remove commented out text

Author: reint-fischer

parcels/examples/tutorial_output.ipynb

@@ -270,9 +270,8 @@
     "y = data_xarray['lat'].values\n",
     "distance = np.cumsum(np.sqrt(np.square(np.diff(x))+np.square(np.diff(y))),axis=1)  # d = (dx^2 + dy^2)^(1/2)\n",
     "\n",
-    "real_time = data_xarray['time']/ns_per_hour\n",
-    "time_since_release = (real_time.values.transpose() - real_time.values[:,0]) # substract the initial time from each timeseries\n",
-    "# time_since_release = time_since_release/ns_per_hour  # convert time to hours"
+    "real_time = data_xarray['time']/ns_per_hour # convert time to hours\n",
+    "time_since_release = (real_time.values.transpose() - real_time.values[:,0]) # substract the initial time from each timeseries"
    ]
   },
   {
@@ -310,7 +309,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The two figures above show the same graph. Time is not needed to create the first figure. The time variable minus the first value of each trajectory gives the x-axis the correct units in the second figure. We can also plot the distance travelled as a function of the absolute time easily, since the `time` variable matches up with the data for each individual trajectory."
+    "The two figures above show the same graph. Time is not needed to create the first figure. The time variable minus the first value of each trajectory gives the x-axis the correct units in the second figure. \n",
+    "\n",
+    "We can also plot the distance travelled as a function of the absolute time easily, since the `time` variable matches up with the data for each individual trajectory."
    ]
   },
   {