##// END OF EJS Templates
Document _repr_mimebundle_...
Matthias Bussonnier -
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@@ -960,7 +960,7 b' class MimeBundleFormatter(BaseFormatter):'
960 960 if method is not None:
961 961 d = {}
962 962 d['include'] = include
963 d['exclude'] = include
963 d['exclude'] = exclude
964 964 return method(**d)
965 965 return None
966 966 else:
@@ -116,8 +116,6 b' def test_for_type():'
116 116 def test_for_type_string():
117 117 f = PlainTextFormatter()
118 118
119 mod = C.__module__
120
121 119 type_str = '%s.%s' % (C.__module__, 'C')
122 120
123 121 # initial return, None
@@ -166,7 +164,6 b' def test_lookup_by_type():'
166 164 f = PlainTextFormatter()
167 165 f.for_type(C, foo_printer)
168 166 nt.assert_is(f.lookup_by_type(C), foo_printer)
169 type_str = '%s.%s' % (C.__module__, 'C')
170 167 with nt.assert_raises(KeyError):
171 168 f.lookup_by_type(A)
172 169
@@ -475,6 +472,31 b' def test_repr_mime():'
475 472 nt.assert_equal(d['image/png'], 'i-overwrite', '_repr_mimebundle_ take precedence')
476 473
477 474
475
476 def test_pass_correct_include_exclude():
477 class Tester(object):
478
479 def __init__(self, include=None, exclude=None):
480 self.include = include
481 self.exclude = exclude
482
483 def _repr_mimebundle_(self, include, exclude, **kwargs):
484 if include and (include != self.include):
485 raise ValueError('include got modified: display() may be broken.')
486 if exclude and (exclude != self.exclude):
487 raise ValueError('exclude got modified: display() may be broken.')
488
489 return None
490
491 include = {'a', 'b', 'c'}
492 exclude = {'c', 'e' , 'f'}
493
494 f = get_ipython().display_formatter
495 f.format(Tester(include=include, exclude=exclude), include=include, exclude=exclude)
496 f.format(Tester(exclude=exclude), exclude=exclude)
497 f.format(Tester(include=include), include=include)
498
499
478 500 def test_repr_mime_meta():
479 501 class HasReprMimeMeta(object):
480 502 def _repr_mimebundle_(self, include=None, exclude=None):
@@ -499,5 +521,3 b' def test_repr_mime_meta():'
499 521 'height': 10,
500 522 }
501 523 })
502
503
This diff has been collapsed as it changes many lines, (1058 lines changed) Show them Hide them
@@ -47,7 +47,7 b''
47 47 "cell_type": "code",
48 48 "execution_count": 1,
49 49 "metadata": {
50 "collapsed": false
50 "collapsed": true
51 51 },
52 52 "outputs": [],
53 53 "source": [
@@ -67,13 +67,13 b''
67 67 "cell_type": "code",
68 68 "execution_count": 2,
69 69 "metadata": {
70 "collapsed": false
70 "collapsed": true
71 71 },
72 72 "outputs": [],
73 73 "source": [
74 "%matplotlib inline\n",
75 74 "import numpy as np\n",
76 "import matplotlib.pyplot as plt"
75 "import matplotlib.pyplot as plt\n",
76 "plt.ion()"
77 77 ]
78 78 },
79 79 {
@@ -94,7 +94,8 b''
94 94 "* `_repr_jpeg_`: return raw JPEG data\n",
95 95 "* `_repr_png_`: return raw PNG data\n",
96 96 "* `_repr_svg_`: return raw SVG data as a string\n",
97 "* `_repr_latex_`: return LaTeX commands in a string surrounded by \"$\"."
97 "* `_repr_latex_`: return LaTeX commands in a string surrounded by \"$\".\n",
98 "* `_repr_mimebundle_`: return a full mimebundle containing the mapping from all mimetypes to data "
98 99 ]
99 100 },
100 101 {
@@ -108,7 +109,7 b''
108 109 "cell_type": "code",
109 110 "execution_count": 3,
110 111 "metadata": {
111 "collapsed": false
112 "collapsed": true
112 113 },
113 114 "outputs": [],
114 115 "source": [
@@ -157,141 +158,16 b''
157 158 {
158 159 "cell_type": "code",
159 160 "execution_count": 4,
160 "metadata": {
161 "collapsed": false
162 },
161 "metadata": {},
163 162 "outputs": [
164 163 {
165 164 "data": {
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165 "image/png": 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290 166 "text/latex": [
291 167 "$\\mathcal{N}(\\mu=2, \\sigma=1),\\ N=1000$"
292 168 ],
293 169 "text/plain": [
294 "<__main__.Gaussian at 0x10665a4e0>"
170 "<__main__.Gaussian at 0x116fe76d8>"
295 171 ]
296 172 },
297 173 "execution_count": 4,
@@ -314,141 +190,16 b''
314 190 {
315 191 "cell_type": "code",
316 192 "execution_count": 5,
317 "metadata": {
318 "collapsed": false
319 },
193 "metadata": {},
320 194 "outputs": [
321 195 {
322 196 "data": {
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197 "image/png": 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447 198 "text/latex": [
448 199 "$\\mathcal{N}(\\mu=2, \\sigma=1),\\ N=1000$"
449 200 ],
450 201 "text/plain": [
451 "<__main__.Gaussian at 0x10665a4e0>"
202 "<__main__.Gaussian at 0x116fe76d8>"
452 203 ]
453 204 },
454 205 "metadata": {},
@@ -469,136 +220,11 b''
469 220 {
470 221 "cell_type": "code",
471 222 "execution_count": 6,
472 "metadata": {
473 "collapsed": false
474 },
223 "metadata": {},
475 224 "outputs": [
476 225 {
477 226 "data": {
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601 ]
227 "image/png": 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602 228 },
603 229 "metadata": {},
604 230 "output_type": "display_data"
@@ -627,145 +253,16 b''
627 253 {
628 254 "cell_type": "code",
629 255 "execution_count": 7,
630 "metadata": {
631 "collapsed": false
632 },
256 "metadata": {},
633 257 "outputs": [
634 258 {
635 259 "data": {
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260 "image/png": 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764 261 "text/latex": [
765 262 "$\\mathcal{N}(\\mu=0, \\sigma=2),\\ N=2000$"
766 263 ],
767 264 "text/plain": [
768 "<__main__.Gaussian at 0x106ab8c18>"
265 "<__main__.Gaussian at 0x116fe7668>"
769 266 ]
770 267 },
771 268 "execution_count": 7,
@@ -788,270 +285,18 b''
788 285 {
789 286 "cell_type": "code",
790 287 "execution_count": 8,
791 "metadata": {
792 "collapsed": false
793 },
288 "metadata": {},
794 289 "outputs": [
795 290 {
796 291 "data": {
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292 "image/png": 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1054 ]
299 "image/png": 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GmQgkqXEmAklqnIlAkhq3btQVkxwCfAB4MvAjYEtVvSfJvsCHgY3AncAvV9UD44eqlbbx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\nLnYAAAAASUVORK5CYII=\n"
1055 300 },
1056 301 "metadata": {},
1057 302 "output_type": "display_data"
@@ -1093,9 +338,7 b''
1093 338 {
1094 339 "cell_type": "code",
1095 340 "execution_count": 9,
1096 "metadata": {
1097 "collapsed": false
1098 },
341 "metadata": {},
1099 342 "outputs": [
1100 343 {
1101 344 "data": {
@@ -1124,7 +367,7 b''
1124 367 "cell_type": "code",
1125 368 "execution_count": 10,
1126 369 "metadata": {
1127 "collapsed": false
370 "collapsed": true
1128 371 },
1129 372 "outputs": [],
1130 373 "source": [
@@ -1158,9 +401,7 b''
1158 401 {
1159 402 "cell_type": "code",
1160 403 "execution_count": 11,
1161 "metadata": {
1162 "collapsed": false
1163 },
404 "metadata": {},
1164 405 "outputs": [
1165 406 {
1166 407 "data": {
@@ -1187,9 +428,7 b''
1187 428 {
1188 429 "cell_type": "code",
1189 430 "execution_count": 12,
1190 "metadata": {
1191 "collapsed": false
1192 },
431 "metadata": {},
1193 432 "outputs": [
1194 433 {
1195 434 "data": {
@@ -1220,24 +459,22 b''
1220 459 {
1221 460 "cell_type": "code",
1222 461 "execution_count": 13,
1223 "metadata": {
1224 "collapsed": false
1225 },
462 "metadata": {},
1226 463 "outputs": [
1227 464 {
1228 465 "name": "stdout",
1229 466 "output_type": "stream",
1230 467 "text": [
468 " text/plain : PlainTextFormatter\n",
469 " text/html : HTMLFormatter\n",
470 " text/markdown : MarkdownFormatter\n",
471 " image/svg+xml : SVGFormatter\n",
1231 472 " image/png : PNGFormatter\n",
1232 473 " application/pdf : PDFFormatter\n",
1233 " text/html : HTMLFormatter\n",
1234 474 " image/jpeg : JPEGFormatter\n",
1235 " text/plain : PlainTextFormatter\n",
1236 " text/markdown : MarkdownFormatter\n",
1237 " application/json : JSONFormatter\n",
1238 " application/javascript : JavascriptFormatter\n",
1239 475 " text/latex : LatexFormatter\n",
1240 " image/svg+xml : SVGFormatter\n"
476 " application/json : JSONFormatter\n",
477 " application/javascript : JavascriptFormatter\n"
1241 478 ]
1242 479 }
1243 480 ],
@@ -1258,7 +495,7 b''
1258 495 "cell_type": "code",
1259 496 "execution_count": 14,
1260 497 "metadata": {
1261 "collapsed": false
498 "collapsed": true
1262 499 },
1263 500 "outputs": [],
1264 501 "source": [
@@ -1276,9 +513,7 b''
1276 513 {
1277 514 "cell_type": "code",
1278 515 "execution_count": 15,
1279 "metadata": {
1280 "collapsed": false
1281 },
516 "metadata": {},
1282 517 "outputs": [
1283 518 {
1284 519 "name": "stdout",
@@ -1320,9 +555,7 b''
1320 555 {
1321 556 "cell_type": "code",
1322 557 "execution_count": 16,
1323 "metadata": {
1324 "collapsed": false
1325 },
558 "metadata": {},
1326 559 "outputs": [
1327 560 {
1328 561 "name": "stdout",
@@ -1376,7 +609,7 b''
1376 609 "cell_type": "code",
1377 610 "execution_count": 17,
1378 611 "metadata": {
1379 "collapsed": false
612 "collapsed": true
1380 613 },
1381 614 "outputs": [],
1382 615 "source": [
@@ -1394,9 +627,7 b''
1394 627 {
1395 628 "cell_type": "code",
1396 629 "execution_count": 18,
1397 "metadata": {
1398 "collapsed": false
1399 },
630 "metadata": {},
1400 631 "outputs": [
1401 632 {
1402 633 "data": {
@@ -1419,9 +650,7 b''
1419 650 {
1420 651 "cell_type": "code",
1421 652 "execution_count": 19,
1422 "metadata": {
1423 "collapsed": false
1424 },
653 "metadata": {},
1425 654 "outputs": [
1426 655 {
1427 656 "data": {
@@ -1446,6 +675,199 b''
1446 675 "cell_type": "markdown",
1447 676 "metadata": {},
1448 677 "source": [
678 "## Custom Mimetypes with `_repr_mimebundle_`\n",
679 "\n",
680 "Available on IPython 5.4+ and 6.1+.\n",
681 "\n",
682 "For objects needing full control over the `repr` protocol may decide to implement the `_repr_mimebundle_(include, exclude)` method.\n",
683 "Unlike the other `_repr_*_` methods must return many representation of the object in a mapping object which keys are _mimetypes_ and value are associated data. The `_repr_mimebundle_()` method, may also return a second mapping from _mimetypes_ to metadata. \n",
684 "\n",
685 "Example:"
686 ]
687 },
688 {
689 "cell_type": "code",
690 "execution_count": 20,
691 "metadata": {
692 "collapsed": true
693 },
694 "outputs": [],
695 "source": [
696 "class Gaussian(object):\n",
697 " \"\"\"A simple object holding data sampled from a Gaussian distribution.\n",
698 " \"\"\"\n",
699 " def __init__(self, mean=0.0, std=1, size=1000):\n",
700 " self.data = np.random.normal(mean, std, size)\n",
701 " self.mean = mean\n",
702 " self.std = std\n",
703 " self.size = size\n",
704 " # For caching plots that may be expensive to compute\n",
705 " self._png_data = None\n",
706 " \n",
707 " def _figure_data(self, format):\n",
708 " fig, ax = plt.subplots()\n",
709 " ax.hist(self.data, bins=50)\n",
710 " ax.set_xlim(-10.0,10.0)\n",
711 " data = print_figure(fig, format)\n",
712 " # We MUST close the figure, otherwise IPython's display machinery\n",
713 " # will pick it up and send it as output, resulting in a double display\n",
714 " plt.close(fig)\n",
715 " return data\n",
716 " \n",
717 " def _compute_mathml(self):\n",
718 " return \"\"\"\n",
719 " <math xmlns=\"http://www.w3.org/1998/Math/MathML\">\n",
720 " <mrow class=\"MJX-TeXAtom-ORD\">\n",
721 " <mi class=\"MJX-tex-caligraphic\" mathvariant=\"script\">N</mi>\n",
722 " </mrow>\n",
723 " <mo stretchy=\"false\">(</mo>\n",
724 " <mi>&#x03BC;<!-- ΞΌ --></mi>\n",
725 " <mo>=</mo>\n",
726 " <mn>{mu}</mn>\n",
727 " <mo>,</mo>\n",
728 " <mi>&#x03C3;<!-- Οƒ --></mi>\n",
729 " <mo>=</mo>\n",
730 " <mn>{sigma}</mn>\n",
731 " <mo stretchy=\"false\">)</mo>\n",
732 " <mo>,</mo>\n",
733 " <mtext>&#xA0;</mtext>\n",
734 " <mi>N</mi>\n",
735 " <mo>=</mo>\n",
736 " <mn>{N}</mn>\n",
737 " </math>\n",
738 " \"\"\".format(N=self.size, mu=self.mean, sigma=self.std)\n",
739 " \n",
740 " def _repr_mimebundle_(self, include, exclude, **kwargs):\n",
741 " \"\"\"\n",
742 " repr_mimebundle shoudl accept include, exclude and **kwargs\n",
743 " \"\"\"\n",
744 " if self._png_data is None:\n",
745 " self._png_data = self._figure_data('png')\n",
746 " math = r'$\\mathcal{N}(\\mu=%.2g, \\sigma=%.2g),\\ N=%d$' % (self.mean,\n",
747 " self.std, self.size)\n",
748 " data = {'image/png':self._png_data,\n",
749 " 'text/latex':math,\n",
750 " 'application/mathml+xml': self._compute_mathml()\n",
751 " }\n",
752 " if include:\n",
753 " data = {k:v for (k,v) in data.items() if k in include}\n",
754 " if exclude:\n",
755 " data = {k:v for (k,v) in data.items() if k not in exclude}\n",
756 " return data"
757 ]
758 },
759 {
760 "cell_type": "code",
761 "execution_count": 21,
762 "metadata": {},
763 "outputs": [
764 {
765 "data": {
766 "application/mathml+xml": "\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\">\n <mrow class=\"MJX-TeXAtom-ORD\">\n <mi class=\"MJX-tex-caligraphic\" mathvariant=\"script\">N</mi>\n </mrow>\n <mo stretchy=\"false\">(</mo>\n <mi>&#x03BC;<!-- ΞΌ --></mi>\n <mo>=</mo>\n <mn>0.0</mn>\n <mo>,</mo>\n <mi>&#x03C3;<!-- Οƒ --></mi>\n <mo>=</mo>\n <mn>1</mn>\n <mo stretchy=\"false\">)</mo>\n <mo>,</mo>\n <mtext>&#xA0;</mtext>\n <mi>N</mi>\n <mo>=</mo>\n <mn>1000</mn>\n </math>\n ",
767 "image/png": 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768 "text/latex": [
769 "$\\mathcal{N}(\\mu=0, \\sigma=1),\\ N=1000$"
770 ],
771 "text/plain": [
772 "<__main__.Gaussian at 0x11a614e80>"
773 ]
774 },
775 "metadata": {},
776 "output_type": "display_data"
777 }
778 ],
779 "source": [
780 "# that is deffinitively wrong as it shoudl show the PNG. \n",
781 "display(Gaussian())"
782 ]
783 },
784 {
785 "cell_type": "markdown",
786 "metadata": {},
787 "source": [
788 "In the above example, the 3 mimetypes are embeded in the notebook document this allowing custom extensions and converters to display the representation(s) of their choice.\n",
789 "\n",
790 "For example, converting this noetebook to _epub_ may decide to use the MathML representation as most ebook reader cannot run mathjax (unlike browsers). \n",
791 "\n",
792 "\n",
793 "### Implementation guidelines\n",
794 "\n",
795 "The `_repr_mimebundle_` methods is also given two keywords parameters : `include` and `exclude`. Each can be a containers (e.g.:`list`, `set` ...) of mimetypes to return or `None`, This allows implementation to avoid computing potentially unnecessary and expensive mimetypes representations. \n",
796 "\n",
797 "When `include` is non-empty (empty `list` or None), `_repr_mimebundle_` may decide to returns only the mimetypes in include.\n",
798 "When `exclude` is non-empty, `_repr_mimebundle_` may decide to not return any mimetype in exclude. \n",
799 "If both `include` and `exclude` and overlap, mimetypes present in exclude may not be returned. \n",
800 "\n",
801 "If implementations decide to ignore the `include` and `exclude` logic and always returns a full mimebundles, the IPython kernel will take care of removing non-desired representations.\n",
802 "\n",
803 "The `_repr_mimebundle_` method should accept arbitrary keyword arguments for future compatiility.\n"
804 ]
805 },
806 {
807 "cell_type": "code",
808 "execution_count": 22,
809 "metadata": {},
810 "outputs": [
811 {
812 "data": {
813 "text/latex": [
814 "$\\mathcal{N}(\\mu=0, \\sigma=1),\\ N=1000$"
815 ]
816 },
817 "metadata": {},
818 "output_type": "display_data"
819 }
820 ],
821 "source": [
822 "display(Gaussian(), include={'text/latex'}) # only show latex"
823 ]
824 },
825 {
826 "cell_type": "code",
827 "execution_count": 23,
828 "metadata": {},
829 "outputs": [
830 {
831 "data": {
832 "application/mathml+xml": "\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\">\n <mrow class=\"MJX-TeXAtom-ORD\">\n <mi class=\"MJX-tex-caligraphic\" mathvariant=\"script\">N</mi>\n </mrow>\n <mo stretchy=\"false\">(</mo>\n <mi>&#x03BC;<!-- ΞΌ --></mi>\n <mo>=</mo>\n <mn>0.0</mn>\n <mo>,</mo>\n <mi>&#x03C3;<!-- Οƒ --></mi>\n <mo>=</mo>\n <mn>1</mn>\n <mo stretchy=\"false\">)</mo>\n <mo>,</mo>\n <mtext>&#xA0;</mtext>\n <mi>N</mi>\n <mo>=</mo>\n <mn>1000</mn>\n </math>\n ",
833 "text/latex": [
834 "$\\mathcal{N}(\\mu=0, \\sigma=1),\\ N=1000$"
835 ],
836 "text/plain": [
837 "<__main__.Gaussian at 0x116fe7550>"
838 ]
839 },
840 "metadata": {},
841 "output_type": "display_data"
842 }
843 ],
844 "source": [
845 "display(Gaussian(), exclude={'image/png'}) # exclude png"
846 ]
847 },
848 {
849 "cell_type": "code",
850 "execution_count": 24,
851 "metadata": {},
852 "outputs": [
853 {
854 "data": {
855 "text/plain": [
856 "<__main__.Gaussian at 0x11a8a0b38>"
857 ]
858 },
859 "metadata": {},
860 "output_type": "display_data"
861 }
862 ],
863 "source": [
864 "display(Gaussian(), include={'text/plain', 'image/png'}, exclude={'image/png'}) # keep only plain/text"
865 ]
866 },
867 {
868 "cell_type": "markdown",
869 "metadata": {},
870 "source": [
1449 871 "## More complex display with `_ipython_display_`"
1450 872 ]
1451 873 },
@@ -1462,9 +884,9 b''
1462 884 },
1463 885 {
1464 886 "cell_type": "code",
1465 "execution_count": 20,
887 "execution_count": 25,
1466 888 "metadata": {
1467 "collapsed": false
889 "collapsed": true
1468 890 },
1469 891 "outputs": [],
1470 892 "source": [
@@ -1494,15 +916,13 b''
1494 916 },
1495 917 {
1496 918 "cell_type": "code",
1497 "execution_count": 21,
1498 "metadata": {
1499 "collapsed": false
1500 },
919 "execution_count": 26,
920 "metadata": {},
1501 921 "outputs": [
1502 922 {
1503 923 "data": {
1504 924 "text/html": [
1505 "<div id=\"4ad544ff-a161-4493-ba2c-f99531e317bd\" style=\"height: 300px; width:80%;\"></div>"
925 "<div id=\"c6929609-3cb6-4443-9574-d9f71791a987\" style=\"height: 300px; width:80%;\"></div>"
1506 926 ]
1507 927 },
1508 928 "metadata": {},
@@ -1515,7 +935,7 b''
1515 935 " require([\"//cdnjs.cloudflare.com/ajax/libs/flot/0.8.2/jquery.flot.min.js\"], function() {\n",
1516 936 " var line = JSON.parse(\"[[0.0, 0.0], [0.20408163265306123, 0.20266793654820095], [0.40816326530612246, 0.39692414892492234], [0.6122448979591837, 0.5747060412161791], [0.8163265306122449, 0.7286347834693503], [1.0204081632653061, 0.8523215697196184], [1.2244897959183674, 0.9406327851124867], [1.4285714285714286, 0.9899030763721239], [1.6326530612244898, 0.9980874821347183], [1.836734693877551, 0.9648463089837632], [2.0408163265306123, 0.8915592304110037], [2.2448979591836737, 0.7812680235262639], [2.4489795918367347, 0.6385503202266021], [2.6530612244897958, 0.469329612777201], [2.857142857142857, 0.28062939951435684], [3.0612244897959187, 0.0802816748428135], [3.2653061224489797, -0.12339813736217871], [3.4693877551020407, -0.3219563150726187], [3.673469387755102, -0.5071517094845144], [3.8775510204081636, -0.6712977935519321], [4.081632653061225, -0.8075816909683364], [4.285714285714286, -0.9103469443107828], [4.4897959183673475, -0.9753282860670456], [4.6938775510204085, -0.9998286683840896], [4.8979591836734695, -0.9828312039256306], [5.1020408163265305, -0.9250413717382029], [5.3061224489795915, -0.8288577363730427], [5.510204081632653, -0.6982723955653996], [5.714285714285714, -0.5387052883861563], [5.918367346938775, -0.35677924089893803], [6.122448979591837, -0.16004508604325057], [6.326530612244898, 0.04333173336868346], [6.530612244897959, 0.2449100710119793], [6.73469387755102, 0.4363234264718193], [6.938775510204081, 0.6096271964908323], [7.142857142857143, 0.7576284153927202], [7.346938775510204, 0.8741842988197335], [7.551020408163265, 0.9544571997387519], [7.755102040816327, 0.9951153947776636], [7.959183673469388, 0.9944713672636168], [8.16326530612245, 0.9525518475314604], [8.36734693877551, 0.8710967034823207], [8.571428571428571, 0.7534867274396376], [8.775510204081632, 0.6046033165061543], [8.979591836734695, 0.43062587038273736], [9.183673469387756, 0.23877531564403087], [9.387755102040817, 0.03701440148506237], [9.591836734693878, -0.1662827938487564], [9.795918367346939, -0.3626784288265488], [10.0, -0.5440211108893699]]\");\n",
1517 937 " console.log(line);\n",
1518 " $.plot(\"#4ad544ff-a161-4493-ba2c-f99531e317bd\", [line]);\n",
938 " $.plot(\"#c6929609-3cb6-4443-9574-d9f71791a987\", [line]);\n",
1519 939 " });\n",
1520 940 " "
1521 941 ]
@@ -1548,9 +968,9 b''
1548 968 "name": "python",
1549 969 "nbconvert_exporter": "python",
1550 970 "pygments_lexer": "ipython3",
1551 "version": "3.4.2"
971 "version": "3.6.0"
1552 972 }
1553 973 },
1554 974 "nbformat": 4,
1555 "nbformat_minor": 0
975 "nbformat_minor": 1
1556 976 }
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