-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathmatplotlib2tikz.py
1723 lines (1497 loc) · 61.2 KB
/
matplotlib2tikz.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
# -*- coding: utf-8 -*-
#
# Copyright (C) 2010--2014 Nico Schlömer
#
# This file is part of matplotlib2tikz.
#
# matplotlib2tikz is free software: you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by the Free
# Software Foundation, either version 3 of the License, or (at your option) any
# later version.
#
# matplotlib2tikz is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
# FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for
# more details.
#
# You should have received a copy of the GNU General Public License along with
# matplotlib2tikz. If not, see <http://www.gnu.org/licenses/>.
#
'''Script to convert Matplotlib generated figures into TikZ/Pgfplots figures.
'''
# imported modules
import matplotlib as mpl
import numpy as np
import os
import warnings
import matplotlib.backends.backend_agg as bagg
import matplotlib._png as _png
# meta info
__author__ = 'Nico Schlömer'
__email__ = '[email protected]'
__copyright__ = 'Copyright (c) 2010--2014, %s <%s>' % (__author__, __email__)
__credits__ = []
__license__ = 'GNU Lesser General Public License (LGPL), Version 3'
__version__ = '0.1.0'
__maintainer__ = 'Nico Schlömer'
__status__ = 'Development'
def save(filepath,
figure='gcf',
encoding=None,
figurewidth=None,
figureheight=None,
textsize=10.0,
tex_relative_path_to_data=None,
strict=False,
draw_rectangles=False,
wrap=True,
extra=None,
show_info=True
):
'''Main function. Here, the recursion into the image starts and the
contents are picked up. The actual file gets written in this routine.
:param figure: either a Figure object or 'gcf' (default).
:param filepath: The file to which the TikZ output will be written.
:type filepath: str
:param encoding: Which encoding to use for the file.
:param figurewidth: If not ``None``, this will be used as figure width
within the TikZ/Pgfplot output. If ``figureheight``
is not given, ``matplotlib2tikz`` will try to preserve
the original width/height ratio.
Note that ``figurewidth`` can be a string literal,
such as ``'\\figurewidth'``.
:type figurewidth: str
:param figureheight: If not ``None``, this will be used as figure height
within the TikZ/Pgfplot output. If ``figurewidth`` is
not given, ``matplotlib2tikz`` will try to preserve
the original width/height ratio. Note that
``figurewidth`` can be a string literal, such as
``'\\figureheight'``.
:type figureheight: str
:param textsize: The text size (in pt) that the target latex document is
using. Default is 10.0.
:type textsize: float
:param tex_relative_path_to_data: In some cases, the TikZ file will have to
refer to another file, e.g., a PNG for
image plots. When ``\\input`` into a
regular LaTeX document, the additional
file is looked for in a folder relative
to the LaTeX file, not the TikZ file.
This arguments optionally sets the
relative path from the LaTeX file to the
data.
:type tex_relative_path_to_data: str
:param strict: Whether or not to strictly stick to matplotlib's appearance.
This influences, for example, whether tick marks are set
exactly as in the matplotlib plot, or if TikZ/Pgfplots
can decide where to put the ticks.
:type strict: bool
:param draw_rectangles: Whether or not to draw Rectangle objects.
You normally don't want that as legend, axes, and
other entities which are natively taken care of by
Pgfplots are represented as rectangles in
matplotlib. Some plot types (such as bar plots)
cannot otherwise be represented though.
Don't expect working or clean output when using
this option.
:type draw_rectangles: bool
:param wrap: Whether ``'\\begin{tikzpicture}'`` and
``'\\end{tikzpicture}'`` will be written. One might need to
provide custom arguments to the environment (eg. scale= etc.).
Default is ``True``.
:type wrap: bool
:param extra: Extra axis options to be passed (as a set) to pgfplots.
Default is ``None``.
:type extra: a set of strings for the pfgplots axes.
:returns: None
The following optional attributes of matplotlib's objects are recognized
and handled:
- axes.Axes._matplotlib2tikz_anchors
This attribute can be set to a list of ((x,y), anchor_name) tuples.
Invisible nodes at the respective location will be created which can be
referenced from outside the axis environment.
'''
# not as default value because gcf() would be evaluated at import time
if figure == 'gcf':
figure = mpl.pyplot.gcf()
data = {}
data['fwidth'] = figurewidth
data['fheight'] = figureheight
data['rel data path'] = tex_relative_path_to_data
data['output dir'] = os.path.dirname(filepath)
data['strict'] = strict
data['draw rectangles'] = draw_rectangles
data['tikz libs'] = set()
data['pgfplots libs'] = set()
data['font size'] = textsize
data['custom colors'] = {}
if extra:
data['extra axis options'] = extra.copy()
else:
data['extra axis options'] = set()
# open file
import codecs
file_handle = codecs.open(filepath, 'w', encoding)
if show_info:
print('file encoding: {0}'.format(file_handle.encoding))
# gather the file content
data, content = _handle_children(data, figure)
disclaimer = (
'This file was created by matplotlib v%s.\n'
'%s\n'
'All rights reserved.\n') \
% (__version__, __copyright__)
if show_info:
disclaimer += \
'\nThe lastest updates can be retrieved from\n\n' \
+ 'https://github.com/nschloe/matplotlib2tikz\n\n' \
+ 'where you can also submit bug reports and leave' \
+ 'comments.\n'
# write disclaimer to the file header
file_handle.write(_tex_comment(disclaimer))
# write the contents
if wrap:
file_handle.write('\\begin{tikzpicture}\n\n')
coldefs = _get_color_definitions(data)
if coldefs:
file_handle.write('\n'.join(coldefs))
file_handle.write('\n\n')
file_handle.write(''.join(content))
if wrap:
file_handle.write('\\end{tikzpicture}')
# close file
file_handle.close()
# print message about necessary pgfplot libs to command line
if show_info:
_print_pgfplot_libs_message(data)
return
def _tex_comment(comment):
'''Prepends each line in string with the LaTeX comment key, '%'.
'''
return '% ' + str.replace(comment, '\n', '\n% ') + "\n"
def _print_tree(obj, indent=''):
'''Recursively prints the tree structure of the matplotlib object.
'''
print(indent, type(obj))
for child in obj.get_children():
_print_tree(child, indent + ' ')
return
def _get_color_definitions(data):
'''Returns the list of custom color definitions for the TikZ file.
'''
definitions = []
for name, rgb in data['custom colors'].items():
definitions.append('\\definecolor{%s}{rgb}{%.15g,%.15g,%.15g}'
% (name, rgb[0], rgb[1], rgb[2])
)
return definitions
#def _parse_text(text):
#'''Parses input text for LaTeX expressions and escaptes them if
#necessary.'''
#replace_list = ['_', '$', '\\', '%']
#return
def _draw_axes(data, obj):
'''Returns the Pgfplots code for an axis environment.
'''
content = []
# Are we dealing with an axis that hosts a colorbar?
# Skip then.
# TODO instead of testing here, rather blacklist the colorbar axis
# plots as soon as they have been found, e.g., by
# _find_associated_colorbar()
if _extract_colorbar(obj):
return
# instantiation
nsubplots = 1
subplot_index = 0
is_subplot = False
if isinstance(obj, mpl.axes.Subplot):
geom = obj.get_geometry()
nsubplots = geom[0]*geom[1]
if nsubplots > 1:
is_subplot = True
subplot_index = geom[2]
if subplot_index == 1:
content.append(
'\\begin{groupplot}[group style='
'{group size=%.d by %.d}]\n' % (geom[1], geom[0])
)
data['pgfplots libs'].add('groupplots')
axis_options = []
# check if axes need to be displayed at all
if not obj.axison:
axis_options.append('hide x axis')
axis_options.append('hide y axis')
# get plot title
title = obj.get_title()
if title:
axis_options.append('title={' + title + '}')
# get axes titles
xlabel = obj.get_xlabel()
if xlabel:
axis_options.append('xlabel={' + xlabel + '}')
ylabel = obj.get_ylabel()
if ylabel:
axis_options.append('ylabel={' + ylabel + '}')
# Axes limits.
# Sort the limits so make sure that the smaller of the two is actually
# *min.
xlim = sorted(list(obj.get_xlim()))
axis_options.append('xmin=%.15g' % xlim[0]
+ ', xmax=%.15g' % xlim[1]
)
ylim = sorted(list(obj.get_ylim()))
axis_options.append('ymin=%.15g' % ylim[0]
+ ', ymax=%.15g' % ylim[1]
)
# axes scaling
xscale = obj.get_xscale()
yscale = obj.get_yscale()
if xscale == 'log' and yscale == 'log':
env = 'loglogaxis'
elif xscale == 'log':
env = 'semilogxaxis'
elif yscale == 'log':
env = 'semilogyaxis'
else:
env = 'axis'
if not obj.get_axisbelow():
axis_options.append('axis on top')
# aspect ratio, plot width/height
aspect = obj.get_aspect()
if aspect == 'auto' or aspect == 'normal':
aspect_num = None # just take the given width/height values
elif aspect == 'equal':
aspect_num = 1.0
else:
try:
aspect_num = float(aspect)
except ValueError:
print('Aspect ratio not a number?!')
if data['fwidth'] and data['fheight']:
# width and height overwrite aspect ratio
axis_options.append('width='+data['fwidth'])
axis_options.append('height='+data['fheight'])
elif data['fwidth']:
# only data['fwidth'] given. calculate height by the aspect ratio
axis_options.append('width='+data['fwidth'])
if aspect_num:
alpha = aspect_num * (ylim[1]-ylim[0])/(xlim[1]-xlim[0])
if alpha != 1.0:
# Concatenate the literals, as data['fwidth'] could as well be
# a LaTeX length variable such as \figurewidth.
data['fheight'] = str(alpha) + '*' + data['fwidth']
else:
data['fheight'] = data['fwidth']
axis_options.append('height='+data['fheight'])
elif data['fheight']:
# only data['fheight'] given. calculate width by the aspect ratio
axis_options.append('height='+data['fheight'])
if aspect_num:
alpha = aspect_num * (ylim[1]-ylim[0])/(xlim[1]-xlim[0])
if alpha != 1.0:
# Concatenate the literals, as data['fheight'] could as well be
# a LaTeX length variable such as \figureheight.
data['fwidth'] = str(1.0/alpha) + '*' + data['fheight']
else:
data['fwidth'] = data['fheight']
axis_options.append('width='+data['fwidth'])
else:
if aspect_num:
print('Non-automatic aspect ratio demanded, but neither height '
'nor width of the plot are given. Discard aspect ratio.')
# get ticks
axis_options.extend(_get_ticks(data, 'x', obj.get_xticks(),
obj.get_xticklabels()))
axis_options.extend(_get_ticks(data, 'y', obj.get_yticks(),
obj.get_yticklabels()))
# Don't use get_{x,y}gridlines for gridlines; see discussion on
# <http://sourceforge.net/mailarchive/forum.php?thread_name=AANLkTima87pQkZmJhU2oNb8uxD2dfeV-Pa-uXWAFc2-v%40mail.gmail.com&forum_name=matplotlib-users>
# Coordinate of the lines are entirely meaningless, but styles (colors,...
# are respected.
if obj.xaxis._gridOnMajor:
axis_options.append('xmajorgrids')
elif obj.xaxis._gridOnMinor:
axis_options.append('xminorgrids')
if obj.yaxis._gridOnMajor:
axis_options.append('ymajorgrids')
elif obj.yaxis._gridOnMinor:
axis_options.append('yminorgrids')
# find color bar
colorbar = _find_associated_colorbar(obj)
if colorbar:
colorbar_styles = []
orientation = colorbar.orientation
limits = colorbar.get_clim()
if orientation == 'horizontal':
axis_options.append('colorbar horizontal')
colorbar_ticks = colorbar.ax.get_xticks()
axis_limits = colorbar.ax.get_xlim()
# In matplotlib, the colorbar color limits are determined by
# get_clim(), and the tick positions are as usual with respect to
# {x,y}lim. In Pgfplots, however, they are mixed together.
# Hence, scale the tick positions just like {x,y}lim are scaled
# to clim.
colorbar_ticks = (colorbar_ticks - axis_limits[0]) \
/ (axis_limits[1] - axis_limits[0]) \
* (limits[1] - limits[0]) \
+ limits[0]
# Getting the labels via get_* might not actually be suitable:
# they might not reflect the current state.
# http://sourceforge.net/mailarchive/message.php?msg_name=AANLkTikdNFwSAhMIlLjnd4Ai8-XIdJYGmrwq6PrHkbgi%40mail.gmail.com
colorbar_ticklabels = colorbar.ax.get_xticklabels()
colorbar_styles.extend(_get_ticks(data, 'x', colorbar_ticks,
colorbar_ticklabels))
elif orientation == 'vertical':
axis_options.append('colorbar')
colorbar_ticks = colorbar.ax.get_yticks()
axis_limits = colorbar.ax.get_ylim()
# In matplotlib, the colorbar color limits are determined by
# get_clim(), and the tick positions are as usual with respect to
# {x,y}lim. In Pgfplots, however, they are mixed together.
# Hence, scale the tick positions just like {x,y}lim are scaled
# to clim.
colorbar_ticks = (colorbar_ticks - axis_limits[0]) \
/ (axis_limits[1] - axis_limits[0]) \
* (limits[1] - limits[0]) \
+ limits[0]
# Getting the labels via get_* might not actually be suitable:
# they might not reflect the current state.
# http://sourceforge.net/mailarchive/message.php?msg_name=AANLkTikdNFwSAhMIlLjnd4Ai8-XIdJYGmrwq6PrHkbgi%40mail.gmail.com
colorbar_ticklabels = colorbar.ax.get_yticklabels()
colorbar_styles.extend(_get_ticks(data, 'y', colorbar_ticks,
colorbar_ticklabels))
else:
raise RuntimeError('Unknown color bar orientation ''%s''. Abort.' %
orientation)
mycolormap, is_custom_cmap = _mpl_cmap2pgf_cmap(colorbar.get_cmap())
if is_custom_cmap:
axis_options.append('colormap=' + mycolormap)
else:
axis_options.append('colormap/' + mycolormap)
axis_options.append('point meta min=%.15g' % limits[0])
axis_options.append('point meta max=%.15g' % limits[1])
if colorbar_styles:
axis_options.append('colorbar style={%s}'
% ','.join(colorbar_styles)
)
# actually print the thing
if is_subplot:
content.append('\\nextgroupplot')
else:
content.append('\\begin{%s}' % env)
# Run through the children objects, gather the content, and give them the
# opportunity to contribute to data['extra axis options'].
data, children_content = _handle_children(data, obj)
if data['extra axis options']:
axis_options.extend(data['extra axis options'])
if axis_options:
options = ',\n'.join(axis_options)
content.append('[\n' + options + '\n]\n')
content.extend(children_content)
# anchors
if hasattr(obj, "_matplotlib2tikz_anchors"):
try:
for coord, anchor_name in obj._matplotlib2tikz_anchors:
content.append('\\node (%s) at (axis cs:%e,%e) {};\n'
% (anchor_name, coord[0], coord[1])
)
except:
print('Axes attribute _matplotlib2tikz_anchors wrongly set:'
"Expected a list of ((x,y), anchor_name), got '%s'"
% str(obj._matplotlib2tikz_anchors)
)
if not is_subplot:
content.append('\\end{%s}\n\n' % env)
elif is_subplot and nsubplots == subplot_index:
content.append('\\end{groupplot}\n\n')
return data, content
def _get_ticks(data, xy, ticks, ticklabels):
'''
Gets a {'x','y'}, a number of ticks and ticks labels, and returns the
necessary axis options for the given configuration.
'''
axis_options = []
pgfplots_ticks = []
pgfplots_ticklabels = []
is_label_necessary = False
for (tick, ticklabel) in zip(ticks, ticklabels):
pgfplots_ticks.append(tick)
# store the label anyway
label = ticklabel.get_text()
pgfplots_ticklabels.append(label)
# Check if the label is necessary.
# If *one* of the labels is, then all of them must
# appear in the TikZ plot.
is_label_necessary = (label and label != str(tick))
# TODO This seems not quite to be the test whether labels are
# necessary.
# Leave the ticks to Pgfplots if not in STRICT mode and if there are no
# explicit labels.
if data['strict'] or is_label_necessary:
if pgfplots_ticks:
axis_options.append('%stick={%s}'
% (xy,
','.join(['%.15g' % el for el in pgfplots_ticks]))
)
else:
axis_options.append('%stick=\\empty' % xy)
if is_label_necessary:
axis_options.append('%sticklabels={%s}'
% (xy, ','.join(pgfplots_ticklabels))
)
return axis_options
def _mpl_cmap2pgf_cmap(cmap):
'''Converts a color map as given in matplotlib to a color map as
represented in Pgfplots.
'''
if not isinstance(cmap, mpl.colors.LinearSegmentedColormap):
print('Don''t know how to handle color map. Using ''blackwhite''.')
is_custom_colormap = False
return ('blackwhite', is_custom_colormap)
if cmap.is_gray():
is_custom_colormap = False
return ('blackwhite', is_custom_colormap)
# For an explanation of what _segmentdata contains, see
# http://matplotlib.sourceforge.net/examples/pylab_examples/custom_cmap.html
# A key sentence:
# If there are discontinuities, then it is a little more complicated.
# Label the 3 elements in each row in the cdict entry for a given color as
# (x, y0, y1). Then for values of x between x[i] and x[i+1] the color
# value is interpolated between y1[i] and y0[i+1].
segdata = cmap._segmentdata
red = segdata['red']
green = segdata['green']
blue = segdata['blue']
# Loop over the data, stop at each spot where the linear interpolations is
# interrupted, and set a color mark there.
#
# Set initial color.
k_red = 0
k_green = 0
k_blue = 0
x = 0.0
colors = []
X = []
while True:
# find next x
x = min(red[k_red][0], green[k_green][0], blue[k_blue][0])
if red[k_red][0] == x:
red_comp = red[k_red][1]
k_red += 1
else:
red_comp = _linear_interpolation(x,
(red[k_red-1][0], red[k_red][0]),
(red[k_red-1][2], red[k_red][1])
)
if green[k_green][0] == x:
green_comp = green[k_green][1]
k_green += 1
else:
green_comp = _linear_interpolation(x,
(green[k_green-1][0],
green[k_green][0]),
(green[k_green-1][2],
green[k_green][1])
)
if blue[k_blue][0] == x:
blue_comp = blue[k_blue][1]
k_blue += 1
else:
blue_comp = _linear_interpolation(x,
(blue[k_blue-1][0],
blue[k_blue][0]),
(blue[k_blue-1][2],
blue[k_blue][1])
)
X.append(x)
colors.append((red_comp, green_comp, blue_comp))
if x >= 1.0:
break
# The Pgfplots color map has an actual physical scale, like (0cm,10cm), and
# the points where the colors change is also given in those units. As of
# now (2010-05-06) it is crucial for Pgfplots that the difference between
# two successive points is an integer multiple of a given unity (parameter
# to the colormap; e.g., 1cm). At the same time, TeX suffers from
# significant round-off errors, so make sure that this unit is not too
# small such that the round- off errors don't play much of a role. A unit
# of 1pt, e.g., does most often not work.
unit = 'pt'
# Scale to integer
X = _scale_to_int(np.array(X))
color_changes = []
for (k, x) in enumerate(X):
color_changes.append('rgb(%d%s)=(%.15g,%.15g,%.15g)'
% ((x, unit) + colors[k])
)
colormap_string = '{mymap}{[1%s] %s}' % \
(unit, '; '.join(color_changes))
is_custom_colormap = True
return (colormap_string, is_custom_colormap)
def _scale_to_int(X):
'''
Scales the array X such that it contains only integers.
'''
X = X / _gcd_array(X)
return [int(entry) for entry in X]
def _gcd_array(X):
'''
Return the largest real value h such that all elements in x are integer
multiples of h.
'''
greatest_common_divisor = 0.0
for x in X:
greatest_common_divisor = _gcd(greatest_common_divisor, x)
return greatest_common_divisor
def _gcd(a, b):
'''Euclidean algorithm for calculating the GCD of two numbers a, b.
This algoritm also works for real numbers:
Find the greatest number h such that a and b are integer multiples of h.
'''
# Keep the tolerance somewhat significantly above machine precision as
# otherwise round-off errors will be accounted for, returning 1.0e-10
# instead of 1.0 for the values
# [1.0, 2.0000000001, 3.0, 4.0].
while a > 1.0e-5:
a, b = b % a, a
return b
def _linear_interpolation(x, X, Y):
'''Given two data points [X,Y], linearly interpolate those at x.
'''
return (Y[1]*(x-X[0]) + Y[0]*(X[1]-x)) / (X[1]-X[0])
def _transform_to_data_coordinates(obj, xdata, ydata):
'''Transform to data coordinates
The coordinates might not be in data coordinates, but could be partly in
axes coordinates. For example, the matplotlib command
axes.axvline(2)
will have the y coordinates set to 0 and 1, not to the limits. Therefore, a
two stage transform is to be applied, first transforming to display
coordinates, then from display to data. In case of problems
(non-invertible, or whatever), print a warning and continue anyways.
'''
try:
import matplotlib.transforms
points = zip(xdata, ydata)
transform = matplotlib.transforms.composite_transform_factory(
obj.get_transform(),
obj.get_axes().transData.inverted()
)
points_data = transform.transform(points)
xdata, ydata = zip(*points_data)
except:
print("Problem during transformation, continuing with original data")
return (xdata, ydata)
TIKZ_LINEWIDTHS = {0.1: 'ultra thin',
0.2: 'very thin',
0.4: 'thin',
0.6: 'semithick',
0.8: 'thick',
1.2: 'very thick',
1.6: 'ultra thick'
}
def _draw_line2d(data, obj):
'''Returns the Pgfplots code for an Line2D environment.
'''
content = []
addplot_options = []
# get the linewidth (in pt)
line_width = _mpl_linewidth2pgfp_linewidth(data,obj.get_linewidth())
if line_width:
addplot_options.append(line_width)
# get line color
color = obj.get_color()
data, line_xcolor, _ = _mpl_color2xcolor(data, color)
addplot_options.append(line_xcolor)
alpha = obj.get_alpha()
if alpha is not None:
addplot_options.append('opacity=%r' % alpha)
show_line, linestyle = _mpl_linestyle2pgfp_linestyle(obj.get_linestyle())
if show_line and linestyle:
addplot_options.append(linestyle)
marker_face_color = obj.get_markerfacecolor()
marker_edge_color = obj.get_markeredgecolor()
data, marker, extra_mark_options = \
_mpl_marker2pgfp_marker(data, obj.get_marker(), marker_face_color is not None)
if marker:
addplot_options.append('mark=' + marker)
mark_size = obj.get_markersize()
if mark_size:
# setting half size because pgfplots counts the radius/half-width
pgf_size = int(mark_size/2)
# make sure we didn't round off to zero by accident
if pgf_size == 0 and mark_size != 0:
pgf_size = 1
addplot_options.append('mark size=%d' % pgf_size)
mark_options = []
if extra_mark_options:
mark_options.append(extra_mark_options)
if marker_face_color is not None:
data, face_xcolor, _ = _mpl_color2xcolor(data, marker_face_color)
else:
face_xcolor = line_xcolor
if marker_edge_color is not None:
data, draw_xcolor, _ = _mpl_color2xcolor(data, marker_edge_color)
else:
draw_xcolor = line_xcolor
if face_xcolor != line_xcolor:
mark_options.append('fill=' + face_xcolor)
if draw_xcolor != line_xcolor and draw_xcolor != face_xcolor:
mark_options.append('draw=' + draw_xcolor)
if mark_options:
addplot_options.append('mark options={%s}' % ','.join(mark_options)
)
if marker and not show_line:
addplot_options.append('only marks')
# process options
content.append('\\addplot ')
if addplot_options:
options = ', '.join(addplot_options)
content.append('[' + options + ']\n')
content.append('coordinates {\n')
# print the hard numerical data
xdata, ydata = _transform_to_data_coordinates(obj, *obj.get_data())
try:
has_mask = ydata.mask.any()
except AttributeError:
has_mask = 0
if has_mask:
# matplotlib jumps at masked images, while Pgfplots by default
# interpolates. Hence, if we have a masked plot, make sure that
# Pgfplots jump as well.
data['extra axis options'].add('unbounded coords=jump')
for (x, y, is_masked) in zip(xdata, ydata, ydata.mask):
if is_masked:
content.append('(%.15g,nan) ' % x)
else:
content.append('(%.15g,%.15g) ' % (x, y))
else:
for (x, y) in zip(xdata, ydata):
content.append('(%.15g,%.15g)\n' % (x, y))
content.append('\n};\n')
return data, content
# for matplotlib markers, see
# http://matplotlib.sourceforge.net/api/artist_api.html#matplotlib.lines.Line2D.set_marker
MP_MARKER2PGF_MARKER = {'.': '*', # point
'o': 'o', # circle
'+': '+', # plus
'x': 'x', # x
'None': None,
' ': None,
'': None
}
# the following markers are only available with PGF's plotmarks library
MP_MARKER2PLOTMARKS = {'v': ('triangle', 'rotate=180'), # triangle down
'1': ('triangle', 'rotate=180'),
'^': ('triangle', None), # triangle up
'2': ('triangle', None),
'<': ('triangle', 'rotate=270'), # triangle left
'3': ('triangle', 'rotate=270'),
'>': ('triangle', 'rotate=90'), # triangle right
'4': ('triangle', 'rotate=90'),
's': ('square', None),
'p': ('pentagon', None),
'*': ('asterisk', None),
'h': ('star', None), # hexagon 1
'H': ('star', None), # hexagon 2
'd': ('diamond', None), # diamond
'D': ('diamond', None), # thin diamond
'|': ('|', None), # vertical line
'_': ('_', None) # horizontal line
}
def _mpl_marker2pgfp_marker(data, mpl_marker, is_marker_face_color):
'''Translates a marker style of matplotlib to the corresponding style
in Pgfplots.
'''
# try default list
try:
pgfplots_marker = MP_MARKER2PGF_MARKER[mpl_marker]
if is_marker_face_color and pgfplots_marker == 'o':
pgfplots_marker = '*'
data['pgfplots libs'].add('plotmarks')
marker_options = None
return (data, pgfplots_marker, marker_options)
except KeyError:
pass
# try plotmarks list
try:
data['pgfplots libs'].add('plotmarks')
pgfplots_marker, marker_options = MP_MARKER2PLOTMARKS[mpl_marker]
if is_marker_face_color and not pgfplots_marker in ['|', '_']:
pgfplots_marker += '*'
return (data, pgfplots_marker, marker_options)
except KeyError:
pass
if mpl_marker == ',': # pixel
print('Unsupported marker ''%r''.' % mpl_marker)
else:
print('Unknown marker ''%r''.' % mpl_marker)
return (data, None, None)
MPLLINESTYLE_2_PGFPLOTSLINESTYLE = {'None': None,
'-': None,
':': 'dotted',
'--': 'dashed',
'-.': 'dash pattern=on 1pt off 3pt '
'on 3pt off 3pt'
}
def _mpl_linewidth2pgfp_linewidth(data,line_width):
if data['strict']:
# Takes the matplotlib linewidths, and just translate them
# into Pgfplots.
try:
return TIKZ_LINEWIDTHS[ line_width ]
except KeyError:
# explicit line width
return 'line width=%spt' % line_width
else:
# The following is an alternative approach to line widths.
# The default line width in matplotlib is 1.0pt, in Pgfplots 0.4pt
# ('thin').
# Match the two defaults, and scale for the rest.
scaled_line_width = line_width / 1.0 # scale by default line width
if scaled_line_width == 0.25:
return 'ultra thin'
elif scaled_line_width == 0.5:
return 'very thin'
elif scaled_line_width == 1.0:
return ''# Pgfplots default line width, 'thin'
elif scaled_line_width == 1.5:
return 'semithick'
elif scaled_line_width == 2:
return 'thick'
elif scaled_line_width == 3:
return 'very thick'
elif scaled_line_width == 4:
return 'ultra thick'
else:
# explicit line width
return 'line width=%rpt' % (0.4*line_width)
def _mpl_linestyle2pgfp_linestyle(line_style):
'''Translates a line style of matplotlib to the corresponding style
in Pgfplots.
'''
if isinstance(line_style,tuple):
offset, spacing = line_style
if offset is None and spacing is None:
return True, None # solid line
elif spacing == (1.0, 3.0):
return True, 'dotted'
elif spacing == (6.0, 6.0):
return True, 'dashed'
else:
pattern = []
for s in spacing:
if len(pattern)%2:
pattern.append('off %dpt' % (s,))
else:
pattern.append('on %dpt' % (s,))
line_style = 'dash pattern=' + ' '.join(pattern)
return True, line_style
else:
show_line = (line_style != 'None')
try:
style = MPLLINESTYLE_2_PGFPLOTSLINESTYLE[line_style]
except KeyError:
print('Unknown line style ''%r''. Using default.' % line_style)
style = None
return show_line, style
def _draw_image(data, obj):
'''Returns the Pgfplots code for an image environment.
'''
content = []
if not 'img number' in data.keys():
data['img number'] = 0
# Make sure not to overwrite anything.
file_exists = True
while file_exists:
data['img number'] = data['img number'] + 1
filename = os.path.join(data['output dir'],
'img' + str(data['img number']) + '.png'
)
file_exists = os.path.isfile(filename)
# store the image as in a file
img_array = obj.get_array()
dims = img_array.shape
if len(dims) == 2: # the values are given as one real number: look at cmap
clims = obj.get_clim()
mpl.pyplot.imsave(fname=filename,
arr=img_array,
cmap=obj.get_cmap(),
vmin=clims[0],
vmax=clims[1]
)
elif len(dims) == 3 and dims[2] in [3, 4]:
# RGB (+alpha) information at each point
# convert to PIL image (after upside-down flip)
import Image
image = Image.fromarray(np.flipud(img_array))
image.save(filename)
else:
raise RuntimeError('Unable to store image array.')
# write the corresponding information to the TikZ file
extent = obj.get_extent()
# the format specification will only accept tuples, not lists
if isinstance(extent, list): # convert to () list
extent = tuple(extent)
if data['rel data path']:
rel_filepath = os.path.join(data['rel data path'],
os.path.basename(filename)
)
else:
rel_filepath = os.path.basename(filename)
# Explicitly use \pgfimage as includegrapics command, as the default
# \includegraphics fails unexpectedly in some cases
content.append('\\addplot graphics [includegraphics cmd=\pgfimage,'
'xmin=%.15g, xmax=%.15g, '
'ymin=%.15g, ymax=%.15g] {%s};\n'
% (extent + (rel_filepath,))
)
data, cont = _handle_children(data, obj)
content.extend(cont)
return data, content
def _draw_quadmesh( data, obj, dpi=50 ):
'''Returns the Pgfplots code for an quadmesh environment.