HT EOS workflow on alloy system; Add notebook comments (#30, #31)

mlip_arena/tasks/eos_alloy/run.ipynb

@@ -283,17 +283,14 @@
     "    )\n",
     "    \n",
     "    for i, method in enumerate(methods):\n",
-    "        \n",
     "        ev0s = []\n",
     "        for fi, formula in enumerate(formulae):\n",
-    "        \n",
     "            filtered_data = df[(df['formula'] == formula) & (df['method'] == method)]\n",
     "            filtered_data = filtered_data.drop_duplicates(subset=['method', 'formula', 'volume'], keep='last')\n",
     "            \n",
     "            ev0s.append((filtered_data['v0'].drop_duplicates()[0], filtered_data['e0'].drop_duplicates()[0]))\n",
-    "            \n",
     "            c = Formula(formula) // Formula('Cr') / len(Formula(formula))\n",
-    "\n",
+    "            # Plot EOS curves at different compositions\n",
     "            axes[i].plot(\n",
     "                filtered_data['volume'], filtered_data['energy'],\n",
     "                c=cmap(norm(c)),\n",
@@ -302,9 +299,9 @@
     "            axes[i].set(\n",
     "                title=method\n",
     "            )\n",
-    "        \n",
+    "\n",
+    "        # Plot equilibrium volume and energy line\n",
     "        ev0s = np.array(sorted(ev0s, key=lambda x: x[1]))\n",
-    "        \n",
     "        axes[i].plot(ev0s[:, 0], ev0s[:, 1], \"--\", color=\"black\", lw=1)\n",
     "        axes[i].set(\n",
     "            xlabel='volume', ylabel='energy'\n",
@@ -314,7 +311,6 @@
     "    sm.set_array([])\n",
     "    cbar = fig.colorbar(sm, ax=axes, orientation='vertical', aspect=20)\n",
     "    cbar.set_label(\"Cr fraction\", rotation=270, labelpad=15)\n",
-    "    \n",
     "    plt.show()"
    ]
   },
@@ -567,6 +563,7 @@
     }
    ],
    "source": [
+    "# Calculate compositions\n",
     "elements = set().union(*[set(Formula(f)) for f in df['formula']])\n",
     "\n",
     "data = df.assign(**{\n",
@@ -37017,14 +37014,12 @@
    "source": [
     "import plotly.express as px\n",
     "\n",
-    "\n",
     "for i, method in enumerate(methods):\n",
     "    filtered_data = data[data['method'] == method]\n",
     "    filtered_data = filtered_data.drop_duplicates(subset=['method', 'formula', 'volume'], keep='last')\n",
     "    \n",
     "    fig = px.scatter_ternary(\n",
-    "        filtered_data, a=\"Fe\", b=\"Ni\", c=\"Cr\", color=\"b0\", #size=\"total\", size_max=15,\n",
-    "        # color_discrete_map = {\"Joly\": \"blue\", \"Bergeron\": \"green\", \"Coderre\":\"red\"} \n",
+    "        filtered_data, a=\"Fe\", b=\"Ni\", c=\"Cr\", color=\"b0\", \n",
     "    )\n",
     "    \n",
     "    fig.update_layout(title=method)\n",