Added basic plotting example for Python.

book/content/examples/01_basic/07_basic_example_da_ii.ipynb

@@ -65,25 +65,6 @@
     "import os\n"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "['Fig16_LoveSeat.txt', 'Fig16_Sofa.txt', 'Fig16_SingleChair.txt']\n"
-     ]
-    }
-   ],
-   "source": [
-    "folder_path='data/Furniture_calorimetry'\n",
-    "files = os.listdir(folder_path)\n",
-    "print(files)"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -107,10 +88,37 @@
    "source": [
     "#Describe the Design fire HRR:\n",
     "time_series = np.linspace(0,130)#creating time series\n",
-    "alpha=0.19\n",
+    "alpha=0.19  # ultra fast\n",
     "HRR = alpha_t_squared(time_series, alpha)\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['Fig16_LoveSeat.txt', 'Fig16_Sofa.txt', 'Fig16_SingleChair.txt']\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Check files with experiment data.\n",
+    "folder_path='./data/Furniture_calorimetry'\n",
+    "files = os.listdir(folder_path)\n",
+    "print(files)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 6,
@@ -130,26 +138,42 @@
    "source": [
     "# Read the data from the experiments.\n",
     "for file in files:\n",
+    "    # Filter out specific type of files.\n",
     "    if file.endswith('.txt'):\n",
-    "        file_path = os.path.join(folder_path,file)\n",
+    "        # Create data series label.\n",
     "        label = os.path.splitext(file )[0].split('_')[-1]  # Extract label from filename\n",
-    "        df = pd.read_csv(file_path, header=0)\n",
+    "        \n",
+    "        # Read file.\n",
+    "        file_path = os.path.join(folder_path,file)\n",
+    "        furniture_df = pd.read_csv(file_path, header=0)\n",
+    "        \n",
     "        if \"Chair\" in file:\n",
     "            # Shift data series such that the increasing slopes align.\n",
-    "            plt.plot(df['Time'] - 60, df['HRR'], label=label.capitalize())\n",
+    "            time_shift = 60\n",
     "        else:\n",
-    "            plt.plot(df['Time'], df['HRR'], label=label.capitalize())\n",
+    "            time_shift = 0\n",
+    "            \n",
+    "        # Plot data series.\n",
+    "        plt.plot(furniture_df['Time'] - time_shift, \n",
+    "                 furniture_df['HRR'], \n",
+    "                 label=label.capitalize())\n",
     "\n",
-    "# Assuming alpha_t_squared function results are stored in variables time_series and HRR\n",
-    "plt.plot(time_series + 90, HRR, color='k', linestyle='-.', label=\"Ultra fast\")\n",
+    "# Plot alpha_t_squared function results.\n",
+    "virtual_ignition_time = 90\n",
+    "plt.plot(time_series + virtual_ignition_time, \n",
+    "         HRR, \n",
+    "         color='k', linestyle='-.', \n",
+    "         label=\"Ultra fast\")\n",
     "\n",
     "\n",
     "# Plot meta data.\n",
     "plt.xlabel(\"Time / s\")\n",
     "plt.ylabel(\"Heat Release Rate / kW\")\n",
-    "plt.grid()\n",
     "plt.legend()\n",
-    "plt.show()"
+    "plt.grid()\n",
+    "\n",
+    "# Show plot.\n",
+    "plt.show() "
    ]
   }
  ],