Fix overlapping legends in matplotlib plot

espressomd · Sep 30, 2020 · 6426cbf · 6426cbf
1 parent 4e7ee29
commit 6426cbf
Showing 1 changed file with 12 additions and 11 deletions.
diff --git a/doc/tutorials/01-lennard_jones/01-lennard_jones.ipynb b/doc/tutorials/01-lennard_jones/01-lennard_jones.ipynb
@@ -699,23 +699,24 @@
     "# Plot total energy and instantaneous temperature\n",
     "import matplotlib.pyplot as plt\n",
     "\n",
-    "fig1,ax = plt.subplots(num=None, figsize=(10, 6),\n",
+    "fig1,ax1 = plt.subplots(num=None, figsize=(10, 6),\n",
     "                       dpi=80, facecolor='w', edgecolor='k')\n",
     "fig1.set_tight_layout(False)\n",
     "\n",
     "t = np.arange(0,SAMPLING_ITERATIONS*SAMPLING_INTERVAL,SAMPLING_INTERVAL)\n",
-    "ax.plot(t,e_total, lw=2, label='e_total')\n",
-    "ax.set_xlabel('time step', fontsize=20)\n",
-    "ax.set_ylabel('total energy', fontsize=20)\n",
-    "ax.legend(fontsize=16)\n",
-    "ax.tick_params(axis='both', labelsize=16)\n",
-    "ax2 = ax.twinx()\n",
-    "ax2.plot(t,e_kin/ (1.5 * N_PART), color='r', ls='--', lw=2,\n",
+    "ln1 = ax1.plot(t, e_total, lw=2, label='total energy')\n",
+    "ax1.set_xlabel('time step', fontsize=20)\n",
+    "ax1.set_ylabel('Energy', fontsize=20)\n",
+    "ax1.tick_params(axis='both', labelsize=16)\n",
+    "ax2 = ax1.twinx()\n",
+    "ln2 = ax2.plot(t, e_kin/ (1.5 * N_PART), color='r', ls='--', lw=2,\n",
     "         label='instantaneous temperature')\n",
     "ax2.axhline(TEMPERATURE, ls='-.', lw=3, color='k')\n",
-    "ax2.set_ylabel('instantaneous temperature', fontsize=20)\n",
-    "ax2.legend(fontsize=16)\n",
+    "ax2.set_ylabel('Temperature', fontsize=20)\n",
     "ax2.tick_params(axis='both', labelsize=16)\n",
+    "lns = ln1 + ln2\n",
+    "labs = [l.get_label() for l in lns]\n",
+    "ax1.legend(lns, labs, fontsize=16)\n",
     "print(\"average simulation temperature: {:1.3f}\".format(np.round(e_kin.mean()/ (1.5 * N_PART),3)),\n",
     "     \"\\t(which differs by {:1.3f}% from TEMPERATURE)\".format(np.round(((e_kin.mean()/ (1.5 * N_PART) - TEMPERATURE) / TEMPERATURE)*100,3)))\n",
     "```"
@@ -740,7 +741,7 @@
     "solution2": "hidden"
    },
    "source": [
-    "``` python\n",
+    "```python\n",
     "# autocorrelation using numpy.correlate\n",
     "def autocor(x):\n",
     "    mean=x.mean()\n",