diff --git a/notebooks/01_exploration.ipynb b/notebooks/01_exploration.ipynb
index 0fbcb2e..a4ee9d2 100644
--- a/notebooks/01_exploration.ipynb
+++ b/notebooks/01_exploration.ipynb
@@ -10,11 +10,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 144,
+   "execution_count": 1,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2018-11-09T01:48:38.686778Z",
-     "start_time": "2018-11-09T01:48:31.350515Z"
+     "end_time": "2018-11-11T22:32:56.827980Z",
+     "start_time": "2018-11-11T22:32:56.532764Z"
     }
    },
    "outputs": [],
@@ -29,11 +29,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 145,
+   "execution_count": 2,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2018-11-09T01:48:38.721265Z",
-     "start_time": "2018-11-09T01:48:38.687781Z"
+     "end_time": "2018-11-11T22:33:22.254342Z",
+     "start_time": "2018-11-11T22:32:56.828981Z"
     },
     "scrolled": true
    },
@@ -55,11 +55,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 146,
+   "execution_count": 13,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2018-11-09T01:48:55.758881Z",
-     "start_time": "2018-11-09T01:48:38.723271Z"
+     "end_time": "2018-11-12T06:21:34.344883Z",
+     "start_time": "2018-11-12T06:21:23.543798Z"
     },
     "pixiedust": {
      "displayParams": {}
@@ -70,7 +70,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\z5189959\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\numpy\\lib\\arraysetops.py:518: FutureWarning:\n",
+      "C:\\Users\\z5189959\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\numpy\\lib\\arraysetops.py:472: FutureWarning:\n",
       "\n",
       "elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
       "\n"
@@ -82,23 +82,25 @@
     "df_waves = pd.read_csv(os.path.join(data_folder, 'waves.csv'), index_col=[0,1])\n",
     "df_tides = pd.read_csv(os.path.join(data_folder, 'tides.csv'), index_col=[0,1])\n",
     "df_profiles = pd.read_csv(os.path.join(data_folder, 'profiles.csv'), index_col=[0,1,2])\n",
-    "df_sites = pd.read_csv(os.path.join(data_folder, 'sites.csv'),index_col=[0])\n"
+    "df_sites = pd.read_csv(os.path.join(data_folder, 'sites.csv'),index_col=[0])\n",
+    "df_profile_features = pd.read_csv(os.path.join(data_folder, 'profile_features.csv'),index_col=[0])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 147,
+   "execution_count": 18,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2018-11-09T01:48:56.438469Z",
-     "start_time": "2018-11-09T01:48:55.759856Z"
-    }
+     "end_time": "2018-11-12T06:29:07.451994Z",
+     "start_time": "2018-11-12T06:29:06.845896Z"
+    },
+    "scrolled": false
    },
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "89b213f09e874adaa67419df3a32499a",
+       "model_id": "d5226c9774bd4353aac2cc8f5732b182",
        "version_major": 2,
        "version_minor": 0
       },
@@ -121,12 +123,26 @@
        "VBox(children=(HBox(children=(Dropdown(description='site_id:   ', index=943, options=('AVOCAn0001', 'AVOCAn0002', 'AVOCAn0003', 'AVOCAn0004', 'AVOCAn0005', 'AVOCAn0006', 'AVOCAn0007', 'AVOCAn0008', 'AVOCAn0009', 'AVOCAs0001', 'AVOCAs0002', 'AVOCAs0003', 'AVOCAs0004', 'AVOCAs0005', 'AVOCAs0006', 'AVOCAs0007', 'AVOCAs0008', 'BILG0001', 'BILG0002', 'BILG0003', 'BILG0004', 'BILG0005', 'BLUEYS0001', 'BLUEYS0002', 'BLUEYS0003', 'BLUEYS0004', 'BLUEYS0005', 'BLUEYS0006', 'BOAT0001', 'BOAT0002', 'BOAT0003', 'BOAT0004', 'BOAT0005', 'BOOM0001', 'BOOM0002', 'BOOM0003', 'BOOM0004', 'BOOM0005', 'BOOM0006', 'BOOM0007', 'BOOM0008', 'BOOM0009', 'BOOM0010', 'BOOM0011', 'BOOM0012', 'BOOM0013', 'BOOM0014', 'CATHIE0001', 'CATHIE0002', 'CATHIE0003', 'CATHIE0004', 'CATHIE0005', 'CATHIE0006', 'CATHIE0007', 'CATHIE0008', 'CATHIE0009', 'CATHIE0010', 'CATHIE0011', 'CATHIE0012', 'CATHIE0013', 'CATHIE0014', 'CATHIE0015', 'CATHIE0016', 'CATHIE0017', 'CATHIE0018', 'CATHIE0019', 'CATHIE0020', 'CATHIE0021', 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'MONA0008', 'MONA0009', 'MONA0010', 'MONA0011', 'MONA0012', 'MONA0013', 'MONA0014', 'MONA0015', 'MONA0016', 'MONA0017', 'MONA0018', 'MONA0019', 'MONA0020', 'MONA0021', 'NAMB0001', 'NAMB0002', 'NAMB0003', 'NAMB0004', 'NAMB0005', 'NAMB0006', 'NAMB0007', 'NAMB0008', 'NAMB0009', 'NAMB0010', 'NAMB0011', 'NAMB0012', 'NAMB0013', 'NAMB0014', 'NAMB0015', 'NAMB0016', 'NAMB0017', 'NAMB0018', 'NAMB0019', 'NAMB0020', 'NAMB0021', 'NAMB0022', 'NAMB0023', 'NAMB0024', 'NAMB0025', 'NAMB0026', 'NAMB0027', 'NAMB0028', 'NAMB0029', 'NAMB0030', 'NAMB0031', 'NAMB0032', 'NAMB0033', 'NAMB0034', 'NAMB0035', 'NAMB0036', 'NAMB0037', 'NAMB0038', 'NAMB0039', 'NAMB0040', 'NAMB0041', 'NAMB0042', 'NAMB0043', 'NAMB0044', 'NAMB0045', 'NAMB0046', 'NAMB0047', 'NAMB0048', 'NAMB0049', 'NAMB0050', 'NAMB0051', 'NAMB0052', 'NAMB0053', 'NAMB0054', 'NAMB0055', 'NAMB0056', 'NAMB0057', 'NAMB0058', 'NAMB0059', 'NAMB0060', 'NAMB0061', 'NAMB0062', 'NAMB0063', 'NAMB0064', 'NAMB0065', 'NAMB0066', 'NAMB0067', 'NAMB0068', 'NAMB0069', 'NAMB0070', 'NAMB0071', 'NAMB0072', 'NAMB0073', 'NARRA0001', 'NARRA0002', 'NARRA0003', 'NARRA0004', 'NARRA0005', 'NARRA0006', 'NARRA0007', 'NARRA0008', 'NARRA0009', 'NARRA0010', 'NARRA0011', 'NARRA0012', 'NARRA0013', 'NARRA0014', 'NARRA0015', 'NARRA0016', 'NARRA0017', 'NARRA0018', 'NARRA0019', 'NARRA0020', 'NARRA0021', 'NARRA0022', 'NARRA0023', 'NARRA0024', 'NARRA0025', 'NARRA0026', 'NARRA0027', 'NARRA0028', 'NARRA0029', 'NARRA0030', 'NARRA0031', 'NARRA0032', 'NARRA0033', 'NARRA0034', 'NARRA0035', 'NARRA0036', 'NINEMn0001', 'NINEMn0002', 'NINEMn0003', 'NINEMn0004', 'NINEMn0005', 'NINEMn0006', 'NINEMn0007', 'NINEMn0008', 'NINEMn0009', 'NINEMn0010', 'NINEMn0011', 'NINEMn0012', 'NINEMn0013', 'NINEMn0014', 'NINEMn0015', 'NINEMn0016', 'NINEMn0017', 'NINEMn0018', 'NINEMn0019', 'NINEMn0020', 'NINEMn0021', 'NINEMn0022', 'NINEMn0023', 'NINEMn0024', 'NINEMn0025', 'NINEMn0026', 'NINEMn0027', 'NINEMn0028', 'NINEMn0029', 'NINEMn0030', 'NINEMn0031', 'NINEMn0032', 'NINEMn0033', 'NINEMn0034', 'NINEMn0035', 'NINEMn0036', 'NINEMn0037', 'NINEMn0038', 'NINEMn0039', 'NINEMn0040', 'NINEMn0041', 'NINEMn0042', 'NINEMn0043', 'NINEMn0044', 'NINEMn0045', 'NINEMn0046', 'NINEMn0047', 'NINEMn0048', 'NINEMn0049', 'NINEMn0050', 'NINEMn0051', 'NINEMn0052', 'NINEMn0053', 'NINEMn0054', 'NINEMs0001', 'NINEMs0002', 'NINEMs0003', 'NINEMs0004', 'NINEMs0005', 'NINEMs0006', 'NINEMs0007', 'NINEMs0008', 'NINEMs0009', 'NINEMs0010', 'NINEMs0011', 'NINEMs0012', 'NINEMs0013', 'NINEMs0014', 'NINEMs0015', 'NINEMs0016', 'NINEMs0017', 'NINEMs0018', 'NINEMs0019', 'NINEMs0020', 'NINEMs0021', 'NINEMs0022', 'NINEMs0023', 'NINEMs0024', 'NINEMs0025', 'NINEMs0026', 'NINEMs0027', 'NINEMs0028', 'NINEMs0029', 'NINEMs0030', 'NINEMs0031', 'NINEMs0032', 'NINEMs0033', 'NINEMs0034', 'NINEMs0035', 'NINEMs0036', 'NINEMs0037', 'NINEMs0038', 'NINEMs0039', 'NINEMs0040', 'NINEMs0041', 'NINEMs0042', 'NINEMs0043', 'NINEMs0044', 'NINEMs0045', 'NINEMs0046', 'NINEMs0047', 'NINEMs0048', 'NINEMs0049', 'NINEMs0050', 'NINEMs0051', 'NINEMs0052', 'NINEMs0053', 'NINEMs0054', 'NINEMs0055', 'NINEMs0056', 'NINEMs0057', 'NINEMs0058', 'NINEMs0059', 'NINEMs0060', 'NSHORE_n0001', 'NSHORE_n0002', 'NSHORE_n0003', 'NSHORE_n0004', 'NSHORE_n0005', 'NSHORE_n0006', 'NSHORE_n0007', 'NSHORE_n0008', 'NSHORE_n0009', 'NSHORE_n0010', 'NSHORE_n0011', 'NSHORE_n0012', 'NSHORE_n0013', 'NSHORE_n0014', 'NSHORE_n0015', 'NSHORE_n0016', 'NSHORE_n0017', 'NSHORE_n0018', 'NSHORE_n0019', 'NSHORE_n0020', 'NSHORE_n0021', 'NSHORE_n0022', 'NSHORE_n0023', 'NSHORE_n0024', 'NSHORE_n0025', 'NSHORE_n0026', 'NSHORE_n0027', 'NSHORE_n0028', 'NSHORE_n0029', 'NSHORE_n0030', 'NSHORE_n0031', 'NSHORE_n0032', 'NSHORE_n0033', 'NSHORE_n0034', 'NSHORE_n0035', 'NSHORE_n0036', 'NSHORE_n0037', 'NSHORE_n0038', 'NSHORE_n0039', 'NSHORE_n0040', 'NSHORE_n0041', 'NSHORE_n0042', 'NSHORE_n0043', 'NSHORE_n0044', 'NSHORE_n0045', 'NSHORE_n0046', 'NSHORE_n0047', 'NSHORE_n0048', 'NSHORE_n0049', 'NSHORE_n0050', 'NSHORE_n0051', 'NSHORE_n0052', 'NSHORE_n0053', 'NSHORE_n0054', 'NSHORE_n0055', 'NSHORE_n0056', 'NSHORE_n0057', 'NSHORE_n0058', 'NSHORE_n0059', 'NSHORE_n0060', 'NSHORE_n0061', 'NSHORE_n0062', 'NSHORE_n0063', 'NSHORE_n0064', 'NSHORE_n0065', 'NSHORE_n0066', 'NSHORE_n0067', 'NSHORE_n0068', 'NSHORE_n0069', 'NSHORE_n0070', 'NSHORE_n0071', 'NSHORE_n0072', 'NSHORE_n0073', 'NSHORE_n0074', 'NSHORE_n0075', 'NSHORE_n0076', 'NSHORE_n0077', 'NSHORE_n0078', 'NSHORE_n0079', 'NSHORE_n0080', 'NSHORE_n0081', 'NSHORE_n0082', 'NSHORE_s0001', 'NSHORE_s0002', 'NSHORE_s0003', 'NSHORE_s0004', 'NSHORE_s0005', 'NSHORE_s0006', 'NSHORE_s0007', 'NSHORE_s0008', 'NSHORE_s0009', 'NSHORE_s0010', 'NSHORE_s0011', 'NSHORE_s0012', 'NSHORE_s0013', 'NSHORE_s0014', 'NSHORE_s0015', 'NSHORE_s0016', 'NSHORE_s0017', 'NSHORE_s0018', 'NSHORE_s0019', 'NSHORE_s0020', 'NSHORE_s0021', 'NSHORE_s0022', 'NSHORE_s0023', 'NSHORE_s0024', 'NSHORE_s0025', 'NSHORE_s0026', 'NSHORE_s0027', 'NSHORE_s0028', 'NSHORE_s0029', 'NSHORE_s0030', 'NSHORE_s0031', 'NSHORE_s0032', 'NSHORE_s0033', 'NSHORE_s0034', 'NSHORE_s0035', 'NSHORE_s0036', 'NSHORE_s0037', 'NSHORE_s0038', 'NSHORE_s0039', 'NSHORE_s0040', 'NSHORE_s0041', 'NSHORE_s0042', 'NSHORE_s0043', 'NSHORE_s0044', 'OLDBAR0001', 'OLDBAR0002', 'OLDBAR0003', 'OLDBAR0004', 'OLDBAR0005', 'OLDBAR0006', 'OLDBAR0007', 'OLDBAR0008', 'OLDBAR0009', 'OLDBAR0010', 'OLDBAR0011', 'OLDBAR0012', 'OLDBAR0013', 'OLDBAR0014', 'OLDBAR0015', 'OLDBAR0016', 'OLDBAR0017', 'OLDBAR0018', 'OLDBAR0019', 'OLDBAR0020', 'OLDBAR0021', 'OLDBAR0022', 'OLDBAR0023', 'OLDBAR0024', 'OLDBAR0025', 'OLDBAR0026', 'OLDBAR0027', 'OLDBAR0028', 'OLDBAR0029', 'OLDBAR0030', 'OLDBAR0031', 'OLDBAR0032', 'OLDBAR0033', 'OLDBAR0034', 'OLDBAR0035', 'OLDBAR0036', 'ONEMILE0001', 'ONEMILE0002', 'ONEMILE0003', 'ONEMILE0004', 'ONEMILE0005', 'ONEMILE0006', 'ONEMILE0007', 'ONEMILE0008', 'ONEMILE0009', 'ONEMILE0010', 'ONEMILE0011', 'ONEMILE0012', 'ONEMILE0013', 'PEARLn0001', 'PEARLn0002', 'PEARLn0003', 'PEARLn0004', 'PEARLn0005', 'PEARLs0001', 'PEARLs0002', 'PEARLs0003', 'PEARLs0004', 'PEARLs0005', 'SCOT0001', 'SCOT0002', 'SCOT0003', 'SCOT0004', 'SCOT0005', 'SCOT0006', 'SCOT0007', 'SCOT0008', 'SCOT0009', 'SCOT0010', 'SCOT0011', 'SCOT0012', 'STOCNn0001', 'STOCNn0002', 'STOCNn0003', 'STOCNn0004', 'STOCNn0005', 'STOCNn0006', 'STOCNn0007', 'STOCNn0008', 'STOCNn0009', 'STOCNn0010', 'STOCNn0011', 'STOCNn0012', 'STOCNn0013', 'STOCNn0014', 'STOCNn0015', 'STOCNn0016', 'STOCNn0017', 'STOCNn0018', 'STOCNn0019', 'STOCNn0020', 'STOCNn0021', 'STOCNn0022', 'STOCNn0023', 'STOCNn0024', 'STOCNn0025', 'STOCNn0026', 'STOCNn0027', 'STOCNn0028', 'STOCNn0029', 'STOCNn0030', 'STOCNn0031', 'STOCNn0032', 'STOCNn0033', 'STOCNn0034', 'STOCNn0035', 'STOCNn0036', 'STOCNn0037', 'STOCNn0038', 'STOCNn0039', 'STOCNn0040', 'STOCNn0041', 'STOCNn0042', 'STOCNn0043', 'STOCNn0044', 'STOCNn0045', 'STOCNn0046', 'STOCNn0047', 'STOCNn0048', 'STOCNn0049', 'STOCNn0050', 'STOCNn0051', 'STOCNn0052', 'STOCNn0053', 'STOCNn0054', 'STOCNn0055', 'STOCNn0056', 'STOCNn0057', 'STOCNn0058', 'STOCNn0059', 'STOCNn0060', 'STOCNn0061', 'STOCNn0062', 'STOCNn0063', 'STOCNn0064', 'STOCNn0065', 'STOCNs0001', 'STOCNs0002', 'STOCNs0003', 'STOCNs0004', 'STOCNs0005', 'STOCNs0006', 'STOCNs0007', 'STOCNs0008', 'STOCNs0009', 'STOCNs0010', 'STOCNs0011', 'STOCNs0012', 'STOCNs0013', 'STOCNs0014', 'STOCNs0015', 'STOCNs0016', 'STOCNs0017', 'STOCNs0018', 'STOCNs0019', 'STOCNs0020', 'STOCNs0021', 'STOCNs0022', 'STOCNs0023', 'STOCNs0024', 'STOCNs0025', 'STOCNs0026', 'STOCNs0027', 'STOCNs0028', 'STOCNs0029', 'STOCNs0030', 'STOCNs0031', 'STOCNs0032', 'STOCNs0033', 'STOCNs0034', 'STOCNs0035', 'STOCNs0036', 'STOCNs0037', 'STOCNs0038', 'STOCNs0039', 'STOCNs0040', 'STOCNs0041', 'STOCNs0042', 'STOCNs0043', 'STOCNs0044', 'STOCNs0045', 'STOCNs0046', 'STOCNs0047', 'STOCNs0048', 'STOCNs0049', 'STOCNs0050', 'STOCNs0051', 'STOCNs0052', 'STOCNs0053', 'STOCNs0054', 'STOCNs0055', 'STOCNs0056', 'STOCNs0057', 'STOCNs0058', 'STOCNs0059', 'STOCNs0060', 'STOCNs0061', 'STOCNs0062', 'STOCNs0063', 'STOCNs0064', 'STOCNs0065', 'STOCNs0066', 'STOCNs0067', 'STOCNs0068', 'STOCNs0069', 'STOCNs0070', 'STOCNs0071', 'STOCNs0072', 'STOCNs0073', 'STOCNs0074', 'STOCNs0075', 'STOCNs0076', 'STOCNs0077', 'STOCNs0078', 'STOCNs0079', 'STOCNs0080', 'STOCNs0081', 'STOCNs0082', 'STOCNs0083', 'STOCNs0084', 'STOCNs0085', 'STOCNs0086', 'STOCNs0087', 'STOCNs0088', 'STOCNs0089', 'STOCNs0090', 'STOCNs0091', 'STOCNs0092', 'STOCNs0093', 'STOCNs0094', 'STOCNs0095', 'STOCNs0096', 'STOCNs0097', 'STOCNs0098', 'STOCNs0099', 'STOCNs0100', 'STOCNs0101', 'STOCNs0102', 'STOCNs0103', 'STOCNs0104', 'STOCNs0105', 'STOCNs0106', 'STOCNs0107', 'STOCNs0108', 'STOCNs0109', 'STOCNs0110', 'STOCNs0111', 'STOCNs0112', 'STOCNs0113', 'STOCNs0114', 'STOCNs0115', 'STOCNs0116', 'STOCNs0117', 'STOCNs0118', 'STOCNs0119', 'STOCNs0120', 'STOCNs0121', 'STOCNs0122', 'STOCNs0123', 'STOCNs0124', 'STOCNs0125', 'STOCNs0126', 'STOCNs0127', 'STOCNs0128', 'STOCNs0129', 'STOCNs0130', 'STOCNs0131', 'STOCNs0132', 'STOCNs0133', 'STOCNs0134', 'STOCNs0135', 'STOCNs0136', 'STOCNs0137', 'STOCNs0138', 'STOCNs0139', 'STOCNs0140', 'STOCNs0141', 'STOCNs0142', 'STOCNs0143', 'STOCNs0144', 'STOCNs0145', 'STOCNs0146', 'STOCNs0147', 'STOCNs0148', 'STOCNs0149', 'STOCNs0150', 'STOCNs0151', 'STOCNs0152', 'STOCNs0153', 'STOCNs0154', 'STOCNs0155', 'STOCNs0156', 'STOCNs0157', 'STOCNs0158', 'STOCNs0159', 'STOCNs0160', 'STOCNs0161', 'STOCNs0162', 'STOCNs0163', 'STOCNs0164', 'STOCNs0165', 'STOCNs0166', 'STOCNs0167', 'STOCNs0168', 'STOCNs0169', 'STOCNs0170', 'STOCNs0171', 'STOCNs0172', 'STOCNs0173', 'STOCNs0174', 'STOCNs0175', 'STOCNs0176', 'STOCNs0177', 'STOCNs0178', 'STOCNs0179', 'STOCNs0180', 'STOCNs0181', 'STOCNs0182', 'STOCNs0183', 'STOCNs0184', 'STOCNs0185', 'STOCNs0186', 'STOCNs0187', 'STOCNs0188', 'STOCNs0189', 'STOCNs0190', 'STOCNs0191', 'STOCNs0192', 'STOCNs0193', 'STOCNs0194', 'STOCNs0195', 'STOCNs0196', 'STOCNs0197', 'STOCNs0198', 'STOCNs0199', 'STOCNs0200', 'STOCNs0201', 'STOCNs0202', 'STOCNs0203', 'STOCNs0204', 'STOCNs0205', 'STOCNs0206', 'STOCNs0207', 'STOCNs0208', 'STOCNs0209', 'STOCS0001', 'STOCS0002', 'STOCS0003', 'STOCS0004', 'STOCS0005', 'STOCS0006', 'STOCS0007', 'STOCS0008', 'STOCS0009', 'STOCS0010', 'STOCS0011', 'STOCS0012', 'STOCS0013', 'STOCS0014', 'STOCS0015', 'STOCS0016', 'STOCS0017', 'STOCS0018', 'STOCS0019', 'STOCS0020', 'STOCS0021', 'STOCS0022', 'STOCS0023', 'STOCS0024', 'STOCS0025', 'STOCS0026', 'STOCS0027', 'STOCS0028', 'STOCS0029', 'STOCS0030', 'STOCS0031', 'STOCS0032', 'STOCS0033', 'STOCS0034', 'STOCS0035', 'STOCS0036', 'STOCS0037', 'STOCS0038', 'STOCS0039', 'STOCS0040', 'STOCS0041', 'STOCS0042', 'STOCS0043', 'STOCS0044', 'STOCS0045', 'STOCS0046', 'STUART0001', 'STUART0002', 'STUART0003', 'STUART0004', 'STUART0005', 'STUART0006', 'STUART0007', 'STUART0008', 'STUART0009', 'STUART0010', 'STUART0011', 'STUART0012', 'STUART0013', 'STUART0014', 'STUART0015', 'STUART0016', 'STUART0017', 'STUART0018', 'STUART0019', 'STUART0020', 'STUART0021', 'STUART0022', 'STUART0023', 'STUART0024', 'STUART0025', 'STUART0026', 'STUART0027', 'STUART0028', 'STUART0029', 'STUART0030', 'STUART0031', 'STUART0032', 'STUART0033', 'STUART0034', 'STUART0035', 'STUART0036', 'STUART0037', 'STUART0038', 'STUART0039', 'STUART0040', 'STUART0041', 'STUART0042', 'STUART0043', 'STUART0044', 'STUART0045', 'STUART0046', 'STUART0047', 'STUART0048', 'STUART0049', 'STUART0050', 'STUART0051', 'STUART0052', 'STUART0053', 'STUART0054', 'STUART0055', 'STUART0056', 'STUART0057', 'STUART0058', 'STUART0059', 'STUART0060', 'STUART0061', 'STUART0062', 'STUART0063', 'STUART0064', 'STUART0065', 'STUART0066', 'STUART0067', 'STUART0068', 'STUART0069', 'STUART0070', 'STUART0071', 'STUART0072', 'STUART0073', 'STUART0074', 'STUART0075', 'STUART0076', 'STUART0077', 'STUART0078', 'STUART0079', 'STUART0080', 'STUART0081', 'STUART0082', 'STUART0083', 'STUART0084', 'STUART0085', 'STUART0086', 'STUART0087', 'STUART0088', 'STUART0089', 'SWRO0001', 'SWRO0002', 'SWRO0003', 'SWRO0004', 'SWRO0005', 'SWRO0006', 'SWRO0007', 'SWRO0008', 'SWRO0009', 'SWRO0010', 'SWRO0011', 'SWRO0012', 'SWRO0013', 'SWRO0014', 'SWRO0015', 'SWRO0016', 'SWRO0017', 'SWRO0018', 'SWRO0019', 'SWRO0020', 'SWRO0021', 'SWRO0022', 'SWRO0023', 'SWRO0024', 'SWRO0025', 'SWRO0026', 'TREACH0001', 'TREACH0002', 'TREACH0003', 'TREACH0004', 'TREACH0005', 'TREACH0006', 'TREACH0007', 'TREACH0008', 'TREACH0009', 'TREACH0010', 'TREACH0011', 'TREACH0012', 'TREACH0013', 'TREACH0014', 'TREACH0015', 'TREACH0016', 'WAMBE0001', 'WAMBE0002', 'WAMBE0003', 'WAMBE0004', 'WAMBE0005', 'WAMBE0006', 'WAMBE0007', 'WAMBE0008', 'WAMBE0009', 'WAMBE0010', 'WAMBE0011', 'WAMBE0012', 'WAMBE0013', 'WAMBE0014', 'WAMBE0015', 'WAMBE0016', 'WAMBE0017', 'WAMBE0018', 'WAMBE0019', 'WAMBE0020', 'WAMBE0021', 'WAMBE0022', 'WAMBE0023', 'WAMBE0024', 'WAMBE0025', 'WAMBE0026', 'WAMBE0027'), value='NARRA0001'),)), HBox(children=(FigureWidget({\n",
        "    'data': [{'name': 'Pre Storm Profile',\n",
        "              'type': 'scatter',\n",
-       "              'uid': '5f83eb47-e017-4192-a508-54a2f91a379c',\n",
+       "              'uid': 'a4b395ae-dd30-4b11-8943-b57902ef3fbc',\n",
        "              'x': [0],\n",
        "              'y': [0]},\n",
        "             {'name': 'Post Storm Profile',\n",
        "              'type': 'scatter',\n",
-       "              'uid': '91e7e1e3-4be0-42c5-96f1-6536602059fd',\n",
+       "              'uid': 'ca7b4abf-cfd0-4527-b57e-7f23ef048d19',\n",
+       "              'x': [0],\n",
+       "              'y': [0]},\n",
+       "             {'marker': {'color': 'rgb(17, 157, 255)', 'size': 20},\n",
+       "              'mode': 'markers',\n",
+       "              'name': 'Pre-storm dune crest',\n",
+       "              'type': 'scatter',\n",
+       "              'uid': 'f14b6086-8986-43e0-bfb5-d4a9d08735c9',\n",
+       "              'x': [0],\n",
+       "              'y': [0]},\n",
+       "             {'marker': {'color': 'rgb(231, 99, 250)', 'size': 20},\n",
+       "              'mode': 'markers',\n",
+       "              'name': 'Pre-storm dune toe',\n",
+       "              'type': 'scatter',\n",
+       "              'uid': 'fbc7b977-16fd-453e-b7a5-67a4337ca75c',\n",
        "              'x': [0],\n",
        "              'y': [0]}],\n",
        "    'layout': {'legend': {'x': 0, 'y': 1},\n",
@@ -154,7 +170,7 @@
        "              'text': array(['AVOCAn0001', 'AVOCAn0002', 'AVOCAn0003', ..., 'WAMBE0025', 'WAMBE0026',\n",
        "                             'WAMBE0027'], dtype='<U12'),\n",
        "              'type': 'scattermapbox',\n",
-       "              'uid': '77f3ed9c-0deb-4ba3-8e85-cffb6b3eaf5c'},\n",
+       "              'uid': 'e1eeba12-494d-4fca-b196-7d9728480f74'},\n",
        "             {'lat': [0],\n",
        "              'lon': [0],\n",
        "              'marker': {'color': 'rgb(255, 0, 0)', 'opacity': 0.5, 'size': 20},\n",
@@ -162,7 +178,7 @@
        "              'text': array(['AVOCAn0001', 'AVOCAn0002', 'AVOCAn0003', ..., 'WAMBE0025', 'WAMBE0026',\n",
        "                             'WAMBE0027'], dtype='<U12'),\n",
        "              'type': 'scattermapbox',\n",
-       "              'uid': '510eb04a-f70a-4364-a348-73c07cb3b8b2'}],\n",
+       "              'uid': '716f1003-999e-4a6b-9f08-783b3f0d27f8'}],\n",
        "    'layout': {'autosize': True,\n",
        "               'hovermode': 'closest',\n",
        "               'mapbox': {'accesstoken': ('pk.eyJ1IjoiY2hyaXNsZWFtYW4iLCJ' ... 'Hp5bCJ9.U2dwFg2c7RFjUNSayERUiw'),\n",
@@ -201,6 +217,26 @@
     "    y = [0],\n",
     "    name='Post Storm Profile'\n",
     ")\n",
+    "trace3 = go.Scatter(\n",
+    "    x = [0],\n",
+    "    y = [0],\n",
+    "    name='Pre-storm dune crest',\n",
+    "    mode = 'markers',\n",
+    "    marker = dict(\n",
+    "          color = 'rgb(17, 157, 255)',\n",
+    "          size = 20,\n",
+    "        ),\n",
+    ")\n",
+    "trace4 = go.Scatter(\n",
+    "    x = [0],\n",
+    "    y = [0],\n",
+    "    name='Pre-storm dune toe',\n",
+    "    mode = 'markers',\n",
+    "        marker = dict(\n",
+    "          color = 'rgb(231, 99, 250)',\n",
+    "          size = 20,\n",
+    "         ),\n",
+    ")\n",
     "\n",
     "layout = go.Layout(\n",
     "    title = 'Bed Profiles',\n",
@@ -224,7 +260,7 @@
     "    )\n",
     ")\n",
     "\n",
-    "g1 = go.FigureWidget(data=[trace1, trace2],\n",
+    "g1 = go.FigureWidget(data=[trace1, trace2, trace3, trace4],\n",
     "                    layout=layout)\n",
     "\n",
     "\n",
@@ -290,13 +326,22 @@
     "    prestorm_x = prestorm_profile.index.get_level_values('x').tolist()\n",
     "    prestorm_z = prestorm_profile.z.tolist()\n",
     "    \n",
+    "    site_features = df_profile_features.query('site_id == \"{}\"'.format(site_id))\n",
+    "    dune_crest_x = site_features.dune_crest_x\n",
+    "    dune_crest_z = site_features.dune_crest_z\n",
+    "    dune_toe_x = site_features.dune_toe_x\n",
+    "    dune_toe_z = site_features.dune_toe_z\n",
     "    \n",
     "    with g1.batch_update():\n",
     "        g1.data[0].x = prestorm_x\n",
     "        g1.data[0].y = prestorm_z\n",
     "        g1.data[1].x = poststorm_x\n",
     "        g1.data[1].y = poststorm_z\n",
-    "\n",
+    "        g1.data[2].x = dune_crest_x\n",
+    "        g1.data[2].y = dune_crest_z\n",
+    "        g1.data[3].x = dune_toe_x\n",
+    "        g1.data[3].y = dune_toe_z\n",
+    "        \n",
     "    # Update \n",
     "    site_coords = df_sites.query('site_id == \"{}\"'.format(site_id))\n",
     "    with g2.batch_update():\n",
@@ -315,11 +360,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 148,
+   "execution_count": 8,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2018-11-09T01:48:59.291083Z",
-     "start_time": "2018-11-09T01:48:56.439445Z"
+     "end_time": "2018-11-11T22:35:30.219167Z",
+     "start_time": "2018-11-11T22:35:30.045086Z"
     }
    },
    "outputs": [
@@ -882,7 +927,7 @@
        "};\n",
        "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
        "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
        "\n",
        "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
        "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
@@ -1106,7 +1151,7 @@
     {
      "data": {
       "text/html": [
-       "<img 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7tYzx8TUMYO73M4A+M5Efdra2na91J5CLav47rvvjnPPPTeKIXDixImxbNmyWLFiRWzevDmGDh3aabfuvPPOuPjii+MrX/lKTJgwIZ588sm44IIL4owzzoiFCxfWdRgGwLqYbESAAAECBLoUcAawS6Ju3aBpBsBx48bF2LFja2f02h8jRoyIadOm1c7q7fr4i7/4i/jpT38a//zP/9zxo7/8y7+MRx99NB5++OG6kA2AdTHZiAABAgQIdCnQ/hnAl1u3d7oJpCj2GcAuCfdog6YYAF9//fXYf//9Y+3atTF9+vQOgBkzZkRLS0usW7euE8qaNWvisssui+9+97tx0kknxTPPPBN//Md/HOeff35ce+21u0XcsWNHFP+0P4oBcMiQIdHa2hoDBgzYI3gbEyBAgAABAm8VaL8LuPi/O1+edBdw9yelKQbALVu2xODBg2P9+vW1y7ntjzlz5sSqVaviiSee2K3cl770pSjO+hVXwX/961/H5ZdfXruE/HaPmTNnxqxZszr92ADY/cH0jAQIECBQTQHfA9g7695UA+CGDRti/PjxHXKzZ8+O22+/PR5//PFOmg899FCceeaZ8YUvfCGKy8dPPfVUFGcML7nkkrjxxhudAeyd/HkVAgQIECDQScBvAun5UDTFALg3l4CLu4NPPvnk2l3D7Y877rgjLr300njttdeib9++Xer7DGCXRDYgQIAAAQINJ6B/N9HXwBRn8U444YS3XMIdOXJkTJ06dbc3gRTbfvjDH4558+Z1BHP16tVx0UUX1QbAfv36dRlYAeqSyAYECBAgQKDhBPTvJhoA278GZunSpbXLwLfddlssX748Nm3aFMOGDYvzzjuv9jnB9juCi8/z3XLLLbXt2i8BF58BLAbD4rnqeQhQPUq2IUCAAAECjSWgfzfRAFhEq7iBY/78+bUvgh49enTt+/wmT55cS92UKVNi+PDhsXLlytp/Fzd9tH9G8KWXXor3vve98bGPfaz2/w488MC6kipAdTHZiAABAgQINJSA/t1kA2Bvp0uAelvc6xEgQIAAgbyA/m0ATKVIgFJ8igkQIECAQCkC+rcBMBU8AUrxKSZAgAABAqUI6N8GwFTwBCjFp5gAAQIECJQioH8bAFPBE6AUn2ICBAgQIFCKgP5tAEwFT4BSfIoJECBAgEApAvq3ATAVPAFK8SkmsFcCPf0rovZqpxQRILBPCejfBsBUYAUoxaeYwB4L9MYvid/jnVJAgMA+J6B/GwBToRWgFJ9iAnskUAx/l9/xw2jbparPb/57ySfHxmmjD9+j57QxAQLVFNC/DYCp5AtQik8xgboFisu+p8z7Xmxt3b7bmmIIPGxg/3jkmlOjX9/2kbDup7chAQIVE9C/DYCpyAtQik8xgboFNj79izhr+Q+63H71JSfH+KMP7nI7GxAgUG0B/dsAmHoHCFCKTzGBugXub3kpZqxp6XL7W88cE1PHDO5yOxsQIFBtAf3bAJh6BwhQik8xgboFnAGsm8qGBAjUIaB/GwDriMnbbyJAKT7FBOoWaP8M4Mut2zvdBFI8ic8A1k1pQwIEIkL/NgCm3ggClOJTTGCPBNrvAi6Kdr4T2F3Ae8RoYwIEDIC1DPRpa2vb9VsVhKNOAQNgnVA2I9BNAr4HsJsgPQ2Bigvo3wbA1FtAgFJ8ignslYDfBLJXbIoIENhJQP82AKbeEAKU4lNMgAABAgRKEdC/DYCp4AlQik8xAQIECBAoRUD/NgCmgidAKT7FBAgQIECgFAH92wCYCp4ApfgUEyBAgACBUgT0bwNgKngClOJTTIAAAQIEShHQvw2AqeAJUIpPMQECBAgQKEVA/zYApoInQCk+xQQIECBAoBQB/dsAmAqeAKX4FBMgQIAAgVIE9G8DYCp4ApTiU0yAAAECBEoR0L8NgKngCVCKTzEBAgQIEChFQP82AKaCJ0ApPsUECBAgQKAUAf3bAJgKngCl+BQTIECAAIFSBPRvA2AqeAKU4lNMgAABAgRKEdC/DYCp4AlQik8xAQIECBAoRUD/NgCmgidAKT7FBAgQIECgFAH92wCYCp4ApfgUEyBAgACBUgT0bwNgKngClOJTTIAAAQIEShHQvw2AqeAJUIpPMQECBAgQKEVA/zYApoInQCk+xQQIECBAoBQB/dsAmAqeAKX4FBMgQIAAgVIE9G8DYCp4ApTiU0yAAAECBEoR0L8NgKngCVCKTzEBAgQIEChFQP82AKaCJ0ApPsUECBAgQKAUAf3bAJgKngCl+BQTIECAAIFSBPRvA2AqeAKU4lNMgAABAgRKEdC/DYCp4AlQik8xAQIECBAoRUD/NgCmgidAKT7FBAgQIECgFAH92wCYCp4ApfgUEyBAgACBUgT0bwNgKngClOJTTIAAAQIEShHQvw2AqeAJUIpPMQECBAgQKEVA/zYApoInQCk+xQQIECBAoBQB/dsAmAqeAKX4FBMgQIAAgVIE9G8DYCp4ApTiU0yAAAECBEoR0L8NgKngCVCKTzEBAgQIEChFQP82AKaCJ0ApPsUECBAgQKAUAf3bAJgKngCl+BQTIECAAIFSBPRvA2AqeAKU4lNMgAABAgRKEdC/DYCp4AlQik8xAQIECBAoRUD/NgCmgidAKT7FBAgQIECgFAH92wCYCp4ApfgUEyBAgACBUgT0bwNgKngClOJTTIAAAQIEShHQv5tsAFy8eHEsWLAgtm7dGqNGjYpFixbFpEmT3jZcr776alx//fVxzz33xC9/+cs46qij4m//9m/jj/7oj+oKpADVxWQjAgQIECDQUAL6dxMNgHfffXece+65UQyBEydOjGXLlsWKFSti8+bNMXTo0E7Be/3112vbHXrooXHdddfFkUceGS+88EIccMABcdxxx9UVVAGqi8lGBAgQIECgoQT07yYaAMeNGxdjx46NJUuWdIRsxIgRMW3atJg7d26n4C1durR2tvDxxx+Pd73rXXsVTAHaKzZFBAgQIECgVAH9u0kGwOJs3v777x9r166N6dOnd4RqxowZ0dLSEuvWresUtOIy76BBg2p1999/f7z3ve+Ns88+O6655pro16/fboO5Y8eOKP5pfxQBGjJkSLS2tsaAAQNKDbMXJ0CAAAECBOoTMAA2yQC4ZcuWGDx4cKxfvz4mTJjQsfpz5syJVatWxRNPPNEpEe9///vjueeei3POOSeuuOKK+NnPfhZXXnllFEPjTTfdtNsEzZw5M2bNmtXpZwbA+t5wtiJAgAABAo0gYABssgFww4YNMX78+I5szZ49O26//fbaZd5dH8ccc0xs3749nn322Y4zfrfcckvHTSS7C6gzgI3wtrUPBAgQIEAgJ2AAbJIBcG8uAX/wgx+sffbvwQcf7EjRAw88ULsDuBj09ttvvy7TJUBdEtmAAAECBAg0nID+3SQDYJGs4iaQE044oXYXcPtj5MiRMXXq1N3eBFLc+XvXXXfFM888E3379q2V3HrrrTFv3rwoLinX8xCgepRsQ4AAAQIEGktA/26iAbD9a2CKu3uLy8C33XZbLF++PDZt2hTDhg2L8847r/Y5wfY7gouvfCkGxAsuuCA+9alP1T4DeNFFF8WnP/3p2ncD1vMQoHqUbEOAAAECBBpLQP9uogGwiFZx9m/+/Pm1L4IePXp0LFy4MCZPnlxL3ZQpU2L48OGxcuXKjhRu3LgxrrrqqtqdwsVwePHFF7/jXcC7xleAGusNbW8IECBAgEA9Avp3kw2A9Sx6d24jQN2p6bkIECBAgEDvCOjfBsBU0gQoxaeYAAECBAiUIqB/GwBTwROgFJ9iAgQIECBQioD+bQBMBU+AUnyKCRAgQIBAKQL6twEwFTwBSvEpJkCAAAECpQjo3wbAVPAEKMWnmAABAgQIlCKgfxsAU8EToBSfYgIECBAgUIqA/m0ATAVPgFJ8igkQIECAQCkC+rcBMBU8AUrxKSZAgAABAqUI6N8GwFTwBCjFp5gAAQIECJQioH8bAFPBE6AUn2ICBAgQIFCKgP5tAEwFT4BSfIoJECBAgEApAvq3ATAVPAFK8SkmQIAAAQKlCOjfBsBU8AQoxaeYAAECBAiUIqB/GwBTwWuWAE2ZMiXGjBkTixYt2iuPmTNnxn333RctLS21+gsuuCBeffXV2v/zIECAAAECjSbQLP0749qnra2tLfMEVa5tlgAZAKucYsdOgACB6gk0S//OrJwBMKHXLAEyACZCoJQAAQIE9jmBZunfGXgDYEKvWQJUDIDHHnts9O/fP1asWBH77bdfXHbZZVFc2i0era2t8dnPfrZ2SXf79u1x4oknxsKFC+O4446r/byrS8A7duyo1a9ZsyYKs/b6D3zgAwl9pQQIECBAYO8EmqV/793R//9VBsCEXrMEqBgAf/SjH8XVV18dZ599dmzcuLH2Ob7vfOc78eEPfzgmTZoUgwYNiptuuikGDhwYy5Yti5UrV8aTTz5Z+/9dDYAzZsyIr3/967XhctiwYTF//vz45je/GU899VSt3oMAAQIECPSmQLP074yZATCh1ywBKgbAN954Ix5++OEOjZNOOilOPfXU+MhHPhLTp0+PV155Jd797nd3/Pz3fu/34nOf+1xceuml7zgA/s///E8cdNBBtYGxGC6Lx//93//F8OHD4zOf+UztzKAHAQIECBDoTYFm6d8ZMwNgQq9ZAlQMgKNGjYq///u/79CYOnVqHHzwwTFixIi49tpr4z3vec9bpH71q1/FX/3VX8W8efPecQD88Y9/XLtU/Nxzz9XO/rU/iqGyGAy/8pWvJFZAKQECBAgQ2HOBZunfe37k/6/CAJjQa5YA7e4mkGnTpsWBBx5YGwC/9KUvxUMPPdRJqvj5IYcc8o4D4GOPPVb7ipnnn38+hg4d2vEcxfMXA+aXv/zlxAooJUCAAAECey7QLP17z4/cAJgx66htlgC90wB4zjnnxOmnn177vF5x2XZ3j3f6DGBxCbj4nN9Xv/rVt1wCPuqoo2qXgIuziB4ECBAgQKA3BZqlf2fMnAFM6DVLgN5pACwGt8mTJ8e2bdtql3vf9773xZYtW+Lb3/52FGfxijt6u7oJpBj01q5dWzvbV5wFbL8J5Omnn65dBvYgQIAAAQK9KdAs/TtjZgBM6DVLgN5pACxu3iiGv+uvvz6+8Y1vxM9//vM47LDDakPh3LlzY8iQIV0OgMVXxxQ3jKxevbr2XL4GJhE6pQQIECCQFmiW/p2BMAAm9AQogaeUAAECBAiUJKB/+x7AVPQEKMWnmAABAgQIlCKgfxsAU8EToBSfYgIECBAgUIqA/m0ATAVPgFJ8igkQIECAQCkC+rcBMBU8AUrxKSZAgAABAqUI6N8GwFTwBCjFp5gAAQIECJQioH8bAFPBE6AUn2ICBAgQIFCKgP5tAEwFT4BSfIoJECBAgEApAvq3ATAVPAFK8SkmQIAAAQKlCOjfBsBU8AQoxaeYAAECBAiUIqB/GwBTwROgFJ9iAgQIECBQioD+bQBMBU+AUnyKCRAgQIBAKQL6twEwFTwBSvEpJkCAAAECpQjo3wbAVPAEKMWnmAABAgQIlCKgfxsAU8EToBSfYgIECBAgUIqA/m0ATAVPgFJ8igkQIECAQCkC+rcBMBU8AUrxKSZAgAABAqUI6N8GwFTwBCjFp5gAAQIECJQioH8bAFPBE6AUn2ICBAgQIFCKgP5tAEwFT4BSfIoJECBAgEApAvq3ATAVPAFK8SkmQIAAAQKlCOjfBsBU8AQoxaeYAAECBAiUIqB/GwBTwROgFJ9iAgQIECBQioD+bQBMBU+AUnyKCRAgQIBAKQL6twEwFTwBSvEpJkCAAAECpQjo3wbAVPAEKMWnmAABAgQIlCKgfxsAU8EToBSfYgIECBAgUIqA/m0ATAVPgFJ8igkQIECAQCkC+rcBMBU8AUrxKSZAgAABAqUI6N8GwFTwBCjFp5gAAQIECJQioH8bAFPBE6AUn2ICBAgQIFCKgP5tAEwFT4BSfIoJECBAgEApAvq3ATAVPAFK8VnIpHgAABveSURBVCkmQIAAAQKlCOjfTTYALl68OBYsWBBbt26NUaNGxaJFi2LSpEldhmvNmjVx1llnxdSpU+O+++7rcvv2DQSobiobEiBAgACBhhHQv5toALz77rvj3HPPjWIInDhxYixbtixWrFgRmzdvjqFDh75t6J5//vna9r/7u78bgwYNMgA2zNvTjhAgQIAAgZ4RMAA20QA4bty4GDt2bCxZsqQjLSNGjIhp06bF3Llzd5ugN954Iz74wQ/GhRdeGA8//HC8+uqrBsCeea95VgIECBAg0DACBsAmGQBff/312H///WPt2rUxffr0joDNmDEjWlpaYt26dbsN3c033xw//vGP4957740LLrigywFwx44dUfyz8yXgIUOGRGtrawwYMKBhgm1HCBAgQIAAgbcXMAA2yQC4ZcuWGDx4cKxfvz4mTJjQseJz5syJVatWxRNPPNEpBcW2Z5xxRm1APOSQQ+oaAGfOnBmzZs3q9FwGQH/MECBAgACBfUfAANhkA+CGDRti/PjxHQmcPXt23H777fH444+/JZXbtm2LY489tvZ5wdNPP732M2cA9503rj0lQIAAAQIZAQNgkwyAe3oJuDjrd/zxx0e/fv068vPmm2/W/r1v3761M4ZHH310l9kSoC6JbECAAAECBBpOQP9ukgGwSFZxE8gJJ5xQO6vX/hg5cmTtq112vQlk+/bt8dRTT70lkDfccEMUZwZvvfXWOOaYY2K//fbrMrAC1CWRDQgQIECAQMMJ6N9NNAC2fw3M0qVLa5eBb7vttli+fHls2rQphg0bFuedd17tc4Jvd0dwPZeAd02wADXce9oOESBAgACBLgX07yYaAIvVLs7+zZ8/v/ZF0KNHj46FCxfG5MmTa0GYMmVKDB8+PFauXLnbYBgAu3y/2IAAAQIECDSFgAGwyQbA3k6lAPW2uNcjQIAAAQJ5Af3bAJhKkQCl+BQTIECAAIFSBPRvA2AqeAKU4lNMgAABAgRKEdC/DYCp4AlQik8xAQIECBAoRUD/NgCmgidAKT7FBAgQIECgFAH92wCYCp4ApfgUEyBAgACBUgT0bwNgKngClOJTTIAAAQIEShHQvw2AqeAJUIpPMQECBAgQKEVA/zYApoInQCk+xQQIECBAoBQB/dsAmAqeAKX4FBMgQIAAgVIE9G8DYCp4ApTiU0yAAAECBEoR0L8NgKngCVCKTzEBAgQIEChFQP82AKaCJ0ApPsUECBAgQKAUAf3bAJgKngCl+BQTIECAAIFSBPRvA2AqeAKU4lNMgAABAgRKEdC/DYCp4AlQik8xAQIECBAoRUD/NgCmgidAKT7FBAgQIECgFAH92wCYCp4ApfgUEyBAgACBUgT0bwNgKngClOJTTIAAAQIEShHQvw2AqeAJUIpPMQECBAgQKEVA/zYApoInQCk+xQQIECBAoBQB/dsAmAqeAKX4FBMgQIAAgVIE9G8DYCp4ApTiU0yAAAECBEoR0L8NgKngCVCKTzEBAgQIEChFQP82AKaCJ0ApPsUECBAgQKAUAf3bAJgKngCl+BQTIECAAIFSBPRvA2AqeAKU4lNMgAABAgRKEdC/DYCp4AlQik8xAQIECBAoRUD/NgCmgidAKT7FBAgQIECgFAH92wCYCp4ApfgUEyBAgACBUgT0bwNgKngClOJTTIAAAQIEShHQvw2AqeAJUIpPMQECBAgQKEVA/zYApoInQCk+xQQIECBAoBQB/dsAmAqeAKX4FBMgQIAAgVIE9G8DYCp4ApTiU0yAAAECBEoR0L8NgKngCVCKTzEBAgQIEChFQP82AKaCJ0ApPsUECBAgQKAUAf3bAJgKngCl+BQTIECAAIFSBPRvA2AqeAKU4lNMgAABAgRKEdC/DYCp4AlQik8xAQIECBAoRUD/NgCmgidAKT7FBAgQIECgFAH92wCYCp4ApfgUEyBAgACBUgT0bwNgKngClOJTTIAAAQIEShHQvw2AqeAJUIpPMQECBAgQKEVA/zYApoInQCk+xQQIECBAoBQB/dsAmAqeAKX4FBMgQIAAgVIE9G8DYCp4ApTiU0yAAAECBEoR0L8NgKngCVCKTzEBAgQIEChFQP82AKaCJ0ApPsUECBAgQKAUAf3bAJgKngCl+BQTIECAAIFSBPRvA2AqeAKU4lNMgAABAgRKEdC/DYCp4AlQik8xAQIECBAoRUD/NgCmgidAKT7FBAgQIECgFAH92wCYCp4ApfgUEyBAgACBUgT0bwNgKngClOJTTIAAAQIEShHQvw2AqeAJUIpPMQECBAgQKEVA/zYApoInQCk+xQQIECBAoBQB/dsAmAqeAKX4FBMgQIAAgVIE9O8mGwAXL14cCxYsiK1bt8aoUaNi0aJFMWnSpN2Ga/ny5fG1r30tfvKTn9R+fsIJJ8ScOXPipJNOqjuMAlQ3lQ0JECBAgEDDCOjfTTQA3n333XHuuedGMQROnDgxli1bFitWrIjNmzfH0KFDO4XunHPOqW03YcKE6N+/f8yfPz/uueee2LRpUwwePLiukApQXUw2IkCAAAECDSWgfzfRADhu3LgYO3ZsLFmypCNkI0aMiGnTpsXcuXO7DN4bb7wRBx10UPzd3/1dnHfeeV1uX2wgQHUx2YgAAQIECDSUgP7dJAPg66+/Hvvvv3+sXbs2pk+f3hGyGTNmREtLS6xbt67L4G3bti0OPfTQ2nN89KMf7XJ7A2BdRDYiQIAAAQINJ2AAbJIBcMuWLbXLtuvXr69d0m1/FJ/pW7VqVTzxxBNdhu/KK6+M73znO7XPBBaXhHf32LFjRxT/tD+KAA0ZMiRaW1tjwIABXb6GDQgQIECAAIHyBQyATTYAbtiwIcaPH9+RrNmzZ8ftt98ejz/++Dumrfj83xe/+MV46KGH4thjj33bbWfOnBmzZs3q9HMDYPlvZntAgAABAgTqFTAANskAmLkE/Dd/8zfxhS98IR588ME48cQT3zE7zgDW+9ayHQECBAgQaFwBA2CTDIBFxIqbQIqvcinuAm5/jBw5MqZOnfq2N4EUXxlTDH/Fpd+TTz55j5MqQHtMpoAAAQIECJQuoH830QDY/jUwS5curV0Gvu2226L4rr/ia12GDRtWu7O3+Jxg+x3BxWXfG2+8Me66667a18G0P377t387in/qeQhQPUq2IUCAAAECjSWgfzfRAFhEqzj7Vwx2xRdBjx49OhYuXBiTJ0+upW7KlCkxfPjwWLlyZe2/i39//vnnOyXy5ptvjuKzfvU8BKgeJdsQIECAAIHGEtC/m2wA7O14CVBvi3s9AgQIECCQF9C/DYCpFAlQik8xAQIECBAoRUD/NgCmgidAKT7FBAgQIECgFAH92wCYCp4ApfgUEyBAgACBUgT0bwNgKngClOJTTIAAAQIEShHQvw2AqeAJUIpPMQECBAgQKEVA/zYApoInQCk+xQQIECBAoBQB/dsAmAqeAKX4FBMgQIAAgVIE9G8DYCp4ApTiU0yAAAECBEoR0L8NgKngCVCKTzEBAgQIEChFQP82AKaCJ0ApPsUECBAgQKAUAf3bAJgKngCl+BQTIECAAIFSBPRvA2AqeAKU4lNMgAABAgRKEdC/DYCp4AlQik8xAQIECBAoRUD/NgCmgidAKT7FBAgQIECgFAH92wCYCp4ApfgUEyBAgACBUgT0bwNgKngClOJTTIAAAQIEShHQvw2AqeAJUIpPMQECBAgQKEVA/zYApoInQO/M98abbfHos/8Vr2zbHoce0D9OOmpQ9OvbJ2WumAABAgQIZAX0bwNgKkMC9PZ8//STrTHrW5tja+v2jo0OH9g/bv7YyDht9OEpd8UECBAgQCAjoH8bADP5CQHaPV8x/F1+xw+jbZcft5/7W/LJsYbAVPIUEyBAgEBGQP82AGbyYwDcjV5x2feUed97y5m/nTcrhsDDBvaPR6451eXgVPoUEyBAgMDeChgADYB7m51anQB15tv49C/irOU/6NJ19SUnx/ijD+5yOxsQIECAAIHuFtC/DYCpTAlQZ777W16KGWtaunS99cwxMXXM4C63swEBAgQIEOhuAf3bAJjKlAA5A5gKkGICBAgQKEVA/zYApoInQJ352j8D+HLr9k43gRRb+wxgKnKKCRAgQKAbBPRvA2AqRgK0e772u4CLn+58J7C7gFNxU0yAAAEC3SSgfxsAU1ESoLfn8z2AqWgpJkCAAIEeFNC/DYCpeAnQO/P5TSCpeCkmQIAAgR4S0L8NgKloCVCKTzEBAgQIEChFQP82AKaCJ0ApPsUECBAgQKAUAf3bAJgKngCl+BQTIECAAIFSBPRvA2AqeAKU4lNMgAABAgRKEdC/DYCp4AlQik8xAQIECBAoRUD/NgCmgidAKT7FBAgQIECgFAH92wCYCp4ApfgUEyBAgACBUgT0bwNgKngClOJTTIAAAQIEShHQvw2AqeAJUIpPMQECBBpGwBfXN8xS9MqO6N8GwFTQBCjFp5gAAQINIeBXVzbEMvTqTujfBsBU4AQoxaeYAAECpQsUw9/ld/ww2nbZkz6/+e8lnxwbp40+vPT9tAPdK6B/GwBTiRKgFJ9iAgQIlCpQXPY9Zd73Ymvr9t3uRzEEHjawfzxyzanRr2/7SFjqLnvxbhLQvw2AqSgJUIpPMQECBEoV2Pj0L+Ks5T/och9WX3JyjD/64C63s8G+I6B/GwBTaRWgFJ9iAgQIlCpwf8tLMWNNS5f7cOuZY2LqmMFdbmeDfUdA/zYAptIqQCk+xQQIEChVwBnAUvlLfXH92wCYCqAApfgUEyBAoFSB9s8Avty6vdNNIMWO+QxgqcvToy+ufxsAUwEToBSfYgIECJQu0H4XcLEjO98J7C7g0pemR3dA/zYApgImQCk+xQQIEGgIAd8D2BDL0Ks7oX8bAFOBE6AUn2ICBAg0jIDfBNIwS9ErO6J/GwBTQROgFJ9iAgQIECBQioD+bQBMBU+AUnyKCRAgQIBAKQL6twEwFTwBSvEpJkCAAAECpQjo3wbAVPAEKMWnmAABAgQIlCKgfxsAU8EToBSfYgIECBAgUIqA/m0ATAVPgFJ8igkQIECAQCkC+rcBMBU8AUrxKSZAgAABAqUI6N8GwFTwBCjFp5gAAQIECJQioH8bAFPBE6AUn2ICBAgQ6GYBX2hdH6j+bQCsLylvs5UApfgUEyBAgEA3CviVdvVj6t9NNgAuXrw4FixYEFu3bo1Ro0bFokWLYtKkSW+biG984xtx4403xtNPPx1HH310zJ49O6ZPn153ggSobiobEiBAgEAPChTD3+V3/DDadnmNPr/57yWfHBunjT68B/dg33pq/buJBsC77747zj333CiGwIkTJ8ayZctixYoVsXnz5hg6dGinZG7cuLE2HP71X/91bei7995746abbopHHnkkxo0bV1eSBaguJhsRIECAQA8KFJd9T5n3vdjaun23r1IMgYcN7B+PXHNq9OvbPhL24A7tA0+tfzfRAFgMbWPHjo0lS5Z0RG/EiBExbdq0mDt3bqc4nnHGGVEE4IEHHuj42WmnnRYHHXRQrF69uq74ClBdTDYiQIAAgR4U2Pj0L+Ks5T/o8hVWX3JyjD/64C63q8IG+neTDICvv/567L///rF27dq3XMKdMWNGtLS0xLp16zrluTgreNVVV9X+aX8sXLiwdtn4+eefryv/AlQXk40IECBAoAcF7m95KWasaenyFW49c0xMHTO4y+2qsIH+3SQD4JYtW2Lw4MGxfv36mDBhQkd258yZE6tWrYonnniiU57322+/WLlyZZx99tkdP7vrrrviwgsvjB07duw2/8X/3/lnRYCGDBkSra2tMWDAgCq8ZxwjAQIECDSYgDOAe74gBsAmGwA3bNgQ48eP70hCcVPH7bffHo8//vhuB8BiODzrrLM6fnbnnXfGxRdfHNu37/5zFDNnzoxZs2Z1ei4D4J6/+VQQIECAQPcItH8G8OXW7Z1uAilewWcAOzsbAJtkAOytS8DOAHbPH1aehQABAgS6V6D9LuDiWXe+E9hdwLt3NgA2yQBYLG9xE8gJJ5xQuwu4/TFy5MiYOnXq294Esm3btvj2t7/dsf3pp58eBx54oJtAuvfPJc9GgAABAr0g4HsA60c2ADbRANj+NTBLly6tXQa+7bbbYvny5bFp06YYNmxYnHfeebXPCbbfEVxcLp48eXLtu/+KIfH++++PG264wdfA1P/+sSUBAgQINJiA3wRS34IYAJtoACyWvDj7N3/+/NoXQY8ePTqKu3qLIa94TJkyJYYPH1678aP98fWvf7029D3zzDMdXwT9J3/yJ/WlJ6L2NTIDBw50E0jdYjYkQIAAAQLlC+jfTTYA9nakBKi3xb0eAQIECBDIC+jfBsBUigQoxaeYAAECBAiUIqB/GwBTwROgFJ9iAgQIECBQioD+bQBMBU+AUnyKCRAgQIBAKQL6twEwFTwBSvEpJkCAAAECpQjo3wbAVPAEKMWnmAABAgQIlCKgfxsAU8EToBSfYgIECBAgUIqA/m0ATAVPgFJ8igkQIECAQCkC+rcBMBU8AUrxKSZAgAABAqUI6N8GwFTwWltba787+IUXXogBAwaknksxAQIECBAg0DsCxQA4ZMiQePXVV2u/0auKjz5tbW1tVTzw7jjmF198sRYgDwIECBAgQGDfEyhO4Bx55JH73o53wx4bABOIb775ZmzZsiUOOOCA6NOnT+KZOpe2/+3E2cVuZd3rJ7Mee03XI4XWo0dY9/pJrcde0/VIofXomrU497Vt27Y44ogjom/fvl0XNOEWBsAGXVSfT2ishbEe1qOxBBprb7w/rEdjCdibegQMgPUolbCNP1BLQH+Hl7Qe1qOxBBprb7w/rEdjCdibegQMgPUolbCNP1BLQDcANha69bAe+4xAY+2o/tFY69Goe2MAbNCV2bFjR8ydOzc+//nPx7vf/e4G3cvq7Jb1aKy1th7Wo7EEGmtvvD8aaz0adW8MgI26MvaLAAECBAgQINBDAgbAHoL1tAQIECBAgACBRhUwADbqytgvAgQIECBAgEAPCRgAewjW0xIgQIAAAQIEGlXAANioK2O/CBAgQIAAAQI9JGAA7CHYzNMuXrw4FixYEFu3bo1Ro0bFokWLYtKkSZmnVLsXAsVd2Pfcc088/vjj8Z73vCcmTJgQ8+bNi/e973178WxKulugWJ/rrrsuZsyYUXuPeJQj8NJLL8U111wTDzzwQPzqV7+KY445Jr785S/HCSecUM4OVfhVf/3rX8fMmTPjzjvvjJdffjkOP/zwuOCCC+KGG26o7G+7qHAcujx0A2CXRL27wd133x3nnntuFEPgxIkTY9myZbFixYrYvHlzDB06tHd3puKvdtppp8WZZ54ZH/jAB6L4g/X666+P//iP/6itxW/91m9VXKfcw//Xf/3X+MQnPhEDBgyID33oQwbAkpbjl7/8ZRx//PG1Nbj88svj0EMPjaeffjqGDx8eRx99dEl7Vd2XnT17dixcuDBWrVpVO3nwb//2b3HhhRfGF77whdpflDwI7CxgAGywPIwbNy7Gjh0bS5Ys6dizESNGxLRp02rfC+hRnsDPf/7zWoNbt25dTJ48ubwdqfgrv/baa7X3SPGXpKKxjRkzxgBYUiauvfbaWL9+fTz88MMl7YGX3Vngox/9aPzO7/xO7Qxs++PjH/947L///nH77bfDIvAWAQNgAwXi9ddfr71R165dG9OnT+/Ys+Jvbi0tLbXBw6M8gaeeeip+//d/v3YWcPTo0eXtSMVf+fzzz49BgwbVznRMmTLFAFhiHkaOHBl/+Id/GC+++GLtz6fBgwfHFVdcEZdcckmJe1Xdl/7iF78YS5cuje9+97u1S/GPPfZYfOQjH6n9Bemss86qLowj362AAbCBgrFly5baH6DF36iLz5u1P+bMmVM7pf/EE0800N5Wa1fa2tpi6tSpUVzycrajvLVfs2ZN7axfcWmrf//+BsDylqL2ysUaFI+rr746/uzP/iweffTR+MxnPlP76Mp5551X8t5V7+WLP6eKz8UWn1Xu169fvPHGG1FcFi5+o5QHgV0FDIANlIn2AXDDhg0xfvz4jj0r3sDF6fviZgSPcgSuvPLK+Md//Md45JFH4sgjjyxnJyr+qi+88EKceOKJtbMbxx13XE3DGcByQ7HffvvV1qT4M6v98elPfzqKz2hu3Lix3J2r4KsXf0H67Gc/W7uJsPgMYHHlqBjIb7nllijOnHsQ2FnAANhAeXAJuIEWY6dd+dSnPhX33XdffP/734+jjjqqMXeyAntVrEHx0YjizEb7ozjD0adPn9odjsXvP935ZxUgKf0Qhw0bFn/wB39Qu1Gt/VF8frk4S1vcHezRuwJDhgyJ4nOZxV9Y2x/FWtxxxx1OIPTuUuwTr2YAbLBlKm4CKb4+ofiAe/uj+JxNcfnRTSC9u1jF5ZRi+Lv33nvjoYceqn3+z6M8gW3btsXzzz//lh0o7nB8//vfX/saEp/L7P21Ofvss6M4M7vzxyKuuuqq+Jd/+Ze3nBXs/T2r5isefPDBteG7uCO7/VH0ja9+9avx5JNPVhPFUb+tgAGwwcLR/jUwxQd5i8vAt912Wyxfvjw2bdoUxd+2PXpPoPgw+1133RX333//W777b+DAgbXvBfQoX8Al4HLXoLjUW3xeedasWbWv5Sk+A1jcAFL8uXXOOeeUu3MVfPXiO/8efPDB2mcwi0vAP/rRj+LSSy+Niy66qPa5QA8COwsYABswD8XZv/nz59e+CLo4q1Hc7ehrR3p/oYpLi7t7FH+bLv6g9ShfwABY/hr8wz/8Q+0mg5/97Ge1j0gUN4S4C7icdSnOkt944421qxavvPJKHHHEEbW7f2+66aYoPq/pQcAAKAMECBAgQIAAgQoLOANY4cV36AQIECBAgEA1BQyA1Vx3R02AAAECBAhUWMAAWOHFd+gECBAgQIBANQUMgNVcd0dNgAABAgQIVFjAAFjhxXfoBAgQIECAQDUFDIDVXHdHTYAAAQIECFRYwABY4cV36AQIECBAgEA1BQyA1Vx3R02AAAECBAhUWMAAWOHFd+gECBAgQIBANQUMgNVcd0dNgAABAgQIVFjAAFjhxXfoBAgQIECAQDUFDIDVXHdHTYAAAQIECFRYwABY4cV36AQIECBAgEA1BQyA1Vx3R02AAAECBAhUWMAAWOHFd+gECBAgQIBANQUMgNVcd0dNgAABAgQIVFjAAFjhxXfoBAgQIECAQDUFDIDVXHdHTYAAAQIECFRYwABY4cV36AQIECBAgEA1BQyA1Vx3R02AAAECBAhUWMAAWOHFd+gECBAgQIBANQUMgNVcd0dNgAABAgQIVFjAAFjhxXfoBAgQIECAQDUFDIDVXHdHTYAAAQIECFRYwABY4cV36AQIECBAgEA1BQyA1Vx3R02AAAECBAhUWMAAWOHFd+gECBAgQIBANQUMgNVcd0dNgAABAgQIVFjAAFjhxXfoBAgQIECAQDUFDIDVXHdHTYAAAQIECFRYwABY4cV36AQIECBAgEA1Bf4/MyDXfURWV6gAAAAASUVORK5CYII=\" 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+       "<img 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\" width=\"640\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -1121,12 +1166,14 @@
        "9"
       ]
      },
-     "execution_count": 148,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
+    "\n",
+    "# Test of using matplotlib for manual point clicking\n",
     "%matplotlib notebook\n",
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
@@ -1171,21 +1218,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 149,
+   "execution_count": 12,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2018-11-09T01:48:59.300107Z",
-     "start_time": "2018-11-09T01:48:59.292086Z"
+     "end_time": "2018-11-11T22:35:57.104492Z",
+     "start_time": "2018-11-11T22:35:57.098475Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[]"
+       "[((3.0, 0.3693345274194554),),\n",
+       " ((6.0, 0.5016711151639491),),\n",
+       " ((1.0, 0.10238977657533999),),\n",
+       " ((2.0, 0.04706622152810236),),\n",
+       " ((4.0, 0.04404424214020075),)]"
       ]
      },
-     "execution_count": 149,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/notebooks/qgis.qgz b/notebooks/qgis.qgz
index aa09b91..1ad4364 100644
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