{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Exporting Images\n",
"\n",
"> [ Simple example](./Simple%20example.ipynb)\n",
">\n",
"> [ Advanced examples](./More%20examples.ipynb)\n",
">\n",
"> [ Linking and Layout](./Linking%20and%20Layout.ipynb)\n",
">\n",
"> Exporting Images\n",
"\n",
"Any `SankeyWidget` can be exported as either an raster (PNG) or vector (SVG) image."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from ipysankeywidget import SankeyWidget\n",
"from ipywidgets import Layout"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"links = [\n",
" {'source': 'start', 'target': 'A', 'value': 2},\n",
" {'source': 'A', 'target': 'B', 'value': 2},\n",
" {'source': 'C', 'target': 'A', 'value': 2},\n",
" {'source': 'A', 'target': 'C', 'value': 2},\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "a3676b3cb671497fab4e0451a4dd8bb5",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"SankeyWidget(layout=Layout(height='200', width='500'), links=[{'source': 'start', 'target': 'A', 'value': 2}, …"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"layout = Layout(width=\"500\", height=\"200\")\n",
"sankey = SankeyWidget(links=links, layout=layout)\n",
"sankey"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can use `IPython.display` classes to ensure embedded versions of your diagram will persist in your notebook, even without JavaScript!"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"from IPython.display import (\n",
" Image,\n",
" SVG\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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hm9wXQ74Psf3qNOiA4GWgQfeSdsjSSnk+yy++tFWKqzAH+GD0k4csB5lXN+XxTJhlXUViCTyMDXpFs7bOpu8D4+TMa8YYs0EATzxWqJVHwbYfBUc0VzhY/mfivNqt6Juvx7LFWPhGN+Ql8tbkiBOaw8D4QsjvIbaW3l+4FQetMPhAgAbdB+hBT7Lb81nbbDgJuRIDiw6gHUeJSfgcN2Kp6Op6tOneSz8fShlOuu3pCuNqMGUIMwH0wY/GO3E2luw9W+Q5IpGvk6Xzat4TKvJOaI5Ol9vTYS6/KOtOgx7l0h1k3sqrlo7Sogiez9rg+UyM5ACLFMDP4fnskZIRhUuHNSJ66VJHv+namottrmSIEoHupYyPwbjIYzC+5EqhjMCUuU/w/jTAnSymzemGovd3/DUCTmiOShdb36b2KJVmqPNCgx7q4suM8inPZx3i77VRl6d9Xmcm4jDHIuVmLI6zxE10LGu5Z3bHcLNS+lbhRYiDMwKGCzI095sxaK4/F6vbnatdR7QeXrTLCQ0WvtkhWxs+XjB7c2iy061oz8fonvrerD2xRt8uy7ux+xb+9ZIADbqXtAOWVtktdYdopeH5TFyCQT/5nK1jW9blRixC8vDIwklPrY5P6cpEkU297r68LVp+D5Ez5CoBI+CERnY7ocFE+AJTJLAOwUd2TrxBU31InNC8ny6+47Ct7aco7dLF/wz5IeSOfs7zUJYJ0KBnGXAQox9XVTMxpuU1xjHwfCbh+SyIWnqtk2lG9eOB0sLipzPt2WvrAeMuQG7Gep0jphdwAkYeiv74Q+Hz4PzeTmgca+Sxul2yUzW03HPB1gDl4k3oYleCuxFi55/3HktyAP7/McSuxPcIhMEHAjToPkD3K8mJ82vLYbvnYMT6+UahL3dPDWd+KehDumCxVipnceOIC5+zzj0as6CDlpjiQ9ZZIBuxKNNOaLTC6mtYvtbJ1wJOaDbsckKj4ISm0k8nNLaLwNa874RY426nX74HKYPcAhkNsbXzbLxGiJZhXwRo0PdFKALny6vqjnOFuRq18WmYeoYhO6ySC2PWSMe5v2nBhS+hKTRr5rb8lpojXSPtnFwGEhg0gS87oTGirH1Fu55Xs1oq04DGtXd8cEJj56HbVoN7IPf1ypCdwnkD5F97HeOuxwRo0D0G7lVy4296ZrQs6JqujJwJY54ancp55CkPEm/Bz/bipkUXveZFWcBhDebtZu17wYssMI0AEbCDVjHO4yQsG3wSmup3OaERWPhGug065tRviL3RmEUnNPZhtobcLjA1EvI4xC600wyh4xtA8DPQoPtJP8NpT5i3fBwWv5gmjZqmRPJ4g9E2GU4ixNHJ19CMubj5rllveZoJKc7zND0mlmsE0NwGJzQQGPmLVEKL0uTUVlFVtwr986swwHMVRtqvbq6eaUeeZzJYw27d076ayUgZ1/AI0KAPj5/vd4+/veZkJym/DkVOgUzqqQyyTpgqGmAwL+G75v7mBXv3fJaNgpzwwxWHm4S2NRkGEvCOgJEleO5PxcJQp6I2j12sbldVa5vEm9C91ISWuibH6CZhnKamuyo3ZbPLybtMMyVLgAY9gM/BuPh9RbJ9wuj8mBytuxIHYc3w0Q4kacRBCqtU4UU9UAl5IJaeHC2SYkQAs+CrStbzGZxpPadV3uKW6gvW+qWMShj7kcVAAr4TgFk/CEpAzIl2BI3B2rV26EjpvLpOKWs3YkzJRxgouw2/LVjpWbWhdt+mtW6V0rRpYdqUVq1Kxtq6sO8o3da86BJH6KTre8aowJcI0KB/CYfv/8StBnkdh80UUgttXxcHphsbGKjuJcawTb2Q9rPb7jDsImA9n2n5tCMLHmha9E3bp+dzMMf7rACTJ4G9E8DIevySlKNZvnzXTwrq8PbnBVbd/sjA9Kd+fLRwu2uAODfyhJnjtq988tdY1/4lXLYZ12/BN8JmzBpJ7SvlbE7GxAdZ7s/fe95y8CwNeg4WeuSybD2fSfWU0cmHNyy6OEArVJkp/OqK3NPGDPUiAGNehH9LsS21HwSpGTT4DkDfvVDwvTYxceJWOb/mNankq8ptf23dwtnWhzpDlgjQoGcJLKP1hEAHahHLOlX7kqAto3nEjSv2Swht/UIzkEDOEoBthyMbWWlcUQk/EW7p/NqXYfWXrV844//hYxefAAyZJECDnkmajMsbAtK04sdgqexMPDJUz2fZVtSM1BPRQuljkNuM0A+JpLMSS8++/+avrxejDsqbtmmTKC6IJUpiRhZr4xbDmUix42BfyxKMyShRShbDoUgxfoiL8Ws7FjWucdg/EBnBhoEEhk4Az5MDY342Yji7dH7dX7VZ/usNCy96mYZ96Ez73kmD3pcI/w8ygc/xg/DoCKOXvrvo4u1BVjSRNGO7+yC91xIjmzd0uDuu3/Szyz6xqfcMJqi/ZbpdttNK6rg9N5Aw/qalhTFVWCryVBmuL0N7KramDD/QE9HRijXKGUhgkASM+IoSzs9Lq2rrlfP0vY13Xlg/yBh4eT8EaND7gcJDwSIAw2Gn3CxJFn64bGP8+vZgabcHbYwc7VOd1khH/XjTwm5jvgftBnU47W3ur7jJyq4Al7Dlb8cOd938YzEo6lilxLGobcHQY7w0AwkMiICs0K57f+mtdc8kRcG9Hy4479MB3caL+iVAg94vFh4MBAGJqTSufHhk8aTlmfJ85lW+FJqx0YTtVXI700GSb3lW25k9213XvZa3Xc97mVUiNXagyByLVoLjYNi/CgJTbPP9TgW5QwK7E5Bo9bkwJjvPLL+l7u51d83oz5Pb7nfxyG4EaNB3Q8IDfhPAiNlmyIOlBSUrMu35zKu8YSJ8PvLgeXCMWOV5or0SXPuLSrt62J/SIkTcqPK22sNdCQOvTAWGQVWgFj8B532g00tR7gaPgBEjXWXiZVU1Z+x3UP5P011EwdMzwBrRoAe4cHJNNfzYf4CJroub8mf8IVuezzxjigm5vtgsR+zwLI8DSQge7FCLt360raRq8WVzn9jfLVAVSsSOQytGBT58rPOawoFEx2uiTwADMb+5bUviCKyCObfljll2nXiGARKgQR8gKFw2CWJ/eP4A6YIMJ5yOmzXEEwchw1HUk3slPJ8JGPKFM/8II+h9O3UWMimlA584toi9DfiMCPz6/emZCS+BjBUh0Bdf9nrhkTqmYNxtLV5WoLmeS+am4OTsn0kqKe8vm//EPzRVX9qUsxQGmXEa9IEDm4tL/xFiPQwNN/wOEVhjftlwIwr5/X+B/ovXV8+yTbSRClK7xvjQ5o7aTfgGpKEvvql7wJ0ddLfUPgiH3frcgTG3syLVFw8jj0NHQwrsOYbcIICP/IOMyf/Xslvq5jTdNePj3Mj18HJJgz5wfifhUts/2TnwW3a70v7YHpqWlbudzZUDUrwuXHP/eq89n3nIV0vh4gfJ84D2jcDX0AcCJT3a+QVca0VgLn3etgMOnZwQ8qvgiqZ6WYFe+LEDiYvXhJmAGYO1Z/8Fgy2/lx6fEebMZF13GvRuxEXYLIT8DWQ05L8hP4I8BbkE8n8gx0Fs/+SbkGsgjZCfQK6AHALZDHkUMg+ShBwFeQTyY8j5kMsh70F6mhL/AftnQiohuRAMfohfjgl9/9rqi1ZHP8NYjN+XEM0pY1gYBwuJCvvc7Hx2xt787BgskoMmelNhDTzm/eOdM3m+YGeiWSNgsNZ8V6G78Oz4CzeGdZBs1uD0iZgGvRvIv2BzDeR+SCtkNsQ2i9umvhGQzyH2h+INSDNkPeS3kAsh/xeyBjIdchOkAfIA5FTICZBFkMMgtlnZGv3xEBusH2F7X6QDmkxh2PTzSiUeWLfgMvtBkxPBenzzY1CccULY5D7EJ2LTz6Z/glufS4uYEl+d396x4WjXuBWg0D3grtvL2BBT4G1BIYCPtZMa21vt7+tdQdEpiHrQoHeXyrnYWIN7fbqQnsb2cciJkCWQIsg3IP8bYmvoZZBKyALIbRAb/g2yBXKk/QfBGnMbNkFsTXyr/QfBxu1ArrT/RDZYz2fCPKMS8oHGu2fZD6CcChqD4pQPg+KEq+2zlZMhvVbBO8i8lVSYMG/5OEfFKuAsJNUfj1aiyajx5SyjHi6h3Er5txPn177dXD3TfsQx9EOABr0bytvYXAqxxrsaYh+YUZCeYA17F8TWvm1ogtgfhRKIbYovhVwGsaGxeyOmYtsB+VtIjzG3p2xcL9qdSAYpuuDCtMaY5EPB8nzmLW3parib8jZNm5pRuVNDHwjd9DO4Edc+Y68vi78wQrS1HoPV9CrgI7QCzSjHwcgfMJC4eI3/BFBWt6OrpT7dOuO/QgHTgAa9u0D+BzbWYNta899DnoTY2rpt0rPBGudVEHuNDV+D/AfEHsczhhXGd517Dfv2p9xeUwfpiQO7KcN/ELZRHBDXIZR8ojOxY0nPGuI2w7kaMMDdF9csYZi25ucz0RQ/xw5qfSst2Bg5rqp2Qp5d2c72w6OpXhp9RChnC/gJ1qu0sfhMoeq6HcnZ1lKGPgRo0LuBfIrN30F+CLGD2r4H2Q9yLsT2nX8V8hDEBmusbQ0+AbFG3zbV21r5LyGXQ+ygna9A7HKXr0B6B/sBYINtto9EwJdMG/rJlxppHmleMOOzSGQqA5lADRCtvN6Pi1NcR32QpSfNxoWpcTHNuNF+gIup8ZqiTe3mWKy6VyGwuh1e+WNx2P4eMASAAKaDnlE6f8U31ldX/lcA1AmUCjToQjyLEvkQMgeyFnIdxDbBzYDYMAVSALFf9TbYl/tAyA8gtpZuwyGQKyC2dm5/xXsM9xvY7x1sc7sNETDocpvQ+tFCqX8bdM9n3ci9/SvdhIaXFG8TRWqYtWY/OBmGQeDN+Kx23G7f3fT7a2TpzTVlKk8dhyV9bV88jLykE5phMB7urZjZMBdTGV9Oz34YbnSRuZ8GXQhbO78a8i7kZcjhkG9AeprFy7Fvw2mQjyE9hv1b2Lc18/0htgmoBLI1vbUD4pKQv0B6h0npf2Zja416Txq9rwn0Pga6fYpK4JJkUcvjofF85gNROyjOh2TRfJS7g+Kyx1ua9T9Lvev2fX/KpnPUvOUjO6WD/nc01WPhG3R1wCENndBkrwy+HLNdSXDzqMMuwdHHvnwmt/+jQRfiZjwCpZDqXo/Cq9j/Tvr/P2Nra/DW6FuDPA3yc8hcyBOQHRA73c32zVlDbWvtX4OsgthBcb3DCvxjB9/9O+RGSJgM+sfoV3w4v10txwIPNs8MeyVg29u9ryxjsj/sCkO2CaRbpWx3mxU4oYmr8Z2nljs6WUEnNCkiWf+jlLwKzn8et34fsp5YSBKgQRdiI8rqDIhtRj8Yshlia+09YQN2JkBGQqzRtuGfIHdA7D32q93WxvMgEyHrILaPvb/wnzho568XQz7v74KgHYN9sPl/8MDPWlaweWvgpZPqQ/ejjh6RleIGTjogV8bjuqW7y8522y2zWqWc0OTlHaccOydeoKk+1X1XGBCNQ6+GraVP6FhxJn6gXgp9ZjKUARr0XSCtEe9tyHed6R7F/kXvA9i3zetWekICOx/0/LOXrR0p3zNafi+X+XsKo7SblSsXrzup7WnRvda2vwqFLHWdlBqORjzXGgvaeN8s4Hkuw5Fg2gnNy9DWyped0NjR9C6a6mVq0anUaf4ZPAF0MV2Mu2jQ0+ho0Af/DEX5DrSqizcwmuu3G0ZUvsKmrKEXtVQS3ta8N+ictjb0Msv6nf04oRkff2Z0rDNRIbSCcacTmsGXgTod67zvx3Xeu8nRoA/+CYrcHahIfoj5t3VdWq34cGElWg4ZhksA09C1/TryPHBhGc+RDyfBlvgFtpXvxbTsdEKzQ6KJXmPQXbeRt7NoGPolYPL0CPF1nKrt93SOHaRBz7EC78muNeKYevN8TLrPr100aw32va9O9igTwa2LSejKhxVG4UucTe4hfp76OKF51GZl7M3L4IQmv9sJDUbVozvsKMxPzA9xNjOqOl60sxAhDTog0KBn9NEKbmTWWQgsdoOU6uWkcF5pWXiBHbzDkCUCUuW5mKefpdj3Eq3htLW90AnlqfTKi3agbWqwbcoJTVfzV1wXTmikrMCb/TUY+dGhzFwGlMbguJPsLAOIDy9cBjKQwSho0DMIM2hRocG3BQOt30Ar7GuxNrGS/UzelZBMuFo43je5cy1378rYr5TSTmjqkb6VVJh02/KxyYQzWTnqSKn1ZPTHT5ZCjYexy4UWm/3K26YejulF7/fwyNUtDXoESr679q2ajdHvwYi8KxPmPbck7910/1wEchi+LLgFwnWSPujNaWs+QPc/ycY7L7ZeHa10j6jHDgaLFewYJcc7SXcCOoAmoD9+gjEGWzkB01HHRMnYa6WOQZZp0AGBIWgErMcyI1qVkG340m6z+zDabRhj1b0vZasW+jPhqha46GwpLjn8w/RXe9BykrP6yITSfgxLQLdKLtTIcva5GkzG0wtA2am0u02ntc32n7evHxMTeiQe1GLHkcUmCVG6BL8pxXiOijEcowQjMoqxbEuxFqYEv0HF+BDAvl1Hw4wdjC7Zvhbrux+R7TTCED9r6MEqpbhVZ331zNTW7jOEkwB+FPE76X2TO2jRoIfzkfFU63QFoGW4ie5Q7b/K08VHO0Zfbp2mDDe+od4vtTtxqPdG6T4a9CiVJvMSGAIKg+J0agFBb1XCJwQNurfIczq1jxfMtitrWnmpbH7dNWjSv8EfIJJT+wCeL78/Tx9TjToBZ4dP0wA5bS3qj1ZQ89dUPeNBTH+1Hic9DzqHR/n3hk2D3psG90kgQwQcFyvF+RDwFeH4kCyTJIEUAYz5ecAPFOjdsv4xcj7QoOf8I0AA2SCQwOiibMS7rzgxcInv9L4g8XzWCOS3Ketl0vtgUs6xvE83YCny5Q9YgVCdaBDAqGFfauiYCcEaejQeoVDmYu2BF1onVQw+EaBB9wk8k402gS7j+FND16yhR/vJCnbuxm97rMAXDY3hhwTA06D78vQx0agTUCLpi0HHVDm+01F/uAKcv5jJ88egK7kjwFg8U40vv2eomVAuEXAS/jS5c1BcLj1lwctrR6zIF6cxmC7XFTwa3mtEg+49c6aYAwR2jEj4UkPHSl58p3Pg+QpqFp2CDl9q6Eoo1tDxUPDlD+qbQb1CTcCvGjqgcVBcqJ+ccCvvyHx/auhCsIaOR4cGPdzvD7UPKAHHxHypoUfJ4UZAi5Zq7YWA7BC+1NDhN4EGHeVCg76Xh5OnSGCoBDp8MuhwmsF3eqiFxvuGTUAp408N3Qg2uaP0+PIP+xFmBCSwOwGnpMunGjr70HcvDR7xikAyX/ti0IVhk7stYxp0r550ppNTBNS2PF8MOt/pnHrMApdZ2SV9aXLH0q+sofPlD9z7QIUiQiA//wtfVorDKHcOiovIMxTGbEjpT5M7VkhkHzoeGNbQw/jWUOfAE8gzBf7U0CX70AP/cERYQWn8GRRnNAfF2ceKBj3CLxez5h+BkiLlSw3daE5b86/UmbKMOf70oXMeeurho0HnO0gCWSDwqSjxpYYu+ZGehdJklAMloLVPTe6ch54qIhr0gT6pvI4EBkGgePVmXww62tz4Tg+inHhphgn41OSOkSMcFIei5Muf4eeZ0ZGAJbD6CuFLkzv6MDkojo+gbwSk8KmG7moOikOp06D79ugz4UgTmH2FLzV0OGfhOx3pByvYmdNKt/uhoRGSBh3g+fL78fQxzRwggLoylm3zIaOyLP7CCB/SZZIkYBcq9OOZh0silSR+GnQ+AySQPQJSJLIX+Z5j1p1tU/Z8lmdIIHsEpJEV2Yt9zzFj2pov79qeNfLnDGvo/nBnqjlAwBjR5kc28aN6rR/pMs3cJjCuqmYiVmw7xw8K6Lv35V3zI697S5MGfW90eI4EhkEAL9dnw7h9GLeaU8vm110zjAh4KwkMikB51dJReULegTb3vEHdmKGLpTJbMxRVqKOJhVp7Kk8CASaAzsSPoV65HyoaY24om1dzvCv1426hWrMxPmuLH3owzQgTWLrUKXu98Eg3zxzvGnkVcjrGr9waLTf5lXaQ0qVBD1JpUJdoETBmg0AbpF/BSHmGEs4ZqkOI0qpav9RgulEl8Cbq47Agyvj3jKfRmlEH5zVHFfNg8sUm98HQ4rUkMBgCSqwdzOW8lgRIYPAE4JDoo/pbprMPHeho0Af//PAOEhgQAUeq1QO6kBeRAAkMnYAxa4Z+c7TupEGPVnkyNwEisK6gci3cOm4PkEpUhQQiR8BV6u3IZWqIGaJBHyI43kYC+yQQlxpLy6zc53W8gARIYMgEsIz760O+OWI30qBHrECZnWARUMZ9OVgaURsSiA4B9J9vaKq+tCk6ORpeTmjQh8ePd5PAXgk4HXkvCiG5itVeKfEkCQyNgDH6+aHdGc27aNCjWa7MVUAIrP1F5RdC6D8FRB2qQQKRImCUXBGpDA0zMzTowwTI20lgXwS0lk/u6xqeJwESGBwBLNzU0Fw9c93g7or21TTo0S5f5i4ABDYUz3gVvtc+DIAqVIEEIkNAavNYZDKToYzQoGcIJKMhgT0SwGh3bcSSPZ7nCRIggcERkOajScUlvx/cTdG/mgY9+mXMHAaAwMim9uUYkbsxAKpQBRIIPQEl5X+8GD+HPtD7lCQNeh8g/JcEskFg9WOzu6TUv8xG3IyTBHKLgHm3sWAGnRP0U+g06P1A4SESyAaBxupZaCKUr2UjbsZJArlAAH7PdcyRC4RdtIlhNwI06Lsh4QESyB4B/Az9VEjTmr0UGDMJRJiAUUs+uHPmqgjncFhZo0EfFj7eTAKDI9B014yP4dL0zsHdxatJgARA4L+LG9v+nST2TIAGfc9seIYEskKgsbry90aYpVmJnJGSQDQJfKGNW2XHokQze5nJFQ16ZjgyFhIYFIHywpKfG2P+PKibeDEJ5CIBKZKuMfM3LLqYs0T2Uf5yH+d5mgRIIEsEjrhxxX7JIv0brHhVnqUkGC0JhJ2AUUr8pHHBzKfCnhEv9GcN3QvKTIME+iFg13nvcPNu4Pz0fuDwEAmAgJTyVzTmA38UaNAHzopXkkDGCWz62fRPumKJ7+On65OMR84ISSDUBOQDTdUzHgx1FjxWnk3uHgNnciTQH4EJ85aPc6RzL5vf+6PDY7lEAC1WWgv9y+aFsx7OpXxnIq806JmgyDhIIAMEKu56tviLLckfYQT8uRmIjlGQQAgJyG1wifqj5gWVr4ZQed9VpkH3vQioAAl8mcCkecsv0kr9QBhZ8uUz/I8EoksANfNXOlXbHR8vmL05urnMbs5o0LPLl7GTwJAIHHLr0oPz3eKbpDTnDykC3kQCoSEgP1FS39u9NHJolA6kojTogSwWKkUC3QRKf7D8eJMXm4s1rKeQCQlEiYA0sl0LsyRZ9OGSjfHr26OUN7/yQoPuF3mmSwIDJmBk2fzaaUao64Qxkwd8Gy8kgWAS6MAH6u+SXXn/2XLPBVuDqWI4taJBD2e5UeucJGDkxKraM5RQlwmhzzRCctppTj4H4cy0XW8BqyMuN0osa66e+Vk4cxFsrWnQg10+1I4E+iVQNveJ/U2Bc5pQzulCm9Nw0f79XsiDJOATAevqFK1Kq4TWf8IKMa+uL1r5rojH6fY0i+VBg55FuIyaBDwhEI+r8raphxvHmaS1e7CU4iAj5cFGi+59k9oWeaILE8kZAtZgayG3wohshmzBGgqblRRbcHCLFHpjcdHIVavj59BVcM48EcwoCZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACZAACYSLwP8HN+LGbPJ3W8kAAAAASUVORK5CYII=\n",
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import base64\n",
"data = base64.decodebytes(bytes(sankey.png, 'ascii'))\n",
"Image(data)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"image/svg+xml": [
""
],
"text/plain": [
""
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SVG(sankey.svg)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Saving images to files\n",
"\n",
"One way of saving images of the diagrams is to display them as above, then right-click and download.\n",
"\n",
"You can also save the image data to disk using `save_png` and `save_svg`:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"!rm test.svg test.png"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"sankey.save_svg('test.svg')"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"![](\"test.svg\")
\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%%html\n",
""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Because the diagram is actually drawn in the browser, it is not immediately available to save to disk. It can be convenient to display the diagram in the notebook and simultaneously save it, so `auto_save_png` and `auto_save_svg` methods are available which save the images as soon as they are available:"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipysankeywidget/sankey_widget.py:150: UserWarning: No png image available! Try auto_save_png() instead?\n",
" warnings.warn('No png image available! Try auto_save_png() instead?')\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "7b5fb85ae2f14ed7bb6394a5d5b3b7bb",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"SankeyWidget(layout=Layout(height='200', width='500'), links=[{'source': 'start', 'target': 'A', 'value': 2}, …"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# This won't work\n",
"s = SankeyWidget(links=links, layout=layout)\n",
"s.save_png('test.png')\n",
"s"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"![](\"test.png\")
\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%%html\n",
""
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "af7de206a3084484b539f424fb8accef",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"SankeyWidget(layout=Layout(height='200', width='500'), links=[{'source': 'start', 'target': 'A', 'value': 2}, …"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# This does work\n",
"SankeyWidget(links=links, layout=layout).auto_save_png('test.png')"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%%html\n",
""
]
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.9"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"state": {
"4693e717c5c24724b43acd5d8a442a35": {
"model_module": "jupyter-sankey-widget",
"model_module_version": "^0.2.3",
"model_name": "SankeyModel",
"state": {
"_model_module_version": "^0.2.3",
"_view_module_version": "^0.2.3",
"layout": "IPY_MODEL_d944a9a6144442a3afdf56dffbee2d7f",
"links": [
{
"source": "start",
"target": "A",
"value": 2
},
{
"source": "A",
"target": "B",
"value": 2
},
{
"source": "C",
"target": "A",
"value": 2
},
{
"source": "A",
"target": "C",
"value": 2
}
],
"nodes": [
{
"id": "A"
},
{
"id": "start"
},
{
"id": "B"
},
{
"id": "C"
}
],
"order": [],
"png": "iVBORw0KGgoAAAANSUhEUgAAAfQAAADICAYAAAAeGRPoAAAayklEQVR4nO3dfZAc1Xku8Fd8WVKIEFhr7c70OY0TyA0YDDay8QeOhRE2MnKQDbJlDEiOxDpXoJjVznnPLJbtAeOY74j4I9gBVrEh4LXCauY9PdrFslcmIJC8VUnudd1/7q26t27KuUmFqlRyr6/tfFj5o1dkLVbaD/XM29Pz/KqeKrRCqz49fc6jnu3pJgIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAOhOw0R0hIg+o70hAAAAsDCLiegfieifiehHytsCAAAAC/QxIvoFEX2W0rP0i3U3BwAAABYiENEEES0nop8T0e/rbg4AAADM1wpK32rfMvXrhIj+p97mAAAAwELcTkQ/I6Kzpn69idK33d+htkUAAAAwb4cofct9+VTOJaJ/IaJHFLcJAAAA5uF8Ss/GZ8r/IaJT9TYNAAAA5uouIvp/RPQ+Ilo9LRVKS/0qpe0CAACAefgfRPTMDF9fSkT/n4gea+/mAAAAwHy9i9Kz8OuP8/t1IvoHIjqjbVsEAAAA8/Y1St9uX0ppsR9r89TXr2vjNgEAAMBJmKnQAQAAoMOg0AEAAAoAhQ4AAFAAKHQAAIDcqQ0v7uNwQdnXr7W+eatxjYpl+bxlud9w+KrlsNv6xh7jGvssy/NEdMRy6Lc+TCJIFvnVVet/TEQ15ZkAANAhasOLe4f2XlgeStZFPmy3XnZZFpnv4ksodCTjoNABAE7oyKJoILnY+sanLMtu6+VwFosvodCRjINCBwA4xvLaxPKSlw9ZL1+KOTnQisWXUOhIxkGhAwAQUe9Qs2fqLPzJdiy+hEJHMg4KHQC62JFFxoX3RF52ZfVW+lxDKHQk46DQAaDrnLO9ucy4ZLP1ErQWX0KhIxkHhQ4AXaO8I/kNy1KLORzUXnwJhY5kHBQ6ABSeGWy8zfrkUe0Fd3oIhY5kHBQ6ABSW9fuusC4May+0M4VQ6EjGOUGh/yWldyacnp8S0SEiuqpN0xEAYL6OLLKVsCZ28pT2AnuiEAodyTizFPpfENFNU7mFiCpE9L+J6OdE9Mb2zE0AgDmpnRI5+aD1jT3aC+tcQih0JOPMUuhhhq+/m9Kz9e2tm5cAAHO1euK0qCIftix17QV1PiEUOpJxFlDob6K00Le0boICAMymNnKG8WGjYWlqL6QLCaHQkYwzS6GPEdHyqZxDRBdPfe1vpr4GANBm/bLUuGSz5fCc9gJ6MiEUOpJx5nlR3NHc1qaZCwCQ6tk2cqbl0G85fF974cwihEJHMs4shf4SEa2eluuI6HFCqQNAuyyvTSyPfNhuWZ7XXjCzDKHQkYyzgJ+hExEJpVe7AwC0RmlQVhgfKpbDC9oLZStCKHQk4yyw0B8ion8lokWtmckA0LUM10vGyc6Y5SXtBbKVIRQ6knEWUOivm/q9H7VuRgNA1+kbTGLD4W7Lckh7YWxHCIWOZJxZCv2viGjrtFSJaJLSn6F/tD2zHAAKLRqon2e93Gc5/FB7QWxnCIWOZJx5XuX+E0pv/Xp9m6Y6ABRVH4cLrJdd2ougVgiFjmQcPJwFANrKcLLKupCrJ59phFDoSMZBoQNAW1gvV8QsT2gvenkJodCRjINCB4CWiqvN98UcntRe7PIWQqEjGQeFDgAtcGRR5JtrLct3tBe5vIZQ6EjGQaEDQHZWT5xmWNYbH/ZqL255D6HQkYyDQgeAk1cbOcNUwkbLIdFe1DolhEJHMg4KHQAWrjax2Hq5pdOffKYRQqEjGQeFDgDz1rNt5Ezrm7cW5clnGiEUOpJxUOgAMGfLaxPLI5bfs9wo5ANTskrs5Cnrw12Gw2dKXtj48EXL4RuWw7ctS2I4OUBER6xv3mp9mIxZDlgv45ZFrG/siZ08ZV0YNk6+Zlnuj12y03K4I3bhd2w1bIhc/Rrr6u+OnJyvfUwAAEAHKQ3KCuMaFe2izG2q8ogZlPWW910Vefm0dWF4tj9DWZ2hsxwyTp41nDwUsdxe9vVre4f2Xki1icXaxw0AAOREjxvpNS7cWfQnn803MScHYg732GpYQ7c9+/oyN2+IWZ6ez/egVr/lzuGHhmXUevmS5bApqiSXn7O9uUz7mAIAgDbqG0xi68NdsQ8va5dnzvKt8lCyjvonT+/ZNnKm5dC/0OsISO9n6MFweDDmxpaoklxO/bJU+3gDAICMRQP18yyHe62Xwzkoz1wkZnnJOPlCNJBcfHQ/xdzYYlmeP5nvS7m5KE4OW5ZnjAt3loeSdX2DSax4CAIAwMno43CB8eFh/XLJUVieNxy2nVUNZx/dT+WKvDOrm+ZQbgp9xpL/nvWyK+bGFjPYeBsNHFyieHgCAMBs+ri+yjj5mn6B5CmyP3aylbaNnPnqjho4uMRwuDvLv4dyXeiv2SeHY5anLctQ2TXWlbxYvaMWAABeVfLhXcaHx/WLIkfhMGZ9uOnYq8NXVsYvsl4aWf991FGFPlNkf+Rll2H5ZB/XV1FtGFfVAwC0S8zhSsuCJ5/9cjEFWw0bqH/y9GP3l62ENbGTllwYSB1f6MeE5VD6+XupRk4+WOZmpHCIAwAU2ZFFkUuusT6MqC/6OYphGTWV5DraMHLqTHvNcthkOfywVX8/Fa3QZwrLfuPDw8Ylm/uq4TKcxQMALMSGkVPNoKw3Dk8+Oybfjlz9GqIji4636wyHba3eDuqGQj82LIdiDk9aDj7yzbXl7TiLBwA4vtrIGdY3Pmp9COoLeL7yragqq2fbfcaHje3YHurGQp853zWcPGRcsrnkxt5K25uva/0kKaRTiGgrEb1ERP9ERD8lov9KRJ6IXvPjJADIs9rEYsuNm62X8Rws0rmJ4fBYuSLvnMsuLHH47XZtF6HQZ0zsw8vpdR7CkUuuiQak3OKZUwSnENEeIjpCRBOUljgT0SgR/YKIxohoxh8tAUCebBs5M64mW9PPDusvyHmJ4fDVvmq4bK67MXJyfqsugJsphEKfR2TccHjQcthUqjbfQrWRM1o4ozrRDkrLfHCG3/udqd/7VFu3CADm7pztzWURy+0xJwf0F9z8xPjwcB+HC+a1M/tlaSs+mnaiEAp9wZm6JfG3jA8VMxg+sOLOsb7WzLKOsIiI/oaIDp7g//kzIrq/PZsDAHNWGpQVpiI78AjT6ZHDlsO90UD9vIXs05jDPe3eZkKhZxsOY8aFByw3bi670Uu76Cz+QkrPwFl7QwBgjnrcSK9lGcKTz/4jsQ8v26rUTuYzz+UdconGthMKvbXHhpOXrZc/Ma5RMU7e3+OS3gynY55cTWmh36C9IQAwizI3I1uVGp58Nm2xZnnJsgz1uJGTXKRrp1jf2KMxBkKhtz2GZcyy3G99uKm8Qy6Z6WZCHehKSgt9o/aGAMBx4MlnM4QbLxiuD5YGZUUm+9g1rtcaC6HQ1RM7edly2G24Pmi5fvXJ/wNRxX+itNCHTvD/3EREt7dncwDgVXjy2QwLLycHIpbbl9cmlme2ozeMnGpYxrTGRCj0XMa4xj7r5T5bqd8UVepv7oCz+EVE9LdE9BdT/32sJUT090Q03M6NAuhqJTf2VsPhq9oLWr4i34uryS8/+SwjppJcpzk2QqF3RKZ+vLPbVGSHrYY1b/h0fWXWx2IGPkPpWfpMZ+EPE9G/EdG72rpFAN3Iuvq7Y5YntBeuXIXDc1ElufHYJ59lybCMao6RUOgdG8PStBzujSrJjSsr4xdRbeK0Vh2nc3Q6ET1HaanvJ6KdU3lh6mtf0Ns0gKK7efxXjEs+bpw8q7045SzBOPlYqz9ypHVl+/QQCr0wiTkcjFmesBzusCxXZXWNxzydRukd4f6OiH5G6e1ff0C4+h2gNaKB+nmGG5/BZ8h/OcaFvWZQ1h/vyWdZs16q2mMmFHrRE6yXLxmXfHxlJbTrLP7zRFRrw98D0IX6ZWnkGu+1Xthw+LMcLDJ5y0jkkhM++awVLIfva4+dUOhdl5jlCeOSgcg31/YNJnELDm0UOkBWequj59pKWGNYfte6MKy9gOQ2nDxjq2GNxmsUDSQXq4/fo9CRMBmzHLAsfxSx3G5Y1pe58Y6SF3sShzcKHWBOaiNnRANSXlkZv8gMJr9lBmW9Yfmk9eGumMOT2otDR4Rld+Qa79V8GWNubFHfDx6FjswSDmPGh8cNhweNk53GyW1RJbkx8s21USW5PBpILo6cnF/asdeUBmVFT/pJEBQ6wCw+T0Q19QnewTFOvtbH9VXaLyQRkWX5I+39YT0KHck+v7pq/Y+JqBb78KJxjX2Wk2esC4/GLtlpOWyKXOO9eBwtdDsU+gITedk17yeftZhl+XPt/WI9Ch3JPkcLfdb/l8NzhpOHjA8bz9neXKY9JwHaCYU+r5zck89aadnAyDn6+ycNodCRjDPnQj82LPeXK/JO7fkJ0A4o9LktCoesD3e16OrdTJRdcqnufpJGXE229ky/811tYvHy2sTyFXeO9cWV8Tf2Du29sFRtviWuNt8XcfhIzI0txjUqMYd70jsJyp7YhxfVX28kd1lwoR8Ny3eMk/frzVCA1kOhnyAxy0vGhTs74cEWZddYp7WfDMtolveiXzYwcs7KSrjIVsMa6+UW4+QL+Ghkd+ekC30qxsmzMYcrszpWAfIEhT5TOLxgXKOidFesBbHVsEFtf1XDr7VlkAMHlxhOVlkOm6yX+yyHRP1YQdqSrAr9PyK7cBEdFA0KfXo4/CDzJ5+1ifVyi8o+q8ojmuMuDcoKy3KV5XBHzPJEzOGg+nGEZJ7sCz29ra3l+tWaxy9AllDoPkymd1dr3trTgieftYv1zVs19l3Ekq9nUdcmTltZGb8oqiQ3Wg734iy+GGlFoR9N5OXT7b6jI0ArdHehc3jOctjUyieftUtcTbYq7cN+7bHPZmVl/A22EtYYlwxYF4ZjlpfUjz1kXmlloVsfJg2HL9PAwSXaxyoU20YiuqWF36c7C51DYiphY6uffNZOWneJMyy/qz32eeufPD2q1N9sK/WbrJf7jGvsUz8mkROm1YU+lZHeoWaP9uEJxbWX0mcAt+r7dFWhGx/2Gpb1tFr9Gc+ZMy7ZrLJPOWzTHnsWetxIr+X61Ybrg5bDbpzF5yttKvRJy+G5uDL+Ru3jEYrpZAt9EaXPEu7uQmf5TuSba4lqp5zEvsw1rYviIh+2a4+9JfonT596tvxNluV+wzKmfhx3cdpW6D5MGtfY10mfcIH8uIiIxonoH4non4ioQURH/3X4l0R0ZFpWENFiIvoDIvprIvopEf13IvocpcV91CtE9HtE9HUi+gkR/bcZvs9RhS70mMOTluWq7F+2/EnfPlbYzxzu0B57u/S4pNc4eb9xjYr18iexk5e1j/FuSTsLPY3soX5Zqn3MQedYTGkxByL6IBHdSER/RUT/hdKCvpCIDhDRISJaRemZ9leI6O+J6FYiWkNpIf8bEU2/MOkVIvq7qT/7n4nobTN8n6MKWegxyxPWyxWZv2I5ZlzycY19bSqyQ3vsavonTy+70UstN242LjxgOeAsvkVpf6GHSePDw9qHGHSOt1B6xjz9DPLNRLSHiM6a+vWxb5UnlJb0dIeI6I+n/foVIvoREZ067Wvd8Za7C48aTnLx5LN2M04+prHPjQ8V7bHnyYo7x/rMYPiA8aFiWb4Z+4Cz+AyiUejWh8kyN2/QPqagMyyj9Gz7fxFRhYguo19+65xo5iI+hYguIKJriWgHEf1fIto97fdfIaJ75/B9iApT6Pl78lm7lVluUNr3rD32XKuNnJHeZ19uMU4etF7G9edL50Wr0GMfXix5sdqHEXSG84noCUqL/QgR/S2l5X7UsUW8edr/+2NKz9j/ml5b6DuP+XuKV+gcfmi93JfHJ59piDh8ROd1kCHtsXeaaEDKkUuusV7YsjyJs/jZo1Xo6TEevq59zEBnWUREl1D6M/IjRLR66uvTi/g3iOhfiegbRPT6aX/2MHVTobMcMhzuzvOTzzSYQVmv8XoYJ8ceazBf25uvK7mxtxqXbDacPGQ5PKc+z3IW1UL3YbLbrsmB+dtC6VXo0+9StoSIfkFEn5j69fQiXk9p2U9/a3kZpVfI7572tUIWevrkM9lpuF6a/64uvpKXD6m8Li5BobdAeXszinxzreXgpz6tcUh7DmpGvdBZvqN9TEC+9VL6UbUxIvowpVe6j1Ja0EdL65uUvqV+HaVvz/+ciIaJ6GIiWkfpBXGvENF3p74f0cyFPv37TL87Wv4LncMLxoeOevKZBrXHp7LUtMfeFWrDi/uq4TLjks3Gh4etD99Vn5ttjHqh+zCJ56nDbK6m9C3znxHRPxDRBBFdPu33V1P6EbSfENHZRHQ9pZ89/ymlZX4dEX186ve/OPVnZir0Y7/PUfktdJbnIx+2d+KTzzREvrlWZZHjcLf22LtVmZtR5OSD1ks1dvJUkc/i81DoMcvT2q85wInkr9A5fN/6xqc6+clnGoyT9+ssco17tMcOU2rDi/u4vsqwfNJw4w+sl/3q8zmj5KHQrQ+TEcvbtV9mgOPJUaHLuOWwCXdnWhhbDWuUXrcvaY8djq+0Y68p+/q11ks15safdupZfF4K3Tj5gvZrCnA8OSh0adhq2FCkJ59piKvN9ym9fvdpjx3mYeDgEjPYeFv6dD7ZZb18T7sk55K8FLrl8AOqFe/hTlAMKoUesxywrvG5qJJcTnTk2JvpwAJEldHVGguccfKg9tjh5PQNJnF5KFlnXLjTsjxjvRxWL868FroPk1FldLX2awYwk7YWesyNe2IOV2oPuoiMC+9RKXTc77p4+mVpxPL22MlWW5VH0utaUOivHvO49wLkVEsLPWZ5yXDykBkMH6Da8OJZtwYWzLr6u3UWONmlPXZovXOr+84tcfhty8FbDru7vNCf1X49AGaSbaGz7Dc+PGxcsrnkxt5K25uv0x5gtyhz8x0qixuHL2uPHTTUTjFu9NfLrrHOuEbFcOMxy/J8NxS69WES98WAPFp4obMcirnxp9ZLtezr15Z27DXag+lmEcvbVQrdyVe0xw75URqUFeUdcknkm2vjarLVsnzecvi69RJO5mfzeSt0/Bwd8ui4hW5YxqwLw8aFB4wPFevllsjVrym75FLcfjV/+ri+SmVxc+FR7bFD5+gdavb0cbjAernCsKyPq8lW66VqODxoWf7YsnzTcvKMcWGvYWlaL/sty5/nrdAth03a+xIACip9RKfKwoYnUUFblXx4V/ooWr1Cjzl8Vns/AEBBlXfIJRoLm+HGY9pjh+4UsXxCr9TlG9rjB4CCWlkZv0il0H14XHvs0L3UztQ5eUZ77ABQUL2+8SadhS3s1h47dK++arhM5R+yLGPaYweAgioNyW+qFLoP39IeO3Svnm0jZ2oc97EPL2qPHQAKKnJyvsrCxuFJ7bFDd1P6h+yk9rgBoKCigfp5KgsbC36WCHpqE4txhg4AhRJXxt+odKYyoj126F5n+++epVLoTia0xw4ABdU3mMQ6hS57tMcO3at3qNmjctxzwEVxANAaZW5GGgubYRnVHjt0r/J2nePeemlojx0ACspwvaRzpiJ17bFD97LV8Gs6hd7AO1MA0Bo9bqRX6UwlaI8dupfWxzVjJ09pjx0ACkrrZ4mGpak9duheWrc8ti4Ma48dAAqqNCgrlAodFweBGq3HBluf4CmDANAaZ1XD2SoLG4fntMcO3cv6fVeoHPdVeUR77ABQUFqfx7Ve9muPHbqXZblK47g3LjygPXYAKCi1e1rjBhugKPLNtSrHPYd7tMcOAEXVL0tVztA5/EB76NC9zKCsVznuXeNz2mMHgKKqDavc09py4wXtoUP3sr7xUZXj3ktVe+wAUFT9k6drLGwxh4PaQ4fuZX24SeO4Ny4Z0B47ABTVhpFTVQrdh5e1hw7dK+bGFp1Cl9u0xw4ABaaxsFmP50KDHlMJG1X+IVtNtmqPHQAKLHbyskqhDxxcoj126E6G5ZMq/5Dlxs3aYweAArNevqexuJV3yCXaY4fuZFl+X+OYj1zjeu2xA0CBWS9BY3EzTh7UHjt0n2hAyipn5z5MRi65Rnv8AFBg1odvay1wxiWbtccPXeTm8V8xPjyudbxbL1do7wIAKDDjwgN6C1x6pl7y8qEeN9KrvS+guAzLessh0TzWS16s9n4AgAKLWG7XXOQQpDsih4mOLNKe7wBQYOWhZJ3+Yocghc+I9lwHgII7t7rv3BwsdghS6MQcPqs91wGgC1gv+7UXPAQpcsqusU57ngNAFzAcHtRe8BCkyIkGpKw9zwGgC9hq2KC94CFIUWOcPKs9xwGgSywbGDlHe9FDkKIG91sAgLYyHL6svfAhSPEih5ffMbpce34DQBeJXP0a/cUPQYoV48ID2nMbALqQZRHtBRBBipSyG71Ue14DQBeKOHxEewFEkKIkZnlae04DQBezPqg8fQ1BipaoKqu15zMAdDFbCWu0F0IE6fQYJ1/RnssAAGS9fEN7QUSQjg2HF3qHmj3a8xgAgIwb/XX1RRFBOjXVsEF7DgMAvMo4+Zj6woggHZfkUe25CwDwGtbLLv0FEkE6IzEnB0qDskJ73gIAvEbPtpEzrQ/f1l4oEaQTElVGV2vPWQCA4zqrGs42PuzVXiwRJM8xleQ67bkKADCrN3y6vtJ6wefTEWSmcOjXnqMAAHNWvu3Z18dOnlJfPBEkN5HDEcsntOcmAMD81YYXGw5f1V9IEUQ3sQ8vWr/vCu0pCQBwUiyHfu0FFUG0YljGIifna89DAIBMlN3opYZlTHtxRZC2xoXh5bUJPN8cAIqlZ9vImYbD3eqLLIK0I7j4DQCKLuZwpfWyX33BRZAWxHDyUI9LerXnGQBAe/TL0jLLDTHL09oLMIJklD9cWRm/SHtqAQCoKe+QS2KX7LQcXsjBoowgcw+H7xsnO0uD8pva8wgAID8GDi6JKvJhy+Fe4xr71BdrBDkmsQ8vGm48ZpzcVnbJpdpTBgCgI/S4pNe48B7r5ZbYJTutC49aTp5B2SPtizRiH75ofNjY6xtv0p4TAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACfy75LzNEjWYwl8AAAAAElFTkSuQmCC",
"scale": 15,
"svg": ""
}
},
"66129eb179764e3ca7d5dbc429d20ba7": {
"model_module": "jupyter-sankey-widget",
"model_module_version": "^0.2.3",
"model_name": "SankeyModel",
"state": {
"_model_module_version": "^0.2.3",
"_view_module_version": "^0.2.3",
"layout": "IPY_MODEL_d944a9a6144442a3afdf56dffbee2d7f",
"links": [
{
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",
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