{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Analyze a BigDFT run" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this example we will inspect how the BigDFT python library can be used to retrieve the results from a run.\n", "\n", "As a first operation we have to be sure that the path for the BigDFT scripts is present in the PYTHONPATH.\n", "If not so, this might be updated by the script in the following way:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [], "source": [ "#write here the position of the BigDFT installation (usually /install/lib/pythonX.X/site-packages)\n", "import os\n", "BIGDFT_PYTHONDIR=os.path.abspath(\n", " os.path.join(os.pardir,os.pardir,'src','python')\n", " ) #refer to the sources, only for test \n", "#then update the path\n", "import sys\n", "if BIGDFT_PYTHONDIR not in sys.path: \n", " sys.path+=[BIGDFT_PYTHONDIR]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can load the Logfiles module:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/usr/local/lib/python2.7/dist-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n", " warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n" ] } ], "source": [ "from BigDFT import Logfiles as lf \n", "#for interactive plots remove the following line\n", "%matplotlib inline " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let us now load a file into a instance of a Logfile class. Imagine that our logfile corresponds to a single-point run, and it is present in a file named \"log-HBDMI.yaml\":\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "HBDMI=lf.Logfile('testfiles/log-HBDMI.yaml')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The run is now loaded. To inspect its behaviour we might print it down to inspect the usual information:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "- Atom types:\n", " - C\n", " - H\n", " - N\n", " - O\n", "- Cell: Free BC\n", "- Convergence criterion on forces: 0.0\n", "- Symmetry group: disabled\n", "- Energy: -127.35074499502582\n", "- fermi_level: -0.1921099447862\n", "- Max val of Forces: 0.01730347812308\n", "- Number of Atoms: 28\n", "- Convergence criterion on Wfn. Residue: 0.0001\n", "- No. of KS orbitals per k-point:\n", " - 41\n", " - 0\n", "\n" ] } ], "source": [ "print HBDMI\n", "#HBDMI.geopt_plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The above information can also be accessed separately, by having a look at the attributes of the HBDMI object:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "['evals',\n", " 'forcemax_cv',\n", " 'log',\n", " 'symmetry',\n", " 'energy',\n", " 'label',\n", " 'forcemax',\n", " 'fermi_level',\n", " 'forces',\n", " 'nat',\n", " 'astruct',\n", " 'gnrm_cv']" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "HBDMI.__dict__.keys() #you may also type: dir(HBDMI)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For this reason, we might consider to postprocess some of the variables for study of the system. Here an example:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The average energy per atom is: -4.54824089268 ( -127.350744995 Ha), 28 atoms)\n", "There are also, [41, 0] (up,down) orbitals in the run\n" ] } ], "source": [ "print 'The average energy per atom is:',HBDMI.energy/HBDMI.nat,\\\n", " '(',HBDMI.energy,' Ha),',HBDMI.nat,' atoms)'\n", "print 'There are also,',HBDMI.evals[0].info,' (up,down) orbitals in the run'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We might access the Density of States of this system (note that if the matplotlib inlining is deactivated, the RadioButton widget below allows to adjust the smearing):" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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AihUrEn7M/PnzMcYwcuTIqOtMnDiR8ePHY61l1qxZzW5nc3Xt2pXa2lo2b97c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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "HBDMIDos=HBDMI.get_dos(label='HBDMI molecule')\n", "HBDMIDos.plot(sigma=0.1)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "HBDMI.wfn_plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Case of a periodic system" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The above case was a Free BC molecule single point run. Let us now consider the case of a periodic calculation.\n", "We take as an example a logfile coming from one run of the DeltaTest benchmark (see [this page](https://molmod.ugent.be/deltacodesdft) to know what it is all about). In any case, let us load the \"log-K-1.0.yaml\" file:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "- Atom types:\n", " - K\n", "- Cell:\n", " - 9.98888442684\n", " - 9.98888442684\n", " - 9.98888442684\n", "- Convergence criterion on forces: 0.0\n", "- Symmetry group: not prim.\n", "- Energy: -56.52301363451743\n", "- fermi_level: 0.0609691899665294\n", "- Max val of Forces: 2.038812434232e-07\n", "- Number of Atoms: 2\n", "- Convergence criterion on Wfn. Residue: 1e-08\n", "- kpt_mesh:\n", " - 15\n", " - 15\n", " - 15\n", "- No. of KS orbitals per k-point:\n", " - 13\n", " - 0\n", "\n" ] } ], "source": [ "K=lf.Logfile('testfiles/log-K.yaml')\n", "print K" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here we can see that there are also other attributes available, like the k-points and the pressure (in GPa):" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "['__doc__',\n", " '__getitem__',\n", " '__init__',\n", " '__module__',\n", " '__str__',\n", " '_get_bz',\n", " '_initialize_class',\n", " '_print_information',\n", " 'astruct',\n", " 'energy',\n", " 'evals',\n", " 'fermi_level',\n", " 'forcemax',\n", " 'forcemax_cv',\n", " 'geopt_plot',\n", " 'get_brillouin_zone',\n", " 'get_dos',\n", " 'kpt_mesh',\n", " 'kpts',\n", " 'label',\n", " 'log',\n", " 'nat',\n", " 'nkpt',\n", " 'symmetry']" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dir(K)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here we might trace the density of states but also the band structure plot, in a similar fashion (sse also the Band Structure notebook):" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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qqxQXF3PllVeW+wu5UaNGnHPOOSxZsgSAI488ks6dO/PAAw+wf/9+zj33XH70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\nq1+uwTvvyDEH11jm2YPIGv3XliOShgBvACPNbG7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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "lattice [[ 9.98888443 0. 0. ]\n", " [ 0. 9.98888443 0. ]\n", " [ 0. 0. 9.98888443]]\n", "spacegroup Im-3m (229)\n", "Lattice found: cubic\n", "irreductible k-points 120\n", "Interpolation bias 2.38385636069e-09\n" ] }, { "data": { "image/png": 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mTHjtgHWZ1WIPqolGP6C7+32i0Xfp61sFCEymfNzu2Qwf/kfc7qOw28fvdnyQ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\nP/00ly74H/z4/9zEnEsuKbS3/l4VROPSrvgjbVuXe5nca+a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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "K.get_dos().plot()\n", "K.get_brillouin_zone().plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As another example for the system we might inspect the kpoints:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'Wgt': 0.0003, 'Bz': [0.0, 0.0, 0.0], 'Rc': [0.0, 0.0, 0.0]}\n", "{'Wgt': 0.0024, 'Bz': [0.2935, 0.2935, 0.2935], 'Rc': [0.4667, 0.4667, 0.4667]}\n" ] } ], "source": [ "print K.kpts[0]\n", "print K.kpts[-1]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Case of a Geometry optimization" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For a geometry optimization the situation is similar, with the extra point that the code automatically recognize multiple runs inside the logfile. Let us see the example of the following logfile:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "WARNING: More than one document are present expected a single document in the stream\n", " in \"\", line 2, column 2\n", "but found another document\n", " in \"\", line 729, column 1\n", "Loading...\n", "21 %\n", "29 %\n", "37 %\n", "45 %\n", "53 %\n", "61 %\n", "68 %\n", "76 %\n", "84 %\n", "92 %\n", "100 %\n", "Found 11 different runs\n", "- Atom types:\n", " - C\n", " - H\n", "- Cell: Free BC\n", "- Convergence criterion on forces: 0.01\n", "- Symmetry group: disabled\n", "- Energy: -14.900068217309986\n", "- fermi_level: -0.2935133380623\n", "- Threshold fluctuation of Forces: 0.000771111\n", "- Max val of Forces: 0.00376314\n", "- Number of Atoms: 8\n", "- Convergence criterion on Wfn. Residue: 0.0001\n", "- No. of KS orbitals per k-point:\n", " - 7\n", " - 0\n", "\n" ] } ], "source": [ "geopt=lf.Logfile('testfiles/GEOPT-all_sqnmbiomode.out.ref.yaml')\n", "print geopt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The interesting point is that now the logfile can be iterated among the different geometry steps:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0 -14.8960952539\n", "1 -14.8973771723\n", "2 -14.8984824334\n", "3 -14.8988612802\n", "4 -14.8992643257\n", "5 -14.8995896652\n", "6 -14.8996942689\n", "7 -14.8997814206\n", "8 -14.8998305686\n", "9 -14.8999870545\n", "10 -14.9000682173\n" ] } ], "source": [ "en=[l.energy for l in geopt]\n", "for i,e in enumerate(en):\n", " print i,e" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The geopt_plot() function allows to plot the relation beween energy and forces, where it can be also seen that the desired criterion is reached. Errorbars show the local fluctuation of the forces, an indication of the (cleaned) center of mass drift. See the example:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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vnjVp0sRSU1Pt3//+d5FrbM+ePTZo0CCrX7+++Xw+v2uiefPmftdtSe9dQS++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\n0VT1u7uvju1a5e67Cuq5E1jSw3eJ/GfpZFoRqRJ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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "geopt.geopt_plot()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.6" } }, "nbformat": 4, "nbformat_minor": 0 }