From 26e35901936205740b5bc925045e27fb2b684b8e Mon Sep 17 00:00:00 2001 From: Oliver Beckstein Date: Tue, 18 Apr 2017 10:24:55 -0700 Subject: [PATCH] updated example notebook --- docs/propkatraj-example.ipynb | 38 ++++++++++++++++++++--------------- 1 file changed, 22 insertions(+), 16 deletions(-) diff --git a/docs/propkatraj-example.ipynb b/docs/propkatraj-example.ipynb index d660aad..552fff2 100644 --- a/docs/propkatraj-example.ipynb +++ b/docs/propkatraj-example.ipynb @@ -10,7 +10,9 @@ { "cell_type": "code", "execution_count": 1, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "import MDAnalysis as mda\n", @@ -104,8 +106,10 @@ " \n", " Results\n", " -------\n", - " sim : :class:`mdsynthesis.Sim`\n", - " Sim that was operated on. Returned here for convenience; useful with `dask`.\n", + " pkas : :class:`pandas.DataFrame`\n", + " DataFrame giving estimated pKa value for each residue for each\n", + " trajectory frame. Residue numbers are given as column labels, times as\n", + " row labels.\n", "\n" ] } @@ -153,7 +157,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -1941,7 +1945,7 @@ "[98 rows x 75 columns]" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -1952,7 +1956,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -2228,7 +2232,7 @@ "[8 rows x 75 columns]" ] }, - "execution_count": 11, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -2246,8 +2250,10 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": {}, + "execution_count": 11, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "import seaborn as sns\n", @@ -2256,14 +2262,14 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 12, "metadata": {}, "outputs": [ { "data": { - 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HcvDg8h4o293nyAx72DrvHwBgJ0mqAADbtlkioJkkQCIRkCz/W12YOp/sH2580PDyEpQX\n5qfr919Z3IHIgHYywx62zvsHoL1WTzhJkqmpC0nW3v9td8IJdBNJFQBg26qJgL2N9pJayQ88P3e+\n4TkWKq2PqxdVKlc2P2h0V2vOAwNg/U1+9b1RKu2vPXejN/mr9zqanDxb27/hgx982GAuADDwhobq\n7z8M/UJSpUUmJ88mMSMGgMG1t5T8+W/bfLC/kf/yb663MJoet5SNq02WVv7f6F5lqcHzQObn55Os\nTaoAALB1jSacvOMd7zFWSl+SVGmRxx77VJLkwx/+aIcjAQB62e23v7LpPVXGxw81PGajPhgkq2/y\nk9bvi3f69BNr2gYOAGD7WrG8sKWFO8O1EYNAUqUFJifP5plnvlRr+7AAYNBUKleyMLe9apOFSlJZ\ntGRVMzd+rR4U7hUqg+lGlUqlbhsA2Lrp6alMT03lwL7xuv17do0kSRZn6pdoX5ptsPcgQAtIqrRA\ntUql2latAgDspJmZmU6H0BEqgwEABseBfeM59te/f0uvPf7z39niaGjWy1/+1Tl37ulaG/qRpEoL\nXLjwbN02AAyKUml/Fodnt72nSmnUHgfNmJkZvNnwKoPpVqVSqW4bgMF26tSjOXPmqTXPVSrLVdmr\n9/W6++7XrFmmEnrdf/gPv7am/cADb+9gNLAzJFVa4NZbX1K7yb/11pd0NhgAoK+svyFfXaXytrd9\ne8bGxpL0/w25ymC61V13vbo2G/Ouu17d4WgA6Gbz8/NJ1iZVAOg9kiot8NrXvi6PP/7pWpsbs36w\nyMwNAGhsdZXKzEylllTpdyqD6VZf+MJvrmnfc8/rOxgNAN3i6NH7XzSOMaj74m1FpXIl83PzW17G\n69LsdEaWRlocFc04cuTe2jjpkSP3djYY2CGSKlu0OhFw8eLF2vM//uM/lp//+X+fRCJgq8zcAKBT\nunEj9PU35G9+87eu6R+Um3KVwQAA0P3uuef1OX36iVob+pGkCh23frDIzA2A3rRQWd4XpZ5ry/ny\n7N5gsthCJclo6+O6EZ/85D9Pknz/9//zzgbCi9x33wM5ceJYrQ3d4siRe2u/m2ZjAkBrlEr7MzpU\n2tZG9cNjQy2Oima5JqLfSaps0epEwOTk2dqN1Ac/+HBXzW4FgHYYHz+0Yf/0zFSS5ObRDY4b3fw8\nO2ly8myeffYrtbbv8+4yMXE4e/bsqbWhW0xMHM4dd9xZawMADDoVKvQ7SZUWmJg4nN273eQDMLiO\nHTuxYX8vVCFWq1Sq7W6tVhkaGsrS0lKtPSgmJ8/m6tWrtbZrLho5fvyhTE9PNeyv9lU/l+oZHz+0\n6efaamZjAkDrXZqdbrinyszC8j6DY3tLDV87Pta5CVtAf5NUaZFB2SQWAPrVhQvn67a7zYEDB3Px\n4nO19qB47LFPrWl/+MMf7WA0dLPp6alcmLqQlBpcnw8PJ0kuzM3U7680eH4DknwAbJbUT3Ymsd+v\nNqtgvzq3vL7w8Fj9/XjHxw51tAoe6G+SKk3a7MvxypXLSXwx9rNTpx7NmTNP1R7Xuxi6++7XrNkf\nBgBa7eabD9SSKjfffKDD0bTPhQvP1m1DXaWx7D16ZEsvXTh1usXBADAIpqenMjU1lZvGxhses3t4\neYPBhdmluv2XZ6Z3JLaNrB/rqFSuJFne06SqE2Md/VAJD/QvSZUmTU9PZXrqQsb37avbP7Jr13Jj\nplL/9bOzOxUaHTIyssFuywD0nOqSWuvb3aZUKtVt97tbb31JnnnmS7U2ADQyOXk2iSoy2u+msfG8\n840nt/z6R37ywRZGszXz88sVIKuTKgCsJanSpGqmvpHS3r3bPgfd7ejR+1WhANBxR47cmxMnjtXa\ng+K1r31dHn/807U2ADRy+vQTSSRVoBnrxzpUgABsTlLlBlxfWmpYcbLZhrHXu3jGKwDQO3uVTEwc\nzq6VCtlBGiz6whd+c037nnte38FoAOhWk5Nnc+7c07X2IH1XAgDtIanSpNtvf+WGe6pU+zbaBMsG\nWQDQvV760pfVkiovfenLOhxNY08++Zlcv3691h6U5MLU1IW6bQBYrVqlUm1LqgCwU9bvSZR0z75E\n7CxJlSbZIAsA+luvLKu1frBoUJIqzz03XbcNAADQDsePP7Rm0n2lcqW2D1FVdQLc6uc///nPrUm+\njI8f2nSsme7W1qRKURR3J/lIuVx+XVEUfz7Jx5MsJplP8u3lcvkr647/7STPrzz8g3K5/EA7470R\nCwsLnQ4BANiGiYnDueOOO2vtbjU/v1C33e+uXbtWtw0Aq/XKJAn6T6VyJXNz89vabP7yzHRGr4+0\nMCqglb785T/M7OxsdjXY/iFJaj2rtoKYn5vL/NxckuUtIuy73fvallQpiuLvJ7kvSWXlqZNJ3lsu\nl/9LURTvSPLBJO9fdfxokqFyufy6dsW4Hd4MAND7emHwZXHxWt12v9u9e3euXr1aawNAPb0ySQKA\n/lRNpTROu9AP2nlH+vtJjiR5bOXxm8rl8h+vimNu3fFfk2SsKIrPrvR/d7lc/o9tifQGTU6ezeLi\nYq3twg02tn7NSetNAp3i86h3vPSlL88zz3yp1oZuMjl5NokBXOgWvTBJgv5TKu3Pnl2lvPONJ7d8\njkd+8sHs3WcoFrrV+j236y3/VatQWVXNMjIysuYe077bva9tSZVyufxTRVG8atXjP06Soij+SpL3\nJHntupfMJPm+JD+a5M8mebIoiqJcLm84JfOWW8aye/dwK0Ov60d+5Efya7/2a0mSqakX3kwf+cg/\nyaFDy2+Mr/u6r8vb3/72HY+l3wwP70qS3HbbTR2OhFb5zu/8zly48MKmwpcvX87c3At51HrrTf7S\nL/1ifuu3zqw5z6233prv//7v3+Fo2QmrPzOT5d+BJLnpphfe5z4z+8v6n3l1Y/H3v//v1p7rhp/5\nvn17a987yQufQzfffPOaY7rpO+nmm2/O888/X2t3U2w76b3vfXf+3t/7e7X2oPy9uXGr39PbOceN\n/I595jM/lST5q3/1Ndv+s4Ht816kE5a/fxZbcp5OXuf0yphMr8RJf/nEJ35wzeP1970LCwt57rnn\nkiQHDhzI3r17k3THvS+t1dG1E4qi+NtJHkryN8vl8vl13b+b5PfK5fJSkt8timIqyUuTfHmjcz73\n3MyOxLre7OxCFheXB4LXr/FdfX52diHnz19uSzy9ZP2mTutV+44effOG57GpU+/4yleezdTU+dy8\nb/nxniR7Rl/on13ZEmDf3uurXjWTucsvvJ+fn00WF697T/Wo1Z+ZSWpJtbGx0ppj/Hz7x/qf+dDK\nLJ3Vz3XDz/wNb/i2vOEN31Z7/OCD70ySfOxj/3zNcZ2Oc7WDB8drSZWDB8e7Krad9LKX/em84hWv\nqrUH5e/NjXv++eeTubksnDq9tRNUZvL8DVxzTE6ezRe/+MUkya/8ylOqVQAG1Orr3O2ep5PXOdW/\nR7dfa/VKnPS39feTH/rQP6olVb7qq16Whx/+v2p9fld7z0ZJ244lVYqieEuSdyR5Xblcnq5zyFuT\n/C9J/m5RFC9LcnOSP65zXEccPXp/bSmQt771aG1m68jISE6efKSToXW96empTE+dzy2je+r2712Z\nXLhUudjwHM/NXd2J0Nghm+05tG9va85D91r9mZm8MHDt87J/rf6ZT06erW0Y+453vMeA4zaVSqW6\n7UFw330PdDoEeJHTp59Y0/YZBwCwfZZqppt1JKlSFMVwkh9M8kyS00VRJMmvlMvlY0VR/OskDyf5\nl0k+XRTFr2d5j5+3brb0V6ccOHAwzz77lVqbzd0yuicf/cZiy6//wGfLLYwGaLVmK9KqyZVGVKT1\nBwOOrXXkyL21JNWgrRnvd4dmlEr7Mzu8K3uPHtnS6xdOnU5pdKzFUQFAd2jHvdpODIavP2e9OA2w\n97fqhPbVv0fdZpDv1QZNW5Mq5XL5S0n+8srD8QbHfPuqh0d3OiZuTDNfjIkvMtYqlfZn79Bs3vs3\n61cnNePj//5q9ox17xcna335y3+Y2dnZ1fuyrVHdt21qav3Kj2uPUZ0ELzYxcTh33HFnrQ10lptn\nAKouz0znkZ98sGH/3EIlSTK6t3618eWZ6Rzat7MbWC+vHjKVm8fqDstlz/BIkuTa7FLDczw/U2/B\nmcZ2YjB8ZGSkZeeiO/Xiihfu1QZHR/dU6RdXrlyu2x4EvZAlBjpjaCgZ28ZE35n2bJFFGxhwbD3/\njtA9JiYO1/b76eab58nJs0m6O0aAXjY+vnky5Mrs8hjK3n31x1AO7TvU1Hm26+ax8XzgW35gy6//\n6M+8b8P+nRgMX39O6Fbu1QaDpEoL3HrrS/LMM1+qtftZL2aJgfYrlfZn167ZvOFbtn6On/6ZZF+D\nmw16i9k6reffEbhR1aUYfX4A7Ixmli02hgL9z7VWd9mpvXkkVVrgvvseqM3AtYEqALyY2TpAv5qc\nPFubYDU5ebYrb6QnJ8/m3Lmna+1ujBEAGGyt2O/HvqxsplWrLkmqtECvlPwDQKf4fgT6VbUCpNru\nxs+7XogRgN5lMJxWqO73Mz56oG7/yK6VfXor1+q/fu7SToVGj9jss6iRM2eeWlPN0sznkaRKi6hQ\nAVhrZmZ5Ca96FhaW/79378av37ev9XEBQCtVKpW67W7SCzEC0Luqg+EH9o3X7d+za3lT+cWZpbr9\nl2ZvbON7+lN1WaZGSns237R1s3PQ37785T/M7Oxsdg0NNTxmaWn5c2h66kLd/utLS039HkmqtIjZ\nXgAv2GxzxdnZ5ZkD+/Y1Pm7fvuY2ewSgf+zUmscAwLJK5Urm5uY33Wx+I5dmpjN6fWTNcwf2jecf\nfPMPbOl8//fPbj0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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -2287,7 +2293,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 13, "metadata": { "collapsed": true }, @@ -2298,14 +2304,14 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 14, "metadata": {}, "outputs": [ { "data": { - "image/png": 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Fv1/RZSr2OjKzlwPXAh3Are7+iXz5ZGw/BrjT3dvCf/cB3wDG3P34YsqUJ68Z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\nAAAASUVORK5CYII=\n", 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fLuZcZeXzdoK//S7gZwTnfHf4vnbgfwP/5O7fyC5PRF7vJOJzZGZ/Ff5encDV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\nRU5ErkJggg==\n", 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