Index: trunk/tests/testing_Etienne/.ipynb_checkpoints/SD_ToolBox_Testing-checkpoint.ipynb
===================================================================
diff -u -r115 -r117
--- trunk/tests/testing_Etienne/.ipynb_checkpoints/SD_ToolBox_Testing-checkpoint.ipynb	(.../SD_ToolBox_Testing-checkpoint.ipynb)	(revision 115)
+++ trunk/tests/testing_Etienne/.ipynb_checkpoints/SD_ToolBox_Testing-checkpoint.ipynb	(.../SD_ToolBox_Testing-checkpoint.ipynb)	(revision 117)
@@ -140,6 +140,26 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "# get the coordinates of the WAM locations\n",
+    "lonWAM = DS.variables['lon'][:] # list with longitude positions\n",
+    "latWAM = DS.variables['lat'][:] # list with latitude positions \n",
+    "\n",
+    "coordsWAM = {'LON': [], 'LAT': []}\n",
+    "for i, j in zip(lonWAM, latWAM):\n",
+    "    coordsWAM['LON'].append(i)\n",
+    "    coordsWAM['LAT'].append(j)\n",
+    "\n",
+    "# set other data variables    \n",
+    "varWAM = [v.lower() for v in variables[5:]] # list with the five wave parameters -> it automatically only uses swh, pp1d, mwd\n",
+    "timeWAMy = [1986] # 1987 to 2018"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -149,26 +169,13 @@
       "Extracting variable: Tp, year 1986.\n",
       "Extracting variable: MWD, year 1986.\n",
       "Writing C:\\checkouts\\trunk\\tests\\testing_Etienne\\datasets\\WAM_ERA5_WAVE.nc\n",
-      "writing variable pp1d\n",
+      "writing variable mwd\n",
       "writing variable swh\n",
-      "writing variable mwd\n"
+      "writing variable pp1d\n"
      ]
     }
    ],
    "source": [
-    "# get the coordinates of the WAM locations\n",
-    "lonWAM = DS.variables['lon'][:] # list with longitude positions\n",
-    "latWAM = DS.variables['lat'][:] # list with latitude positions \n",
-    "\n",
-    "coordsWAM = {'LON': [], 'LAT': []}\n",
-    "for i, j in zip(lonWAM, latWAM):\n",
-    "    coordsWAM['LON'].append(i)\n",
-    "    coordsWAM['LAT'].append(j)\n",
-    "\n",
-    "# set other data variables    \n",
-    "varWAM = [v.lower() for v in variables[5:]] # list with the five wave parameters -> ind automatically only uses swh, pp1d, mwd\n",
-    "timeWAMy = [1986] # 1987 to 2018\n",
-    "\n",
     "# use the SDToolBox function to create input data\n",
     "Input_DataWAM = ind.InputData(\n",
     "    input_coordinates=coordsWAM,\n",
@@ -189,7 +196,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -244,7 +251,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -266,7 +273,7 @@
     "folder2 = r'C:\\checkouts\\trunk\\tests\\testing_Etienne\\datasets'\n",
     "\n",
     "# open the data in this script to get the info\n",
-    "DS_WAM_ERA5 = Dataset(os.path.join(folder2,'WAM_ERA5.nc'))\n",
+    "DS_WAM_ERA5 = Dataset(os.path.join(folder2,'WAM_ERA5_WAVE.nc'))\n",
     "\n",
     "# get the relevant data from the netcdf files\n",
     "time_WAM_ERA5 = list(DS_WAM_ERA5.variables['time'])\n",
@@ -326,49 +333,56 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['msl']\n",
-      "Extracting variable: Hs, year 1986.\n"
+      "['swh', 'pp1d', 'mwd']\n",
+      "Extracting variable: Hs, year 1986.\n",
+      "Extracting variable: Tp, year 1986.\n",
+      "Extracting variable: MWD, year 1986.\n",
+      "Writing C:\\checkouts\\trunk\\tests\\testing_Etienne\\datasets\\BOX_ERA5_WAVE.nc\n",
+      "writing variable swh\n"
      ]
     },
     {
-     "ename": "KeyError",
-     "evalue": "'swh'",
+     "ename": "ValueError",
+     "evalue": "shape mismatch: objects cannot be broadcast to a single shape",
      "output_type": "error",
      "traceback": [
       "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
-      "\u001b[1;32m<ipython-input-91-46658c84726f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     21\u001b[0m \u001b[1;31m# use the SDToolBox function to extract data\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     22\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mInput_DataBOX\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minput_variables\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 23\u001b[1;33m \u001b[0mExtract_Data_ERA5BOX\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mexd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mExtractData\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_era_5\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdir_ERA5\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mInput_DataBOX\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     24\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     25\u001b[0m \u001b[1;31m# generate output data for waves\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mC:\\checkouts\\trunk\\SDToolBox\\extract_data.py\u001b[0m in \u001b[0;36mget_era_5\u001b[1;34m(directory_path, input_data)\u001b[0m\n\u001b[0;32m     55\u001b[0m         return data_extractor.extract_subset(\n\u001b[0;32m     56\u001b[0m                 \u001b[0mdirectory_path\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdirectory_path\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 57\u001b[1;33m                 \u001b[0minput_data\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0minput_data\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     58\u001b[0m             )\n\u001b[0;32m     59\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mC:\\checkouts\\trunk\\SDToolBox\\extract_data.py\u001b[0m in \u001b[0;36mextract_subset\u001b[1;34m(self, directory_path, input_data)\u001b[0m\n\u001b[0;32m    245\u001b[0m                         \u001b[0mvar_name\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mvariable_key\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    246\u001b[0m                         value=self.__get_variable_subset(\n\u001b[1;32m--> 247\u001b[1;33m                             \u001b[0moutput_data\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_from_var_dict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvariable_key\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    248\u001b[0m                             \u001b[0minput_data\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    249\u001b[0m                             \u001b[0minput_dataset\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mC:\\checkouts\\trunk\\SDToolBox\\output_data.py\u001b[0m in \u001b[0;36mget_from_var_dict\u001b[1;34m(self, var_name)\u001b[0m\n\u001b[0;32m    187\u001b[0m             \u001b[0mAny\u001b[0m \u001b[1;33m-\u001b[0m\u001b[1;33m-\u001b[0m \u001b[0mValue\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mrequested\u001b[0m \u001b[0mvariable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    188\u001b[0m         \"\"\"\n\u001b[1;32m--> 189\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__data_dict\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvar_val_key\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mvar_name\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    190\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    191\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mset_in_var_dict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvar_name\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mAny\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mKeyError\u001b[0m: 'swh'"
+      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-6-016787fd068e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     29\u001b[0m     \u001b[0mdir_path\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34mr'C:\\checkouts\\trunk\\tests\\testing_Etienne\\datasets'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     30\u001b[0m     \u001b[0mbase_name\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'BOX'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 31\u001b[1;33m     dataset_code='ERA5_WAVE')\n\u001b[0m",
+      "\u001b[1;32mC:\\checkouts\\trunk\\SDToolBox\\output_data.py\u001b[0m in \u001b[0;36mgenerate_netcdf\u001b[1;34m(self, dir_path, base_name, dataset_code)\u001b[0m\n\u001b[0;32m    170\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__set_geo_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnetcdf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    171\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__set_dataset_variables\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnetcdf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdataset_code\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 172\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__set_variables_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnetcdf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdataset_code\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    173\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__set_global_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnetcdf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdataset_code\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    174\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mC:\\checkouts\\trunk\\SDToolBox\\output_data.py\u001b[0m in \u001b[0;36m__set_variables_data\u001b[1;34m(self, netcdf, dataset_code)\u001b[0m\n\u001b[0;32m    597\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mis_gridded\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    598\u001b[0m                 \u001b[0mnetcdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvariables\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mvar_name\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m\\\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 599\u001b[1;33m                     \u001b[0mvariables\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mvar_name\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    600\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    601\u001b[0m                 \u001b[1;31m# When non-gridded we need to transpose the dimensions.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mnetCDF4\\_netCDF4.pyx\u001b[0m in \u001b[0;36mnetCDF4._netCDF4.Variable.__setitem__\u001b[1;34m()\u001b[0m\n",
+      "\u001b[1;32m~\\anaconda3\\envs\\SDToolBox_env\\lib\\site-packages\\netCDF4\\utils.py\u001b[0m in \u001b[0;36m_StartCountStride\u001b[1;34m(elem, shape, dimensions, grp, datashape, put, use_get_vars)\u001b[0m\n\u001b[0;32m    363\u001b[0m         \u001b[0mfullslice\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    364\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mfullslice\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mdatashape\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mput\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mhasunlim\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 365\u001b[1;33m         \u001b[0mdatashape\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mbroadcasted_shape\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdatashape\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    366\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    367\u001b[0m     \u001b[1;31m# pad datashape with zeros for dimensions not being sliced (issue #906)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32m~\\anaconda3\\envs\\SDToolBox_env\\lib\\site-packages\\netCDF4\\utils.py\u001b[0m in \u001b[0;36mbroadcasted_shape\u001b[1;34m(shp1, shp2)\u001b[0m\n\u001b[0;32m    971\u001b[0m     \u001b[0ma\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mas_strided\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mshape\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mshp1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstrides\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mshp1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    972\u001b[0m     \u001b[0mb\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mas_strided\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mshape\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mshp2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstrides\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mshp2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 973\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbroadcast\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mb\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[1;31mValueError\u001b[0m: shape mismatch: objects cannot be broadcast to a single shape"
      ]
     }
    ],
    "source": [
     "# select a spatial range (box) for which data is to be extracted\n",
-    "steplon = 0.5 # degrees\n",
-    "lonl = -5 # left lon value\n",
-    "lonr = 11 # right lon value\n",
-    "steplat = 0.5\n",
-    "latl = 50 # lower lat value\n",
-    "latu = 62 # upper lat value\n",
-    "xrang = np.arange(lonl, lonr+steplon, steplon).tolist() \n",
-    "yrang = np.arange(latl, latu+steplat, steplat).tolist() \n",
+    "steplon = 1 # degrees\n",
+    "lonl = 3 # left lon value\n",
+    "lonr = 4 # right lon value\n",
+    "steplat = 1 # degrees\n",
+    "latl = 53 # lower lat value\n",
+    "latu = 54 # upper lat value\n",
+    "xrange = np.arange(lonl, lonr+steplon, steplon).tolist() \n",
+    "yrange = np.arange(latl, latu+steplat, steplat).tolist() \n",
+    "varBOX = ['swh', 'pp1d', 'mwd']\n",
     "\n",
-    "coordsBOX = {'LON': xrang, 'LAT': yrang}\n",
+    "coordsBOX = {'LON': xrange, 'LAT': yrange}\n",
     "    \n",
     "# use the SDToolBox function to create input data\n",
-    "Input_DataBOX = ind.InputData(\n",
+    "Input_DataBOX= ind.InputData(\n",
     "    input_coordinates=coordsBOX, \n",
-    "    input_variables=['msl'], \n",
+    "    input_variables=varBOX, \n",
     "    input_scenarios=['era5'],\n",
     "    input_years=timeWAMy, \n",
     "    is_gridded = True)\n",
@@ -406,7 +420,16 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['msl']\n",
+      "Extracting variable: msl_p, year 1986.\n"
+     ]
+    }
+   ],
    "source": [
     "# select a spatial range (box) for which data is to be extracted\n",
     "steplon = 0.5 # degrees\n",
@@ -421,10 +444,9 @@
     "coordsBOX = {'LON': xrang, 'LAT': yrang}\n",
     "    \n",
     "# use the SDToolBox function to create input data\n",
-    "del(Input_DataBOX) # to clear up the previous one that was defined\n",
     "Input_DataBOX = ind.InputData(\n",
     "    input_coordinates=coordsBOX, \n",
-    "    input_variables=['msl_p'], \n",
+    "    input_variables=['msl'], \n",
     "    input_scenarios=['era5'],\n",
     "    input_years=timeWAMy, \n",
     "    is_gridded = True)\n",
Index: trunk/tests/testing_Etienne/SD_ToolBox_Testing.ipynb
===================================================================
diff -u -r115 -r117
--- trunk/tests/testing_Etienne/SD_ToolBox_Testing.ipynb	(.../SD_ToolBox_Testing.ipynb)	(revision 115)
+++ trunk/tests/testing_Etienne/SD_ToolBox_Testing.ipynb	(.../SD_ToolBox_Testing.ipynb)	(revision 117)
@@ -140,6 +140,26 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "# get the coordinates of the WAM locations\n",
+    "lonWAM = DS.variables['lon'][:] # list with longitude positions\n",
+    "latWAM = DS.variables['lat'][:] # list with latitude positions \n",
+    "\n",
+    "coordsWAM = {'LON': [], 'LAT': []}\n",
+    "for i, j in zip(lonWAM, latWAM):\n",
+    "    coordsWAM['LON'].append(i)\n",
+    "    coordsWAM['LAT'].append(j)\n",
+    "\n",
+    "# set other data variables    \n",
+    "varWAM = [v.lower() for v in variables[5:]] # list with the five wave parameters -> it automatically only uses swh, pp1d, mwd\n",
+    "timeWAMy = [1986] # 1987 to 2018"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -149,26 +169,13 @@
       "Extracting variable: Tp, year 1986.\n",
       "Extracting variable: MWD, year 1986.\n",
       "Writing C:\\checkouts\\trunk\\tests\\testing_Etienne\\datasets\\WAM_ERA5_WAVE.nc\n",
-      "writing variable pp1d\n",
+      "writing variable mwd\n",
       "writing variable swh\n",
-      "writing variable mwd\n"
+      "writing variable pp1d\n"
      ]
     }
    ],
    "source": [
-    "# get the coordinates of the WAM locations\n",
-    "lonWAM = DS.variables['lon'][:] # list with longitude positions\n",
-    "latWAM = DS.variables['lat'][:] # list with latitude positions \n",
-    "\n",
-    "coordsWAM = {'LON': [], 'LAT': []}\n",
-    "for i, j in zip(lonWAM, latWAM):\n",
-    "    coordsWAM['LON'].append(i)\n",
-    "    coordsWAM['LAT'].append(j)\n",
-    "\n",
-    "# set other data variables    \n",
-    "varWAM = [v.lower() for v in variables[5:]] # list with the five wave parameters -> ind automatically only uses swh, pp1d, mwd\n",
-    "timeWAMy = [1986] # 1987 to 2018\n",
-    "\n",
     "# use the SDToolBox function to create input data\n",
     "Input_DataWAM = ind.InputData(\n",
     "    input_coordinates=coordsWAM,\n",
@@ -189,7 +196,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -244,7 +251,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -266,7 +273,7 @@
     "folder2 = r'C:\\checkouts\\trunk\\tests\\testing_Etienne\\datasets'\n",
     "\n",
     "# open the data in this script to get the info\n",
-    "DS_WAM_ERA5 = Dataset(os.path.join(folder2,'WAM_ERA5.nc'))\n",
+    "DS_WAM_ERA5 = Dataset(os.path.join(folder2,'WAM_ERA5_WAVE.nc'))\n",
     "\n",
     "# get the relevant data from the netcdf files\n",
     "time_WAM_ERA5 = list(DS_WAM_ERA5.variables['time'])\n",
@@ -326,49 +333,56 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['msl']\n",
-      "Extracting variable: Hs, year 1986.\n"
+      "['swh', 'pp1d', 'mwd']\n",
+      "Extracting variable: Hs, year 1986.\n",
+      "Extracting variable: Tp, year 1986.\n",
+      "Extracting variable: MWD, year 1986.\n",
+      "Writing C:\\checkouts\\trunk\\tests\\testing_Etienne\\datasets\\BOX_ERA5_WAVE.nc\n",
+      "writing variable swh\n"
      ]
     },
     {
-     "ename": "KeyError",
-     "evalue": "'swh'",
+     "ename": "ValueError",
+     "evalue": "shape mismatch: objects cannot be broadcast to a single shape",
      "output_type": "error",
      "traceback": [
       "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
-      "\u001b[1;32m<ipython-input-91-46658c84726f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     21\u001b[0m \u001b[1;31m# use the SDToolBox function to extract data\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     22\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mInput_DataBOX\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minput_variables\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 23\u001b[1;33m \u001b[0mExtract_Data_ERA5BOX\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mexd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mExtractData\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_era_5\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdir_ERA5\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mInput_DataBOX\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     24\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     25\u001b[0m \u001b[1;31m# generate output data for waves\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mC:\\checkouts\\trunk\\SDToolBox\\extract_data.py\u001b[0m in \u001b[0;36mget_era_5\u001b[1;34m(directory_path, input_data)\u001b[0m\n\u001b[0;32m     55\u001b[0m         return data_extractor.extract_subset(\n\u001b[0;32m     56\u001b[0m                 \u001b[0mdirectory_path\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdirectory_path\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 57\u001b[1;33m                 \u001b[0minput_data\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0minput_data\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     58\u001b[0m             )\n\u001b[0;32m     59\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mC:\\checkouts\\trunk\\SDToolBox\\extract_data.py\u001b[0m in \u001b[0;36mextract_subset\u001b[1;34m(self, directory_path, input_data)\u001b[0m\n\u001b[0;32m    245\u001b[0m                         \u001b[0mvar_name\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mvariable_key\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    246\u001b[0m                         value=self.__get_variable_subset(\n\u001b[1;32m--> 247\u001b[1;33m                             \u001b[0moutput_data\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_from_var_dict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvariable_key\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    248\u001b[0m                             \u001b[0minput_data\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    249\u001b[0m                             \u001b[0minput_dataset\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mC:\\checkouts\\trunk\\SDToolBox\\output_data.py\u001b[0m in \u001b[0;36mget_from_var_dict\u001b[1;34m(self, var_name)\u001b[0m\n\u001b[0;32m    187\u001b[0m             \u001b[0mAny\u001b[0m \u001b[1;33m-\u001b[0m\u001b[1;33m-\u001b[0m \u001b[0mValue\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mrequested\u001b[0m \u001b[0mvariable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    188\u001b[0m         \"\"\"\n\u001b[1;32m--> 189\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__data_dict\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvar_val_key\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mvar_name\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    190\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    191\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mset_in_var_dict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvar_name\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mAny\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mKeyError\u001b[0m: 'swh'"
+      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-6-016787fd068e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     29\u001b[0m     \u001b[0mdir_path\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34mr'C:\\checkouts\\trunk\\tests\\testing_Etienne\\datasets'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     30\u001b[0m     \u001b[0mbase_name\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'BOX'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 31\u001b[1;33m     dataset_code='ERA5_WAVE')\n\u001b[0m",
+      "\u001b[1;32mC:\\checkouts\\trunk\\SDToolBox\\output_data.py\u001b[0m in \u001b[0;36mgenerate_netcdf\u001b[1;34m(self, dir_path, base_name, dataset_code)\u001b[0m\n\u001b[0;32m    170\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__set_geo_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnetcdf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    171\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__set_dataset_variables\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnetcdf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdataset_code\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 172\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__set_variables_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnetcdf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdataset_code\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    173\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__set_global_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnetcdf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdataset_code\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    174\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mC:\\checkouts\\trunk\\SDToolBox\\output_data.py\u001b[0m in \u001b[0;36m__set_variables_data\u001b[1;34m(self, netcdf, dataset_code)\u001b[0m\n\u001b[0;32m    597\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mis_gridded\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    598\u001b[0m                 \u001b[0mnetcdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvariables\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mvar_name\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m\\\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 599\u001b[1;33m                     \u001b[0mvariables\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mvar_name\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    600\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    601\u001b[0m                 \u001b[1;31m# When non-gridded we need to transpose the dimensions.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mnetCDF4\\_netCDF4.pyx\u001b[0m in \u001b[0;36mnetCDF4._netCDF4.Variable.__setitem__\u001b[1;34m()\u001b[0m\n",
+      "\u001b[1;32m~\\anaconda3\\envs\\SDToolBox_env\\lib\\site-packages\\netCDF4\\utils.py\u001b[0m in \u001b[0;36m_StartCountStride\u001b[1;34m(elem, shape, dimensions, grp, datashape, put, use_get_vars)\u001b[0m\n\u001b[0;32m    363\u001b[0m         \u001b[0mfullslice\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    364\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mfullslice\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mdatashape\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mput\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mhasunlim\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 365\u001b[1;33m         \u001b[0mdatashape\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mbroadcasted_shape\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdatashape\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    366\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    367\u001b[0m     \u001b[1;31m# pad datashape with zeros for dimensions not being sliced (issue #906)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32m~\\anaconda3\\envs\\SDToolBox_env\\lib\\site-packages\\netCDF4\\utils.py\u001b[0m in \u001b[0;36mbroadcasted_shape\u001b[1;34m(shp1, shp2)\u001b[0m\n\u001b[0;32m    971\u001b[0m     \u001b[0ma\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mas_strided\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mshape\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mshp1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstrides\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mshp1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    972\u001b[0m     \u001b[0mb\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mas_strided\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mshape\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mshp2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstrides\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mshp2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 973\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbroadcast\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mb\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[1;31mValueError\u001b[0m: shape mismatch: objects cannot be broadcast to a single shape"
      ]
     }
    ],
    "source": [
     "# select a spatial range (box) for which data is to be extracted\n",
-    "steplon = 0.5 # degrees\n",
-    "lonl = -5 # left lon value\n",
-    "lonr = 11 # right lon value\n",
-    "steplat = 0.5\n",
-    "latl = 50 # lower lat value\n",
-    "latu = 62 # upper lat value\n",
-    "xrang = np.arange(lonl, lonr+steplon, steplon).tolist() \n",
-    "yrang = np.arange(latl, latu+steplat, steplat).tolist() \n",
+    "steplon = 1 # degrees\n",
+    "lonl = 3 # left lon value\n",
+    "lonr = 4 # right lon value\n",
+    "steplat = 1 # degrees\n",
+    "latl = 53 # lower lat value\n",
+    "latu = 54 # upper lat value\n",
+    "xrange = np.arange(lonl, lonr+steplon, steplon).tolist() \n",
+    "yrange = np.arange(latl, latu+steplat, steplat).tolist() \n",
+    "varBOX = ['swh', 'pp1d', 'mwd']\n",
     "\n",
-    "coordsBOX = {'LON': xrang, 'LAT': yrang}\n",
+    "coordsBOX = {'LON': xrange, 'LAT': yrange}\n",
     "    \n",
     "# use the SDToolBox function to create input data\n",
-    "Input_DataBOX = ind.InputData(\n",
+    "Input_DataBOX= ind.InputData(\n",
     "    input_coordinates=coordsBOX, \n",
-    "    input_variables=['msl'], \n",
+    "    input_variables=varBOX, \n",
     "    input_scenarios=['era5'],\n",
     "    input_years=timeWAMy, \n",
     "    is_gridded = True)\n",
@@ -406,7 +420,16 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['msl']\n",
+      "Extracting variable: msl_p, year 1986.\n"
+     ]
+    }
+   ],
    "source": [
     "# select a spatial range (box) for which data is to be extracted\n",
     "steplon = 0.5 # degrees\n",
@@ -421,10 +444,9 @@
     "coordsBOX = {'LON': xrang, 'LAT': yrang}\n",
     "    \n",
     "# use the SDToolBox function to create input data\n",
-    "del(Input_DataBOX) # to clear up the previous one that was defined\n",
     "Input_DataBOX = ind.InputData(\n",
     "    input_coordinates=coordsBOX, \n",
-    "    input_variables=['msl_p'], \n",
+    "    input_variables=['msl'], \n",
     "    input_scenarios=['era5'],\n",
     "    input_years=timeWAMy, \n",
     "    is_gridded = True)\n",