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Last active March 14, 2017 21:46
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{
"cells": [
{
"metadata": {
"editable": true,
"deletable": true
},
"cell_type": "markdown",
"source": "# Extract NECOFS water levels using NetCDF4-Python and analyze/visualize with Pandas"
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "# Plot forecast water levels from NECOFS model from list of lon,lat locations\n# (uses the nearest point, no interpolation)\nimport netCDF4\nimport datetime as dt\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom StringIO import StringIO\n%matplotlib inline",
"execution_count": 1,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "#NECOFS MassBay grid\nmodel='Massbay'\nurl='http://www.smast.umassd.edu:8080/thredds/dodsC/FVCOM/NECOFS/Forecasts/NECOFS_FVCOM_OCEAN_MASSBAY_FORECAST.nc'\n# GOM3 Grid\n#model='GOM3'\n#url='http://www.smast.umassd.edu:8080/thredds/dodsC/FVCOM/NECOFS/Forecasts/NECOFS_GOM3_FORECAST.nc'",
"execution_count": 2,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "def dms2dd(d,m,s):\n return d+(m+s/60.)/60.\n ",
"execution_count": 3,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "dms2dd(41,33,15.7)",
"execution_count": 4,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "41.55436111111111"
},
"metadata": {},
"execution_count": 4
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "-dms2dd(70,30,20.2)",
"execution_count": 5,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "-70.50561111111111"
},
"metadata": {},
"execution_count": 5
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "x = '''\nStation, Lat, Lon\nFalmouth Harbor, 41.541575, -70.608020\nSage Lot Pond, 41.554361, -70.505611\n'''",
"execution_count": 6,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "x = '''\nStation, Lat, Lon\nBoston, 42.368186, -71.047984\nCarolyn Seep Spot, 39.8083, -69.5917\nFalmouth Harbor, 41.541575, -70.608020\n'''",
"execution_count": 7,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "# Enter desired (Station, Lat, Lon) values here:\nx = '''\nStation, Lat, Lon\nBoston, 42.368186, -71.047984\nScituate Harbor, 42.199447, -70.720090\nScituate Beach, 42.209973, -70.724523\nFalmouth Harbor, 41.541575, -70.608020\nMarion, 41.689008, -70.746576\nMarshfield, 42.108480, -70.648691\nProvincetown, 42.042745, -70.171180\nSandwich, 41.767990, -70.466219\nHampton Bay, 42.900103, -70.818510\nGloucester, 42.610253, -70.660570\n'''",
"execution_count": 8,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "# Create a Pandas DataFrame\nobs=pd.read_csv(StringIO(x.strip()), sep=\",\\s*\",index_col='Station')",
"execution_count": 9,
"outputs": [
{
"output_type": "stream",
"text": "-c:2: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n",
"name": "stderr"
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "obs",
"execution_count": 10,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": " Lat Lon\nStation \nBoston 42.368186 -71.047984\nScituate Harbor 42.199447 -70.720090\nScituate Beach 42.209973 -70.724523\nFalmouth Harbor 41.541575 -70.608020\nMarion 41.689008 -70.746576\nMarshfield 42.108480 -70.648691\nProvincetown 42.042745 -70.171180\nSandwich 41.767990 -70.466219\nHampton Bay 42.900103 -70.818510\nGloucester 42.610253 -70.660570",
"text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Lat</th>\n <th>Lon</th>\n </tr>\n <tr>\n <th>Station</th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>Boston</th>\n <td>42.368186</td>\n <td>-71.047984</td>\n </tr>\n <tr>\n <th>Scituate Harbor</th>\n <td>42.199447</td>\n <td>-70.720090</td>\n </tr>\n <tr>\n <th>Scituate Beach</th>\n <td>42.209973</td>\n <td>-70.724523</td>\n </tr>\n <tr>\n <th>Falmouth Harbor</th>\n <td>41.541575</td>\n <td>-70.608020</td>\n </tr>\n <tr>\n <th>Marion</th>\n <td>41.689008</td>\n <td>-70.746576</td>\n </tr>\n <tr>\n <th>Marshfield</th>\n <td>42.108480</td>\n <td>-70.648691</td>\n </tr>\n <tr>\n <th>Provincetown</th>\n <td>42.042745</td>\n <td>-70.171180</td>\n </tr>\n <tr>\n <th>Sandwich</th>\n <td>41.767990</td>\n <td>-70.466219</td>\n </tr>\n <tr>\n <th>Hampton Bay</th>\n <td>42.900103</td>\n <td>-70.818510</td>\n </tr>\n <tr>\n <th>Gloucester</th>\n <td>42.610253</td>\n <td>-70.660570</td>\n </tr>\n </tbody>\n</table>\n</div>"
},
"metadata": {},
"execution_count": 10
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "# find the indices of the points in (x,y) closest to the points in (xi,yi)\ndef nearxy(x,y,xi,yi):\n ind = np.ones(len(xi),dtype=int)\n for i in np.arange(len(xi)):\n dist = np.sqrt((x-xi[i])**2+(y-yi[i])**2)\n ind[i] = dist.argmin()\n return ind",
"execution_count": 11,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "# open NECOFS remote OPeNDAP dataset \nnc=netCDF4.Dataset(url).variables",
"execution_count": 12,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "# find closest NECOFS nodes to station locations\nobs['0-Based Index'] = nearxy(nc['lon'][:],nc['lat'][:],obs['Lon'],obs['Lat'])\nobs",
"execution_count": 13,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": " Lat Lon 0-Based Index\nStation \nBoston 42.368186 -71.047984 90913\nScituate Harbor 42.199447 -70.720090 37964\nScituate Beach 42.209973 -70.724523 28474\nFalmouth Harbor 41.541575 -70.608020 47470\nMarion 41.689008 -70.746576 49654\nMarshfield 42.108480 -70.648691 24272\nProvincetown 42.042745 -70.171180 26595\nSandwich 41.767990 -70.466219 38036\nHampton Bay 42.900103 -70.818510 13022\nGloucester 42.610253 -70.660570 22082",
"text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Lat</th>\n <th>Lon</th>\n <th>0-Based Index</th>\n </tr>\n <tr>\n <th>Station</th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>Boston</th>\n <td>42.368186</td>\n <td>-71.047984</td>\n <td>90913</td>\n </tr>\n <tr>\n <th>Scituate Harbor</th>\n <td>42.199447</td>\n <td>-70.720090</td>\n <td>37964</td>\n </tr>\n <tr>\n <th>Scituate Beach</th>\n <td>42.209973</td>\n <td>-70.724523</td>\n <td>28474</td>\n </tr>\n <tr>\n <th>Falmouth Harbor</th>\n <td>41.541575</td>\n <td>-70.608020</td>\n <td>47470</td>\n </tr>\n <tr>\n <th>Marion</th>\n <td>41.689008</td>\n <td>-70.746576</td>\n <td>49654</td>\n </tr>\n <tr>\n <th>Marshfield</th>\n <td>42.108480</td>\n <td>-70.648691</td>\n <td>24272</td>\n </tr>\n <tr>\n <th>Provincetown</th>\n <td>42.042745</td>\n <td>-70.171180</td>\n <td>26595</td>\n </tr>\n <tr>\n <th>Sandwich</th>\n <td>41.767990</td>\n <td>-70.466219</td>\n <td>38036</td>\n </tr>\n <tr>\n <th>Hampton Bay</th>\n <td>42.900103</td>\n <td>-70.818510</td>\n <td>13022</td>\n </tr>\n <tr>\n <th>Gloucester</th>\n <td>42.610253</td>\n <td>-70.660570</td>\n <td>22082</td>\n </tr>\n </tbody>\n</table>\n</div>"
},
"metadata": {},
"execution_count": 13
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "# get time values and convert to datetime objects\ntimes = nc['time']\njd = netCDF4.num2date(times[:],times.units)",
"execution_count": 14,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "# get all time steps of water level from each station\nnsta = len(obs)\nz = np.ones((len(jd),nsta))\nfor i in range(nsta):\n z[:,i] = nc['zeta'][:,obs['0-Based Index'][i]]\n ",
"execution_count": 15,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "# make a DataFrame out of the interpolated time series at each location\nzvals=pd.DataFrame(z,index=jd,columns=obs.index)",
"execution_count": 16,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "# list out a few values\nzvals.head()",
"execution_count": 17,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "Station Boston Scituate Harbor Scituate Beach \\\n2017-03-11 00:00:00.000 0.260008 0.486000 0.381463 \n2017-03-11 01:01:52.500 1.052041 1.092550 1.129166 \n2017-03-11 01:58:07.500 1.647629 1.578530 1.592741 \n2017-03-11 03:00:00.000 1.702411 1.646736 1.677559 \n2017-03-11 04:01:52.500 1.414511 1.312948 1.327706 \n\nStation Falmouth Harbor Marion Marshfield Provincetown \\\n2017-03-11 00:00:00.000 0.392506 0.973188 0.371882 0.293114 \n2017-03-11 01:01:52.500 0.276473 0.553178 1.102932 1.018170 \n2017-03-11 01:58:07.500 0.046371 0.093620 1.598297 1.614599 \n2017-03-11 03:00:00.000 -0.070460 -0.450842 1.690268 1.803100 \n2017-03-11 04:01:52.500 -0.087120 -0.806962 1.335137 1.458376 \n\nStation Sandwich Hampton Bay Gloucester \n2017-03-11 00:00:00.000 0.330359 0.415981 0.436011 \n2017-03-11 01:01:52.500 1.046942 1.126426 1.117460 \n2017-03-11 01:58:07.500 1.628950 1.549906 1.555701 \n2017-03-11 03:00:00.000 1.792436 1.635421 1.627011 \n2017-03-11 04:01:52.500 1.433764 1.308162 1.252133 ",
"text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th>Station</th>\n <th>Boston</th>\n <th>Scituate Harbor</th>\n <th>Scituate Beach</th>\n <th>Falmouth Harbor</th>\n <th>Marion</th>\n <th>Marshfield</th>\n <th>Provincetown</th>\n <th>Sandwich</th>\n <th>Hampton Bay</th>\n <th>Gloucester</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>2017-03-11 00:00:00.000</th>\n <td>0.260008</td>\n <td>0.486000</td>\n <td>0.381463</td>\n <td>0.392506</td>\n <td>0.973188</td>\n <td>0.371882</td>\n <td>0.293114</td>\n <td>0.330359</td>\n <td>0.415981</td>\n <td>0.436011</td>\n </tr>\n <tr>\n <th>2017-03-11 01:01:52.500</th>\n <td>1.052041</td>\n <td>1.092550</td>\n <td>1.129166</td>\n <td>0.276473</td>\n <td>0.553178</td>\n <td>1.102932</td>\n <td>1.018170</td>\n <td>1.046942</td>\n <td>1.126426</td>\n <td>1.117460</td>\n </tr>\n <tr>\n <th>2017-03-11 01:58:07.500</th>\n <td>1.647629</td>\n <td>1.578530</td>\n <td>1.592741</td>\n <td>0.046371</td>\n <td>0.093620</td>\n <td>1.598297</td>\n <td>1.614599</td>\n <td>1.628950</td>\n <td>1.549906</td>\n <td>1.555701</td>\n </tr>\n <tr>\n <th>2017-03-11 03:00:00.000</th>\n <td>1.702411</td>\n <td>1.646736</td>\n <td>1.677559</td>\n <td>-0.070460</td>\n <td>-0.450842</td>\n <td>1.690268</td>\n <td>1.803100</td>\n <td>1.792436</td>\n <td>1.635421</td>\n <td>1.627011</td>\n </tr>\n <tr>\n <th>2017-03-11 04:01:52.500</th>\n <td>1.414511</td>\n <td>1.312948</td>\n <td>1.327706</td>\n <td>-0.087120</td>\n <td>-0.806962</td>\n <td>1.335137</td>\n <td>1.458376</td>\n <td>1.433764</td>\n <td>1.308162</td>\n <td>1.252133</td>\n </tr>\n </tbody>\n</table>\n</div>"
},
"metadata": {},
"execution_count": 17
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "# plotting at DataFrame is easy!\nax=zvals.plot(figsize=(16,4),grid=True,title=('NECOFS Forecast Water Level from %s Forecast' % model),legend=False);\n# read units from dataset for ylabel\nplt.ylabel(nc['zeta'].units)\n# plotting the legend outside the axis is a bit tricky\nbox = ax.get_position()\nax.set_position([box.x0, box.y0, box.width * 0.8, box.height])\nax.legend(loc='center left', bbox_to_anchor=(1, 0.5));\n",
"execution_count": 18,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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xiqIoJiNmi7t+3alWrVqxaNEioqKiCAkJ4erVq7z00ksAREdH07x5c1MdZiGD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iscKkRizKfF6Ojs3eXXlovuv3fLc2Ll5aI6VCWSV3xVnvbOoO3Xbeccc0ttNnFlWZlIPXRI/KWr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oKQ+PIM7iKPmGIfDZZ8BoDGN/ST8Bb2qYFffDD6G8HIPWPooMrfD21n38gdxUjuMdjjT9W717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\npZRSSimllFIeRzurSimllFJKKaU8zv8DKnV70qEm2uAAAAAASUVORK5CYII=\n",
"text/plain": "<matplotlib.figure.Figure at 0x7fa7967ba950>"
},
"metadata": {}
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "# what is the maximum water level at Scituate over this period?\nzvals['Boston'].max()",
"execution_count": 19,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "2.0235898494720459"
},
"metadata": {},
"execution_count": 19
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "# make a new DataFrame of maximum water levels at all stations\nb=pd.DataFrame(zvals.idxmax(),columns=['time of max water level (UTC)'])\n# create heading for new column containing max water level\nzmax_heading='zmax (%s)' % nc['zeta'].units\n# Add new column to DataFrame\nb[zmax_heading]=zvals.max()",
"execution_count": 20,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true,
"editable": true,
"deletable": true
},
"cell_type": "code",
"source": "b",
"execution_count": 21,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": " time of max water level (UTC) zmax (meters)\nStation \nBoston 2017-03-14 18:00:00.000 2.023590\nScituate Harbor 2017-03-14 18:00:00.000 1.815455\nScituate Beach 2017-03-11 15:00:00.000 1.790602\nFalmouth Harbor 2017-03-14 15:00:00.000 0.659908\nMarion 2017-03-15 03:00:00.000 1.420215\nMarshfield 2017-03-11 15:00:00.000 1.804025\nProvincetown 2017-03-11 15:00:00.000 1.883487\nSandwich 2017-03-11 15:00:00.000 1.914992\nHampton Bay 2017-03-14 16:58:07.500 1.792463\nGloucester 2017-03-14 16:58:07.500 1.740331",
"text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>time of max water level (UTC)</th>\n <th>zmax (meters)</th>\n </tr>\n <tr>\n <th>Station</th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>Boston</th>\n <td>2017-03-14 18:00:00.000</td>\n <td>2.023590</td>\n </tr>\n <tr>\n <th>Scituate Harbor</th>\n <td>2017-03-14 18:00:00.000</td>\n <td>1.815455</td>\n </tr>\n <tr>\n <th>Scituate Beach</th>\n <td>2017-03-11 15:00:00.000</td>\n <td>1.790602</td>\n </tr>\n <tr>\n <th>Falmouth Harbor</th>\n <td>2017-03-14 15:00:00.000</td>\n <td>0.659908</td>\n </tr>\n <tr>\n <th>Marion</th>\n <td>2017-03-15 03:00:00.000</td>\n <td>1.420215</td>\n </tr>\n <tr>\n <th>Marshfield</th>\n <td>2017-03-11 15:00:00.000</td>\n <td>1.804025</td>\n </tr>\n <tr>\n <th>Provincetown</th>\n <td>2017-03-11 15:00:00.000</td>\n <td>1.883487</td>\n </tr>\n <tr>\n <th>Sandwich</th>\n <td>2017-03-11 15:00:00.000</td>\n <td>1.914992</td>\n </tr>\n <tr>\n <th>Hampton Bay</th>\n <td>2017-03-14 16:58:07.500</td>\n <td>1.792463</td>\n </tr>\n <tr>\n <th>Gloucester</th>\n <td>2017-03-14 16:58:07.500</td>\n <td>1.740331</td>\n </tr>\n </tbody>\n</table>\n</div>"
},
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