{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook will load data, perform a tidal analyis, compare with observations, plot the results, and save the analysis in a spreadsheet. Eight Tidal Constituents: M2, K1, O1, S2, P1, N2, Q1 and K2 are considered.\n", "- Links consistuents that cannot be separated over 40 days\n", "- Corrects nodal calculations" ] }, { "cell_type": "code", "execution_count": 57, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# imports\n", "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import netCDF4 as NC\n", "from scipy.optimize import curve_fit\n", "from salishsea_tools import tidetools\n", "from salishsea_tools import viz_tools\n", "from salishsea_tools import bathy_tools\n", "from salishsea_tools import nc_tools\n", "#from nowcast import figures\n", "import scipy.io as sio\n", "import collections\n", "import pandas as pd\n", "import csv\n", "import math\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Run Details" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, let's define the run that we will be analyzing. We can analyze a different run by changing runname in the cell below. A spreadsheet called tide_runs.ods contains a list of runs that we can look at." ] }, { "cell_type": "code", "execution_count": 58, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "../../myResults/NEMO36_Tides/GmO_N36_D/\n" ] } ], "source": [ "# pathname for data - all of the tide runs are stored in this directory\n", "#path = '/data/nsoontie/MEOPAR/SalishSea/results/tides/'\n", "path = '../../myResults/NEMO36_Tides/'\n", "\n", "#the run we want to analyze\n", "runname = 'GmO_N36_D'\n", "nemo = '3.6'\n", "start = 'apr2003' # 'oct2002' or 'apr2003' 'dec2015'\n", "\n", "#joining the two string together\n", "name = path +runname +'/'\n", "\n", "print (name)\n", "if nemo == '3.4':\n", " timeinc = 0\n", "elif nemo == '3.6':\n", " if start == 'dec2015':\n", " timeinc = 3659558400\n", " elif start == 'apr2003':\n", " timeinc = 3259872000.\n", " \n", "TSout = {'West': {'M2': {'Amp': 0, \n", " 'Pha': 0},\n", " 'K1': {'Amp': 0,\n", " 'Pha': 0},\n", " 'O1': {'Amp': 0,\n", " 'Pha': 0},\n", " 'S2': {'Amp': 0,\n", " 'Pha': 0},\n", " 'N2': {'Amp': 0,\n", " 'Pha': 0},\n", " 'Q1': {'Amp': 0,\n", " 'Pha': 0}\n", " },\n", " 'North': {'M2': {'Amp': 0, \n", " 'Pha': 0},\n", " 'K1': {'Amp': 0,\n", " 'Pha': 0},\n", " 'O1': {'Amp': 0,\n", " 'Pha': 0},\n", " 'S2': {'Amp': 0,\n", " 'Pha': 0},\n", " 'N2': {'Amp': 0,\n", " 'Pha': 0},\n", " 'Q1': {'Amp': 0,\n", " 'Pha': 0}\n", " }\n", " }" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We'll also load the bathymetry data in case we want to look at that. The package **tidetools** has a function get_SS_bathy_data() that returns bathymetry and grid data." ] }, { "cell_type": "code", "execution_count": 59, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# grid\n", "grid = NC.Dataset('../../nemo-forcing/grid/bathy_downonegrid.nc')\n", "bathy, X, Y = tidetools.get_bathy_data(grid)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Observations" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "Next, we can load some observations from a text file: /data/nsoontie/MEOPAR/analysis/compare_tides/obs_tidal_wlev_const_all.csv Note: This file contains a mix of M2/K1 measurements from Foreman et al (1995), US tidal harmonics, Foreman et al (2004) and Foreman et al (2012) (for Northern tides).\n" ] }, { "cell_type": "code", "execution_count": 60, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " site lat lon M2_amp M2_pha K1_amp K1_pha\n", "0 Sooke 48.36700 123.7330 43.8 282.7 56.9 266.4\n", "1 Port Angeles 48.12500 123.4400 51.8 307.4 66.9 261.4\n", "2 Pedder Bay 48.33100 123.5490 34.2 308.0 62.7 269.0\n", "3 Esquimalt 48.43300 123.4330 36.7 317.1 64.3 268.1\n", "4 Clover Point 48.40500 123.3470 40.3 320.3 64.2 269.8\n", "5 Victoria 48.41700 123.3670 37.3 316.1 62.7 269.2\n", "6 Finnerty Cove 48.47300 123.2950 44.7 357.7 70.8 277.5\n", "7 Port Townsend 48.14500 122.7550 65.2 350.0 75.0 270.8\n", "8 Sidney 48.65000 123.4000 55.4 5.9 76.7 277.6\n", "9 Patricia Bay 48.65000 123.4500 60.3 14.4 76.0 281.3\n", "10 Maple Bay 48.81700 123.6170 68.5 17.0 79.3 281.2\n", "11 Fulford Harbour 48.76700 123.4500 58.2 12.7 75.3 280.0\n", "12 Ladysmith 48.98300 123.8000 70.8 16.3 79.8 281.8\n", "13 Patos Island 48.78300 122.9670 68.0 25.0 79.0 285.6\n", "14 Tumbo Channel 48.79200 123.1080 72.6 31.0 81.1 286.9\n", "15 Whaler Bay 48.88500 123.3250 83.4 32.9 84.7 287.5\n", "16 Silva Bay 49.15300 123.7000 92.2 32.0 86.5 286.7\n", "17 Ferndale 48.83300 122.7170 72.3 23.8 80.1 283.6\n", "18 Blaine 48.99000 122.7600 77.4 25.1 82.3 284.3\n", "19 Tsawwassen 48.99000 123.1330 81.1 27.8 83.4 284.8\n", "20 Sandheads 49.10000 123.3000 86.9 30.9 83.7 286.5\n", "21 Point Grey 49.25000 123.2670 94.5 33.9 90.6 287.0\n", "22 Point Atkinson 49.33300 123.2500 91.8 31.2 86.2 286.1\n", "23 Squamish 49.70000 123.1500 94.2 31.2 87.4 286.8\n", "24 Gibsons Landing 49.40000 123.5000 94.7 30.1 87.2 285.2\n", "25 Halfmoon Bay 49.51700 123.9170 96.4 31.5 88.0 285.8\n", "26 Irvines Landing 49.63300 124.0500 98.8 31.9 88.0 286.7\n", "27 Winchelsea 49.30000 124.0830 95.2 32.6 87.5 286.7\n", "28 Northwest Bay 49.30000 124.2000 95.6 32.7 87.2 286.7\n", "29 Cherry Point 48.86300 122.7570 73.2 21.8 81.5 281.9\n", ".. ... ... ... ... ... ... ...\n", "47 Sneeoosh Point 48.40000 122.5467 102.6 18.3 78.4 282.0\n", "48 Turner Bay 48.44500 122.5550 94.4 16.7 75.4 281.4\n", "49 Armitage Island 48.53500 122.7967 57.3 0.5 75.6 276.4\n", "50 Friday Harbour 48.54670 123.0100 56.5 9.7 75.8 278.8\n", "51 Richardson 48.44670 122.9000 52.2 340.1 71.3 270.9\n", "52 Cherry Point 48.86330 122.7567 73.4 22.8 81.7 282.8\n", "53 Blaine 48.99167 122.7650 76.3 24.8 78.4 286.3\n", "54 Port Renfrew 48.55000 124.4300 70.8 241.1 45.3 254.1\n", "55 Little River 49.74000 124.9200 99.4 32.9 90.2 287.0\n", "56 Twin Islets 50.03000 124.9300 101.3 35.4 90.4 287.5\n", "57 Campbell River 50.04000 125.2400 82.5 18.4 84.6 284.0\n", "58 Seymour Narrows 50.13000 125.3400 94.6 320.1 69.2 272.1\n", "59 Owen Bay 50.31000 125.2200 85.0 319.9 67.8 272.7\n", "60 Big Bay 50.36000 125.1300 75.5 14.9 83.3 283.5\n", "61 Chatham Point 50.33000 125.4400 90.3 305.1 65.4 270.5\n", "62 Yorke Island 50.44000 125.9700 117.1 271.8 55.8 260.0\n", "63 Powell River 49.86000 124.5500 100.7 34.3 90.4 286.6\n", "64 Lund 49.98000 124.7600 102.2 35.4 88.9 287.9\n", "65 Nymphe Cove 50.13000 125.3600 61.5 350.4 77.0 279.9\n", "66 Brown Bay 50.16000 125.3700 93.5 315.9 67.9 270.1\n", "67 Maude Island E 50.13000 125.3300 55.6 7.4 81.1 283.9\n", "68 Welsford Island 50.22000 125.1300 99.4 35.1 91.1 286.9\n", "69 Redonda Bay 50.26000 124.9900 97.5 36.7 87.1 287.4\n", "70 Channel Islands 50.31000 124.7500 102.6 35.9 89.9 288.0\n", "71 Turnback Point 50.42000 125.1200 102.0 37.0 91.7 287.6\n", "72 Orford Bay 50.59000 124.8600 101.5 37.2 90.3 288.1\n", "73 Waddington Harbour 50.87000 124.8700 103.4 38.0 89.2 288.2\n", "74 Shoal Bay 50.46000 125.3600 89.9 307.5 66.6 269.6\n", "75 Kelsey Bay 50.39000 125.9600 117.0 276.3 57.7 261.4\n", "76 Tacoma 47.26670 122.4133 113.9 11.8 83.8 277.9\n", "\n", "[77 rows x 7 columns]\n" ] } ], "source": [ "filename = '/data/nsoontie/MEOPAR/analysis/compare_tides/obs_tidal_wlev_const_all.csv'\n", "filename = '../compare_tides/obs_tidal_wlev_const_all.csv'\n", "\n", "harm_obs = pd.read_csv(filename,sep=';',header=0)\n", "harm_obs = harm_obs.rename(columns={'Site': 'site', 'Lat': 'lat', 'Lon': 'lon', \n", " 'M2 amp': 'M2_amp', 'M2 phase (deg UT)': 'M2_pha',\n", " 'K1 amp': 'K1_amp', 'K1 phase (deg UT)': 'K1_pha'})\n", "print (harm_obs)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is a list of observations that we can compare with our model output. Now we have a struc object called harm_obs that contains the data printed above." ] }, { "cell_type": "code", "execution_count": 61, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " site lat lon O1_amp O1_pha P1_amp P1_pha \\\n", "0 Neah Bay 48.385 -124.616 30.90 231.50 15.50 244.60 \n", "1 Port Renfrew 48.537 -124.476 28.30 234.80 14.07 250.60 \n", "2 Port Angeles 48.129 -123.400 39.10 241.60 20.70 259.40 \n", "3 Victoria 48.413 -123.399 37.00 247.80 19.70 264.60 \n", "4 Port Townsend 48.112 -122.758 45.00 249.90 23.90 268.40 \n", "5 Bangor 47.748 -122.727 46.60 251.90 26.00 273.90 \n", "6 Seattle 47.605 -122.338 45.80 255.40 25.20 274.50 \n", "7 Tacoma 47.267 -122.413 45.90 255.10 25.50 277.20 \n", "8 Cherry Point 48.863 -122.758 45.60 260.00 25.60 281.40 \n", "9 Friday Harbor 48.540 -123.010 42.30 256.40 23.60 274.90 \n", "10 Hanbury Point 48.580 -123.172 43.60 253.60 23.40 271.40 \n", "11 Sidney 48.658 -123.383 44.40 255.80 24.20 275.20 \n", "12 Fulford Harbour 48.765 -123.453 43.00 257.80 23.40 277.80 \n", "13 Patos Island 48.783 -122.967 45.50 262.10 24.50 284.60 \n", "14 Tsawwassen 48.991 -123.137 47.20 261.80 25.90 282.60 \n", "15 Point Atkinson 49.334 -123.250 48.30 263.20 26.80 283.10 \n", "16 Winchelsea Islands 49.300 -124.083 47.70 263.50 27.40 286.20 \n", "17 Little River 49.744 -124.918 49.26 263.94 28.62 285.67 \n", "18 Twin Islets 50.029 -124.936 49.29 264.24 28.62 286.97 \n", "19 Campbell River 50.042 -125.247 48.46 263.74 24.60 280.57 \n", "20 Seymour Narrows 50.135 -125.347 41.27 254.54 21.28 271.47 \n", "21 Owen Bay 50.311 -125.223 38.19 251.34 20.97 267.47 \n", "22 Big Bay 50.394 -125.136 46.63 262.44 25.33 282.07 \n", "23 Chatham Point 50.332 -125.441 37.46 249.04 20.39 265.97 \n", "24 Yorke Island 50.444 -125.975 32.16 241.04 17.10 257.67 \n", "25 Alert Bay 50.588 -126.937 30.60 239.84 16.00 251.77 \n", "26 Port Hardy 50.720 -127.476 29.70 233.50 15.40 245.50 \n", "27 Montagu Point 50.639 -126.213 31.10 237.60 16.60 251.30 \n", "28 Siwash Bay 50.680 -125.763 31.30 239.40 17.10 253.20 \n", "29 Winter Harbour 50.490 -128.044 27.26 231.20 13.39 242.90 \n", "30 Bella Bella 52.177 -128.111 27.80 236.20 14.20 247.20 \n", "31 Tofino 49.144 -125.937 24.50 227.20 12.30 237.90 \n", "\n", " Q1_amp Q1_pha S2_amp S2_pha N2_amp N2_pha K2_amp K2_pha \n", "0 5.50 222.10 22.80 272.6 16.60 222.80 6.00 266.40 \n", "1 5.04 225.90 21.04 268.7 15.15 217.30 4.92 263.10 \n", "2 6.60 232.80 14.60 326.4 11.60 280.10 2.70 332.70 \n", "3 6.10 236.00 10.20 332.8 9.10 292.00 2.00 341.90 \n", "4 7.40 243.60 16.80 13.0 14.20 321.80 5.00 18.30 \n", "5 8.00 247.20 25.70 29.5 20.80 333.50 7.30 28.50 \n", "6 7.50 250.60 25.80 37.9 21.20 340.20 7.20 36.50 \n", "7 7.60 250.60 28.20 37.8 22.50 341.20 8.20 39.60 \n", "8 7.60 253.20 17.90 50.3 15.40 354.50 5.00 50.50 \n", "9 6.80 244.00 13.30 34.9 12.20 341.30 3.50 40.60 \n", "10 7.50 247.00 12.70 18.0 11.30 324.90 3.80 37.90 \n", "11 7.50 247.00 13.20 26.8 12.00 334.60 3.80 37.90 \n", "12 7.00 251.60 13.90 37.2 11.90 342.60 3.90 40.00 \n", "13 7.80 253.20 16.70 54.8 14.30 354.20 4.90 58.50 \n", "14 6.90 258.50 20.00 55.0 17.20 0.20 5.60 59.40 \n", "15 7.70 258.80 22.90 59.9 18.40 2.90 6.20 59.90 \n", "16 8.00 257.40 23.60 62.0 20.60 5.60 6.40 64.60 \n", "17 8.38 257.20 25.02 61.6 21.64 5.42 6.80 62.56 \n", "18 7.89 258.59 25.82 64.8 21.82 9.12 6.92 63.66 \n", "19 8.08 252.39 20.27 43.6 19.20 2.82 5.42 49.76 \n", "20 7.25 244.99 30.27 339.6 20.48 290.52 8.29 333.06 \n", "21 6.37 244.89 27.52 339.6 17.89 290.92 6.89 335.26 \n", "22 8.20 224.79 19.29 35.3 15.94 346.02 4.72 35.56 \n", "23 5.82 243.69 29.44 326.8 19.57 276.22 8.05 322.36 \n", "24 5.33 234.89 38.56 301.2 25.73 248.12 10.70 293.76 \n", "25 5.18 231.09 40.63 290.0 26.97 237.72 11.19 279.96 \n", "26 5.00 224.30 42.00 281.4 27.30 227.80 10.90 276.20 \n", "27 5.20 230.40 49.60 292.7 31.60 238.70 12.50 285.50 \n", "28 5.20 232.50 50.60 296.7 32.70 242.50 14.00 290.00 \n", "29 4.89 224.50 29.55 273.1 20.74 219.00 7.87 265.80 \n", "30 4.90 225.60 40.10 280.0 27.10 227.50 10.90 271.10 \n", "31 4.40 219.60 27.90 269.5 20.30 215.60 7.60 261.60 \n" ] } ], "source": [ "filename = '../Idalia/other_constituents.csv'\n", "\n", "harm_other = pd.read_csv(filename,sep=',',header=0)\n", "harm_other = harm_other.rename(columns={'Site': 'site', 'Lat': 'lat', 'Lon': 'lon', \n", " 'O1 amp': 'O1_amp', 'O1 phase (deg UT)': 'O1_pha',\n", " 'P1 amp': 'P1_amp', 'P1 phase (deg UT)': 'P1_pha',\n", " 'Q1 amp': 'Q1_amp', 'Q1 phase (deg UT)': 'Q1_pha',\n", " 'S2 amp': 'S2_amp', 'S2 phase (deg UT)': 'S2_pha',\n", " 'N2 amp': 'N2_amp', 'N2 phase (deg UT)': 'N2_pha',\n", " 'K2 amp': 'K2_amp', 'K2 phase (deg UT)': 'K2_pha'})\n", "print (harm_other)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We don't have model output at all of the above locations. The model outputs are listed below. There is a location.nc file in the run directory for each of the stations listed below." ] }, { "cell_type": "code", "execution_count": 62, "metadata": { "collapsed": false }, "outputs": [], "source": [ "stations = ['PortRenfrew','SheringhamPoint','PedderBay', 'Esquimalt',\n", " 'Victoria','CloverPoint','FinnertyCove', 'FulfordHarbour',\n", " 'TumboChannel','PatosIsland','WhalerBay', 'Tsawwassen',\n", " 'Sandheads', 'PointGrey','PointAtkinson','GibsonsLanding', #'WinchelseaIs',\n", " 'HalfmoonBay','IrvinesLanding','PowellRiver', #'LittleRiver', \n", " 'Lund',\n", " 'TwinIslets','CampbellRiver','MaudeIslandE', 'NympheCove',\n", " 'SeymourNarrows','BrownBay','ChathamPoint','KelseyBay',\n", " 'YorkeIsland']\n", "numsta=len(stations)\n", "#again with spaces because the text file likes that\n", "stations_obs = ['Port Renfrew','Sheringham Point','Pedder Bay', 'Esquimalt',\n", " 'Victoria','Clover Point','Finnerty Cove', 'Fulford Harbour',\n", " 'Tumbo Channel','Patos Island','Whaler Bay', 'Tsawwassen',\n", " 'Sandheads', 'Point Grey','Point Atkinson','Gibsons Landing', #'Winchelsea',\n", " 'Halfmoon Bay','Irvines Landing','Powell River', #'Little River', \n", " 'Lund',\n", " 'Twin Islets','Campbell River','Maude Island E', 'Nymphe Cove',\n", " 'Seymour Narrows','Brown Bay','Chatham Point','Kelsey Bay',\n", " 'Yorke Island']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, we can plot these locations on a map of our domain." ] }, { "cell_type": "code", "execution_count": 63, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 63, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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+fXutXLkyrJ8tIFGZSK8+Gi+MMYskfWWt/WnIfc0k7ZU01Fr7QQXPt78P+cfT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mSEv+7znAAXI0bSXBjoz/H6RtO8F+8KgI/VDvOmGwCYWjCYYUu/Xc1TE+cAsPl+4P/cz5/vvYLC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AIg9ZlepuK3HeEuswl3MSWTzL5qIJY7jl6SPYZp0PKGmz+M/7W5D1o2AHbLjOJAD++cpe1LdV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\nQAb4RgE4O7N19dkNCLq7ccT69Tj1ne8EAHz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CXVEURXHEhlJQbUw3vEHsIj1LTW39JTCp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Ez6KUOz6IrVQCXu6wxK0BUKheLM4rSSdECk76VxPZWPdcTYrJ8uzdrx538QyH5JCujozTZu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\nvyqfASdrmvakruvlmqbNAWYA9w/2IBUKhUKxa7GnR9Hb0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UqgKxQKhUKhUAw5Enba5c2Z\n3fYSbwq6ufb9o3nwmPe4cL/FuA6MsHz7MM787w9ZU5vPlPxaQlEr25rTk84vws6qRbFqMUJRa6sI\nuVw9xtzRW0mxhyltysQfSUTfR2Q0o+saWxqz4nsDlGQ1sqK6gEqvaVa3m4tzgKuN9yUtJEu9W8rC\nY5pEvt1JNeJFHomU59uhOlUi7U0uiGiwNVOEcU2qiF9XBPx2cYLfnvTZuJP6koMIc7uRjm7pY455\nTYqMxZxQiBh15wduS0T5i6VVH39qAVr6dh1Fv6Ki6LsfSqArFAqFQjGIqCi6omdobZ5JWzhd79wB\nftn2Io567hyc1jBT82vITfEbEW+dVHuIGl9qUv25iU5Ut7K0qhCnLcJ1cxbSHHRS6UnDF3ZwyKhS\n/nbya0RjFkqTJglS7UFGZzbRGHCx3Zuc9u7BbQ+ztTEr3n5uj8A0gotp4sye44c6o57bqkvEWUdE\nd9gq6eS6JinlDS7jWIt87Doi4P1mX/WwRLS3G9kLw7yyjy0mdeOOKDS4JQpvj4rApw8O6hrS29wa\nk3FHLDLuD0rhJznwQv2OvEOKAUSJ9N2LPegvp0KhUCgUQwMl0hW9pWdt4WSHYNTOkqrWKfBXv3cc\nV793HBbNiITGJwBk/db6CTz4xRwuO+ArXhv2T9bW5TIuuwFPyMG25gxGZjaxqSE7fr5sd4BRmU1U\neNJpCCRE/4ScOgC2NElU3apFieq7SWu17ogajuf2qLRAa3ZCVZpEzGOaiHN7LJH6PsxIdfca0Xfz\ndTNlvcEl52tyivg2zx20tb6mSb0bJtVKynxfBHqdW2rpfXb5WkQ1SbnfiBLnCsUgsgfkHCkUCoVC\noVDsCSS3ftNJttPWEGHeWbp5MGrnnk8O5ayXT+O1dZMIRa28tm4SRzx7DkuqCklzhChvTpi95aW0\nMCzNy7q6XHwhe/xao7OkFtmsVd9jxLnZdswaS7ib57eIQ3uymds9MekPHraIYE8JS3szM4U8MwDZ\nfjkuLSSp7FZdjOWiRnQ+ZJGU+KhFIut+W+Ljjlpai/besCpfJhVMQ7jZ5cqRfRdCTfruPqgIukKh\nUCgUOwEVRVcMLK1T5DtLi0+mKejm5dVTeXn11Fav3/LhEby6djILS0fGXytI9TE+p54FW8YQjiX6\nqQciNsJRKydNXMfiiuFU+1Kp8qbhCbl2/JZ2BUxxbLqbewxTN0cUHgol9gtbJWINIrwzAwlhbNaA\nB4yf6WFXohUbSC36cI+kt7vCCTM3R1RqyJ29jJ7/JEfWbxvX13SJ4m/LgL239+5cip2KSnXfPdD0\n7vOlFD1A0zRdvZcKhUKh6C1KpCuGEhYtZvRP17o1dxuT1UAkZkkysJPfQQ8d+y4Xz/oaf9hOnd/N\n00v34Y+LDqA5uBuL9JuM9+o3RiT8khRJOd+eBh4HlDRKuvij/sQx1xrt0sze5i321uc0xX6lUXu+\nLUOM3KwxcXk3+4+7ImIiBzC9WtZt+6h3xkWpYkjns8PnI1tvyw7APpXwihLpuxJKoA8cmqah67rW\n/Z47hkpxVygUCoVCoVAAkgIf1a1txLkeT5FPZktjdht3eUmxv+mDI5n79Hnc8fE8FlcMJ6ZrRGK7\n8U/Omzq4t4BN0td1Es7uXof0Nzf3/52R4p4dEFO5Iq8sBT6pVbfFpJ48r0WeF3rFuK0uRQzkIpaE\nmZzHKUvYIktnJGu3K51QlikTAGb7tmQm1bafNFAMedSk766PiqD3EyqCrlAoFIq+on5QKRS7MLeR\niHbfY0xknGtMXFQYbe3MHugTxUQPdzgRbW/Lzca5THf3UuNc63Nbn3PfSticJUI+PSRCfrxh5pbX\nkhiLSbI4N//kHDROJg62ZiZS7E2O2Sjr/1Z3PE7FkEZF0vufwYqgK4HeTyiBrlAoFIodQYl0xe6E\n2RZOM9q47XFcZTizb8gxTOIsIqRTwjCiWWrK7bH2IjqZG433rd6oVd9i9Jt/a4KsZ1VArZHynhaC\nsQ0SgQcR6JAwnzNp+2cm5wBZh6wJ93gNSZk/YT082dybu1YMIZRA739UirtCoVAoFAqFYpdExxJP\nl98jabHLomuQGpZ09IBNRHBpJvgc8vzmLn6K3xuVJdsvBnDpQahOlZrzIo+YzAWscm6vQ7ZVGfXq\nZqp7TJPFdHm/nUQk/cxcGV/YarjDG+tJtXJ+Jc53adSk766LEugKhUKhUAwBVLRDodiNMOvOC72y\nmAJ5e6osMU0EfFcRdJOIxehP7pBzOSNybFkm1KZKTXrIKoZ01anSdi1kTRxrLqYIj1ikFt4VkXP5\nbdDolEj9qCZxgd+naiDfHcUgoUT6rokS6AqFQqFQDBGUSFcodhMeCEsP89wWWWZVyDKuXkzd6l1g\n72E7NGdUluEeWWyx1os1JiZvmi7nzAxKxN2qJyYGwtaEqZzXIYZyjqik4De6wOuEoE0Ee3Gzip4r\nFDsRJdAVCoVCoVAoFIr+xqJLnblVF7HujsjzfSoltbwqDX7VgXt6W+4xatVTQ7JkBaSmPaaJKNdI\nmNBZdRHtupHaLsb6xn66OLabru3NTkmzN/utT6yDvaplEkCx26Ci6LseyiSun1AmcQqFQqHoL9QP\nKoViN+WiVFmvzpf1fhWyfijU9XFXOqHBMIv7aIysKw03d9MIzh6F/Sphao2Y0YFMEsQ0WQOsNZzg\nlxWK2P94TCKSH7XAmStEoD+lIui7GypDa8cZLJM420BfQKFQKBQKRe/Qb79diXSFYnfhVuP3fLMT\n/MbjrnqVd8Tvg3CRDVblS2o6SI/0ZPbfBlFNFo9DauBjmqS0azosKZJ2agA1xkRBkREt9xmu8/aY\nsU0JdIViZ6FS3BUKhUKhUCgUioHCdFJvMozY1uZJmnpWQFLSrT3MwHQb7u0FPll0TZaATUS5KyJ9\n0B1R6aFekyp150HDQK48QyLpFl0c4dONWnVHVGrPTfO5FvvAvh+KnYKa9N11UAJdoVAoFIohiEpH\nVCh2E4JWcUo3ndsh4azeU66zSSq6WXv+1QgIWWQBMYFzR8TRPWwFmy7p7JuyYVuGuLtbjXp4sye7\nuVh0MaGzx8BnFyd3xW6JEum7BirFXaFQKBSKIYpKdVcodgFux3BLN0zbzHXEIo9rXCKqy4z08rwW\nEduF3p5f47cRuMEqDu0hn4hql5Hq3uCS9YYcWZs15avzZXFG5Lk7YkTzjfGaYh8S+0yulW0KhWKn\noSLoCoVCoVAoFApFX4kZqea68Ti553jYAhXp4thuj8pS4IPsgBG1jva83dp9UYl4u8MwzCsR8YA1\nkUK/NleW7WlSax7TJHrvdSSNE2MCIWmtkUi1D1tlUey2qEnfoY+KoCsUCoVCMYRRUXSFYohjOqSb\nkeegEf8y09mjxvOSRvhLL6LmHeF1SPq6OwLjGmBFgQjqmAZbsmQflxEN99shIyiC3qJLOrxmjDNm\nRM+jGqSHZD/zHrICOzZGxZBHu/NOVUY1hFERdIVCoVAohjjqh5RCMYS5k0QUPWKRqLnXIZHzinRJ\nH3dFpK3ZjpIZEBFtCurMoETkU8ISkXdGJVpflSbCPGyMJ2iFiBEdj1gT0fSUsLRVG9sgywv18KeW\nHR+nQqHoMyqCrlAoFAqFQqHYc7hFSzin90dyym2ICNaMczY7ZW2awBX4ZN1dr/OeYPY3TwtJCn22\nX64zzCuRemsskaJuRvbNCH68Rt54nBaSiPq4ekmdf6F+h4b21Pde4ZyZS1u91hK2s7khmzfWT+T+\nzw6mKejeoWsMBpuveJiYrjHukSt39lAGFBVFH7qoCLpCoVAoFLsA6oeUQtFPmK3H+qtyxDxf0AZb\ns6SVWr07EdFOC8nSH/gciXr3bL8I7AKfOLC7IpKubrZQM13aDR84bFE51mypNswHE+okXX4HxbmJ\nrmu8smYydyyYxx0L5vH3ZTPIcgW4/uDPWHTB38h0+vvlOgOJrmvd77SboMqnhiYqgq5QKBQKxS6C\nqkdXKPqBinQxaaOH5mxdcb1NTuMzjNhCVonOZxomcDENHunHmm4zTd6qy6SAIyoTBJouIt0WTTjJ\nm9iS7tMRgTxDJI9tkPWzjf03PuCVNZN5bvnM+PNr3gux6IK/MSWvlssOXMTdnxzWr9dTKHY3lEBX\nKBQKhUKhUOx+mEknbee00kJQlQqXWiTq/OAORLcDNhHE9UbqtjUGKVExWuuPlPa2PBCGy9wirssy\npGVbdarR31yT9HZdE2d4s4WamS9rusVPrZHI+nCP9D0fYPwRB88um8n9R73PAcO3xV/vKpX89sM+\n4rbDPmbeM+fyaemYVtt+Mn05Vx/0OZPzavEEnby7cRzXzz+af572EnNHb8V61x3tznfMuA1cceCX\n7D+8gnRnkPLmDF5ePYV7Pp1Lc1Da1M0dvYWPznkGXdfQNJ3obYnzPLN0Jue/dkq/vB9DDZXqPvRQ\nKe6Kbtm4ESwWWX75y673XbkSfv5zGD8eUlISx/3oR7I9Gk28dswxAz92hUKh2N1QP6QUih3E55Ae\n4kErNDn7do7/c8PFqbA9VQSyJSZCPcc/cOLc5FG/XGtUk4jy3BapgTdr3s06c02XOvQYsuS3SJQ9\nLSTjtMXgcd/AjTMJzbC4T26x3lUquY7W4fZr53zGc6e+zKjMJp5eug9PLd2Hqfk1LPz5k2Q6gx0e\nc9thC3j7rH+w//AK3lg3kT98NZv1dblcM+dzPjvvKVLtYri3pTGLOxbMoznopDHg4vYFh8dT9V9Z\nM3nH3oAhjsrMGlqoCPoAYOli2iMtDYYNg333hR/8AE47DWy7yKegdVOS8+GHcOKJEAwm9u3smO7O\ntTOIRuHVV+Gtt+DLL2H7dvB4ICcHRoyAww+HU0+F2bN39kgVCsWejkp1Vyh2ANMBvTal98feYBiw\nVRkp7WY/cZsO6JAa7o8Rds8THlmfbtSOb8qW9HrTKK6tMVyOHxolUkyOkeJ+f2RQhppqD3LuzKXo\nusaX5SP6fJ4xWQ3cfcSHVPtS2fcvF1LpzQDgpg+O4vkfvMQZe33XTqDPG7OZ2w9bwMLSUZzwwll4\nQ4kJmZ/tvZRnTnmFOw9fwDXvHUtpUxa//mQe581cig4qFV+x09hFpOGuR2cC1OeDTZskKv2f/8D0\n6fDSSzBhwuCOr7d0J7gB/u//IBSSfc47D+bOhSyjJWdxce/ONdi8/TZcdRWsXSvPk8e2fbssixfD\n734Hxx8PjzwC48btnLEqFAqFQqHohq4STR71w1k5EnXO7kF9+K0a/NqI/ZoO6UHjJ7Tp3J5rtCb7\n3SAJdJPhHhHeE+rhuwLw2xJ90M3fMlGLZApMMMT8jqT094BTJ6+hJFvq2oelevnepLUUpXnZUJ/D\nY18f0OfznjV9OVZN59FFB8bFuckN84/i9KmrsGh6q9cvP+ArdF3jl2+c3EqcAzy3fCZXzv6Ss6Yv\n55r3ju3zuHYXVKr70EEJ9AHmlVdAT/pb0dAAn38Ozz8Pfj+sWCGp3kuWJMTsUGPcOIkud8XWrbBm\njQjbE0+EJ57oeD+rtftzDTYPPADXXy+fk6bB8OGS3TB9unwm1dXw2WfwxhsywfL223DggRJtP/jg\nnT16hUKxp6Ki6ApFF+gkBGpbLk0BAhJ19jkAT+fnucXobX69Bh4HeI3ItNnCzBmRlHFXBH47OBHp\nVoQtYhzX7JSU98q0RO05gMcQpTO2y3r/bfD5wA1H03S+N2kt35skEQ9/xMaWxiyeWz6D+z87OF7v\n3RdmFlYBsLB0ZLttZc1ZlDVnMDqzqdXrs0eUE45Z+NG0lR2e02GNkp/SQpbLT2Ng6LeAG2iUSB8a\nKIE+QJhi7+ST22875xy48ko47DCoq4PSUrj/frj33sEfZ39RVpZ4vM8+O28cveXJJ+G66+Sz0jS4\n5RZZ7G08Uy65BKqq4IILJAW+vh5OOAG++Ubq7RUKhWJnoES6QtEJEYsIdM1IPU/mMSPavZ+Rbn1p\nSuvX254nYBPR2+AWozWrnjBcyzIi8IMtzq83fsJHjOuaaftbM2Vti0l6u0UHr13arg3zwe+DAzos\nXdc499VT+MfyGf1+7kynjH27L63D7du9ae0Eem5KC1ZN57a5H3d6Xh1Ic4SUQFcMGZRA30lMmQK/\n+Y2YrmmapLnvygI9kJQh5uyj38pgs349XH55Ip390UdFiHdGYaFEzU87TdZeL/z4x5L6PpTS9RUK\nhUKh2OOJaSJQYxrQJu38EkOQL7SIcIWOxTnAfVE4P1VUXAxJF7cniXGr3vFxA8mtGkR0iZaHrJAZ\nhCIPrCyQe7bGZD9Nl/sP2MHrgFw/XGMXJ/gBRGs7IdIJMV3Dbu04rTLL1b70oDkoPzCHpXpZU5vf\nbvuwNG+715oCLjRNJ/931/doTAoVRR8KKBf3nciJJ8pa16UuPdDmb1EgAP/7H1x6qaRU5+WBwwHZ\n2ZJ+feml8N13vbvm4sUiSmfMgNxcOV9uLhx0kESSFy9uf0xXLu6HHNLakV3XJQJt7m+xtI5G99bF\nfd06Gdf++0NBgYw3Kwv22w8uuww++qh395/MPfdImQFIpkNX4tzEYoGnnpKx6DosXQr//W/Xx0Qi\n8Pe/w+mnQ0mJGAW6XDB6tFz3kUegtrbrc3z3ndTIz5wpn5fLJcZ1p5wC//pX9+Pur++S+Xk7HInX\n/vlPOPpoKCoCt1vu8fzzZQJEoVAMPOqHlELRAS12qcduWxN+USqUZcpijcl+qSG4rpOY1TV2iaLX\npkBtqkSmNSOCntciEWrLIIv0iEUc6P02qEyHNXmyzvHLWMzIuUWXPumFXhHnXoe81tm9DjINARfD\nUn1YtFi7bfsntWMzWVJViKbpHDKqtN22kRmNjMxobvf6l+UjyHYFmJxX0+NxRXUNq7YTJl6GECoz\na+eiBPpOJL/N5F9jY+vnEyZItPbPfxbh3NAgAre5GVatktdnzIDbbuv+Wj4fnHEGHHAA/PGPIsYa\nG+V8jY2waJHUYh9wAFRWdnyOjqLEZmp48rbk1zStY1f77iLOkYhMJEydKuP69lspB4hGxVl96VJ4\n7DE48kj44ovu778t9fUiLE3uuqvnx2ZnwxVXJJ7/4Q+d77toEUycCOeeK0K+tFQmBcJhKC+HN9+U\ncoezzur4+GhUzPdmzoTf/148Cxob5fjKSnjtNfjJT6QWvqaL/3v667uU/Ln5/TLBcNZZ4uBfXS0m\ngaWl8PTTcr7587s+n0Kh6B+USFco2qBrRn25wWVG+nJlukSVvykyUuCR9PTOUtQfCEvauFnjbYvJ\n4ojK2h4dNDf0OPcaafZ5fpkk6AjdyCBwRmQpzZSJha7udZBZtK0YmyXGeTOXtHr9nBlLmDOyrN3+\nL6yYTiRm4bIDFlGc3jqV/b6j5mO1tBf6D385G03T+dvJr1GY1t5rwG0LcUBxeavX6lpSyE/14bAO\njfdJsecxNKbQ9lDaCqqM1oaUBAIS6Tz6aBFoxcUSjd62TWqfX3xRhOw990j6dWcRYL9fHNWXLBGB\n5XZLX/I5c6SFWFOTCL8335Roud6LScP77hPhvHy5iDtNE8F4+umJfbpqO9cRui6R4bfekvPZ7dLe\nbN48mdTw+WD1anjnHblub8ZrsmCBiFxNg732gr337t3xZ58NN98s1/7qKxlTamrrfT7+WBzfzbZz\n48fL+z55skSgKyrk2Lfe6vwefvADeP11Ob64GM48UyLebrcY8/3rXzJ58cUX8j356quOSwz667uU\nzLnnynfmwAPlvkaOlEyA556TNnXBoIj3tWuHrgGiQqFQKHZTHvXDOU5xa7dHoUmD8xywIh22p0n/\ncEsM9q+AI4xUv44c2H+RDquskB5KmK+lhMXF/Z72gnDQ+F0YCMNFRkp7yArrchLl9lEjio7RZm35\nMMgMwJXOAa9D7ymPLjqQ82Yu5fGT3uCosZsoa85k5rAqZo8o5/W1kzhp4rpW+29uzOG2jw7nniM+\nZNlFj/PvldNoCro4euxGsl0BllUVMn3Y9lbHfLRlLNfPP5p7j5zP+sse4a31E9jcmE2aI8TozEYO\nG72VT0tHceILP40f88HmEmYNr+Ddnz7HJ1tHE4zaWFY1jDfXTxqU92WooFLddx5KoO9E3nhD1poG\nY8ZASpt2nM8/D0cd1bnAvftuOPZYSQO/9VZpbebuwN/iiisS4nzffSXqWlTUfr+HHpKU8bYTBV1h\nupgni9MpU+B73+v5Odpy770JcT5mjIjAyZM73u/bb6WvfG/5PMnB9KCDen98cbGkmJeXSyT6q6/g\niCMS2xsbJWMhaPwfeNNNcOedHX+Wfj8sXNj+9QcfTIjzc8+FP/2pvfi++mq48UYxGVyxQgR2R9kA\n/fVdMolExDfhjjvaR90vvFAmWF5/XQT7M89IloBCoRhYlGGcQpHEpSlACJYZPxJaDBG+JUui5geX\ngjsMf+okAg1wcSpSeI64tIesEjmHRO36zsYZBXdEzOo0ZIwg44wlifSDyiQ1foiIc4A1tfkc+fez\n+c2RH3DSxHVEYhY+2Tqag548n9Omrm4n0AHuX3goZc2ZXDX7C86duRRP0Mk7G8Zz/fyjeP9nz8Xr\n1JN54PODWVg6kssP/IpDRpXyvUlraQq42OZJ5/FvZvHPFXu12v/uT+aS6Qpy8sS1zBlZhlXTeXbZ\njD1OoIMS6TsLTe9L+FHRDk3TdPO9NEWQpnXeUmzNGnFxr6mR/a69VqLRveWDDyQqqmmSsv2jH7Xe\nvnmzpFjHYhJ9/u47iaT2ho0bJUVa06S2+K9/7Xocv/61CNKOiEYlcqtpkp7+3nutt3s8MGqURPXd\nbhHgkwbg7+EZZ0jUWNMkhf5Xv+r9OY4+Wu5b00SE/uxniW133SXiVdMk2v700707t98v70N9vUwg\nfPZZ1/sfcohMOmRnS892Wx+m3rr7LgEceqhMJmiaCPq33ur4XGvXykSNponXwNtv9348CoWibyiR\nrlAYXJQKdSmw3ag7b3AlROsB26DYA/m+zlO+LzaiD2tzZT3KSKt+pqnj/XcWVzqhKk2WT0ZDk0ta\nv0GiJ7ppHHf2Mlk/7hv8cQ4gaY4g26/5HUsqizjk6fN39nB2K5RAT6BpGrquD7g1tKpBHyDMWt1X\nX229PPusRBhnzUqkuBcXi0DvC7NnJx5/9VX77f/+d2KS4Morey/OB5s33xRxrmkieAdCnIMIX5O+\npl8nH1dX13rbCy/I2mqVCYve8vbbiXP2ZPLArGE3/QT6QnffpbZcfnnn2yZNkiwNXZcad4VCoVAo\nBp3HffCfGhhfLwZqUYssMQ0q0qWuvKt67LBFFrNWXdck1X2okRKWyYZCr/Q5z/ZLpsCWLImoh6yw\nNQtGN0kN/mCb2vUjuW4fVq119MuixXjo2HdxWqO8vGbKThrZ7oua9B18VIr7AKLrUjvdEaaB2tSp\n8J//iDN3R1RXiwP4+++L0KmvTziPt6W8vP1ryZHXjnqyDzV2tfF2RE2NpIprmhiljRjR+3N8+mni\ncW2tTO50RbKx3+rV4i/Qlh39LrUlWdB3RHGxjKuhoftzKRSK/kOluisUbXiqGfIngisMfrsI9AKf\nRNQ74/yMxHaz17krIrXtA8ntQG//+cY0qbNPDUu6e0YQfHZ5HjFicTrw8WgY2yBinS5S+4cwp01d\nzV3zPmL+prGUNWeQ4/Yzd/RWJubW8W1lEX9cdMDOHuJuiUp1H1yUQB9g2rqVp6ZKi6599hHxfvrp\nrduQJfPCC3DxxZL2nXyutuc0qxSa23eXaCW0OqrjHmokj3fKAE6C5uQkHrd1z+8pycclT7BsS+oM\n0td72LIl8fjii3t3bEeCuD++S8lYLN1nHpj18m3bByoUioFHiXSFwuByQ2S/akTK/XZxQE8LwWtV\nnR/niCbErVnXnRqCqxzw0ABH0Xsr0jVkrFkBKGmEgA3CVlg4EjYb/1mPN1IH67swmNkF+Kq8mE9L\nR3Ho6K3kumWyZHNjFr/+5DB+u/BgQlElbRS7PupbPEDoetc16N3x0UdSu2yeZ7/9xORr7FjIzEyI\nn1hMnL6h42uZQsvplHTroU6yMExLG7jrJEe117X3IOkRyccVFyce98c9NCWVt3XXkq4toTa/G/rr\nu5RMb8ekUCgUCsVOwTSHywrAemN23hGVVPeu8Ntkv9IMmGTUnA20ME/mZmN8MU3aqnVF0JoQ6ZoO\ne1VLJL0qFdbnwriGhLndulyYWgOXpHRtkDdEWba9iNP/8+OdPYw9EhVFHzyUQB+i3H67CCZNE4Ox\ns8/ueL/uIp2mI3swKKJrqIv0ZAd5r1eyDQaCOXPEtR761ke9ogLKjBadVmvrdO+299AXkoV9WRkM\nH96380D/fZcUCsWuhYqiK/ZYrjMiyA8nOZZvzJbaaw3ZNrqxY5FqGsMtN1LjJtdJtP2xQRKz5j/Z\n64xaea8Drg6LyZs9Ju3TbIbhW9j4UVdltAFyh0WIb8uQMVelS7p7WkiyBhxRGO6BRpc8v8w98Cn7\nit0KJdIHB2USNwQJBMSRW9NE+HUmqEB6YXdFcqR4zZr+Gd9Akjze1asH7jqHHSalBbou7clWrOjd\n8c8+K2vzM0pukdcf95AckTcnAvpCf36XFArFrof6IaXYI4lpEgE/YhRsyoYXp4nBm27Uatuj4HPI\n0pagFWpTZK0j+w6WOE8mpkn03xVJGNoFrdDgltdb7DI+Hak3ByjNhM3ZsGi4GMRFtUR6fkyT5xcp\nVzMAACAASURBVFWpsvjsieMUCsWQQgn0IUhtrUQ8AcaN63rfd97pevuhhyYev/bajo1rMBis8ebm\nwk9+knjem9+wjY3wyCOJ51dc0Xp7Xp64mOs6LFvWM8O1thx2WOJx21Z0vaE/v0sKhUKhUAxpbrDK\nUu8WYWoK2Zgmqd+aLqnt1phE07M6MEmxxyRqnRKWxzuLBjcEbbDdSKnzOMWBvSxDtjU7E0u9W15f\nUiR938sy4d1xEiV3RSTibmYPhGyQFoaaVFkU7Th7xlKit93Bz/ZeurOHMiRRmVkDjxLoQ5DkaOzG\njZ3v19wsQrGreuAzzkiktf/hD4nWbkOVE08U8zFdh3/8Y2Cj/jfdJL3WdV1c0h9/vPtjYjH4+c+l\n1ziI2Z9Zt53MT38q62gUbrml92M76SQxstN1+OMf+/659ed3SaFQ7JqoKLpij+G+aMKlfUOORMjX\n5YpQ1ZAUcFdYxOrTTfCHDgT6lizDFT0mwvYJz+Dew23GkhmQlPSUsLR6q00RV/nKdPguHxYPh/IM\nWZYUyRIxouQakN8Cw5thmFcmJMzUeGcEptRAcbMsfUAjxi/2/YaPznma2mvvJ3jLXVRd/TuWXvhn\n/nrya5w0cW1/viM7hUFodb1Lo0T6wKIE+hAkJwdKSkScffklvPFG+328XvjhD6UWuitGj4bzz5dz\n1dTACSe0dhlvy4IFfa+b7g/S0uC66+RxICBCtas+2kuWdH0/XTFhAjz6qDzWdbj0UrjjjvYmayZV\nVXDKKfDKK/I8PV36zHckai+9FAoL5bzPPScivTPjNb8f5s9v/VpaGtx6qzyurYVjj4VNm7q+n88/\nhxtuaP1af36XFArFrosS6Yo9BotutBFDRGmekZ5u1m0XtMDxG+BqhyxtcURliWkwsqn99oHmLmP9\nUEjEdHpQRHpui6ToD/dI7XlVWkKYp4ZkiVlkcRqO9c6oLCDvS1STtTMqIv5xX6+HpxHjzZ+8wF9O\nep3pBdW8uX4CD3w+h+eW702FJ50z91rBtXMW9stboVDsqSiTuCHKZZfBVVcleqmfdRYccogItxUr\n4KmnpK/12WdLPXRXkc+HH4ZvvoFvv5X1xInw4x+LUVp2tkRPV66EN9+EtWslJXsgHdS74/rrYeFC\neOstEaUzZ8p7MG+emMb5fDLOd9+Ve/rss9Y1273h5z+XlPXrrpP3+q674Mkn4bTTYK+9xOW8pkbG\n8/rrImY1TYTva691njaelQX/+hccd5wY9P3mN/Dii/K+T54MDocI/kWLRDTvv784qydzxRXyeT3/\nPCxdKi3bvv99KQMoLBTBX10t34f586WGfPJkuO++1ufpz++SQqFQKBRDliudUpPtN37eWgxjNKsh\nzqfUyvqZLoS3TsINPbSTnHXvAm7VgJDUnRd6xdgtLSQR9JHNUJ0qYw1bRGwHbIm2cFZdRLoZBdY1\n2XdOmaS/pwcT+/aSM6d/x7HjN7CksojDnjkXX9jZarvTGubAEX2MnCh2KZRh3MChBPoQ5YorRLz9\n+9+SVv33v8tiomkiIh97TESV2b+6I9xuiYyfcw78738SmX7mGVmS0TTpb20ZhLyKrsaraRKlvuwy\n+OtfRYj+5z+ytN2vP8Z71VUwdSr86lfSOq2ionWNefL1NE1E9yOPdF/TPXcufPihlBmUlUmK+T33\ndHzeztz1//53ifTfe68I/ZdekqWzsY0c2X5bf36XFArFrotydVfs9piCNMdwJt+WIQLXjCIX+ETk\nftLFOUzjuHxfn0Vsv/Br4z/j24xo+F+N9MYfuQxxbqSzxwy397Yp2VYdzMy9QuPY0U2yuMN9Htac\nkWXousazy2a0E+cAwaidT7aOafWa3RLhqoO+4CfTVzAuu4FIzMKy7cN4dNGBvLRqWqt9547ewkfn\nPMMdC+bx60/mtTv/5iseJqZrjHvkyvhrZ89YytPff4VzXzmFsuZMbpv7MfsNr0DXNT4tHcU17x3D\n2rr8ducam13PfUfO58ixm3BYoyyrKuSeT8UMSdPUj6GeoET6wKAE+gBgRiB3JBKpafDCC3DyyfDE\nExJBbWmRCPI++4jYPvVUEa89uV5qqgi7zz8XcfbJJyJE/X6JEk+cKILyzDMlOtuXe+rp/fbkXFYr\n/OlPcMklEtH+8EMRuV6vpJaPGwcHHwynn966xVlfOe44OOYYqUV/4w1JB6+uBo9HouXFxXD44SJk\nDzyw5+edPRvWrxfh++qr8jnW1sqkwrBhsPfecu0zz+z8HLfeChdcIN+D+fNlEqG+Hmw2MaSbPBkO\nOkjq92fNan98f3+XzMmAntCbfRUKxcCjRLpit8YZEWO1iEXqtTVdasntURGsdSnwUjemLqZ4bXIN\n/Hh7wl1tnmcH5B6jRlTcjPKbvdDNiDqIQRxIS7nhHskoSAnDg33v517X4kbTdCbm1vVof9v/s3fn\n4VGV9///X2eWZLISEkA2EWSR4lJRcVeQKrbWShe1uHVxad0QtW5VlI+lVVu1rX6k1YrW5Wertdba\nfsrXXXFFqyCLKCCyE7YkJCF7Zs7vj/ucmQmZ7JPMmeT5uK65TjJz5syZYfTK67zf9337wnr5gid1\n4n4b9NnOgXrgv0cqO9igM7+yUs+c+azueHubbn3ja+1+/ZbGhtu2pW+NW63p4z/XgjVj9cePJmnC\ngJ365rjVOmLoVk2Yd4XKamMT84zuX6JFF89X/1CtFqwZq6Xb99GYwlI9//1n9OIXYxiDjpSybMpl\nSWFZls1nCQDwOgI6eq0bnLrTy06Lmxuy3aB63EazbW3it8uzTTv5rmzzvJG7pfsTTCaXKt8carbv\nOi1z1c5SafHVfnf2+QnOxYihlWbG+qdKu/zyX92nWB9cPF8BX0RPLT9Yz3/+FX28dYg2VRQk3P+m\n49/Wr6a+pv+sHqfpT8+Q7Ux/VZRVpf9e8rBG9CvXcY9eqA+2mPfTVgX9y6t+L1tKWEFvjPg07ckL\ntHDDqOhjv5r6qm487l3d+OrJuvf946L3v3T+E/raqHWa9eLXNe+/scrL6eNW6YUZf5VtW/rxC9P1\n5LJDu/Bp9R19pYpuWZbsHrh6wyRxAAD0IX3lDyn0YUP2mFtmo7mFnXbw+ZWth/Mrss3SY8V5Un6d\nGb/upXAumTb9QU77fU3QbGsD5uc9GSacZzaafbIazM0fkSoTTIjXCUu3D9F5//iutu3J1XkHL9dz\nZz+j9Vf/Xjuv/7WeO/tpfXNs0xncLzx0iSK2pWtfPjUaziWppCZHc986UZZl6+LDFifl3P66/OAm\n4VyS/vTx4bIsW0cOi42LH5pXoZP3/1Lrdhdo3n+PbLL//60+QAvXj0zK+fQlXPhNLgI6AAB9DCEd\nvc7MLBNSa4KmAr4pX8pqNOPPc+vNuPSpI6QfFkiz9mpf/3E/s13b32wtO3aslmZ7T5U/l5u1z7Ma\nzEWHer8Zf74t1wT0iGUCuvue429J8txnB2rE76/Rqf/f+frFwsn696oDZEmafsAq/eucv+rP05+X\nJOUE6zS6sFRbK/P0RWlRs+O8vs6E6YmDtyXlvD4uHtLsvk0V5t+2fyh2oWXi4GJJ0jsbRyg2HiDm\nzQ0jk3I+QGcxBh0AAADpbY8TolcXmVncAxEp4MySluG0fAcjJsjakn4QkrY7S9YU29LXc83kaxWZ\nph08v07qX9Ol8drd4vJsSXukHc65u5PaNfqkykxpkBN2R+6Wwj5p/7LYsmtJFLF9em3daL22zp0x\n19b3vrJSf57+gi44ZJn+8dlX9HGxaccvrsxLeIziPeb+glDXuxRs29Lu2ubzBkRsU4v0+yLR+/qF\n6iRJ26sSL1m0bU8KlzJKY0wYlzxU0AEA6IP4Qwq9yvoCUzUvyTJhNbNRCtjmFrHMrTLD3NYXmNuu\nbHOrDppbUY25Dd5jZnHP9Vg4l5wl06zYeu2u/DppeIVZu31glVkXfYQzY3swYtZV71aWnvvsQP1u\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/4vY/t+hIsy0LmXBfmSEVOUusHVYs5deZdvn7a1s+BnoUodzbaHEHAABAenHHSdcGzLJe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\nWrZsmXbv3h0df95SJXzIkCEaPXq0JFP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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig,ax=plt.subplots(1, 1, figsize=(16, 20))\n", "cmap = plt.get_cmap('winter_r')\n", "cmap.set_bad('teal')\n", "\n", "PNW_coastline = sio.loadmat('/ocean/rich/more/mmapbase/bcgeo/PNW.mat')\n", "\n", "#figures.plot_map(ax, PNW_coastline, lat_range=(46.5, 52), lon_range=(-128.5, -121.5))\n", "ax.pcolormesh(X,Y,bathy,cmap=cmap)\n", "for tick in ax.xaxis.get_major_ticks():\n", " tick.label.set_fontsize(14)\n", "for tick in ax.yaxis.get_major_ticks():\n", " tick.label.set_fontsize(14)\n", "\n", "\n", "\n", "for stn in range(numsta):\n", " location = stations_obs[stn]\n", " lon=-harm_obs.lon[harm_obs.site==location]\n", " lat=harm_obs.lat[harm_obs.site==location]\n", " ax.plot(lon,lat,'ow',label=location)\n", " ax.annotate(stn, xy = (lon,lat), xytext = (5,5),ha = 'right', va = 'bottom',\n", " textcoords = 'offset points', fontsize=14, color='#F87902')\n", "\n", "ax.text(\n", " -127, 47.7,\n", " 'Pacific Ocean',\n", " fontsize=30, color='blue')\n", "ax.text(\n", " -124., 51,\n", " ' British Columbia',\n", " fontsize=30, color='black')\n", "ax.text(\n", " -123.8, 46.6, 'Washington State',\n", " fontsize=30, color='black')\n", "ax.text(\n", " -122.3, 47.65, ' Puget\\nSound',\n", " fontsize=20, color='yellow')\n", "ax.text(\n", " -124.5, 48.1,\n", " ' Juan de Fuca Strait',\n", " fontsize=20, color='yellow', rotation=-9)\n", "ax.text(\n", " -124.2, 49.4,\n", " 'Strait of Georgia',\n", " fontsize=20, color='yellow', rotation=-30)\n", "\n", "ax.text(\n", " -127.5, 50.4,\n", " 'Vancouver Island',\n", " fontsize=25, color='black', rotation=-25)\n" ] }, { "cell_type": "code", "execution_count": 64, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "8 21\n" ] } ], "source": [ "# set the split that defines Juan de Fuca and the North\n", "\n", "split1=8; split2=21\n", "print (split1, split2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Tidal Harmonics" ] }, { "cell_type": "code", "execution_count": 65, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "../../myResults/NEMO36_Tides/GmO_N36_D/\n", "Sandheads\n", "(1920,)\n", "-1.59517\n", "../../myResults/NEMO36_Tides/GmO_N36_D/\n", "PointGrey\n", "(1920,)\n", "-1.56449\n", "../../myResults/NEMO36_Tides/GmO_N36_D/\n", "PointAtkinson\n", "(1920,)\n", "-1.57639\n", "../../myResults/NEMO36_Tides/GmO_N36_D/\n", "GibsonsLanding\n", "(1920,)\n", "-1.59548\n", "0.25 3259872900.0 3259872000.0\n" ] }, { "data": { "image/png": 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WxAyCB16EnJknEFjsF2UyaKMNyeLiHHYY4gnK1bvvZS+VoFhUsAOPvaY4T2Go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0+OsUoS1BsyUtdAGsd4/elxx7kqSEMCnmkTGhY5Xp6d48OLFxhoEgmDqoZsuQ5vYpWuwBwUEIKq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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sday=2-1; eday = 23-1\n", "fig, ax = plt.subplots(1,1,figsize=(12,5))\n", "for stn in range(12, 16):\n", " print (name)\n", " print (stations[stn])\n", " fT1 = NC.Dataset(name+stations[stn]+'.nc','r')\n", " time = (fT1.variables[\"time_counter\"][:]-timeinc)/3600. # want hours not seconds\n", " ssh = fT1.variables[\"sossheig\"][:,0,0]\n", " print (ssh.shape)\n", " print (ssh[0])\n", " ax.plot(time[(sday-1)*24*2:eday*24*2],ssh[(sday-1)*24*2:eday*24*2])\n", "print (time[0], fT1.variables['time_counter'][0], timeinc)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We need a way of determing the amplitude and phase of M2/K1/O1/S2 from our model output. We will do this by fitting our model water levels to cosine curves with the known frequency of M2/K1/O1/S2." ] }, { "cell_type": "code", "execution_count": 66, "metadata": { "collapsed": false }, "outputs": [], "source": [ "#constants and fitting\n", "# M2\n", "M2freq = 28.984106 # degrees per hour\n", "M2freq = M2freq*np.pi/180. # radians per hour\n", "#K1\n", "K1freq = 15.041069*np.pi/180.\n", "#O1\n", "O1freq = 13.943036*np.pi/180.\n", "#S2\n", "S2freq = 30.000002*np.pi/180.\n", "#P1\n", "P1freq = 14.958932*np.pi/180.\n", "#N2\n", "N2freq = 28.439730*np.pi/180.\n", "#Q1\n", "Q1freq = 13.398661*np.pi/180.\n", "#K2\n", "K2freq = 30.082138*np.pi/180.\n", "\n", "# initial phase calculation\n", "# our start is currently Oct 26, 2002\n", "# data for phase output from bdytides.F90; found in ocean.output\n", "# NEMO 3.4 writes out in degrees, NEMO 3.6 writes out in radians\n", "# NEMO 3.6 ut phase of tide due to nodes, vt phase of tide relative to Greenwich\n", "# first one printed out is stable, second one is varying fast\n", "# first on is ut second one is vt\n", "if start == 'oct2002':\n", " K1ft = 1.050578\n", " K1uvt = 296.314842\n", " M2ft = 0.987843\n", " M2uvt = 245.888564\n", " O1ft = 1.081364\n", " O1uvt = 312.950020\n", " S2ft = 1.0\n", " S2uvt = 0.0\n", " P1ft = 1.0\n", " P1uvt = 55.79460\n", " N2ft = 0.98784\n", " N2uvt = 353.570277\n", " Q1ft = 1.081364\n", " Q1uvt = 60.631733\n", " K2ft = 1.114095\n", " K2uvt = 52.129248\n", "\n", "# for start of Apr 21, 2003\n", "elif start == 'apr2003':\n", "\n", " K1ft = 1.065505\n", " K1uvt = 111.481741 \n", " M2ft = 0.982328\n", " M2uvt = 250.506179\n", " O1ft = 1.105495\n", " O1uvt = 142.040782\n", " S2ft = 1.000000 \n", " S2uvt = 0.000000\n", " P1ft = 1.000000\n", " P1uvt = 241.335269\n", " N2ft = 0.982328\n", " N2uvt = 205.684028\n", " Q1ft = 1.105495 \n", " Q1uvt = 97.218631\n", " K2ft = 1.159036 \n", " K2uvt = 42.361669\n", " \n", "elif start == 'dec2015':\n", " \n", " M2ft = 1.03774639446235\n", " M2uvt = (-12.5687951531251+15.0747977989126)*180./np.pi \n", " S2ft = 1.00000000000000\n", " S2uvt = (0.000000000000000+6.28609418926624)*180./np.pi \n", " N2ft = 1.03774639446235\n", " N2uvt = (-12.5687951531251+15.0140965178508)*180./np.pi \n", " K1ft = 0.882044509440140\n", " K1uvt = (-1.198932264051458E-002+6.25441043983728)*180./np.pi \n", " O1ft = 0.806243380430995\n", " O1uvt = (-12.5500821639088 + 8.82038735907528)*180./np.pi\n", " Q1ft = 0.806243380430995\n", " Q1uvt = (-12.5500821639088 + 8.75968607801354)*180./np.pi \n", " K2ft = 0.746702716634735\n", " K2uvt = (-2.156203094515553E-002 + 15.6504135332644)*180./np.pi \n", " P1ft = 1.00000000000000 \n", " P1uvt = (0.000000000000000E+000 + 3.168374942895902E-002)*180./np.pi\n", " \n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "However, with our typical 40-day output, we cannot separate K1 from P1 and K2 from S2. So we want to work ratios with these." ] }, { "cell_type": "code", "execution_count": 67, "metadata": { "collapsed": true }, "outputs": [], "source": [ "K1_amp_obs=np.zeros(numsta); K1_pha_obs=np.zeros(numsta)\n", "K2_amp_obs=np.zeros(numsta); K2_pha_obs=np.zeros(numsta)\n", "S2_amp_obs=np.zeros(numsta); S2_pha_obs=np.zeros(numsta)\n", "P1_amp_obs=np.zeros(numsta); P1_pha_obs=np.zeros(numsta)\n", "\n", "P1K1_amp = np.zeros(numsta); P1K1_pha = np.zeros(numsta)\n", "K2S2_amp = np.zeros(numsta); K2S2_pha = np.zeros(numsta)\n", "\n", "for stn in range(numsta):\n", " location=stations_obs[stn]\n", " K1_amp_obs[stn]=harm_obs.K1_amp[harm_obs.site==location]/100\n", " K1_pha_obs[stn]=harm_obs.K1_pha[harm_obs.site==location]\n", " if (harm_other.site==location).any():\n", " K2_amp_obs[stn]=harm_other.K2_amp[harm_other.site==location]/100\n", " K2_pha_obs[stn]=harm_other.K2_pha[harm_other.site==location]\n", " S2_amp_obs[stn]=harm_other.S2_amp[harm_other.site==location]/100\n", " S2_pha_obs[stn]=harm_other.S2_pha[harm_other.site==location]\n", " P1_amp_obs[stn]=harm_other.P1_amp[harm_other.site==location]/100\n", " P1_pha_obs[stn]=harm_other.P1_pha[harm_other.site==location]\n", " \n", " P1K1_amp[stn] = P1_amp_obs[stn] / K1_amp_obs[stn]\n", " P1K1_pha[stn] = P1_pha_obs[stn] - K1_pha_obs[stn]\n", " K2S2_amp[stn] = K2_amp_obs[stn] / S2_amp_obs[stn]\n", " K2S2_pha[stn] = K2_pha_obs[stn] - S2_pha_obs[stn]\n", " " ] }, { "cell_type": "code", "execution_count": 68, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def interpolate_ratios(amp_ratio, pha_diff):\n", " for stn in range(numsta):\n", " if (amp_ratio[stn] == 0) or (np.isnan(amp_ratio[stn])):\n", " if (amp_ratio[stn-1] != 0) and not(np.isnan(amp_ratio[stn-1])):\n", " if amp_ratio[stn+1] != 0 and not(np.isnan(amp_ratio[stn+1])):\n", " amp_ratio[stn] = 0.5*(amp_ratio[stn-1] + amp_ratio[stn+1])\n", " pha_diff[stn] = 0.5*(pha_diff[stn-1] + pha_diff[stn+1])\n", " else:\n", " amp_ratio[stn] = amp_ratio[stn-1]\n", " pha_diff[stn] = pha_diff[stn-1]\n", " elif (amp_ratio[stn+1] != 0) and not(np.isnan(amp_ratio[stn+1])):\n", " amp_ratio[stn] = amp_ratio[stn+1]\n", " pha_diff[stn] = pha_diff[stn+1]\n", " print (stations[stn], amp_ratio[stn], pha_diff[stn])" ] }, { "cell_type": "code", "execution_count": 69, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SheringhamPoint 0.31059602649 -3.5\n", "PedderBay 0.31059602649 -3.5\n", "Esquimalt 0.312395301921 -4.05\n", "CloverPoint 0.314194577352 -4.6\n", "FinnertyCove 0.312475774732 -3.4\n", "TumboChannel 0.310441777195 -1.6\n", "WhalerBay 0.310339070516 -1.6\n", "Sandheads 0.310551558753 -2.2\n", "PointGrey 0.310728215571 -2.6\n", "GibsonsLanding 0.31090487239 -3.0\n", "HalfmoonBay 0.31090487239 -3.0\n", "IrvinesLanding 0.31090487239 -3.0\n", "PowellRiver 0.31090487239 -3.0\n", "Lund 0.313748896372 -1.765\n", "MaudeIslandE 0.290780141844 -3.43\n", "NympheCove 0.299147296356 -2.03\n", "BrownBay 0.309644075586 -2.58\n", "KelseyBay 0.309112656605 -3.43\n" ] } ], "source": [ "interpolate_ratios(P1K1_amp, P1K1_pha)" ] }, { "cell_type": "code", "execution_count": 70, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SheringhamPoint 0.233840304183 -5.6\n", "PedderBay 0.233840304183 -5.6\n", "Esquimalt 0.214959367778 1.75\n", "CloverPoint 0.196078431373 9.1\n", "FinnertyCove 0.23832698547 5.95\n", "TumboChannel 0.286994356611 3.25\n", "WhalerBay 0.286706586826 4.05\n", "Sandheads 0.28 4.4\n", "PointGrey 0.275371179039 2.2\n", "GibsonsLanding 0.270742358079 0.0\n", "HalfmoonBay 0.270742358079 0.0\n", "IrvinesLanding 0.270742358079 0.0\n", "PowellRiver 0.270742358079 0.0\n", "Lund 0.269375826599 -0.57\n", "MaudeIslandE 0.26739023187 6.16\n", "NympheCove 0.270629374276 -0.19\n", "BrownBay 0.273653008342 -5.49\n", "KelseyBay 0.275463563278 -5.94\n" ] } ], "source": [ "interpolate_ratios(K2S2_amp, K2S2_pha)" ] }, { "cell_type": "code", "execution_count": 71, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 71, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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JVNN+JaJnbCF6R+Ji3brr6O39NEePBoBx9GjA5s3rWbfuupPq+jx7+So5fj5De+XeSyXr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\nv1xwTNOKiBXt6p2I+Fng/cD/KDaqSYLJ59i/DPxm+/G/B74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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig,ax = plt.subplots(2, 2, figsize=(10,10))\n", "ax[0,0].plot(P1K1_amp, '*')\n", "ax[0,1].plot(P1K1_pha, 'o')\n", "ax[1,0].plot(K2S2_amp, '*')\n", "ax[1,1].plot(K2S2_pha, 'o')" ] }, { "cell_type": "code", "execution_count": 72, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# function for fitting 6 frequencies and inferring 2 with constant\n", "def sixplustwo(xplus, M2amp, M2pha, K1amp, K1pha, O1amp, O1pha, S2amp, S2pha,\n", " N2amp, N2pha, Q1amp, Q1pha, Constant):\n", " x = xplus[0]\n", "\n", " P1K1amp = xplus[1]\n", " P1K1pha = xplus[2]\n", " K2S2amp = xplus[3]\n", " K2S2pha = xplus[4]\n", " \n", " return (M2amp * M2ft * np.cos(M2freq*x - (M2pha - M2uvt) *np.pi/180.) +\n", " K1amp * K1ft * np.cos(K1freq*x - (K1pha - K1uvt) *np.pi/180.) +\n", " O1amp * O1ft * np.cos(O1freq*x - (O1pha - O1uvt) *np.pi/180.) +\n", " S2amp * S2ft * np.cos(S2freq*x - (S2pha - S2uvt) *np.pi/180.) +\n", " P1K1amp * K1amp *P1ft * np.cos(P1freq*x - (K1pha + P1K1pha - P1uvt) *np.pi/180.) +\n", " N2amp * N2ft * np.cos(N2freq*x - (N2pha - N2uvt) *np.pi/180.) +\n", " Q1amp * Q1ft * np.cos(Q1freq*x - (Q1pha - Q1uvt) *np.pi/180.) +\n", " K2S2amp * S2amp *K2ft * np.cos(K2freq*x - (S2pha + K2S2pha - K2uvt) *np.pi/180.) + Constant )" ] }, { "cell_type": "code", "execution_count": 73, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "../../myResults/NEMO36_Tides/GmO_N36_D\n", "odict_keys(['nav_lat', 'nav_lon', 'sossheig', 'time_centered', 'time_centered_bounds', 'time_counter', 'time_counter_bounds'])\n", "\n", "float64 time_counter(time_counter)\n", " axis: T\n", " standard_name: time\n", " long_name: Time axis\n", " calendar: gregorian\n", " units: seconds since 1900-01-01 00:00:00\n", " time_origin: 1900-01-01 00:00:00\n", " bounds: time_counter_bounds\n", "unlimited dimensions: time_counter\n", "current shape = (1920,)\n", "filling off\n", "\n", "3259872000.0\n", "1800.0\n", "3259872900.0\n", "\n", "float64 time_counter(time_counter)\n", " axis: T\n", " standard_name: time\n", " units: seconds since 2003-04-21 00:00:00\n", " calendar: gregorian\n", " title: Time\n", " long_name: Time axis\n", " time_origin: 2003-APR-21 00:00:00\n", " bounds: time_counter_bnds\n", "unlimited dimensions: time_counter\n", "current shape = (3840,)\n", "filling on, default _FillValue of 9.969209968386869e+36 used\n", "\n", "450.0\n" ] } ], "source": [ "# Testing to Find the Time Shift\n", "\n", "fPA = NC.Dataset(path+runname+'/PointAtkinson.nc')\n", "print (path+runname)\n", "#nc_tools.show_dataset_attrs(fPA)\n", "nc_tools.show_variables(fPA)\n", "nc_tools.show_variable_attrs(fPA,'time_counter')\n", "print (fPA.variables['time_counter'][0]-900.)\n", "print (fPA.variables['time_counter'][1]-fPA.variables['time_counter'][0])\n", "print (fPA.variables['time_centered'][0])\n", "\n", "fPO = NC.Dataset('/ocean/sallen/allen/research/MEOPAR/myResults/oldtopog/PointAtkinson.nc')\n", "nc_tools.show_variable_attrs(fPO,'time_counter')\n", "print (fPO.variables['time_counter'][0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can apply this fit to our model output." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Use Full Time Series for Best Estimate of Amplitudes/Phases" ] }, { "cell_type": "code", "execution_count": 74, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "../../myResults/NEMO36_Tides/GmO_N36_D/PortRenfrew\n", "../../myResults/NEMO36_Tides/GmO_N36_D/SheringhamPoint\n", "../../myResults/NEMO36_Tides/GmO_N36_D/PedderBay\n", "../../myResults/NEMO36_Tides/GmO_N36_D/Esquimalt\n", "../../myResults/NEMO36_Tides/GmO_N36_D/Victoria\n", "../../myResults/NEMO36_Tides/GmO_N36_D/CloverPoint\n", "../../myResults/NEMO36_Tides/GmO_N36_D/FinnertyCove\n", "354.123857399\n", "../../myResults/NEMO36_Tides/GmO_N36_D/FulfordHarbour\n", "../../myResults/NEMO36_Tides/GmO_N36_D/TumboChannel\n", "../../myResults/NEMO36_Tides/GmO_N36_D/PatosIsland\n", "../../myResults/NEMO36_Tides/GmO_N36_D/WhalerBay\n", "../../myResults/NEMO36_Tides/GmO_N36_D/Tsawwassen\n", "../../myResults/NEMO36_Tides/GmO_N36_D/Sandheads\n", "../../myResults/NEMO36_Tides/GmO_N36_D/PointGrey\n", "../../myResults/NEMO36_Tides/GmO_N36_D/PointAtkinson\n", "../../myResults/NEMO36_Tides/GmO_N36_D/GibsonsLanding\n", "../../myResults/NEMO36_Tides/GmO_N36_D/HalfmoonBay\n", "../../myResults/NEMO36_Tides/GmO_N36_D/IrvinesLanding\n", "../../myResults/NEMO36_Tides/GmO_N36_D/PowellRiver\n", "../../myResults/NEMO36_Tides/GmO_N36_D/Lund\n", "../../myResults/NEMO36_Tides/GmO_N36_D/TwinIslets\n", "../../myResults/NEMO36_Tides/GmO_N36_D/CampbellRiver\n", "../../myResults/NEMO36_Tides/GmO_N36_D/MaudeIslandE\n", "../../myResults/NEMO36_Tides/GmO_N36_D/NympheCove\n", "../../myResults/NEMO36_Tides/GmO_N36_D/SeymourNarrows\n", "../../myResults/NEMO36_Tides/GmO_N36_D/BrownBay\n", "../../myResults/NEMO36_Tides/GmO_N36_D/ChathamPoint\n", "../../myResults/NEMO36_Tides/GmO_N36_D/KelseyBay\n", "../../myResults/NEMO36_Tides/GmO_N36_D/YorkeIsland\n" ] } ], "source": [ "#allocate space for our arrays\n", "M2_amp=[]; M2_pha=[]; K1_amp=[]; K1_pha=[]\n", "O1_amp=[]; O1_pha=[]; S2_amp=[]; S2_pha=[]\n", "N2_amp=[]; N2_pha=[]\n", "Q1_amp=[]; Q1_pha=[]\n", "\n", "M2_amp_obs=np.zeros(numsta); M2_pha_obs=np.zeros(numsta)\n", "N2_amp_obs=np.zeros(numsta); N2_pha_obs=np.zeros(numsta)\n", "Q1_amp_obs=np.zeros(numsta); Q1_pha_obs=np.zeros(numsta)\n", "O1_amp_obs=np.zeros(numsta); O1_pha_obs=np.zeros(numsta)\n", "\n", "ts = 240\n", "te = ssh.shape[0]\n", "timeplus = np.zeros([5,te-ts])\n", "\n", "for stn in range(numsta):\n", " print (name+stations[stn])\n", " fT1 = NC.Dataset(name+stations[stn]+'.nc','r')\n", " time = (fT1.variables[\"time_counter\"][ts:te]-timeinc)/3600. # want hours not seconds\n", " ssh = fT1.variables[\"sossheig\"][:,0,0]\n", " timeplus[0] = time\n", " timeplus[1] = P1K1_amp[stn]*np.ones_like(time); timeplus[2] = P1K1_pha[stn]*np.ones_like(time)\n", " timeplus[3] = K2S2_amp[stn]*np.ones_like(time); timeplus[4] = K2S2_pha[stn]*np.ones_like(time)\n", "\n", " fitted, cov = curve_fit(sixplustwo,timeplus,ssh[ts:te]) \n", " if fitted[0] < 0:\n", " fitted[0] = -fitted[0]\n", " fitted[1] = fitted[1]+180\n", "\n", " M2_amp.append(fitted[0])\n", " pha = fitted[1]\n", " if pha > 360:\n", " pha=pha-360\n", " elif pha < 0:\n", " pha = pha+360\n", " if stn == 6:\n", " print (pha)\n", " M2_pha.append(pha)\n", "\n", " if fitted[2] < 0:\n", " fitted[2] = - fitted[2]\n", " fitted[3] = fitted[3] + 180\n", " K1_amp.append(fitted[2])\n", " pha = fitted[3]\n", " if pha > 360:\n", " pha = pha-360\n", " elif pha < 0:\n", " pha = pha + 360\n", " K1_pha.append(pha) \n", " \n", " if fitted[4] < 0:\n", " fitted[4] = -fitted[4]\n", " fitted[5] = fitted[5]+180\n", " O1_amp.append(fitted[4])\n", " pha= fitted[5]\n", " if pha > 360:\n", " pha=pha-360\n", " elif pha < 0:\n", " pha = pha + 360\n", " O1_pha.append(pha) \n", " \n", " if fitted[6] < 0:\n", " fitted[6] = -fitted[6]\n", " fitted[7] = fitted[7]+180\n", " S2_amp.append(fitted[6])\n", " pha= fitted[7]\n", " if pha > 360:\n", " pha=pha-360\n", " elif pha < 0:\n", " pha = pha + 360\n", " S2_pha.append(pha) \n", " \n", " if fitted[8] < 0:\n", " fitted[8] = -fitted[8]\n", " fitted[9] = fitted[9]+180\n", " N2_amp.append(fitted[8])\n", " pha= fitted[9]\n", " if pha > 360:\n", " pha=pha-360\n", " elif pha < 0:\n", " pha = pha + 360\n", " N2_pha.append(pha) \n", " \n", " if fitted[10] < 0:\n", " fitted[10] = -fitted[10]\n", " fitted[11] = fitted[11]+180\n", " Q1_amp.append(fitted[10])\n", " pha= fitted[11]\n", " if pha > 360:\n", " pha=pha-360\n", " Q1_pha.append(pha) \n", "\n", " #now the observations\n", " location=stations_obs[stn]\n", " M2_amp_obs[stn]=harm_obs.M2_amp[harm_obs.site==location]/100\n", " M2_pha_obs[stn]=harm_obs.M2_pha[harm_obs.site==location]\n", " K1_amp_obs[stn]=harm_obs.K1_amp[harm_obs.site==location]/100\n", " K1_pha_obs[stn]=harm_obs.K1_pha[harm_obs.site==location]\n", " \n", " #O1/S2/P1/N2/Q1/K2 are in the other file\n", " if (harm_other.site==location).any():\n", " O1_amp_obs[stn]=harm_other.O1_amp[harm_other.site==location]/100\n", " O1_pha_obs[stn]=harm_other.O1_pha[harm_other.site==location]\n", " S2_amp_obs[stn]=harm_other.S2_amp[harm_other.site==location]/100\n", " S2_pha_obs[stn]=harm_other.S2_pha[harm_other.site==location]\n", " N2_amp_obs[stn]=harm_other.N2_amp[harm_other.site==location]/100\n", " N2_pha_obs[stn]=harm_other.N2_pha[harm_other.site==location]\n", " Q1_amp_obs[stn]=harm_other.Q1_amp[harm_other.site==location]/100\n", " Q1_pha_obs[stn]=harm_other.Q1_pha[harm_other.site==location]\n", " #Mask the arrays so that we can do statistics without the 0's throwing things off.\n", " O1_amp_obs =np.ma.masked_values(O1_amp_obs, 0)\n", " O1_pha_obs =np.ma.masked_values(O1_pha_obs, 0)\n", " S2_amp_obs =np.ma.masked_values(S2_amp_obs, 0)\n", " S2_pha_obs =np.ma.masked_values(S2_pha_obs, 0)\n", " N2_amp_obs =np.ma.masked_values(N2_amp_obs, 0)\n", " N2_pha_obs =np.ma.masked_values(N2_pha_obs, 0)\n", " Q1_amp_obs =np.ma.masked_values(Q1_amp_obs, 0)\n", " Q1_pha_obs =np.ma.masked_values(Q1_pha_obs, 0)" ] }, { "cell_type": "code", "execution_count": 75, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 75, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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YD85QjRAcDCAfrxBl5bWtEUA/ULM51+/DWKZNPx1uLeuV1IhMw5Az0volKbob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\nNs+6kEb3SVrgW0+2Fs4Lq5EQWNKFBnD/0OTMdDkI4dnZiKqC9978B7y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wN0ZQmxOZi709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4vSmlo8uGo4kGCFYhJi1QJX0+6SDG2bLAoWJLl0TZVl4Y5WLICFZ+ux6oCqIcN5eX1MTrvqTu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yKgQd8CAk4zSysoYC/plD16yhyf+uu5KFoOvGySME5W4jt511Q7omjGPHyAonrR7SBYAX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WtrSsUFd6oIcqyhqcLsJRTBEtbQ6S4fwek7ViQ+dE042VFj7bl1BF1raOya22sawLeGpg6rjx9v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\nkxXqCMaEhto8vhyhoYCGbW7bFubCzpmj7T1SuzUkLQMDeuhx0kn+11cst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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "stn = 20\n", "timeplus[0] = time\n", "timeplus[1] = P1K1_amp[stn]*np.ones_like(time); timeplus[2] = P1K1_pha[stn]*np.ones_like(time)\n", "timeplus[3] = K2S2_amp[stn]*np.ones_like(time); timeplus[4] = K2S2_pha[stn]*np.ones_like(time)\n", "thefit = sixplustwo(timeplus, M2_amp[stn], M2_pha[stn], K1_amp[stn], K1_pha[stn], O1_amp[stn], O1_pha[stn], \n", " S2_amp[stn], S2_pha[stn], N2_amp[stn], N2_pha[stn], Q1_amp[stn], Q1_pha[stn], 0.)\n", "theobs = sixplustwo(timeplus, M2_amp_obs[stn], M2_pha_obs[stn], K1_amp_obs[stn], K1_pha_obs[stn], \n", " O1_amp_obs[stn], O1_pha_obs[stn], \n", " S2_amp_obs[stn], S2_pha_obs[stn], N2_amp_obs[stn], N2_pha_obs[stn], \n", " Q1_amp_obs[stn], Q1_pha_obs[stn], 0.)\n", "fT1 = NC.Dataset(name+stations[stn]+'.nc','r')\n", "ssh = fT1.variables[\"sossheig\"][:,0,0]\n", "fig, ax = plt.subplots(3,1,figsize=(15,15))\n", "ax[0].plot(time, thefit, linewidth=3)\n", "ax[0].plot(time, theobs, linewidth=2)\n", "ax[0].plot(time, ssh[ts:te]-0.1)\n", "ax[0].set_title('Model Output')\n", "ax[1].plot(time, ssh[ts:te]-thefit-0.1)\n", "ax[1].set_title('Model Ouput - Fit')\n", "ax[2].plot(time, theobs-thefit)\n", "ax[2].set_title(\"Observations Predictions - Fit\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The model data is saved in lists M2_amp, M2_pha, K1_amp, K1_pha. We have also saved the observations in M2_amp_obs, etc.\n", "\n", "We can compare model and observations by plotting." ] }, { "cell_type": "code", "execution_count": 76, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "315.54791804 31.3253692208 75.7774511806\n" ] } ], "source": [ "print (M2_pha[4], M2_pha[14], M2_pha[14]-M2_pha[4]+360)" ] }, { "cell_type": "code", "execution_count": 77, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "316.1 31.2 75.1\n" ] } ], "source": [ "print (M2_pha_obs[4], M2_pha_obs[14], M2_pha_obs[14]+360-M2_pha_obs[4])" ] }, { "cell_type": "code", "execution_count": 78, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 0.708 0.487 0.342 0.367 0.373 0.403 0.447 0.582 0.726 0.68\n", " 0.834 0.811 0.869 0.945 0.918 0.947 0.964 0.988 1.007 1.022\n", " 1.013 0.825 0.556 0.615 0.946 0.935 0.903 1.17 1.171]\n" ] } ], "source": [ "print (M2_amp_obs)" ] }, { "cell_type": "code", "execution_count": 79, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.901846153846 mean amp obs\n", "SoG [-2.19542223 -1.22479499 0.07586193 -1.74975972 0.16507876 3.12732116\n", " -0.12536922 -1.6678781 -0.52894291 -0.25039887 0.99400532 2.07805186\n", " 1.36689132]\n", "0.999946570494 Amp\n", "0.00497263834354 Pha\n", "North [ 1.76690119 -1.70555429]\n", "0.999294951295\n", "0.0306734513582\n" ] }, { "data": { "image/png": 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yS8rhHogMzt0gkwrqmSkARUVFLF++nAMPPDDbTWmVPi/JZdEofPOMDczdOZ6R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\nasU63weuj4g56f5y4NCIeHzAtopxQRwzs5zxdWbGrsb2zO2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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Plotting M2\n", "labels=['JdF/Islands','SoG','North']\n", "fig=tidetools.plot_scatter_pha_amp(M2_amp,M2_amp_obs,M2_pha,M2_pha_obs,'M2',figsize=(14,6),\n", " split1=split1,split2=split2, labels=labels)\n", "\n", "ax_amp,ax_pha = fig.axes\n", "min_value, max_value = ax_amp.set_xlim(0, 1.2)\n", "ax_amp.plot([min_value, max_value], [min_value, max_value], color='red',lw=2)\n", "\n", "min_value, max_value = ax_pha.set_xlim(0, 360)\n", "ax_pha.plot([min_value, max_value], [min_value, max_value], color='red',lw=2)\n", "\n", "SoGratio = np.mean(M2_amp_obs[split1:split2]/M2_amp[split1:split2])\n", "print (np.mean(M2_amp_obs[split1:split2]), 'mean amp obs')\n", "print (\"SoG\", M2_pha_obs[split1:split2]-M2_pha[split1:split2])\n", "\n", "\n", "TSout['West']['M2']['Amp'] = SoGratio\n", "TSout['West']['M2']['Pha'] = np.mean(M2_pha_obs[split1:split2]-M2_pha[split1:split2])\n", "\n", "TSout['North']['M2']['Amp'] = np.mean(M2_amp_obs[-2:]/M2_amp[-2:])\n", "TSout['North']['M2']['Pha'] = np.mean(M2_pha_obs[-2:]-M2_pha[-2:]) \n", "\n", "print (SoGratio, 'Amp')\n", "print (TSout['West']['M2']['Pha'], 'Pha')\n", "\n", "print (\"North\", M2_pha_obs[-2:]-M2_pha[-2:])\n", "\n", "print (TSout['North']['M2']['Amp']) \n", "print (TSout['North']['M2']['Pha']) " ] }, { "cell_type": "code", "execution_count": 80, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SoG [-0.87284528 1.43708679 0.34042665 -0.65854925 0.1025621 0.38410467\n", " 0.36231416 -1.40094529 -0.59264421 -0.35142789 -0.37853586 0.73817389\n", " 0.03054662]\n", "0.990025093955\n", "-0.0661332994153\n", "North [ 7.39314778 5.91381236]\n", "0.909192405015\n", "6.65348006746\n" ] }, { "data": { "image/png": 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DQrL34F5uW35bg+tGa9OmTXU6qxQVFTUoOD/84Q/Zvn07O3bsYOvWreH9TU3dQ1BYampq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\n3sA+r1dmDK2vx+uVvhjl89Mb7f/+NUke0E56PM3gJqcAL2y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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Plotting - K1\n", "\n", "fig=tidetools.plot_scatter_pha_amp(K1_amp,K1_amp_obs,K1_pha,K1_pha_obs,'K1',figsize=(14,6),\n", " split1=split1, split2=split2, labels=labels)\n", "\n", "ax_amp,ax_pha = fig.axes\n", "min_value, max_value = ax_amp.set_xlim(0, 1.2)\n", "ax_amp.plot([min_value, max_value], [min_value, max_value], color='red',lw=2)\n", "\n", "min_value, max_value = ax_pha.set_xlim(0, 360)\n", "ax_pha.plot([min_value, max_value], [min_value, max_value], color='red',lw=2)\n", "\n", "TSout['West']['K1']['Amp'] = np.mean(K1_amp_obs[split1:split2]/K1_amp[split1:split2])\n", "TSout['West']['K1']['Pha'] = np.mean(K1_pha_obs[split1:split2]-K1_pha[split1:split2])\n", "\n", "TSout['North']['K1']['Amp'] = np.mean(K1_amp_obs[-2:]/K1_amp[-2:])\n", "TSout['North']['K1']['Pha'] = np.mean(K1_pha_obs[-2:]-K1_pha[-2:])\n", "\n", "print (\"SoG\", K1_pha_obs[split1:split2]-K1_pha[split1:split2])\n", "print (TSout['West']['K1']['Amp'])\n", "print (TSout['West']['K1']['Pha'])\n", "\n", "print (\"North\", K1_pha_obs[-2:]-K1_pha[-2:])\n", "print (TSout['North']['K1']['Amp'] )\n", "print (TSout['North']['K1']['Pha'] )" ] }, { "cell_type": "code", "execution_count": 81, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SoG [-- 0.5162589643491629 -- -1.0728417350749169 -- -- 0.25128443051977456 --\n", " -- -- -- -- -0.12375121139046996]\n", "0.993814504425\n", "-0.107262387899\n", "North [-- 7.098203504888517]\n", "0.931566748215\n", "7.09820350489\n" ] }, { "data": { "image/png": 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Ro0ezZs0adu7cydatW5k4cSIrV66M7jN//vwa44O3b9/OggULahzj2GOP5bLL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\nGUkTkISqynK3ow+S3B44t6r2mTX9EuCwqro6yd2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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Plotting - O1\n", "\n", "fig=tidetools.plot_scatter_pha_amp(O1_amp,O1_amp_obs,O1_pha,O1_pha_obs,'O1',figsize=(14,6),\n", " split1=split1, split2=split2, labels=labels)\n", "\n", "ax_amp,ax_pha = fig.axes\n", "min_value, max_value = ax_amp.set_xlim(0, 1.2)\n", "ax_amp.plot([min_value, max_value], [min_value, max_value], color='red',lw=2)\n", "\n", "min_value, max_value = ax_pha.set_xlim(0, 360)\n", "ax_pha.plot([min_value, max_value], [min_value, max_value], color='red',lw=2)\n", "\n", "TSout['West']['O1']['Amp'] = np.mean(O1_amp_obs[split1:split2]/O1_amp[split1:split2])\n", "TSout['West']['O1']['Pha'] = np.mean(O1_pha_obs[split1:split2]-O1_pha[split1:split2])\n", "\n", "TSout['North']['O1']['Amp'] = np.mean(O1_amp_obs[-2:]/O1_amp[-2:])\n", "TSout['North']['O1']['Pha'] = np.mean(O1_pha_obs[-2:]-O1_pha[-2:])\n", "\n", "print (\"SoG\", O1_pha_obs[split1:split2]-O1_pha[split1:split2])\n", "print (TSout['West']['O1']['Amp'])\n", "print (TSout['West']['O1']['Pha'])\n", "\n", "print (\"North\", O1_pha_obs[-2:]-O1_pha[-2:])\n", "print (TSout['North']['O1']['Amp'] )\n", "print (TSout['North']['O1']['Pha'] )" ] }, { "cell_type": "code", "execution_count": 82, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SoG [-- 0.10345625361050992 -- -1.5336799792765277 -- -- -0.19457565898763107\n", " -- -- -- -- -- 2.1199963929421344]\n", "0.997477741519\n", "0.123799252072\n", "North [-- -0.21518163627450804]\n", "1.00745155133\n", "-0.215181636275\n" ] }, { "data": { "image/png": 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rTWlu/csvv+wDBw700tJS79q1qz/00EP1tk+fPt3LysoccMDLysp8+vTp9fbZ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\na2IOM4MjaS+yqZlHk822ORvYELgKeC9ZW3VsRKz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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Plotting - S2\n", "\n", "fig=tidetools.plot_scatter_pha_amp(S2_amp,S2_amp_obs,S2_pha,S2_pha_obs,'S2',figsize=(14,6),\n", " split1=split1, split2=split2, labels=labels)\n", "\n", "ax_amp,ax_pha = fig.axes\n", "min_value, max_value = ax_amp.set_xlim(0, 1.2)\n", "ax_amp.plot([min_value, max_value], [min_value, max_value], color='red',lw=2)\n", "\n", "min_value, max_value = ax_pha.set_xlim(0, 360)\n", "ax_pha.plot([min_value, max_value], [min_value, max_value], color='red',lw=2)\n", "\n", "TSout['West']['S2']['Amp'] = np.mean(S2_amp_obs[split1:split2]/S2_amp[split1:split2])\n", "TSout['West']['S2']['Pha'] = np.mean(S2_pha_obs[split1:split2]-S2_pha[split1:split2])\n", "\n", "TSout['North']['S2']['Amp'] = np.mean(S2_amp_obs[-2:]/S2_amp[-2:])\n", "TSout['North']['S2']['Pha'] = np.mean(S2_pha_obs[-2:]-S2_pha[-2:])\n", "\n", "print (\"SoG\", S2_pha_obs[split1:split2]-S2_pha[split1:split2])\n", "print (TSout['West']['S2']['Amp'])\n", "print (TSout['West']['S2']['Pha'])\n", "\n", "print (\"North\", S2_pha_obs[-2:]-S2_pha[-2:])\n", "print (TSout['North']['S2']['Amp'] )\n", "print (TSout['North']['S2']['Pha'] )" ] }, { "cell_type": "code", "execution_count": 83, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SoG [-- -3.596496465510313 -- -0.7693696568419748 -- -- -0.11044247201252944 --\n", " -- -- -- -- 3.9300069634948596]\n", "1.0056646519\n", "-0.136575407717\n", "North [-- 0.0740307660430517]\n", "1.00052960163\n", "0.0740307660431\n" ] }, { "data": { "image/png": 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58Goz2/4PODtheSnQv5l9vSnNrX/11Vd9wIABXlxc7F27dvVHHnmk3vYpU6Z4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\nNdp2KjcTAIwFU17bOMgczHKem+AgY2ZmOeEgY2Y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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Plotting - N2\n", "\n", "fig=tidetools.plot_scatter_pha_amp(N2_amp,N2_amp_obs,N2_pha,N2_pha_obs,'N2',figsize=(14,6),\n", " split1=split1, split2=split2, labels=labels)\n", "\n", "ax_amp,ax_pha = fig.axes\n", "min_value, max_value = ax_amp.set_xlim(0, 1.2)\n", "ax_amp.plot([min_value, max_value], [min_value, max_value], color='red',lw=2)\n", "\n", "min_value, max_value = ax_pha.set_xlim(0, 360)\n", "ax_pha.plot([min_value, max_value], [min_value, max_value], color='red',lw=2)\n", "\n", "TSout['West']['N2']['Amp'] = np.mean(N2_amp_obs[split1:split2]/N2_amp[split1:split2]) \n", "TSout['West']['N2']['Pha'] = np.mean(N2_pha_obs[split1:split2]-N2_pha[split1:split2])\n", "\n", "TSout['North']['N2']['Amp'] = np.mean(N2_amp_obs[-2:]/N2_amp[-2:])\n", "TSout['North']['N2']['Pha'] = np.mean(N2_pha_obs[-2:]-N2_pha[-2:])\n", "\n", "print (\"SoG\", N2_pha_obs[split1:split2]-N2_pha[split1:split2])\n", "print (TSout['West']['N2']['Amp'])\n", "print (TSout['West']['N2']['Pha'])\n", "\n", "print (\"North\", N2_pha_obs[-2:]-N2_pha[-2:])\n", "print (TSout['North']['N2']['Amp'] )\n", "print (TSout['North']['N2']['Pha'] )" ] }, { "cell_type": "code", "execution_count": 84, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SoG [-- -2.9419299835951165 -- 1.2049915510871188 -- -- 0.3592464198349603 --\n", " -- -- -- -- 0.4567320990878443]\n", "0.992251988257\n", "-0.230239978396\n", "North [-- 7.218067213692507]\n", "0.955535702159\n", "7.21806721369\n" ] }, { "data": { "image/png": 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GNHCspn4G9Sxfvtz32msvb9u2rbdv395vvfXWWttvvvlm79ixY6JPtWvXzidN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\nBxkzM4eZTjnImJlZnjnImJkBDjOrcpAxM7M8c5A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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Plotting - Q1\n", "\n", "fig=tidetools.plot_scatter_pha_amp(Q1_amp,Q1_amp_obs,Q1_pha,Q1_pha_obs,'Q1',figsize=(14,6),\n", " split1=split1, split2=split2, labels=labels)\n", "\n", "ax_amp,ax_pha = fig.axes\n", "min_value, max_value = ax_amp.set_xlim(0, 1.2)\n", "ax_amp.plot([min_value, max_value], [min_value, max_value], color='red',lw=2)\n", "\n", "min_value, max_value = ax_pha.set_xlim(0, 360)\n", "ax_pha.plot([min_value, max_value], [min_value, max_value], color='red',lw=2)\n", "\n", "\n", "TSout['West']['Q1']['Amp'] = np.mean(Q1_amp_obs[split1:split2]/Q1_amp[split1:split2])\n", "TSout['West']['Q1']['Pha'] = np.mean(Q1_pha_obs[split1:split2]-Q1_pha[split1:split2]) \n", "\n", "TSout['North']['Q1']['Amp'] = np.mean(Q1_amp_obs[-2:]/Q1_amp[-2:])\n", "TSout['North']['Q1']['Pha'] = np.mean(Q1_pha_obs[-2:]-Q1_pha[-2:]) \n", "\n", "print (\"SoG\", Q1_pha_obs[split1:split2]-Q1_pha[split1:split2])\n", "print (TSout['West']['Q1']['Amp'])\n", "print (TSout['West']['Q1']['Pha']) \n", "\n", "print (\"North\", Q1_pha_obs[-2:]-Q1_pha[-2:])\n", "print (TSout['North']['Q1']['Amp'] )\n", "print (TSout['North']['Q1']['Pha'] )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The model performs well when the dots are close to the red line." ] }, { "cell_type": "code", "execution_count": 85, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'North': {'S2': {'Amp': 1.007451551325621, 'Pha': -0.21518163627450804}, 'K1': {'Amp': 0.90919240501507015, 'Pha': 6.6534800674565417}, 'N2': {'Amp': 1.0005296016330354, 'Pha': 0.074030766043051699}, 'O1': {'Amp': 0.93156674821510022, 'Pha': 7.0982035048885166}, 'Q1': {'Amp': 0.9555357021589741, 'Pha': 7.2180672136925068}, 'M2': {'Amp': 0.99929495129476509, 'Pha': 0.030673451358239845}}, 'West': {'S2': {'Amp': 0.99747774151918511, 'Pha': 0.12379925207212139}, 'K1': {'Amp': 0.99002509395526239, 'Pha': -0.066133299415329166}, 'N2': {'Amp': 1.0056646519018293, 'Pha': -0.13657540771748944}, 'O1': {'Amp': 0.99381450442468544, 'Pha': -0.10726238789911235}, 'Q1': {'Amp': 0.99225198825699834, 'Pha': -0.23023997839629828}, 'M2': {'Amp': 0.99994657049399938, 'Pha': 0.0049726383435359893}}}\n" ] } ], "source": [ "print (TSout)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Statistics" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We would like to save some statistics so that we can determine which runs give us the best match with observations. So, we will define some functions that will help us calculate statistics." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Mean Error (absolute value)" ] }, { "cell_type": "code", "execution_count": 86, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def mean(diff):\n", " return np.mean(abs(diff))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### RMS Error" ] }, { "cell_type": "code", "execution_count": 87, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def rms(diff):\n", " return np.sqrt(np.mean(diff**2))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Complex differences" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is a way of measuring distances in the complex plane. We can think of our tidal amplitude and phase as a point on the complex plane. So we would like to measure the distance between a point given by the model and a point given by the observations. The function below does this." ] }, { "cell_type": "code", "execution_count": 88, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def complex_diff(Ao,go,Am,gm):\n", " #calculates complex differences between observations and model\n", " #Ao, go - amplitude and phase from observations\n", " #Am, gm - amplitude and phase from model\n", " D = np.sqrt((Ao*np.cos(np.pi*go/180)-Am*np.cos(np.pi*gm/180))**2 + \n", " (Ao*np.sin(np.pi*go/180)-Am*np.sin(np.pi*gm/180))**2)\n", " \n", " return D" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Some other things we will look at are\n", "\n", "$R = \\frac{A_m}{A_o}$, the ratio of modelled to observed amplitude and \n", "\n", "$\\Delta \\phi = \\phi_m - \\phi_o$, the difference betwen modelled and observed phase." ] }, { "cell_type": "code", "execution_count": 89, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 0.0379399 0.03605283 0.00978363 0.03761776] 0.0303485306333\n" ] } ], "source": [ "#R\n", "R_M2 = M2_amp/M2_amp_obs\n", "R_K1 = K1_amp/K1_amp_obs\n", "#delta phi (adjust so between -180, 180)\n", "Dphi_M2 = M2_pha-M2_pha_obs; \n", "Dphi_M2 = Dphi_M2 -360*(Dphi_M2>180) + 360*(Dphi_M2<-180)\n", "Dphi_K1 = K1_pha-K1_pha_obs\n", "Dphi_K1 = Dphi_K1 -360*(Dphi_K1>180) + 360*(Dphi_K1<-180)\n", "#Complex differences\n", "D_M2= complex_diff(np.array(M2_amp_obs),np.array(M2_pha_obs), np.array(M2_amp),np.array(M2_pha))\n", "D_K1= complex_diff(np.array(K1_amp_obs),np.array(K1_pha_obs), np.array(K1_amp),np.array(K1_pha))\n", "D_O1= complex_diff(np.ma.array(O1_amp_obs),np.ma.array(O1_pha_obs), np.ma.array(O1_amp),np.ma.array(O1_pha))\n", "D_S2= complex_diff(np.ma.array(S2_amp_obs),np.ma.array(S2_pha_obs), np.ma.array(S2_amp),np.ma.array(S2_pha))\n", "D_N2= complex_diff(np.ma.array(N2_amp_obs),np.ma.array(N2_pha_obs), np.ma.array(N2_amp),np.ma.array(N2_pha))\n", "D_Q1= complex_diff(np.ma.array(Q1_amp_obs),np.ma.array(Q1_pha_obs), np.ma.array(Q1_amp),np.ma.array(Q1_pha))\n", "print (D_M2[2:6], np.mean(D_M2[2:6]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Saving the results" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will now save these statistics in a spreadsheet" ] }, { "cell_type": "code", "execution_count": 90, "metadata": { "collapsed": false }, "outputs": [ { "ename": "TypeError", "evalue": "a bytes-like object is required, not 'str'", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[1;34m'Station Name'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[1;34m'R (M2)'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'Delta phi (M2)'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'D (M2)'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 8\u001b[1;33m \u001b[1;34m'R (K1)'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'Delta phi (K1)'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'D (K1)'\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 9\u001b[0m ])\n\u001b[0;32m 10\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mstn\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnumsta\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;31mTypeError\u001b[0m: a bytes-like object is required, not 'str'" ] } ], "source": [ "outfile = runname+'.csv'\n", "\n", "with open(outfile, 'wb') as csvfile:\n", " writer = csv.writer(csvfile, delimiter=',')\n", " writer.writerow([\n", " 'Station Name', \n", " 'R (M2)', 'Delta phi (M2)', 'D (M2)',\n", " 'R (K1)', 'Delta phi (K1)', 'D (K1)'\n", " ])\n", " for stn in range(numsta):\n", " location = stations_obs[stn]\n", " writer.writerow([stations_obs[stn],\n", " R_M2[stn], Dphi_M2[stn], D_M2[stn],\n", " R_K1[stn], Dphi_K1[stn], D_K1[stn]])\n", "\n", " #write averages and rms\n", " writer.writerow(['Mean Difference',\n", " mean(M2_amp-M2_amp_obs),mean(Dphi_M2),mean(D_M2), \n", " mean(K1_amp-K1_amp_obs),mean(Dphi_K1),mean(D_K1)])\n", " writer.writerow(['RMS Difference',\n", " rms(M2_amp-M2_amp_obs),rms(Dphi_M2),rms(D_M2), \n", " rms(K1_amp-K1_amp_obs),rms(Dphi_K1),rms(D_K1)])\n", " #without the north\n", " writer.writerow(['Mean Difference no North no PR',\n", " mean(M2_amp[1:split2]-M2_amp_obs[1:split2]),mean(Dphi_M2[1:split2]),mean(D_M2[1:split2]), \n", " mean(K1_amp[1:split2]-K1_amp_obs[1:split2]),mean(Dphi_K1[1:split2]),mean(D_K1[1:split2])])\n", " writer.writerow(['RMS Difference no North no PR',\n", " rms(M2_amp[1:split2]-M2_amp_obs[1:split2]),rms(Dphi_M2[1:split2]),rms(D_M2[1:split2]), \n", " rms(K1_amp[1:split2]-K1_amp_obs[1:split2]),rms(Dphi_K1[1:split2]),rms(D_K1[1:split2])])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now there is a csv file in this directory with data about this run. It should be called runname.csv (where runname is the string we defined at the beginning of the notebook).\n", "\n", "Things to try:\n", "1. Add the complex differences information printed in the .csv file to tide_runs.ods. Also, if you notice any discrepancies, you can correct them. (Check M2 amplitude at Yorke Island)\n", "2. Work through the notebook with a different run. There is a list of runs in tide_runs.ods\n", "3. Commit and push any changes you've made to this notebook and tide_runs.odt. \n", "Try this:\n", " * hg status (see what changes have been made)\n", " * hg in\n", " * hg commit mynotebook.ipynb (write a commit message and then save and exit)\n", " * hg commit tide_runs.odt\n", " * hg pull --rebase\n", " * pg push\n", " \n", "4. Add any new csv files to the repository.\n", "Try this:\n", " * hg add filename.csv\n", " * hg commit filename.csv\n", " * hg pull --rebase\n", " * hg push\n", " \n", "5. Repeat with all the runs listed in tide_runs.odt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Plots comparing measured and model amplitudes and phases" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "plt.figure(figsize=(20,12))\n", "\n", "plt.subplot(3,2,1)\n", "plt.plot(np.array(M2_amp), '-bo', label = 'model')\n", "plt.plot(M2_amp_obs, 'r-o', label = 'observation')\n", "plt.ylim((0.3,1.3))\n", "plt.title('M2 Amplitude')\n", "plt.legend( loc='upper left' )\n", "\n", "plt.subplot(3,2,2)\n", "plt.plot(np.array(K1_amp), '-bo', label = 'model')\n", "plt.plot(K1_amp_obs, 'r-o', label = 'observation')\n", "plt.title('K1 Amplitude')\n", "\n", "plt.subplot(3,2,3)\n", "# use the un-wrap function to plot the M2 phase more smoothly\n", "pha_uwm = 180./np.pi * np.unwrap((np.array(M2_pha))*np.pi/180.)\n", "plt.plot(pha_uwm, '-bo', label = 'model')\n", "pha_uw = 180./np.pi * np.unwrap(np.array(M2_pha_obs)*np.pi/180.)\n", "plt.plot(pha_uw, 'r-o', label = 'observation')\n", "plt.title('M2 Phase')\n", "\n", "plt.subplot(3,2,4)\n", "pha_uw = 180./np.pi * np.unwrap((np.array(K1_pha))*np.pi/180.)\n", "plt.plot(pha_uw, '-bo', label = 'model')\n", "plt.plot(K1_pha_obs, 'r-o', label = 'observation')\n", "plt.ylim((245,295))\n", "plt.title('K1 Phase')\n", "\n", "plt.subplot(3,2,5)\n", "plt.plot(D_M2, '-bo', label = 'M2')\n", "plt.plot(D_K1, '-go', label = 'K1')\n", "plt.plot((0,30),(0.05,0.05),'k')\n", "plt.plot((0,30),(0.10,0.10),'r')\n", "plt.ylim((0,0.5))\n", "plt.title('D error')\n", "plt.legend( loc='upper left' )\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "S_M2_amp =[0.81796594981353787, 0.58179663165988404, 0.32721527983734328, 0.33301854629278987, 0.33182009758572201, 0.33335988978569214, 0.37262690513061936, 0.47803724001914821, 0.76169885554259253, 0.70303608264417961, 0.83441811463548532, 0.81038178372584047, 0.88924863927669251, 0.92291668835873131, 0.92528642573620279, 0.92708554337687221, 0.97186745021953891, 0.99008962519318389, 1.0104938653574274, 1.0424872258774132, 1.0339748559161059, 0.81647033002975733, 0.62855943384043089, 0.6281276494314838, 0.59982497040887706, 0.91766195442050613, 0.98470695914773221, 1.1750995194900644, 1.1641418000518871]\n", "S_M2_pha =[231.70087338077767, 246.8346272505064, 280.61345724675436, 294.01113561226316, 298.32945634086707, 302.34910604358527, 349.45735869033183, 9.6187167682703034, 33.026761185393298, 25.25761537536448, 32.142427075739192, 28.724244493671563, 29.854819687552208, 30.589764003661628, 30.716301323815514, 30.845594548277688, 31.352881756715988, 31.583460490483901, 32.581761034889155, 32.88157718881746, 33.349768476521263, 18.907952568145106, 357.37521447974547, 344.966653323424, 351.41260102119486, 310.27266040290533, 299.6131712504702, 274.6100536345358, 273.39389940946035]\n", "S_K1_amp =[0.46620238668937491, 0.54775592624668346, 0.62336982624343718, 0.63973158805461383, 0.65184922440835646, 0.66057847399548664, 0.72550375684688451, 0.75355773256988012, 0.84304869161948126, 0.82304770052036202, 0.8564923283826591, 0.84454355069955411, 0.86725095546444986, 0.87129988589140794, 0.86593626071139251, 0.87399549321899139, 0.88682087783902708, 0.89052058701213388, 0.89968632710580798, 0.90846210405972316, 0.91010616927977983, 0.84667321748426194, 0.79016417661225991, 0.75020026652394067, 0.79220776158699524, 0.66728988733516137, 0.64016020034578169, 0.56781550023732319, 0.5644943600526271]\n", "S_K1_pha =[249.16405591522613, 257.05973209735021, 266.58707764365994, 267.05565730516582, 267.3703139483444, 267.57406182793716, 275.3147133634908, 279.37270299241624, 287.55876409635982, 284.10168038262879, 287.02142153805926, 284.99250055965047, 285.91139251534031, 286.31767919206936, 285.53519011464579, 286.15531294135207, 285.95283693592955, 286.94132412236769, 286.58602905644142, 286.95109254814417, 287.2626660314782, 284.94162283332389, 282.4623568253017, 279.60944497950373, 283.00778612693961, 270.05868447585368, 267.32225157060719, 261.00793896779192, 261.23071856768365]\n", "S_D_M2 =[ 0.16625969, 0.17951281, 0.15906926, 0.14399509, 0.11621831, 0.13389999,\n", " 0.09472401, 0.10776225, 0.04434292, 0.02324491, 0.01103787, 0.01309181,\n", " 0.02582918, 0.05829261, 0.01065969, 0.02335071, 0.00825068, 0.00585006,\n", " 0.03045116, 0.04977764, 0.04220142, 0.01121144, 0.1262386, 0.0603622,\n", " 0.53398219, 0.09257765, 0.12175468, 0.03495713, 0.03319541]\n", "S_D_K1 = [ 0.04172159, 0.04244914, 0.02657573, 0.01213842, 0.03215966, 0.03138739,\n", " 0.03245773, 0.00826599, 0.03342904, 0.03920169, 0.01186245, 0.01091408,\n", " 0.03149171, 0.03627737, 0.0093824, 0.01469177, 0.00721647, 0.01116176,\n", " 0.00431927, 0.02450076, 0.00716952, 0.01392518, 0.02894072, 0.02017138,\n", " 0.17277305, 0.01172017, 0.03845835, 0.00998477, 0.01369324]\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "fig, ax = plt.subplots(3,1,figsize=(10,10))\n", "ax[0].plot(S_M2_amp, '-o', color='grey')\n", "ax[0].plot(S_K1_amp, '-s', color='grey')\n", "ax[0].plot(M2_amp_obs, 'g-o', label = 'M2 observation')\n", "ax[0].plot(np.array(M2_amp), '-ro', label = 'M2 model')\n", "ax[0].plot(K1_amp_obs, 'k-s', label = 'K1 observation')\n", "ax[0].plot(np.array(K1_amp), '-bs', label = 'K1 model')\n", "ax[0].set_title('Barotropic Tides - Sea Surface Height')\n", "ax[0].set_ylabel('Amplitude(m)')\n", "ax[0].legend(loc='upper left')\n", "\n", "pha_uw = 180./np.pi * np.unwrap(np.array(S_M2_pha)*np.pi/180.)\n", "ax[1].plot(pha_uw, '-o', color='grey')\n", "pha_uw = 180./np.pi * np.unwrap(np.array(S_K1_pha)*np.pi/180.)\n", "ax[1].plot(pha_uw, '-s', color='grey')\n", "pha_uw = 180./np.pi * np.unwrap(np.array(M2_pha_obs)*np.pi/180.)\n", "ax[1].plot(pha_uw, 'g-o', label = 'M2 observation')\n", "pha_uwm = 180./np.pi * np.unwrap((np.array(M2_pha))*np.pi/180.)\n", "ax[1].plot(pha_uwm, '-ro', label = 'M2 model')\n", "ax[1].plot(K1_pha_obs, 'k-s', label = 'K1 observation')\n", "pha_uw = 180./np.pi * np.unwrap((np.array(K1_pha))*np.pi/180.)\n", "ax[1].plot(pha_uw, '-bs', label = 'K1 model')\n", "ax[1].set_ylabel('Phase (deg UTC)')\n", "ax[1].legend(loc=(0.36, 0.4))\n", "\n", "ax[2].plot(S_D_M2, '-o', color = 'grey')\n", "ax[2].plot(S_D_K1, '-s', color = 'grey')\n", "ax[2].plot(D_M2, '-ro', label = 'M2')\n", "ax[2].plot(D_K1, '-bs', label = 'K1')\n", "ax[2].yaxis.grid(True)\n", "ax[2].set_ylim((0,0.6))\n", "ax[2].legend( loc='upper left' )\n", "ax[2].set_ylabel('Complex Difference (m)')\n", "ax[2].set_xlabel('Station Number (see map)')\n", "\n", "ax[0].set_xlim((0,28))\n", "ax[2].set_xlim((0,28))\n", "ax[1].set_xlim((0,28))\n", "\n", "ax[0].text(15, 0.35, 'Grey is Soontiens et al (2016) Tides')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "plt.figure(figsize=(12,5))\n", "plt.plot(M2_amp_obs, 'r-s', label = 'observation')\n", "plt.plot(M2_amp, '-mo', label='results')\n", "print (np.mean(M2_amp[2:6]), np.mean(M2_amp[2:6])*SoGratio)\n", "print (np.mean(M2_amp_obs[2:6]))" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "plt.figure(figsize=(12,5))\n", "pha_uw = 180./np.pi * np.unwrap(np.array(M2_pha_obs)*np.pi/180.)\n", "plt.plot(pha_uw, 'r-s', label = 'observation')\n", "pha_uw_mod = 180./np.pi * np.unwrap(np.array(M2_pha)*np.pi/180.)\n", "plt.plot(pha_uw_mod, 'b*-', label='results')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "plt.plot(pha_uw_mod-pha_uw, 'bo-')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "diffy_obs = pha_uw[1:]-pha_uw[0:-1]\n", "diffy_new = pha_uw_mod[1:]-pha_uw_mod[:-1]\n", "\n", "plt.plot(diffy_obs,'r',label='obs')\n", "plt.plot(diffy_new,'g*-', label='new')\n", "\n", "plt.xlim((0,15))\n", "plt.ylim((-5,50))\n", "plt.legend()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "je=15\n", "plt.figure(figsize=(14,7))\n", "plt.subplot(1,2,1)\n", "plt.plot(pha_uw[:je], M2_amp_obs[:je],'ro-')\n", "plt.plot(pha_uw_mod[:je],np.array(M2_amp[:je]),'ms-')\n", "\n", "plt.arrow(365-20, 0.55+0.2, 20, -0.2)\n", "plt.text(365-100, 0.55+0.2, \"too much amplitude drop in Boundary Pass\")\n", "plt.subplot(1,2,2)\n", "plt.plot(pha_uw[:je], M2_amp_obs[:je],'ro-')\n", "\n", "plt.plot(pha_uw_mod[:je],np.array(M2_amp[:je]),'ms-')\n", "plt.arrow(265+20, 0.55+0.2, -20, -0.2)\n", "plt.text(265+20, 0.55+0.2, \"too little phase shift in JdF\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "cmap = plt.get_cmap('PuBu')\n", "cmap.set_bad('burlywood')\n", "\n", "fig,axs=plt.subplots(3, 2, figsize=(8,20))\n", "\n", "constituent = ('M2', 'K1', 'O1', 'S2', 'N2', 'Q1')\n", "error_D = (D_M2, D_K1, D_O1, D_S2, D_N2, D_Q1)\n", "\n", "\n", "for row in range(3):\n", "\n", " for ax, error_D1, const in zip(axs[row], error_D[row*2:row*2+2], constituent[row*2:row*2+2]):\n", " ax.pcolormesh(X,Y,bathy,cmap='PuBu')\n", "\n", " for stn in range(numsta):\n", " location = stations_obs[stn]\n", " lon=-harm_obs.lon[harm_obs.site==location]\n", " lat=harm_obs.lat[harm_obs.site==location]\n", " if error_D1 [stn] <= 0.05:\n", " ax.plot(lon,lat,'og',label=location,markersize=10,markeredgecolor='g')\n", " if error_D1 [stn] > 0.1:\n", " ax.plot(lon,lat,'or',label=location,markersize=10,markeredgecolor='r')\n", " if 0.1 >= error_D1[stn] > 0.05:\n", " ax.plot(lon,lat,'oy',label=location,markersize=10,markeredgecolor='y')\n", " \n", " ax.annotate(stn, xy = (lon,lat), xytext = (5,5),ha = 'right', va = 'bottom',\n", " textcoords = 'offset points')\n", " ax.set_title(const)\n", " ax.axis([-126.1,-122,47,51])\n", " \n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### First Plot: M2 D error. Second Plot: K1 D error. Markers increase in size as D error increases." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Green: D error <= 0.05, Yellow: 0.05 < D error <= 0.1, Red: D error > 0.1" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "fig, axs = plt.subplots(4,2,figsize=(10,15))\n", "axs[0,0].plot(np.array(O1_amp)/np.array(K1_amp), '-bo', label = 'model')\n", "axs[0,0].plot((0,28),(0.560,0.560), 'r-', label = 'observation')\n", "axs[0,0].set_title('O1/K1 Amplitude')\n", "pha_uw = 180./np.pi * np.unwrap((np.array(O1_pha)-np.array(K1_pha))*np.pi/180.)\n", "axs[0,1].plot(pha_uw, '-bo', label = 'model')\n", "axs[0,1].plot((0,28),(-22.9,-22.9), 'r-', label = 'observation')\n", "axs[0,1].set_title('O1-K1 Phase')\n", "\n", "axs[1,0].plot(np.array(S2_amp)/np.array(M2_amp), '-bo', label = 'model')\n", "axs[1,0].plot((0,28),(0.249,0.249), 'r-', label = 'observation')\n", "axs[1,0].set_title('S2/M2 Amplitude')\n", "pha_uw = 180./np.pi * np.unwrap((np.array(S2_pha)-np.array(M2_pha))*np.pi/180.)\n", "axs[1,1].plot(pha_uw, '-bo', label = 'model')\n", "axs[1,1].plot((0,28),( 28.7, 28.7), 'r-', label = 'observation')\n", "axs[1,1].set_title('S2-M2 Phase')\n", "\n", "axs[2,0].plot(np.array(N2_amp)/np.array(M2_amp), '-bo', label = 'model')\n", "axs[2,0].plot((0,28),(0.200,0.200), 'r-', label = 'observation')\n", "axs[2,0].set_title('N2/M2 Amplitude')\n", "\n", "pha_uw = 180./np.pi * np.unwrap((np.array(N2_pha)-np.array(M2_pha))*np.pi/180.)\n", "axs[2,1].plot(pha_uw, '-bo', label = 'model')\n", "axs[2,1].plot((0,28),(-28.3, -28.3), 'r-', label = 'observation')\n", "axs[2,1].set_title('N2-M2 Phase')\n", "\n", "axs[3,0].plot(np.array(Q1_amp)/np.array(K1_amp), '-bo', label = 'model')\n", "axs[3,0].plot((0,28),(0.089,0.089), 'r-', label = 'observation')\n", "axs[3,0].set_title('Q1/K1 Amplitude')\n", "\n", "pha_uw = 180./np.pi * np.unwrap((np.array(Q1_pha)-np.array(K1_pha))*np.pi/180.)\n", "axs[3,1].plot(pha_uw+360., '-bo', label = 'model')\n", "axs[3,1].plot((0,28),(-27.3+360,-27.3+360), 'r-', label = 'observation')\n", "axs[3,1].set_title('Q1-K1 Phase')\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "sample = 17\n", "start = np.zeros(sample)\n", "tend = np.zeros(sample)\n", "for i in range(sample):\n", " start[i] = 196+(480-196)*np.random.rand()\n", " tend[i] = te-(480-196)*np.random.rand()\n", "print start\n", "print tend\n", "timelength = (tend-start)/96.\n", "print np.mean(timelength),2*np.std(timelength)\n", "print time[start[1]:tend[1]]\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "#allocate space for our arrays\n", "M2_amp=np.zeros((numsta,sample)); M2_pha=np.zeros((numsta,sample))\n", "K1_amp=np.zeros((numsta,sample)); K1_pha=np.zeros((numsta,sample))\n", "O1_amp=np.zeros((numsta,sample)); O1_pha=np.zeros((numsta,sample))\n", "S2_amp=np.zeros((numsta,sample)); S2_pha=np.zeros((numsta,sample))\n", "N2_amp=np.zeros((numsta,sample)); N2_pha=np.zeros((numsta,sample))\n", "Q1_amp=np.zeros((numsta,sample)); Q1_pha=np.zeros((numsta,sample))\n", "\n", "\n", "\n", "\n", "for it,tst,tet in zip(range(sample),start.astype(int),tend.astype(int)):\n", " \n", " timeplus = np.zeros([5,tet-tst])\n", " \n", " for stn in range(numsta):\n", " fT1 = NC.Dataset(name+stations[stn]+'.nc','r')\n", " time = (fT1.variables[\"time_counter\"][tst:tet]-timeinc)/3600. # want hours not seconds\n", " ssh = fT1.variables[\"sossheig\"][:,0,0]\n", " timeplus[0] = time\n", " timeplus[1] = P1K1_amp[stn]*np.ones_like(time); timeplus[2] = P1K1_pha[stn]*np.ones_like(time)\n", " timeplus[3] = K2S2_amp[stn]*np.ones_like(time); timeplus[4] = K2S2_pha[stn]*np.ones_like(time) \n", " \n", " fitted, cov = curve_fit(sixplustwo,timeplus,ssh[tst:tet]) \n", " if fitted[0] < 0:\n", " fitted[0] = -fitted[0]\n", " fitted[1] = fitted[1]+180\n", "\n", " M2_amp[stn,it] = fitted[0]\n", " pha = fitted[1]\n", " if pha > 360:\n", " pha=pha-360\n", " elif pha < 0:\n", " pha = pha + 360\n", " M2_pha[stn,it] = pha\n", " \n", " if fitted[2] < 0:\n", " fitted[2] = -fitted[2]\n", " fitted[3] = fitted[3]+180\n", "\n", " K1_amp[stn,it] = fitted[2]\n", " pha= fitted[3]\n", " if pha > 360:\n", " pha=pha-360\n", " K1_pha[stn,it]= pha \n", " \n", " if fitted[4] < 0:\n", " fitted[4] = -fitted[4]\n", " fitted[5] = fitted[5]+180\n", " O1_amp[stn,it] =fitted[4]\n", " pha= fitted[5]\n", " if pha > 360:\n", " pha=pha-360\n", " O1_pha[stn,it]= pha \n", " \n", " if fitted[6] < 0:\n", " fitted[6] = -fitted[6]\n", " fitted[7] = fitted[7]+180\n", " S2_amp[stn,it] =fitted[6]\n", " pha= fitted[7]\n", " if pha > 360:\n", " pha=pha-360\n", " S2_pha[stn,it]= pha \n", " \n", " if fitted[8] < 0:\n", " fitted[8] = -fitted[8]\n", " fitted[9] = fitted[9]+180\n", " N2_amp[stn,it] = fitted[8]\n", " pha= fitted[9]\n", " if pha > 360:\n", " pha=pha-360\n", " N2_pha[stn,it] = pha\n", " \n", " if fitted[10] < 0:\n", " fitted[10] = -fitted[10]\n", " fitted[11] = fitted[11]+180\n", " Q1_amp[stn,it] = fitted[10]\n", " pha= fitted[11]\n", " if pha > 360:\n", " pha=pha-360\n", " Q1_pha[stn,it] = pha\n", " " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "jdef = range(3)\n", "south = range(14,18)\n", "north = range(27,29)\n", "print 'M2'\n", "print ' JdeFuca'\n", "print np.mean(M2_amp[jdef]),2*np.std(np.mean(M2_amp[jdef],axis=0))\n", "print np.mean(M2_amp_obs[jdef]), np.mean(M2_amp_obs[jdef])-np.mean(M2_amp[jdef])\n", "print np.mean(M2_amp_obs[jdef])/np.mean(M2_amp[jdef])\n", "print np.mean(M2_pha[jdef]),2*np.std(np.mean(M2_pha[jdef],axis=0))\n", "print np.mean(M2_pha_obs[jdef]), np.mean(M2_pha_obs[jdef])-np.mean(M2_pha[jdef])\n", "print ' South'\n", "print np.mean(M2_amp[south]),2*np.std(np.mean(M2_amp[south],axis=0))\n", "print np.mean(M2_amp_obs[south]), np.mean(M2_amp_obs[south])-np.mean(M2_amp[south])\n", "print np.mean(M2_amp_obs[south])/np.mean(M2_amp[south])\n", "print np.mean(M2_pha[south]),2*np.std(np.mean(M2_pha[south],axis=0))\n", "print np.mean(M2_pha_obs[south]), np.mean(M2_pha_obs[south])-np.mean(M2_pha[south])\n", "print ' North'\n", "print np.mean(M2_amp[north]),2*np.std(np.mean(M2_amp[north],axis=0))\n", "print np.mean(M2_amp_obs[north]), np.mean(M2_amp_obs[north])-np.mean(M2_amp[north])\n", "print np.mean(M2_amp_obs[north])/np.mean(M2_amp[north])\n", "print np.mean(M2_pha[north]),2*np.std(np.mean(M2_pha[north],axis=0))\n", "print np.mean(M2_pha_obs[north]), np.mean(M2_pha_obs[north])-np.mean(M2_pha[north])\n", "print '==============================================='\n", "print 'K1'\n", "print ' JdeFuca'\n", "print np.mean(K1_amp[jdef]),2*np.std(np.mean(K1_amp[jdef],axis=0))\n", "print np.mean(K1_amp_obs[jdef]), np.mean(K1_amp_obs[jdef])-np.mean(K1_amp[jdef])\n", "print np.mean(K1_amp_obs[jdef])/np.mean(K1_amp[jdef])\n", "print np.mean(K1_pha[jdef]),2*np.std(np.mean(K1_pha[jdef],axis=0))\n", "print np.mean(K1_pha_obs[jdef]), np.mean(K1_pha_obs[jdef])-np.mean(K1_pha[jdef])\n", "print ' South'\n", "print np.mean(K1_amp[south]),2*np.std(np.mean(K1_amp[south],axis=0))\n", "print np.mean(K1_amp_obs[south]), np.mean(K1_amp_obs[south])-np.mean(K1_amp[south])\n", "print np.mean(K1_amp_obs[south])/np.mean(K1_amp[south])\n", "print np.mean(K1_pha[south]),2*np.std(np.mean(K1_pha[south],axis=0))\n", "print np.mean(K1_pha_obs[south]), np.mean(K1_pha_obs[south])-np.mean(K1_pha[south])\n", "print ' North'\n", "print np.mean(K1_amp[north]),2*np.std(np.mean(K1_amp[north],axis=0))\n", "print np.mean(K1_amp_obs[north]), np.mean(K1_amp_obs[north])-np.mean(K1_amp[north])\n", "print np.mean(K1_amp_obs[north])/np.mean(K1_amp[north])\n", "print np.mean(K1_pha[north]),2*np.std(np.mean(K1_pha[north],axis=0))\n", "print np.mean(K1_pha_obs[north]), np.mean(K1_pha_obs[north])-np.mean(K1_pha[north])\n", "print '==============================================='" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "print 'O1'\n", "print ' South'\n", "print np.mean(O1_amp[south]/K1_amp[south]),2*np.std(np.mean(O1_amp[south]/K1_amp[south],axis=0))\n", "print np.mean(O1_amp_obs[south]/K1_amp_obs[south]), (np.mean(O1_amp_obs[south]/K1_amp_obs[south])\n", " -np.mean(O1_amp[south]/K1_amp[south]))\n", "print np.mean(O1_amp_obs[south]/K1_amp_obs[south])/np.mean(O1_amp[south]/K1_amp[south])\n", "print np.mean(O1_pha[south]-K1_pha[south]),2*np.std(np.mean(O1_pha[south]-K1_pha[south],axis=0))\n", "print np.mean(O1_pha_obs[south]-K1_pha_obs[south]), (np.mean(O1_pha_obs[south]-K1_pha_obs[south])\n", " -np.mean(O1_pha[south]-K1_pha[south]))\n", "print ' North'\n", "print np.mean(O1_amp[north]/K1_amp[north]),2*np.std(np.mean(O1_amp[north]/K1_amp[north],axis=0))\n", "print np.mean(O1_amp_obs[north]/K1_amp_obs[north]), (np.mean(O1_amp_obs[north]/K1_amp_obs[north])\n", " -np.mean(O1_amp[north]/K1_amp[north]))\n", "print np.mean(O1_amp_obs[north]/K1_amp_obs[north])/np.mean(O1_amp[north]/K1_amp[north])\n", "print np.mean(O1_pha[north]-K1_pha[north]),2*np.std(np.mean(O1_pha[north]-K1_pha[north],axis=0))\n", "print np.mean(O1_pha_obs[north]-K1_pha_obs[north]), (np.mean(O1_pha_obs[north]-K1_pha_obs[north])\n", " -np.mean(O1_pha[north]-K1_pha[north]))\n", "print '==============================================='\n", "print 'S2'\n", "code = ('south','north')\n", "for dir,dire in zip(code,(south,north)):\n", " print dir\n", " print np.mean(S2_amp[dire]/M2_amp[dire]),2*np.std(np.mean(S2_amp[dire]/M2_amp[dire],axis=0))\n", " print np.mean(S2_amp_obs[dire]/M2_amp_obs[dire]), (np.mean(S2_amp_obs[dire]/M2_amp_obs[dire])\n", " -np.mean(S2_amp[dire]/M2_amp[dire]))\n", " print np.mean(S2_amp_obs[dire]/M2_amp_obs[dire])/np.mean(S2_amp[dire]/M2_amp[dire])\n", " unwrap = np.unwrap(np.array(S2_pha)*np.pi/180.)*180./np.pi\n", " M2_un = np.unwrap(np.array(M2_pha)*np.pi/180.)*180./np.pi\n", " plt.plot (unwrap[dire],'r',M2_un[dire],'b')\n", " print np.mean(unwrap[dire]-M2_un[dire])+360.,2*np.std(np.mean(unwrap[dire]-M2_un[dire],axis=0))\n", " print np.mean(S2_pha_obs[dire]-M2_pha_obs[dire]), (np.mean(S2_pha_obs[dire]-M2_pha_obs[dire])\n", " -np.mean(unwrap[dire]-M2_un[dire]))-360." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "const = ('Q1', 'N2')\n", "model_amp = (Q1_amp, N2_amp)\n", "model_pha = ()\n", "for const, model_amp, model_pha, obs_amp, obs_pha in zip(('Q1','N2'),\n", " (Q1_amp, N2_amp),(Q1_pha, N2_pha), \n", " (Q1_amp_obs, N2_amp_obs), (Q1_pha_obs, N2_pha_obs)):\n", " print const\n", " for dir,dire in zip(code,(south,north)):\n", " print dir\n", " print np.mean(model_amp[dire]/K1_amp[dire]),2*np.std(np.mean(model_amp[dire]/K1_amp[dire],axis=0))\n", " print np.mean(obs_amp[dire]/K1_amp_obs[dire]), (np.mean(obs_amp[dire]/K1_amp_obs[dire])\n", " -np.mean(model_amp[dire]/K1_amp[dire]))\n", " print np.mean(obs_amp[dire]/K1_amp_obs[dire])/np.mean(model_amp[dire]/K1_amp[dire])\n", " unwrap = np.unwrap(np.array(model_pha)*np.pi/180.)*180./np.pi\n", " K1_un = np.unwrap(np.array(K1_pha)*np.pi/180.)*180./np.pi\n", " print np.mean(unwrap[dire]-K1_un[dire]),2*np.std(np.mean(unwrap[dire]-K1_un[dire],axis=0))\n", " print np.mean(obs_pha[dire]-K1_pha_obs[dire]), (np.mean(obs_pha[dire]-K1_pha_obs[dire])\n", " -np.mean(unwrap[dire]-K1_un[dire]))" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "fig,axs = plt.subplots(6,2,figsize=(15,25))\n", "for i in range(sample):\n", " pha_uw = 180./np.pi * np.unwrap(np.array(M2_pha[:,i])*np.pi/180.)\n", " axs[0,1].plot(pha_uw ,'-ob', label = 'model')\n", "pha_uw = 180./np.pi * np.unwrap(np.array(M2_pha_obs)*np.pi/180.)\n", "axs[0,1].plot(pha_uw, 'r-*', label = 'observation')\n", "axs[0,1].set_title('M2 Phase')\n", "for i in range(sample):\n", " axs[0,0].plot(M2_amp[:,i], '-bo', label = 'model')\n", "axs[0,0].plot(M2_amp_obs, 'r-*', label = 'observation')\n", "axs[0,0].set_title('M2 Amp')\n", "\n", "for i in range(sample):\n", " if K1_pha[0,i] < -360:\n", " K1_pha[0,i] = K1_pha[0,i] +720.\n", " elif K1_pha[0,i] < 0:\n", " K1_pha[0,i] = K1_pha[0,i] + 360.\n", " pha_uw = 180./np.pi * np.unwrap(np.array(K1_pha[:,i])*np.pi/180.)\n", " axs[1,1].plot(pha_uw, '-bo', label = 'model')\n", "axs[1,1].plot(K1_pha_obs, 'r-*', label = 'observation')\n", "axs[1,1].set_title('K1 Phase')\n", "for i in range(sample):\n", " axs[1,0].plot(K1_amp[:,i], '-bo', label = 'model')\n", "axs[1,0].plot(K1_amp_obs, 'r-*', label = 'observation')\n", "axs[1,0].set_title('K1 Amp')\n", "\n", "for i in range(sample):\n", " if O1_pha[0,i] < 0:\n", " O1_pha[0,i] = O1_pha[0,i] + 360\n", " pha_uw = 180./np.pi * np.unwrap(np.array(O1_pha[:,i])*np.pi/180.)\n", " axs[2,1].plot(pha_uw, '-bo', label = 'model')\n", "axs[2,1].plot(O1_pha_obs, 'r-*', label = 'observation', markersize = 15)\n", "axs[2,1].set_title('O1 Phase')\n", "for i in range(sample):\n", " axs[2,0].plot(O1_amp[:,i], '-bo', label = 'model')\n", "axs[2,0].plot(O1_amp_obs, 'r-*', label = 'observation', markersize = 15)\n", "axs[2,0].set_title('O1 Amp')\n", "\n", "for i in range(sample):\n", " if S2_pha[0,i] < 0:\n", " S2_pha[0,i] = S2_pha[0,i] + 360\n", " pha_uw = 180./np.pi * np.unwrap(np.array(S2_pha[:,i])*np.pi/180.)\n", " axs[3,1].plot(pha_uw, '-bo', label = 'model')\n", "pha_uw = 180./np.pi * np.unwrap(np.array(S2_pha_obs)*np.pi/180.)\n", "vsmall = 1e-6\n", "pha_uwm = np.ma.masked_array(pha_uw, mask=(abs(pha_uw-360)