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1157 lines
64 KiB
Plaintext
1157 lines
64 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Data exploration\n",
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"This notebook provides an example how the data has been loaded and accessed for further analysis."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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|
"metadata": {
|
|
"ExecuteTime": {
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"end_time": "2018-11-19T00:22:35.172482Z",
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"start_time": "2018-11-19T00:22:35.000206Z"
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}
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},
|
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"outputs": [],
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"source": [
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"# Enable autoreloading of our modules. \n",
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"# Most of the code will be located in the /src/ folder, \n",
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"# and then called from the notebook.\n",
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"\n",
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"%reload_ext autoreload\n",
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"%autoreload"
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]
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},
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{
|
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"cell_type": "code",
|
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"execution_count": 2,
|
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"metadata": {
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"ExecuteTime": {
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"end_time": "2018-11-19T00:22:50.594936Z",
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"start_time": "2018-11-19T00:22:35.173486Z"
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},
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"from IPython.core.debugger import set_trace\n",
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"\n",
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"import pandas as pd\n",
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"import numpy as np\n",
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"import os\n",
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"\n",
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"import plotly\n",
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"import plotly.graph_objs as go\n",
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"import plotly.plotly as py\n",
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"\n",
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"from ipywidgets import widgets\n",
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"from IPython.display import display, clear_output, Image"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {
|
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"ExecuteTime": {
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"end_time": "2018-11-19T00:51:58.002082Z",
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"start_time": "2018-11-19T00:51:45.127794Z"
|
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},
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|
"pixiedust": {
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"displayParams": {}
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}
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},
|
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"C:\\Users\\z5189959\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\numpy\\lib\\arraysetops.py:472: FutureWarning:\n",
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"\n",
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"elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
|
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"\n"
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]
|
|
}
|
|
],
|
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"source": [
|
|
"data_folder = '../data/interim'\n",
|
|
"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",
|
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"df_profile_features = pd.read_csv(os.path.join(data_folder, 'profile_features.csv'),index_col=[0])\n",
|
|
"df_impacts_compared = pd.read_csv(os.path.join(data_folder,'impacts_observed_vs_forecasted_mean_slope_sto06.csv'),index_col=[0])\n",
|
|
"df_twl = pd.read_csv(os.path.join(data_folder,'twl_mean_slope_sto06.csv'),index_col=[0,1])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 60,
|
|
"metadata": {
|
|
"ExecuteTime": {
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|
"end_time": "2018-11-19T01:46:34.068613Z",
|
|
"start_time": "2018-11-19T01:46:34.021932Z"
|
|
}
|
|
},
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"outputs": [
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{
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"data": {
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'LHOUSEs0017', 'LHOUSEs0018', 'LHOUSEs0019', 'LHOUSEs0020', 'LHOUSEs0021', 'LHOUSEs0022', 'LHOUSEs0023', 'LHOUSEs0024', 'LHOUSEs0025', 'LHOUSEs0026', 'LHOUSEs0027', 'LHOUSEs0028', 'LHOUSEs0029', 'LHOUSEs0030', 'LHOUSEs0031', 'LHOUSEs0032', 'MACM0001', 'MACM0002', 'MACM0003', 'MACM0004', 'MACM0005', 'MACM0006', 'MACM0007', 'MACM0008', 'MACM0009', 'MACM0010', 'MACM0011', 'MACM0012', 'MACM0013', 'MACM0014', 'MACM0015', 'MACM0016', 'MANNING0001', 'MANNING0002', 'MANNING0003', 'MANNING0004', 'MANNING0005', 'MANNING0006', 'MANNING0007', 'MANNING0008', 'MANNING0009', 'MANNING0010', 'MANNING0011', 'MANNING0012', 'MANNING0013', 'MANNING0014', 'MANNING0015', 'MANNING0016', 'MANNING0017', 'MANNING0018', 'MANNING0019', 'MANNING0020', 'MANNING0021', 'MANNING0022', 'MANNING0023', 'MANNING0024', 'MANNING0025', 'MANNING0026', 'MANNING0027', 'MANNING0028', 'MANNING0029', 'MANNING0030', 'MANNING0031', 'MANNING0032', 'MANNING0033', 'MANNING0034', 'MANNING0035', 'MANNING0036', 'MANNING0037', 'MANNING0038', 'MANNING0039', 'MANNING0040', 'MANNING0041', 'MANNING0042', 'MANNING0043', 'MANNING0044', 'MANNING0045', 'MANNING0046', 'MANNING0047', 'MANNING0048', 'MANNING0049', 'MANNING0050', 'MANNING0051', 'MANNING0052', 'MANNING0053', 'MANNING0054', 'MANNING0055', 'MANNING0056', 'MANNING0057', 'MANNING0058', 'MANNING0059', 'MANNING0060', 'MANNING0061', 'MANNING0062', 'MANNING0063', 'MANNING0064', 'MANNING0065', 'MANNING0066', 'MANNING0067', 'MANNING0068', 'MANNING0069', 'MANNING0070', 'MANNING0071', 'MANNING0072', 'MANNING0073', 'MANNING0074', 'MANNING0075', 'MANNING0076', 'MANNING0077', 'MANNING0078', 'MANNING0079', 'MANNING0080', 'MANNING0081', 'MANNING0082', 'MANNING0083', 'MANNING0084', 'MANNING0085', 'MANNING0086', 'MANNING0087', 'MANNING0088', 'MANNING0089', 'MANNING0090', 'MANNING0091', 'MANNING0092', 'MANNING0093', 'MANNING0094', 'MANNING0095', 'MANNING0096', 'MANNING0097', 'MANNING0098', 'MANNING0099', 'MANNING0100', 'MANNING0101', 'MANNING0102', 'MANNING0103', 'MANNING0104', 'MANNING0105', 'MANNING0106', 'MANNING0107', 'MANNING0108', 'MANNING0109', 'MANNING0110', 'MANNING0111', 'MANNING0112', 'MANNING0113', 'MANNING0114', 'MANNING0115', 'MANNING0116', 'MANNING0117', 'MANNING0118', 'MANNING0119', 'MANNING0120', 'MANNING0121', 'MANNING0122', 'MANNING0123', 'MANNING0124', 'MANNING0125', 'MANNING0126', 'MANNING0127', 'MONA0001', 'MONA0002', 'MONA0003', 'MONA0004', 'MONA0005', 'MONA0006', 'MONA0007', '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",
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" 'data': [{'name': 'Pre Storm Profile',\n",
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" 'type': 'scatter',\n",
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" 'uid': 'a7ef1527-c36f-4f59-9d62-64928b7b924f',\n",
|
|
" 'x': [0],\n",
|
|
" 'y': [0]},\n",
|
|
" {'name': 'Post Storm Profile',\n",
|
|
" 'type': 'scatter',\n",
|
|
" 'uid': '8f93d4ab-7ef5-4798-b76d-ea742faf88a5',\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': 'fd8574f3-f280-4ef6-9792-d1c14df1eb55',\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': '4e6d2022-7ff2-42e6-9334-d76411906808',\n",
|
|
" 'x': [0],\n",
|
|
" 'y': [0]}],\n",
|
|
" 'layout': {'height': 300,\n",
|
|
" 'legend': {'x': 0.5, 'y': 1},\n",
|
|
" 'margin': {'b': 50, 'l': 20, 'r': 20, 't': 50},\n",
|
|
" 'title': 'Bed Profiles',\n",
|
|
" 'xaxis': {'autorange': True,\n",
|
|
" 'range': [0, 200],\n",
|
|
" 'showgrid': True,\n",
|
|
" 'showline': True,\n",
|
|
" 'title': 'x (m)',\n",
|
|
" 'zeroline': True},\n",
|
|
" 'yaxis': {'autorange': False,\n",
|
|
" 'range': [-1, 20],\n",
|
|
" 'showgrid': True,\n",
|
|
" 'showline': True,\n",
|
|
" 'title': 'z (m)',\n",
|
|
" 'zeroline': True}}\n",
|
|
"}), FigureWidget({\n",
|
|
" 'data': [{'lat': array([-33.46381539, -33.46301835, -33.46221051, ..., -33.4279646 ,\n",
|
|
" -33.42732743, -33.42671036]),\n",
|
|
" 'lon': array([151.43639576, 151.43690633, 151.43738179, ..., 151.4501613 ,\n",
|
|
" 151.45092222, 151.45170635]),\n",
|
|
" 'marker': {'size': 10},\n",
|
|
" 'mode': 'markers',\n",
|
|
" 'text': array(['AVOCAn0001', 'AVOCAn0002', 'AVOCAn0003', ..., 'WAMBE0025', 'WAMBE0026',\n",
|
|
" 'WAMBE0027'], dtype='<U12'),\n",
|
|
" 'type': 'scattermapbox',\n",
|
|
" 'uid': 'e77778d2-afdf-479f-9ecb-642bad6011db'},\n",
|
|
" {'lat': [0],\n",
|
|
" 'lon': [0],\n",
|
|
" 'marker': {'color': 'rgb(255, 0, 0)', 'opacity': 0.5, 'size': 20},\n",
|
|
" 'mode': 'markers',\n",
|
|
" 'text': array(['AVOCAn0001', 'AVOCAn0002', 'AVOCAn0003', ..., 'WAMBE0025', 'WAMBE0026',\n",
|
|
" 'WAMBE0027'], dtype='<U12'),\n",
|
|
" 'type': 'scattermapbox',\n",
|
|
" 'uid': 'e9d1a48c-46d8-4783-b50c-81ff73913f8a'}],\n",
|
|
" 'layout': {'autosize': True,\n",
|
|
" 'height': 300,\n",
|
|
" 'hovermode': 'closest',\n",
|
|
" 'mapbox': {'accesstoken': ('pk.eyJ1IjoiY2hyaXNsZWFtYW4iLCJ' ... 'Hp5bCJ9.U2dwFg2c7RFjUNSayERUiw'),\n",
|
|
" 'bearing': 0,\n",
|
|
" 'center': {'lat': -33.7, 'lon': 151.3},\n",
|
|
" 'pitch': 0,\n",
|
|
" 'style': 'satellite-streets',\n",
|
|
" 'zoom': 12},\n",
|
|
" 'margin': {'b': 50, 'l': 20, 'r': 20, 't': 50},\n",
|
|
" 'showlegend': False}\n",
|
|
"}))), FigureWidget({\n",
|
|
" 'data': [{'name': 'Hs0', 'type': 'scatter', 'uid': 'f4c191f6-fd4f-41f5-b779-95260f23f281', 'x': [0, 1], 'y': [0, 1]},\n",
|
|
" {'name': 'Tp',\n",
|
|
" 'type': 'scatter',\n",
|
|
" 'uid': '6f12399d-6b75-40f7-b713-893f7c353f38',\n",
|
|
" 'x': [0, 2],\n",
|
|
" 'y': [0, 2],\n",
|
|
" 'yaxis': 'y2'},\n",
|
|
" {'name': 'beta',\n",
|
|
" 'type': 'scatter',\n",
|
|
" 'uid': 'd8212fc8-5399-4c1f-8623-ba5ade277599',\n",
|
|
" 'x': [0, 3],\n",
|
|
" 'y': [0, 3],\n",
|
|
" 'yaxis': 'y3'}],\n",
|
|
" 'layout': {'height': 200,\n",
|
|
" 'margin': {'b': 50, 'l': 50, 'r': 50, 't': 50},\n",
|
|
" 'title': 'Hydro/Morpho Parameters',\n",
|
|
" 'xaxis': {'domain': [0.0, 0.9], 'title': 'time', 'zeroline': False},\n",
|
|
" 'yaxis': {'title': 'Hs0 (m)'},\n",
|
|
" 'yaxis2': {'overlaying': 'y', 'side': 'right', 'title': 'Tp (s)'},\n",
|
|
" 'yaxis3': {'overlaying': 'y', 'position': 0.97, 'side': 'right', 'title': 'beta (-)'}}\n",
|
|
"}), FigureWidget({\n",
|
|
" 'data': [{'line': {'color': 'rgb(91,220,229)', 'width': 2},\n",
|
|
" 'name': 'R High',\n",
|
|
" 'type': 'scatter',\n",
|
|
" 'uid': '0aa45aab-f418-4273-b898-080a738dd57a',\n",
|
|
" 'x': [0, 1],\n",
|
|
" 'y': [0, 1]},\n",
|
|
" {'line': {'color': 'rgb(13,174,186)', 'width': 2},\n",
|
|
" 'name': 'R Low',\n",
|
|
" 'type': 'scatter',\n",
|
|
" 'uid': 'd874630e-6006-4d4e-a962-a95e817855fb',\n",
|
|
" 'x': [0, 2],\n",
|
|
" 'y': [0, 2]},\n",
|
|
" {'line': {'color': 'rgb(214, 117, 14)', 'dash': 'dot', 'width': 2},\n",
|
|
" 'name': 'Dune Crest',\n",
|
|
" 'type': 'scatter',\n",
|
|
" 'uid': '0042b440-e49a-4d54-8ac2-fac51d6b67e1',\n",
|
|
" 'x': [0, 3],\n",
|
|
" 'y': [0, 3]},\n",
|
|
" {'line': {'color': 'rgb(142, 77, 8)', 'dash': 'dash', 'width': 2},\n",
|
|
" 'name': 'Dune Toe',\n",
|
|
" 'type': 'scatter',\n",
|
|
" 'uid': '996ee70f-9f12-4670-b771-d1c01ee1cdff',\n",
|
|
" 'x': [0, 3],\n",
|
|
" 'y': [0, 3]},\n",
|
|
" {'line': {'color': 'rgb(8,51,137)', 'dash': 'dot', 'width': 2},\n",
|
|
" 'name': 'Tide+Surge WL',\n",
|
|
" 'type': 'scatter',\n",
|
|
" 'uid': '0331b331-b34a-4bd2-befe-3ef7d9c71b65',\n",
|
|
" 'x': [0, 4],\n",
|
|
" 'y': [0, 4]}],\n",
|
|
" 'layout': {'height': 200,\n",
|
|
" 'margin': {'b': 50, 'l': 50, 'r': 50, 't': 50},\n",
|
|
" 'title': 'Water Level & Dune Toe/Crest',\n",
|
|
" 'xaxis': {'domain': [0.0, 0.95], 'title': 'time', 'zeroline': False},\n",
|
|
" 'yaxis': {'title': 'Water Level (m)'}}\n",
|
|
"})))"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Create widgets for filtering by observed and forecasted impacts\n",
|
|
"\n",
|
|
"filter_title = widgets.HTML(\n",
|
|
" value=\"<b>Filter by observed and predicted impacts:</b>\",\n",
|
|
")\n",
|
|
"\n",
|
|
"observed_impact_select = widgets.SelectMultiple(\n",
|
|
" options=df_impacts_compared.storm_regime_observed.dropna().unique(),\n",
|
|
" value=df_impacts_compared.storm_regime_observed.dropna().unique().tolist(),\n",
|
|
" description='Observed Impacts',\n",
|
|
" disabled=False\n",
|
|
")\n",
|
|
"\n",
|
|
"forecasted_impact_select = widgets.SelectMultiple(\n",
|
|
" options=df_impacts_compared.storm_regime_forecasted.dropna().unique(),\n",
|
|
" value=df_impacts_compared.storm_regime_forecasted.dropna().unique().tolist(),\n",
|
|
" description='Forecasted Impacts',\n",
|
|
" disabled=False\n",
|
|
")\n",
|
|
"\n",
|
|
"filter_container = widgets.VBox(children=[filter_title,widgets.HBox(children=[forecasted_impact_select,observed_impact_select])])\n",
|
|
"\n",
|
|
"\n",
|
|
"# Create widgets for selecting site_id\n",
|
|
"\n",
|
|
"site_id_title = widgets.HTML(\n",
|
|
" value=\"<b>Filter by site_id:</b>\",\n",
|
|
")\n",
|
|
"\n",
|
|
"site_id_select = widgets.Dropdown(\n",
|
|
" description='site_id: ',\n",
|
|
" value='NARRA0001',\n",
|
|
" options=df_profiles.index.get_level_values('site_id').unique().sort_values().tolist()\n",
|
|
")\n",
|
|
"site_id_container = widgets.VBox(children=[site_id_title,widgets.HBox(children=[site_id_select])])\n",
|
|
"\n",
|
|
"\n",
|
|
"\n",
|
|
"# Add panel for pre/post storm profiles\n",
|
|
"trace1 = go.Scatter(\n",
|
|
" x = [0],\n",
|
|
" y = [0],\n",
|
|
" name='Pre Storm Profile'\n",
|
|
")\n",
|
|
"trace2 = go.Scatter(\n",
|
|
" x = [0],\n",
|
|
" 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",
|
|
" height=300,\n",
|
|
" legend=dict(x=0.5, y=1),\n",
|
|
" margin=dict(t=50,b=50,l=20,r=20),\n",
|
|
" xaxis=dict(\n",
|
|
" title = 'x (m)',\n",
|
|
" autorange=True,\n",
|
|
" showgrid=True,\n",
|
|
" zeroline=True,\n",
|
|
" showline=True,\n",
|
|
" range=[0, 200]\n",
|
|
" ),\n",
|
|
" yaxis=dict(\n",
|
|
" title = 'z (m)',\n",
|
|
" autorange=False,\n",
|
|
" showgrid=True,\n",
|
|
" zeroline=True,\n",
|
|
" showline=True,\n",
|
|
" range=[-1, 20]\n",
|
|
" )\n",
|
|
")\n",
|
|
"\n",
|
|
"g1 = go.FigureWidget(data=[trace1, trace2, trace3, trace4],\n",
|
|
" layout=layout)\n",
|
|
"\n",
|
|
"\n",
|
|
"# Add panel for google maps\n",
|
|
"mapbox_access_token = 'pk.eyJ1IjoiY2hyaXNsZWFtYW4iLCJhIjoiY2pvNTY1MzZpMDc2OTN2bmw5MGsycHp5bCJ9.U2dwFg2c7RFjUNSayERUiw'\n",
|
|
"\n",
|
|
"data = [\n",
|
|
" go.Scattermapbox(\n",
|
|
" lat=df_sites['lat'],\n",
|
|
" lon=df_sites['lon'],\n",
|
|
" mode='markers',\n",
|
|
" marker=dict(\n",
|
|
" size=10\n",
|
|
" ),\n",
|
|
" text=df_sites.index.get_level_values('site_id'),\n",
|
|
" ),\n",
|
|
" go.Scattermapbox(\n",
|
|
" lat=[0],\n",
|
|
" lon=[0],\n",
|
|
" mode='markers',\n",
|
|
" marker=dict(\n",
|
|
" size=20,\n",
|
|
" color='rgb(255, 0, 0)',\n",
|
|
" opacity = 0.5,\n",
|
|
" ),\n",
|
|
" text=df_sites.index.get_level_values('site_id'),\n",
|
|
" ),\n",
|
|
"]\n",
|
|
"\n",
|
|
"layout = go.Layout(\n",
|
|
" autosize=True,\n",
|
|
" height=300,\n",
|
|
" hovermode='closest',\n",
|
|
" showlegend=False,\n",
|
|
" margin=dict(t=50,b=50,l=20,r=20),\n",
|
|
" mapbox=dict(\n",
|
|
" accesstoken=mapbox_access_token,\n",
|
|
" bearing=0,\n",
|
|
" center=dict(\n",
|
|
" lat=-33.7,\n",
|
|
" lon=151.3\n",
|
|
" ),\n",
|
|
" pitch=0,\n",
|
|
" zoom=12,\n",
|
|
" style='satellite-streets'\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"fig = dict(data=data, layout=layout)\n",
|
|
"g2 = go.FigureWidget(data=data,layout=layout)\n",
|
|
"\n",
|
|
"\n",
|
|
"# Add panel for time series\n",
|
|
"\n",
|
|
"trace_Hs0 = go.Scatter(\n",
|
|
" x = [0,1],\n",
|
|
" y = [0,1],\n",
|
|
" name='Hs0'\n",
|
|
")\n",
|
|
"trace_Tp = go.Scatter(\n",
|
|
" x = [0,2],\n",
|
|
" y = [0,2],\n",
|
|
" name='Tp',\n",
|
|
" yaxis='y2'\n",
|
|
")\n",
|
|
"trace_beta = go.Scatter(\n",
|
|
" x = [0,3],\n",
|
|
" y = [0,3],\n",
|
|
" name='beta',\n",
|
|
" yaxis='y3'\n",
|
|
")\n",
|
|
"data=[trace_Hs0, trace_Tp, trace_beta]\n",
|
|
"\n",
|
|
"layout = go.Layout(\n",
|
|
" title = 'Hydro/Morpho Parameters',\n",
|
|
" height=200,\n",
|
|
" margin=dict(t=50,b=50,l=50,r=50),\n",
|
|
" xaxis=dict(\n",
|
|
" title='time',\n",
|
|
" domain=[0.0, 0.9],\n",
|
|
" zeroline=False,\n",
|
|
" ),\n",
|
|
" yaxis=dict(\n",
|
|
" title = 'Hs0 (m)',\n",
|
|
" ),\n",
|
|
" yaxis2=dict(\n",
|
|
" title='Tp (s)',\n",
|
|
" overlaying='y',\n",
|
|
" side='right'\n",
|
|
" ),\n",
|
|
" yaxis3=dict(\n",
|
|
" title='beta (-)',\n",
|
|
" overlaying='y',\n",
|
|
" side='right',\n",
|
|
" position=0.97\n",
|
|
" )\n",
|
|
")\n",
|
|
"\n",
|
|
"g3 = go.FigureWidget(data=data, layout=layout)\n",
|
|
"\n",
|
|
"\n",
|
|
"# Add panel for water level\n",
|
|
"\n",
|
|
"trace_R_high = go.Scatter(\n",
|
|
" x = [0,1],\n",
|
|
" y = [0,1],\n",
|
|
" name='R High',\n",
|
|
" line = dict(\n",
|
|
" color = ('rgb(91,220,229)'),\n",
|
|
" width = 2)\n",
|
|
")\n",
|
|
"trace_R_low = go.Scatter(\n",
|
|
" x = [0,2],\n",
|
|
" y = [0,2],\n",
|
|
" name='R Low',\n",
|
|
" line = dict(\n",
|
|
" color = ('rgb(13,174,186)'),\n",
|
|
" width = 2)\n",
|
|
")\n",
|
|
"trace_dune_crest = go.Scatter(\n",
|
|
" x = [0,3],\n",
|
|
" y = [0,3],\n",
|
|
" name='Dune Crest',\n",
|
|
" line = dict(\n",
|
|
" color = ('rgb(214, 117, 14)'),\n",
|
|
" width = 2,\n",
|
|
" dash = 'dot')\n",
|
|
")\n",
|
|
"trace_dune_toe = go.Scatter(\n",
|
|
" x = [0,3],\n",
|
|
" y = [0,3],\n",
|
|
" name='Dune Toe',\n",
|
|
" line = dict(\n",
|
|
" color = ('rgb(142, 77, 8)'),\n",
|
|
" width = 2,\n",
|
|
" dash = 'dash')\n",
|
|
")\n",
|
|
"trace_tide = go.Scatter(\n",
|
|
" x = [0,4],\n",
|
|
" y = [0,4],\n",
|
|
" name='Tide+Surge WL',\n",
|
|
" line = dict(\n",
|
|
" color = ('rgb(8,51,137)'),\n",
|
|
" width = 2,\n",
|
|
" dash = 'dot')\n",
|
|
")\n",
|
|
"\n",
|
|
"data=[trace_R_high, trace_R_low, trace_dune_crest, trace_dune_toe,trace_tide]\n",
|
|
"\n",
|
|
"layout = go.Layout(\n",
|
|
" title = 'Water Level & Dune Toe/Crest',\n",
|
|
" height=200,\n",
|
|
" margin=dict(t=50,b=50,l=50,r=50),\n",
|
|
" xaxis=dict(\n",
|
|
" title='time',\n",
|
|
" domain=[0.0, 0.95],\n",
|
|
" zeroline=False,\n",
|
|
" ),\n",
|
|
" yaxis=dict(\n",
|
|
" title = 'Water Level (m)',\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"g4 = go.FigureWidget(data=data, layout=layout)\n",
|
|
"\n",
|
|
"\n",
|
|
"def update_profile(change):\n",
|
|
" \n",
|
|
" site_id = site_id_select.value\n",
|
|
" site_profile = df_profiles.query('site_id == \"{}\"'.format(site_id))\n",
|
|
" prestorm_profile = site_profile.query('profile_type == \"prestorm\"')\n",
|
|
" poststorm_profile = site_profile.query('profile_type == \"poststorm\"')\n",
|
|
"\n",
|
|
" poststorm_x = poststorm_profile.index.get_level_values('x').tolist()\n",
|
|
" poststorm_z = poststorm_profile.z.tolist()\n",
|
|
"\n",
|
|
" 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",
|
|
" # Update beach profile section plots\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",
|
|
" 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",
|
|
" # Relocate plan of satellite imagery\n",
|
|
" site_coords = df_sites.query('site_id == \"{}\"'.format(site_id))\n",
|
|
" with g2.batch_update():\n",
|
|
" g2.layout.mapbox['center'] = {\n",
|
|
" 'lat': site_coords['lat'].values[0],\n",
|
|
" 'lon': site_coords['lon'].values[0]\n",
|
|
" }\n",
|
|
" g2.layout.mapbox['zoom'] = 15\n",
|
|
" g2.data[1].lat = [site_coords['lat'].values[0]]\n",
|
|
" g2.data[1].lon = [site_coords['lon'].values[0]]\n",
|
|
" g2.data[1].text = site_coords['lon'].index.get_level_values('site_id').tolist()\n",
|
|
"\n",
|
|
" # Update time series plots \n",
|
|
" df_timeseries = df_twl.query(\"site_id=='{}'\".format(site_id))\n",
|
|
" times = df_timeseries.index.get_level_values('datetime').tolist()\n",
|
|
" with g3.batch_update():\n",
|
|
" g3.data[0].x = times\n",
|
|
" g3.data[1].x = times\n",
|
|
" g3.data[2].x = times\n",
|
|
" g3.data[0].y = df_timeseries.Hs0.tolist()\n",
|
|
" g3.data[1].y = df_timeseries.Tp.tolist()\n",
|
|
" g3.data[2].y = df_timeseries.beta.tolist()\n",
|
|
" \n",
|
|
" # Update water levels plot\n",
|
|
" df_timeseries = df_twl.query(\"site_id=='{}'\".format(site_id))\n",
|
|
" with g4.batch_update():\n",
|
|
" g4.data[0].x = times\n",
|
|
" g4.data[1].x = times\n",
|
|
" g4.data[2].x = [min(times), max(times)]\n",
|
|
" g4.data[3].x = [min(times), max(times)]\n",
|
|
" g4.data[4].x = times\n",
|
|
" g4.data[0].y = df_timeseries.R_high.tolist()\n",
|
|
" g4.data[1].y = df_timeseries.R_low.tolist()\n",
|
|
" g4.data[2].y = dune_crest_z.tolist()[0], dune_crest_z.tolist()[0],\n",
|
|
" g4.data[3].y = dune_toe_z.tolist()[0], dune_toe_z.tolist()[0],\n",
|
|
" g4.data[4].y = df_timeseries.tide.tolist()\n",
|
|
" \n",
|
|
" \n",
|
|
"def update_filter(change):\n",
|
|
" \n",
|
|
" # Get filtered impacts\n",
|
|
" observed_impacts = observed_impact_select.value\n",
|
|
" forecasted_impacts = forecasted_impact_select.value\n",
|
|
" \n",
|
|
" # Get sites with these impacts \n",
|
|
" site_id_select.options = df_impacts_compared.loc[df_impacts_compared.storm_regime_forecasted.isin(forecasted_impacts) & \n",
|
|
" df_impacts_compared.storm_regime_observed.isin(observed_impacts),].index.tolist()\n",
|
|
" \n",
|
|
" \n",
|
|
"site_id_select.observe(update_profile, names=\"value\")\n",
|
|
"observed_impact_select.observe(update_filter, names=\"value\")\n",
|
|
"forecasted_impact_select.observe(update_filter, names=\"value\")\n",
|
|
"\n",
|
|
"widgets.VBox([filter_container,site_id_container,widgets.HBox([g1,g2]),g3,g4])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 178,
|
|
"metadata": {
|
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"ExecuteTime": {
|
|
"end_time": "2018-11-19T03:23:37.582663Z",
|
|
"start_time": "2018-11-19T03:23:37.577662Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
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"([3.111490610630103, 3.111490610630103],)"
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]
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},
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"execution_count": 178,
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"metadata": {},
|
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"output_type": "execute_result"
|
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}
|
|
],
|
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"source": [
|
|
"g4.data[2].y"
|
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]
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}
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],
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"display_name": "Python 3",
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"r": {
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"delete_cmd_postfix": ") ",
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