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removed references to h5py dependence
Cavendish McKay -
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1 {
1 {
2 "metadata": {
2 "metadata": {
3 "name": "octavemagic_extension"
3 "name": "octavemagic_extension"
4 },
4 },
5 "nbformat": 3,
5 "nbformat": 3,
6 "nbformat_minor": 0,
6 "nbformat_minor": 0,
7 "worksheets": [
7 "worksheets": [
8 {
8 {
9 "cells": [
9 "cells": [
10 {
10 {
11 "cell_type": "heading",
11 "cell_type": "heading",
12 "level": 1,
12 "level": 1,
13 "metadata": {},
13 "metadata": {},
14 "source": [
14 "source": [
15 "octavemagic: Octave inside IPython"
15 "octavemagic: Octave inside IPython"
16 ]
16 ]
17 },
17 },
18 {
18 {
19 "cell_type": "heading",
19 "cell_type": "heading",
20 "level": 2,
20 "level": 2,
21 "metadata": {},
21 "metadata": {},
22 "source": [
22 "source": [
23 "Installation"
23 "Installation"
24 ]
24 ]
25 },
25 },
26 {
26 {
27 "cell_type": "markdown",
27 "cell_type": "markdown",
28 "metadata": {},
28 "metadata": {},
29 "source": [
29 "source": [
30 "The `octavemagic` extension provides the ability to interact with Octave. It depends on the `oct2py` and `h5py` packages,\n",
30 "The `octavemagic` extension provides the ability to interact with Octave. It depends on the `oct2py` package,\n",
31 "which may be installed using `easy_install`.\n",
31 "which may be installed using `easy_install`.\n",
32 "\n",
32 "\n",
33 "To enable the extension, load it as follows:"
33 "To enable the extension, load it as follows:"
34 ]
34 ]
35 },
35 },
36 {
36 {
37 "cell_type": "code",
37 "cell_type": "code",
38 "collapsed": false,
38 "collapsed": false,
39 "input": [
39 "input": [
40 "%load_ext octavemagic"
40 "%load_ext octavemagic"
41 ],
41 ],
42 "language": "python",
42 "language": "python",
43 "metadata": {},
43 "metadata": {},
44 "outputs": [],
44 "outputs": [],
45 "prompt_number": 18
45 "prompt_number": 18
46 },
46 },
47 {
47 {
48 "cell_type": "heading",
48 "cell_type": "heading",
49 "level": 2,
49 "level": 2,
50 "metadata": {},
50 "metadata": {},
51 "source": [
51 "source": [
52 "Overview"
52 "Overview"
53 ]
53 ]
54 },
54 },
55 {
55 {
56 "cell_type": "markdown",
56 "cell_type": "markdown",
57 "metadata": {},
57 "metadata": {},
58 "source": [
58 "source": [
59 "Loading the extension enables three magic functions: `%octave`, `%octave_push`, and `%octave_pull`.\n",
59 "Loading the extension enables three magic functions: `%octave`, `%octave_push`, and `%octave_pull`.\n",
60 "\n",
60 "\n",
61 "The first is for executing one or more lines of Octave, while the latter allow moving variables between the Octave and Python workspace.\n",
61 "The first is for executing one or more lines of Octave, while the latter allow moving variables between the Octave and Python workspace.\n",
62 "Here you see an example of how to execute a single line of Octave, and how to transfer the generated value back to Python:"
62 "Here you see an example of how to execute a single line of Octave, and how to transfer the generated value back to Python:"
63 ]
63 ]
64 },
64 },
65 {
65 {
66 "cell_type": "code",
66 "cell_type": "code",
67 "collapsed": false,
67 "collapsed": false,
68 "input": [
68 "input": [
69 "x = %octave [1 2; 3 4];\n",
69 "x = %octave [1 2; 3 4];\n",
70 "x"
70 "x"
71 ],
71 ],
72 "language": "python",
72 "language": "python",
73 "metadata": {},
73 "metadata": {},
74 "outputs": [
74 "outputs": [
75 {
75 {
76 "output_type": "pyout",
76 "output_type": "pyout",
77 "prompt_number": 19,
77 "prompt_number": 19,
78 "text": [
78 "text": [
79 "array([[ 1., 2.],\n",
79 "array([[ 1., 2.],\n",
80 " [ 3., 4.]])"
80 " [ 3., 4.]])"
81 ]
81 ]
82 }
82 }
83 ],
83 ],
84 "prompt_number": 19
84 "prompt_number": 19
85 },
85 },
86 {
86 {
87 "cell_type": "code",
87 "cell_type": "code",
88 "collapsed": false,
88 "collapsed": false,
89 "input": [
89 "input": [
90 "a = [1, 2, 3]\n",
90 "a = [1, 2, 3]\n",
91 "\n",
91 "\n",
92 "%octave_push a\n",
92 "%octave_push a\n",
93 "%octave a = a * 2;\n",
93 "%octave a = a * 2;\n",
94 "%octave_pull a\n",
94 "%octave_pull a\n",
95 "a"
95 "a"
96 ],
96 ],
97 "language": "python",
97 "language": "python",
98 "metadata": {},
98 "metadata": {},
99 "outputs": [
99 "outputs": [
100 {
100 {
101 "output_type": "pyout",
101 "output_type": "pyout",
102 "prompt_number": 20,
102 "prompt_number": 20,
103 "text": [
103 "text": [
104 "array([[2, 4, 6]])"
104 "array([[2, 4, 6]])"
105 ]
105 ]
106 }
106 }
107 ],
107 ],
108 "prompt_number": 20
108 "prompt_number": 20
109 },
109 },
110 {
110 {
111 "cell_type": "markdown",
111 "cell_type": "markdown",
112 "metadata": {},
112 "metadata": {},
113 "source": [
113 "source": [
114 "When using the cell magic, `%%octave` (note the double `%`), multiple lines of Octave can be executed together. Unlike\n",
114 "When using the cell magic, `%%octave` (note the double `%`), multiple lines of Octave can be executed together. Unlike\n",
115 "with the single cell magic, no value is returned, so we use the `-i` and `-o` flags to specify input and output variables."
115 "with the single cell magic, no value is returned, so we use the `-i` and `-o` flags to specify input and output variables."
116 ]
116 ]
117 },
117 },
118 {
118 {
119 "cell_type": "code",
119 "cell_type": "code",
120 "collapsed": false,
120 "collapsed": false,
121 "input": [
121 "input": [
122 "%%octave -i x -o y\n",
122 "%%octave -i x -o y\n",
123 "y = x + 3;"
123 "y = x + 3;"
124 ],
124 ],
125 "language": "python",
125 "language": "python",
126 "metadata": {},
126 "metadata": {},
127 "outputs": [],
127 "outputs": [],
128 "prompt_number": 21
128 "prompt_number": 21
129 },
129 },
130 {
130 {
131 "cell_type": "code",
131 "cell_type": "code",
132 "collapsed": false,
132 "collapsed": false,
133 "input": [
133 "input": [
134 "y"
134 "y"
135 ],
135 ],
136 "language": "python",
136 "language": "python",
137 "metadata": {},
137 "metadata": {},
138 "outputs": [
138 "outputs": [
139 {
139 {
140 "output_type": "pyout",
140 "output_type": "pyout",
141 "prompt_number": 22,
141 "prompt_number": 22,
142 "text": [
142 "text": [
143 "array([[ 4., 5.],\n",
143 "array([[ 4., 5.],\n",
144 " [ 6., 7.]])"
144 " [ 6., 7.]])"
145 ]
145 ]
146 }
146 }
147 ],
147 ],
148 "prompt_number": 22
148 "prompt_number": 22
149 },
149 },
150 {
150 {
151 "cell_type": "heading",
151 "cell_type": "heading",
152 "level": 2,
152 "level": 2,
153 "metadata": {},
153 "metadata": {},
154 "source": [
154 "source": [
155 "Plotting"
155 "Plotting"
156 ]
156 ]
157 },
157 },
158 {
158 {
159 "cell_type": "markdown",
159 "cell_type": "markdown",
160 "metadata": {},
160 "metadata": {},
161 "source": [
161 "source": [
162 "Plot output is automatically captured and displayed, and using the `-f` flag you may choose its format (currently, `png` and `svg` are supported)."
162 "Plot output is automatically captured and displayed, and using the `-f` flag you may choose its format (currently, `png` and `svg` are supported)."
163 ]
163 ]
164 },
164 },
165 {
165 {
166 "cell_type": "code",
166 "cell_type": "code",
167 "collapsed": false,
167 "collapsed": false,
168 "input": [
168 "input": [
169 "%%octave -f svg\n",
169 "%%octave -f svg\n",
170 "\n",
170 "\n",
171 "p = [12 -2.5 -8 -0.1 8];\n",
171 "p = [12 -2.5 -8 -0.1 8];\n",
172 "x = 0:0.01:1;\n",
172 "x = 0:0.01:1;\n",
173 "\n",
173 "\n",
174 "polyout(p, 'x')\n",
174 "polyout(p, 'x')\n",
175 "plot(x, polyval(p, x));"
175 "plot(x, polyval(p, x));"
176 ],
176 ],
177 "language": "python",
177 "language": "python",
178 "metadata": {},
178 "metadata": {},
179 "outputs": [
179 "outputs": [
180 {
180 {
181 "output_type": "display_data",
181 "output_type": "display_data",
182 "text": [
182 "text": [
183 "12*x^4 - 2.5*x^3 - 8*x^2 - 0.1*x^1 + 8"
183 "12*x^4 - 2.5*x^3 - 8*x^2 - 0.1*x^1 + 8"
184 ]
184 ]
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185 },
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190 "\n",
190 "\n",
191 "<desc>Produced by GNUPLOT 4.4 patchlevel 0 </desc>\n",
191 "<desc>Produced by GNUPLOT 4.4 patchlevel 0 </desc>\n",
192 "\n",
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222 "\t\t<text><tspan>6.5</tspan>\n",
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265 "\t<path d=\"M93.0,91.2 L93.0,82.8 M93.0,11.3 L93.0,19.7 \"/>\n",
266 "\t<g style=\"stroke:none; fill:rgb(0,0,0); font-family:{}; font-size:10.00pt; text-anchor:middle\" transform=\"translate(93.0,106.2)\">\n",
266 "\t<g style=\"stroke:none; fill:rgb(0,0,0); font-family:{}; font-size:10.00pt; text-anchor:middle\" transform=\"translate(93.0,106.2)\">\n",
267 "\t\t<text><tspan>0.4</tspan>\n",
267 "\t\t<text><tspan>0.4</tspan>\n",
268 "\t\t</text>\n",
268 "\t\t</text>\n",
269 "\t</g>\n",
269 "\t</g>\n",
270 "\t<path d=\"M121.3,91.2 L121.3,82.8 M121.3,11.3 L121.3,19.7 \"/>\n",
270 "\t<path d=\"M121.3,91.2 L121.3,82.8 M121.3,11.3 L121.3,19.7 \"/>\n",
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271 "\t<g style=\"stroke:none; fill:rgb(0,0,0); font-family:{}; font-size:10.00pt; text-anchor:middle\" transform=\"translate(121.3,106.2)\">\n",
272 "\t\t<text><tspan>0.6</tspan>\n",
272 "\t\t<text><tspan>0.6</tspan>\n",
273 "\t\t</text>\n",
273 "\t\t</text>\n",
274 "\t</g>\n",
274 "\t</g>\n",
275 "\t<path d=\"M149.6,91.2 L149.6,82.8 M149.6,11.3 L149.6,19.7 \"/>\n",
275 "\t<path d=\"M149.6,91.2 L149.6,82.8 M149.6,11.3 L149.6,19.7 \"/>\n",
276 "\t<g style=\"stroke:none; fill:rgb(0,0,0); font-family:{}; font-size:10.00pt; text-anchor:middle\" transform=\"translate(149.6,106.2)\">\n",
276 "\t<g style=\"stroke:none; fill:rgb(0,0,0); font-family:{}; font-size:10.00pt; text-anchor:middle\" transform=\"translate(149.6,106.2)\">\n",
277 "\t\t<text><tspan>0.8</tspan>\n",
277 "\t\t<text><tspan>0.8</tspan>\n",
278 "\t\t</text>\n",
278 "\t\t</text>\n",
279 "\t</g>\n",
279 "\t</g>\n",
280 "\t<path d=\"M177.9,91.2 L177.9,82.8 M177.9,11.3 L177.9,19.7 \"/>\n",
280 "\t<path d=\"M177.9,91.2 L177.9,82.8 M177.9,11.3 L177.9,19.7 \"/>\n",
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281 "\t<g style=\"stroke:none; fill:rgb(0,0,0); font-family:{}; font-size:10.00pt; text-anchor:middle\" transform=\"translate(177.9,106.2)\">\n",
282 "\t\t<text><tspan>1</tspan>\n",
282 "\t\t<text><tspan>1</tspan>\n",
283 "\t\t</text>\n",
283 "\t\t</text>\n",
284 "\t</g>\n",
284 "\t</g>\n",
285 "\t<path d=\"M36.4,11.3 L36.4,91.2 L177.9,91.2 L177.9,11.3 L36.4,11.3 Z \"/>\n",
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286 "</g>\n",
286 "</g>\n",
287 "\t<a xlink:title=\"Plot #1\">\n",
287 "\t<a xlink:title=\"Plot #1\">\n",
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290 "</g>\n",
290 "</g>\n",
291 "\t</a>\n",
291 "\t</a>\n",
292 "<g style=\"fill:none; color:black; stroke:currentColor; stroke-width:0.50; stroke-linecap:butt; stroke-linejoin:miter\">\n",
292 "<g style=\"fill:none; color:black; stroke:currentColor; stroke-width:0.50; stroke-linecap:butt; stroke-linejoin:miter\">\n",
293 "</g>\n",
293 "</g>\n",
294 "</svg>"
294 "</svg>"
295 ]
295 ]
296 }
296 }
297 ],
297 ],
298 "prompt_number": 23
298 "prompt_number": 23
299 },
299 },
300 {
300 {
301 "cell_type": "markdown",
301 "cell_type": "markdown",
302 "metadata": {},
302 "metadata": {},
303 "source": [
303 "source": [
304 "The plot size is adjusted using the `-s` flag:"
304 "The plot size is adjusted using the `-s` flag:"
305 ]
305 ]
306 },
306 },
307 {
307 {
308 "cell_type": "code",
308 "cell_type": "code",
309 "collapsed": false,
309 "collapsed": false,
310 "input": [
310 "input": [
311 "%%octave -s 500,500\n",
311 "%%octave -s 500,500\n",
312 "\n",
312 "\n",
313 "# butterworth filter, order 2, cutoff pi/2 radians\n",
313 "# butterworth filter, order 2, cutoff pi/2 radians\n",
314 "b = [0.292893218813452 0.585786437626905 0.292893218813452];\n",
314 "b = [0.292893218813452 0.585786437626905 0.292893218813452];\n",
315 "a = [1 0 0.171572875253810];\n",
315 "a = [1 0 0.171572875253810];\n",
316 "freqz(b, a, 32);"
316 "freqz(b, a, 32);"
317 ],
317 ],
318 "language": "python",
318 "language": "python",
319 "metadata": {},
319 "metadata": {},
320 "outputs": [
320 "outputs": [
321 {
321 {
322 "output_type": "display_data",
322 "output_type": "display_data",
323 "png": 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2ZvTl5+jRo0WrkCu02YtuPQtKEYTRdR32HzmO02q1NE0LP0L9gjCTmZ+fX1xcjPquoJdv\ntXaOS+7iL1++TFVQgjZ7r127VrQKNaT4IEy73RYEwbIshmFM05QkKVLAfXt7ezAY7H5eXVhfX+/3\n+wkH8U7nS+7iDx48WLQKuUKbvfv2xU8zQ8ZRvFtnGKbb7VqW5TiOoihMRKfyyiuvvPTSSxnpVkK2\ntrY2NjZSHDDo4h2HsCwRxVIk2NAWlKDNXqoetXOjeLcOxE6Jufvuu++99950lSkzhw4dOnnyZEaD\nuy7etglUcGBZguV5EKRaFLwdKTnnzp07c+ZMSTZ35YBt2yTiRtwkGAaBvKTgMiyCIC6Qt95sNotW\nhJDyzNZjk3pQouTkXDBHFIkoEschhrGTSCNJpQjOIAgyjsq79UyDEiUk+QauGDDMTijGtnfm7zxP\nRLFci6vjcLf/FTuTUlWVEMLzfPJEF1iI2nWcJBLd5DSkisR366Zp6rruOA7HcTGWOl1UN5v6dSLd\niNvb25ubm/FEVxGYrce+2rFpNBreB4X/+l9/6YknfvMDHzj8+7//ppw1iQrLsjzPB2+znOF53jAM\n0zSTu3VZlsP8RPkk+j5BQgjHceO+a4ZhEELQs1eUmG5d13Vd1zVNY1lW13VBELrdbryhWq2Wr7BX\npMBxv9+/cuVKPNFVBLbg5p/aLEkSfNXdzWK2/a1Pf/rSf//vv/e+9/1Mmb/+LMuyLJv/D6EPnudT\nqRmi6zrDMGFuAJ/E4CcIoxmGEdwp0mw2G40GuvWKEsetw6Yht6WRoiiO4yR5akvipI4ePUpPuTtS\nhEN35YKP8Cogis7y8vJLL31Plu8WRVxTzYNWqxUvmjTyE+R5HnaN+IJ7HMfBjA09exWJ00ajVC2N\nKAzClKfNCMMwoijef///1DRiWaTRILa986vfaDSWlpampqYajcbIWaplWY1GY2FhYWFhodFoGIYx\n8hYKeVpIDMMQBGFqamp5eTnYDz2M5vBsqus6KOYOFZQFjdcXFhaWlpZkWU7lUzNN03GccdU14knk\nOG7kmaIoYp+yihJntp5RSyPTNDmOi/qwjEGYYnEc5/WHNuI4pNUia2vb99wzrygK3CS2bTcajWaz\n6dXZfbHdbsN/W62Wbdu+uWHI00Ki67ppmhA5hOdLXx9dSB6drDnP85ZlGYZhWRYo5jiOqqqqqnon\n0W6UEjTXdb3RaCRf7jZNc5xPjyfRcRzY2h38E8/z8NsQI35lmv6C0qWlnpldw+iIotjpdHwv8jwf\nYyjImud5HlZvOI4TRXEwGIR/+yOPPAIlm3meP3bs2JkzZ7wHH/3oR0FVTdPgoNPpaJrmPej1eoqi\neA+Gw6GiKL1ez3vgjpDFUJqm+YbqdDq+oeDAN5SiKDkM5RriGgWAy/N9IoPBUJKGijJ0P8Z2ux18\no++VwWAgSZJvqJCnhYHneVEUfS9qmhZ80UtQ8+FwCH7fpxXDMO5/e70ex3G+2xgWn4KjRYLn+ZEj\nhJQILWsUDyzLdrvdceIIIcFvOoV4v+DHjh3jef7MmTNw4HqbBx988JFHHila0x1ub0dyHGdcRVyG\nYbw/+8lbGnlptVqiKLrLpDClghlHGFRVTSVpDNkVVVUNw3A/KWhY2Gw2R87mvvjFb375y0cPH771\n4Q/fgCmhdzJr27YgCFD/Z8JnF/K0MAiC0Gw2g7PX5eXlTqfjNcENvDAME9ScvJ675Xtxaur2V0lV\nVZZlg1NgWZYZhkmSZ7mwsNBsNoMjh5QIcSeY79u2bdu24zi2bcMTTFCcIAjwMxBbYXoo6XYkSFgc\neRLDMOH9bFR8Nw2s19u2HTIfZnV1dWVlhR63Hlz1yhOY87rHI88xDENVVY7j7r+f/cEP3vaBD/zU\n9PT/+853/gfvOTBJhDQMiKuA+/B96CFPC8nIiATDMG7Ff1dzGB8mOjEu9bh3Jc/GGWd4eInBLBpY\nJBiXyVaehRwkPLfduiiKIQudZ70jhuO48G59cXERtyPlxq6pdRD+vjNgTT70oS+vrfmnBQzD+Ors\nQ5qszxOFPC0M48LEcKcFNSdxO5ll9xkxDAMLAClKhAWtYDIMIcSyLMyEqSJxMmHIqAZGkVoapcj0\n9HTCJtTVgmGYwlOwJwApcV4NWZY89tj/+D//521u+V8yag8aBOJ8d1HI08Lr5nsFAhHg1oOak7hz\nVY7jDG9vqtcZ+WLUkUeqlFDiyB88yLkqdhqBxCOOWxdF0TeFmdDSyDTNVqsV6ethGEb4mwmCMOEH\nrzql6oQbJOhzW62Wqqpnz/49yxJZJnAjWJblc7JeD+sS8rSQWJblvXSO4zQaDXcnzjjNYwgSRdG2\nbZ/mEOaOMZqXcXuakkhstVqwY8v3OnwNcysqh6RInATH8C2NLMsSBAEORkbnYUHM+5Mgy7IvKX4y\nGITJB0EQ4PEffB/HcSNXhyRJkmVZEATQE3aua5omy7JlWR/72Odk+S2KshNMWF5ehpCObduWZQUX\n7kKeNhkIzVuW1ev1ZFnWdR0SHC3L8q78T9bcFSrLMjhW27bhloafB7hE7mntdltVVVdzSCJkGAY0\niZdcQF5fzxhZgWBXib5PELBtWxTFkV/eCcmUSMmJWZjXcRz4ArgtjUbG4GzbXlpaIoRIkjTy1oGc\nX++alSiKkVaTMROmhMCcmrwet/X9VVUJw0Ce+07ylS/VykfI06LqNvKemax5urLiAb9S434Y0pII\nv6a9Xq/MEb9SUapMmET11qGS3OQvANxnk28y93sb47v027/927/wC79w7ty5SO+qLu6FKlqRRBgG\nMU3SbFajBmTZWFpa0jQt06mMLMscx+F6aXhK5dYTFeYN41xGhu18hCxdNJKZmZm5ubl4760i9Zg9\niSLhOCLLRFFIxX+hCgC2tmYqYmQWPFIVKl9vfX5+fnFxsWgt8qM2S1gsS9ptoqrENAnud4lEDs9q\nuAWp0sRMcCwPa2trtNWEKSqXNAsgDiPLY0+grdoU2oskp/JuncIgTD3iMC6StBOQGUltnk5CgvYi\nySmLW4fd4THeSGEQpn7fBPDsI3PEactxQnuR5BTs1qFC9PLyMnTnijHC+vp6v99PXbHS4maw1Qyo\njxp8Ii/z3qssQHuR5BTs1qHiR7fbjb3svrW1tbGxka5WZaZUbTTSBW4Bn2ev5W/YBNBeJDkFu3WO\n4xIu6x86dIi2XaZVT1qfQNCz05Zmh/YiySlLbD02GISpGT7PTttDOtqLJKfybv3KlSvnz58XBEEQ\nhOPHjz/00EPeg4997GNw30B3DuIpK+8e2LYNFZ3cA0KIqqrgPd0Dd4QshoKOZb4xfUPBwfe//32o\nuOCOGXson1blGUqSyGc/++1PfvJHhJBPf/rTOWtV7F0BFbvKfK+mO9Rf/MVflFCrCUMdP358pLdR\nFGVtbY2Ug0TFA8YRvtGSCxR6jFEC6fz5829+85tPnz498q+pVPZACkGWCccRfEZHSsW4x4uVlZVn\nn332iSeeyFmfkWSyyzTnRksnT56kJ00K1ktp+K3SNCLL5JOf/NHv//6bitYlP2KXHa4olbN3gqt5\n8cUX89RkApm49fCNlpLT7/dp22VKqMn21TRy+rT9zne+qb6LxH50XS9Juah8oM3efKh8TZijR4+O\ni8DUEkocusvKyn+AuCglnp02H0ebvflQ+SXT7e3tzc3NorXIjxrnrY/Etu1mkxgGqVEhnEnUO80p\nCG325kPl3TqFQZg6lfraFVikaTZJq0Vo+DmjrfQVbfbmQyaZMOFptVqwsuw4jm3bbpJM+JQY7I5E\nCY5DZJmkvdyOIOlQnzYayVEUJWFlZwqDMISOTBjAzZRgGCKKpNWqeXH2ymWGJIQ2e/MBgzAVg84g\nDCCKxHFqHmSnLShBm735UPlMmMXFRdpqwhStQq74aoY0m6TRIJpW2yaotNVIoc3efKj8bH16enp2\ndrZoLfKjfm00JhN8QlcUEqsyfzWgLSJBm735UHm3vrq6urKyUrQW+QErM0VrkR9qoLkGx42uzF4P\ngvbWG9rszYdEQRjDMGzbTrjmGfxcI2W2YBCm3ox8SJckoqrEsmq4R4m2oARt9uZDHLcOJV9gCdtx\nnIRuPVjhK9JzGYVBmKJVyJVxN4Oi1DPfkbagBG325kOcIEzylkY++DuJ9EljEKbejHtIZxiiKKPb\nn1Ya2oIStNmbD3Hceqka9Bw8ePDw4cNFa5EftWxRPYEJ4TiOIwxDDCNPdTKHto11tNmbDyVaMjVN\nM0a1k/n5+cXFxSz0KSfo1r0oCjFNUqeyIrS5OdrszYdSuHVBEJaXl1utliAIjUYjknPvdrvvfe97\n6emO9Dd/8zeWZZWwpVFGQ7373e+ePFSzST70obXadEcClcp8r6Y71Ac+8IESalWf7kh5tjTy0mq1\nRFF0Z6BwccO32jh37tyZM2fe//73J9GhQsC9SM+E3TTNXSd0pklMk5SjGkdSwthbJ2pjb0lrwuTc\n0sjFl0gjSRLkTYb0XBQGYYpWIVfCfOd5fsez18A/1MPHhYc2e/PhtlvPs6XRZDiOC+/W19bWrly5\nQs/NAU9U5Vmyzhpd18MkXEFRAVhErTQh7a0NtNmbD6WIrSNIcprNGuY7IkgMMnfrEH+PtApqGEb4\n2eihQ4do22VKz1SdRNmFyLKE4ypfVIC2qStt9uZDtm7dsixBEFRVlWV55AmCIBh3Jh7LsiyKYvi9\nlOvr6/1+P6mi1cG2bar6hEXaeyVJlS/bS9VeM0KfvfkQp3iAr6WRIAjwejAlxvXO49x0u91WVbXV\nakFw3DAMURQjrSZvbW1tbGxENaG6UNXIlETvdSmKRFUrnBVD1W82oc/efMi86R3MLicvabq5lRzH\nRa15gk3vEB+qShSl8munSLUoVYJj5rF1lmV39bkMw4BrjlHHCoMw9SbGQ7okVbggO21BCdrszYfK\nZ8Jcv379ueeeK1qL/EC3viuQGVvRIDttbo42e/Mh8yBM1mAQBgniOPUs24uUFrqCMFmzvb29ublZ\ntBb54TgOVaum8R5NGGZn62nloOpRjNBnbz4U79Ydx4EiX4IgRM1wJ4T0+/0rV65kpFsJsSxrXOme\nWhK7M70kVTKHPba9FYU2e/OhYLfuOA6UbNQ0TdM0x3EEQYjk2Y8ePXr69OnsNCwbtEWckjzVVnHt\ntCRP8blBm735ULBbV1VVkqRmswllxJvNpiiKrSjfRQzC1JskD+k8T2ybVOtq0RaUoM3efCjYrbMs\n66svpihKpCADBmHqTcKHdEWp2ISdtqAEbfbmQ5xdpikSbG9t23ak7PXFxUXaasIUrUKuJKwZAsmO\ntk2qUs+YthoptNmbD8UvmfpoNBqRPumnn3763Llz9HRHchyHYZiStzRKcagk1wpG2N7+f37v9zbD\na1XsXcGybMnv1XSH8o1ZEq3q0x0pRWI0WgJkWeY4LpJbf+973/vggw9+5CMfiaxlNYE7j55VU1VV\nk6+qtVqE46rRZCMVeytEbewtVd56JkGYeI2WYvh0gkGYupPKQ7qikEajGm6dtqAEbfbmQyZuPWqj\nJchrlCQpxmc8PT09Ozsb9V3VJUbZnEqTVpM/SGMvvw+hrakhbfbmQ/Gx9SQ+nRCyurq6srKSulal\nxQ1HUoKaUscj2HRa/mTHtOytCrTZmw/Fb0cK+vRIqawHDx48fPhwBqqVFEjwL1qL/EhxFaHZrECy\nIz2rJgBt9uZDkQmOsMVUURRfxGZ5eXkwGIQcZH5+fnFxMQPtSgpVPp2k+rVnWeI4ZU92pM3N0WZv\nPhQ5W7csy7ZtXdeFO4m0i3JtbQ23I9WYdLerNJtlLxRD2/Yc2uzNhyJn6zzP93q9hIPMzMzMzc2l\nok8lwCXTJMDFM83yZsXQ9jRGm735UPySaUIoDMJQ9U1I/SG92SR3NkUvF7QFJWizNx8q79YxCFNv\nsnhIZ5jy9k6iLShBm735UHm3jiBRUZRST9gRJCEFl/pKzqFDh3CXaY3JYhciRNjLmRJD265L2uzN\nh5hu3XEctzIOz/OSJMVeygvuR4jUKWJ9fb3f78cTXUUgqZ+e8LppmlmEX2HTaTkKeNxBRvaWFtrs\nzYc4bh3yzTmO0zSNEAIZip1OJ55nb7VanU7H+0okn7W1tbWxsRFDbkWhqocGyazNAtxijkPKllhE\nW1sJ2uzNhzgVHGVZ5nneu4cIepDGq142NZWoiqSqqrT1gUNSwbKIaZJAwX8EiUOpKjjGWTJN3tIo\nRSgMwlA1wcmuAA7HkRJeSKoK/hD67M2HOG49eUujkZimGSPCcP369eeeey6h6AqBbj1FeL50m05p\nc3O02ZsP6SQ4Rm1p5EMQhOXl5VarJQhCo9GI5NxffvnlP/mTP6GnOxLLsjzPl7ylUYpDkde/+Vlo\n5Tj6l770r6W6K5rNZsnv1XSHgoW0smlVn+5IebY08tJqtURRdJdJ4eKOa7UR5Pz582fPnn344Yfj\nSa8c8JtHTwkB27YzTfvRdcKyJaolkLW9ZaM29pYqtn47EybPlkZefCEdSZIMwwj/Yff7fdp2mRKa\ntlzrup7pV0WSiCyXyK1nbW/ZoM3efLjt1vNsaTQZjuPCu/WjR4+ePn06XQXKDD0OHcjhO88wJdqa\nRJuPo83efIgZW8/Op0dle3t7c3OzWB3yxHEcqlLXc1gfVpQStdegaj2c0GdvPsRx65FaGpmmCVnt\n4cc3DCP8FnkKgzBY6itdGIYwTFn64dFW+oo2e/Mhslt3Wxr55unLy8vBky3LEgRBVVVZlkeOJgiC\ncWfVJVmWRVEMvyS4uLhIW00YqsrC5PM4KEllmbAX/vibM7TZmw+Riwe4LY18P7Mj5+Oudx7nptvt\ntqqqrVYLQsaGYYiiGCncNj09PTs7G/78qkNPDgyQT5oE9MMrA/VICwkPbfbmxDBjer1ep9OZfM5g\nMOh0Op1OZzAYRB3/0Ucfffzxx+NqVz3gQhWtRX4oipKPoE5nqGn5iJpEbvaWhNrY2+l0ymNL5vXW\nYfvM5HMYhoG6LjGmoj/60Y/27NkTV7vq8f3vf3/v3sqXUw7PgQMH8llL4HlShg2PudlbEtbX14tW\noYZUvo3GzZs3X3311aK1yI9+v//KK68UrUV+3LhxI7fMnzJ49jztLQNXr14tWoUaUnm3fuPGDaru\njNXV1ZWVlaK1yI8LFy7kJkuSiu+alKe9ZYCqL29uFP847+3IwbKsoiiRVlGmp6cXFhYy0650HDx4\n8PDhw0VrkR/Hjh3LUxzLEssiBaYa5Wxv4VD15c2Ngmfrtm0LgsAwjKZpnU6H5/lGoxEptkibW5+f\nn19cXCxai/w4evRonuIKn7DnbG/hUPXlzY2C3brjOJqmSZIEM3RRFDVNa0VJIb558+YzzzyTmYKl\nY21tjartV5cvX85TnNvmtChytrdwrl27VrQKNaRgtx7cXMNxXKTZ+t69e/fv35+2XuVlZmZmbm6u\naC3y4+DBgzlLhDanRZG/vcWyb9++olWoIaVbMo3ashaDMPUm/6CE2+a0EDAIgySnLG7dsixohtBq\ntSLtMsUgTL0pJCghioVN2DEIgyQnUXvoccToyKHrOnj2YLWZybz1rW+9evXqgQMHCCEvvfTS9PT0\nnj173IMDBw4wDLOwsHDt2rV9+/YtLCwMBoNbt24dOXLEPbh169a1a9dOnDjhHhBCrl69euTIkX37\n9rkH7ghZDAU3t3eowWAwGAy8Q8HBq6++Oj8/v7m56Y65sLAQbyifVuUc6lvf+ta9995777335qYV\nHFy9+h5CHs//rnjuuedmZmbgpi3nvZruUE899dTb3/72smk1YaiLFy9C1NfnbV577bX3vOc9X/jC\nF8L7ruzIxK0bhhGjIwcgyzLDMFiFGUEQJB6ZuPWECIKgaRrWAEIQBIlBWWLrXqA7UtFaIAiCVJIy\nunXLsmgrP4sgCJIWBbv14J7SVqs1blkVQRAE2ZWCY+uWZamq6jgO5KpD0rqiKDhbRxAEiUcplkxt\n24ZgOsdx6NARBEGSUAq3jiAIgqRFGZdMEQRBkNigW0cQBKkV6NYRBEFqBbp1BEGQWoFuHUEQpFag\nW0cQBKkV6NYRBEFqBbp1BEGQWoFuHUEQpFagW0cQBKkV6NYRBEFqBbp1BEGQWoFuHUEQpFagW0cQ\nBKkV6NYRBEFqBbp1BEGQWoFuHUEQpFagW0cQBKkV6NYRBEFqBbp1BEGQWoFuHUEQpFagW0cQBKkV\n6NYRBEFqBbp1BEGQWoFuHUEQpFagW0cQBKkV6NYRBEFqBbp1BEGQWlEKt26aZqPREARBVVXHcYpW\nB0EQpMIU79Z1XVdVVVGUdrvNMIwgCEVrhCAIUmGmhsNhgeIdx1leXu52uwzDwCuqqrIsK0lSgVoh\nCIJUl4Jn64ZhiKLo+nRCiCRJuq4XqBKCIEilKdit27bNcZz3FZZlMbyOIAgSm73Firdtm+d534ss\ny4YfQRCkf/qn/+snfuInCCGvvPLKnj17pqam3IPp6emZmZmZmZnNzc29e/fOzMxsbW298sors7Oz\n7sErr7yysbHBMIx7QAhxHGdubm7v3r3ugTtCikP96EdvmZt7CsYkhHiH2traunXrlneo9fX11157\nzTeU4zj79u3zajV5qJdeunbs2Is//vGPX3jhhZ/8yZ+86667nn32Wfdgbm5ubm7uxRdfvOuuu+bm\n5m7e/B9veMONI0eODAaDW7duwcFgMDhx4sStW7euXbvmHhw5cmTfvn1Xr151DxYWFhYWFq5du7Zv\n3z44IISEGQpO844Ze6h4WsGBb6gTJ04QQrxDwYF3KDgIP9TLL7/8Mz/zM6kMlaJWqQ/13e9+9/77\n7y+bVrGHunjx4v79+wkhL7300vT09J49e+CAEPKrv/qrX/rSlxK4w9Qo2K0nn5g/++w3P/ShKU3T\nUtGnCP5jyPOOHz/+b//2bwmFmWbYM22b2PYu5zgO8cTPiPvcNfLA9/PNsmTkz7eqqjzPB3/s64cg\nCJ1Op2gtMocSMz/1qU/96Z/+adFa7FCwW0/O3XfffeTIkaK1yINUzCzKWwZ/JMYtoFy48K7V1WPe\nnx9XZ4Yhd0bsEKRE3HPPPUWrsEPBbp1L/DXds2fPvn37UlGm5FTazODcfNwPzC/+4v/9O7/zCZ4/\nBv91HGJZO3+yLGIYxH0dHhTcA47bOajKRP/q1atFq5AHlJhJCIFQTBkofrZuWZbvidtyv8chuHHj\nBiX3DSVmPvDAA97/MkxYNw0TfNsmqjrir/C7Uqr5Pj5l1oynn366aBV2KNiti6IIe5HcVyDlMfwI\nGISpGfPz8/HeONn7WxZxHGKaxDD8SwLg8cfF+rOj0o9f4aHETIJBGBcIwui6DvuPHMdptVqR1j8x\nCFMzLly4ba0cuQAAIABJREFUkMV6KUzSRw4M03xw9154PtvZPSWPX5SYSTAI46XdbguCYFkWwzCm\naUqSFCngfvPmzWeeeSY79coDZOPVHl8QJgfA1/s8PqzxeqP57slpzespefyixExCyPPPP1+0CjsU\n79YZhul2u5ZlOY6jKIp3x2kY9u7dC2mktYeS2XrsIEy6jPTd4Ot98/rYjp6SD5QSMwkhMzMzRauw\nQ/FuHYidEjM9Pb2wsJCuMuWEEjPLDLhv77weEnWCjt5Ny0Ho4cCBA0WrsENZ3Hpsfvqnf3p2drZo\nLfIg0kpydWk2m0WrEAFI1Ak6+lbrjsxLjhsxnadhkw6hxszTp0//wz/8Q9Fa7FB5tz4zMzM3N1e0\nFnkQqaYCUhRBR++m3wAsu+PokZpx8ODBolXYIXO3bhiGbdveFMYgpmnquu44DsdxUcPr8/Pzi4uL\nidWsADTsp88C0zRN0yTFPQeAl1dVlRDC8zzD8N6V2HFz+QnAQtSu94MrMcad4yanIeE5evRo0Srs\nkFUFR2h4tLy8bBiGObEQScI2Guvr6/1+P5my1WDyZcwHx3FkWV5aWpqammo0GqZptlqt4GkjXywK\nlmV5ni/86vE87ziOaZocRySJNJs7/xiGGAaRZaKqRFVDFe2RZTmSRPgvNCDzoqrquMtiGAbWx47K\n6upq0SrskNVsnWEYRVE4jhv3zQcgUd1to6EoiuM4kWYKW1tbGxsb6ShdbuxdK29lDPQ8URQFNhbY\ntg1+IfgoNvLFomBZlmXZqBlWqTPup8UbsYENU7BL1nF26qP5JvK6rjMME2YC7pMoSZJhGOTORRpd\n1w3DCO4UaTabjUYDJ+yRuH79etEq7JCVWw+Z2TKyjUak++nQoUMnT56Mo2LVKPw7puu6KIquGizL\nttvtpaWlYrWqEwxDRJG4XtcblIcMHJYlrVYrXjTJ9fLenwSe52HXiO8Ly3Ecy7IYionEqVOnilZh\nh8q30cAgTG7A4ofvRd+sXJZlcBPeh/2RQQPbtmVZXl5eXlhYaDQavkd+0zThvYQQwzAEQZiamlpe\nXk7YxHzyUPDs2Gg0vFEm3wi6rguCoOu6ZVmNRsMdKigL4pALCwtLS0uyLMdQm+eJouzEajiOGAb5\n9V9/5tq1j9u2OLJsUjyJHMeNPFMURYzDRKL+QZiQJG+jgUGY3OA4Llixxzebg7/66vwEAyDgE33x\nHMuy3GgAy7KKoqiqCs5X0zS4K3RdX15ebrfbMTY66LpumiYMBbE+Xx9duMIQPIT/NhqNZrPpm95a\nlmUYhmVZzWaz3W47jgN6eifRuq7ruq5pWrvdhv82Go0k9UphZdVx/suRI44ofhAm8uT1xBuOiykR\ngu8jp+Q8z8NvQ4z4lWlGqOxfLJKUWi2g8gRhyDAig8GgM4Zutxs8v9Pp8Dw/bjSe5zudTvDF8Po8\n8sgji4uLsNx/7NixM2fOeA8++tGPwviapsFBp9PRNM170Ov1FEXxHgyHQ0VRer2e98AdIYuhNE3z\nDdXpdHxDwYFvKEVRchjKpdlsQraSpmkjP+6QnyDHccG3i6LoE8fzvCRJvtMm31ETVBJF0feipmnB\nF7202233c3QBv+99ZTAYMAzj/rfX63EcNxgMvOd0u11CSHC0SPA87xuh1xs2m8MPf9hZXPzCE09s\n9nqTJCqKAiO4sCw74XMkhAS/nhTi/YIfO3aM5/kzZ87AgettHnzwwUceeaRoTXeYGg6HkX4GJiyR\nMwwDMwUvsGQ6bkuCIAhwq/leDL+F4fz582fPnn344YdDnl9dbNsuSeq6aZqWZdm2DUujwbne5E/Q\nner6XoewjPeNgiC483QvMGGP2BxRgN+k4FCdTsc7IXUDLwzDwGTWpyqEXHwvTk3d/iqpqsqybPCy\nyLLMMEySPMuFhYVmsxkcGSRynOTNmxRFv0R49IEnKtu2bdt2HMe27ZEXmRAiCAL8DMRWmB5M0/zK\nV77y2c9+tmhFCIkRhBFFMcXtjsnbaPT7/StXrqSiTMnRdb0kOzDdVGjHcQRB4Dgu0ucYXKADWJYN\nxrJHuhuGYWL8yI0UyjCMW/HfMAxVVWG1kBDiOE6wGUAYxr0reTbOOJNBorvLyc2o+d733jszc8uy\nbu9+CmbRQEAMpvZBsF98eC5dulS0CjsUv8s0YRuNo0ePnj59Om2lykjhPj0YWAcfYRhGJLcOTnnk\nn4Jua6T7Hrl4uyvjwsQwvm3b3lxbwN3KFInkk5VxjLt0PoluRo2q/v36+oJpvhtm8T/4wdvuu+9/\nBd8Lv21BtS3LwkyY8Jw9e7ZoFXYoOBNGFEXf1yZqG43t7e3Nzc209SojhS+Zjtt/EHUSKoqi4St3\nSwghRNf14CQ3mGSi63q8PPRg8BACEe5irCRJvmHjzVVhbTn4+sgXo448UqUJEufnB5BOA6GUCxfe\nJctE1++oTTbyB89xnHg/n9Syvr5etAo7FOzW3TYa8F/IMIs0QaAqCFOsApZl+Zws5IQEf4bBXXpf\nMU3TfQW2ffqyHmENJvhEAonV4LNAAcj3iKe/dw7hOE6j0fDm3vgeE1ut1sjMxV0RRdG2bd/nBWHu\nGKN5GbenKYxEhiH33fe/zp79e00jHEdaLSLLpNUiivL/wY4t35jwEFaS5ZxKUJ4gTOQl05C0Wi24\n/2BNxv3ND66kufFZt41GJLeuqmq8qhdIVOBjMk0TrrZt25Zljcw1hCA1uHtYdeR5vtlser0M7FCF\nocCfBhfuYOnVNE2oLEQIgdyYSP4RNlJaltXr9eC3BBIcLctSFMX7myTLsnuvgm7w88OyrKubLMtw\nY3McBwkC8PMA57unQdajG2CEG9u2bcMwWJZNUtRwaWlJ07TgDb+rREEQ4Bp6L/JTT73MssoDD/zK\n9PSMKN5RgAzyI3G9NCQQrys8Ugpk5dajAtWLwLlHeiO69ZwBh0gIYRhmwhO6exqZWKQMXOTI2SKJ\nmBMVEvdJYqRW7l9j3IpRZcUDfqXGXZbYEh2HGAaBBypRJAxjLy8v93q9wosuVIVSufXIeetl49FH\nH3388ceL1iIPEqY8V5EY+ek0ALPvjAYfDIaaNnzggW/80i/973Y7IyE1pNPpvP3tby9aix0Kjq0n\nZ3FxEWvCIFQR3B2SIgxDJIk8+ujlr371Zxxnp7Rk4rVeKsi/De84ik9wTMj09DQl3ZGoWryCUAMh\nBMrCeEuMITlkp0BI3b3khkFUlTgOkSRsADKWkrThJYVnwiRndXV1ZWWlaC3yIF5WRuUAMyVJ8tal\nqKVPr9AHKoo7FccsizQapNUi4bNtK2RmQi5cuFC0CjtkOFuHakpuLdAJCQxJuiNhEKZmUGImqaCl\nEJ+RJGLbO5nvUKJg8ve1cmbGpjxBmKxm65D1BbX3NE2DLMaROykSdkfCIEzNoMRMUmVLWZY0m0TT\noP77Lk2dqmtmVMoThMkqE0aSpPad6+jNZjOYyzEYDFiW9da6g+qA4QV98IMf/MxnPpNE1aoQ6bJU\nF0rMHNbIUkieUZShogy9JSSB2pg5mU6n8653vatoLXbIKgjDsqxv86GiKMGZePLuSDMzM3Nzcwm1\nrQSUzHooMZPUyFIIzhByOzgjirc7+dXGzF05ePBg0SrskJVbD25Os207GDRP3h1pfn5+cXExnpLV\ngpItV5SYSepoKQRnCCG6ThoNwvPg3+tm5jiOHj1atAo75JcJM3IOPtLXR/p5X1tbw5owdYISM0mt\nLZUk0m7vRN7f/e5LRRepy4nLly8XrcIOkd06lPgYyYSCurIsS5I0spBFZJXvpN/v/8Ef/AH0vTx+\n/PhDDz3kPfjYxz4GqThuTg5k3XgPoOOa94AQoqoqbMJ2D9wRshgKOpb5xvQNtX///uBQUFkl6lBw\nUM6h9u/fX6xWud0VPkszvcEKGYpl7WaT3H33f/nUp67LMpFlswxaJRzq+PHjI72NoiivvfYaKQeZ\nd0cihMiyzHHcyHB58u5IWBMGQSqBrhPLIixLJGmXnMgqUqqaMNl2R4K8xglFGZPvl1tfX+/3+wkH\nqQRuvcN6Q4mZhBpLXTPdZVWo268odXPuq6urRauwQ4ax9V19OhAM3UTqjrS1tbWxsRFHv6pReBuN\nfKDETEKNpT4zYVlVknYS3uvUU+/69etFq7BDhtuRgj49eB8n74506NAh3GVaJygxk1Bj6Ugza+nc\nT506VbQKO2Ti1mGLabAn/fLysu/M5N2RqArCFK1CHlBiJqHG0glm1sy5lycIk0neumVZ0ILLt7g6\nMu+l3W4LgmBZltsdKVLAHYMwNYMSMwk1lu5qJjh3N+YuSaSiG5jKE4TB7kgIgpQF17k3mxVbUC1V\nJkxZCvNyHMfzfIwOW9vb25ubm1moVDZwclczKLE0kpksSzSNKApR1R3/XiHW19eLVmGHsrj12PT7\nfdxlWicoMZNQY2kMM8G5cxxpNCbVhiwbly5dKlqFHcoShIkNBmEQpMbA/tDyJ7ljECZNMAhTMygx\nk1BjaUIzvakyJYeKIAxkK0L9BFmWJ3y6pmk2Gg1BEFRVjVolBoMwNYMSMwk1liY3E1JleL7sMZny\nBGGyaqPR6/U4jtM0rdfrDYfDdrvNcVy32w2eqWka/GkwGDSbTY7jIglSFKXT6aSjNIIg5abZHErS\niGYdhdPpdIJtgooiq3rr0O7OzUAXRZFl2Var5asFBjP6brcLOTCKokAHVEo24CEIEglFIY5zOwkS\nGUlWQRiO43y7ijiOCxZ7GdkdKdJT2+rq6srKShJVqwIlHdwpMZNQY2nqZjLM7ZhMqZYnLly4ULQK\nO+S3ZDqyXl3y7kiLi4tYE6ZOUGImocbSjMzkeaJppNUihpHF8HF44IEHilZhh6yCMC6wfRSabASr\nsdu2HfT1kbojTU9Pz87OJtWyClDSE5ISMwk1lmZnJsPseHZVLUVAZn5+vmgVdsi8O5JlWYZhBIMt\n7mgxFX+dJ5988rd+67do6I507ty50rY0SnGoc+fOFatVbneFz9KStDRKfahf/MVfzFQrjjNFkfzy\nL6998pN/mYOBE7oj/d3f/R0pB3l0RwJkWWYYxpeun7w70vnz58+ePfvwww+HPL+62LZNw/yOEjMJ\nNZbmY6bjEFXdaYpdCKZpfuUrX/nsZz9bjPg7ybY7khdN0wRB8H3GybsjYRCmZlBiJqHG0nzMLENA\npsJBmCRwHBfclJSwO9La2hpuR6oTlJhJqLE0TzMVhYhiYRkyly9fLkDqKHJ161BU3ftK8u5IMzMz\nc3Nz6ehXbnByVzMosTRnMzmusAyZgwcP5i1yDFm59Uaj4Zt0t1othmGCyewkWXek+fn5xcXFxPpW\nAErKmVFiJqHG0vzNhICMbeddRubo0aO5yhtPVm5dURRVVZeXl1VVhQPYdxo8s91u67ouy7KqqtD+\nNFLAHYMwNYMSMwk1lhZlJgRk8vTs5QnCZJW3znFcp9OxbRuC6YqijGuRwTBMt9uF9PYJp40DgzA1\ngxIzCTWWFmgmzA9lmYyaT6ZPeYIw2W5HYlk25IcaOyUGgzA1gxIzCTWWFmsmxxGOy8mz1z8Ikxvr\n6+v9fr9oLfIAG9XXDEosLdxMSSIcl0c0ZnV1NXMZ4ai8W9/a2trY2ChaizzArgs1gxJLy2CmJBGW\nJVkH+a9fv56tgNBg0zsEQagA3HpGBdaoa3oHFRUmLIgn6Y6EQZiaQYmZhBpLy2OmJBHHyXDOTlcQ\nBqrkGGO2B+i6rqqqoijtdpthGEEQIg2OQZiaQYmZhBpLS2WmohDLysqzlycIk7lbN02TYZhxQRLY\nf9TpdDiOYxgGyn5FSnQ9dOgQ1luvE5SYSaixtGxmahqxrEz2oJ46dSr9QWORuVtXVXVCvCl5d6Tt\n7e3Nzc1EKlaEUs16soMSMwk1lpbQTPDsUUpPhWJ9fT3lEeOSrVtXVXVkmXWX5N2R+v0+7jKtE5SY\nSaixtJxmNpvEMFL27JcuXUpzuARk6Nah4YaiKBPOsW076PQjbUs7evTo6dOn4+hXNUqyyJ41lJhJ\nqLG0tGam7tnPnj2b2ljJyLA70uTwiztaVAV89Hq9D3/4w9CvhOO4X/mVX/EefOlLX4JnQMuy4MC2\nbdDTPQCLvAeEENM0QTf3wB0hi6Esy/INZdu2b6hLly4FhzJNM8ZQcFDOoWDKU6BWud0VPkszvcEK\nHOqLX/xiCbWCA0Uhjz1248KFfw8/FMdxI72NoihXr14lJWEYkXa7zY9BFEX3tE6n4/svz/PB0Xie\n73Q6wRfD6/Poo48+/vjjEY2oJIqiFK1CHlBi5pAaS0tu5mAw9Diq+HQ6nbe//e0pDJQGWXVH0nWd\n53n3RxIqeVmWNbIwbxIwCFMzKDGTUGNpyc1kGMJxxDRJ8h2N5QnCZFXqi+d5t3wjIcRxHHiQCfpx\ny7J86Y+RuiMhCIIkQVFIo5GCWy8R+TwUjAvCdLtd3+vtdluSpPAjYxCmZlBi5pAaSythZrs91LRE\nI5QqCFNwqa/k3ZEWFxdxO1KdoMRMQo2llTBTFIllkYQJHA888EBK6iQl23rrhBDLsqDSi23bsiwH\nGyS1221BEKDNqWmaUbsjTU9Pz87OpqpyScGuCzWDEkurYqYoklaLJFkImJ+fT0+dRGQ+W4c2Sd1u\ndzAYjGx6B92RJEmCrJiov+2rq6srKyspKVtq1Jw7MxYEJWYSaiytipkQW08yYb9w4UJayiQk89l6\nSGKnxGAQpmZQYiahxtIKmSlJiSbs5QnCVL6NBgZhagYlZhJqLK2QmaBp7Bo2FAVhsmZtbQ1rwtQJ\nSswk1FhaLTMVJX57vMuXL6eqS3wq79ZnZmbm5uaK1iIPKjTrSQIlZhJqLK2WmQxDeJ7E6/xx8ODB\ntNWJSYax9eBSybjudKZp6roO9RYURZlQ8THI/Pz84uJiIkUrAiWN/Sgxk1BjaeXMlCQiCHF2Jx09\nejQDdeKQ4Wy91Wr5isaM/N1O2B0JgzA1gxIzCTWWVtFMRYnTQak8QZhsM2F2/aGG/Ufdbhdm6Iqi\nOI6j63r41XMMwtQMSswk1FhaRTN5njQaRBRJlMBBiYIwBcfWk3dHwiBMzaDETEKNpRU1U1FIqxXt\nLVQEYVzcGsdBkndHWl9f7/f7ifSrCOXp4J4plJhJqLG0omaCW4qU7Li6upqRMlHJNggjCILjOAzD\nOI7Dsqymab7lUNu2gz/mkZ7atra2NjY2UtC19JSwJ2QWUGImocbS6popSUTXI+xOun79epbqRCDD\n7kjNZlPTtG63C8UDeJ6XZTk4WiL1CdnY2PijP/oj6Fdy/Pjxhx56yHvwsY99DCYLuq7DAWTdeA9s\n24akHfeAEKKqKtyO7oE7QhZD6bruG8o0Td9QPM8Hh1JVNcZQcFDOoeBnvkCtcrsrfJZmeoMVOJRb\noLtUWoUZyrbNy5cvWdYdQx0/fnykt1EUpTzR4KnhcBjpDYZhjIt9MwzTbrcnvFcQBE3TvJNxQRAU\nRfFN2AVB6HQ6IfU5d+7cmTNn3v/+94c8v7qYplnRMGUkKDGTUGNppc10HKKqZFQtKz+maX7uc5/7\ny7/8y+yV2p2suiONhOM427a9bj15dyQMwtQMSswk1FhaaTMj9U6qcBAmdYK9kCJ1Rzp06BCW+qoT\nlJhJqLG06mZChD0Mp06dyliXsOTq1g3D8E3PRVH0LZRDymP4Mbe3tzc3N9PRr9xUetYTHkrMJNRY\nWgMzJYmEmWqur69nr0sosnLrgiAYhuF9RZZlX4o6SaM7Ur/fx12mdYISMwk1ltbATJ4nYaLFly5d\nyl6XUEReMg2J4ziqqrrtp2EOPrIHueM4giBwHOd2R4rk1iGjoLprMgiC1ADIBhzp4vInq7x1hmE0\nTXMcBwLlEwp4QXcky7Icx4la54tQFoSp4j7sqFBiJqHGUkrMJDQEYQCGYWAqvauz5jguzGlBMAhT\nMygxk1BjKSVmkjIFYYrPhEnID3/4w6JVyIlICUKVpqLbzaNCyQdKiZml6qhcebeOIAiCeKm8W79x\n48bVq1eL1iIPKDGzPO3bs4aSD5QSMwkhTz/9dNEq7JBTBUdZlgVBaDQaI5/ITNNsNBqCIKiqGrVK\nzN13333kyJGUNC01lJhZnvbtWUPJB0qJmYSQe+65p2gVdsi2giMhRJZl27YlSRJFceTGBCi3BLVi\ndF0XBKHb7YYff8+ePfv27UtP3/JCiZnlad+eNZR8oJSYSQiZnp4uWoUdsnXrjUaD4zjt9Uo5wTyn\n5N2RMAhTMy5cuEDJLgRKPlBKzCSUBGEgsUlRlAnnJO+OhEGYmoFBmJpBiZmEkiCMruuT6/SSNLoj\nYRCmZmAQpmZQYiYpUxAm2yVTlmWhAj0UEgieYNt2cAtSpD1pN2/efOaZZxJpWRGuXbtWtAp5UJ72\n7VlDyQdKiZmEkOeff75oFXaIPFt36wEEYRjGnXqbpskwjK7rrVYLSgLIshys95K8O9KhQ4c0TfvS\nl75ECHnppZemp6f37NnjHhw4cIBhmIWFhWvXru3bt29hYWEwGNy6devIkSPuwa1bt65du3bixAn3\ngBBy9erVI0eO7Nu3zz1wR8hiKLj1vUMNBoPBYOAd6saNG8ePH/cNdfXq1YWFhahDwUE5hyKE/OEf\n/uHv/u7vFqVVbnfFyy+/LAhCPjdYgUM9++yzDz30UNm0ij3UxYsX9+/fH/Q2hJAHH3wwoTdLi8hu\n3e0IFcTXHclxHMMw3OVQURSXl5d5nk+3QET4PkoIgiA0kFV3JI7jLMvq9XrB5VBvkbPk3ZEQBEEQ\nL1nF1iEg45uYj5ynJ+yOhCAIgnjJcMmU4zhfzSbLsnyePXl3JARBEMRLhm5dUZRWq+Uuitq2reu6\nz2Un746EIAiCeMmqOxJgWVaj0QBXbpqmpmnBYHrC7kgIgiCIl2zdOgBhlsk7wqE7Ejj3rPVBEASp\nMXm4dQRBECQ3Kl9vHUEQBPGCbh1BEKRWoFtHEASpFejWEQRBagW6dQRBkFqBbh1BEKRWoFtHEASp\nFejWEQRBagW6dQRBkFqBbh1BEKRWoFtHEASpFejWEQRBagW6dQRBkFqBbh1BEKRWoFtHEASpFejW\nEQRBagW6dQRBkFqBbh1BEKRWoFtHEASpFejWEQRBagW6dQRBkFqBbh1BEKRWoFtHEASpFejWEQRB\nagW6dQRBkFqBbh1BEKRWoFtHEASpFaVw66ZpNhoNQRBUVXUcp2h1EARBKkzxbl3XdVVVFUVpt9sM\nwwiCULRGCIIgFWZqOBwWKN5xnOXl5W63yzAMvKKqKsuykiQVqBWCIEh1KXi2bhiGKIquTyeESJKk\n63qBKiEIglSagt26bdscx3lfYVkWw+sIgiCxKd6te6fqAMuyhSiDIAhSA/YWKz75xPytb/21p576\n5bvuuosQ8uqrV6anv3/XXd9/6aWXpqen9+zZc+DAAYZhFhYWrl27tm/fvoWFhcFgcOvWrSNHjrgH\nt27dunbt2okTJ9wDQsjVq1ePHDmyb98+98AdAQ5u3rw5HA737NmTfCg4IIR4hxoMBoPBwDsUHLzh\nDW9gGObFF190x1xYWIg3lE+ryUOtrq6eOHHi5ZdfTj5UJK2++93vHj58+N57783aQN9d8a//+q/D\n4fCtb31r1I8y4Q324osvwkec4r0aZqjhcLi4uLi2tpa1gb6her3ez//8z+dgoG+ob33rW6dOnYox\n1MWLF/fv308IcZ0MHLz22mvvec97vvCFLyR0aKlQsFtPztTUD3/nd65qmkYIMU1i28S2CSHEcQjD\nEJ4nLEuymP2/973vffDBBz/ykY+kP3Qp5aqqyvM8z/MoF+WmiCAInU4nZ6FZyDVN0zTNFAdMQsFu\n3RdYj8GBAwfgd5gQ4rsnHYdYFjEMAo8E6Tr6o0ePnj59Ouko1ZG7urqav1CUW3u5g8GAKrn5UPxs\n3bIs3xzBsqzwb3/11Vdv3bo18k/gxL1jw1xe13dcfBJHv729vbm5Ge09aVCU3OvXr+cvFOXWXu64\nL29d5eZDwW5dFEXYi+S+AimP4Ue4efMmREjDAO57sqNnWcJx/ol/kH6/f+XKlfB6pkVRck+dOpW/\nUJRbe7lHjhyhSm4+lCIIo+s67D9yHKfVakGgPCR33313kk9opKO3LKKqXiUJx/mn84uLiydPnowt\nNzZFyV1fX89fKMqtvVycrWdB8UGYdrstCIJlWQzDmKYpSVKkgPuePXv27duXoj7g6L0PDKZJDIPY\nNoFUTIYhHEemp6dnZ2dTlBuSouReunTpkUceQbkoN13CP2rXQ24+FO/WGYbpdruWZTmOoyhKMI19\nMjdu3Lh69WpGugG+AL1lEdsmX/vaf/zOd+Zg6RviNolXf0Oxurq6srKSf8bC2bNnc5aIcmmQ6+Y7\nUCI3H4p360DslJiEQZgYgAd/8sl/PHv27MMPE0KIae6k3JDsEyuLCsIgCFIVyuLWY7O0tFTIrtRf\n+7Vfc+VOTqwkqU7nvXLzhOd5lItyUydSfkQN5OZDwRUck1PU9hzYehAyGOLdJ0VGrdNmJBdBkHyA\n7UjNZrNoRQipwWz94MGDhw8fzl9upKmNzwlb1h3JNrAGG9JRF1UwR1VVQkghGxEzApZzJptTP6tD\n4ianIVWk8m59fn5+cXExf7lJ3KsvIONLqZzs5bNw641Gw1uch2EYKHnvlcXzvGEYpmnWxsHJsrzr\n3Kp+VofEMAxCCHr2ilJ5t762tnblypX8v3WwFTZ58QMSSKmc7OVTlOsiSRJ8jd2Ao23bjUZDkiT3\ni83zfHlKXiRH13WGYXa9bWpmdXiazSbcAEUrgsSh8m59ZmZmbm4uf7lREzHDM9nLHzjwlvvv3043\nmdJ1Xl43J4ri8vKyr8lJbWi1WiUJg5YTjuNYlsVQTEUpvpdpQgoMwuQT5gYX32zu/HvnO9/U79+r\nqgT+wT6pLGAYRhTFYH0e6Cc+NTW1vLzcarWCb4Stwo1GY2lpaWpqqtFojJzwWpbVaDSgUm6j0TAM\nY2RoIYJDAAAf2UlEQVRXLBC3tLQEp6UydzZN03GckbkQIG5hYWFpaUmW5XGFo8NoZRiGIAhwoSBG\nLwiCIAheM1utFrwI1xneIggCPDxFEhfytJCXnRAiiiL2Kasqw4rzwQ9+8DOf+Uz+crvdbrfbLVxu\npzNsNoeKMpSkoaIMO53hYBBnWEVRFEXxvShJkleWoigcx4miOBgMhsPhYDCQJCn4rm6322w23Tf2\nej2O4zqdjvecXq/Hsmy73Xb/K0kSz/O+oTRN43neHarb7YqiGJQYFUVRJEkKvq5pGsdxrjiQHrwy\nYbRSFEUUxV6vNxwOB4MBSCSEdDodeNF9b6fT4Tiu3W7Dxez1er1ez31v+IsQ5rSQl939KyFkEO9+\noo9Op5P8zkyLygdhKMe7Axby5d0JNOyKih2uabVawZaEDMO02233uNlsLi8v+6IZHMd538WyrKIo\nvlVHKOjmzpdZlm02m6q3EA8htm3rut7tdr0jQ6mJhGuYlmUFFydAXKfTcYNOUMdieXnZW4oujFam\naVqW5ZbzhgsFTzY+tUENhmFg/daNeLgXOeRFCHlamMvuAg+jwQKrYTBNUpUlCUnKZNtgsVTerR86\ndKiQXZfpLlqmItdXiBjSKN2n+ZEFy7wYhuGGXGzb5nnedS7jpDMMY4+JAbkRAIZhgtF5URQFQWAY\nhuM48BoMw/hKvOm67vWnLoqiGIaR0K0HIzAQR/apynGcL7gcRisobeQ7QZKkcQ6UEOL16VHFhT8t\nzGX3wvN8PLfuq7eB5Ezl3fr6+nq/389fLriz/LPIw8v1pVGaJnEjpbAZyjcGz/Ous0viNA3DUFUV\n1twIIY7jBF0Dy7LdblfXdcMw4LEAwh1euyzLGhm7T6geGXP1xvkvn6MPo9XIoSavPI/7QENehJCn\nhbnsPrBffBWpvFvf2tra2NjIX25Rt3tsub6JPNQ2gPry8HqYhL9dsW271Wp1u12vFxvZD4xhGF+d\nfUEQvG+EmXIWm7xHPmSEfPwKoxXHccGPKd4HF/IihL9Wu152L5ZlYSZMFckwE0YNMHkFXxAEVVWj\n3v0FBmEKicOkIpfjiKKQZpNoGuF5YlnkwoV3XbjwrlaLROlMNYKRoYzgZxoMR4iiyLKsN/GG5/mM\nMjFGul2O43z5J4DvxTBaSZLUarV8IsbNpicT8iKEPC3MZXdxHMdxnKKCjUgSMnTrrVaLv5ORz3q6\nrkODpHa7zTCMIAiRpBQYhBkXVq6WXI4jkkTOnv37s2f/XhR3cuRVlcRz8UEf0Wq1gt7EsiyfGwK7\nfPtaWZaVZdn3Xl3X47lI78jBGYYoirDw6H1RlmXfT1QYrWCPrpunaFlW8Pzwqoa5CCFPC3PZXQzD\ncCNpSLXIsNTX1NTugzuOs7y87H0GVFUVvhUhpVSi1FfJ5QqC4A3ZcxzXbDZte6dCGSGEYYhpqrZt\nkNdTLAghkPIMiRbeCIAsy24KDfyV53lZllmW1TQNRDQaDZZl3SQN27Yty4IUPZ9u8JAHr0OYHtRL\nuElqaWkpKM5xHFVV3cg4rHzatm0YBsuy3kb1YbQyTdMwDNu2YQeAKIq+b4Rt2+CILctiWdZ9r6Io\nPsVCXoRdTwt/2eFkjuNGrsQiQUpV6qtgt67rum3b3msB29a9qVqTUVWVwkpMOeNz8bvmTbqPFBzH\nTfC/4HoIIZCbsetpJL3fM1g29HpqF1f5ybJiaBXmG5FQXJjTwlx227aXl5d7vV4t9xhnAXVu3TTN\ncV9vSJnwLfUsLS3BVogwnD9//uzZsw9DP4scgchp/jd9UXJdfC5eFKua9jtywp4dUecrxSLLcjC5\nE5lAqdx6tpkwgiA4jsMwjOM48Azu80eQYuV7V6RwXr/fv3LlSgq6RgTmO0WVGCvw6YRliftlt+3b\nGTWQaVOhuV273c4tnQnC6xUKaEQKhCKlI+q21MFg0BmDbzN9s9n07pPWNE0URd9oPM/7tpXDi+H1\neeSRRxYXFyEOc+zYsTNnzngPPvrRj8L4mqbBQafT0TTNe9Dr9WDXr3swHA5hG7f3wB0hi6E0TfMN\n5e5F9o3pG0pRlIRDpUWnc0cNA6Tb7brJAqIoBu9zpCp4v+DHjh3jef7MmTNw4HqbBx988JFHHila\n0x0iB2Em1Aby7iwfiSAI7qKZ+0pwgUgQhJFBz5FgECYfxuVLBHGc2wXIRu57ykhuuqBclBuJUgVh\nIic4wrxjJJN9OiGE4zhfcl7yrNgCgzAjs33rKjd8CjnDEEnaqTfJccQwiCwTVY1ZJKSoIoIoF+VW\nl+J3mQZ3WkdyW4uLi1gTJgfiRVrdAgYwhYf8dSg1HPJ5o6gIL8pFudUlV7duGIZv1UgURdiL5D0n\n0n7x6enp2dnZ1FQMTVG5KEXJTfjEClN4AMpMunULJv9OFbUdBuWi3OqS1S7TYCsAWZaDrXZg7uk+\nEEEHhkg/pKurqysrK4n1jczIOic1ljuh+mBUOG6nboG7qVWWyah9+ynLjQTKRbnVJau8dd+GPZiD\nj1xPcBxHEARIbId9fZHcOi6Z5kPWS1uGQSyLOA7huDtCNLVZUkO59ZZbqiXTDLcjEc9+tsm7DQkh\nlmVBXaGoDgt3mdYMt7okhOBr/ayM1IdSufVse5lCrVee53d11lDXP8YkFIMw+ZDbQ6s3RGMY5PTp\nb6tq0rqSMaAtOIBy60TxmTAJOXjw4OHDh/OXS9tST/7PQyxLFIVw3AZkScIUnudJBgXYR1DU8x/K\nrbfcfMg2CJMDGIShB8chprkzc4cQPIKUBIqCMDmwtraG25FyoAzbRqCyGGx0IoTIMpFlouski8ou\nZbAX5dZPbj5UPggzMzMzNzeXv1zMWy9WrijuzNYhC56kXU6ybPai3HrIzQcMwiA1AVJobHsnPlPr\nry1SOjAIkyYYhMmH8j8sQwpNu014nug6UdVE8Zny24tyqyg3HyofhEEQH24hGjc+E6kKDYJUHQzC\nIPUH4jME/TuSGRiESZP19fV+v5+/XLfjJSVyC9kDlZZciM80m4RhdilBk67cGKDcesvNh8oHYba2\ntjY2NvKXm1u/tJLILeS3JHW5bv6MWyV4XP57PexFuWWTmw8YhEGoBkqMEdzfhCQDgzBpgkGYfKjr\nw3JwfxPEZ+pqL8otVm4+JArCGIZh2/aEfuqmaeq6DqUZFUUZt5Um5GkjwSBMPtT+YRniM24Xp8uX\nf5JhdmnxkQW1v86Uy82HOEEY8MJQsNhxnHHtpHVd13UdelLrum4YRrfbjX3aODAIg2SBt9G2KBbg\n35FqUfkgDMMwiqJ0u90J/S6gz1Gn04ES6oqi8Dwf3AIQ8rQJbG9vb25uxrAiIY7jFDJxLkoubbMq\nx7Gh0bai7LRwyqc+MG3XmTa5+RDHrXMct2ujZGiH5A2nSJIU9NchT5tAv9/HXaY5QNtuQFcudGFt\nNokkEdMkjQZptUh2PqFwe1FuDUiUCWOaJsy1g39SVZXjOF+z6aWlpV6vF+O0CWAQBskZ296Jz2D/\nJsSlVEGYrPLWbdsOutpg1bSQp03gxo0bTz755Li/xuiiFxLsZUqtXOjvQbLx7yW0F+V6GZdCs7Ky\nsr29nUyp1LgdhHEcxxxDjKf+kPHf5GHiH/zgB5///OdBz49//ONf+cpXvAef/exn4WPQdR0OYL3X\ne2DbNnTAcg8IIaqqQvTNPXBHgAPLsv78z/88laHI6+vGPvV8Q8HB17/+dcuyvGPGHsqn1eShHnvs\nsbSGiqTV+973vnwM9B186lOf2vWjZFnCMLoomqJIPvKRb//6rz/TapEvfvGbSe4KUCndezXMUPBi\nKkNF0sq9r7I20DfU+973vnhDffzjHx/pbS5evLi1tUXKwe0gjGEY4+JNDMO02+3g6xOCMIIgwPqn\n70XfySFPmwAGYZDygPEZailpEEYURTG9bXa7rqlGOg1BKkGm8RkECUmGu0yDoZuRwZyQp41jdXV1\nZWUlqm7JgR9neuTS1iE+oVzw75pGRJEYBpHlsPkzFbUX5ZaKrNy6KIo+7wO5jPFOm8Di4uLJkydj\n6xmbMFmedZI7YY8Cyp1A0L9Pzn+vur0otwxk5dbB9bjBeth2FLyUIU+bwPT09OzsbAoaR4RhmELa\nihYll7aek6nLdf075L+P8++1sRflFkgct95qtQRBEARBVVXLsoTX8Z3Wbrd1XZdlWVVVQRAkSRo5\nzQx52jgwCJMPtD0sZyfX9e8j96/Wz16Umz+ZF+a1LAtqeE2eY4Y8Lcj58+fPnj378MMPJ1MzMpi3\njnLTwq0/4zjk535u7bHHDuUj1wsN1zlTuSXNhMmIrFNiCgzC5C+0QLm0PSznKRfqEwCGcUhViePs\n1H/P7dOm4TqXQW4+VL7e+traGtaEyQHaancUJddx9GaTaBrhONJqRUihSQht17neNWEq3/RuZmZm\nbm4uf7k4W0e5mcrluJ1qwG4KPMNkWCK4cHspkZsP2PQOQaqBbRPT3Jm5cxzh+fxCNMiulCq2jkGY\nmGAQBuXmLJdld0oEg+tIN0RTQntrKTcfMAgTEwzCoNwC5UKLPvJ6iAYq5iXpsl1ye2sjNx8wCIMg\ndcBxiGkS0yQMQ1iW8DwWoskVDMKkyfr6er/fz1+ubduF9M0qSm4he6BQbnhgQVXTSLNJOG6n0bYs\n357LZyQ3IbTJzYfKB2G2trY2Njbyl1tIQ9EC5dLWc7LSct0sGkKIaZJWizgOYRjC82TcY22l7a2Q\n3HzAIAyCUAFEaSyLOM5OlAarYqcIBmHSBIMw+UDbw3L95EKUBvY6ieLtcjStFrGsGtpbTrn5gEGY\nmGAQBuVWVy7kSgKWRUyT/N3fHTHNAtZa632diwKDMAiC7AAuHmYOmE4TiVIFYRLN1g3DsG1bgTZf\nAYKlL8f5X2gFCxUcFUWJlJq9vb29ubkZ/vy0wAqOKLd+cn1rrbBlB+qOZeTiabvO+RAntm6aZqPR\nWF5eNgxjQoiq1WrxdzLyOuq6rqqqoijtdpthmGDd9sn0+33cZZoDtO0GRLk8v7OjFeqOuRmTEIvP\nTm4+1HuXaZwgDLgVjuNM02y1Wp1OZ/TQU7sP7jjO8vJyt9t1p5+qqrIsG75BEgZhECRP3NI0uyZN\nUkXlgzAp9tKEzqXekIIkSY1GI7xbxyBMPtD2sIxyx+FdboWkSTfaCjGcSOqX394qkkeCo2ma4/I3\nbNv2/UiwLBsp2QODMPlA28Myyg2DmzQJ/xjmjlhNmBzCatlbFRJlwuwahOF53nEchmEcx2FZVtM0\n3zQTJua+EIogCOPGDHL+/Pk3v/nNp0+fHvnXGF30EARJjreMMKlRJeFxq4krKyvPPvvsE088kbM+\nI7k9W3ccxxxDvOlhs9nUNK3b7XY6nW63y/O8LMu+c5JnYa+vr3/jG98APT/3uc99/etf9x788z//\nMySoWpYFB7ZtgznuARjuPSCeJwz3wB0hi6HcObh3TN9QcOAbyjRNHCrdocpzV1R6KNs2RdFpNgnP\nm4riMAz5z/+5f+7cdVUlv/3b/S9+8TnHqaSBn/vc50Z6m4sXL25tbZGSMHyddrvNj0EUxeEoOp0O\nz/Mj/zQSnud7vZ7vlU6nEzwt/JiPPvro448/Hv78tOh0OkHNayxXUZT8haLcWsodDIbt9lBRhooy\nfPvb/7HZHOZ/R6dub6fTKeqzC3J7yVQURTF2teZwcBznW6lIvvq6uLh48uTJhIPEIMV140rIDb+I\njXJR7mQgIv96vfi3EHLHuivL7uyEypSirnM+FF88wLIsX2w9Usxnenp6dnY2baV2B9tooFyUm5Zc\nr4+1rJ16NQDD7MTls5BbV3It9WUYhm+yKYqibwkCUh7Dj7m6urqyspKOflGA+Bo9coN7hlEuys1C\nLsfd7u3XbBJRJI6zk10Dtcnc8gbpyq0TWc3WBUGQJMnroGVZ9qWok9dDCrquwzOR4zitVkvTtPCC\nMAiTDzQEB1BuCeVCTMZ1JI5DLOt2BXkSK1k+jNxKEyfBsdVquevC3sRzb1ai4ziqqroBFpiDj9yC\n5TiOIAiQiWiapiRJka447jJFEJpxi8gDLHtHF5Ec1SjRLlOy66JqEgaDAWRuDAaDyWdCHuSupwX5\n4Ac/+JnPfCaugvHpdrvdbpceuZqm5S8U5aLcqHS7Q03bSbORpCGk2QT9SupyS5oJkwUMw4ScR8eO\nLczMzMzNzcV7bxJwyRTlotwSyvVN1W17J2jjO6HeS6ZYbx1BEIrwBW0g04bjku6ALVUQpvJN79bW\n1rAmTA7QVrsD5dZVLs8TRSEsq3szbVqtnTQbVSW6nmbl4UIoPm89IRiEyYfaPKSjXJTrlevLtCGv\nT+cN4/Yr8ZJtCgSDMAiCIGOBlEo3buM4t5NtvFOsUgVhKj9bX19f7/f7+cuFqkD5zzWKkmuaZiG/\nnSgX5RYrN9gqxLaJbd+xDMuyZH19IW0d41N5t761tbWxsZG/3OS1J6sll7YO8SgX5Y4jWLXGssh/\n+297y+PZMQiDIAiSlFIFYSqfCVNgEKaQiUZRcgspRINyUW7N5OZD5d36j370o+effz5/ud///vf/\n/d//nR653/nOdwqJ/6Dcesv9p3/6p/yFFig3Hyrv1q9du/bqq6/mL/fJJ5985ZVX6JF748aNQvLl\nUW695X7729/OX2iBcvOh8m791VdfvXXrVv5yt7e3Nzc36ZG7vr6ev1CUW3u5hXx5C5SbD5V36zdv\n3rx27Vr+cvv9fiG7W4uSe+nSpfyFotzayy3ky1ug3HyImeDoOI6u67DswPO8JEkjdz+apqnruuM4\nHMcpijJuh2TI00Zy4MCBEydOxLMiCUePHj19+jQ9cs+ePZu/UJRbe7mFfHkLlJsPcWbrjuM0Gg3H\ncTRN0zQNCqYH11t0XVdVVVGUdrvNMIwgCCNHC3naODAIkw+0BQdQbj5gECYL4rh1VVUlSWo2myzL\nsizbbDZFUWx5N1293ueo0+lAfwxFUXieD5b1CXnaBDAIkw+0BQdQbj5gECYL4rh1lmV97UYVRfEt\no0M7JG84RZKkoL8OedoEMAiTD7QFB1BuPmAQJgviuHVFUXyv2LbtC4h7m+EBLMsGAzUhT0MQBEFC\nkk5NmEaj4ds1a9t2cEN/sEBVyNMm8MILL3z+85+H46tXrx45cmTfvn3uwZ49e+65557FxcUrV67M\nzc0tLi72+/2NjY2TJ0+6B5ubm1euXDl9+rR7QAhZWVk5efLk7Oyse+COAAff+c53VldXr1y5knwo\nOCCEeIfq9/vPPfecdyg4ePLJJx3H8Y55+PDheEP5tJo8VLvdfuMb35jKUJG0+vKXvzw1NUUIydpA\n313x1a9+FaYXUT/KhDfY1772tVu3bvX7/RTv1TBDfe1rX3vjG9+Yg4G+oS5dumSaZg4G+oa6ePHi\nV7/61RhDfeMb34CZvs/bPP3007Ozs+EdV6bcduuO44zbj8AwzISmdLIsS5Lk884hZ9zJJ+aPPvro\nX/3VX/31X/81IeTGjRt33333nj173IMjR4686U1vmp+fX1tbm5mZmZ+fX19f39raWl1ddQ+2t7f7\n/f6LL77oHhBCVldXn3322enpaffAHQEOjh079uMf/xice8Kh4ADO9Kp3/fp171Bw8Ja3vGXPnj0X\nL150xzx48GC8oXxaTR7qvvvue/bZZ23bTj5UJK1OnDixtrZmmmbWBvruire97W0vvPCCaZpRP8qE\nN9gDDzzwwgsvfPOb30zxXg0z1AMPPPDss88GL1rqBvqGOnXqlGmaORjoG+r++++/cOFCjKH+5V/+\n5Xvf+95Ib/PYY48l9GZpcdutQ5bhyJMYhmm32yP/JMsyx3GSJGWiXQg+8YlPfOITnyhKOoIgSNm4\n7dZFUfQthE4G8holSRrp00O2nI7dmRpBEAQZScxdppN9OhAM6YwM8oQ8DUEQBAlDzO1IQZ/uqxYr\niqKv9CXkMvqGCnkagiAIEpLIbh22mCqK4punLy8ve/8L0RU3WA/bjoJT+5CnIQiCICGJ3B3JNE1Z\nloM5iKZp+oaCST1sHzVNc1zEJuRpCIIgSBgyb3pnWRbU8JpcwCvkaQiCIMhkKt/LFEEQBPFS+Xrr\nCIIgiBd06wiCILUC3TqCIEitQLeOIAhSK9CtIwiC1Ap06wiCILUinXrrRZGkt3UOAxqGYdt2sOtI\ndnJDtg7PVC7LsoqiTC6an/oHZ9u2russy07ey5aWXFVVfa/wPB/sHJC6XO+AcHdBq8hxJfNSkavr\nuq80COBrsZC6XFe6aZohh0pRrmVZYDj09azYfpphZdE0jeO4brc7GAyazSbHcSUZsNPpiKLIcZwo\nijzP5yZ3MBjwPK8oSq/X6/V68G0fDAZZy+31ehzHaZrW6/WGw2G73YZhs5brRRRFaIQ74ZwU5RJC\nOncCtmctF4D2Bu12ezgcwmedqVye5zsBJriOFO2FPee9Xm8wGGiaxrJsPtcZuit3Op3hcNhutyfL\nLSFVdeuDwYBlWa/PUhRF07QyDNjtdsGpdTqdXd16inIlSYKvukuz2VQUJWu5rr3eV0RRzFquS6fT\nkSRp8tVOV274+VDq9oqi2Gw285QbFJfP59vtdn0fKHzQWcsdDoc+Px7UpORU1a1rmuZzWDBnLM+A\nw3BuPUW5I7/t4xTIwl4vLMvmJhceSiZf7XTlhnfr6crVNG2cP81Uro8JHjNFuYqiBCclOdxXvV4v\neCOJolihCXtVl0xT721dVLPsFOWGaR2ehdwgpmmOCzSnLldVVVEUdw19ZmQvhH1zk6vr+oSIdnZy\nfZimOa56dopygwsGwcGzkDtyIYFlWV8J8TJTYbce/CZH6m2d9YBlkNtoNMYtIWYh17Is0zRVVW21\nWuO8T7pyHccxTTPMonTq9gqCsLy83Gq1BEFoNBrjPEjqclmWtW1bVVVVVSc0nMnuvgKvN2G6kJZc\nURRt2261Wu7IsiyP+6xTlMvzvM+zO44DC9QxRiuEqrr11OfROUzMc5Y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323 "png": 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2ZvTl5+jRo0WrkCu02YtuPQtKEYTRdR32HzmO02q1NE0LP0L9gjCTmZ+fX1xcjPquoJdv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\noLWOJ5MfPqUANvwAgmKwshJ2uRwAAAAASUVORK5CYII=\n"
324 }
324 }
325 ],
325 ],
326 "prompt_number": 24
326 "prompt_number": 24
327 },
327 },
328 {
328 {
329 "cell_type": "code",
329 "cell_type": "code",
330 "collapsed": false,
330 "collapsed": false,
331 "input": [
331 "input": [
332 "%%octave -s 600,200 -f png\n",
332 "%%octave -s 600,200 -f png\n",
333 "\n",
333 "\n",
334 "subplot(121);\n",
334 "subplot(121);\n",
335 "[x, y] = meshgrid(0:0.1:3);\n",
335 "[x, y] = meshgrid(0:0.1:3);\n",
336 "r = sin(x - 0.5).^2 + cos(y - 0.5).^2;\n",
336 "r = sin(x - 0.5).^2 + cos(y - 0.5).^2;\n",
337 "surf(x, y, r);\n",
337 "surf(x, y, r);\n",
338 "\n",
338 "\n",
339 "subplot(122);\n",
339 "subplot(122);\n",
340 "sombrero()"
340 "sombrero()"
341 ],
341 ],
342 "language": "python",
342 "language": "python",
343 "metadata": {},
343 "metadata": {},
344 "outputs": [
344 "outputs": [
345 {
345 {
346 "output_type": "display_data",
346 "output_type": "display_data",
347 "png": 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o+c0vuXcdy7LFFxupVMr3KaNMwCoUiqSkpLCwsNDQ0MDAwN27dxe/TpNTDoRQ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\ns3n9+vUisv3wfpQNkODt4PXr14V+Iv7gt1BKvSiIhn/4jWdr6ZrKWAsw5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347 "png": 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o+c0vuXcdy7LFFxupVMr3KaNMwCoUiqSkpLCwsNDQ0MDAwN27dxe/TpNTDoRQ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\n5/72haEj66ampq5du4bTAEiSlH7OEZt6qIr97kcT3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348 }
348 }
349 ],
349 ],
350 "prompt_number": 25
350 "prompt_number": 25
351 },
351 },
352 {
352 {
353 "cell_type": "heading",
353 "cell_type": "heading",
354 "level": 2,
354 "level": 2,
355 "metadata": {},
355 "metadata": {},
356 "source": [
356 "source": [
357 "Future work"
357 "Future work"
358 ]
358 ]
359 },
359 },
360 {
360 {
361 "cell_type": "markdown",
361 "cell_type": "markdown",
362 "metadata": {},
362 "metadata": {},
363 "source": [
363 "source": [
364 "After the next release of `oct2py`, we'll add the ability to interrupt/kill the current Octave session without restarting the Python kernel."
364 "After the next release of `oct2py`, we'll add the ability to interrupt/kill the current Octave session without restarting the Python kernel."
365 ]
365 ]
366 }
366 }
367 ],
367 ],
368 "metadata": {}
368 "metadata": {}
369 }
369 }
370 ]
370 ]
371 } No newline at end of file
371 }
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@@ -1,674 +1,673 b''
1 =============
1 =============
2 0.13 Series
2 0.13 Series
3 =============
3 =============
4
4
5 Release 0.13
5 Release 0.13
6 ============
6 ============
7
7
8 IPython 0.13 contains several major new features, as well as a large amount of
8 IPython 0.13 contains several major new features, as well as a large amount of
9 bug and regression fixes. The previous version (0.12) was released on December
9 bug and regression fixes. The previous version (0.12) was released on December
10 19 2011, and in this development cycle we had:
10 19 2011, and in this development cycle we had:
11
11
12 - ~6 months of work.
12 - ~6 months of work.
13 - 373 pull requests merged.
13 - 373 pull requests merged.
14 - 742 issues closed (non-pull requests).
14 - 742 issues closed (non-pull requests).
15 - contributions from 62 authors.
15 - contributions from 62 authors.
16 - 1760 commits.
16 - 1760 commits.
17 - a diff of 114226 lines.
17 - a diff of 114226 lines.
18
18
19 The amount of work included in this release is so large, that we can only cover
19 The amount of work included in this release is so large, that we can only cover
20 here the main highlights; please see our :ref:`detailed release statistics
20 here the main highlights; please see our :ref:`detailed release statistics
21 <issues_list_013>` for links to every issue and pull request closed on GitHub
21 <issues_list_013>` for links to every issue and pull request closed on GitHub
22 as well as a full list of individual contributors.
22 as well as a full list of individual contributors.
23
23
24
24
25 Major Notebook improvements: new user interface and more
25 Major Notebook improvements: new user interface and more
26 --------------------------------------------------------
26 --------------------------------------------------------
27
27
28 The IPython Notebook, which has proven since its release to be wildly popular,
28 The IPython Notebook, which has proven since its release to be wildly popular,
29 has seen a massive amount of work in this release cycle, leading to a
29 has seen a massive amount of work in this release cycle, leading to a
30 significantly improved user experience as well as many new features.
30 significantly improved user experience as well as many new features.
31
31
32 The first user-visible change is a reorganization of the user interface; the
32 The first user-visible change is a reorganization of the user interface; the
33 left panel has been removed and was replaced by a real menu system and a
33 left panel has been removed and was replaced by a real menu system and a
34 toolbar with icons. Both the toolbar and the header above the menu can be
34 toolbar with icons. Both the toolbar and the header above the menu can be
35 collapsed to leave an unobstructed working area:
35 collapsed to leave an unobstructed working area:
36
36
37 .. image:: ../_static/ipy_013_notebook_spectrogram.png
37 .. image:: ../_static/ipy_013_notebook_spectrogram.png
38 :width: 460px
38 :width: 460px
39 :alt: New user interface for Notebook
39 :alt: New user interface for Notebook
40 :align: center
40 :align: center
41 :target: ../_static/ipy_013_notebook_spectrogram.png
41 :target: ../_static/ipy_013_notebook_spectrogram.png
42
42
43 The notebook handles very long outputs much better than before (this was a
43 The notebook handles very long outputs much better than before (this was a
44 serious usability issue when running processes that generated massive amounts
44 serious usability issue when running processes that generated massive amounts
45 of output). Now, in the presence of outputs longer than ~100 lines, the
45 of output). Now, in the presence of outputs longer than ~100 lines, the
46 notebook will automatically collapse to a scrollable area and the entire left
46 notebook will automatically collapse to a scrollable area and the entire left
47 part of this area controls the display: one click in this area will expand the
47 part of this area controls the display: one click in this area will expand the
48 output region completely, and a double-click will hide it completely. This
48 output region completely, and a double-click will hide it completely. This
49 figure shows both the scrolled and hidden modes:
49 figure shows both the scrolled and hidden modes:
50
50
51 .. image:: ../_static/ipy_013_notebook_long_out.png
51 .. image:: ../_static/ipy_013_notebook_long_out.png
52 :width: 460px
52 :width: 460px
53 :alt: Scrolling and hiding of long output in the notebook.
53 :alt: Scrolling and hiding of long output in the notebook.
54 :align: center
54 :align: center
55 :target: ../_static/ipy_013_notebook_long_out.png
55 :target: ../_static/ipy_013_notebook_long_out.png
56
56
57 .. note::
57 .. note::
58
58
59 The auto-folding of long outputs is disabled in Firefox due to bugs in its
59 The auto-folding of long outputs is disabled in Firefox due to bugs in its
60 scrolling behavior. See :ghpull:`2047` for details.
60 scrolling behavior. See :ghpull:`2047` for details.
61
61
62 Uploading notebooks to the dashboard is now easier: in addition to drag and
62 Uploading notebooks to the dashboard is now easier: in addition to drag and
63 drop (which can be finicky sometimes), you can now click on the upload text and
63 drop (which can be finicky sometimes), you can now click on the upload text and
64 use a regular file dialog box to select notebooks to upload. Furthermore, the
64 use a regular file dialog box to select notebooks to upload. Furthermore, the
65 notebook dashboard now auto-refreshes its contents and offers buttons to shut
65 notebook dashboard now auto-refreshes its contents and offers buttons to shut
66 down any running kernels (:ghpull:`1739`):
66 down any running kernels (:ghpull:`1739`):
67
67
68 .. image:: ../_static/ipy_013_dashboard.png
68 .. image:: ../_static/ipy_013_dashboard.png
69 :width: 460px
69 :width: 460px
70 :alt: Improved dashboard
70 :alt: Improved dashboard
71 :align: center
71 :align: center
72 :target: ../_static/ipy_013_dashboard.png
72 :target: ../_static/ipy_013_dashboard.png
73
73
74
74
75 Cluster management
75 Cluster management
76 ~~~~~~~~~~~~~~~~~~
76 ~~~~~~~~~~~~~~~~~~
77
77
78 The notebook dashboard can now also start and stop clusters, thansk to a new
78 The notebook dashboard can now also start and stop clusters, thansk to a new
79 tab in the dashboard user interface:
79 tab in the dashboard user interface:
80
80
81 .. image:: ../_static/ipy_013_dashboard_cluster.png
81 .. image:: ../_static/ipy_013_dashboard_cluster.png
82 :width: 460px
82 :width: 460px
83 :alt: Cluster management from the notebook dashboard
83 :alt: Cluster management from the notebook dashboard
84 :align: center
84 :align: center
85 :target: ../_static/ipy_013_dashboard_cluster.png
85 :target: ../_static/ipy_013_dashboard_cluster.png
86
86
87 This interface allows, for each profile you have configured, to start and stop
87 This interface allows, for each profile you have configured, to start and stop
88 a cluster (and optionally override the default number of engines corresponding
88 a cluster (and optionally override the default number of engines corresponding
89 to that configuration). While this hides all error reporting, once you have a
89 to that configuration). While this hides all error reporting, once you have a
90 configuration that you know works smoothly, it is a very convenient interface
90 configuration that you know works smoothly, it is a very convenient interface
91 for controlling your parallel resources.
91 for controlling your parallel resources.
92
92
93
93
94 New notebook format
94 New notebook format
95 ~~~~~~~~~~~~~~~~~~~
95 ~~~~~~~~~~~~~~~~~~~
96
96
97 The notebooks saved now use version 3 of our format, which supports heading
97 The notebooks saved now use version 3 of our format, which supports heading
98 levels as well as the concept of 'raw' text cells that are not rendered as
98 levels as well as the concept of 'raw' text cells that are not rendered as
99 Markdown. These will be useful with converters_ we are developing, to pass raw
99 Markdown. These will be useful with converters_ we are developing, to pass raw
100 markup (say LaTeX). That conversion code is still under heavy development and
100 markup (say LaTeX). That conversion code is still under heavy development and
101 not quite ready for prime time, but we welcome help on this front so that we
101 not quite ready for prime time, but we welcome help on this front so that we
102 can merge it for full production use as soon as possible.
102 can merge it for full production use as soon as possible.
103
103
104 .. _converters: https://github.com/ipython/nbconvert
104 .. _converters: https://github.com/ipython/nbconvert
105
105
106 .. note::
106 .. note::
107
107
108 v3 notebooks can *not* be read by older versions of IPython, but we provide
108 v3 notebooks can *not* be read by older versions of IPython, but we provide
109 a `simple script`_ that you can use in case you need to export a v3
109 a `simple script`_ that you can use in case you need to export a v3
110 notebook to share with a v2 user.
110 notebook to share with a v2 user.
111
111
112 .. _simple script: https://gist.github.com/1935808
112 .. _simple script: https://gist.github.com/1935808
113
113
114
114
115 JavaScript refactoring
115 JavaScript refactoring
116 ~~~~~~~~~~~~~~~~~~~~~~
116 ~~~~~~~~~~~~~~~~~~~~~~
117
117
118 All the client-side JavaScript has been decoupled to ease reuse of parts of the
118 All the client-side JavaScript has been decoupled to ease reuse of parts of the
119 machinery without having to build a full-blown notebook. This will make it much
119 machinery without having to build a full-blown notebook. This will make it much
120 easier to communicate with an IPython kernel from existing web pages and to
120 easier to communicate with an IPython kernel from existing web pages and to
121 integrate single cells into other sites, without loading the full notebook
121 integrate single cells into other sites, without loading the full notebook
122 document-like UI. :ghpull:`1711`.
122 document-like UI. :ghpull:`1711`.
123
123
124 This refactoring also enables the possibility of writing dynamic javascript
124 This refactoring also enables the possibility of writing dynamic javascript
125 widgets that are returned from Python code and that present an interactive view
125 widgets that are returned from Python code and that present an interactive view
126 to the user, with callbacks in Javascript executing calls to the Kernel. This
126 to the user, with callbacks in Javascript executing calls to the Kernel. This
127 will enable many interactive elements to be added by users in notebooks.
127 will enable many interactive elements to be added by users in notebooks.
128
128
129 An example of this capability has been provided as a proof of concept in
129 An example of this capability has been provided as a proof of concept in
130 :file:`docs/examples/widgets` that lets you directly communicate with one or more
130 :file:`docs/examples/widgets` that lets you directly communicate with one or more
131 parallel engines, acting as a mini-console for parallel debugging and
131 parallel engines, acting as a mini-console for parallel debugging and
132 introspection.
132 introspection.
133
133
134
134
135 Improved tooltips
135 Improved tooltips
136 ~~~~~~~~~~~~~~~~~
136 ~~~~~~~~~~~~~~~~~
137
137
138 The object tooltips have gained some new functionality. By pressing tab several
138 The object tooltips have gained some new functionality. By pressing tab several
139 times, you can expand them to see more of a docstring, keep them visible as you
139 times, you can expand them to see more of a docstring, keep them visible as you
140 fill in a function's parameters, or transfer the information to the pager at the
140 fill in a function's parameters, or transfer the information to the pager at the
141 bottom of the screen. For the details, look at the example notebook
141 bottom of the screen. For the details, look at the example notebook
142 :file:`01_notebook_introduction.ipynb`.
142 :file:`01_notebook_introduction.ipynb`.
143
143
144 .. figure:: ../_static/ipy_013_notebook_tooltip.png
144 .. figure:: ../_static/ipy_013_notebook_tooltip.png
145 :width: 460px
145 :width: 460px
146 :alt: Improved tooltips in the notebook.
146 :alt: Improved tooltips in the notebook.
147 :align: center
147 :align: center
148 :target: ../_static/ipy_013_notebook_tooltip.png
148 :target: ../_static/ipy_013_notebook_tooltip.png
149
149
150 The new notebook tooltips.
150 The new notebook tooltips.
151
151
152 Other improvements to the Notebook
152 Other improvements to the Notebook
153 ----------------------------------
153 ----------------------------------
154
154
155 These are some other notable small improvements to the notebook, in addition to
155 These are some other notable small improvements to the notebook, in addition to
156 many bug fixes and minor changes to add polish and robustness throughout:
156 many bug fixes and minor changes to add polish and robustness throughout:
157
157
158 * The notebook pager (the area at the bottom) is now resizeable by dragging its
158 * The notebook pager (the area at the bottom) is now resizeable by dragging its
159 divider handle, a feature that had been requested many times by just about
159 divider handle, a feature that had been requested many times by just about
160 anyone who had used the notebook system. :ghpull:`1705`.
160 anyone who had used the notebook system. :ghpull:`1705`.
161
161
162 * It is now possible to open notebooks directly from the command line; for
162 * It is now possible to open notebooks directly from the command line; for
163 example: ``ipython notebook path/`` will automatically set ``path/`` as the
163 example: ``ipython notebook path/`` will automatically set ``path/`` as the
164 notebook directory, and ``ipython notebook path/foo.ipynb`` will further
164 notebook directory, and ``ipython notebook path/foo.ipynb`` will further
165 start with the ``foo.ipynb`` notebook opened. :ghpull:`1686`.
165 start with the ``foo.ipynb`` notebook opened. :ghpull:`1686`.
166
166
167 * If a notebook directory is specified with ``--notebook-dir`` (or with the
167 * If a notebook directory is specified with ``--notebook-dir`` (or with the
168 corresponding configuration flag ``NotebookManager.notebook_dir``), all
168 corresponding configuration flag ``NotebookManager.notebook_dir``), all
169 kernels start in this directory.
169 kernels start in this directory.
170
170
171 * Fix codemirror clearing of cells with ``Ctrl-Z``; :ghpull:`1965`.
171 * Fix codemirror clearing of cells with ``Ctrl-Z``; :ghpull:`1965`.
172
172
173 * Text (markdown) cells now line wrap correctly in the notebook, making them
173 * Text (markdown) cells now line wrap correctly in the notebook, making them
174 much easier to edit :ghpull:`1330`.
174 much easier to edit :ghpull:`1330`.
175
175
176 * PNG and JPEG figures returned from plots can be interactively resized in the
176 * PNG and JPEG figures returned from plots can be interactively resized in the
177 notebook, by dragging them from their lower left corner. :ghpull:`1832`.
177 notebook, by dragging them from their lower left corner. :ghpull:`1832`.
178
178
179 * Clear ``In []`` prompt numbers on "Clear All Output". For more
179 * Clear ``In []`` prompt numbers on "Clear All Output". For more
180 version-control-friendly ``.ipynb`` files, we now strip all prompt numbers
180 version-control-friendly ``.ipynb`` files, we now strip all prompt numbers
181 when doing a "Clear all output". This reduces the amount of noise in
181 when doing a "Clear all output". This reduces the amount of noise in
182 commit-to-commit diffs that would otherwise show the (highly variable) prompt
182 commit-to-commit diffs that would otherwise show the (highly variable) prompt
183 number changes. :ghpull:`1621`.
183 number changes. :ghpull:`1621`.
184
184
185 * The notebook server now requires *two* consecutive ``Ctrl-C`` within 5
185 * The notebook server now requires *two* consecutive ``Ctrl-C`` within 5
186 seconds (or an interactive confirmation) to terminate operation. This makes
186 seconds (or an interactive confirmation) to terminate operation. This makes
187 it less likely that you will accidentally kill a long-running server by
187 it less likely that you will accidentally kill a long-running server by
188 typing ``Ctrl-C`` in the wrong terminal. :ghpull:`1609`.
188 typing ``Ctrl-C`` in the wrong terminal. :ghpull:`1609`.
189
189
190 * Using ``Ctrl-S`` (or ``Cmd-S`` on a Mac) actually saves the notebook rather
190 * Using ``Ctrl-S`` (or ``Cmd-S`` on a Mac) actually saves the notebook rather
191 than providing the fairly useless browser html save dialog. :ghpull:`1334`.
191 than providing the fairly useless browser html save dialog. :ghpull:`1334`.
192
192
193 * Allow accessing local files from the notebook (in urls), by serving any local
193 * Allow accessing local files from the notebook (in urls), by serving any local
194 file as the url ``files/<relativepath>``. This makes it possible to, for
194 file as the url ``files/<relativepath>``. This makes it possible to, for
195 example, embed local images in a notebook. :ghpull:`1211`.
195 example, embed local images in a notebook. :ghpull:`1211`.
196
196
197
197
198 Cell magics
198 Cell magics
199 -----------
199 -----------
200
200
201 We have completely refactored the magic system, finally moving the magic
201 We have completely refactored the magic system, finally moving the magic
202 objects to standalone, independent objects instead of being the mixin class
202 objects to standalone, independent objects instead of being the mixin class
203 we'd had since the beginning of IPython (:ghpull:`1732`). Now, a separate base
203 we'd had since the beginning of IPython (:ghpull:`1732`). Now, a separate base
204 class is provided in :class:`IPython.core.magic.Magics` that users can subclass
204 class is provided in :class:`IPython.core.magic.Magics` that users can subclass
205 to create their own magics. Decorators are also provided to create magics from
205 to create their own magics. Decorators are also provided to create magics from
206 simple functions without the need for object orientation. Please see the
206 simple functions without the need for object orientation. Please see the
207 :ref:`magic` docs for further details.
207 :ref:`magic` docs for further details.
208
208
209 All builtin magics now exist in a few subclasses that group together related
209 All builtin magics now exist in a few subclasses that group together related
210 functionality, and the new :mod:`IPython.core.magics` package has been created
210 functionality, and the new :mod:`IPython.core.magics` package has been created
211 to organize this into smaller files.
211 to organize this into smaller files.
212
212
213 This cleanup was the last major piece of deep refactoring needed from the
213 This cleanup was the last major piece of deep refactoring needed from the
214 original 2001 codebase.
214 original 2001 codebase.
215
215
216 We have also introduced a new type of magic function, prefixed with `%%`
216 We have also introduced a new type of magic function, prefixed with `%%`
217 instead of `%`, which operates at the whole-cell level. A cell magic receives
217 instead of `%`, which operates at the whole-cell level. A cell magic receives
218 two arguments: the line it is called on (like a line magic) and the body of the
218 two arguments: the line it is called on (like a line magic) and the body of the
219 cell below it.
219 cell below it.
220
220
221 Cell magics are most natural in the notebook, but they also work in the
221 Cell magics are most natural in the notebook, but they also work in the
222 terminal and qt console, with the usual approach of using a blank line to
222 terminal and qt console, with the usual approach of using a blank line to
223 signal cell termination.
223 signal cell termination.
224
224
225 For example, to time the execution of several statements::
225 For example, to time the execution of several statements::
226
226
227 %%timeit x = 0 # setup
227 %%timeit x = 0 # setup
228 for i in range(100000):
228 for i in range(100000):
229 x += i**2
229 x += i**2
230
230
231 This is particularly useful to integrate code in another language, and cell
231 This is particularly useful to integrate code in another language, and cell
232 magics already exist for shell scripts, Cython, R and Octave. Using ``%%script
232 magics already exist for shell scripts, Cython, R and Octave. Using ``%%script
233 /usr/bin/foo``, you can run a cell in any interpreter that accepts code via
233 /usr/bin/foo``, you can run a cell in any interpreter that accepts code via
234 stdin.
234 stdin.
235
235
236 Another handy cell magic makes it easy to write short text files: ``%%file
236 Another handy cell magic makes it easy to write short text files: ``%%file
237 ~/save/to/here.txt``.
237 ~/save/to/here.txt``.
238
238
239 The following cell magics are now included by default; all those that use
239 The following cell magics are now included by default; all those that use
240 special interpreters (Perl, Ruby, bash, etc.) assume you have the requisite
240 special interpreters (Perl, Ruby, bash, etc.) assume you have the requisite
241 interpreter installed:
241 interpreter installed:
242
242
243 * ``%%!``: run cell body with the underlying OS shell; this is similar to
243 * ``%%!``: run cell body with the underlying OS shell; this is similar to
244 prefixing every line in the cell with ``!``.
244 prefixing every line in the cell with ``!``.
245
245
246 * ``%%bash``: run cell body under bash.
246 * ``%%bash``: run cell body under bash.
247
247
248 * ``%%capture``: capture the output of the code in the cell (and stderr as
248 * ``%%capture``: capture the output of the code in the cell (and stderr as
249 well). Useful to run codes that produce too much output that you don't even
249 well). Useful to run codes that produce too much output that you don't even
250 want scrolled.
250 want scrolled.
251
251
252 * ``%%file``: save cell body as a file.
252 * ``%%file``: save cell body as a file.
253
253
254 * ``%%perl``: run cell body using Perl.
254 * ``%%perl``: run cell body using Perl.
255
255
256 * ``%%prun``: run cell body with profiler (cell extension of ``%prun``).
256 * ``%%prun``: run cell body with profiler (cell extension of ``%prun``).
257
257
258 * ``%%python3``: run cell body using Python 3.
258 * ``%%python3``: run cell body using Python 3.
259
259
260 * ``%%ruby``: run cell body using Ruby.
260 * ``%%ruby``: run cell body using Ruby.
261
261
262 * ``%%script``: run cell body with the script specified in the first line.
262 * ``%%script``: run cell body with the script specified in the first line.
263
263
264 * ``%%sh``: run cell body using sh.
264 * ``%%sh``: run cell body using sh.
265
265
266 * ``%%sx``: run cell with system shell and capture process output (cell
266 * ``%%sx``: run cell with system shell and capture process output (cell
267 extension of ``%sx``).
267 extension of ``%sx``).
268
268
269 * ``%%system``: run cell with system shell (``%%!`` is an alias to this).
269 * ``%%system``: run cell with system shell (``%%!`` is an alias to this).
270
270
271 * ``%%timeit``: time the execution of the cell (extension of ``%timeit``).
271 * ``%%timeit``: time the execution of the cell (extension of ``%timeit``).
272
272
273 This is what some of the script-related magics look like in action:
273 This is what some of the script-related magics look like in action:
274
274
275 .. image:: ../_static/ipy_013_notebook_script_cells.png
275 .. image:: ../_static/ipy_013_notebook_script_cells.png
276 :width: 460px
276 :width: 460px
277 :alt: Cluster management from the notebook dashboard
277 :alt: Cluster management from the notebook dashboard
278 :align: center
278 :align: center
279 :target: ../_static/ipy_013_notebook_script_cells.png
279 :target: ../_static/ipy_013_notebook_script_cells.png
280
280
281 In addition, we have also a number of :ref:`extensions <extensions_overview>`
281 In addition, we have also a number of :ref:`extensions <extensions_overview>`
282 that provide specialized magics. These typically require additional software
282 that provide specialized magics. These typically require additional software
283 to run and must be manually loaded via ``%load_ext <extension name>``, but are
283 to run and must be manually loaded via ``%load_ext <extension name>``, but are
284 extremely useful. The following extensions are provided:
284 extremely useful. The following extensions are provided:
285
285
286 **Cython magics** (extension :ref:`cythonmagic <extensions_cythonmagic>`)
286 **Cython magics** (extension :ref:`cythonmagic <extensions_cythonmagic>`)
287 This extension provides magics to automatically build and compile Python
287 This extension provides magics to automatically build and compile Python
288 extension modules using the Cython_ language. You must install Cython
288 extension modules using the Cython_ language. You must install Cython
289 separately, as well as a C compiler, for this to work. The examples
289 separately, as well as a C compiler, for this to work. The examples
290 directory in the source distribution ships with a full notebook
290 directory in the source distribution ships with a full notebook
291 demonstrating these capabilities:
291 demonstrating these capabilities:
292
292
293 .. image:: ../_static/ipy_013_notebook_cythonmagic.png
293 .. image:: ../_static/ipy_013_notebook_cythonmagic.png
294 :width: 460px
294 :width: 460px
295 :alt: Cython magic
295 :alt: Cython magic
296 :align: center
296 :align: center
297 :target: ../_static/ipy_013_notebook_cythonmagic.png
297 :target: ../_static/ipy_013_notebook_cythonmagic.png
298
298
299 .. _cython: http://cython.org
299 .. _cython: http://cython.org
300
300
301 **Octave magics** (extension :ref:`octavemagic <extensions_octavemagic>`)
301 **Octave magics** (extension :ref:`octavemagic <extensions_octavemagic>`)
302 This extension provides several magics that support calling code written in
302 This extension provides several magics that support calling code written in
303 the Octave_ language for numerical computing. You can execute single-lines
303 the Octave_ language for numerical computing. You can execute single-lines
304 or whole blocks of Octave code, capture both output and figures inline
304 or whole blocks of Octave code, capture both output and figures inline
305 (just like matplotlib plots), and have variables automatically converted
305 (just like matplotlib plots), and have variables automatically converted
306 between the two languages. To use this extension, you must have Octave
306 between the two languages. To use this extension, you must have Octave
307 installed as well as the oct2py_ and h5py_ packages. The examples
307 installed as well as the oct2py_ package. The examples
308 directory in the source distribution ships with a full notebook
308 directory in the source distribution ships with a full notebook
309 demonstrating these capabilities:
309 demonstrating these capabilities:
310
310
311 .. image:: ../_static/ipy_013_notebook_octavemagic.png
311 .. image:: ../_static/ipy_013_notebook_octavemagic.png
312 :width: 460px
312 :width: 460px
313 :alt: Octave magic
313 :alt: Octave magic
314 :align: center
314 :align: center
315 :target: ../_static/ipy_013_notebook_octavemagic.png
315 :target: ../_static/ipy_013_notebook_octavemagic.png
316
316
317 .. _octave: http://www.gnu.org/software/octave
317 .. _octave: http://www.gnu.org/software/octave
318 .. _oct2py: http://pypi.python.org/pypi/oct2py
318 .. _oct2py: http://pypi.python.org/pypi/oct2py
319 .. _h5py: http://code.google.com/p/h5py
320
319
321 **R magics** (extension :ref:`rmagic <extensions_rmagic>`)
320 **R magics** (extension :ref:`rmagic <extensions_rmagic>`)
322 This extension provides several magics that support calling code written in
321 This extension provides several magics that support calling code written in
323 the R_ language for statistical data analysis. You can execute
322 the R_ language for statistical data analysis. You can execute
324 single-lines or whole blocks of R code, capture both output and figures
323 single-lines or whole blocks of R code, capture both output and figures
325 inline (just like matplotlib plots), and have variables automatically
324 inline (just like matplotlib plots), and have variables automatically
326 converted between the two languages. To use this extension, you must have
325 converted between the two languages. To use this extension, you must have
327 R installed as well as the rpy2_ package that bridges Python and R. The
326 R installed as well as the rpy2_ package that bridges Python and R. The
328 examples directory in the source distribution ships with a full notebook
327 examples directory in the source distribution ships with a full notebook
329 demonstrating these capabilities:
328 demonstrating these capabilities:
330
329
331 .. image:: ../_static/ipy_013_notebook_rmagic.png
330 .. image:: ../_static/ipy_013_notebook_rmagic.png
332 :width: 460px
331 :width: 460px
333 :alt: R magic
332 :alt: R magic
334 :align: center
333 :align: center
335 :target: ../_static/ipy_013_notebook_rmagic.png
334 :target: ../_static/ipy_013_notebook_rmagic.png
336
335
337 .. _R: http://www.r-project.org
336 .. _R: http://www.r-project.org
338 .. _rpy2: http://rpy.sourceforge.net/rpy2.html
337 .. _rpy2: http://rpy.sourceforge.net/rpy2.html
339
338
340
339
341 Tab completer improvements
340 Tab completer improvements
342 --------------------------
341 --------------------------
343
342
344 Useful tab-completion based on live inspection of objects is one of the most
343 Useful tab-completion based on live inspection of objects is one of the most
345 popular features of IPython. To make this process even more user-friendly, the
344 popular features of IPython. To make this process even more user-friendly, the
346 completers of both the Qt console and the Notebook have been reworked.
345 completers of both the Qt console and the Notebook have been reworked.
347
346
348 The Qt console comes with a new ncurses-like tab completer, activated by
347 The Qt console comes with a new ncurses-like tab completer, activated by
349 default, which lets you cycle through the available completions by pressing tab,
348 default, which lets you cycle through the available completions by pressing tab,
350 or select a completion with the arrow keys (:ghpull:`1851`).
349 or select a completion with the arrow keys (:ghpull:`1851`).
351
350
352 .. figure:: ../_static/ipy_013_qtconsole_completer.png
351 .. figure:: ../_static/ipy_013_qtconsole_completer.png
353 :width: 460px
352 :width: 460px
354 :alt: ncurses-like completer, with highlighted selection.
353 :alt: ncurses-like completer, with highlighted selection.
355 :align: center
354 :align: center
356 :target: ../_static/ipy_013_qtconsole_completer.png
355 :target: ../_static/ipy_013_qtconsole_completer.png
357
356
358 The new improved Qt console's ncurses-like completer allows to easily
357 The new improved Qt console's ncurses-like completer allows to easily
359 navigate thought long list of completions.
358 navigate thought long list of completions.
360
359
361 In the notebook, completions are now sourced both from object introspection and
360 In the notebook, completions are now sourced both from object introspection and
362 analysis of surrounding code, so limited completions can be offered for
361 analysis of surrounding code, so limited completions can be offered for
363 variables defined in the current cell, or while the kernel is busy
362 variables defined in the current cell, or while the kernel is busy
364 (:ghpull:`1711`).
363 (:ghpull:`1711`).
365
364
366
365
367 We have implemented a new configurable flag to control tab completion on
366 We have implemented a new configurable flag to control tab completion on
368 modules that provide the ``__all__`` attribute::
367 modules that provide the ``__all__`` attribute::
369
368
370 IPCompleter.limit_to__all__= Boolean
369 IPCompleter.limit_to__all__= Boolean
371
370
372 This instructs the completer to honor ``__all__`` for the completion.
371 This instructs the completer to honor ``__all__`` for the completion.
373 Specifically, when completing on ``object.<tab>``, if True: only those names
372 Specifically, when completing on ``object.<tab>``, if True: only those names
374 in ``obj.__all__`` will be included. When False [default]: the ``__all__``
373 in ``obj.__all__`` will be included. When False [default]: the ``__all__``
375 attribute is ignored. :ghpull:`1529`.
374 attribute is ignored. :ghpull:`1529`.
376
375
377
376
378 Improvements to the Qt console
377 Improvements to the Qt console
379 ------------------------------
378 ------------------------------
380
379
381 The Qt console continues to receive improvements and refinements, despite the
380 The Qt console continues to receive improvements and refinements, despite the
382 fact that it is by now a fairly mature and robust component. Lots of small
381 fact that it is by now a fairly mature and robust component. Lots of small
383 polish has gone into it, here are a few highlights:
382 polish has gone into it, here are a few highlights:
384
383
385 * A number of changes were made to the underlying code for easier integration
384 * A number of changes were made to the underlying code for easier integration
386 into other projects such as Spyder_ (:ghpull:`2007`, :ghpull:`2024`).
385 into other projects such as Spyder_ (:ghpull:`2007`, :ghpull:`2024`).
387
386
388 * Improved menus with a new Magic menu that is organized by magic groups (this
387 * Improved menus with a new Magic menu that is organized by magic groups (this
389 was made possible by the reorganization of the magic system
388 was made possible by the reorganization of the magic system
390 internals). :ghpull:`1782`.
389 internals). :ghpull:`1782`.
391
390
392 * Allow for restarting kernels without clearing the qtconsole, while leaving a
391 * Allow for restarting kernels without clearing the qtconsole, while leaving a
393 visible indication that the kernel has restarted. :ghpull:`1681`.
392 visible indication that the kernel has restarted. :ghpull:`1681`.
394
393
395 * Allow the native display of jpeg images in the qtconsole. :ghpull:`1643`.
394 * Allow the native display of jpeg images in the qtconsole. :ghpull:`1643`.
396
395
397 .. _spyder: https://code.google.com/p/spyderlib
396 .. _spyder: https://code.google.com/p/spyderlib
398
397
399
398
400
399
401 Parallel
400 Parallel
402 --------
401 --------
403
402
404 The parallel tools have been improved and fine-tuned on multiple fronts. Now,
403 The parallel tools have been improved and fine-tuned on multiple fronts. Now,
405 the creation of an :class:`IPython.parallel.Client` object automatically
404 the creation of an :class:`IPython.parallel.Client` object automatically
406 activates a line and cell magic function ``px`` that sends its code to all the
405 activates a line and cell magic function ``px`` that sends its code to all the
407 engines. Further magics can be easily created with the :meth:`.Client.activate`
406 engines. Further magics can be easily created with the :meth:`.Client.activate`
408 method, to conveniently execute code on any subset of engines. :ghpull:`1893`.
407 method, to conveniently execute code on any subset of engines. :ghpull:`1893`.
409
408
410 The ``%%px`` cell magic can also be given an optional targets argument, as well
409 The ``%%px`` cell magic can also be given an optional targets argument, as well
411 as a ``--out`` argument for storing its output.
410 as a ``--out`` argument for storing its output.
412
411
413 A new magic has also been added, ``%pxconfig``, that lets you configure various
412 A new magic has also been added, ``%pxconfig``, that lets you configure various
414 defaults of the parallel magics. As usual, type ``%pxconfig?`` for details.
413 defaults of the parallel magics. As usual, type ``%pxconfig?`` for details.
415
414
416 The exception reporting in parallel contexts has been improved to be easier to
415 The exception reporting in parallel contexts has been improved to be easier to
417 read. Now, IPython directly reports the remote exceptions without showing any
416 read. Now, IPython directly reports the remote exceptions without showing any
418 of the internal execution parts:
417 of the internal execution parts:
419
418
420 .. image:: ../_static/ipy_013_par_tb.png
419 .. image:: ../_static/ipy_013_par_tb.png
421 :width: 460px
420 :width: 460px
422 :alt: Improved parallel exceptions.
421 :alt: Improved parallel exceptions.
423 :align: center
422 :align: center
424 :target: ../_static/ipy_013_par_tb.png
423 :target: ../_static/ipy_013_par_tb.png
425
424
426 The parallel tools now default to using ``NoDB`` as the storage backend for
425 The parallel tools now default to using ``NoDB`` as the storage backend for
427 intermediate results. This means that the default usage case will have a
426 intermediate results. This means that the default usage case will have a
428 significantly reduced memory footprint, though certain advanced features are
427 significantly reduced memory footprint, though certain advanced features are
429 not available with this backend. For more details, see :ref:`parallel_db`.
428 not available with this backend. For more details, see :ref:`parallel_db`.
430
429
431 The parallel magics now display all output, so you can do parallel plotting or
430 The parallel magics now display all output, so you can do parallel plotting or
432 other actions with complex display. The ``px`` magic has now both line and cell
431 other actions with complex display. The ``px`` magic has now both line and cell
433 modes, and in cell mode finer control has been added about how to collate
432 modes, and in cell mode finer control has been added about how to collate
434 output from multiple engines. :ghpull:`1768`.
433 output from multiple engines. :ghpull:`1768`.
435
434
436 There have also been incremental improvements to the SSH launchers:
435 There have also been incremental improvements to the SSH launchers:
437
436
438 * add to_send/fetch steps for moving connection files around.
437 * add to_send/fetch steps for moving connection files around.
439
438
440 * add SSHProxyEngineSetLauncher, for invoking to `ipcluster engines` on a
439 * add SSHProxyEngineSetLauncher, for invoking to `ipcluster engines` on a
441 remote host. This can be used to start a set of engines via PBS/SGE/MPI
440 remote host. This can be used to start a set of engines via PBS/SGE/MPI
442 *remotely*.
441 *remotely*.
443
442
444 This makes the SSHLauncher usable on machines without shared filesystems.
443 This makes the SSHLauncher usable on machines without shared filesystems.
445
444
446 A number of 'sugar' methods/properties were added to AsyncResult that are
445 A number of 'sugar' methods/properties were added to AsyncResult that are
447 quite useful (:ghpull:`1548`) for everday work:
446 quite useful (:ghpull:`1548`) for everday work:
448
447
449 * ``ar.wall_time`` = received - submitted
448 * ``ar.wall_time`` = received - submitted
450 * ``ar.serial_time`` = sum of serial computation time
449 * ``ar.serial_time`` = sum of serial computation time
451 * ``ar.elapsed`` = time since submission (wall_time if done)
450 * ``ar.elapsed`` = time since submission (wall_time if done)
452 * ``ar.progress`` = (int) number of sub-tasks that have completed
451 * ``ar.progress`` = (int) number of sub-tasks that have completed
453 * ``len(ar)`` = # of tasks
452 * ``len(ar)`` = # of tasks
454 * ``ar.wait_interactive()``: prints progress
453 * ``ar.wait_interactive()``: prints progress
455
454
456 Added :meth:`.Client.spin_thread` / :meth:`~.Client.stop_spin_thread` for
455 Added :meth:`.Client.spin_thread` / :meth:`~.Client.stop_spin_thread` for
457 running spin in a background thread, to keep zmq queue clear. This can be used
456 running spin in a background thread, to keep zmq queue clear. This can be used
458 to ensure that timing information is as accurate as possible (at the cost of
457 to ensure that timing information is as accurate as possible (at the cost of
459 having a background thread active).
458 having a background thread active).
460
459
461 Set TaskScheduler.hwm default to 1 instead of 0. 1 has more
460 Set TaskScheduler.hwm default to 1 instead of 0. 1 has more
462 predictable/intuitive behavior, if often slower, and thus a more logical
461 predictable/intuitive behavior, if often slower, and thus a more logical
463 default. Users whose workloads require maximum throughput and are largely
462 default. Users whose workloads require maximum throughput and are largely
464 homogeneous in time per task can make the optimization themselves, but now the
463 homogeneous in time per task can make the optimization themselves, but now the
465 behavior will be less surprising to new users. :ghpull:`1294`.
464 behavior will be less surprising to new users. :ghpull:`1294`.
466
465
467
466
468 Kernel/Engine unification
467 Kernel/Engine unification
469 -------------------------
468 -------------------------
470
469
471 This is mostly work 'under the hood', but it is actually a *major* achievement
470 This is mostly work 'under the hood', but it is actually a *major* achievement
472 for the project that has deep implications in the long term: at last, we have
471 for the project that has deep implications in the long term: at last, we have
473 unified the main object that executes as the user's interactive shell (which we
472 unified the main object that executes as the user's interactive shell (which we
474 refer to as the *IPython kernel*) with the objects that run in all the worker
473 refer to as the *IPython kernel*) with the objects that run in all the worker
475 nodes of the parallel computing facilities (the *IPython engines*). Ever since
474 nodes of the parallel computing facilities (the *IPython engines*). Ever since
476 the first implementation of IPython's parallel code back in 2006, we had wanted
475 the first implementation of IPython's parallel code back in 2006, we had wanted
477 to have these two roles be played by the same machinery, but a number of
476 to have these two roles be played by the same machinery, but a number of
478 technical reasons had prevented that from being true.
477 technical reasons had prevented that from being true.
479
478
480 In this release we have now merged them, and this has a number of important
479 In this release we have now merged them, and this has a number of important
481 consequences:
480 consequences:
482
481
483 * It is now possible to connect any of our clients (qtconsole or terminal
482 * It is now possible to connect any of our clients (qtconsole or terminal
484 console) to any individual parallel engine, with the *exact* behavior of
483 console) to any individual parallel engine, with the *exact* behavior of
485 working at a 'regular' IPython console/qtconsole. This makes debugging,
484 working at a 'regular' IPython console/qtconsole. This makes debugging,
486 plotting, etc. in parallel scenarios vastly easier.
485 plotting, etc. in parallel scenarios vastly easier.
487
486
488 * Parallel engines can always execute arbitrary 'IPython code', that is, code
487 * Parallel engines can always execute arbitrary 'IPython code', that is, code
489 that has magics, shell extensions, etc. In combination with the ``%%px``
488 that has magics, shell extensions, etc. In combination with the ``%%px``
490 magics, it is thus extremely natural for example to send to all engines a
489 magics, it is thus extremely natural for example to send to all engines a
491 block of Cython or R code to be executed via the new Cython and R magics. For
490 block of Cython or R code to be executed via the new Cython and R magics. For
492 example, this snippet would send the R block to all active engines in a
491 example, this snippet would send the R block to all active engines in a
493 cluster::
492 cluster::
494
493
495 %%px
494 %%px
496 %%R
495 %%R
497 ... R code goes here
496 ... R code goes here
498
497
499 * It is possible to embed not only an interactive shell with the
498 * It is possible to embed not only an interactive shell with the
500 :func:`IPython.embed` call as always, but now you can also embed a *kernel*
499 :func:`IPython.embed` call as always, but now you can also embed a *kernel*
501 with :func:`IPython.embed_kernel()`. Embedding an IPython kernel in an
500 with :func:`IPython.embed_kernel()`. Embedding an IPython kernel in an
502 application is useful when you want to use :func:`IPython.embed` but don't
501 application is useful when you want to use :func:`IPython.embed` but don't
503 have a terminal attached on stdin and stdout.
502 have a terminal attached on stdin and stdout.
504
503
505 * The new :func:`IPython.parallel.bind_kernel` allows you to promote Engines to
504 * The new :func:`IPython.parallel.bind_kernel` allows you to promote Engines to
506 listening Kernels, and connect QtConsoles to an Engine and debug it
505 listening Kernels, and connect QtConsoles to an Engine and debug it
507 directly.
506 directly.
508
507
509 In addition, having a single core object through our entire architecture also
508 In addition, having a single core object through our entire architecture also
510 makes the project conceptually cleaner, easier to maintain and more robust.
509 makes the project conceptually cleaner, easier to maintain and more robust.
511 This took a lot of work to get in place, but we are thrilled to have this major
510 This took a lot of work to get in place, but we are thrilled to have this major
512 piece of architecture finally where we'd always wanted it to be.
511 piece of architecture finally where we'd always wanted it to be.
513
512
514
513
515 Official Public API
514 Official Public API
516 -------------------
515 -------------------
517
516
518 We have begun organizing our API for easier public use, with an eye towards an
517 We have begun organizing our API for easier public use, with an eye towards an
519 official IPython 1.0 release which will firmly maintain this API compatible for
518 official IPython 1.0 release which will firmly maintain this API compatible for
520 its entire lifecycle. There is now an :mod:`IPython.display` module that
519 its entire lifecycle. There is now an :mod:`IPython.display` module that
521 aggregates all display routines, and the :mod:`IPython.config` namespace has
520 aggregates all display routines, and the :mod:`IPython.config` namespace has
522 all public configuration tools. We will continue improving our public API
521 all public configuration tools. We will continue improving our public API
523 layout so that users only need to import names one level deeper than the main
522 layout so that users only need to import names one level deeper than the main
524 ``IPython`` package to access all public namespaces.
523 ``IPython`` package to access all public namespaces.
525
524
526
525
527 IPython notebook file icons
526 IPython notebook file icons
528 ---------------------------
527 ---------------------------
529
528
530 The directory ``docs/resources`` in the source distribution contains SVG and
529 The directory ``docs/resources`` in the source distribution contains SVG and
531 PNG versions of our file icons, as well as an ``Info.plist.example`` file with
530 PNG versions of our file icons, as well as an ``Info.plist.example`` file with
532 instructions to install them on Mac OSX. This is a first draft of our icons,
531 instructions to install them on Mac OSX. This is a first draft of our icons,
533 and we encourage contributions from users with graphic talent to improve them
532 and we encourage contributions from users with graphic talent to improve them
534 in the future:
533 in the future:
535
534
536 .. image:: ../../resources/ipynb_icon_128x128.png
535 .. image:: ../../resources/ipynb_icon_128x128.png
537 :alt: IPython notebook file icon.
536 :alt: IPython notebook file icon.
538
537
539
538
540 New top-level `locate` command
539 New top-level `locate` command
541 ------------------------------
540 ------------------------------
542
541
543 Add `locate` entry points; these would be useful for quickly locating IPython
542 Add `locate` entry points; these would be useful for quickly locating IPython
544 directories and profiles from other (non-Python) applications. :ghpull:`1762`.
543 directories and profiles from other (non-Python) applications. :ghpull:`1762`.
545
544
546 Examples::
545 Examples::
547
546
548 $> ipython locate
547 $> ipython locate
549 /Users/me/.ipython
548 /Users/me/.ipython
550
549
551 $> ipython locate profile foo
550 $> ipython locate profile foo
552 /Users/me/.ipython/profile_foo
551 /Users/me/.ipython/profile_foo
553
552
554 $> ipython locate profile
553 $> ipython locate profile
555 /Users/me/.ipython/profile_default
554 /Users/me/.ipython/profile_default
556
555
557 $> ipython locate profile dne
556 $> ipython locate profile dne
558 [ProfileLocate] Profile u'dne' not found.
557 [ProfileLocate] Profile u'dne' not found.
559
558
560
559
561 Other new features and improvements
560 Other new features and improvements
562 -----------------------------------
561 -----------------------------------
563
562
564 * **%install_ext**: A new magic function to install an IPython extension from
563 * **%install_ext**: A new magic function to install an IPython extension from
565 a URL. E.g. ``%install_ext
564 a URL. E.g. ``%install_ext
566 https://bitbucket.org/birkenfeld/ipython-physics/raw/default/physics.py``.
565 https://bitbucket.org/birkenfeld/ipython-physics/raw/default/physics.py``.
567
566
568 * The ``%loadpy`` magic is no longer restricted to Python files, and has been
567 * The ``%loadpy`` magic is no longer restricted to Python files, and has been
569 renamed ``%load``. The old name remains as an alias.
568 renamed ``%load``. The old name remains as an alias.
570
569
571 * New command line arguments will help external programs find IPython folders:
570 * New command line arguments will help external programs find IPython folders:
572 ``ipython locate`` finds the user's IPython directory, and ``ipython locate
571 ``ipython locate`` finds the user's IPython directory, and ``ipython locate
573 profile foo`` finds the folder for the 'foo' profile (if it exists).
572 profile foo`` finds the folder for the 'foo' profile (if it exists).
574
573
575 * The :envvar:`IPYTHON_DIR` environment variable, introduced in the Great
574 * The :envvar:`IPYTHON_DIR` environment variable, introduced in the Great
576 Reorganization of 0.11 and existing only in versions 0.11-0.13, has been
575 Reorganization of 0.11 and existing only in versions 0.11-0.13, has been
577 deprecated. As described in :ghpull:`1167`, the complexity and confusion of
576 deprecated. As described in :ghpull:`1167`, the complexity and confusion of
578 migrating to this variable is not worth the aesthetic improvement. Please use
577 migrating to this variable is not worth the aesthetic improvement. Please use
579 the historical :envvar:`IPYTHONDIR` environment variable instead.
578 the historical :envvar:`IPYTHONDIR` environment variable instead.
580
579
581 * The default value of *interactivity* passed from
580 * The default value of *interactivity* passed from
582 :meth:`~IPython.core.interactiveshell.InteractiveShell.run_cell` to
581 :meth:`~IPython.core.interactiveshell.InteractiveShell.run_cell` to
583 :meth:`~IPython.core.interactiveshell.InteractiveShell.run_ast_nodes`
582 :meth:`~IPython.core.interactiveshell.InteractiveShell.run_ast_nodes`
584 is now configurable.
583 is now configurable.
585
584
586 * New ``%alias_magic`` function to conveniently create aliases of existing
585 * New ``%alias_magic`` function to conveniently create aliases of existing
587 magics, if you prefer to have shorter names for personal use.
586 magics, if you prefer to have shorter names for personal use.
588
587
589 * We ship unminified versions of the JavaScript libraries we use, to better
588 * We ship unminified versions of the JavaScript libraries we use, to better
590 comply with Debian's packaging policies.
589 comply with Debian's packaging policies.
591
590
592 * Simplify the information presented by ``obj?/obj??`` to eliminate a few
591 * Simplify the information presented by ``obj?/obj??`` to eliminate a few
593 redundant fields when possible. :ghpull:`2038`.
592 redundant fields when possible. :ghpull:`2038`.
594
593
595 * Improved continuous integration for IPython. We now have automated test runs
594 * Improved continuous integration for IPython. We now have automated test runs
596 on `Shining Panda <https://jenkins.shiningpanda.com/ipython>`_ and `Travis-CI
595 on `Shining Panda <https://jenkins.shiningpanda.com/ipython>`_ and `Travis-CI
597 <http://travis-ci.org/#!/ipython/ipython>`_, as well as `Tox support
596 <http://travis-ci.org/#!/ipython/ipython>`_, as well as `Tox support
598 <http://tox.testrun.org>`_.
597 <http://tox.testrun.org>`_.
599
598
600 * The `vim-ipython`_ functionality (externally developed) has been updated to
599 * The `vim-ipython`_ functionality (externally developed) has been updated to
601 the latest version.
600 the latest version.
602
601
603 .. _vim-ipython: https://github.com/ivanov/vim-ipython
602 .. _vim-ipython: https://github.com/ivanov/vim-ipython
604
603
605 * The ``%save`` magic now has a ``-f`` flag to force overwriting, which makes
604 * The ``%save`` magic now has a ``-f`` flag to force overwriting, which makes
606 it much more usable in the notebook where it is not possible to reply to
605 it much more usable in the notebook where it is not possible to reply to
607 interactive questions from the kernel. :ghpull:`1937`.
606 interactive questions from the kernel. :ghpull:`1937`.
608
607
609 * Use dvipng to format sympy.Matrix, enabling display of matrices in the Qt
608 * Use dvipng to format sympy.Matrix, enabling display of matrices in the Qt
610 console with the sympy printing extension. :ghpull:`1861`.
609 console with the sympy printing extension. :ghpull:`1861`.
611
610
612 * Our messaging protocol now has a reasonable test suite, helping ensure that
611 * Our messaging protocol now has a reasonable test suite, helping ensure that
613 we don't accidentally deviate from the spec and possibly break third-party
612 we don't accidentally deviate from the spec and possibly break third-party
614 applications that may have been using it. We encourage users to contribute
613 applications that may have been using it. We encourage users to contribute
615 more stringent tests to this part of the test suite. :ghpull:`1627`.
614 more stringent tests to this part of the test suite. :ghpull:`1627`.
616
615
617 * Use LaTeX to display, on output, various built-in types with the SymPy
616 * Use LaTeX to display, on output, various built-in types with the SymPy
618 printing extension. :ghpull:`1399`.
617 printing extension. :ghpull:`1399`.
619
618
620 * Add Gtk3 event loop integration and example. :ghpull:`1588`.
619 * Add Gtk3 event loop integration and example. :ghpull:`1588`.
621
620
622 * ``clear_output`` improvements, which allow things like progress bars and other
621 * ``clear_output`` improvements, which allow things like progress bars and other
623 simple animations to work well in the notebook (:ghpull:`1563`):
622 simple animations to work well in the notebook (:ghpull:`1563`):
624
623
625 * `clear_output()` clears the line, even in terminal IPython, the QtConsole
624 * `clear_output()` clears the line, even in terminal IPython, the QtConsole
626 and plain Python as well, by printing `\r` to streams.
625 and plain Python as well, by printing `\r` to streams.
627
626
628 * `clear_output()` avoids the flicker in the notebook by adding a delay,
627 * `clear_output()` avoids the flicker in the notebook by adding a delay,
629 and firing immediately upon the next actual display message.
628 and firing immediately upon the next actual display message.
630
629
631 * `display_javascript` hides its `output_area` element, so using display to
630 * `display_javascript` hides its `output_area` element, so using display to
632 run a bunch of javascript doesn't result in ever-growing vertical space.
631 run a bunch of javascript doesn't result in ever-growing vertical space.
633
632
634 * Add simple support for running inside a virtualenv. While this doesn't
633 * Add simple support for running inside a virtualenv. While this doesn't
635 supplant proper installation (as users should do), it helps ad-hoc calling of
634 supplant proper installation (as users should do), it helps ad-hoc calling of
636 IPython from inside a virtualenv. :ghpull:`1388`.
635 IPython from inside a virtualenv. :ghpull:`1388`.
637
636
638
637
639 Major Bugs fixed
638 Major Bugs fixed
640 ----------------
639 ----------------
641
640
642 In this cycle, we have :ref:`closed over 740 issues <issues_list_013>`, but a
641 In this cycle, we have :ref:`closed over 740 issues <issues_list_013>`, but a
643 few major ones merit special mention:
642 few major ones merit special mention:
644
643
645 * The ``%pastebin`` magic has been updated to point to gist.github.com, since
644 * The ``%pastebin`` magic has been updated to point to gist.github.com, since
646 unfortunately http://paste.pocoo.org has closed down. We also added a -d flag
645 unfortunately http://paste.pocoo.org has closed down. We also added a -d flag
647 for the user to provide a gist description string. :ghpull:`1670`.
646 for the user to provide a gist description string. :ghpull:`1670`.
648
647
649 * Fix ``%paste`` that would reject certain valid inputs. :ghpull:`1258`.
648 * Fix ``%paste`` that would reject certain valid inputs. :ghpull:`1258`.
650
649
651 * Fix sending and receiving of Numpy structured arrays (those with composite
650 * Fix sending and receiving of Numpy structured arrays (those with composite
652 dtypes, often used as recarrays). :ghpull:`2034`.
651 dtypes, often used as recarrays). :ghpull:`2034`.
653
652
654 * Reconnect when the websocket connection closes unexpectedly. :ghpull:`1577`.
653 * Reconnect when the websocket connection closes unexpectedly. :ghpull:`1577`.
655
654
656 * Fix truncated representation of objects in the debugger by showing at least
655 * Fix truncated representation of objects in the debugger by showing at least
657 80 characters' worth of information. :ghpull:`1793`.
656 80 characters' worth of information. :ghpull:`1793`.
658
657
659 * Fix logger to be Unicode-aware: logging could crash ipython if there was
658 * Fix logger to be Unicode-aware: logging could crash ipython if there was
660 unicode in the input. :ghpull:`1792`.
659 unicode in the input. :ghpull:`1792`.
661
660
662 * Fix images missing from XML/SVG export in the Qt console. :ghpull:`1449`.
661 * Fix images missing from XML/SVG export in the Qt console. :ghpull:`1449`.
663
662
664 * Fix deepreload on Python 3. :ghpull:`1625`, as well as having a much cleaner
663 * Fix deepreload on Python 3. :ghpull:`1625`, as well as having a much cleaner
665 and more robust implementation of deepreload in general. :ghpull:`1457`.
664 and more robust implementation of deepreload in general. :ghpull:`1457`.
666
665
667
666
668 Backwards incompatible changes
667 Backwards incompatible changes
669 ------------------------------
668 ------------------------------
670
669
671 * The exception :exc:`IPython.core.error.TryNext` previously accepted
670 * The exception :exc:`IPython.core.error.TryNext` previously accepted
672 arguments and keyword arguments to be passed to the next implementation
671 arguments and keyword arguments to be passed to the next implementation
673 of the hook. This feature was removed as it made error message propagation
672 of the hook. This feature was removed as it made error message propagation
674 difficult and violated the principle of loose coupling.
673 difficult and violated the principle of loose coupling.
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