace: horizontal spacing between subplots 

541 :param hspace: vertical spacing between subplots 

542 ''' 

543 

544 left, top, right, bottom = map( 

545 float, (left, top, right, bottom)) 

546 

547 if w is not None: 

548 left = right = float(w) 

549 

550 if h is not None: 

551 top = bottom = float(h) 

552 

553 if all is not None: 

554 left = right = top = bottom = float(all) 

555 

556 ufac = units_dict.get(units, units) / inch 

557 

558 left *= ufac 

559 right *= ufac 

560 top *= ufac 

561 bottom *= ufac 

562 

563 width, height = fig.get_size_inches() 

564 

565 rel_wspace = None 

566 rel_hspace = None 

567 

568 if wspace is not None: 

569 wspace *= ufac 

570 if nw is None: 

571 raise ValueError('wspace must be given in combination with nw') 

572 

573 wsub = (width - left - right - (nw-1) * wspace) / nw 

574 rel_wspace = wspace / wsub 

575 else: 

576 wsub = width - left - right 

577 

578 if hspace is not None: 

579 hspace *= ufac 

580 if nh is None: 

581 raise ValueError('hspace must be given in combination with nh') 

582 

583 hsub = (height - top - bottom - (nh-1) * hspace) / nh 

584 rel_hspace = hspace / hsub 

585 else: 

586 hsub = height - top - bottom 

587 

588 fig.subplots_adjust( 

589 left=left/width, 

590 right=1.0 - right/width, 

591 bottom=bottom/height, 

592 top=1.0 - top/height, 

593 wspace=rel_wspace, 

594 hspace=rel_hspace) 

595 

596 def labelpos(axes, xpos=0., ypos=0.): 

597 xpos *= ufac 

598 ypos *= ufac 

599 axes.get_yaxis().set_label_coords(-((left-xpos) / wsub), 0.5) 

600 axes.get_xaxis().set_label_coords(0.5, -((bottom-ypos) / hsub)) 

601 

602 return labelpos 

603 

604 

605mpl_margins.__doc__ %= _doc_units 

606 

607 

608def mpl_labelspace(axes): 

609 ''' 

610 Add some extra padding between label and ax annotations. 

611 ''' 

612 

613 xa = axes.get_xaxis() 

614 ya = axes.get_yaxis() 

615 for attr in ('labelpad', 'LABELPAD'): 

616 if hasattr(xa, attr): 

617 setattr(xa, attr, xa.get_label().get_fontsize()) 

618 setattr(ya, attr, ya.get_label().get_fontsize()) 

619 break 

620 

621 

622def mpl_papersize(paper, orientation='landscape'): 

623 ''' 

624 Get paper size in inch from string. 

625 

626 Returns argument suitable to be passed to the ``figsize`` argument of 

627 :py:func:`pyplot.figure`. 

628 

629 :param paper: string selecting paper size. Choices: %s 

630 :param orientation: ``'landscape'``, or ``'portrait'`` 

631 

632 :returns: ``(width, height)`` 

633 ''' 

634 

635 return papersize(paper, orientation=orientation, units='inch') 

636 

637 

638mpl_papersize.__doc__ %= _doc_papersizes 

639 

640 

641class InvalidColorDef(ValueError): 

642 pass 

643 

644 

645def mpl_graph_color(i): 

646 return to01(graph_colors[i % len(graph_colors)]) 

647 

648 

649def mpl_color(x): 

650 ''' 

651 Convert string into color float tuple ranged 0-1 for use with Matplotlib. 

652 

653 Accepts tango color names, matplotlib color names, and slash-separated 

654 strings. In the latter case, if values are larger than 1., the color 

655 is interpreted as 0-255 ranged. Single-valued (grayscale), three-valued 

656 (color) and four-valued (color with alpha) are accepted. An 

657 :py:exc:`InvalidColorDef` exception is raised when the convertion fails. 

658 ''' 

659 

660 import matplotlib.colors 

661 

662 if x in tango_colors: 

663 return to01(tango_colors[x]) 

664 

665 s = x.split('/') 

666 if len(s) in (1, 3, 4): 

667 try: 

668 vals = list(map(float, s)) 

669 if all(0. <= v <= 1. for v in vals): 

670 return vals 

671 

672 elif all(0. <= v <= 255. for v in vals): 

673 return to01(vals) 

674 

675 except ValueError: 

676 try: 

677 return matplotlib.colors.colorConverter.to_rgba(x) 

678 except Exception: 

679 pass 

680 

681 raise InvalidColorDef('invalid color definition: %s' % x) 

682 

683 

684hours = 3600. 

685days = hours*24 

686approx_months = days*30.5 

687approx_years = days*365 

688 

689 

690nice_time_tinc_inc_approx_units = { 

691 'seconds': 1, 

692 'months': approx_months, 

693 'years': approx_years} 

694 

695 

696def nice_time_tick_inc(tinc_approx): 

697 

698 if tinc_approx >= approx_years: 

699 return max(1.0, nice_value(tinc_approx / approx_years)), 'years' 

700 

701 elif tinc_approx >= approx_months: 

702 nice = [1, 2, 3, 6] 

703 for tinc in nice: 

704 if tinc*approx_months >= tinc_approx or tinc == nice[-1]: 

705 return tinc, 'months' 

706 

707 elif tinc_approx > days: 

708 return nice_value(tinc_approx / days) * days, 'seconds' 

709 

710 elif tinc_approx >= 1.0: 

711 nice = [ 

712 1., 2., 5., 10., 20., 30., 60., 120., 300., 600., 1200., 1800., 

713 1*hours, 2*hours, 3*hours, 6*hours, 12*hours, days, 2*days] 

714 

715 for tinc in nice: 

716 if tinc >= tinc_approx or tinc == nice[-1]: 

717 return tinc, 'seconds' 

718 

719 else: 

720 return nice_value(tinc_approx), 'seconds' 

721 

722 

723def nice_time_tick_inc_approx_secs(tinc_approx): 

724 v, unit = nice_time_tick_inc(tinc_approx) 

725 return v * nice_time_tinc_inc_approx_units[unit] 

726 

727 

728def time_tick_labels(tmin, tmax, tinc, tinc_unit): 

729 

730 if tinc_unit == 'years': 

731 tt = time.gmtime(int(tmin)) 

732 tmin_year = tt[0] 

733 if tt[1:6] != (1, 1, 0, 0, 0): 

734 tmin_year += 1 

735 

736 tmax_year = time.gmtime(int(tmax))[0] 

737 

738 tick_times_year = arange2( 

739 math.ceil(tmin_year/tinc)*tinc, 

740 math.floor(tmax_year/tinc)*tinc, 

741 tinc).astype(int) 

742 

743 times = [ 

744 to_time_float(calendar.timegm((year, 1, 1, 0, 0, 0))) 

745 for year in tick_times_year] 

746 

747 labels = ['%04i' % year for year in tick_times_year] 

748 

749 elif tinc_unit == 'months': 

750 tt = time.gmtime(int(tmin)) 

751 tmin_ym = tt[0] * 12 + (tt[1] - 1) 

752 if tt[2:6] != (1, 0, 0, 0): 

753 tmin_ym += 1 

754 

755 tt = time.gmtime(int(tmax)) 

756 tmax_ym = tt[0] * 12 + (tt[1] - 1) 

757 

758 tick_times_ym = arange2( 

759 math.ceil(tmin_ym/tinc)*tinc, 

760 math.floor(tmax_ym/tinc)*tinc, tinc).astype(int) 

761 

762 times = [ 

763 to_time_float(calendar.timegm((ym // 12, ym % 12 + 1, 1, 0, 0, 0))) 

764 for ym in tick_times_ym] 

765 

766 labels = [ 

767 '%04i-%02i' % (ym // 12, ym % 12 + 1) for ym in tick_times_ym] 

768 

769 elif tinc_unit == 'seconds': 

770 imin = int(num.ceil(tmin/tinc)) 

771 imax = int(num.floor(tmax/tinc)) 

772 nticks = imax - imin + 1 

773 tmin_ticks = imin * tinc 

774 times = tmin_ticks + num.arange(nticks) * tinc 

775 times = times.tolist() 

776 

777 if tinc < 1e-6: 

778 fmt = '%Y-%m-%d.%H:%M:%S.9FRAC' 

779 elif tinc < 1e-3: 

780 fmt = '%Y-%m-%d.%H:%M:%S.6FRAC' 

781 elif tinc < 1.0: 

782 fmt = '%Y-%m-%d.%H:%M:%S.3FRAC' 

783 elif tinc < 60: 

784 fmt = '%Y-%m-%d.%H:%M:%S' 

785 elif tinc < 3600.*24: 

786 fmt = '%Y-%m-%d.%H:%M' 

787 else: 

788 fmt = '%Y-%m-%d' 

789 

790 nwords = len(fmt.split('.')) 

791 

792 labels = [time_to_str(t, format=fmt) for t in times] 

793 labels_weeded = [] 

794 have_ymd = have_hms = False 

795 ymd = hms = '' 

796 for ilab, lab in reversed(list(enumerate(labels))): 

797 words = lab.split('.') 

798 if nwords > 2: 

799 words[2] = '.' + words[2] 

800 if float(words[2]) == 0.0: # or (ilab == 0 and not have_hms): 

801 have_hms = True 

802 else: 

803 hms = words[1] 

804 words[1] = '' 

805 else: 

806 have_hms = True 

807 

808 if nwords > 1: 

809 if words[1] in ('00:00', '00:00:00'): # or (ilab == 0 and not have_ymd): # noqa 

810 have_ymd = True 

811 else: 

812 ymd = words[0] 

813 words[0] = '' 

814 else: 

815 have_ymd = True 

816 

817 labels_weeded.append('\n'.join(reversed(words))) 

818 

819 labels = list(reversed(labels_weeded)) 

820 if (not have_ymd or not have_hms) and (hms or ymd): 

821 words = ([''] if nwords > 2 else []) + [ 

822 hms if not have_hms else '', 

823 ymd if not have_ymd else ''] 

824 

825 labels[0:0] = ['\n'.join(words)] 

826 times[0:0] = [tmin] 

827 

828 return times, labels 

829 

830 

831def mpl_time_axis(axes, approx_ticks=5.): 

832 

833 ''' 

834 Configure x axis of a matplotlib axes object for interactive time display. 

835 

836 :param axes: Axes to be configured. 

837 :type axes: :py:class:`matplotlib.axes.Axes` 

838 

839 :param approx_ticks: Approximate number of ticks to create. 

840 :type approx_ticks: float 

841 

842 This function tries to use nice tick increments and tick labels for time 

843 ranges from microseconds to years, similar to how this is handled in 

844 Snuffler. 

845 ''' 

846 

847 from matplotlib.ticker import Locator, Formatter 

848 

849 class labeled_float(float): 

850 pass 

851 

852 class TimeLocator(Locator): 

853 

854 def __init__(self, approx_ticks=5.): 

855 self._approx_ticks = approx_ticks 

856 Locator.__init__(self) 

857 

858 def __call__(self): 

859 vmin, vmax = self.axis.get_view_interval() 

860 return self.tick_values(vmin, vmax) 

861 

862 def tick_values(self, vmin, vmax): 

863 if vmax < vmin: 

864 vmin, vmax = vmax, vmin 

865 

866 if vmin == vmax: 

867 return [] 

868 

869 tinc_approx = (vmax - vmin) / self._approx_ticks 

870 tinc, tinc_unit = nice_time_tick_inc(tinc_approx) 

871 times, labels = time_tick_labels(vmin, vmax, tinc, tinc_unit) 

872 ftimes = [] 

873 for t, label in zip(times, labels): 

874 ftime = labeled_float(t) 

875 ftime._mpl_label = label 

876 ftimes.append(ftime) 

877 

878 return self.raise_if_exceeds(ftimes) 

879 

880 class TimeFormatter(Formatter): 

881 

882 def __call__(self, x, pos=None): 

883 if isinstance(x, labeled_float): 

884 return x._mpl_label 

885 else: 

886 return time_to_str(x, format='%Y-%m-%d %H:%M:%S.6FRAC') 

887 

888 axes.xaxis.set_major_locator(TimeLocator(approx_ticks=approx_ticks)) 

889 axes.xaxis.set_major_formatter(TimeFormatter())