1# http://pyrocko.org - GPLv3
2#
3# The Pyrocko Developers, 21st Century
4# ---|P------/S----------~Lg----------
5from __future__ import absolute_import, print_function
7import math
8import random
9import logging
11try:
12 from StringIO import StringIO as BytesIO
13except ImportError:
14 from io import BytesIO
16import numpy as num
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
25try:
26 newstr = unicode
27except NameError:
28 newstr = str
30points_in_region = od.points_in_region
32logger = logging.getLogger('pyrocko.plot.automap')
34earthradius = 6371000.0
35r2d = 180./math.pi
36d2r = 1./r2d
37km = 1000.
38d2m = d2r*earthradius
39m2d = 1./d2m
40cm = gmtpy.cm
43def darken(c, f=0.7):
44 return (c[0]*f, c[1]*f, c[2]*f)
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
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()
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)
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()
72 return topo.positive_region((west, east, south, north))
75class NoTopo(Exception):
76 pass
79class OutOfBounds(Exception):
80 pass
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')
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()
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
104 def x(self):
105 return self.xmin + num.arange(self.nx) * self.dx
107 def y(self):
108 return self.ymin + num.arange(self.ny) * self.dy
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()
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')
127 if population is None:
128 population = 0
129 else:
130 population = int(population)
132 Object.__init__(self, name=name, lat=lat, lon=lon,
133 population=population, asciiname=asciiname)
135 name = Unicode.T()
136 lat = Float.T()
137 lon = Float.T()
138 population = Int.T()
139 asciiname = String.T()
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_plate_velocities = Bool.T(default=False)
159 show_plate_names = Bool.T(default=False)
160 show_boundaries = Bool.T(default=False)
161 illuminate_factor_land = Float.T(default=0.5)
162 illuminate_factor_ocean = Float.T(default=0.25)
163 color_wet = Tuple.T(3, Int.T(), default=(216, 242, 254))
164 color_dry = Tuple.T(3, Int.T(), default=(172, 208, 165))
165 color_boundaries = Tuple.T(3, Int.T(), default=(1, 1, 1))
166 topo_resolution_min = Float.T(
167 default=40.,
168 help='minimum resolution of topography [dpi]')
169 topo_resolution_max = Float.T(
170 default=200.,
171 help='maximum resolution of topography [dpi]')
172 replace_topo_color_only = FloatTile.T(
173 optional=True,
174 help='replace topo color while keeping topographic shading')
175 topo_cpt_wet = String.T(default='light_sea')
176 topo_cpt_dry = String.T(default='light_land')
177 axes_layout = String.T(optional=True)
178 custom_cities = List.T(City.T())
179 gmt_config = Dict.T(String.T(), String.T())
180 comment = String.T(optional=True)
181 approx_ticks = Int.T(default=4)
183 def __init__(self, gmtversion='newest', **kwargs):
184 Object.__init__(self, **kwargs)
185 self._gmt = None
186 self._scaler = None
187 self._widget = None
188 self._corners = None
189 self._wesn = None
190 self._minarea = None
191 self._coastline_resolution = None
192 self._rivers = None
193 self._dems = None
194 self._have_topo_land = None
195 self._have_topo_ocean = None
196 self._jxyr = None
197 self._prep_topo_have = None
198 self._labels = []
199 self._area_labels = []
200 self._gmtversion = gmtversion
202 def save(self, outpath, resolution=75., oversample=2., size=None,
203 width=None, height=None, psconvert=False, crop_eps_mode=False):
205 '''
206 Save the image.
208 Save the image to ``outpath``. The format is determined by the filename
209 extension. Formats are handled as follows: ``'.eps'`` and ``'.ps'``
210 produce EPS and PS, respectively, directly with GMT. If the file name
211 ends with ``'.pdf'``, GMT output is fed through ``gmtpy-epstopdf`` to
212 create a PDF file. For any other filename extension, output is first
213 converted to PDF with ``gmtpy-epstopdf``, then with ``pdftocairo`` to
214 PNG with a resolution oversampled by the factor ``oversample`` and
215 finally the PNG is downsampled and converted to the target format with
216 ``convert``. The resolution of rasterized target image can be
217 controlled either by ``resolution`` in DPI or by specifying ``width``
218 or ``height`` or ``size``, where the latter fits the image into a
219 square with given side length. To save transparency use
220 ``psconvert=True``.
221 '''
223 gmt = self.gmt
224 self.draw_labels()
225 self.draw_axes()
226 if self.show_topo and self.show_topo_scale:
227 self._draw_topo_scale()
229 gmt.save(outpath, resolution=resolution, oversample=oversample,
230 crop_eps_mode=crop_eps_mode,
231 size=size, width=width, height=height, psconvert=psconvert)
233 @property
234 def scaler(self):
235 if self._scaler is None:
236 self._setup_geometry()
238 return self._scaler
240 @property
241 def wesn(self):
242 if self._wesn is None:
243 self._setup_geometry()
245 return self._wesn
247 @property
248 def widget(self):
249 if self._widget is None:
250 self._setup()
252 return self._widget
254 @property
255 def layout(self):
256 if self._layout is None:
257 self._setup()
259 return self._layout
261 @property
262 def jxyr(self):
263 if self._jxyr is None:
264 self._setup()
266 return self._jxyr
268 @property
269 def pxyr(self):
270 if self._pxyr is None:
271 self._setup()
273 return self._pxyr
275 @property
276 def gmt(self):
277 if self._gmt is None:
278 self._setup()
280 if self._have_topo_ocean is None:
281 self._draw_background()
283 return self._gmt
285 def _setup(self):
286 if not self._widget:
287 self._setup_geometry()
289 self._setup_lod()
290 self._setup_gmt()
292 def _setup_geometry(self):
293 wpage, hpage = self.width, self.height
294 ml, mr, mt, mb = self._expand_margins()
295 wpage -= ml + mr
296 hpage -= mt + mb
298 wreg = self.radius * 2.0
299 hreg = self.radius * 2.0
300 if wpage >= hpage:
301 wreg *= wpage/hpage
302 else:
303 hreg *= hpage/wpage
305 self._wreg = wreg
306 self._hreg = hreg
308 self._corners = corners(self.lon, self.lat, wreg, hreg)
309 west, east, south, north = extent(self.lon, self.lat, wreg, hreg, 10)
311 x, y, z = ((west, east), (south, north), (-6000., 4500.))
313 xax = gmtpy.Ax(mode='min-max', approx_ticks=self.approx_ticks)
314 yax = gmtpy.Ax(mode='min-max', approx_ticks=self.approx_ticks)
315 zax = gmtpy.Ax(mode='min-max', inc=1000., label='Height',
316 scaled_unit='km', scaled_unit_factor=0.001)
318 scaler = gmtpy.ScaleGuru(data_tuples=[(x, y, z)], axes=(xax, yax, zax))
320 par = scaler.get_params()
322 west = par['xmin']
323 east = par['xmax']
324 south = par['ymin']
325 north = par['ymax']
327 self._wesn = west, east, south, north
328 self._scaler = scaler
330 def _setup_lod(self):
331 w, e, s, n = self._wesn
332 if self.radius > 1500.*km:
333 coastline_resolution = 'i'
334 rivers = False
335 else:
336 coastline_resolution = 'f'
337 rivers = True
339 self._minarea = (self.skip_feature_factor * self.radius/km)**2
341 self._coastline_resolution = coastline_resolution
342 self._rivers = rivers
344 self._prep_topo_have = {}
345 self._dems = {}
347 cm2inch = gmtpy.cm/gmtpy.inch
349 dmin = 2.0 * self.radius * m2d / (self.topo_resolution_max *
350 (self.height * cm2inch))
351 dmax = 2.0 * self.radius * m2d / (self.topo_resolution_min *
352 (self.height * cm2inch))
354 for k in ['ocean', 'land']:
355 self._dems[k] = topo.select_dem_names(k, dmin, dmax, self._wesn)
356 if self._dems[k]:
357 logger.debug('using topography dataset %s for %s'
358 % (','.join(self._dems[k]), k))
360 def _expand_margins(self):
361 if len(self.margins) == 0 or len(self.margins) > 4:
362 ml = mr = mt = mb = 2.0
363 elif len(self.margins) == 1:
364 ml = mr = mt = mb = self.margins[0]
365 elif len(self.margins) == 2:
366 ml = mr = self.margins[0]
367 mt = mb = self.margins[1]
368 elif len(self.margins) == 4:
369 ml, mr, mt, mb = self.margins
371 return ml, mr, mt, mb
373 def _setup_gmt(self):
374 w, h = self.width, self.height
375 scaler = self._scaler
377 if gmtpy.is_gmt5(self._gmtversion):
378 gmtconf = dict(
379 MAP_TICK_PEN_PRIMARY='1.25p',
380 MAP_TICK_PEN_SECONDARY='1.25p',
381 MAP_TICK_LENGTH_PRIMARY='0.2c',
382 MAP_TICK_LENGTH_SECONDARY='0.6c',
383 FONT_ANNOT_PRIMARY='12p,1,black',
384 FONT_LABEL='12p,1,black',
385 PS_CHAR_ENCODING='ISOLatin1+',
386 MAP_FRAME_TYPE='fancy',
387 FORMAT_GEO_MAP='D',
388 PS_MEDIA='Custom_%ix%i' % (
389 w*gmtpy.cm,
390 h*gmtpy.cm),
391 PS_PAGE_ORIENTATION='portrait',
392 MAP_GRID_PEN_PRIMARY='thinnest,0/50/0',
393 MAP_ANNOT_OBLIQUE='6')
394 else:
395 gmtconf = dict(
396 TICK_PEN='1.25p',
397 TICK_LENGTH='0.2c',
398 ANNOT_FONT_PRIMARY='1',
399 ANNOT_FONT_SIZE_PRIMARY='12p',
400 LABEL_FONT='1',
401 LABEL_FONT_SIZE='12p',
402 CHAR_ENCODING='ISOLatin1+',
403 BASEMAP_TYPE='fancy',
404 PLOT_DEGREE_FORMAT='D',
405 PAPER_MEDIA='Custom_%ix%i' % (
406 w*gmtpy.cm,
407 h*gmtpy.cm),
408 GRID_PEN_PRIMARY='thinnest/0/50/0',
409 DOTS_PR_INCH='1200',
410 OBLIQUE_ANNOTATION='6')
412 gmtconf.update(
413 (k.upper(), v) for (k, v) in self.gmt_config.items())
415 gmt = gmtpy.GMT(config=gmtconf, version=self._gmtversion)
417 layout = gmt.default_layout()
419 layout.set_fixed_margins(*[x*cm for x in self._expand_margins()])
421 widget = layout.get_widget()
422 widget['P'] = widget['J']
423 widget['J'] = ('-JA%g/%g' % (self.lon, self.lat)) + '/%(width)gp'
424 scaler['R'] = '-R%g/%g/%g/%gr' % self._corners
426 # aspect = gmtpy.aspect_for_projection(
427 # gmt.installation['version'], *(widget.J() + scaler.R()))
429 aspect = self._map_aspect(jr=widget.J() + scaler.R())
430 widget.set_aspect(aspect)
432 self._gmt = gmt
433 self._layout = layout
434 self._widget = widget
435 self._jxyr = self._widget.JXY() + self._scaler.R()
436 self._pxyr = self._widget.PXY() + [
437 '-R%g/%g/%g/%g' % (0, widget.width(), 0, widget.height())]
438 self._have_drawn_axes = False
439 self._have_drawn_labels = False
441 def _draw_background(self):
442 self._have_topo_land = False
443 self._have_topo_ocean = False
444 if self.show_topo:
445 self._have_topo = self._draw_topo()
447 self._draw_basefeatures()
449 def _get_topo_tile(self, k):
450 t = None
451 demname = None
452 for dem in self._dems[k]:
453 t = topo.get(dem, self._wesn)
454 demname = dem
455 if t is not None:
456 break
458 if not t:
459 raise NoTopo()
461 return t, demname
463 def _prep_topo(self, k):
464 gmt = self._gmt
465 t, demname = self._get_topo_tile(k)
467 if demname not in self._prep_topo_have:
469 grdfile = gmt.tempfilename()
471 is_flat = num.all(t.data[0] == t.data)
473 gmtpy.savegrd(
474 t.x(), t.y(), t.data, filename=grdfile, naming='lonlat')
476 if self.illuminate and not is_flat:
477 if k == 'ocean':
478 factor = self.illuminate_factor_ocean
479 else:
480 factor = self.illuminate_factor_land
482 ilumfn = gmt.tempfilename()
483 gmt.grdgradient(
484 grdfile,
485 N='e%g' % factor,
486 A=-45,
487 G=ilumfn,
488 out_discard=True)
490 ilumargs = ['-I%s' % ilumfn]
491 else:
492 ilumargs = []
494 if self.replace_topo_color_only:
495 t2 = self.replace_topo_color_only
496 grdfile2 = gmt.tempfilename()
498 gmtpy.savegrd(
499 t2.x(), t2.y(), t2.data, filename=grdfile2,
500 naming='lonlat')
502 if gmt.is_gmt5():
503 gmt.grdsample(
504 grdfile2,
505 G=grdfile,
506 n='l',
507 I='%g/%g' % (t.dx, t.dy), # noqa
508 R=grdfile,
509 out_discard=True)
510 else:
511 gmt.grdsample(
512 grdfile2,
513 G=grdfile,
514 Q='l',
515 I='%g/%g' % (t.dx, t.dy), # noqa
516 R=grdfile,
517 out_discard=True)
519 gmt.grdmath(
520 grdfile, '0.0', 'AND', '=', grdfile2,
521 out_discard=True)
523 grdfile = grdfile2
525 self._prep_topo_have[demname] = grdfile, ilumargs
527 return self._prep_topo_have[demname]
529 def _draw_topo(self):
530 widget = self._widget
531 scaler = self._scaler
532 gmt = self._gmt
533 cres = self._coastline_resolution
534 minarea = self._minarea
536 JXY = widget.JXY()
537 R = scaler.R()
539 try:
540 grdfile, ilumargs = self._prep_topo('ocean')
541 gmt.pscoast(D=cres, S='c', A=minarea, *(JXY+R))
542 gmt.grdimage(grdfile, C=topo.cpt(self.topo_cpt_wet),
543 *(ilumargs+JXY+R))
544 gmt.pscoast(Q=True, *(JXY+R))
545 self._have_topo_ocean = True
546 except NoTopo:
547 self._have_topo_ocean = False
549 try:
550 grdfile, ilumargs = self._prep_topo('land')
551 gmt.pscoast(D=cres, G='c', A=minarea, *(JXY+R))
552 gmt.grdimage(grdfile, C=topo.cpt(self.topo_cpt_dry),
553 *(ilumargs+JXY+R))
554 gmt.pscoast(Q=True, *(JXY+R))
555 self._have_topo_land = True
556 except NoTopo:
557 self._have_topo_land = False
559 def _draw_topo_scale(self, label='Elevation [km]'):
560 dry = read_cpt(topo.cpt(self.topo_cpt_dry))
561 wet = read_cpt(topo.cpt(self.topo_cpt_wet))
562 combi = cpt_merge_wet_dry(wet, dry)
563 for level in combi.levels:
564 level.vmin /= km
565 level.vmax /= km
567 topo_cpt = self.gmt.tempfilename() + '.cpt'
568 write_cpt(combi, topo_cpt)
570 (w, h), (xo, yo) = self.widget.get_size()
571 self.gmt.psscale(
572 D='%gp/%gp/%gp/%gph' % (xo + 0.5*w, yo - 2.0*gmtpy.cm, w,
573 0.5*gmtpy.cm),
574 C=topo_cpt,
575 B='1:%s:' % label)
577 def _draw_basefeatures(self):
578 gmt = self._gmt
579 cres = self._coastline_resolution
580 rivers = self._rivers
581 minarea = self._minarea
583 color_wet = self.color_wet
584 color_dry = self.color_dry
586 if self.show_rivers and rivers:
587 rivers = ['-Ir/0.25p,%s' % gmtpy.color(self.color_wet)]
588 else:
589 rivers = []
591 fill = {}
592 if not self._have_topo_land:
593 fill['G'] = color_dry
595 if not self._have_topo_ocean:
596 fill['S'] = color_wet
598 if self.show_boundaries:
599 fill['N'] = '1/1p,%s,%s' % (
600 gmtpy.color(self.color_boundaries), 'solid')
602 gmt.pscoast(
603 D=cres,
604 W='thinnest,%s' % gmtpy.color(darken(gmtpy.color_tup(color_dry))),
605 A=minarea,
606 *(rivers+self._jxyr), **fill)
608 if self.show_plates:
609 self.draw_plates()
611 def _draw_axes(self):
612 gmt = self._gmt
613 scaler = self._scaler
614 widget = self._widget
616 if self.axes_layout is None:
617 if self.lat > 0.0:
618 axes_layout = 'WSen'
619 else:
620 axes_layout = 'WseN'
621 else:
622 axes_layout = self.axes_layout
624 scale_km = gmtpy.nice_value(self.radius/5.) / 1000.
626 if self.show_center_mark:
627 gmt.psxy(
628 in_rows=[[self.lon, self.lat]],
629 S='c20p', W='2p,black',
630 *self._jxyr)
632 if self.show_grid:
633 btmpl = ('%(xinc)gg%(xinc)g:%(xlabel)s:/'
634 '%(yinc)gg%(yinc)g:%(ylabel)s:')
635 else:
636 btmpl = '%(xinc)g:%(xlabel)s:/%(yinc)g:%(ylabel)s:'
638 if self.show_scale:
639 scale = 'x%gp/%gp/%g/%g/%gk' % (
640 6./7*widget.width(),
641 widget.height()/7.,
642 self.lon,
643 self.lat,
644 scale_km)
645 else:
646 scale = False
648 gmt.psbasemap(
649 B=(btmpl % scaler.get_params())+axes_layout,
650 L=scale,
651 *self._jxyr)
653 if self.comment:
654 font_size = self.gmt.label_font_size()
656 _, east, south, _ = self._wesn
657 if gmt.is_gmt5():
658 row = [
659 1, 0,
660 '%gp,%s,%s' % (font_size, 0, 'black'), 'BR',
661 self.comment]
663 farg = ['-F+f+j']
664 else:
665 row = [1, 0, font_size, 0, 0, 'BR', self.comment]
666 farg = []
668 gmt.pstext(
669 in_rows=[row],
670 N=True,
671 R=(0, 1, 0, 1),
672 D='%gp/%gp' % (-font_size*0.2, font_size*0.3),
673 *(widget.PXY() + farg))
675 def draw_axes(self):
676 if not self._have_drawn_axes:
677 self._draw_axes()
678 self._have_drawn_axes = True
680 def _have_coastlines(self):
681 gmt = self._gmt
682 cres = self._coastline_resolution
683 minarea = self._minarea
685 checkfile = gmt.tempfilename()
687 gmt.pscoast(
688 M=True,
689 D=cres,
690 W='thinnest,black',
691 A=minarea,
692 out_filename=checkfile,
693 *self._jxyr)
695 points = []
696 with open(checkfile, 'r') as f:
697 for line in f:
698 ls = line.strip()
699 if ls.startswith('#') or ls.startswith('>') or ls == '':
700 continue
701 plon, plat = [float(x) for x in ls.split()]
702 points.append((plat, plon))
704 points = num.array(points, dtype=float)
705 return num.any(points_in_region(points, self._wesn))
707 def have_coastlines(self):
708 self.gmt
709 return self._have_coastlines()
711 def project(self, lats, lons, jr=None):
712 onepoint = False
713 if isinstance(lats, float) and isinstance(lons, float):
714 lats = [lats]
715 lons = [lons]
716 onepoint = True
718 if jr is not None:
719 j, r = jr
720 gmt = gmtpy.GMT(version=self._gmtversion)
721 else:
722 j, _, _, r = self.jxyr
723 gmt = self.gmt
725 f = BytesIO()
726 gmt.mapproject(j, r, in_columns=(lons, lats), out_stream=f, D='p')
727 f.seek(0)
728 data = num.loadtxt(f, ndmin=2)
729 xs, ys = data.T
730 if onepoint:
731 xs = xs[0]
732 ys = ys[0]
733 return xs, ys
735 def _map_box(self, jr=None):
736 ll_lon, ll_lat, ur_lon, ur_lat = self._corners
738 xs_corner, ys_corner = self.project(
739 (ll_lat, ur_lat), (ll_lon, ur_lon), jr=jr)
741 w = xs_corner[1] - xs_corner[0]
742 h = ys_corner[1] - ys_corner[0]
744 return w, h
746 def _map_aspect(self, jr=None):
747 w, h = self._map_box(jr=jr)
748 return h/w
750 def _draw_labels(self):
751 points_taken = []
752 regions_taken = []
754 def no_points_in_rect(xs, ys, xmin, ymin, xmax, ymax):
755 xx = not num.any(la(la(xmin < xs, xs < xmax),
756 la(ymin < ys, ys < ymax)))
757 return xx
759 def roverlaps(a, b):
760 return (a[0] < b[2] and b[0] < a[2] and
761 a[1] < b[3] and b[1] < a[3])
763 w, h = self._map_box()
765 label_font_size = self.gmt.label_font_size()
767 if self._labels:
769 n = len(self._labels)
771 lons, lats, texts, sx, sy, colors, fonts, font_sizes, \
772 angles, styles = list(zip(*self._labels))
774 font_sizes = [
775 (font_size or label_font_size) for font_size in font_sizes]
777 sx = num.array(sx, dtype=float)
778 sy = num.array(sy, dtype=float)
780 xs, ys = self.project(lats, lons)
782 points_taken.append((xs, ys))
784 dxs = num.zeros(n)
785 dys = num.zeros(n)
787 for i in range(n):
788 dx, dy = gmtpy.text_box(
789 texts[i],
790 font=fonts[i],
791 font_size=font_sizes[i],
792 **styles[i])
794 dxs[i] = dx
795 dys[i] = dy
797 la = num.logical_and
798 anchors_ok = (
799 la(xs + sx + dxs < w, ys + sy + dys < h),
800 la(xs - sx - dxs > 0., ys - sy - dys > 0.),
801 la(xs + sx + dxs < w, ys - sy - dys > 0.),
802 la(xs - sx - dxs > 0., ys + sy + dys < h),
803 )
805 arects = [
806 (xs, ys, xs + sx + dxs, ys + sy + dys),
807 (xs - sx - dxs, ys - sy - dys, xs, ys),
808 (xs, ys - sy - dys, xs + sx + dxs, ys),
809 (xs - sx - dxs, ys, xs, ys + sy + dys)]
811 for i in range(n):
812 for ianch in range(4):
813 anchors_ok[ianch][i] &= no_points_in_rect(
814 xs, ys, *[xxx[i] for xxx in arects[ianch]])
816 anchor_choices = []
817 anchor_take = []
818 for i in range(n):
819 choices = [ianch for ianch in range(4)
820 if anchors_ok[ianch][i]]
821 anchor_choices.append(choices)
822 if choices:
823 anchor_take.append(choices[0])
824 else:
825 anchor_take.append(None)
827 def cost(anchor_take):
828 noverlaps = 0
829 for i in range(n):
830 for j in range(n):
831 if i != j:
832 i_take = anchor_take[i]
833 j_take = anchor_take[j]
834 if i_take is None or j_take is None:
835 continue
836 r_i = [xxx[i] for xxx in arects[i_take]]
837 r_j = [xxx[j] for xxx in arects[j_take]]
838 if roverlaps(r_i, r_j):
839 noverlaps += 1
841 return noverlaps
843 cur_cost = cost(anchor_take)
844 imax = 30
845 while cur_cost != 0 and imax > 0:
846 for i in range(n):
847 for t in anchor_choices[i]:
848 anchor_take_new = list(anchor_take)
849 anchor_take_new[i] = t
850 new_cost = cost(anchor_take_new)
851 if new_cost < cur_cost:
852 anchor_take = anchor_take_new
853 cur_cost = new_cost
855 imax -= 1
857 while cur_cost != 0:
858 for i in range(n):
859 anchor_take_new = list(anchor_take)
860 anchor_take_new[i] = None
861 new_cost = cost(anchor_take_new)
862 if new_cost < cur_cost:
863 anchor_take = anchor_take_new
864 cur_cost = new_cost
865 break
867 anchor_strs = ['BL', 'TR', 'TL', 'BR']
869 for i in range(n):
870 ianchor = anchor_take[i]
871 color = colors[i]
872 if color is None:
873 color = 'black'
875 if ianchor is not None:
876 regions_taken.append([xxx[i] for xxx in arects[ianchor]])
878 anchor = anchor_strs[ianchor]
880 yoff = [-sy[i], sy[i]][anchor[0] == 'B']
881 xoff = [-sx[i], sx[i]][anchor[1] == 'L']
882 if self.gmt.is_gmt5():
883 row = (
884 lons[i], lats[i],
885 '%i,%s,%s' % (font_sizes[i], fonts[i], color),
886 anchor,
887 texts[i])
889 farg = ['-F+f+j+a%g' % angles[i]]
890 else:
891 row = (
892 lons[i], lats[i],
893 font_sizes[i], angles[i], fonts[i], anchor,
894 texts[i])
895 farg = ['-G%s' % color]
897 self.gmt.pstext(
898 in_rows=[row],
899 D='%gp/%gp' % (xoff, yoff),
900 *(self.jxyr + farg),
901 **styles[i])
903 if self._area_labels:
905 for lons, lats, text, color, font, font_size, style in \
906 self._area_labels:
908 if font_size is None:
909 font_size = label_font_size
911 if color is None:
912 color = 'black'
914 if self.gmt.is_gmt5():
915 farg = ['-F+f+j']
916 else:
917 farg = ['-G%s' % color]
919 xs, ys = self.project(lats, lons)
920 dx, dy = gmtpy.text_box(
921 text, font=font, font_size=font_size, **style)
923 rects = [xs-0.5*dx, ys-0.5*dy, xs+0.5*dx, ys+0.5*dy]
925 locs_ok = num.ones(xs.size, dtype=num.bool)
927 for iloc in range(xs.size):
928 rcandi = [xxx[iloc] for xxx in rects]
930 locs_ok[iloc] = True
931 locs_ok[iloc] &= (
932 0 < rcandi[0] and rcandi[2] < w
933 and 0 < rcandi[1] and rcandi[3] < h)
935 overlap = False
936 for r in regions_taken:
937 if roverlaps(r, rcandi):
938 overlap = True
939 break
941 locs_ok[iloc] &= not overlap
943 for xs_taken, ys_taken in points_taken:
944 locs_ok[iloc] &= no_points_in_rect(
945 xs_taken, ys_taken, *rcandi)
947 if not locs_ok[iloc]:
948 break
950 rows = []
951 for iloc, (lon, lat) in enumerate(zip(lons, lats)):
952 if not locs_ok[iloc]:
953 continue
955 if self.gmt.is_gmt5():
956 row = (
957 lon, lat,
958 '%i,%s,%s' % (font_size, font, color),
959 'MC',
960 text)
962 else:
963 row = (
964 lon, lat,
965 font_size, 0, font, 'MC',
966 text)
968 rows.append(row)
970 regions_taken.append([xxx[iloc] for xxx in rects])
971 break
973 self.gmt.pstext(
974 in_rows=rows,
975 *(self.jxyr + farg),
976 **style)
978 def draw_labels(self):
979 self.gmt
980 if not self._have_drawn_labels:
981 self._draw_labels()
982 self._have_drawn_labels = True
984 def add_label(
985 self, lat, lon, text,
986 offset_x=5., offset_y=5.,
987 color=None,
988 font='1',
989 font_size=None,
990 angle=0,
991 style={}):
993 if 'G' in style:
994 style = style.copy()
995 color = style.pop('G')
997 self._labels.append(
998 (lon, lat, text, offset_x, offset_y, color, font, font_size,
999 angle, style))
1001 def add_area_label(
1002 self, lat, lon, text,
1003 color=None,
1004 font='3',
1005 font_size=None,
1006 style={}):
1008 self._area_labels.append(
1009 (lon, lat, text, color, font, font_size, style))
1011 def cities_in_region(self):
1012 from pyrocko.dataset import geonames
1013 cities = geonames.get_cities_region(region=self.wesn, minpop=0)
1014 cities.extend(self.custom_cities)
1015 cities.sort(key=lambda x: x.population)
1016 return cities
1018 def draw_cities(self,
1019 exact=None,
1020 include=[],
1021 exclude=[],
1022 nmax_soft=10,
1023 psxy_style=dict(S='s5p', G='black')):
1025 cities = self.cities_in_region()
1027 if exact is not None:
1028 cities = [c for c in cities if c.name in exact]
1029 minpop = None
1030 else:
1031 cities = [c for c in cities if c.name not in exclude]
1032 minpop = 10**3
1033 for minpop_new in [1e3, 3e3, 1e4, 3e4, 1e5, 3e5, 1e6, 3e6, 1e7]:
1034 cities_new = [
1035 c for c in cities
1036 if c.population > minpop_new or c.name in include]
1038 if len(cities_new) == 0 or (
1039 len(cities_new) < 3 and len(cities) < nmax_soft*2):
1040 break
1042 cities = cities_new
1043 minpop = minpop_new
1044 if len(cities) <= nmax_soft:
1045 break
1047 if cities:
1048 lats = [c.lat for c in cities]
1049 lons = [c.lon for c in cities]
1051 self.gmt.psxy(
1052 in_columns=(lons, lats),
1053 *self.jxyr, **psxy_style)
1055 for c in cities:
1056 try:
1057 text = c.name.encode('iso-8859-1').decode('iso-8859-1')
1058 except UnicodeEncodeError:
1059 text = c.asciiname
1061 self.add_label(c.lat, c.lon, text)
1063 self._cities_minpop = minpop
1065 def add_stations(self, stations, psxy_style=dict()):
1067 default_psxy_style = {
1068 'S': 't8p',
1069 'G': 'black'
1070 }
1071 default_psxy_style.update(psxy_style)
1073 lats, lons = zip(*[s.effective_latlon for s in stations])
1075 self.gmt.psxy(
1076 in_columns=(lons, lats),
1077 *self.jxyr, **default_psxy_style)
1079 for station in stations:
1080 self.add_label(
1081 station.effective_lat,
1082 station.effective_lon,
1083 '.'.join(x for x in (station.network, station.station) if x))
1085 def add_kite_scene(self, scene):
1086 tile = FloatTile(
1087 scene.frame.llLon,
1088 scene.frame.llLat,
1089 scene.frame.dLon,
1090 scene.frame.dLat,
1091 scene.displacement)
1093 return tile
1095 def add_gnss_campaign(self, campaign, psxy_style=None, offset_scale=None,
1096 labels=True, vertical=False, fontsize=10):
1098 stations = campaign.stations
1100 if offset_scale is None:
1101 offset_scale = num.zeros(campaign.nstations)
1102 for ista, sta in enumerate(stations):
1103 for comp in sta.components.values():
1104 offset_scale[ista] += comp.shift
1105 offset_scale = num.sqrt(offset_scale**2).max()
1107 size = math.sqrt(self.height**2 + self.width**2)
1108 scale = (size/10.) / offset_scale
1109 logger.debug('GNSS: Using offset scale %f, map scale %f',
1110 offset_scale, scale)
1112 lats, lons = zip(*[s.effective_latlon for s in stations])
1114 if vertical:
1115 rows = [[lons[ista], lats[ista],
1116 0., -s.up.shift,
1117 (s.east.sigma + s.north.sigma) if s.east.sigma else 0.,
1118 s.up.sigma, 0.,
1119 s.code if labels else None]
1120 for ista, s in enumerate(stations)
1121 if s.up is not None]
1123 else:
1124 rows = [[lons[ista], lats[ista],
1125 -s.east.shift, -s.north.shift,
1126 s.east.sigma, s.north.sigma, s.correlation_ne,
1127 s.code if labels else None]
1128 for ista, s in enumerate(stations)
1129 if s.east is not None or s.north is not None]
1131 default_psxy_style = {
1132 'h': 0,
1133 'W': '2p,black',
1134 'A': '+p2p,black+b+a40',
1135 'G': 'black',
1136 'L': True,
1137 'S': 'e%dc/0.95/%d' % (scale, fontsize),
1138 }
1140 if not labels:
1141 for row in rows:
1142 row.pop(-1)
1144 if psxy_style is not None:
1145 default_psxy_style.update(psxy_style)
1147 self.gmt.psvelo(
1148 in_rows=rows,
1149 *self.jxyr,
1150 **default_psxy_style)
1152 def draw_plates(self):
1153 from pyrocko.dataset import tectonics
1155 neast = 20
1156 nnorth = max(1, int(round(num.round(self._hreg/self._wreg * neast))))
1157 norths = num.linspace(-self._hreg*0.5, self._hreg*0.5, nnorth)
1158 easts = num.linspace(-self._wreg*0.5, self._wreg*0.5, neast)
1159 norths2 = num.repeat(norths, neast)
1160 easts2 = num.tile(easts, nnorth)
1161 lats, lons = od.ne_to_latlon(
1162 self.lat, self.lon, norths2, easts2)
1164 bird = tectonics.PeterBird2003()
1165 plates = bird.get_plates()
1167 color_plates = gmtpy.color('aluminium5')
1168 color_velocities = gmtpy.color('skyblue1')
1169 color_velocities_lab = gmtpy.color(darken(gmtpy.color_tup('skyblue1')))
1171 points = num.vstack((lats, lons)).T
1172 used = []
1173 for plate in plates:
1174 mask = plate.contains_points(points)
1175 if num.any(mask):
1176 used.append((plate, mask))
1178 if len(used) > 1:
1180 candi_fixed = {}
1182 label_data = []
1183 for plate, mask in used:
1185 mean_north = num.mean(norths2[mask])
1186 mean_east = num.mean(easts2[mask])
1187 iorder = num.argsort(num.sqrt(
1188 (norths2[mask] - mean_north)**2 +
1189 (easts2[mask] - mean_east)**2))
1191 lat_candis = lats[mask][iorder]
1192 lon_candis = lons[mask][iorder]
1194 candi_fixed[plate.name] = lat_candis.size
1196 label_data.append((
1197 lat_candis, lon_candis, plate, color_plates))
1199 boundaries = bird.get_boundaries()
1201 size = 1.
1203 psxy_kwargs = []
1205 for boundary in boundaries:
1206 if num.any(points_in_region(boundary.points, self._wesn)):
1207 for typ, part in boundary.split_types(
1208 [['SUB'],
1209 ['OSR', 'OTF', 'OCB', 'CTF', 'CCB', 'CRB']]):
1211 lats, lons = part.T
1213 kwargs = {}
1214 if typ[0] == 'SUB':
1215 if boundary.kind == '\\':
1216 kwargs['S'] = 'f%g/%gp+t+r' % (
1217 0.45*size, 3.*size)
1218 elif boundary.kind == '/':
1219 kwargs['S'] = 'f%g/%gp+t+l' % (
1220 0.45*size, 3.*size)
1222 kwargs['G'] = color_plates
1224 kwargs['in_columns'] = (lons, lats)
1225 kwargs['W'] = '%gp,%s' % (size, color_plates),
1227 psxy_kwargs.append(kwargs)
1229 if boundary.kind == '\\':
1230 if boundary.plate_name2 in candi_fixed:
1231 candi_fixed[boundary.plate_name2] += \
1232 neast*nnorth
1234 elif boundary.kind == '/':
1235 if boundary.plate_name1 in candi_fixed:
1236 candi_fixed[boundary.plate_name1] += \
1237 neast*nnorth
1239 candi_fixed = [name for name in sorted(
1240 list(candi_fixed.keys()), key=lambda name: -candi_fixed[name])]
1242 candi_fixed.append(None)
1244 gsrm = tectonics.GSRM1()
1246 for name in candi_fixed:
1247 if name not in gsrm.plate_names() \
1248 and name not in gsrm.plate_alt_names():
1250 continue
1252 lats, lons, vnorth, veast, vnorth_err, veast_err, corr = \
1253 gsrm.get_velocities(name, region=self._wesn)
1255 fixed_plate_name = name
1257 if self.show_plate_velocities:
1258 self.gmt.psvelo(
1259 in_columns=(
1260 lons, lats, veast, vnorth, veast_err, vnorth_err,
1261 corr),
1262 W='0.25p,%s' % color_velocities,
1263 A='9p+e+g%s' % color_velocities,
1264 S='e0.2p/0.95/10',
1265 *self.jxyr)
1267 for _ in range(len(lons) // 50 + 1):
1268 ii = random.randint(0, len(lons)-1)
1269 v = math.sqrt(vnorth[ii]**2 + veast[ii]**2)
1270 self.add_label(
1271 lats[ii], lons[ii], '%.0f' % v,
1272 font_size=0.7*self.gmt.label_font_size(),
1273 style=dict(
1274 G=color_velocities_lab))
1276 break
1278 if self.show_plate_names:
1279 for (lat_candis, lon_candis, plate, color) in label_data:
1280 full_name = bird.full_name(plate.name)
1281 if plate.name == fixed_plate_name:
1282 full_name = '@_' + full_name + '@_'
1284 self.add_area_label(
1285 lat_candis, lon_candis,
1286 full_name,
1287 color=color,
1288 font='3')
1290 for kwargs in psxy_kwargs:
1291 self.gmt.psxy(*self.jxyr, **kwargs)
1294def rand(mi, ma):
1295 mi = float(mi)
1296 ma = float(ma)
1297 return random.random() * (ma-mi) + mi
1300def split_region(region):
1301 west, east, south, north = topo.positive_region(region)
1302 if east > 180:
1303 return [(west, 180., south, north),
1304 (-180., east-360., south, north)]
1305 else:
1306 return [region]
1309class CPTLevel(Object):
1310 vmin = Float.T()
1311 vmax = Float.T()
1312 color_min = Tuple.T(3, Float.T())
1313 color_max = Tuple.T(3, Float.T())
1316class CPT(Object):
1317 color_below = Tuple.T(3, Float.T(), optional=True)
1318 color_above = Tuple.T(3, Float.T(), optional=True)
1319 color_nan = Tuple.T(3, Float.T(), optional=True)
1320 levels = List.T(CPTLevel.T())
1322 def scale(self, vmin, vmax):
1323 vmin_old, vmax_old = self.levels[0].vmin, self.levels[-1].vmax
1324 for level in self.levels:
1325 level.vmin = (level.vmin - vmin_old) / (vmax_old - vmin_old) * \
1326 (vmax - vmin) + vmin
1327 level.vmax = (level.vmax - vmin_old) / (vmax_old - vmin_old) * \
1328 (vmax - vmin) + vmin
1330 def discretize(self, nlevels):
1331 colors = []
1332 vals = []
1333 for level in self.levels:
1334 vals.append(level.vmin)
1335 vals.append(level.vmax)
1336 colors.append(level.color_min)
1337 colors.append(level.color_max)
1339 r, g, b = num.array(colors, dtype=float).T
1340 vals = num.array(vals, dtype=float)
1342 vmin, vmax = self.levels[0].vmin, self.levels[-1].vmax
1343 x = num.linspace(vmin, vmax, nlevels+1)
1344 rd = num.interp(x, vals, r)
1345 gd = num.interp(x, vals, g)
1346 bd = num.interp(x, vals, b)
1348 levels = []
1349 for ilevel in range(nlevels):
1350 color = (
1351 float(0.5*(rd[ilevel]+rd[ilevel+1])),
1352 float(0.5*(gd[ilevel]+gd[ilevel+1])),
1353 float(0.5*(bd[ilevel]+bd[ilevel+1])))
1355 levels.append(CPTLevel(
1356 vmin=x[ilevel],
1357 vmax=x[ilevel+1],
1358 color_min=color,
1359 color_max=color))
1361 cpt = CPT(
1362 color_below=self.color_below,
1363 color_above=self.color_above,
1364 color_nan=self.color_nan,
1365 levels=levels)
1367 return cpt
1370class CPTParseError(Exception):
1371 pass
1374def read_cpt(filename):
1375 with open(filename) as f:
1376 color_below = None
1377 color_above = None
1378 color_nan = None
1379 levels = []
1380 try:
1381 for line in f:
1382 line = line.strip()
1383 toks = line.split()
1385 if line.startswith('#'):
1386 continue
1388 elif line.startswith('B'):
1389 color_below = tuple(map(float, toks[1:4]))
1391 elif line.startswith('F'):
1392 color_above = tuple(map(float, toks[1:4]))
1394 elif line.startswith('N'):
1395 color_nan = tuple(map(float, toks[1:4]))
1397 else:
1398 values = list(map(float, line.split()))
1399 vmin = values[0]
1400 color_min = tuple(values[1:4])
1401 vmax = values[4]
1402 color_max = tuple(values[5:8])
1403 levels.append(CPTLevel(
1404 vmin=vmin,
1405 vmax=vmax,
1406 color_min=color_min,
1407 color_max=color_max))
1409 except Exception:
1410 raise CPTParseError()
1412 return CPT(
1413 color_below=color_below,
1414 color_above=color_above,
1415 color_nan=color_nan,
1416 levels=levels)
1419def color_to_int(color):
1420 return tuple(max(0, min(255, int(round(x)))) for x in color)
1423def write_cpt(cpt, filename):
1424 with open(filename, 'w') as f:
1425 for level in cpt.levels:
1426 f.write(
1427 '%e %i %i %i %e %i %i %i\n' %
1428 ((level.vmin, ) + color_to_int(level.color_min) +
1429 (level.vmax, ) + color_to_int(level.color_max)))
1431 if cpt.color_below:
1432 f.write('B %i %i %i\n' % color_to_int(cpt.color_below))
1434 if cpt.color_above:
1435 f.write('F %i %i %i\n' % color_to_int(cpt.color_above))
1437 if cpt.color_nan:
1438 f.write('N %i %i %i\n' % color_to_int(cpt.color_nan))
1441def cpt_merge_wet_dry(wet, dry):
1442 levels = []
1443 for level in wet.levels:
1444 if level.vmin < 0.:
1445 if level.vmax > 0.:
1446 level.vmax = 0.
1448 levels.append(level)
1450 for level in dry.levels:
1451 if level.vmax > 0.:
1452 if level.vmin < 0.:
1453 level.vmin = 0.
1455 levels.append(level)
1457 combi = CPT(
1458 color_below=wet.color_below,
1459 color_above=dry.color_above,
1460 color_nan=dry.color_nan,
1461 levels=levels)
1463 return combi
1466if __name__ == '__main__':
1467 from pyrocko import util
1468 util.setup_logging('pyrocko.automap', 'info')
1470 import sys
1471 if len(sys.argv) == 2:
1473 n = int(sys.argv[1])
1475 for i in range(n):
1476 m = Map(
1477 lat=rand(-60., 60.),
1478 lon=rand(-180., 180.),
1479 radius=math.exp(rand(math.log(500*km), math.log(3000*km))),
1480 width=30., height=30.,
1481 show_grid=True,
1482 show_topo=True,
1483 color_dry=(238, 236, 230),
1484 topo_cpt_wet='light_sea_uniform',
1485 topo_cpt_dry='light_land_uniform',
1486 illuminate=True,
1487 illuminate_factor_ocean=0.15,
1488 show_rivers=False,
1489 show_plates=True)
1491 m.draw_cities()
1492 print(m)
1493 m.save('map_%02i.pdf' % i)