diff --git a/beaker-notebooks/errorbars_html.bkr b/beaker-notebooks/errorbars_html.bkr
index 8167c0709bd314dcfc8d75f11a51c01cf9d86e6f..d743a376527f0d2382525bd8fcd45e804b3a9709 100644
--- a/beaker-notebooks/errorbars_html.bkr
+++ b/beaker-notebooks/errorbars_html.bkr
@@ -40,13 +40,12 @@
"<p style=\"color: #20335d;;font-weight: 900; font-size: 22pt;\"> NOMAD analytics toolkit</p>",
"<label style=\"text-align: center; color: #20335d; font-weight: 900; font-size: 18pt;\">Analyzing and Estimating Error Bars from High-Accuracy References:</label> <label style=\"color: #20335d;font-weight: 900; font-size: 15pt;\"> Using <a href=\"https://nomad-coe.eu/\">NoMaD</a> for data retrival.</label>",
" </p>",
- " <p style=\"font-size: 15px;\"> Developed by Björn Bieniek and Mikkel Strange</a>, 2017.</p>",
" <p style=\"font-size: 15px; \"> <br> ",
- " Beaker Notebook: Björn Bieniek, Mikkel Strange, Christian Carbogno. <br> <br> ",
- " Curated VASP data: Elisabeth Wruss, Oliver T. Hofmann, Institute of Solid State Physics, Graz University of Technology, NAWI Graz, Petergasse 16, 8010 Graz, Austria<br>",
- " Curated GPAW data: Mikkel Strange, Kristian Sommer Thygesen, CAMD, Department of Physics, Technical University of Denmark. Fysikvej 1 2800 Kgs. Lyngby, Denmark<br>",
- " Curated exciting data: Sven Lubeck, Andris Gulans, Humboldt-Universität zu Berlin, Department of Physics, Zum Grossen Windkanal 6, D-12489 Berlin<br>",
- " Curated FHI-aims data: Björn Bieniek, Christian Carbogno, Fritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany</p>",
+ "<b> Beaker Notebook:</b> Björn Bieniek, Mikkel Strange, and Christian Carbogno. <br> <br> ",
+ "<b> Curated VASP data: </b>Elisabeth Wruss, and Oliver T. Hofmann, <i>Institute of Solid State Physics, Graz University of Technology, NAWI Graz, Petergasse 16, 8010 Graz, Austria</i><br>",
+ " <b>Curated GPAW data:</b> Mikkel Strange, and Kristian Sommer Thygesen, <i>CAMD, Department of Physics, Technical University of Denmark. Fysikvej 1 2800 Kgs. Lyngby, Denmark</i><br>",
+ " <b>Curated exciting data: </b>Sven Lubeck and Andris Gulans, <i>Humboldt-Universität zu Berlin, Department of Physics, Zum Grossen Windkanal 6, D-12489 Berlin</i><br>",
+ " <b>Curated FHI-aims data: </b>Björn Bieniek, and Christian Carbogno, <i>Fritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany</i></p>",
"",
"",
""
@@ -254,8 +253,8 @@
"state": {},
"selectedType": "Hidden",
"pluginName": "IPython",
- "shellId": "27A64174BE534D8A81CD4007A8828BAE",
- "elapsedTime": 626,
+ "shellId": "4CE22EA14B7A45608ED58BBCC25D6400",
+ "elapsedTime": 628,
"height": 51
},
"evaluatorReader": true,
@@ -305,44 +304,39 @@
},
"selectedType": "Results",
"pluginName": "IPython",
- "shellId": "27A64174BE534D8A81CD4007A8828BAE",
- "elapsedTime": 126505,
- "height": 55
+ "shellId": "4CE22EA14B7A45608ED58BBCC25D6400",
+ "elapsedTime": 137974,
+ "height": 56
},
"evaluatorReader": true,
"lineCount": 21,
"initialization": true
},
{
- "id": "markdownZ4RWmh",
- "type": "markdown",
- "body": [
- "<div style=\"font-size: 150%; font-weight: bold;\">Introduction</div>"
- ],
- "evaluatorReader": false
+ "id": "section2UO5n4",
+ "type": "section",
+ "title": "Introduction",
+ "level": 1,
+ "evaluatorReader": false,
+ "collapsed": true
},
{
"id": "markdownNpN3Pg",
"type": "markdown",
"body": [
- "",
- "",
- "",
"<div style=\"max-width: 800px;\">Electronic-structure theory has become an invaluable tool in materials science. Still, the precision of different approaches has only recently been scrutinized thoroughly (for the PBE functional) using extremely accurate numerical settings [1]. A synergistic effort showed that \"most recent codes and methods converge toward a single value\", if extremely accurate and computationally expensive numerical settings ",
"are employed. Little is known, however, about code- and method-specific deviances and error bars that arise under numerical settings commonly used in actual calculations. <br><br>",
"In this notebook, we use the NOMAD infrastructure to shed light on this issue by systematically investigating and analyzing the deviances in total and relative energies as function of typical settings for basis sets, k-grids, etc. For this purpose, the NOMAD team has systematically computed the properties of 71 elemental [1] and 81 binary solids in four different electronic-structure codes using various different computational settings, including extremely accurate ones that constitute a fully converged reference.<br><br>",
"One the one hand, this allows to analyze and compare the convergence behavior of different codes with respect to different settings. On the other hand, this allows to develop models ",
"to estimate the errors in calculations for which no highly converged reference is available. As an example, we have here discuss the following function",
- "<center>",
- "$\\hat{\\Delta}E_{tot}=\\frac{N_{A}\\Delta E_A+N_{B}\\Delta E_B}{N_A+N_B}$.",
- "</center><br><br>",
- "that is used to estimate and predict the (total energy and relative energy) erros in binary systems with $N_A$/$N_B$ atoms of species A/B",
- "from the errors $\\Delta E_{A} $/$ \\Delta E_{B}$ occuring in the respective elemental solids.</div>",
+ "$$\\hat{\\Delta}E_{tot}=\\frac{N_{A}\\Delta E_A+N_{B}\\Delta E_B}{N_A+N_B}$$",
+ "that is used to estimate and predict the (total energy and relative energy) errors in binary systems from the high-accuracy calculations performed for the elemental solids. Here, $N_A$ and $N_B$ denote the number of atoms of species A and B",
+ "in the binary system and $\\Delta E_{A} $ and $ \\Delta E_{B}$ occurring in the respective elemental solids.</div>",
"<br><br>",
"<div style=\"max-width: 800px;\">",
- "[1] K. Lejaeghere et al., Science 351 (2016).<br>",
- "[2] https://nomad-repository.eu.<br>",
- "[3] Reference for calculations: http://dx.doi.org/10.17172/NOMAD/2017.01.24-1",
+ "<b>[1]</b> K. Lejaeghere et al., Science 351 (2016).<br>",
+ "<b>[2]</b> https://nomad-repository.eu.<br>",
+ "<b>[3]</b> Reference for calculations: http://dx.doi.org/10.17172/NOMAD/2017.01.24-1",
"</div>",
"<div style=\"height: 3em;\"></div>",
"<br><br>",
@@ -350,11 +344,20 @@
],
"evaluatorReader": false
},
+ {
+ "id": "sectionja0X3y",
+ "type": "section",
+ "title": "Data Browser: Analyzing the Curated Reference Data Set",
+ "level": 1,
+ "evaluatorReader": false,
+ "collapsed": true
+ },
{
"id": "markdownIvKOSd",
"type": "markdown",
"body": [
- "<div style=\"font-size: 150%; font-weight: bold;\">Data Browser: Analyzing the Curated Reference Data Set</div>"
+ "<p>The next cells allow to inspect the deviations occurring in total and relative energy as function of the numerical settings.<br>",
+ "Click on <i>Explanation</i> for further details and instructions."
],
"evaluatorReader": false
},
@@ -382,8 +385,10 @@
" <button type=\"button\" class=\"close\" data-dismiss=\"modal\" aria-label=\"Close\"><span aria-hidden=\"true\">×</span></button>",
" <h4 class=\"modal-title\" id=\"phasediagram-motivation-modal-label\">Explanation</h4>",
" <div style=\"max-width: 800px;\">",
- "The interface below allows you to explore the error due to numerical settings for the 71 elementary solids and the 82 binary systems (Drop down menu \"Systems\"). The left plot (button \"Add plot\") shows the error with respect to highly converged settings for each electronic structure. The last data set is plotted as periodic table below. The color of the elements relates to the error. By chosing the code (Drop down menu \"Code\") the number of possible numerical settings avaiable in the interface is in- or decresed.<br>",
- "In the right plot (button \"Predict binaries\") the error for the binary systems is calculated from the error of the elementary systems for the selected code and numerical settings. It is plotted against the error obtained directly from the DFT calculations of the binary systems. Points on the black diagonal line indicate agreement between anlytical prediction and the DFT calulation. For points to the right/below of the diagonal the predicted error is larger than the error obtained from the DFT calulation. You can select between the error in the total energy or in the total energy relative to a calculation with cell volume increased by 5% (Drop down menu \"Quantity\"). This allows to explore the effect of error cancellation. Additionally you can explore the error in the cohesive energy for the binary systems. We define the cohesive energy as the total energy of the binary systems minus the the total energy of its constituents in their elemental solid structure, devided by the number of atoms in the binary cell.<br><br>",
+ "The interface below allows you to explore the error due to numerical settings for the 71 elementary solids and the 82 binary systems. Use the drop-down menus to choose a code, a property, and the (code-specific) numerical settings; the <i>Add el. solids/binaries</i> buttons then generate the plots. The upper plots show the errors (deviations) with respect to highly converged settings for the elemental solids (left) and binaries (right). For the elemental solids, an additional, color-coded periodic table is shown below. The color of the elements relates to the error.<br>",
+ "It is possible to inspect errors/deviations in total energy, relative energy, and cohesive energy (Drop down menu <i>Quantity</i>). Relative energies",
+ "are computed as a total energy difference with respect to a cell volume increase of 5%. This allows to explore the effect of error cancellation. Additionally you can explore the error in the cohesive energy for the binary systems. We define the cohesive energy as the total energy of the binary systems minus the the total energy of its constituents in their elemental solid structure, devided by the number of atoms in the binary cell. ",
+ "<br><br>",
"</div> ",
" </div>",
" <div class=\"modal-body phasediagram_instructions\">",
@@ -405,14 +410,14 @@
"result": {
"type": "BeakerDisplay",
"innertype": "Html",
- "object": "<script>\nvar beaker = bkHelper.getBeakerObject().beakerObj;\n</script>\n<style type=\"text/css\">\n .phasediagram_instructions{\n font-size: 15px;\n } \n</style>\n<!-- Button trigger modal -->\n<button type=\"button\" class=\"btn btn-default\" data-toggle=\"modal\" data-target=\"#phasediagram-motivation-modal\">\n Explanation\n</button>\n\n<!-- Modal -->\n<div class=\"modal fade\" id=\"phasediagram-motivation-modal\" tabindex=\"-1\" role=\"dialog\" aria-labelledby=\"phasediagram-motivation-modal-label\" style=\"display: none;\">\n <div class=\"modal-dialog modal-lg\" role=\"document\">\n <div class=\"modal-content\">\n <div class=\"modal-header\">\n <button type=\"button\" class=\"close\" data-dismiss=\"modal\" aria-label=\"Close\"><span aria-hidden=\"true\">×</span></button>\n <h4 class=\"modal-title\" id=\"phasediagram-motivation-modal-label\">Explanation</h4>\n <div style=\"max-width: 800px;\">\nThe interface below allows you to explore the error due to numerical settings for the 71 elementary solids and the 82 binary systems (Drop down menu \"Systems\"). The left plot (button \"Add plot\") shows the error with respect to highly converged settings for each electronic structure. The last data set is plotted as periodic table below. The color of the elements relates to the error. By chosing the code (Drop down menu \"Code\") the number of possible numerical settings avaiable in the interface is in- or decresed.<br>\nIn the right plot (button \"Predict binaries\") the error for the binary systems is calculated from the error of the elementary systems for the selected code and numerical settings. It is plotted against the error obtained directly from the DFT calculations of the binary systems. Points on the black diagonal line indicate agreement between anlytical prediction and the DFT calulation. For points to the right/below of the diagonal the predicted error is larger than the error obtained from the DFT calulation. You can select between the error in the total energy or in the total energy relative to a calculation with cell volume increased by 5% (Drop down menu \"Quantity\"). This allows to explore the effect of error cancellation. Additionally you can explore the error in the cohesive energy for the binary systems. We define the cohesive energy as the total energy of the binary systems minus the the total energy of its constituents in their elemental solid structure, devided by the number of atoms in the binary cell.<br><br>\n</div> \n </div>\n <div class=\"modal-body phasediagram_instructions\">\n\n </div>\n <div class=\"modal-footer\">\n <button type=\"button\" class=\"btn btn-default\" data-dismiss=\"modal\">Close</button>\n<!-- <button type=\"button\" class=\"btn btn-primary\">Save changes</button> -->\n </div>\n </div>\n </div>\n\n<div style=\"height: 3em;\"></div></div>"
+ "object": "<script>\nvar beaker = bkHelper.getBeakerObject().beakerObj;\n</script>\n<style type=\"text/css\">\n .phasediagram_instructions{\n font-size: 15px;\n } \n</style>\n<!-- Button trigger modal -->\n<button type=\"button\" class=\"btn btn-default\" data-toggle=\"modal\" data-target=\"#phasediagram-motivation-modal\">\n Explanation\n</button>\n\n<!-- Modal -->\n<div class=\"modal fade\" id=\"phasediagram-motivation-modal\" tabindex=\"-1\" role=\"dialog\" aria-labelledby=\"phasediagram-motivation-modal-label\" style=\"display: none;\">\n <div class=\"modal-dialog modal-lg\" role=\"document\">\n <div class=\"modal-content\">\n <div class=\"modal-header\">\n <button type=\"button\" class=\"close\" data-dismiss=\"modal\" aria-label=\"Close\"><span aria-hidden=\"true\">×</span></button>\n <h4 class=\"modal-title\" id=\"phasediagram-motivation-modal-label\">Explanation</h4>\n <div style=\"max-width: 800px;\">\nThe interface below allows you to explore the error due to numerical settings for the 71 elementary solids and the 82 binary systems. Use the drop-down menus to choose a code, a property, and the (code-specific) numerical settings; the <i>Add el. solids/binaries</i> buttons then generate the plots. The upper plots show the errors (deviations) with respect to highly converged settings for the elemental solids (left) and binaries (right). For the elemental solids, an additional, color-coded periodic table is shown below. The color of the elements relates to the error.<br>\nIt is possible to inspect errors/deviations in total energy, relative energy, and cohesive energy (Drop down menu <i>Quantity</i>). Relative energies\nare computed as a total energy difference with respect to a cell volume increase of 5%. This allows to explore the effect of error cancellation. Additionally you can explore the error in the cohesive energy for the binary systems. We define the cohesive energy as the total energy of the binary systems minus the the total energy of its constituents in their elemental solid structure, devided by the number of atoms in the binary cell. \n<br><br>\n</div> \n </div>\n <div class=\"modal-body phasediagram_instructions\">\n\n </div>\n <div class=\"modal-footer\">\n <button type=\"button\" class=\"btn btn-default\" data-dismiss=\"modal\">Close</button>\n<!-- <button type=\"button\" class=\"btn btn-primary\">Save changes</button> -->\n </div>\n </div>\n </div>\n\n<div style=\"height: 3em;\"></div></div>"
},
"selectedType": "BeakerDisplay",
"elapsedTime": 0,
- "height": 72
+ "height": 0
},
"evaluatorReader": true,
- "lineCount": 33,
+ "lineCount": 35,
"initialization": true
},
{
@@ -456,15 +461,15 @@
"",
" addDropdownChoice(pprec, \"light\", \"light\");",
" addDropdownChoice(pprec, \"tight\", \"tight\");",
- " addDropdownChoice(pprec, \"really_tight\", \"really_tight\");",
- " addDropdownChoice(prel, \"atomic_zora\", \"atomic_zora\");",
+ " addDropdownChoice(pprec, \"really_tight\", \"really tight\");",
+ " addDropdownChoice(prel, \"atomic_zora\", \"atomic zora\");",
" addDropdownChoice(prel, \"zora\", \"zora\");",
" addDropdownChoice(ptiers, \"minimal\", \"minimal\");",
" addDropdownChoice(ptiers, \"standard\", \"standard\");",
" addDropdownChoice(ptiers, \"tier1\", \"tier1\");",
" addDropdownChoice(ptiers, \"tier2\", \"tier2\");",
- " addDropdownChoice(pxc, \"pbe\", \"pbe\");",
- " addDropdownChoice(pxc, \"pw-lda\", \"pbw-lda\");",
+ " addDropdownChoice(pxc, \"pbe\", \"PBE\");",
+ " addDropdownChoice(pxc, \"pw-lda\", \"LDA\");",
" break;",
"",
" case \"exciting\": ",
@@ -476,7 +481,7 @@
" break;",
" ",
" case \"GPAW\": ",
- " dprec.innerHTML = '$E_{cut}$:';",
+ " dprec.innerHTML = 'PW cutoff:';",
"",
" addDropdownChoice(pprec, \"300\", \"300\");",
" addDropdownChoice(pprec, \"400\", \"400\");",
@@ -492,8 +497,8 @@
" addDropdownChoice(pprec, \"1400\", \"1100\");",
" addDropdownChoice(pprec, \"1500\", \"1100\");",
"",
- " addDropdownChoice(pxc, \"pbe\", \"pbe\");",
- " addDropdownChoice(pxc, \"pw-lda\", \"pbw-lda\");",
+ " addDropdownChoice(pxc, \"pbe\", \"PBE\");",
+ " addDropdownChoice(pxc, \"pw-lda\", \"LDA\");",
" break;",
"",
"",
@@ -560,26 +565,36 @@
" <th>XC-Functional:</th>",
" <td>",
" <select id=\"errorbar_xcfunctional\">",
- " <option value=\"PBE\" selected>PBE</option>",
- " <option value=\"LDA\">LDA</option>",
+ " <option value=\"pbe\" selected>PBE</option>",
+ " <option value=\"pw-lda\">LDA</option>",
" </select>",
" </td>",
" <td id=\"errorbar_xcfunctional_description\" style=\"white-space: pre;\"></td>",
" <th>k-point density:</th>",
" <td>",
" <select id=\"errorbar_kdensity\" >",
- " <option value=\"2\" selected>2</option>",
+ " <option value=\"2\">2</option>",
" <option value=\"4\">4</option> ",
- " <option value=\"8\">8</option> ",
+ " <option value=\"8\" selected>8</option> ",
" </select>",
" </td>",
" <td id=\"errorbar_kdensity_description\" style=\"white-space: pre;\"></td>",
- " <th id=\"errorbar_precision_name\">Precision:</th>",
+ " <th id=\"errorbar_precision_name\">PW cutoff:</th>",
" <td>",
" <select id=\"errorbar_precision\" >",
- " <option value=\"Low\" selected>Low</option>",
- " <option value=\"Normal\">Normal</option> ",
- " <option value=\"Accurate\">Acurate</option> ",
+ " <option value=\"300\">300</option>",
+ " <option value=\"400\">400</option>",
+ " <option value=\"500\">500</option>",
+ " <option value=\"600\" selected>600</option>",
+ " <option value=\"700\">700</option>",
+ " <option value=\"800\">800</option>",
+ " <option value=\"900\">900</option>",
+ " <option value=\"1000\">1000</option>",
+ " <option value=\"1100\">1100</option>",
+ " <option value=\"1200\">1200</option>",
+ " <option value=\"1300\">1300</option>",
+ " <option value=\"1400\">1400</option>",
+ " <option value=\"1500\">1500</option> ",
" </select>",
" </td>",
" <td id=\"errorbar_precision_description\" style=\"white-space: pre;\"></td>",
@@ -588,14 +603,14 @@
" <th>Tiers:</th>",
" <td><select id=\"errorbar_tiers\" ><!-- content inserted programmatically --></select></td>",
" <td id=\"errorbar_tiers_description\" style=\"white-space: pre;\"></td>",
- " <th>relativity treatment:</th>",
+ " <th>Relativity treatment:</th>",
" <td><select id=\"errorbar_relativity\" ><!-- content inserted programmatically --></select></td>",
" <td id=\"errorbar_relativity_description\" style=\"white-space: pre;\"></td>",
" <th>Code:</th>",
" <td><select id=\"errorbar_code\" onchange=\"errorUpdateForm()\">",
- " <option value=\"VASP\">VASP</option>",
+ " <option value=\"GPAW\">GPAW</option>",
" <option value=\"FHI-aims\">FHI-aims</option>",
- " <option value=\"GPAW\">GPAW</option> ",
+ " <option value=\"VASP\">VASP</option>",
" <option value=\"exciting\">exciting</option> ",
" </select></td>",
" <td id=\"errorbar_code_description\" style=\"white-space: pre;\"></td>",
@@ -636,14 +651,14 @@
"result": {
"type": "BeakerDisplay",
"innertype": "Html",
- "object": "<script>\nvar beaker = bkHelper.getBeakerObject().beakerObj;\n</script>\n<script>\n // Adds an option to a dropdown menu\n function addDropdownChoice(dropdown, value, content) {\n var el = document.createElement('option');\n el.value = value;\n el.innerHTML = content\n dropdown.appendChild(el);\n }\n \n \n function errorUpdateForm() {\n var code = document.getElementById(\"errorbar_code\").value;\n \n var dprec = document.getElementById(\"errorbar_precision_name\");\n var pprec = document.getElementById(\"errorbar_precision\"); pprec.innerHTML = '';\n var prel = document.getElementById(\"errorbar_relativity\"); prel.innerHTML = '';\n var ptiers = document.getElementById(\"errorbar_tiers\"); ptiers.innerHTML = '';\n var pxc = document.getElementById(\"errorbar_xcfunctional\"); pxc.innerHTML = '';\n\n switch(code) {\n case \"VASP\": \n dprec.innerHTML = 'Precision:';\n\n addDropdownChoice(pprec, \"Low\", \"Low\");\n addDropdownChoice(pprec, \"Normal\", \"Normal\");\n addDropdownChoice(pprec, \"Accurate\", \"Accurate\");\n addDropdownChoice(pxc, \"PBE\", \"PBE\");\n addDropdownChoice(pxc, \"LDA\", \"LDA\");\n break;\n \n case \"FHI-aims\": \n dprec.innerHTML = 'Integration grid';\n\n addDropdownChoice(pprec, \"light\", \"light\");\n addDropdownChoice(pprec, \"tight\", \"tight\");\n addDropdownChoice(pprec, \"really_tight\", \"really_tight\");\n addDropdownChoice(prel, \"atomic_zora\", \"atomic_zora\");\n addDropdownChoice(prel, \"zora\", \"zora\");\n addDropdownChoice(ptiers, \"minimal\", \"minimal\");\n addDropdownChoice(ptiers, \"standard\", \"standard\");\n addDropdownChoice(ptiers, \"tier1\", \"tier1\");\n addDropdownChoice(ptiers, \"tier2\", \"tier2\");\n addDropdownChoice(pxc, \"pbe\", \"pbe\");\n addDropdownChoice(pxc, \"pw-lda\", \"pbw-lda\");\n break;\n\n case \"exciting\": \n dprec.innerHTML = '';\n\n\n addDropdownChoice(pxc, \"pbe\", \"pbe\");\n\n break;\n \n case \"GPAW\": \n dprec.innerHTML = '$E_{cut}$:';\n\n addDropdownChoice(pprec, \"300\", \"300\");\n addDropdownChoice(pprec, \"400\", \"400\");\n addDropdownChoice(pprec, \"500\", \"500\");\n addDropdownChoice(pprec, \"600\", \"600\");\n addDropdownChoice(pprec, \"700\", \"700\");\n addDropdownChoice(pprec, \"800\", \"800\");\n addDropdownChoice(pprec, \"900\", \"900\");\n addDropdownChoice(pprec, \"1000\", \"1000\");\n addDropdownChoice(pprec, \"1100\", \"1100\");\n addDropdownChoice(pprec, \"1200\", \"1100\");\n addDropdownChoice(pprec, \"1300\", \"1100\");\n addDropdownChoice(pprec, \"1400\", \"1100\");\n addDropdownChoice(pprec, \"1500\", \"1100\");\n\n addDropdownChoice(pxc, \"pbe\", \"pbe\");\n addDropdownChoice(pxc, \"pw-lda\", \"pbw-lda\");\n break;\n\n\n }\n }\n\n\n\n \n function add_monomers() {\n beaker.ctrl_xc = document.getElementById(\"errorbar_xcfunctional\").value;\n beaker.ctrl_kpt = document.getElementById(\"errorbar_kdensity\").value;\n beaker.ctrl_prec = document.getElementById(\"errorbar_precision\").value;\n beaker.ctrl_tiers = document.getElementById(\"errorbar_tiers\").value;\n beaker.ctrl_rel = document.getElementById(\"errorbar_relativity\").value;\n beaker.ctrl_quant = document.getElementById(\"errorbar_quantity\").value;\n beaker.ctrl_code = document.getElementById(\"errorbar_code\").value;\n beaker.ctrl_button = 1\n beaker.evaluate(\"exe_cell\");\n beaker.evaluate(\"ptablecell\");\n }\n function clear_last() {\n beaker.ctrl_button = 2\n beaker.evaluate(\"exe_cell\");\n }\n function clear_plot() {\n beaker.ctrl_button = 3\n beaker.evaluate(\"exe_cell\");\n }\n function add_binaries() {\n beaker.ctrl_xc = document.getElementById(\"errorbar_xcfunctional\").value;\n beaker.ctrl_kpt = document.getElementById(\"errorbar_kdensity\").value;\n beaker.ctrl_prec = document.getElementById(\"errorbar_precision\").value;\n beaker.ctrl_tiers = document.getElementById(\"errorbar_tiers\").value;\n beaker.ctrl_rel = document.getElementById(\"errorbar_relativity\").value;\n beaker.ctrl_quant = document.getElementById(\"errorbar_quantity\").value;\n beaker.ctrl_code = document.getElementById(\"errorbar_code\").value;\n beaker.ctrl_button = 4\n beaker.evaluate(\"exe_cell\");\n }\n function clear_last_bins() {\n beaker.ctrl_button = 5\n beaker.evaluate(\"exe_cell\");\n }\n function clear_plot_bins() {\n beaker.ctrl_button = 6\n beaker.evaluate(\"exe_cell\");\n }\n</script>\n\n<style type=\"text/css\">\n \n .error_table th { font-weight: bold; padding-right: 2ex; }\n .error_table td input { margin-right: 1ex; }\n \n</style>\n\n<!-- Controls area -->\n\n<div class=\"error_control\">\n <table class=\"error_table\">\n \n <tbody><tr>\n <th>XC-Functional:</th>\n <td>\n <select id=\"errorbar_xcfunctional\">\n <option value=\"PBE\" selected=\"\">PBE</option>\n <option value=\"LDA\">LDA</option>\n </select>\n </td>\n <td id=\"errorbar_xcfunctional_description\" style=\"white-space: pre;\"></td>\n <th>k-point density:</th>\n <td>\n <select id=\"errorbar_kdensity\">\n <option value=\"2\" selected=\"\">2</option>\n <option value=\"4\">4</option> \n <option value=\"8\">8</option> \n </select>\n </td>\n <td id=\"errorbar_kdensity_description\" style=\"white-space: pre;\"></td>\n <th id=\"errorbar_precision_name\">Precision:</th>\n <td>\n <select id=\"errorbar_precision\">\n <option value=\"Low\" selected=\"\">Low</option>\n <option value=\"Normal\">Normal</option> \n <option value=\"Accurate\">Acurate</option> \n </select>\n </td>\n <td id=\"errorbar_precision_description\" style=\"white-space: pre;\"></td>\n </tr>\n <tr>\n <th>Tiers:</th>\n <td><select id=\"errorbar_tiers\"><!-- content inserted programmatically --></select></td>\n <td id=\"errorbar_tiers_description\" style=\"white-space: pre;\"></td>\n <th>relativity treatment:</th>\n <td><select id=\"errorbar_relativity\"><!-- content inserted programmatically --></select></td>\n <td id=\"errorbar_relativity_description\" style=\"white-space: pre;\"></td>\n <th>Code:</th>\n <td><select id=\"errorbar_code\" onchange=\"errorUpdateForm()\">\n <option value=\"VASP\">VASP</option>\n <option value=\"FHI-aims\">FHI-aims</option>\n <option value=\"GPAW\">GPAW</option> \n <option value=\"exciting\">exciting</option> \n </select></td>\n <td id=\"errorbar_code_description\" style=\"white-space: pre;\"></td>\n </tr> \n \n <tr>\n <th>Quantity:</th>\n <td><select id=\"errorbar_quantity\">\n <option value=\"E_tot\">Total Energy</option>\n <option value=\"relR\">relative Energy</option>\n <option value=\"E_coh\">Cohesive Energy (binaries)</option>\n </select></td>\n <td id=\"errorbar_quantity_description\" style=\"white-space: pre;\"></td> \n \n\n\n </tr>\n \n </tbody></table>\n \n <table class=\"error_table\">\n \n <tbody><tr>\n <th><button type=\"button\" class=\"btn btn-primary\" style=\"margin-top: 2ex;\" onclick=\"add_monomers();\">Add el. solids</button></th>\n <th><button type=\"button\" class=\"btn clear-primary\" style=\"margin-top: 2ex;\" onclick=\"clear_plot();\">Clear el. solids </button></th>\n <th><button type=\"button\" class=\"btn clearlast-primary\" style=\"margin-top: 2ex;\" onclick=\"clear_last();\">Clear last el. solids</button></th>\n <th><button type=\"button\" class=\"btn btn-secondary\" style=\"margin-top: 2ex;\" onclick=\"add_binaries();\">Add binaries</button></th>\n <th><button type=\"button\" class=\"btn clear-secondary\" style=\"margin-top: 2ex;\" onclick=\"clear_plot_bins();\">Clear binaries</button></th>\n <th><button type=\"button\" class=\"btn clearlast-secondary\" style=\"margin-top: 2ex;\" onclick=\"clear_last_bins();\">Clear last binaries</button></th>\n </tr>\n </tbody></table>\n</div>"
+ "object": "<script>\nvar beaker = bkHelper.getBeakerObject().beakerObj;\n</script>\n<script>\n // Adds an option to a dropdown menu\n function addDropdownChoice(dropdown, value, content) {\n var el = document.createElement('option');\n el.value = value;\n el.innerHTML = content\n dropdown.appendChild(el);\n }\n \n \n function errorUpdateForm() {\n var code = document.getElementById(\"errorbar_code\").value;\n \n var dprec = document.getElementById(\"errorbar_precision_name\");\n var pprec = document.getElementById(\"errorbar_precision\"); pprec.innerHTML = '';\n var prel = document.getElementById(\"errorbar_relativity\"); prel.innerHTML = '';\n var ptiers = document.getElementById(\"errorbar_tiers\"); ptiers.innerHTML = '';\n var pxc = document.getElementById(\"errorbar_xcfunctional\"); pxc.innerHTML = '';\n\n switch(code) {\n case \"VASP\": \n dprec.innerHTML = 'Precision:';\n\n addDropdownChoice(pprec, \"Low\", \"Low\");\n addDropdownChoice(pprec, \"Normal\", \"Normal\");\n addDropdownChoice(pprec, \"Accurate\", \"Accurate\");\n addDropdownChoice(pxc, \"PBE\", \"PBE\");\n addDropdownChoice(pxc, \"LDA\", \"LDA\");\n break;\n \n case \"FHI-aims\": \n dprec.innerHTML = 'Integration grid';\n\n addDropdownChoice(pprec, \"light\", \"light\");\n addDropdownChoice(pprec, \"tight\", \"tight\");\n addDropdownChoice(pprec, \"really_tight\", \"really tight\");\n addDropdownChoice(prel, \"atomic_zora\", \"atomic zora\");\n addDropdownChoice(prel, \"zora\", \"zora\");\n addDropdownChoice(ptiers, \"minimal\", \"minimal\");\n addDropdownChoice(ptiers, \"standard\", \"standard\");\n addDropdownChoice(ptiers, \"tier1\", \"tier1\");\n addDropdownChoice(ptiers, \"tier2\", \"tier2\");\n addDropdownChoice(pxc, \"pbe\", \"PBE\");\n addDropdownChoice(pxc, \"pw-lda\", \"LDA\");\n break;\n\n case \"exciting\": \n dprec.innerHTML = '';\n\n\n addDropdownChoice(pxc, \"pbe\", \"pbe\");\n\n break;\n \n case \"GPAW\": \n dprec.innerHTML = 'PW cutoff:';\n\n addDropdownChoice(pprec, \"300\", \"300\");\n addDropdownChoice(pprec, \"400\", \"400\");\n addDropdownChoice(pprec, \"500\", \"500\");\n addDropdownChoice(pprec, \"600\", \"600\");\n addDropdownChoice(pprec, \"700\", \"700\");\n addDropdownChoice(pprec, \"800\", \"800\");\n addDropdownChoice(pprec, \"900\", \"900\");\n addDropdownChoice(pprec, \"1000\", \"1000\");\n addDropdownChoice(pprec, \"1100\", \"1100\");\n addDropdownChoice(pprec, \"1200\", \"1100\");\n addDropdownChoice(pprec, \"1300\", \"1100\");\n addDropdownChoice(pprec, \"1400\", \"1100\");\n addDropdownChoice(pprec, \"1500\", \"1100\");\n\n addDropdownChoice(pxc, \"pbe\", \"PBE\");\n addDropdownChoice(pxc, \"pw-lda\", \"LDA\");\n break;\n\n\n }\n }\n\n\n\n \n function add_monomers() {\n beaker.ctrl_xc = document.getElementById(\"errorbar_xcfunctional\").value;\n beaker.ctrl_kpt = document.getElementById(\"errorbar_kdensity\").value;\n beaker.ctrl_prec = document.getElementById(\"errorbar_precision\").value;\n beaker.ctrl_tiers = document.getElementById(\"errorbar_tiers\").value;\n beaker.ctrl_rel = document.getElementById(\"errorbar_relativity\").value;\n beaker.ctrl_quant = document.getElementById(\"errorbar_quantity\").value;\n beaker.ctrl_code = document.getElementById(\"errorbar_code\").value;\n beaker.ctrl_button = 1\n beaker.evaluate(\"exe_cell\");\n beaker.evaluate(\"ptablecell\");\n }\n function clear_last() {\n beaker.ctrl_button = 2\n beaker.evaluate(\"exe_cell\");\n }\n function clear_plot() {\n beaker.ctrl_button = 3\n beaker.evaluate(\"exe_cell\");\n }\n function add_binaries() {\n beaker.ctrl_xc = document.getElementById(\"errorbar_xcfunctional\").value;\n beaker.ctrl_kpt = document.getElementById(\"errorbar_kdensity\").value;\n beaker.ctrl_prec = document.getElementById(\"errorbar_precision\").value;\n beaker.ctrl_tiers = document.getElementById(\"errorbar_tiers\").value;\n beaker.ctrl_rel = document.getElementById(\"errorbar_relativity\").value;\n beaker.ctrl_quant = document.getElementById(\"errorbar_quantity\").value;\n beaker.ctrl_code = document.getElementById(\"errorbar_code\").value;\n beaker.ctrl_button = 4\n beaker.evaluate(\"exe_cell\");\n }\n function clear_last_bins() {\n beaker.ctrl_button = 5\n beaker.evaluate(\"exe_cell\");\n }\n function clear_plot_bins() {\n beaker.ctrl_button = 6\n beaker.evaluate(\"exe_cell\");\n }\n</script>\n\n<style type=\"text/css\">\n \n .error_table th { font-weight: bold; padding-right: 2ex; }\n .error_table td input { margin-right: 1ex; }\n \n</style>\n\n<!-- Controls area -->\n\n<div class=\"error_control\">\n <table class=\"error_table\">\n \n <tbody><tr>\n <th>XC-Functional:</th>\n <td>\n <select id=\"errorbar_xcfunctional\">\n <option value=\"pbe\" selected=\"\">PBE</option>\n <option value=\"pw-lda\">LDA</option>\n </select>\n </td>\n <td id=\"errorbar_xcfunctional_description\" style=\"white-space: pre;\"></td>\n <th>k-point density:</th>\n <td>\n <select id=\"errorbar_kdensity\">\n <option value=\"2\">2</option>\n <option value=\"4\">4</option> \n <option value=\"8\" selected=\"\">8</option> \n </select>\n </td>\n <td id=\"errorbar_kdensity_description\" style=\"white-space: pre;\"></td>\n <th id=\"errorbar_precision_name\">PW cutoff:</th>\n <td>\n <select id=\"errorbar_precision\">\n <option value=\"300\">300</option>\n <option value=\"400\">400</option>\n <option value=\"500\">500</option>\n <option value=\"600\" selected=\"\">600</option>\n <option value=\"700\">700</option>\n <option value=\"800\">800</option>\n <option value=\"900\">900</option>\n <option value=\"1000\">1000</option>\n <option value=\"1100\">1100</option>\n <option value=\"1200\">1200</option>\n <option value=\"1300\">1300</option>\n <option value=\"1400\">1400</option>\n <option value=\"1500\">1500</option> \n </select>\n </td>\n <td id=\"errorbar_precision_description\" style=\"white-space: pre;\"></td>\n </tr>\n <tr>\n <th>Tiers:</th>\n <td><select id=\"errorbar_tiers\"><!-- content inserted programmatically --></select></td>\n <td id=\"errorbar_tiers_description\" style=\"white-space: pre;\"></td>\n <th>Relativity treatment:</th>\n <td><select id=\"errorbar_relativity\"><!-- content inserted programmatically --></select></td>\n <td id=\"errorbar_relativity_description\" style=\"white-space: pre;\"></td>\n <th>Code:</th>\n <td><select id=\"errorbar_code\" onchange=\"errorUpdateForm()\">\n <option value=\"GPAW\">GPAW</option>\n <option value=\"FHI-aims\">FHI-aims</option>\n <option value=\"VASP\">VASP</option>\n <option value=\"exciting\">exciting</option> \n </select></td>\n <td id=\"errorbar_code_description\" style=\"white-space: pre;\"></td>\n </tr> \n \n <tr>\n <th>Quantity:</th>\n <td><select id=\"errorbar_quantity\">\n <option value=\"E_tot\">Total Energy</option>\n <option value=\"relR\">relative Energy</option>\n <option value=\"E_coh\">Cohesive Energy (binaries)</option>\n </select></td>\n <td id=\"errorbar_quantity_description\" style=\"white-space: pre;\"></td> \n \n\n\n </tr>\n \n </tbody></table>\n \n <table class=\"error_table\">\n \n <tbody><tr>\n <th><button type=\"button\" class=\"btn btn-primary\" style=\"margin-top: 2ex;\" onclick=\"add_monomers();\">Add el. solids</button></th>\n <th><button type=\"button\" class=\"btn clear-primary\" style=\"margin-top: 2ex;\" onclick=\"clear_plot();\">Clear el. solids </button></th>\n <th><button type=\"button\" class=\"btn clearlast-primary\" style=\"margin-top: 2ex;\" onclick=\"clear_last();\">Clear last el. solids</button></th>\n <th><button type=\"button\" class=\"btn btn-secondary\" style=\"margin-top: 2ex;\" onclick=\"add_binaries();\">Add binaries</button></th>\n <th><button type=\"button\" class=\"btn clear-secondary\" style=\"margin-top: 2ex;\" onclick=\"clear_plot_bins();\">Clear binaries</button></th>\n <th><button type=\"button\" class=\"btn clearlast-secondary\" style=\"margin-top: 2ex;\" onclick=\"clear_last_bins();\">Clear last binaries</button></th>\n </tr>\n </tbody></table>\n</div>"
},
"selectedType": "BeakerDisplay",
"elapsedTime": 0,
- "height": 179
+ "height": 0
},
"evaluatorReader": true,
- "lineCount": 207,
+ "lineCount": 217,
"initialization": true
},
{
@@ -663,10 +678,10 @@
" # el. solids or binaries",
" mono_or_bin=ref_dict_binaries[beaker.ctrl_sys]",
" # The plot label generated from the settings of the drop down menus",
- " lab=beaker.ctrl_quant+', '+beaker.ctrl_code+', '+beaker.ctrl_sys+', '+', '.join(array(keys).tolist())",
+ " lab=beaker.ctrl_quant+', '+beaker.ctrl_code+', '+', '.join(array(keys).tolist())",
" # Error:",
" if beaker.ctrl_quant=='E_tot'or beaker.ctrl_quant=='E_coh':",
- " lab='E_tot, '+beaker.ctrl_code+', '+beaker.ctrl_sys+', '+', '.join(array(keys).tolist())",
+ " lab='E_tot, '+beaker.ctrl_code+', '+', '.join(array(keys).tolist())",
" if beaker.ctrl_code=='FHI-aims':",
" ref_data=data_ref[beaker.ctrl_code,beaker.ctrl_sys+name_base[beaker.ctrl_code],ref_keys[0],ref_keys[1]]",
" else:",
@@ -698,7 +713,7 @@
" # el. solids or binaries",
" mono_or_bin=ref_dict_binaries[beaker.ctrl_sys]",
" # The plot label generated from the settings of the drop down menus",
- " lab=beaker.ctrl_quant+', '+beaker.ctrl_code+', '+beaker.ctrl_sys+', '+', '.join(array(keys).tolist())",
+ " lab=beaker.ctrl_quant+', '+beaker.ctrl_code+', '+', '.join(array(keys).tolist())",
" # Error:",
" if beaker.ctrl_quant=='E_tot':",
" if beaker.ctrl_code=='FHI-aims':",
@@ -769,13 +784,15 @@
"for i in arange(len(xylist)):",
" ax.semilogy(xylist[i][0][0],xylist[i][0][1],'o',label=xylist[i][1])",
"for i in arange(len(xylist_bins)):",
- " ax2.semilogy(xylist_bins[i][0][0],xylist_bins[i][0][1],'o',label=xylist_bins[i][1]) ",
+ " ax2.semilogy(xylist_bins[i][0][0],xylist_bins[i][0][1],'s',label=xylist_bins[i][1]) ",
"",
"# Diagonal line for right plot",
"ax2.set_ylim(ax.get_ylim()[0],ax.get_ylim()[1])",
"# Legend",
- "ax.legend(numpoints=1,loc=4)",
- "ax2.legend(numpoints=1,loc=4)",
+ "ax.legend(bbox_to_anchor=(-0.1, -0.3, 1.3, .0), loc=3,",
+ " ncol=1, mode=\"expand\", borderaxespad=0.,numpoints=1)",
+ "ax2.legend(bbox_to_anchor=(0.1, -0.3, 1.3, .0), loc=3,",
+ " ncol=1, mode=\"expand\", borderaxespad=0.,numpoints=1)",
"# Figure title",
"ax.set_title('El. solids')",
"ax2.set_title('Binaries')",
@@ -791,12 +808,12 @@
"result": "<div class=\"output_subarea output_png\"><img 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ArF+MAVfWn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\n5Dh65Dh65Dh6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"selectedType": "Html",
"pluginName": "IPython",
- "shellId": "27A64174BE534D8A81CD4007A8828BAE",
- "elapsedTime": 1305,
- "height": 706
+ "shellId": "4CE22EA14B7A45608ED58BBCC25D6400",
+ "elapsedTime": 1059,
+ "height": 0
},
"evaluatorReader": true,
- "lineCount": 131
+ "lineCount": 133
},
{
"id": "ptablecell",
@@ -805,7 +822,7 @@
"input": {
"body": [
"# init figure",
- "fig=figure(1,(16,16))",
+ "fig=figure(1,(14.5,14.5))",
"ax=fig.add_subplot(111,aspect=7./18.)",
"",
"# Set data (atomic numbers and error)",
@@ -871,11 +888,11 @@
},
"output": {
"state": {},
- "result": "<div class=\"output_subarea output_png\"><img 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gRERERERER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T8tCFurwN13vMHsV7hSxfdvSzNm8s9+kHoFe6PJgxWhKJGTYbTvY9nOFIBCFQEl1ut/4sg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\nQmCC\n\"></div>",
+ "result": "<div class=\"output_subarea output_png\"><img 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7FXwC7obor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NX6JvZ0O3zGMwcG3Jm1SQOft2ds39Oo1SZg4VrUB3fLngSWpWVlXI7/KPR0tKqBJj+pebc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\n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+ "title": "Estimate Error for Binary Systems",
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- "<div style=\"font-size: 150%; font-weight: bold;\">Estimate error for binary systems</div>"
+ "<p>The next cells allow to inspect models to predict the deviations occuring in total and relative energy as function of the numerical settings.<br>",
+ "Click on <i>Explanation</i> for further details and instructions."
],
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- " .val_instructions{",
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" } ",
"</style>",
"<!-- Button trigger modal -->",
- "<button type=\"button\" class=\"btn btn-default\" data-toggle=\"modal\" data-target=\"#val-motivation-modal\">",
+ "<button type=\"button\" class=\"btn btn-default\" data-toggle=\"modal\" data-target=\"#estimate-bins-modal\">",
" Explanation",
"</button>",
"",
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- "<div class=\"modal fade\" id=\"val-motivation-modal\" tabindex=\"-1\" role=\"dialog\" aria-labelledby=\"phasediagram-motivation-modal-label\">",
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- " <h4 class=\"modal-title\" id=\"val-motivation-modal-label\">Instructions</h4>",
+ " <h4 class=\"modal-title\" id=\"estimate-bins-label\">Explanation</h4>",
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- " <br><br>",
- "Enter the formula of a specific system and calculate the error for a set of numerical settings from the results of the elementary solids with respect to a well converged reference,. The numerical settings and the electronic structure code can be selected in the input mask below.<br>",
- " The settings for the reference calculations are:<br>",
+ "In the left plot the data for the 82 binary system is visualized in the same way as above. In the right plot the error for the binary systems is estimated from the error of the elementary systems by the formula presented above. It is plotted against the error obtained directly from the DFT calculations of the binary systems. <br><br>",
+ "The settings for the reference calculations are:<br>",
" -VASP: 8 k-points\\cdot\\AA{}, Accurate<br>",
" -exciting: 8 k-points\\cdot\\AA{}<br>",
" -GPAW: 8 k-points\\cdot\\AA{}, 1600eV (PW cutoff)<br>",
" -FHI-aims: 8 k-points\\cdot\\AA{}, really tight, tier2<br>",
- " <br><br>",
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"innertype": "Html",
- "object": "<script>\nvar beaker = bkHelper.getBeakerObject().beakerObj;\n</script>\n<style type=\"text/css\">\n .val_instructions{\n font-size: 15px;\n } \n</style>\n<!-- Button trigger modal -->\n<button type=\"button\" class=\"btn btn-default\" data-toggle=\"modal\" data-target=\"#val-motivation-modal\">\n Explanation\n</button>\n\n<!-- Modal -->\n<div class=\"modal fade\" id=\"val-motivation-modal\" tabindex=\"-1\" role=\"dialog\" aria-labelledby=\"phasediagram-motivation-modal-label\">\n <div class=\"modal-dialog modal-lg\" role=\"document\">\n <div class=\"modal-content\">\n <div class=\"modal-header\">\n <button type=\"button\" class=\"close\" data-dismiss=\"modal\" aria-label=\"Close\"><span aria-hidden=\"true\">×</span></button>\n <h4 class=\"modal-title\" id=\"val-motivation-modal-label\">Instructions</h4>\n <div style=\"max-width: 800px;\">\n <br><br>\nEnter the formula of a specific system and calculate the error for a set of numerical settings from the results of the elementary solids with respect to a well converged reference,. The numerical settings and the electronic structure code can be selected in the input mask below.<br>\n The settings for the reference calculations are:<br>\n -VASP: 8 k-points\\cdot\\AA{}, Accurate<br>\n -exciting: 8 k-points\\cdot\\AA{}<br>\n -GPAW: 8 k-points\\cdot\\AA{}, 1600eV (PW cutoff)<br>\n -FHI-aims: 8 k-points\\cdot\\AA{}, really tight, tier2<br>\n <br><br>\n</div> \n </div>\n <div class=\"modal-body val_instructions\">\n\n </div>\n <div class=\"modal-footer\">\n <button type=\"button\" class=\"btn btn-default\" data-dismiss=\"modal\">Close</button>\n<!-- <button type=\"button\" class=\"btn btn-primary\">Save changes</button> -->\n </div>\n </div>\n </div>\n\n<div style=\"height: 3em;\"></div></div>"
+ "object": "<script>\nvar beaker = bkHelper.getBeakerObject().beakerObj;\n</script>\n<style type=\"text/css\">\n .phasediagram_instructions{\n font-size: 15px;\n } \n</style>\n<!-- Button trigger modal -->\n<button type=\"button\" class=\"btn btn-default\" data-toggle=\"modal\" data-target=\"#estimate-bins-modal\">\n Explanation\n</button>\n\n<!-- Modal -->\n<div class=\"modal fade\" id=\"estimate-bins-modal\" tabindex=\"-1\" role=\"dialog\" aria-labelledby=\"estimate-bins-label\">\n <div class=\"modal-dialog modal-lg\" role=\"document\">\n <div class=\"modal-content\">\n <div class=\"modal-header\">\n <button type=\"button\" class=\"close\" data-dismiss=\"modal\" aria-label=\"Close\"><span aria-hidden=\"true\">×</span></button>\n <h4 class=\"modal-title\" id=\"estimate-bins-label\">Explanation</h4>\n <div style=\"max-width: 800px;\">\nIn the left plot the data for the 82 binary system is visualized in the same way as above. In the right plot the error for the binary systems is estimated from the error of the elementary systems by the formula presented above. It is plotted against the error obtained directly from the DFT calculations of the binary systems. <br><br>\nThe settings for the reference calculations are:<br>\n -VASP: 8 k-points\\cdot\\AA{}, Accurate<br>\n -exciting: 8 k-points\\cdot\\AA{}<br>\n -GPAW: 8 k-points\\cdot\\AA{}, 1600eV (PW cutoff)<br>\n -FHI-aims: 8 k-points\\cdot\\AA{}, really tight, tier2<br>\n</div> \n </div>\n <div class=\"modal-body phasediagram_instructions\">\n\n </div>\n <div class=\"modal-footer\">\n <button type=\"button\" class=\"btn btn-default\" data-dismiss=\"modal\">Close</button>\n<!-- <button type=\"button\" class=\"btn btn-primary\">Save changes</button> -->\n </div>\n </div>\n </div>\n\n<div style=\"height: 3em;\"></div></div>"
},
"selectedType": "BeakerDisplay",
"elapsedTime": 0,
- "height": 72
+ "height": 0
},
"evaluatorReader": true,
- "lineCount": 39,
- "initialization": true
+ "lineCount": 37
},
{
"id": "code2MruHL",
@@ -1104,20 +1127,20 @@
"",
" addDropdownChoice(pprec, \"light\", \"light\");",
" addDropdownChoice(pprec, \"tight\", \"tight\");",
- " addDropdownChoice(pprec, \"really_tight\", \"really_tight\");",
- " addDropdownChoice(prel, \"atomic_zora\", \"atomic_zora\");",
+ " addDropdownChoice(pprec, \"really_tight\", \"really tight\");",
+ " addDropdownChoice(prel, \"atomic_zora\", \"atomic zora\");",
" addDropdownChoice(prel, \"zora\", \"zora\");",
" addDropdownChoice(ptiers, \"minimal\", \"minimal\");",
" addDropdownChoice(ptiers, \"standard\", \"standard\");",
" addDropdownChoice(ptiers, \"tier1\", \"tier1\");",
" addDropdownChoice(ptiers, \"tier2\", \"tier2\");",
- " addDropdownChoice(pxc, \"pbe\", \"pbe\");",
- " addDropdownChoice(pxc, \"pw-lda\", \"pbw-lda\");",
+ " addDropdownChoice(pxc, \"pbe\", \"PBE\");",
+ " addDropdownChoice(pxc, \"pw-lda\", \"LDA\");",
" break;",
"",
" ",
" case \"GPAW\": ",
- " dprec.innerHTML = '$E_{cut}$:';",
+ " dprec.innerHTML = 'PW cutoff:';",
"",
" addDropdownChoice(pprec, \"300\", \"300\");",
" addDropdownChoice(pprec, \"400\", \"400\");",
@@ -1133,8 +1156,8 @@
" addDropdownChoice(pprec, \"1400\", \"1100\");",
" addDropdownChoice(pprec, \"1500\", \"1100\");",
"",
- " addDropdownChoice(pxc, \"pbe\", \"pbe\");",
- " addDropdownChoice(pxc, \"pw-lda\", \"pbw-lda\");",
+ " addDropdownChoice(pxc, \"pbe\", \"PBE\");",
+ " addDropdownChoice(pxc, \"pw-lda\", \"LDA\");",
" break;",
"",
"",
@@ -1161,17 +1184,27 @@
" <th>XC-Functional:</th>",
" <td>",
" <select id=\"errorbar_estimate_xcfunctional\">",
- " <option value=\"PBE\" selected>PBE</option>",
- " <option value=\"LDA\">LDA</option>",
+ " <option value=\"pbe\" selected>PBE</option>",
+ " <option value=\"pw-lda\">LDA</option>",
" </select>",
" </td>",
" <td id=\"errorbar_estimate_xcfunctional_description\" style=\"white-space: pre;\"></td>",
- " <th id=\"errorbar_estimate_precision_name\">Precision:</th>",
+ " <th id=\"errorbar_estimate_precision_name\">PW cutoff:</th>",
" <td>",
" <select id=\"errorbar_estimate_precision\" >",
- " <option value=\"Low\" selected>Low</option>",
- " <option value=\"Normal\">Normal</option> ",
- " <option value=\"Accurate\">Acurate</option> ",
+ " <option value=\"300\">300</option>",
+ " <option value=\"400\">400</option>",
+ " <option value=\"500\">500</option>",
+ " <option value=\"600\" selected>600</option>",
+ " <option value=\"700\">700</option>",
+ " <option value=\"800\">800</option>",
+ " <option value=\"900\">900</option>",
+ " <option value=\"1000\">1000</option>",
+ " <option value=\"1100\">1100</option>",
+ " <option value=\"1200\">1200</option>",
+ " <option value=\"1300\">1300</option>",
+ " <option value=\"1400\">1400</option>",
+ " <option value=\"1500\">1500</option> ",
" </select>",
" </td>",
" <td id=\"errorbar_estimate_precision_description\" style=\"white-space: pre;\"></td>",
@@ -1180,7 +1213,7 @@
" <th>Tiers:</th>",
" <td><select id=\"errorbar_estimate_tiers\" ><!-- content inserted programmatically --></select></td>",
" <td id=\"errorbar_estimate_tiers_description\" style=\"white-space: pre;\"></td>",
- " <th>relativity treatment:</th>",
+ " <th>Relativity treatment:</th>",
" <td><select id=\"errorbar_estimate_relativity\" ><!-- content inserted programmatically --></select></td>",
" <td id=\"errorbar_estimate_relativity_description\" style=\"white-space: pre;\"></td>",
"",
@@ -1191,15 +1224,16 @@
" <td><select id=\"errorbar_estimate_quantity\">",
" <option value=\"E_tot\">Total Energy</option>",
" <option value=\"relR\">relative Energy</option>",
+ " <option value=\"E_coh\">Cohesive Energy</option>",
" </select></td>",
" <td id=\"errorbar_estimate_quantity_description\" style=\"white-space: pre;\"></td> ",
" ",
"",
" <th>Code:</th>",
" <td><select id=\"errorbar_estimate_code\" onchange=\"error_estimateUpdateForm()\">",
+ " <option value=\"GPAW\">GPAW</option> ",
+ " <option value=\"FHI-aims\">FHI-aims</option> ",
" <option value=\"VASP\">VASP</option>",
- " <option value=\"FHI-aims\">FHI-aims</option>",
- " <option value=\"GPAW\">GPAW</option> ",
" </select></td>",
" <td id=\"errorbar_estimate_code_description\" style=\"white-space: pre;\"></td>",
" </tr>",
@@ -1215,6 +1249,7 @@
" </tr>",
" </table> ",
"</div>",
+ "",
""
],
"hidden": true
@@ -1224,14 +1259,14 @@
"result": {
"type": "BeakerDisplay",
"innertype": "Html",
- "object": "<script>\nvar beaker = bkHelper.getBeakerObject().beakerObj;\n</script>\n<script>\n \n function add_estimate_plot() { \n beaker.ctrl_xc_estimate = document.getElementById(\"errorbar_estimate_xcfunctional\").value;\n beaker.ctrl_kpt_estimate = 8;\n beaker.ctrl_prec_estimate = document.getElementById(\"errorbar_estimate_precision\").value;\n beaker.ctrl_tiers_estimate = document.getElementById(\"errorbar_estimate_tiers\").value;\n beaker.ctrl_rel_estimate = document.getElementById(\"errorbar_estimate_relativity\").value;\n beaker.ctrl_pred_estimate = 1;\n beaker.ctrl_quant_estimate = document.getElementById(\"errorbar_estimate_quantity\").value;\n beaker.ctrl_code_estimate = document.getElementById(\"errorbar_estimate_code\").value;\n beaker.ctrl_button_estimate = 1\n beaker.evaluate(\"exe_cell_estimate\");\n }\n function clear_estimate_last() {\n beaker.ctrl_button_estimate = 2\n beaker.evaluate(\"exe_cell_estimate\");\n }\n function clear_estimate_plot() {\n beaker.ctrl_button_estimate = 3\n beaker.evaluate(\"exe_cell_estimate\");\n }\n function error_estimateUpdateForm() {\n var code = document.getElementById(\"errorbar_estimate_code\").value;\n \n var dprec = document.getElementById(\"errorbar_estimate_precision_name\");\n var pprec = document.getElementById(\"errorbar_estimate_precision\"); pprec.innerHTML = '';\n var prel = document.getElementById(\"errorbar_estimate_relativity\"); prel.innerHTML = '';\n var ptiers = document.getElementById(\"errorbar_estimate_tiers\"); ptiers.innerHTML = '';\n var pxc = document.getElementById(\"errorbar_estimate_xcfunctional\"); pxc.innerHTML = '';\n\n switch(code) {\n case \"VASP\": \n dprec.innerHTML = 'Precision:';\n\n addDropdownChoice(pprec, \"Low\", \"Low\");\n addDropdownChoice(pprec, \"Normal\", \"Normal\");\n addDropdownChoice(pprec, \"Accurate\", \"Accurate\");\n addDropdownChoice(pxc, \"PBE\", \"PBE\");\n addDropdownChoice(pxc, \"LDA\", \"LDA\");\n break;\n \n case \"FHI-aims\": \n dprec.innerHTML = 'Integration grid:';\n\n addDropdownChoice(pprec, \"light\", \"light\");\n addDropdownChoice(pprec, \"tight\", \"tight\");\n addDropdownChoice(pprec, \"really_tight\", \"really_tight\");\n addDropdownChoice(prel, \"atomic_zora\", \"atomic_zora\");\n addDropdownChoice(prel, \"zora\", \"zora\");\n addDropdownChoice(ptiers, \"minimal\", \"minimal\");\n addDropdownChoice(ptiers, \"standard\", \"standard\");\n addDropdownChoice(ptiers, \"tier1\", \"tier1\");\n addDropdownChoice(ptiers, \"tier2\", \"tier2\");\n addDropdownChoice(pxc, \"pbe\", \"pbe\");\n addDropdownChoice(pxc, \"pw-lda\", \"pbw-lda\");\n break;\n\n \n case \"GPAW\": \n dprec.innerHTML = '$E_{cut}$:';\n\n addDropdownChoice(pprec, \"300\", \"300\");\n addDropdownChoice(pprec, \"400\", \"400\");\n addDropdownChoice(pprec, \"500\", \"500\");\n addDropdownChoice(pprec, \"600\", \"600\");\n addDropdownChoice(pprec, \"700\", \"700\");\n addDropdownChoice(pprec, \"800\", \"800\");\n addDropdownChoice(pprec, \"900\", \"900\");\n addDropdownChoice(pprec, \"1000\", \"1000\");\n addDropdownChoice(pprec, \"1100\", \"1100\");\n addDropdownChoice(pprec, \"1200\", \"1100\");\n addDropdownChoice(pprec, \"1300\", \"1100\");\n addDropdownChoice(pprec, \"1400\", \"1100\");\n addDropdownChoice(pprec, \"1500\", \"1100\");\n\n addDropdownChoice(pxc, \"pbe\", \"pbe\");\n addDropdownChoice(pxc, \"pw-lda\", \"pbw-lda\");\n break;\n\n\n }\n }\n\n\n\n</script>\n\n<style type=\"text/css\">\n \n .error_estimate_table th { font-weight: bold; padding-right: 2ex; }\n .error_estimate_table td input { margin-right: 1ex; }\n \n</style>\n\n<!-- Controls area -->\n\n<div class=\"error_estimate_control\">\n <table class=\"error_estimate_table\">\n \n <tbody><tr>\n <th>XC-Functional:</th>\n <td>\n <select id=\"errorbar_estimate_xcfunctional\"><option value=\"PBE\">PBE</option><option value=\"LDA\">LDA</option></select>\n </td>\n <td id=\"errorbar_estimate_xcfunctional_description\" style=\"white-space: pre;\"></td>\n <th id=\"errorbar_estimate_precision_name\">Precision:</th>\n <td>\n <select id=\"errorbar_estimate_precision\"><option value=\"Low\">Low</option><option value=\"Normal\">Normal</option><option value=\"Accurate\">Accurate</option></select>\n </td>\n <td id=\"errorbar_estimate_precision_description\" style=\"white-space: pre;\"></td>\n </tr>\n <tr>\n <th>Tiers:</th>\n <td><select id=\"errorbar_estimate_tiers\"></select></td>\n <td id=\"errorbar_estimate_tiers_description\" style=\"white-space: pre;\"></td>\n <th>relativity treatment:</th>\n <td><select id=\"errorbar_estimate_relativity\"></select></td>\n <td id=\"errorbar_estimate_relativity_description\" style=\"white-space: pre;\"></td>\n\n </tr> \n \n <tr>\n <th>Quantity:</th>\n <td><select id=\"errorbar_estimate_quantity\">\n <option value=\"E_tot\">Total Energy</option>\n <option value=\"relR\">relative Energy</option>\n </select></td>\n <td id=\"errorbar_estimate_quantity_description\" style=\"white-space: pre;\"></td> \n \n\n <th>Code:</th>\n <td><select id=\"errorbar_estimate_code\" onchange=\"error_estimateUpdateForm()\">\n <option value=\"VASP\">VASP</option>\n <option value=\"FHI-aims\">FHI-aims</option>\n <option value=\"GPAW\">GPAW</option> \n </select></td>\n <td id=\"errorbar_estimate_code_description\" style=\"white-space: pre;\"></td>\n </tr>\n \n </tbody></table>\n <table class=\"error_estimate_table\">\n \n <tbody><tr>\n <th><button type=\"button\" class=\"btn btn-primary\" style=\"margin-top: 2ex;\" onclick=\"add_estimate_plot();\">Compare Reference/Estimated Error in binaries</button></th>\n <th><button type=\"button\" class=\"btn clear-primary\" style=\"margin-top: 2ex;\" onclick=\"clear_estimate_plot();\">Clear plot</button></th>\n <th><button type=\"button\" class=\"btn clearlast-primary\" style=\"margin-top: 2ex;\" onclick=\"clear_estimate_last();\">Clear last set</button></th>\n\n </tr>\n </tbody></table> \n</div>\n"
+ "object": "<script>\nvar beaker = bkHelper.getBeakerObject().beakerObj;\n</script>\n<script>\n \n function add_estimate_plot() { \n beaker.ctrl_xc_estimate = document.getElementById(\"errorbar_estimate_xcfunctional\").value;\n beaker.ctrl_kpt_estimate = 8;\n beaker.ctrl_prec_estimate = document.getElementById(\"errorbar_estimate_precision\").value;\n beaker.ctrl_tiers_estimate = document.getElementById(\"errorbar_estimate_tiers\").value;\n beaker.ctrl_rel_estimate = document.getElementById(\"errorbar_estimate_relativity\").value;\n beaker.ctrl_pred_estimate = 1;\n beaker.ctrl_quant_estimate = document.getElementById(\"errorbar_estimate_quantity\").value;\n beaker.ctrl_code_estimate = document.getElementById(\"errorbar_estimate_code\").value;\n beaker.ctrl_button_estimate = 1\n beaker.evaluate(\"exe_cell_estimate\");\n }\n function clear_estimate_last() {\n beaker.ctrl_button_estimate = 2\n beaker.evaluate(\"exe_cell_estimate\");\n }\n function clear_estimate_plot() {\n beaker.ctrl_button_estimate = 3\n beaker.evaluate(\"exe_cell_estimate\");\n }\n function error_estimateUpdateForm() {\n var code = document.getElementById(\"errorbar_estimate_code\").value;\n \n var dprec = document.getElementById(\"errorbar_estimate_precision_name\");\n var pprec = document.getElementById(\"errorbar_estimate_precision\"); pprec.innerHTML = '';\n var prel = document.getElementById(\"errorbar_estimate_relativity\"); prel.innerHTML = '';\n var ptiers = document.getElementById(\"errorbar_estimate_tiers\"); ptiers.innerHTML = '';\n var pxc = document.getElementById(\"errorbar_estimate_xcfunctional\"); pxc.innerHTML = '';\n\n switch(code) {\n case \"VASP\": \n dprec.innerHTML = 'Precision:';\n\n addDropdownChoice(pprec, \"Low\", \"Low\");\n addDropdownChoice(pprec, \"Normal\", \"Normal\");\n addDropdownChoice(pprec, \"Accurate\", \"Accurate\");\n addDropdownChoice(pxc, \"PBE\", \"PBE\");\n addDropdownChoice(pxc, \"LDA\", \"LDA\");\n break;\n \n case \"FHI-aims\": \n dprec.innerHTML = 'Integration grid:';\n\n addDropdownChoice(pprec, \"light\", \"light\");\n addDropdownChoice(pprec, \"tight\", \"tight\");\n addDropdownChoice(pprec, \"really_tight\", \"really tight\");\n addDropdownChoice(prel, \"atomic_zora\", \"atomic zora\");\n addDropdownChoice(prel, \"zora\", \"zora\");\n addDropdownChoice(ptiers, \"minimal\", \"minimal\");\n addDropdownChoice(ptiers, \"standard\", \"standard\");\n addDropdownChoice(ptiers, \"tier1\", \"tier1\");\n addDropdownChoice(ptiers, \"tier2\", \"tier2\");\n addDropdownChoice(pxc, \"pbe\", \"PBE\");\n addDropdownChoice(pxc, \"pw-lda\", \"LDA\");\n break;\n\n \n case \"GPAW\": \n dprec.innerHTML = 'PW cutoff:';\n\n addDropdownChoice(pprec, \"300\", \"300\");\n addDropdownChoice(pprec, \"400\", \"400\");\n addDropdownChoice(pprec, \"500\", \"500\");\n addDropdownChoice(pprec, \"600\", \"600\");\n addDropdownChoice(pprec, \"700\", \"700\");\n addDropdownChoice(pprec, \"800\", \"800\");\n addDropdownChoice(pprec, \"900\", \"900\");\n addDropdownChoice(pprec, \"1000\", \"1000\");\n addDropdownChoice(pprec, \"1100\", \"1100\");\n addDropdownChoice(pprec, \"1200\", \"1100\");\n addDropdownChoice(pprec, \"1300\", \"1100\");\n addDropdownChoice(pprec, \"1400\", \"1100\");\n addDropdownChoice(pprec, \"1500\", \"1100\");\n\n addDropdownChoice(pxc, \"pbe\", \"PBE\");\n addDropdownChoice(pxc, \"pw-lda\", \"LDA\");\n break;\n\n\n }\n }\n\n\n\n</script>\n\n<style type=\"text/css\">\n \n .error_estimate_table th { font-weight: bold; padding-right: 2ex; }\n .error_estimate_table td input { margin-right: 1ex; }\n \n</style>\n\n<!-- Controls area -->\n\n<div class=\"error_estimate_control\">\n <table class=\"error_estimate_table\">\n \n <tbody><tr>\n <th>XC-Functional:</th>\n <td>\n <select id=\"errorbar_estimate_xcfunctional\">\n <option value=\"pbe\" selected=\"\">PBE</option>\n <option value=\"pw-lda\">LDA</option>\n </select>\n </td>\n <td id=\"errorbar_estimate_xcfunctional_description\" style=\"white-space: pre;\"></td>\n <th id=\"errorbar_estimate_precision_name\">PW cutoff:</th>\n <td>\n <select id=\"errorbar_estimate_precision\">\n <option value=\"300\">300</option>\n <option value=\"400\">400</option>\n <option value=\"500\">500</option>\n <option value=\"600\" selected=\"\">600</option>\n <option value=\"700\">700</option>\n <option value=\"800\">800</option>\n <option value=\"900\">900</option>\n <option value=\"1000\">1000</option>\n <option value=\"1100\">1100</option>\n <option value=\"1200\">1200</option>\n <option value=\"1300\">1300</option>\n <option value=\"1400\">1400</option>\n <option value=\"1500\">1500</option> \n </select>\n </td>\n <td id=\"errorbar_estimate_precision_description\" style=\"white-space: pre;\"></td>\n </tr>\n <tr>\n <th>Tiers:</th>\n <td><select id=\"errorbar_estimate_tiers\"><!-- content inserted programmatically --></select></td>\n <td id=\"errorbar_estimate_tiers_description\" style=\"white-space: pre;\"></td>\n <th>Relativity treatment:</th>\n <td><select id=\"errorbar_estimate_relativity\"><!-- content inserted programmatically --></select></td>\n <td id=\"errorbar_estimate_relativity_description\" style=\"white-space: pre;\"></td>\n\n </tr> \n \n <tr>\n <th>Quantity:</th>\n <td><select id=\"errorbar_estimate_quantity\">\n <option value=\"E_tot\">Total Energy</option>\n <option value=\"relR\">relative Energy</option>\n <option value=\"E_coh\">Cohesive Energy</option>\n </select></td>\n <td id=\"errorbar_estimate_quantity_description\" style=\"white-space: pre;\"></td> \n \n\n <th>Code:</th>\n <td><select id=\"errorbar_estimate_code\" onchange=\"error_estimateUpdateForm()\">\n <option value=\"GPAW\">GPAW</option> \n <option value=\"FHI-aims\">FHI-aims</option> \n <option value=\"VASP\">VASP</option>\n </select></td>\n <td id=\"errorbar_estimate_code_description\" style=\"white-space: pre;\"></td>\n </tr>\n \n </tbody></table>\n <table class=\"error_estimate_table\">\n \n <tbody><tr>\n <th><button type=\"button\" class=\"btn btn-primary\" style=\"margin-top: 2ex;\" onclick=\"add_estimate_plot();\">Compare Reference/Estimated Error in binaries</button></th>\n <th><button type=\"button\" class=\"btn clear-primary\" style=\"margin-top: 2ex;\" onclick=\"clear_estimate_plot();\">Clear plot</button></th>\n <th><button type=\"button\" class=\"btn clearlast-primary\" style=\"margin-top: 2ex;\" onclick=\"clear_estimate_last();\">Clear last set</button></th>\n\n </tr>\n </tbody></table> \n</div>\n\n"
},
"selectedType": "BeakerDisplay",
"elapsedTime": 0,
- "height": 179
+ "height": 0
},
"evaluatorReader": true,
- "lineCount": 159,
+ "lineCount": 171,
"initialization": true
},
{
@@ -1250,7 +1285,7 @@
" # el. solids or binaries",
" mono_or_bin=ref_dict_binaries[beaker.ctrl_sys_estimate]",
" # The plot label generated from the settings of the drop down menus",
- " lab=beaker.ctrl_quant_estimate+', '+beaker.ctrl_code_estimate+', '+beaker.ctrl_sys_estimate+', '+', '.join(array(keys).tolist())",
+ " lab=beaker.ctrl_quant_estimate+', '+beaker.ctrl_code_estimate+', '+', '.join(array(keys).tolist())",
" # Error:",
" if beaker.ctrl_quant_estimate=='E_tot':",
" if beaker.ctrl_code_estimate=='FHI-aims':",
@@ -1366,10 +1401,11 @@
"",
"# Diagonal line for right plot",
"ax2.set_ylim(ax.get_ylim()[0],ax.get_ylim()[1])",
- "ax2.plot(ax2.get_xlim(),ax2.get_ylim(),'-k')",
+ "ax2.plot(ax2.get_xlim(),ax2.get_xlim(),'-k')",
"# Legend",
- "ax.legend(numpoints=1,loc=4)",
- "ax2.legend(numpoints=1,loc=4)",
+ "ax.legend(bbox_to_anchor=(-0.1, -0.3, 1.4, .0), loc=3,",
+ " ncol=1, mode=\"expand\", borderaxespad=0.,numpoints=1)",
+ "#ax2.legend(numpoints=1,loc=4)",
"# Figure title",
"fig.suptitle('Observed/estimated error for binary systems')",
"# Show",
@@ -1382,21 +1418,93 @@
"result": "<div class=\"output_subarea output_png\"><img 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NjI/X19URE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\n1iuAa4CfAgf0Zl5JkvqKNVKSVA5y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+ "id": "section5nlma7",
+ "type": "section",
+ "title": "Estimate Error for Arbitrary Systems",
+ "level": 1,
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{
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"body": [
- "<div style=\"font-size: 150%; font-weight: bold;\">Estimate error for arbitrary system</div>"
+ "<p>The next cells allow to estimate the deviations occurring in total and relative energy as function of the numerical settings for arbitrary systems using the formalism discussed above.<br></p>",
+ "Click on <i>Explanation</i> for further details and instructions."
],
"evaluatorReader": false
},
+ {
+ "id": "codeJSPqh4",
+ "type": "code",
+ "evaluator": "HTML",
+ "input": {
+ "body": [
+ "<style type=\"text/css\">",
+ " .val_instructions{",
+ " font-size: 15px;",
+ " } ",
+ "</style>",
+ "<!-- Button trigger modal -->",
+ "<button type=\"button\" class=\"btn btn-default\" data-toggle=\"modal\" data-target=\"#val-motivation-modal\">",
+ " Explanation",
+ "</button>",
+ "",
+ "<!-- Modal -->",
+ "<div class=\"modal fade\" id=\"val-motivation-modal\" tabindex=\"-1\" role=\"dialog\" aria-labelledby=\"phasediagram-motivation-modal-label\">",
+ " <div class=\"modal-dialog modal-lg\" role=\"document\">",
+ " <div class=\"modal-content\">",
+ " <div class=\"modal-header\">",
+ " <button type=\"button\" class=\"close\" data-dismiss=\"modal\" aria-label=\"Close\"><span aria-hidden=\"true\">×</span></button>",
+ " <h4 class=\"modal-title\" id=\"val-motivation-modal-label\">Instructions</h4>",
+ " <div style=\"max-width: 800px;\">",
+ " <br><br>",
+ "Enter the formula of a specific system and calculate the error for a set of numerical settings from the results of the elementary solids with respect to a well converged reference,. The numerical settings and the electronic structure code can be selected in the input mask below.<br>",
+ " The settings for the reference calculations are:<br>",
+ " -VASP: 8 k-points\\cdot\\AA{}, Accurate<br>",
+ " -exciting: 8 k-points\\cdot\\AA{}<br>",
+ " -GPAW: 8 k-points\\cdot\\AA{}, 1600eV (PW cutoff)<br>",
+ " -FHI-aims: 8 k-points\\cdot\\AA{}, really tight, tier2<br>",
+ " <br><br>",
+ "</div> ",
+ " </div>",
+ " <div class=\"modal-body val_instructions\">",
+ "",
+ " </div>",
+ " <div class=\"modal-footer\">",
+ " <button type=\"button\" class=\"btn btn-default\" data-dismiss=\"modal\">Close</button>",
+ "<!-- <button type=\"button\" class=\"btn btn-primary\">Save changes</button> -->",
+ " </div>",
+ " </div>",
+ " </div>",
+ "",
+ "<div style=\"height: 3em;\"></div>"
+ ],
+ "hidden": true
+ },
+ "output": {
+ "state": {},
+ "result": {
+ "type": "BeakerDisplay",
+ "innertype": "Html",
+ "object": "<script>\nvar beaker = bkHelper.getBeakerObject().beakerObj;\n</script>\n<style type=\"text/css\">\n .val_instructions{\n font-size: 15px;\n } \n</style>\n<!-- Button trigger modal -->\n<button type=\"button\" class=\"btn btn-default\" data-toggle=\"modal\" data-target=\"#val-motivation-modal\">\n Explanation\n</button>\n\n<!-- Modal -->\n<div class=\"modal fade\" id=\"val-motivation-modal\" tabindex=\"-1\" role=\"dialog\" aria-labelledby=\"phasediagram-motivation-modal-label\">\n <div class=\"modal-dialog modal-lg\" role=\"document\">\n <div class=\"modal-content\">\n <div class=\"modal-header\">\n <button type=\"button\" class=\"close\" data-dismiss=\"modal\" aria-label=\"Close\"><span aria-hidden=\"true\">×</span></button>\n <h4 class=\"modal-title\" id=\"val-motivation-modal-label\">Instructions</h4>\n <div style=\"max-width: 800px;\">\n <br><br>\nEnter the formula of a specific system and calculate the error for a set of numerical settings from the results of the elementary solids with respect to a well converged reference,. The numerical settings and the electronic structure code can be selected in the input mask below.<br>\n The settings for the reference calculations are:<br>\n -VASP: 8 k-points\\cdot\\AA{}, Accurate<br>\n -exciting: 8 k-points\\cdot\\AA{}<br>\n -GPAW: 8 k-points\\cdot\\AA{}, 1600eV (PW cutoff)<br>\n -FHI-aims: 8 k-points\\cdot\\AA{}, really tight, tier2<br>\n <br><br>\n</div> \n </div>\n <div class=\"modal-body val_instructions\">\n\n </div>\n <div class=\"modal-footer\">\n <button type=\"button\" class=\"btn btn-default\" data-dismiss=\"modal\">Close</button>\n<!-- <button type=\"button\" class=\"btn btn-primary\">Save changes</button> -->\n </div>\n </div>\n </div>\n\n<div style=\"height: 3em;\"></div></div>"
+ },
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+ "elapsedTime": 0,
+ "height": 0
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{
"id": "code1sT7ei",
"type": "code",
@@ -1443,20 +1551,20 @@
"",
" addDropdownChoice(pprec, \"light\", \"light\");",
" addDropdownChoice(pprec, \"tight\", \"tight\");",
- " addDropdownChoice(pprec, \"really_tight\", \"really_tight\");",
- " addDropdownChoice(prel, \"atomic_zora\", \"atomic_zora\");",
+ " addDropdownChoice(pprec, \"really_tight\", \"really tight\");",
+ " addDropdownChoice(prel, \"atomic_zora\", \"atomic zora\");",
" addDropdownChoice(prel, \"zora\", \"zora\");",
" addDropdownChoice(ptiers, \"minimal\", \"minimal\");",
" addDropdownChoice(ptiers, \"standard\", \"standard\");",
" addDropdownChoice(ptiers, \"tier1\", \"tier1\");",
" addDropdownChoice(ptiers, \"tier2\", \"tier2\");",
- " addDropdownChoice(pxc, \"pbe\", \"pbe\");",
- " addDropdownChoice(pxc, \"pw-lda\", \"pbw-lda\");",
+ " addDropdownChoice(pxc, \"pbe\", \"PBE\");",
+ " addDropdownChoice(pxc, \"pw-lda\", \"LDA\");",
" break;",
"",
" ",
" case \"GPAW\": ",
- " dprec.innerHTML = '$E_{cut}$:';",
+ " dprec.innerHTML = 'PW cutoff:';",
"",
" addDropdownChoice(pprec, \"300\", \"300\");",
" addDropdownChoice(pprec, \"400\", \"400\");",
@@ -1472,8 +1580,8 @@
" addDropdownChoice(pprec, \"1400\", \"1100\");",
" addDropdownChoice(pprec, \"1500\", \"1100\");",
"",
- " addDropdownChoice(pxc, \"pbe\", \"pbe\");",
- " addDropdownChoice(pxc, \"pw-lda\", \"pbw-lda\");",
+ " addDropdownChoice(pxc, \"pbe\", \"PBE\");",
+ " addDropdownChoice(pxc, \"pw-lda\", \"LDA\");",
" break;",
"",
"",
@@ -1500,17 +1608,27 @@
" <th>XC-Functional:</th>",
" <td>",
" <select id=\"errorbar_val_xcfunctional\">",
- " <option value=\"PBE\" selected>PBE</option>",
- " <option value=\"LDA\">LDA</option>",
+ " <option value=\"pbe\" selected>PBE</option>",
+ " <option value=\"pw-lda\">LDA</option>",
" </select>",
" </td>",
" <td id=\"errorbar_val_xcfunctional_description\" style=\"white-space: pre;\"></td>",
- " <th id=\"errorbar_val_precision_name\">Precision:</th>",
+ " <th id=\"errorbar_val_precision_name\">PW cutoff:</th>",
" <td>",
" <select id=\"errorbar_val_precision\" >",
- " <option value=\"Low\" selected>Low</option>",
- " <option value=\"Normal\">Normal</option> ",
- " <option value=\"Accurate\">Acurate</option> ",
+ " <option value=\"300\">300</option>",
+ " <option value=\"400\">400</option>",
+ " <option value=\"500\">500</option>",
+ " <option value=\"600\" selected>600</option>",
+ " <option value=\"700\">700</option>",
+ " <option value=\"800\">800</option>",
+ " <option value=\"900\">900</option>",
+ " <option value=\"1000\">1000</option>",
+ " <option value=\"1100\">1100</option>",
+ " <option value=\"1200\">1200</option>",
+ " <option value=\"1300\">1300</option>",
+ " <option value=\"1400\">1400</option>",
+ " <option value=\"1500\">1500</option> ",
" </select>",
" </td>",
" <td id=\"errorbar_val_precision_description\" style=\"white-space: pre;\"></td>",
@@ -1519,7 +1637,7 @@
" <th>Tiers:</th>",
" <td><select id=\"errorbar_val_tiers\" ><!-- content inserted programmatically --></select></td>",
" <td id=\"errorbar_val_tiers_description\" style=\"white-space: pre;\"></td>",
- " <th>relativity treatment:</th>",
+ " <th>Relativity treatment:</th>",
" <td><select id=\"errorbar_val_relativity\" ><!-- content inserted programmatically --></select></td>",
" <td id=\"errorbar_val_relativity_description\" style=\"white-space: pre;\"></td>",
"",
@@ -1536,9 +1654,9 @@
"",
" <th>Code:</th>",
" <td><select id=\"errorbar_val_code\" onchange=\"error_valUpdateForm()\">",
- " <option value=\"VASP\">VASP</option>",
+ " <option value=\"GPAW\">GPAW</option> ",
" <option value=\"FHI-aims\">FHI-aims</option>",
- " <option value=\"GPAW\">GPAW</option> ",
+ " <option value=\"VASP\">VASP</option> ",
" </select></td>",
" <td id=\"errorbar_val_code_description\" style=\"white-space: pre;\"></td>",
" </tr>",
@@ -1572,14 +1690,14 @@
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"type": "BeakerDisplay",
"innertype": "Html",
- "object": "<script>\nvar beaker = bkHelper.getBeakerObject().beakerObj;\n</script>\n<script>\n \n function process_form() {\n beaker.query = $('#query').val(); \n beaker.ctrl_val_xc = document.getElementById(\"errorbar_val_xcfunctional\").value;\n beaker.ctrl_val_kpt = 8;\n beaker.ctrl_val_prec = document.getElementById(\"errorbar_val_precision\").value;\n beaker.ctrl_val_tiers = document.getElementById(\"errorbar_val_tiers\").value;\n beaker.ctrl_val_rel = document.getElementById(\"errorbar_val_relativity\").value;\n beaker.ctrl_val_pred = 1;\n beaker.ctrl_val_quant = document.getElementById(\"errorbar_val_quantity\").value;\n beaker.ctrl_val_code = document.getElementById(\"errorbar_val_code\").value;\n beaker.evaluate(\"process_formula_cell\");\n }\n \n function error_valUpdateForm() {\n var code = document.getElementById(\"errorbar_val_code\").value;\n \n var dprec = document.getElementById(\"errorbar_val_precision_name\");\n var pprec = document.getElementById(\"errorbar_val_precision\"); pprec.innerHTML = '';\n var prel = document.getElementById(\"errorbar_val_relativity\"); prel.innerHTML = '';\n var ptiers = document.getElementById(\"errorbar_val_tiers\"); ptiers.innerHTML = '';\n var pxc = document.getElementById(\"errorbar_val_xcfunctional\"); pxc.innerHTML = '';\n\n switch(code) {\n case \"VASP\": \n dprec.innerHTML = 'Precision:';\n\n addDropdownChoice(pprec, \"Low\", \"Low\");\n addDropdownChoice(pprec, \"Normal\", \"Normal\");\n addDropdownChoice(pprec, \"Accurate\", \"Accurate\");\n addDropdownChoice(pxc, \"PBE\", \"PBE\");\n addDropdownChoice(pxc, \"LDA\", \"LDA\");\n break;\n \n case \"FHI-aims\": \n dprec.innerHTML = 'Integration grid:';\n\n addDropdownChoice(pprec, \"light\", \"light\");\n addDropdownChoice(pprec, \"tight\", \"tight\");\n addDropdownChoice(pprec, \"really_tight\", \"really_tight\");\n addDropdownChoice(prel, \"atomic_zora\", \"atomic_zora\");\n addDropdownChoice(prel, \"zora\", \"zora\");\n addDropdownChoice(ptiers, \"minimal\", \"minimal\");\n addDropdownChoice(ptiers, \"standard\", \"standard\");\n addDropdownChoice(ptiers, \"tier1\", \"tier1\");\n addDropdownChoice(ptiers, \"tier2\", \"tier2\");\n addDropdownChoice(pxc, \"pbe\", \"pbe\");\n addDropdownChoice(pxc, \"pw-lda\", \"pbw-lda\");\n break;\n\n \n case \"GPAW\": \n dprec.innerHTML = '$E_{cut}$:';\n\n addDropdownChoice(pprec, \"300\", \"300\");\n addDropdownChoice(pprec, \"400\", \"400\");\n addDropdownChoice(pprec, \"500\", \"500\");\n addDropdownChoice(pprec, \"600\", \"600\");\n addDropdownChoice(pprec, \"700\", \"700\");\n addDropdownChoice(pprec, \"800\", \"800\");\n addDropdownChoice(pprec, \"900\", \"900\");\n addDropdownChoice(pprec, \"1000\", \"1000\");\n addDropdownChoice(pprec, \"1100\", \"1100\");\n addDropdownChoice(pprec, \"1200\", \"1100\");\n addDropdownChoice(pprec, \"1300\", \"1100\");\n addDropdownChoice(pprec, \"1400\", \"1100\");\n addDropdownChoice(pprec, \"1500\", \"1100\");\n\n addDropdownChoice(pxc, \"pbe\", \"pbe\");\n addDropdownChoice(pxc, \"pw-lda\", \"pbw-lda\");\n break;\n\n\n }\n }\n\n\n\n</script>\n\n<style type=\"text/css\">\n \n .error_val_table th { font-weight: bold; padding-right: 2ex; }\n .error_val_table td input { margin-right: 1ex; }\n \n</style>\n\n<!-- Controls area -->\n\n<div class=\"error_val_control\">\n <table class=\"error_val_table\">\n \n <tbody><tr>\n <th>XC-Functional:</th>\n <td>\n <select id=\"errorbar_val_xcfunctional\">\n <option value=\"PBE\" selected=\"\">PBE</option>\n <option value=\"LDA\">LDA</option>\n </select>\n </td>\n <td id=\"errorbar_val_xcfunctional_description\" style=\"white-space: pre;\"></td>\n <th id=\"errorbar_val_precision_name\">Precision:</th>\n <td>\n <select id=\"errorbar_val_precision\">\n <option value=\"Low\" selected=\"\">Low</option>\n <option value=\"Normal\">Normal</option> \n <option value=\"Accurate\">Acurate</option> \n </select>\n </td>\n <td id=\"errorbar_val_precision_description\" style=\"white-space: pre;\"></td>\n </tr>\n <tr>\n <th>Tiers:</th>\n <td><select id=\"errorbar_val_tiers\"><!-- content inserted programmatically --></select></td>\n <td id=\"errorbar_val_tiers_description\" style=\"white-space: pre;\"></td>\n <th>relativity treatment:</th>\n <td><select id=\"errorbar_val_relativity\"><!-- content inserted programmatically --></select></td>\n <td id=\"errorbar_val_relativity_description\" style=\"white-space: pre;\"></td>\n\n </tr> \n \n <tr>\n <th>Quantity:</th>\n <td><select id=\"errorbar_val_quantity\">\n <option value=\"E_tot\">Total Energy</option>\n <option value=\"relR\">relative Energy</option>\n </select></td>\n <td id=\"errorbar_val_quantity_description\" style=\"white-space: pre;\"></td> \n \n\n <th>Code:</th>\n <td><select id=\"errorbar_val_code\" onchange=\"error_valUpdateForm()\">\n <option value=\"VASP\">VASP</option>\n <option value=\"FHI-aims\">FHI-aims</option>\n <option value=\"GPAW\">GPAW</option> \n </select></td>\n <td id=\"errorbar_val_code_description\" style=\"white-space: pre;\"></td>\n </tr>\n \n </tbody></table>\n \n</div>\n\n<br><br>\n<p>Enter: Formula:</p>\n\n<p>\n <input id=\"query\" value=\"H2\" size=\"40\" onkeydown=\"if (event.keyCode == 13) process_form()\" type=\"text\">\n</p>\n<p>Examples:</p>\n<p>\n <fontsize=4>\n<code>O2</code> <br>\n<code>FePO4</code>\n\n</fontsize=4></p>\n<button onclick=\"process_form()\"> Estimate error </button>\n\n"
+ "object": "<script>\nvar beaker = bkHelper.getBeakerObject().beakerObj;\n</script>\n<script>\n \n function process_form() {\n beaker.query = $('#query').val(); \n beaker.ctrl_val_xc = document.getElementById(\"errorbar_val_xcfunctional\").value;\n beaker.ctrl_val_kpt = 8;\n beaker.ctrl_val_prec = document.getElementById(\"errorbar_val_precision\").value;\n beaker.ctrl_val_tiers = document.getElementById(\"errorbar_val_tiers\").value;\n beaker.ctrl_val_rel = document.getElementById(\"errorbar_val_relativity\").value;\n beaker.ctrl_val_pred = 1;\n beaker.ctrl_val_quant = document.getElementById(\"errorbar_val_quantity\").value;\n beaker.ctrl_val_code = document.getElementById(\"errorbar_val_code\").value;\n beaker.evaluate(\"process_formula_cell\");\n }\n \n function error_valUpdateForm() {\n var code = document.getElementById(\"errorbar_val_code\").value;\n \n var dprec = document.getElementById(\"errorbar_val_precision_name\");\n var pprec = document.getElementById(\"errorbar_val_precision\"); pprec.innerHTML = '';\n var prel = document.getElementById(\"errorbar_val_relativity\"); prel.innerHTML = '';\n var ptiers = document.getElementById(\"errorbar_val_tiers\"); ptiers.innerHTML = '';\n var pxc = document.getElementById(\"errorbar_val_xcfunctional\"); pxc.innerHTML = '';\n\n switch(code) {\n case \"VASP\": \n dprec.innerHTML = 'Precision:';\n\n addDropdownChoice(pprec, \"Low\", \"Low\");\n addDropdownChoice(pprec, \"Normal\", \"Normal\");\n addDropdownChoice(pprec, \"Accurate\", \"Accurate\");\n addDropdownChoice(pxc, \"PBE\", \"PBE\");\n addDropdownChoice(pxc, \"LDA\", \"LDA\");\n break;\n \n case \"FHI-aims\": \n dprec.innerHTML = 'Integration grid:';\n\n addDropdownChoice(pprec, \"light\", \"light\");\n addDropdownChoice(pprec, \"tight\", \"tight\");\n addDropdownChoice(pprec, \"really_tight\", \"really tight\");\n addDropdownChoice(prel, \"atomic_zora\", \"atomic zora\");\n addDropdownChoice(prel, \"zora\", \"zora\");\n addDropdownChoice(ptiers, \"minimal\", \"minimal\");\n addDropdownChoice(ptiers, \"standard\", \"standard\");\n addDropdownChoice(ptiers, \"tier1\", \"tier1\");\n addDropdownChoice(ptiers, \"tier2\", \"tier2\");\n addDropdownChoice(pxc, \"pbe\", \"PBE\");\n addDropdownChoice(pxc, \"pw-lda\", \"LDA\");\n break;\n\n \n case \"GPAW\": \n dprec.innerHTML = 'PW cutoff:';\n\n addDropdownChoice(pprec, \"300\", \"300\");\n addDropdownChoice(pprec, \"400\", \"400\");\n addDropdownChoice(pprec, \"500\", \"500\");\n addDropdownChoice(pprec, \"600\", \"600\");\n addDropdownChoice(pprec, \"700\", \"700\");\n addDropdownChoice(pprec, \"800\", \"800\");\n addDropdownChoice(pprec, \"900\", \"900\");\n addDropdownChoice(pprec, \"1000\", \"1000\");\n addDropdownChoice(pprec, \"1100\", \"1100\");\n addDropdownChoice(pprec, \"1200\", \"1100\");\n addDropdownChoice(pprec, \"1300\", \"1100\");\n addDropdownChoice(pprec, \"1400\", \"1100\");\n addDropdownChoice(pprec, \"1500\", \"1100\");\n\n addDropdownChoice(pxc, \"pbe\", \"PBE\");\n addDropdownChoice(pxc, \"pw-lda\", \"LDA\");\n break;\n\n\n }\n }\n\n\n\n</script>\n\n<style type=\"text/css\">\n \n .error_val_table th { font-weight: bold; padding-right: 2ex; }\n .error_val_table td input { margin-right: 1ex; }\n \n</style>\n\n<!-- Controls area -->\n\n<div class=\"error_val_control\">\n <table class=\"error_val_table\">\n \n <tbody><tr>\n <th>XC-Functional:</th>\n <td>\n <select id=\"errorbar_val_xcfunctional\">\n <option value=\"pbe\" selected=\"\">PBE</option>\n <option value=\"pw-lda\">LDA</option>\n </select>\n </td>\n <td id=\"errorbar_val_xcfunctional_description\" style=\"white-space: pre;\"></td>\n <th id=\"errorbar_val_precision_name\">PW cutoff:</th>\n <td>\n <select id=\"errorbar_val_precision\">\n <option value=\"300\">300</option>\n <option value=\"400\">400</option>\n <option value=\"500\">500</option>\n <option value=\"600\" selected=\"\">600</option>\n <option value=\"700\">700</option>\n <option value=\"800\">800</option>\n <option value=\"900\">900</option>\n <option value=\"1000\">1000</option>\n <option value=\"1100\">1100</option>\n <option value=\"1200\">1200</option>\n <option value=\"1300\">1300</option>\n <option value=\"1400\">1400</option>\n <option value=\"1500\">1500</option> \n </select>\n </td>\n <td id=\"errorbar_val_precision_description\" style=\"white-space: pre;\"></td>\n </tr>\n <tr>\n <th>Tiers:</th>\n <td><select id=\"errorbar_val_tiers\"><!-- content inserted programmatically --></select></td>\n <td id=\"errorbar_val_tiers_description\" style=\"white-space: pre;\"></td>\n <th>Relativity treatment:</th>\n <td><select id=\"errorbar_val_relativity\"><!-- content inserted programmatically --></select></td>\n <td id=\"errorbar_val_relativity_description\" style=\"white-space: pre;\"></td>\n\n </tr> \n \n <tr>\n <th>Quantity:</th>\n <td><select id=\"errorbar_val_quantity\">\n <option value=\"E_tot\">Total Energy</option>\n <option value=\"relR\">relative Energy</option>\n </select></td>\n <td id=\"errorbar_val_quantity_description\" style=\"white-space: pre;\"></td> \n \n\n <th>Code:</th>\n <td><select id=\"errorbar_val_code\" onchange=\"error_valUpdateForm()\">\n <option value=\"GPAW\">GPAW</option> \n <option value=\"FHI-aims\">FHI-aims</option>\n <option value=\"VASP\">VASP</option> \n </select></td>\n <td id=\"errorbar_val_code_description\" style=\"white-space: pre;\"></td>\n </tr>\n \n </tbody></table>\n \n</div>\n\n<br><br>\n<p>Enter: Formula:</p>\n\n<p>\n <input id=\"query\" value=\"H2\" size=\"40\" onkeydown=\"if (event.keyCode == 13) process_form()\" type=\"text\">\n</p>\n<p>Examples:</p>\n<p>\n <fontsize=4>\n<code>O2</code> <br>\n<code>FePO4</code>\n\n</fontsize=4></p>\n<button onclick=\"process_form()\"> Estimate error </button>\n\n"
},
"selectedType": "BeakerDisplay",
"elapsedTime": 0,
- "height": 331
+ "height": 0
},
"evaluatorReader": true,
- "lineCount": 161,
+ "lineCount": 171,
"initialization": true
},
{
@@ -1647,41 +1765,41 @@
"outputdata": [
{
"type": "out",
- "value": "Total energy error for H2: -22.199865 meV (per atom)\n"
+ "value": "Total energy error for H2: -4.10157794 meV (per atom)\n"
}
]
},
"selectedType": "Results",
"pluginName": "IPython",
- "shellId": "27A64174BE534D8A81CD4007A8828BAE",
- "elapsedTime": 2252,
- "height": 55
+ "shellId": "4CE22EA14B7A45608ED58BBCC25D6400",
+ "elapsedTime": 2467,
+ "height": 0
},
"evaluatorReader": true,
"lineCount": 49
}
],
"namespace": {
- "ctrl_xc": "PBE",
- "ctrl_kpt": "2",
- "ctrl_prec": "Low",
+ "ctrl_xc": "pbe",
+ "ctrl_kpt": "8",
+ "ctrl_prec": "600",
"ctrl_tiers": "",
"ctrl_rel": "",
"ctrl_pred": "1",
"ctrl_quant": "E_tot",
"ctrl_sys": "monomers",
- "ctrl_code": "VASP",
+ "ctrl_code": "GPAW",
"ctrl_buttom": 1,
"ctrl_button": 3,
"query": "H2",
- "ctrl_val_xc": "PBE",
+ "ctrl_val_xc": "pbe",
"ctrl_val_kpt": 8,
- "ctrl_val_prec": "Low",
+ "ctrl_val_prec": "600",
"ctrl_val_tiers": "",
"ctrl_val_rel": "",
"ctrl_val_pred": 1,
"ctrl_val_quant": "E_tot",
- "ctrl_val_code": "VASP",
+ "ctrl_val_code": "GPAW",
"ctrl_estimate_xc": "PBE",
"ctrl_estimate_kpt": 8,
"ctrl_estimate_prec": "Low",
@@ -1693,19 +1811,18 @@
"ctrl_estimate_estimate_tiers": "",
"ctrl_estimate_estimate_rel": "",
"ctrl_estimate_button": 1,
- "ctrl_xc_estimate": "PBE",
+ "ctrl_xc_estimate": "pbe",
"ctrl_kpt_estimate": 8,
"ctrl_button_estimate": 3,
"ctrl_estimate_pred": 1,
"ctrl_estimate_quant": "E_tot",
"ctrl_estimate_code": "VASP",
- "ctrl_prec_estimate": "Low",
+ "ctrl_prec_estimate": "600",
"ctrl_tiers_estimate": "",
"ctrl_rel_estimate": "",
"ctrl_pred_estimate": 1,
"ctrl_quant_estimate": "E_tot",
- "ctrl_code_estimate": "VASP",
+ "ctrl_code_estimate": "GPAW",
"ctrl_sys_estimate": "binaries"
- },
- "locked": true
+ }
}
diff --git a/example-data/errorbars/periodic_table_binaries.png b/example-data/errorbars/periodic_table_binaries.png
new file mode 100644
index 0000000000000000000000000000000000000000..53bf892192c1c8c99e472c0f0ffc704b5e541de1
Binary files /dev/null and b/example-data/errorbars/periodic_table_binaries.png differ
diff --git a/example-data/errorbars/periodic_table_elemental_solids.png b/example-data/errorbars/periodic_table_elemental_solids.png
new file mode 100644
index 0000000000000000000000000000000000000000..098e2f02490504228a37094e94eac7fec911ba48
Binary files /dev/null and b/example-data/errorbars/periodic_table_elemental_solids.png differ