diff --git a/assets/soap_atomic_charges/Logo_NOMAD.png b/assets/soap_atomic_charges/Logo_NOMAD.png new file mode 100644 index 0000000000000000000000000000000000000000..2187e3b9351e11aa693758559114c1f2a6670731 Binary files /dev/null and b/assets/soap_atomic_charges/Logo_NOMAD.png differ diff --git a/soap_atomic_charges.ipynb b/soap_atomic_charges.ipynb index 1493b163d41d615e0f2ed31468c2ab25b22c8c70..25e4c81d6093f969508ca9deab090dda11a37355 100644 --- a/soap_atomic_charges.ipynb +++ b/soap_atomic_charges.ipynb @@ -4,10 +4,37 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Learning atomic charges\n", - "\n", - "_Gábor Csányi (gc121@cam.ac.uk), James R. Kermode (j.r.kermode@warwick.ac.uk)_\n", - "\n", + "<div id=\"teaser\" style=' background-position: right center; background-size: 00px; background-repeat: no-repeat; \n", + " padding-top: 20px;\n", + " padding-right: 10px;\n", + " padding-bottom: 170px;\n", + " padding-left: 10px;\n", + " border-bottom: 14px double #333;\n", + " border-top: 14px double #333;' > \n", + "\n", + " \n", + " <div style=\"text-align:center\">\n", + " <b><font size=\"6.4\">Learning atomic charges</font></b> \n", + " </div>\n", + " \n", + "<p>\n", + " created by:\n", + " Gábor Csányi,\n", + " James R. Kermode\n", + "<br><p> \n", + "gc121@cam.ac.uk, j.r.kermode@warwick.ac.uk\n", + "<br><br> \n", + "\n", + "<div> \n", + "<img style=\"float: right;\" src=\"assets/soap_atomic_charges/Logo_NOMAD.png\" width=\"250\">\n", + "</div>\n", + "</div>" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ "In this tutorial, we will use Gaussian process regression, GPR (or equivalently, Kernel Ridge Regression, KRR) to train and predict charges of atoms in small organic molecules. " ] }, @@ -450,13 +477,6 @@ "\n", "4. For the low-quality fit above, you see that there are two groups of H atoms that are clearly separated. Try to identify what characterises those groups? Inspect the molecules and H atoms in each group. " ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -476,7 +496,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.3" + "version": "3.7.7" } }, "nbformat": 4,