1# http://pyrocko.org - GPLv3 

2# 

3# The Pyrocko Developers, 21st Century 

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

5from __future__ import absolute_import, print_function 

6 

7import math 

8import random 

9import logging 

10 

11try: 

12 from StringIO import StringIO as BytesIO 

13except ImportError: 

14 from io import BytesIO 

15 

16import numpy as num 

17 

18from pyrocko.guts import (Object, Float, Bool, Int, Tuple, String, List, 

19 Unicode, Dict) 

20from pyrocko.guts_array import Array 

21from pyrocko.dataset import topo 

22from pyrocko import orthodrome as od 

23from . import gmtpy 

24 

25try: 

26 newstr = unicode 

27except NameError: 

28 newstr = str 

29 

30points_in_region = od.points_in_region 

31 

32logger = logging.getLogger('pyrocko.plot.automap') 

33 

34earthradius = 6371000.0 

35r2d = 180./math.pi 

36d2r = 1./r2d 

37km = 1000. 

38d2m = d2r*earthradius 

39m2d = 1./d2m 

40cm = gmtpy.cm 

41 

42 

43def darken(c, f=0.7): 

44 return (c[0]*f, c[1]*f, c[2]*f) 

45 

46 

47def corners(lon, lat, w, h): 

48 ll_lat, ll_lon = od.ne_to_latlon(lat, lon, -0.5*h, -0.5*w) 

49 ur_lat, ur_lon = od.ne_to_latlon(lat, lon, 0.5*h, 0.5*w) 

50 return ll_lon, ll_lat, ur_lon, ur_lat 

51 

52 

53def extent(lon, lat, w, h, n): 

54 x = num.linspace(-0.5*w, 0.5*w, n) 

55 y = num.linspace(-0.5*h, 0.5*h, n) 

56 slats, slons = od.ne_to_latlon(lat, lon, y[0], x) 

57 nlats, nlons = od.ne_to_latlon(lat, lon, y[-1], x) 

58 south = slats.min() 

59 north = nlats.max() 

60 

61 wlats, wlons = od.ne_to_latlon(lat, lon, y, x[0]) 

62 elats, elons = od.ne_to_latlon(lat, lon, y, x[-1]) 

63 elons = num.where(elons < wlons, elons + 360., elons) 

64 

65 if elons.max() - elons.min() > 180 or wlons.max() - wlons.min() > 180.: 

66 west = -180. 

67 east = 180. 

68 else: 

69 west = wlons.min() 

70 east = elons.max() 

71 

72 return topo.positive_region((west, east, south, north)) 

73 

74 

75class NoTopo(Exception): 

76 pass 

77 

78 

79class OutOfBounds(Exception): 

80 pass 

81 

82 

83class FloatTile(Object): 

84 xmin = Float.T() 

85 ymin = Float.T() 

86 dx = Float.T() 

87 dy = Float.T() 

88 data = Array.T(shape=(None, None), dtype=float, serialize_as='table') 

89 

90 def __init__(self, xmin, ymin, dx, dy, data): 

91 Object.__init__(self, init_props=False) 

92 self.xmin = float(xmin) 

93 self.ymin = float(ymin) 

94 self.dx = float(dx) 

95 self.dy = float(dy) 

96 self.data = data 

97 self._set_maxes() 

98 

99 def _set_maxes(self): 

100 self.ny, self.nx = self.data.shape 

101 self.xmax = self.xmin + (self.nx-1) * self.dx 

102 self.ymax = self.ymin + (self.ny-1) * self.dy 

103 

104 def x(self): 

105 return self.xmin + num.arange(self.nx) * self.dx 

106 

107 def y(self): 

108 return self.ymin + num.arange(self.ny) * self.dy 

109 

110 def get(self, x, y): 

111 ix = int(round((x - self.xmin) / self.dx)) 

112 iy = int(round((y - self.ymin) / self.dy)) 

113 if 0 <= ix < self.nx and 0 <= iy < self.ny: 

114 return self.data[iy, ix] 

115 else: 

116 raise OutOfBounds() 

117 

118 

119class City(Object): 

120 def __init__(self, name, lat, lon, population=None, asciiname=None): 

121 name = newstr(name) 

122 lat = float(lat) 

123 lon = float(lon) 

124 if asciiname is None: 

125 asciiname = name.encode('ascii', errors='replace') 

126 

127 if population is None: 

128 population = 0 

129 else: 

130 population = int(population) 

131 

132 Object.__init__(self, name=name, lat=lat, lon=lon, 

133 population=population, asciiname=asciiname) 

134 

135 name = Unicode.T() 

136 lat = Float.T() 

137 lon = Float.T() 

138 population = Int.T() 

139 asciiname = String.T() 

140 

141 

142class Map(Object): 

143 lat = Float.T(optional=True) 

144 lon = Float.T(optional=True) 

145 radius = Float.T(optional=True) 

146 width = Float.T(default=20.) 

147 height = Float.T(default=14.) 

148 margins = List.T(Float.T()) 

149 illuminate = Bool.T(default=True) 

150 skip_feature_factor = Float.T(default=0.02) 

151 show_grid = Bool.T(default=False) 

152 show_topo = Bool.T(default=True) 

153 show_scale = Bool.T(default=False) 

154 show_topo_scale = Bool.T(default=False) 

155 show_center_mark = Bool.T(default=False) 

156 show_rivers = Bool.T(default=True) 

157 show_plates = Bool.T(default=False) 

158 show_boundaries = Bool.T(default=False) 

159 illuminate_factor_land = Float.T(default=0.5) 

160 illuminate_factor_ocean = Float.T(default=0.25) 

161 color_wet = Tuple.T(3, Int.T(), default=(216, 242, 254)) 

162 color_dry = Tuple.T(3, Int.T(), default=(172, 208, 165)) 

163 color_boundaries = Tuple.T(3, Int.T(), default=(1, 1, 1)) 

164 topo_resolution_min = Float.T( 

165 default=40., 

166 help='minimum resolution of topography [dpi]') 

167 topo_resolution_max = Float.T( 

168 default=200., 

169 help='maximum resolution of topography [dpi]') 

170 replace_topo_color_only = FloatTile.T( 

171 optional=True, 

172 help='replace topo color while keeping topographic shading') 

173 topo_cpt_wet = String.T(default='light_sea') 

174 topo_cpt_dry = String.T(default='light_land') 

175 axes_layout = String.T(optional=True) 

176 custom_cities = List.T(City.T()) 

177 gmt_config = Dict.T(String.T(), String.T()) 

178 comment = String.T(optional=True) 

179 

180 def __init__(self, gmtversion='newest', **kwargs): 

181 Object.__init__(self, **kwargs) 

182 self._gmt = None 

183 self._scaler = None 

184 self._widget = None 

185 self._corners = None 

186 self._wesn = None 

187 self._minarea = None 

188 self._coastline_resolution = None 

189 self._rivers = None 

190 self._dems = None 

191 self._have_topo_land = None 

192 self._have_topo_ocean = None 

193 self._jxyr = None 

194 self._prep_topo_have = None 

195 self._labels = [] 

196 self._area_labels = [] 

197 self._gmtversion = gmtversion 

198 

199 def save(self, outpath, resolution=75., oversample=2., size=None, 

200 width=None, height=None, psconvert=False): 

201 

202 ''' 

203 Save the image. 

204 

205 Save the image to ``outpath``. The format is determined by the filename 

206 extension. Formats are handled as follows: ``'.eps'`` and ``'.ps'`` 

207 produce EPS and PS, respectively, directly with GMT. If the file name 

208 ends with ``'.pdf'``, GMT output is fed through ``gmtpy-epstopdf`` to 

209 create a PDF file. For any other filename extension, output is first 

210 converted to PDF with ``gmtpy-epstopdf``, then with ``pdftocairo`` to 

211 PNG with a resolution oversampled by the factor ``oversample`` and 

212 finally the PNG is downsampled and converted to the target format with 

213 ``convert``. The resolution of rasterized target image can be 

214 controlled either by ``resolution`` in DPI or by specifying ``width`` 

215 or ``height`` or ``size``, where the latter fits the image into a 

216 square with given side length. To save transparency use 

217 ``psconvert=True``. 

218 ''' 

219 

220 gmt = self.gmt 

221 self.draw_labels() 

222 self.draw_axes() 

223 if self.show_topo and self.show_topo_scale: 

224 self._draw_topo_scale() 

225 

226 gmt.save(outpath, resolution=resolution, oversample=oversample, 

227 size=size, width=width, height=height, psconvert=psconvert) 

228 

229 @property 

230 def scaler(self): 

231 if self._scaler is None: 

232 self._setup_geometry() 

233 

234 return self._scaler 

235 

236 @property 

237 def wesn(self): 

238 if self._wesn is None: 

239 self._setup_geometry() 

240 

241 return self._wesn 

242 

243 @property 

244 def widget(self): 

245 if self._widget is None: 

246 self._setup() 

247 

248 return self._widget 

249 

250 @property 

251 def layout(self): 

252 if self._layout is None: 

253 self._setup() 

254 

255 return self._layout 

256 

257 @property 

258 def jxyr(self): 

259 if self._jxyr is None: 

260 self._setup() 

261 

262 return self._jxyr 

263 

264 @property 

265 def pxyr(self): 

266 if self._pxyr is None: 

267 self._setup() 

268 

269 return self._pxyr 

270 

271 @property 

272 def gmt(self): 

273 if self._gmt is None: 

274 self._setup() 

275 

276 if self._have_topo_ocean is None: 

277 self._draw_background() 

278 

279 return self._gmt 

280 

281 def _setup(self): 

282 if not self._widget: 

283 self._setup_geometry() 

284 

285 self._setup_lod() 

286 self._setup_gmt() 

287 

288 def _setup_geometry(self): 

289 wpage, hpage = self.width, self.height 

290 ml, mr, mt, mb = self._expand_margins() 

291 wpage -= ml + mr 

292 hpage -= mt + mb 

293 

294 wreg = self.radius * 2.0 

295 hreg = self.radius * 2.0 

296 if wpage >= hpage: 

297 wreg *= wpage/hpage 

298 else: 

299 hreg *= hpage/wpage 

300 

301 self._wreg = wreg 

302 self._hreg = hreg 

303 

304 self._corners = corners(self.lon, self.lat, wreg, hreg) 

305 west, east, south, north = extent(self.lon, self.lat, wreg, hreg, 10) 

306 

307 x, y, z = ((west, east), (south, north), (-6000., 4500.)) 

308 

309 xax = gmtpy.Ax(mode='min-max', approx_ticks=4.) 

310 yax = gmtpy.Ax(mode='min-max', approx_ticks=4.) 

311 zax = gmtpy.Ax(mode='min-max', inc=1000., label='Height', 

312 scaled_unit='km', scaled_unit_factor=0.001) 

313 

314 scaler = gmtpy.ScaleGuru(data_tuples=[(x, y, z)], axes=(xax, yax, zax)) 

315 

316 par = scaler.get_params() 

317 

318 west = par['xmin'] 

319 east = par['xmax'] 

320 south = par['ymin'] 

321 north = par['ymax'] 

322 

323 self._wesn = west, east, south, north 

324 self._scaler = scaler 

325 

326 def _setup_lod(self): 

327 w, e, s, n = self._wesn 

328 if self.radius > 1500.*km: 

329 coastline_resolution = 'i' 

330 rivers = False 

331 else: 

332 coastline_resolution = 'f' 

333 rivers = True 

334 

335 self._minarea = (self.skip_feature_factor * self.radius/km)**2 

336 

337 self._coastline_resolution = coastline_resolution 

338 self._rivers = rivers 

339 

340 self._prep_topo_have = {} 

341 self._dems = {} 

342 

343 cm2inch = gmtpy.cm/gmtpy.inch 

344 

345 dmin = 2.0 * self.radius * m2d / (self.topo_resolution_max * 

346 (self.height * cm2inch)) 

347 dmax = 2.0 * self.radius * m2d / (self.topo_resolution_min * 

348 (self.height * cm2inch)) 

349 

350 for k in ['ocean', 'land']: 

351 self._dems[k] = topo.select_dem_names(k, dmin, dmax, self._wesn) 

352 if self._dems[k]: 

353 logger.debug('using topography dataset %s for %s' 

354 % (','.join(self._dems[k]), k)) 

355 

356 def _expand_margins(self): 

357 if len(self.margins) == 0 or len(self.margins) > 4: 

358 ml = mr = mt = mb = 2.0 

359 elif len(self.margins) == 1: 

360 ml = mr = mt = mb = self.margins[0] 

361 elif len(self.margins) == 2: 

362 ml = mr = self.margins[0] 

363 mt = mb = self.margins[1] 

364 elif len(self.margins) == 4: 

365 ml, mr, mt, mb = self.margins 

366 

367 return ml, mr, mt, mb 

368 

369 def _setup_gmt(self): 

370 w, h = self.width, self.height 

371 scaler = self._scaler 

372 

373 if gmtpy.is_gmt5(self._gmtversion): 

374 gmtconf = dict( 

375 MAP_TICK_PEN_PRIMARY='1.25p', 

376 MAP_TICK_PEN_SECONDARY='1.25p', 

377 MAP_TICK_LENGTH_PRIMARY='0.2c', 

378 MAP_TICK_LENGTH_SECONDARY='0.6c', 

379 FONT_ANNOT_PRIMARY='12p,1,black', 

380 FONT_LABEL='12p,1,black', 

381 PS_CHAR_ENCODING='ISOLatin1+', 

382 MAP_FRAME_TYPE='fancy', 

383 FORMAT_GEO_MAP='D', 

384 PS_MEDIA='Custom_%ix%i' % ( 

385 w*gmtpy.cm, 

386 h*gmtpy.cm), 

387 PS_PAGE_ORIENTATION='portrait', 

388 MAP_GRID_PEN_PRIMARY='thinnest,0/50/0', 

389 MAP_ANNOT_OBLIQUE='6') 

390 else: 

391 gmtconf = dict( 

392 TICK_PEN='1.25p', 

393 TICK_LENGTH='0.2c', 

394 ANNOT_FONT_PRIMARY='1', 

395 ANNOT_FONT_SIZE_PRIMARY='12p', 

396 LABEL_FONT='1', 

397 LABEL_FONT_SIZE='12p', 

398 CHAR_ENCODING='ISOLatin1+', 

399 BASEMAP_TYPE='fancy', 

400 PLOT_DEGREE_FORMAT='D', 

401 PAPER_MEDIA='Custom_%ix%i' % ( 

402 w*gmtpy.cm, 

403 h*gmtpy.cm), 

404 GRID_PEN_PRIMARY='thinnest/0/50/0', 

405 DOTS_PR_INCH='1200', 

406 OBLIQUE_ANNOTATION='6') 

407 

408 gmtconf.update( 

409 (k.upper(), v) for (k, v) in self.gmt_config.items()) 

410 

411 gmt = gmtpy.GMT(config=gmtconf, version=self._gmtversion) 

412 

413 layout = gmt.default_layout() 

414 

415 layout.set_fixed_margins(*[x*cm for x in self._expand_margins()]) 

416 

417 widget = layout.get_widget() 

418 widget['P'] = widget['J'] 

419 widget['J'] = ('-JA%g/%g' % (self.lon, self.lat)) + '/%(width)gp' 

420 scaler['R'] = '-R%g/%g/%g/%gr' % self._corners 

421 

422 # aspect = gmtpy.aspect_for_projection( 

423 # gmt.installation['version'], *(widget.J() + scaler.R())) 

424 

425 aspect = self._map_aspect(jr=widget.J() + scaler.R()) 

426 widget.set_aspect(aspect) 

427 

428 self._gmt = gmt 

429 self._layout = layout 

430 self._widget = widget 

431 self._jxyr = self._widget.JXY() + self._scaler.R() 

432 self._pxyr = self._widget.PXY() + [ 

433 '-R%g/%g/%g/%g' % (0, widget.width(), 0, widget.height())] 

434 self._have_drawn_axes = False 

435 self._have_drawn_labels = False 

436 

437 def _draw_background(self): 

438 self._have_topo_land = False 

439 self._have_topo_ocean = False 

440 if self.show_topo: 

441 self._have_topo = self._draw_topo() 

442 

443 self._draw_basefeatures() 

444 

445 def _get_topo_tile(self, k): 

446 t = None 

447 demname = None 

448 for dem in self._dems[k]: 

449 t = topo.get(dem, self._wesn) 

450 demname = dem 

451 if t is not None: 

452 break 

453 

454 if not t: 

455 raise NoTopo() 

456 

457 return t, demname 

458 

459 def _prep_topo(self, k): 

460 gmt = self._gmt 

461 t, demname = self._get_topo_tile(k) 

462 

463 if demname not in self._prep_topo_have: 

464 

465 grdfile = gmt.tempfilename() 

466 

467 is_flat = num.all(t.data[0] == t.data) 

468 

469 gmtpy.savegrd( 

470 t.x(), t.y(), t.data, filename=grdfile, naming='lonlat') 

471 

472 if self.illuminate and not is_flat: 

473 if k == 'ocean': 

474 factor = self.illuminate_factor_ocean 

475 else: 

476 factor = self.illuminate_factor_land 

477 

478 ilumfn = gmt.tempfilename() 

479 gmt.grdgradient( 

480 grdfile, 

481 N='e%g' % factor, 

482 A=-45, 

483 G=ilumfn, 

484 out_discard=True) 

485 

486 ilumargs = ['-I%s' % ilumfn] 

487 else: 

488 ilumargs = [] 

489 

490 if self.replace_topo_color_only: 

491 t2 = self.replace_topo_color_only 

492 grdfile2 = gmt.tempfilename() 

493 

494 gmtpy.savegrd( 

495 t2.x(), t2.y(), t2.data, filename=grdfile2, 

496 naming='lonlat') 

497 

498 if gmt.is_gmt5(): 

499 gmt.grdsample( 

500 grdfile2, 

501 G=grdfile, 

502 n='l', 

503 I='%g/%g' % (t.dx, t.dy), # noqa 

504 R=grdfile, 

505 out_discard=True) 

506 else: 

507 gmt.grdsample( 

508 grdfile2, 

509 G=grdfile, 

510 Q='l', 

511 I='%g/%g' % (t.dx, t.dy), # noqa 

512 R=grdfile, 

513 out_discard=True) 

514 

515 gmt.grdmath( 

516 grdfile, '0.0', 'AND', '=', grdfile2, 

517 out_discard=True) 

518 

519 grdfile = grdfile2 

520 

521 self._prep_topo_have[demname] = grdfile, ilumargs 

522 

523 return self._prep_topo_have[demname] 

524 

525 def _draw_topo(self): 

526 widget = self._widget 

527 scaler = self._scaler 

528 gmt = self._gmt 

529 cres = self._coastline_resolution 

530 minarea = self._minarea 

531 

532 JXY = widget.JXY() 

533 R = scaler.R() 

534 

535 try: 

536 grdfile, ilumargs = self._prep_topo('ocean') 

537 gmt.pscoast(D=cres, S='c', A=minarea, *(JXY+R)) 

538 gmt.grdimage(grdfile, C=topo.cpt(self.topo_cpt_wet), 

539 *(ilumargs+JXY+R)) 

540 gmt.pscoast(Q=True, *(JXY+R)) 

541 self._have_topo_ocean = True 

542 except NoTopo: 

543 self._have_topo_ocean = False 

544 

545 try: 

546 grdfile, ilumargs = self._prep_topo('land') 

547 gmt.pscoast(D=cres, G='c', A=minarea, *(JXY+R)) 

548 gmt.grdimage(grdfile, C=topo.cpt(self.topo_cpt_dry), 

549 *(ilumargs+JXY+R)) 

550 gmt.pscoast(Q=True, *(JXY+R)) 

551 self._have_topo_land = True 

552 except NoTopo: 

553 self._have_topo_land = False 

554 

555 def _draw_topo_scale(self, label='Elevation [km]'): 

556 dry = read_cpt(topo.cpt(self.topo_cpt_dry)) 

557 wet = read_cpt(topo.cpt(self.topo_cpt_wet)) 

558 combi = cpt_merge_wet_dry(wet, dry) 

559 for level in combi.levels: 

560 level.vmin /= km 

561 level.vmax /= km 

562 

563 topo_cpt = self.gmt.tempfilename() + '.cpt' 

564 write_cpt(combi, topo_cpt) 

565 

566 (w, h), (xo, yo) = self.widget.get_size() 

567 self.gmt.psscale( 

568 D='%gp/%gp/%gp/%gph' % (xo + 0.5*w, yo - 2.0*gmtpy.cm, w, 

569 0.5*gmtpy.cm), 

570 C=topo_cpt, 

571 B='1:%s:' % label) 

572 

573 def _draw_basefeatures(self): 

574 gmt = self._gmt 

575 cres = self._coastline_resolution 

576 rivers = self._rivers 

577 minarea = self._minarea 

578 

579 color_wet = self.color_wet 

580 color_dry = self.color_dry 

581 

582 if self.show_rivers and rivers: 

583 rivers = ['-Ir/0.25p,%s' % gmtpy.color(self.color_wet)] 

584 else: 

585 rivers = [] 

586 

587 fill = {} 

588 if not self._have_topo_land: 

589 fill['G'] = color_dry 

590 

591 if not self._have_topo_ocean: 

592 fill['S'] = color_wet 

593 

594 if self.show_boundaries: 

595 fill['N'] = '1/1p,%s,%s' % ( 

596 gmtpy.color(self.color_boundaries), 'solid') 

597 

598 gmt.pscoast( 

599 D=cres, 

600 W='thinnest,%s' % gmtpy.color(darken(gmtpy.color_tup(color_dry))), 

601 A=minarea, 

602 *(rivers+self._jxyr), **fill) 

603 

604 if self.show_plates: 

605 self.draw_plates() 

606 

607 def _draw_axes(self): 

608 gmt = self._gmt 

609 scaler = self._scaler 

610 widget = self._widget 

611 

612 if self.axes_layout is None: 

613 if self.lat > 0.0: 

614 axes_layout = 'WSen' 

615 else: 

616 axes_layout = 'WseN' 

617 else: 

618 axes_layout = self.axes_layout 

619 

620 scale_km = gmtpy.nice_value(self.radius/5.) / 1000. 

621 

622 if self.show_center_mark: 

623 gmt.psxy( 

624 in_rows=[[self.lon, self.lat]], 

625 S='c20p', W='2p,black', 

626 *self._jxyr) 

627 

628 if self.show_grid: 

629 btmpl = ('%(xinc)gg%(xinc)g:%(xlabel)s:/' 

630 '%(yinc)gg%(yinc)g:%(ylabel)s:') 

631 else: 

632 btmpl = '%(xinc)g:%(xlabel)s:/%(yinc)g:%(ylabel)s:' 

633 

634 if self.show_scale: 

635 scale = 'x%gp/%gp/%g/%g/%gk' % ( 

636 6./7*widget.width(), 

637 widget.height()/7., 

638 self.lon, 

639 self.lat, 

640 scale_km) 

641 else: 

642 scale = False 

643 

644 gmt.psbasemap( 

645 B=(btmpl % scaler.get_params())+axes_layout, 

646 L=scale, 

647 *self._jxyr) 

648 

649 if self.comment: 

650 font_size = self.gmt.label_font_size() 

651 

652 _, east, south, _ = self._wesn 

653 if gmt.is_gmt5(): 

654 row = [ 

655 1, 0, 

656 '%gp,%s,%s' % (font_size, 0, 'black'), 'BR', 

657 self.comment] 

658 

659 farg = ['-F+f+j'] 

660 else: 

661 row = [1, 0, font_size, 0, 0, 'BR', self.comment] 

662 farg = [] 

663 

664 gmt.pstext( 

665 in_rows=[row], 

666 N=True, 

667 R=(0, 1, 0, 1), 

668 D='%gp/%gp' % (-font_size*0.2, font_size*0.3), 

669 *(widget.PXY() + farg)) 

670 

671 def draw_axes(self): 

672 if not self._have_drawn_axes: 

673 self._draw_axes() 

674 self._have_drawn_axes = True 

675 

676 def _have_coastlines(self): 

677 gmt = self._gmt 

678 cres = self._coastline_resolution 

679 minarea = self._minarea 

680 

681 checkfile = gmt.tempfilename() 

682 

683 gmt.pscoast( 

684 M=True, 

685 D=cres, 

686 W='thinnest,black', 

687 A=minarea, 

688 out_filename=checkfile, 

689 *self._jxyr) 

690 

691 points = [] 

692 with open(checkfile, 'r') as f: 

693 for line in f: 

694 ls = line.strip() 

695 if ls.startswith('#') or ls.startswith('>') or ls == '': 

696 continue 

697 plon, plat = [float(x) for x in ls.split()] 

698 points.append((plat, plon)) 

699 

700 points = num.array(points, dtype=float) 

701 return num.any(points_in_region(points, self._wesn)) 

702 

703 def have_coastlines(self): 

704 self.gmt 

705 return self._have_coastlines() 

706 

707 def project(self, lats, lons, jr=None): 

708 onepoint = False 

709 if isinstance(lats, float) and isinstance(lons, float): 

710 lats = [lats] 

711 lons = [lons] 

712 onepoint = True 

713 

714 if jr is not None: 

715 j, r = jr 

716 gmt = gmtpy.GMT(version=self._gmtversion) 

717 else: 

718 j, _, _, r = self.jxyr 

719 gmt = self.gmt 

720 

721 f = BytesIO() 

722 gmt.mapproject(j, r, in_columns=(lons, lats), out_stream=f, D='p') 

723 f.seek(0) 

724 data = num.loadtxt(f, ndmin=2) 

725 xs, ys = data.T 

726 if onepoint: 

727 xs = xs[0] 

728 ys = ys[0] 

729 return xs, ys 

730 

731 def _map_box(self, jr=None): 

732 ll_lon, ll_lat, ur_lon, ur_lat = self._corners 

733 

734 xs_corner, ys_corner = self.project( 

735 (ll_lat, ur_lat), (ll_lon, ur_lon), jr=jr) 

736 

737 w = xs_corner[1] - xs_corner[0] 

738 h = ys_corner[1] - ys_corner[0] 

739 

740 return w, h 

741 

742 def _map_aspect(self, jr=None): 

743 w, h = self._map_box(jr=jr) 

744 return h/w 

745 

746 def _draw_labels(self): 

747 points_taken = [] 

748 regions_taken = [] 

749 

750 def no_points_in_rect(xs, ys, xmin, ymin, xmax, ymax): 

751 xx = not num.any(la(la(xmin < xs, xs < xmax), 

752 la(ymin < ys, ys < ymax))) 

753 return xx 

754 

755 def roverlaps(a, b): 

756 return (a[0] < b[2] and b[0] < a[2] and 

757 a[1] < b[3] and b[1] < a[3]) 

758 

759 w, h = self._map_box() 

760 

761 label_font_size = self.gmt.label_font_size() 

762 

763 if self._labels: 

764 

765 n = len(self._labels) 

766 

767 lons, lats, texts, sx, sy, colors, fonts, font_sizes, \ 

768 angles, styles = list(zip(*self._labels)) 

769 

770 font_sizes = [ 

771 (font_size or label_font_size) for font_size in font_sizes] 

772 

773 sx = num.array(sx, dtype=float) 

774 sy = num.array(sy, dtype=float) 

775 

776 xs, ys = self.project(lats, lons) 

777 

778 points_taken.append((xs, ys)) 

779 

780 dxs = num.zeros(n) 

781 dys = num.zeros(n) 

782 

783 for i in range(n): 

784 dx, dy = gmtpy.text_box( 

785 texts[i], 

786 font=fonts[i], 

787 font_size=font_sizes[i], 

788 **styles[i]) 

789 

790 dxs[i] = dx 

791 dys[i] = dy 

792 

793 la = num.logical_and 

794 anchors_ok = ( 

795 la(xs + sx + dxs < w, ys + sy + dys < h), 

796 la(xs - sx - dxs > 0., ys - sy - dys > 0.), 

797 la(xs + sx + dxs < w, ys - sy - dys > 0.), 

798 la(xs - sx - dxs > 0., ys + sy + dys < h), 

799 ) 

800 

801 arects = [ 

802 (xs, ys, xs + sx + dxs, ys + sy + dys), 

803 (xs - sx - dxs, ys - sy - dys, xs, ys), 

804 (xs, ys - sy - dys, xs + sx + dxs, ys), 

805 (xs - sx - dxs, ys, xs, ys + sy + dys)] 

806 

807 for i in range(n): 

808 for ianch in range(4): 

809 anchors_ok[ianch][i] &= no_points_in_rect( 

810 xs, ys, *[xxx[i] for xxx in arects[ianch]]) 

811 

812 anchor_choices = [] 

813 anchor_take = [] 

814 for i in range(n): 

815 choices = [ianch for ianch in range(4) 

816 if anchors_ok[ianch][i]] 

817 anchor_choices.append(choices) 

818 if choices: 

819 anchor_take.append(choices[0]) 

820 else: 

821 anchor_take.append(None) 

822 

823 def cost(anchor_take): 

824 noverlaps = 0 

825 for i in range(n): 

826 for j in range(n): 

827 if i != j: 

828 i_take = anchor_take[i] 

829 j_take = anchor_take[j] 

830 if i_take is None or j_take is None: 

831 continue 

832 r_i = [xxx[i] for xxx in arects[i_take]] 

833 r_j = [xxx[j] for xxx in arects[j_take]] 

834 if roverlaps(r_i, r_j): 

835 noverlaps += 1 

836 

837 return noverlaps 

838 

839 cur_cost = cost(anchor_take) 

840 imax = 30 

841 while cur_cost != 0 and imax > 0: 

842 for i in range(n): 

843 for t in anchor_choices[i]: 

844 anchor_take_new = list(anchor_take) 

845 anchor_take_new[i] = t 

846 new_cost = cost(anchor_take_new) 

847 if new_cost < cur_cost: 

848 anchor_take = anchor_take_new 

849 cur_cost = new_cost 

850 

851 imax -= 1 

852 

853 while cur_cost != 0: 

854 for i in range(n): 

855 anchor_take_new = list(anchor_take) 

856 anchor_take_new[i] = None 

857 new_cost = cost(anchor_take_new) 

858 if new_cost < cur_cost: 

859 anchor_take = anchor_take_new 

860 cur_cost = new_cost 

861 break 

862 

863 anchor_strs = ['BL', 'TR', 'TL', 'BR'] 

864 

865 for i in range(n): 

866 ianchor = anchor_take[i] 

867 color = colors[i] 

868 if color is None: 

869 color = 'black' 

870 

871 if ianchor is not None: 

872 regions_taken.append([xxx[i] for xxx in arects[ianchor]]) 

873 

874 anchor = anchor_strs[ianchor] 

875 

876 yoff = [-sy[i], sy[i]][anchor[0] == 'B'] 

877 xoff = [-sx[i], sx[i]][anchor[1] == 'L'] 

878 if self.gmt.is_gmt5(): 

879 row = ( 

880 lons[i], lats[i], 

881 '%i,%s,%s' % (font_sizes[i], fonts[i], color), 

882 anchor, 

883 texts[i]) 

884 

885 farg = ['-F+f+j+a%g' % angles[i]] 

886 else: 

887 row = ( 

888 lons[i], lats[i], 

889 font_sizes[i], angles[i], fonts[i], anchor, 

890 texts[i]) 

891 farg = ['-G%s' % color] 

892 

893 self.gmt.pstext( 

894 in_rows=[row], 

895 D='%gp/%gp' % (xoff, yoff), 

896 *(self.jxyr + farg), 

897 **styles[i]) 

898 

899 if self._area_labels: 

900 

901 for lons, lats, text, color, font, font_size, style in \ 

902 self._area_labels: 

903 

904 if font_size is None: 

905 font_size = label_font_size 

906 

907 if color is None: 

908 color = 'black' 

909 

910 if self.gmt.is_gmt5(): 

911 farg = ['-F+f+j'] 

912 else: 

913 farg = ['-G%s' % color] 

914 

915 xs, ys = self.project(lats, lons) 

916 dx, dy = gmtpy.text_box( 

917 text, font=font, font_size=font_size, **style) 

918 

919 rects = [xs-0.5*dx, ys-0.5*dy, xs+0.5*dx, ys+0.5*dy] 

920 

921 locs_ok = num.ones(xs.size, dtype=num.bool) 

922 

923 for iloc in range(xs.size): 

924 rcandi = [xxx[iloc] for xxx in rects] 

925 

926 locs_ok[iloc] = True 

927 locs_ok[iloc] &= ( 

928 0 < rcandi[0] and rcandi[2] < w 

929 and 0 < rcandi[1] and rcandi[3] < h) 

930 

931 overlap = False 

932 for r in regions_taken: 

933 if roverlaps(r, rcandi): 

934 overlap = True 

935 break 

936 

937 locs_ok[iloc] &= not overlap 

938 

939 for xs_taken, ys_taken in points_taken: 

940 locs_ok[iloc] &= no_points_in_rect( 

941 xs_taken, ys_taken, *rcandi) 

942 

943 if not locs_ok[iloc]: 

944 break 

945 

946 rows = [] 

947 for iloc, (lon, lat) in enumerate(zip(lons, lats)): 

948 if not locs_ok[iloc]: 

949 continue 

950 

951 if self.gmt.is_gmt5(): 

952 row = ( 

953 lon, lat, 

954 '%i,%s,%s' % (font_size, font, color), 

955 'MC', 

956 text) 

957 

958 else: 

959 row = ( 

960 lon, lat, 

961 font_size, 0, font, 'MC', 

962 text) 

963 

964 rows.append(row) 

965 

966 regions_taken.append([xxx[iloc] for xxx in rects]) 

967 break 

968 

969 self.gmt.pstext( 

970 in_rows=rows, 

971 *(self.jxyr + farg), 

972 **style) 

973 

974 def draw_labels(self): 

975 self.gmt 

976 if not self._have_drawn_labels: 

977 self._draw_labels() 

978 self._have_drawn_labels = True 

979 

980 def add_label( 

981 self, lat, lon, text, 

982 offset_x=5., offset_y=5., 

983 color=None, 

984 font='1', 

985 font_size=None, 

986 angle=0, 

987 style={}): 

988 

989 if 'G' in style: 

990 style = style.copy() 

991 color = style.pop('G') 

992 

993 self._labels.append( 

994 (lon, lat, text, offset_x, offset_y, color, font, font_size, 

995 angle, style)) 

996 

997 def add_area_label( 

998 self, lat, lon, text, 

999 color=None, 

1000 font='3', 

1001 font_size=None, 

1002 style={}): 

1003 

1004 self._area_labels.append( 

1005 (lon, lat, text, color, font, font_size, style)) 

1006 

1007 def cities_in_region(self): 

1008 from pyrocko.dataset import geonames 

1009 cities = geonames.get_cities_region(region=self.wesn, minpop=0) 

1010 cities.extend(self.custom_cities) 

1011 cities.sort(key=lambda x: x.population) 

1012 return cities 

1013 

1014 def draw_cities(self, 

1015 exact=None, 

1016 include=[], 

1017 exclude=[], 

1018 nmax_soft=10, 

1019 psxy_style=dict(S='s5p', G='black')): 

1020 

1021 cities = self.cities_in_region() 

1022 

1023 if exact is not None: 

1024 cities = [c for c in cities if c.name in exact] 

1025 minpop = None 

1026 else: 

1027 cities = [c for c in cities if c.name not in exclude] 

1028 minpop = 10**3 

1029 for minpop_new in [1e3, 3e3, 1e4, 3e4, 1e5, 3e5, 1e6, 3e6, 1e7]: 

1030 cities_new = [ 

1031 c for c in cities 

1032 if c.population > minpop_new or c.name in include] 

1033 

1034 if len(cities_new) == 0 or ( 

1035 len(cities_new) < 3 and len(cities) < nmax_soft*2): 

1036 break 

1037 

1038 cities = cities_new 

1039 minpop = minpop_new 

1040 if len(cities) <= nmax_soft: 

1041 break 

1042 

1043 if cities: 

1044 lats = [c.lat for c in cities] 

1045 lons = [c.lon for c in cities] 

1046 

1047 self.gmt.psxy( 

1048 in_columns=(lons, lats), 

1049 *self.jxyr, **psxy_style) 

1050 

1051 for c in cities: 

1052 try: 

1053 text = c.name.encode('iso-8859-1').decode('iso-8859-1') 

1054 except UnicodeEncodeError: 

1055 text = c.asciiname 

1056 

1057 self.add_label(c.lat, c.lon, text) 

1058 

1059 self._cities_minpop = minpop 

1060 

1061 def add_stations(self, stations, psxy_style=dict()): 

1062 

1063 default_psxy_style = { 

1064 'S': 't8p', 

1065 'G': 'black' 

1066 } 

1067 default_psxy_style.update(psxy_style) 

1068 

1069 lats, lons = zip(*[s.effective_latlon for s in stations]) 

1070 

1071 self.gmt.psxy( 

1072 in_columns=(lons, lats), 

1073 *self.jxyr, **default_psxy_style) 

1074 

1075 for station in stations: 

1076 self.add_label( 

1077 station.effective_lat, 

1078 station.effective_lon, 

1079 '.'.join(x for x in (station.network, station.station) if x)) 

1080 

1081 def add_kite_scene(self, scene): 

1082 tile = FloatTile( 

1083 scene.frame.llLon, 

1084 scene.frame.llLat, 

1085 scene.frame.dLon, 

1086 scene.frame.dLat, 

1087 scene.displacement) 

1088 

1089 return tile 

1090 

1091 def add_gnss_campaign(self, campaign, psxy_style=None, offset_scale=None, 

1092 labels=True, vertical=False, fontsize=10): 

1093 

1094 stations = campaign.stations 

1095 

1096 if offset_scale is None: 

1097 offset_scale = num.zeros(campaign.nstations) 

1098 for ista, sta in enumerate(stations): 

1099 for comp in sta.components.values(): 

1100 offset_scale[ista] += comp.shift 

1101 offset_scale = num.sqrt(offset_scale**2).max() 

1102 

1103 size = math.sqrt(self.height**2 + self.width**2) 

1104 scale = (size/10.) / offset_scale 

1105 logger.debug('GNSS: Using offset scale %f, map scale %f', 

1106 offset_scale, scale) 

1107 

1108 lats, lons = zip(*[s.effective_latlon for s in stations]) 

1109 

1110 if vertical: 

1111 rows = [[lons[ista], lats[ista], 

1112 0., -s.up.shift, 

1113 (s.east.sigma + s.north.sigma) if s.east.sigma else 0., 

1114 s.up.sigma, 0., 

1115 s.code if labels else None] 

1116 for ista, s in enumerate(stations) 

1117 if s.up is not None] 

1118 

1119 else: 

1120 rows = [[lons[ista], lats[ista], 

1121 -s.east.shift, -s.north.shift, 

1122 s.east.sigma, s.north.sigma, s.correlation_ne, 

1123 s.code if labels else None] 

1124 for ista, s in enumerate(stations) 

1125 if s.east is not None or s.north is not None] 

1126 

1127 default_psxy_style = { 

1128 'h': 0, 

1129 'W': '2p,black', 

1130 'A': '+p2p,black+b+a40', 

1131 'G': 'black', 

1132 'L': True, 

1133 'S': 'e%dc/0.95/%d' % (scale, fontsize), 

1134 } 

1135 

1136 if not labels: 

1137 for row in rows: 

1138 row.pop(-1) 

1139 

1140 if psxy_style is not None: 

1141 default_psxy_style.update(psxy_style) 

1142 

1143 self.gmt.psvelo( 

1144 in_rows=rows, 

1145 *self.jxyr, 

1146 **default_psxy_style) 

1147 

1148 def draw_plates(self): 

1149 from pyrocko.dataset import tectonics 

1150 

1151 neast = 20 

1152 nnorth = max(1, int(round(num.round(self._hreg/self._wreg * neast)))) 

1153 norths = num.linspace(-self._hreg*0.5, self._hreg*0.5, nnorth) 

1154 easts = num.linspace(-self._wreg*0.5, self._wreg*0.5, neast) 

1155 norths2 = num.repeat(norths, neast) 

1156 easts2 = num.tile(easts, nnorth) 

1157 lats, lons = od.ne_to_latlon( 

1158 self.lat, self.lon, norths2, easts2) 

1159 

1160 bird = tectonics.PeterBird2003() 

1161 plates = bird.get_plates() 

1162 

1163 color_plates = gmtpy.color('aluminium5') 

1164 color_velocities = gmtpy.color('skyblue1') 

1165 color_velocities_lab = gmtpy.color(darken(gmtpy.color_tup('skyblue1'))) 

1166 

1167 points = num.vstack((lats, lons)).T 

1168 used = [] 

1169 for plate in plates: 

1170 mask = plate.contains_points(points) 

1171 if num.any(mask): 

1172 used.append((plate, mask)) 

1173 

1174 if len(used) > 1: 

1175 

1176 candi_fixed = {} 

1177 

1178 label_data = [] 

1179 for plate, mask in used: 

1180 

1181 mean_north = num.mean(norths2[mask]) 

1182 mean_east = num.mean(easts2[mask]) 

1183 iorder = num.argsort(num.sqrt( 

1184 (norths2[mask] - mean_north)**2 + 

1185 (easts2[mask] - mean_east)**2)) 

1186 

1187 lat_candis = lats[mask][iorder] 

1188 lon_candis = lons[mask][iorder] 

1189 

1190 candi_fixed[plate.name] = lat_candis.size 

1191 

1192 label_data.append(( 

1193 lat_candis, lon_candis, plate, color_plates)) 

1194 

1195 boundaries = bird.get_boundaries() 

1196 

1197 size = 2 

1198 

1199 psxy_kwargs = [] 

1200 

1201 for boundary in boundaries: 

1202 if num.any(points_in_region(boundary.points, self._wesn)): 

1203 for typ, part in boundary.split_types( 

1204 [['SUB'], 

1205 ['OSR', 'OTF', 'OCB', 'CTF', 'CCB', 'CRB']]): 

1206 

1207 lats, lons = part.T 

1208 

1209 kwargs = {} 

1210 if typ[0] == 'SUB': 

1211 if boundary.kind == '\\': 

1212 kwargs['S'] = 'f%g/%gp+t+r' % ( 

1213 0.45*size, 3.*size) 

1214 elif boundary.kind == '/': 

1215 kwargs['S'] = 'f%g/%gp+t+l' % ( 

1216 0.45*size, 3.*size) 

1217 

1218 kwargs['G'] = color_plates 

1219 

1220 kwargs['in_columns'] = (lons, lats) 

1221 kwargs['W'] = '%gp,%s' % (size, color_plates), 

1222 

1223 psxy_kwargs.append(kwargs) 

1224 

1225 if boundary.kind == '\\': 

1226 if boundary.plate_name2 in candi_fixed: 

1227 candi_fixed[boundary.plate_name2] += \ 

1228 neast*nnorth 

1229 

1230 elif boundary.kind == '/': 

1231 if boundary.plate_name1 in candi_fixed: 

1232 candi_fixed[boundary.plate_name1] += \ 

1233 neast*nnorth 

1234 

1235 candi_fixed = [name for name in sorted( 

1236 list(candi_fixed.keys()), key=lambda name: -candi_fixed[name])] 

1237 

1238 candi_fixed.append(None) 

1239 

1240 gsrm = tectonics.GSRM1() 

1241 

1242 for name in candi_fixed: 

1243 if name not in gsrm.plate_names() \ 

1244 and name not in gsrm.plate_alt_names(): 

1245 

1246 continue 

1247 

1248 lats, lons, vnorth, veast, vnorth_err, veast_err, corr = \ 

1249 gsrm.get_velocities(name, region=self._wesn) 

1250 

1251 fixed_plate_name = name 

1252 

1253 self.gmt.psvelo( 

1254 in_columns=( 

1255 lons, lats, veast, vnorth, veast_err, vnorth_err, 

1256 corr), 

1257 W='0.25p,%s' % color_velocities, 

1258 A='9p+e+g%s' % color_velocities, 

1259 S='e0.2p/0.95/10', 

1260 *self.jxyr) 

1261 

1262 for _ in range(len(lons) // 50 + 1): 

1263 ii = random.randint(0, len(lons)-1) 

1264 v = math.sqrt(vnorth[ii]**2 + veast[ii]**2) 

1265 self.add_label( 

1266 lats[ii], lons[ii], '%.0f' % v, 

1267 font_size=0.7*self.gmt.label_font_size(), 

1268 style=dict( 

1269 G=color_velocities_lab)) 

1270 

1271 break 

1272 

1273 for (lat_candis, lon_candis, plate, color) in label_data: 

1274 full_name = bird.full_name(plate.name) 

1275 if plate.name == fixed_plate_name: 

1276 full_name = '@_' + full_name + '@_' 

1277 

1278 self.add_area_label( 

1279 lat_candis, lon_candis, 

1280 full_name, 

1281 color=color, 

1282 font='3') 

1283 

1284 for kwargs in psxy_kwargs: 

1285 self.gmt.psxy(*self.jxyr, **kwargs) 

1286 

1287 

1288def rand(mi, ma): 

1289 mi = float(mi) 

1290 ma = float(ma) 

1291 return random.random() * (ma-mi) + mi 

1292 

1293 

1294def split_region(region): 

1295 west, east, south, north = topo.positive_region(region) 

1296 if east > 180: 

1297 return [(west, 180., south, north), 

1298 (-180., east-360., south, north)] 

1299 else: 

1300 return [region] 

1301 

1302 

1303class CPTLevel(Object): 

1304 vmin = Float.T() 

1305 vmax = Float.T() 

1306 color_min = Tuple.T(3, Float.T()) 

1307 color_max = Tuple.T(3, Float.T()) 

1308 

1309 

1310class CPT(Object): 

1311 color_below = Tuple.T(3, Float.T(), optional=True) 

1312 color_above = Tuple.T(3, Float.T(), optional=True) 

1313 color_nan = Tuple.T(3, Float.T(), optional=True) 

1314 levels = List.T(CPTLevel.T()) 

1315 

1316 def scale(self, vmin, vmax): 

1317 vmin_old, vmax_old = self.levels[0].vmin, self.levels[-1].vmax 

1318 for level in self.levels: 

1319 level.vmin = (level.vmin - vmin_old) / (vmax_old - vmin_old) * \ 

1320 (vmax - vmin) + vmin 

1321 level.vmax = (level.vmax - vmin_old) / (vmax_old - vmin_old) * \ 

1322 (vmax - vmin) + vmin 

1323 

1324 def discretize(self, nlevels): 

1325 colors = [] 

1326 vals = [] 

1327 for level in self.levels: 

1328 vals.append(level.vmin) 

1329 vals.append(level.vmax) 

1330 colors.append(level.color_min) 

1331 colors.append(level.color_max) 

1332 

1333 r, g, b = num.array(colors, dtype=float).T 

1334 vals = num.array(vals, dtype=float) 

1335 

1336 vmin, vmax = self.levels[0].vmin, self.levels[-1].vmax 

1337 x = num.linspace(vmin, vmax, nlevels+1) 

1338 rd = num.interp(x, vals, r) 

1339 gd = num.interp(x, vals, g) 

1340 bd = num.interp(x, vals, b) 

1341 

1342 levels = [] 

1343 for ilevel in range(nlevels): 

1344 color = ( 

1345 float(0.5*(rd[ilevel]+rd[ilevel+1])), 

1346 float(0.5*(gd[ilevel]+gd[ilevel+1])), 

1347 float(0.5*(bd[ilevel]+bd[ilevel+1]))) 

1348 

1349 levels.append(CPTLevel( 

1350 vmin=x[ilevel], 

1351 vmax=x[ilevel+1], 

1352 color_min=color, 

1353 color_max=color)) 

1354 

1355 cpt = CPT( 

1356 color_below=self.color_below, 

1357 color_above=self.color_above, 

1358 color_nan=self.color_nan, 

1359 levels=levels) 

1360 

1361 return cpt 

1362 

1363 

1364class CPTParseError(Exception): 

1365 pass 

1366 

1367 

1368def read_cpt(filename): 

1369 with open(filename) as f: 

1370 color_below = None 

1371 color_above = None 

1372 color_nan = None 

1373 levels = [] 

1374 try: 

1375 for line in f: 

1376 line = line.strip() 

1377 toks = line.split() 

1378 

1379 if line.startswith('#'): 

1380 continue 

1381 

1382 elif line.startswith('B'): 

1383 color_below = tuple(map(float, toks[1:4])) 

1384 

1385 elif line.startswith('F'): 

1386 color_above = tuple(map(float, toks[1:4])) 

1387 

1388 elif line.startswith('N'): 

1389 color_nan = tuple(map(float, toks[1:4])) 

1390 

1391 else: 

1392 values = list(map(float, line.split())) 

1393 vmin = values[0] 

1394 color_min = tuple(values[1:4]) 

1395 vmax = values[4] 

1396 color_max = tuple(values[5:8]) 

1397 levels.append(CPTLevel( 

1398 vmin=vmin, 

1399 vmax=vmax, 

1400 color_min=color_min, 

1401 color_max=color_max)) 

1402 

1403 except Exception: 

1404 raise CPTParseError() 

1405 

1406 return CPT( 

1407 color_below=color_below, 

1408 color_above=color_above, 

1409 color_nan=color_nan, 

1410 levels=levels) 

1411 

1412 

1413def color_to_int(color): 

1414 return tuple(max(0, min(255, int(round(x)))) for x in color) 

1415 

1416 

1417def write_cpt(cpt, filename): 

1418 with open(filename, 'w') as f: 

1419 for level in cpt.levels: 

1420 f.write( 

1421 '%e %i %i %i %e %i %i %i\n' % 

1422 ((level.vmin, ) + color_to_int(level.color_min) + 

1423 (level.vmax, ) + color_to_int(level.color_max))) 

1424 

1425 if cpt.color_below: 

1426 f.write('B %i %i %i\n' % color_to_int(cpt.color_below)) 

1427 

1428 if cpt.color_above: 

1429 f.write('F %i %i %i\n' % color_to_int(cpt.color_above)) 

1430 

1431 if cpt.color_nan: 

1432 f.write('N %i %i %i\n' % color_to_int(cpt.color_nan)) 

1433 

1434 

1435def cpt_merge_wet_dry(wet, dry): 

1436 levels = [] 

1437 for level in wet.levels: 

1438 if level.vmin < 0.: 

1439 if level.vmax > 0.: 

1440 level.vmax = 0. 

1441 

1442 levels.append(level) 

1443 

1444 for level in dry.levels: 

1445 if level.vmax > 0.: 

1446 if level.vmin < 0.: 

1447 level.vmin = 0. 

1448 

1449 levels.append(level) 

1450 

1451 combi = CPT( 

1452 color_below=wet.color_below, 

1453 color_above=dry.color_above, 

1454 color_nan=dry.color_nan, 

1455 levels=levels) 

1456 

1457 return combi 

1458 

1459 

1460if __name__ == '__main__': 

1461 from pyrocko import util 

1462 util.setup_logging('pyrocko.automap', 'info') 

1463 

1464 import sys 

1465 if len(sys.argv) == 2: 

1466 

1467 n = int(sys.argv[1]) 

1468 

1469 for i in range(n): 

1470 m = Map( 

1471 lat=rand(-60., 60.), 

1472 lon=rand(-180., 180.), 

1473 radius=math.exp(rand(math.log(500*km), math.log(3000*km))), 

1474 width=30., height=30., 

1475 show_grid=True, 

1476 show_topo=True, 

1477 color_dry=(238, 236, 230), 

1478 topo_cpt_wet='light_sea_uniform', 

1479 topo_cpt_dry='light_land_uniform', 

1480 illuminate=True, 

1481 illuminate_factor_ocean=0.15, 

1482 show_rivers=False, 

1483 show_plates=True) 

1484 

1485 m.draw_cities() 

1486 print(m) 

1487 m.save('map_%02i.pdf' % i)