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epifanio/Trawl_Fall_2011_abundance_biomass.ipynb

Created February 19, 2014 06:37
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fall_abundance_biomass-Copy0-Copy0.ipynb
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fall_abundance_biomass.ipynb
{
"worksheets": [
{
"cells": [
{
"metadata": {},
"cell_type": "code",
"input": "import pandas as pd\nimport numpy as np\nimport geojson\nfrom geojson import Feature, Point, FeatureCollection \nfrom IPython.core.display import HTML\nfrom OpenLayers2 import makeSingleStyle, makeStyle3, makeQuery3, control3, df2feature",
"prompt_number": 1,
"outputs": [],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "markdown",
"source": "NOAA NMFS NEFSC Bottom Trawl Survey - Fall 2011"
},
{
"metadata": {},
"cell_type": "code",
"input": "data = pd.read_csv('Fall_2011.csv')",
"prompt_number": 2,
"outputs": [],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "data.head()",
"prompt_number": 3,
"outputs": [
{
"text": " SEASON CRUISE6 STATION SVSPP LATITUDE LONGITUDE ABUNDANCE BIOMASS\n0 FALL 201105 6 14 36.977443 -74.63074 228 5.785\n1 FALL 201105 6 15 36.977443 -74.63074 2 0.262\n2 FALL 201105 6 15 36.977443 -74.63074 3 0.331\n3 FALL 201105 6 25 36.977443 -74.63074 2 0.518\n4 FALL 201105 6 63 36.977443 -74.63074 6 0.813\n\n[5 rows x 8 columns]",
"html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>SEASON</th>\n <th>CRUISE6</th>\n <th>STATION</th>\n <th>SVSPP</th>\n <th>LATITUDE</th>\n <th>LONGITUDE</th>\n <th>ABUNDANCE</th>\n <th>BIOMASS</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td> FALL</td>\n <td> 201105</td>\n <td> 6</td>\n <td> 14</td>\n <td> 36.977443</td>\n <td>-74.63074</td>\n <td> 228</td>\n <td> 5.785</td>\n </tr>\n <tr>\n <th>1</th>\n <td> FALL</td>\n <td> 201105</td>\n <td> 6</td>\n <td> 15</td>\n <td> 36.977443</td>\n <td>-74.63074</td>\n <td> 2</td>\n <td> 0.262</td>\n </tr>\n <tr>\n <th>2</th>\n <td> FALL</td>\n <td> 201105</td>\n <td> 6</td>\n <td> 15</td>\n <td> 36.977443</td>\n <td>-74.63074</td>\n <td> 3</td>\n <td> 0.331</td>\n </tr>\n <tr>\n <th>3</th>\n <td> FALL</td>\n <td> 201105</td>\n <td> 6</td>\n <td> 25</td>\n <td> 36.977443</td>\n <td>-74.63074</td>\n <td> 2</td>\n <td> 0.518</td>\n </tr>\n <tr>\n <th>4</th>\n <td> FALL</td>\n <td> 201105</td>\n <td> 6</td>\n <td> 63</td>\n <td> 36.977443</td>\n <td>-74.63074</td>\n <td> 6</td>\n <td> 0.813</td>\n </tr>\n </tbody>\n</table>\n<p>5 rows × 8 columns</p>\n</div>",
"output_type": "pyout",
"metadata": {},
"prompt_number": 3
}
],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "data.tail()",
"prompt_number": 4,
"outputs": [
{
"text": " SEASON CRUISE6 STATION SVSPP LATITUDE LONGITUDE ABUNDANCE BIOMASS\n7871 FALL 201105 395 301 41.70971 -69.877423 1 0.881\n7872 FALL 201105 395 312 41.70971 -69.877423 1 0.090\n7873 FALL 201105 395 313 41.70971 -69.877423 1 0.084\n7874 FALL 201105 395 503 41.70971 -69.877423 1 0.023\n7875 FALL 201105 395 998 41.70971 -69.877423 0 0.710\n\n[5 rows x 8 columns]",
"html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>SEASON</th>\n <th>CRUISE6</th>\n <th>STATION</th>\n <th>SVSPP</th>\n <th>LATITUDE</th>\n <th>LONGITUDE</th>\n <th>ABUNDANCE</th>\n <th>BIOMASS</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>7871</th>\n <td> FALL</td>\n <td> 201105</td>\n <td> 395</td>\n <td> 301</td>\n <td> 41.70971</td>\n <td>-69.877423</td>\n <td> 1</td>\n <td> 0.881</td>\n </tr>\n <tr>\n <th>7872</th>\n <td> FALL</td>\n <td> 201105</td>\n <td> 395</td>\n <td> 312</td>\n <td> 41.70971</td>\n <td>-69.877423</td>\n <td> 1</td>\n <td> 0.090</td>\n </tr>\n <tr>\n <th>7873</th>\n <td> FALL</td>\n <td> 201105</td>\n <td> 395</td>\n <td> 313</td>\n <td> 41.70971</td>\n <td>-69.877423</td>\n <td> 1</td>\n <td> 0.084</td>\n </tr>\n <tr>\n <th>7874</th>\n <td> FALL</td>\n <td> 201105</td>\n <td> 395</td>\n <td> 503</td>\n <td> 41.70971</td>\n <td>-69.877423</td>\n <td> 1</td>\n <td> 0.023</td>\n </tr>\n <tr>\n <th>7875</th>\n <td> FALL</td>\n <td> 201105</td>\n <td> 395</td>\n <td> 998</td>\n <td> 41.70971</td>\n <td>-69.877423</td>\n <td> 0</td>\n <td> 0.710</td>\n </tr>\n </tbody>\n</table>\n<p>5 rows × 8 columns</p>\n</div>",
"output_type": "pyout",
"metadata": {},
"prompt_number": 4
}
],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "newcol = []\ndataset = data.copy()\nfor i in dataset['SVSPP'].unique():\n abundance = 'A_'+str(i)\n biomass = 'B_'+str(i)\n newcol.append(abundance)\n newcol.append(biomass)\n dataset[abundance] = pd.Series(np.zeros(len(dataset)), index=dataset.index)\n dataset[biomass] = pd.Series(np.zeros(len(dataset)), index=dataset.index)",
"prompt_number": 5,
"outputs": [],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "dataset.head()",
"prompt_number": 6,
"outputs": [
{
"text": " SEASON CRUISE6 STATION SVSPP LATITUDE LONGITUDE ABUNDANCE BIOMASS \\\n0 FALL 201105 6 14 36.977443 -74.63074 228 5.785 \n1 FALL 201105 6 15 36.977443 -74.63074 2 0.262 \n2 FALL 201105 6 15 36.977443 -74.63074 3 0.331 \n3 FALL 201105 6 25 36.977443 -74.63074 2 0.518 \n4 FALL 201105 6 63 36.977443 -74.63074 6 0.813 \n\n A_14 B_14 A_15 B_15 A_25 B_25 A_63 B_63 A_72 B_72 A_78 B_78 \n0 0 0 0 0 0 0 0 0 0 0 0 0 ... \n1 0 0 0 0 0 0 0 0 0 0 0 0 ... \n2 0 0 0 0 0 0 0 0 0 0 0 0 ... \n3 0 0 0 0 0 0 0 0 0 0 0 0 ... \n4 0 0 0 0 0 0 0 0 0 0 0 0 ... \n\n[5 rows x 482 columns]",
"html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>SEASON</th>\n <th>CRUISE6</th>\n <th>STATION</th>\n <th>SVSPP</th>\n <th>LATITUDE</th>\n <th>LONGITUDE</th>\n <th>ABUNDANCE</th>\n <th>BIOMASS</th>\n <th>A_14</th>\n <th>B_14</th>\n <th>A_15</th>\n <th>B_15</th>\n <th>A_25</th>\n <th>B_25</th>\n <th>A_63</th>\n <th>B_63</th>\n <th>A_72</th>\n <th>B_72</th>\n <th>A_78</th>\n <th>B_78</th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td> FALL</td>\n <td> 201105</td>\n <td> 6</td>\n <td> 14</td>\n <td> 36.977443</td>\n <td>-74.63074</td>\n <td> 228</td>\n <td> 5.785</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td>...</td>\n </tr>\n <tr>\n <th>1</th>\n <td> FALL</td>\n <td> 201105</td>\n <td> 6</td>\n <td> 15</td>\n <td> 36.977443</td>\n <td>-74.63074</td>\n <td> 2</td>\n <td> 0.262</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td>...</td>\n </tr>\n <tr>\n <th>2</th>\n <td> FALL</td>\n <td> 201105</td>\n <td> 6</td>\n <td> 15</td>\n <td> 36.977443</td>\n <td>-74.63074</td>\n <td> 3</td>\n <td> 0.331</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td>...</td>\n </tr>\n <tr>\n <th>3</th>\n <td> FALL</td>\n <td> 201105</td>\n <td> 6</td>\n <td> 25</td>\n <td> 36.977443</td>\n <td>-74.63074</td>\n <td> 2</td>\n <td> 0.518</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td>...</td>\n </tr>\n <tr>\n <th>4</th>\n <td> FALL</td>\n <td> 201105</td>\n <td> 6</td>\n <td> 63</td>\n <td> 36.977443</td>\n <td>-74.63074</td>\n <td> 6</td>\n <td> 0.813</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td> 0</td>\n <td>...</td>\n </tr>\n </tbody>\n</table>\n<p>5 rows × 482 columns</p>\n</div>",
"output_type": "pyout",
"metadata": {},
"prompt_number": 6
}
],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "for i, v in enumerate(dataset.index):\n abundance='A_'+str(dataset['SVSPP'][i])\n biomass='B_'+str(dataset['SVSPP'][i])\n dataset[biomass][i] = dataset['BIOMASS'][i]\n dataset[abundance][i] = dataset['ABUNDANCE'][i]",
"prompt_number": 7,
"outputs": [],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "df = dataset.groupby(['STATION','SEASON','CRUISE6','LATITUDE','LONGITUDE'])[newcol].sum().reset_index()",
"prompt_number": 8,
"outputs": [],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "df.head()",
"prompt_number": 9,
"outputs": [
{
"text": " STATION SEASON CRUISE6 LATITUDE LONGITUDE A_14 B_14 A_15 B_15 \\\n0 6 FALL 201105 36.977443 -74.630740 228 5.785 5 0.593 \n1 7 FALL 201105 36.955818 -74.920427 0 0.000 0 0.000 \n2 8 FALL 201105 36.848960 -75.008222 0 0.000 0 0.000 \n3 9 FALL 201105 36.753893 -74.965790 0 0.000 0 0.000 \n4 10 FALL 201105 36.804232 -74.701542 5 1.135 0 0.000 \n\n A_25 B_25 A_63 B_63 A_72 B_72 A_78 B_78 A_104 B_104 A_112 \\\n0 2 0.518 6 0.813 3 0.345 190 19.103 6 0.662 7 \n1 0 0.000 0 0.000 13 1.552 412 24.329 62 5.666 0 \n2 0 0.000 0 0.000 0 0.000 54 2.916 2 0.184 0 \n3 0 0.000 0 0.000 0 0.000 130 6.416 0 0.000 0 \n4 20 4.402 2 0.832 5 0.944 123 10.238 7 0.883 0 \n\n \n0 ... \n1 ... \n2 ... \n3 ... \n4 ... \n\n[5 rows x 479 columns]",
"html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>STATION</th>\n <th>SEASON</th>\n <th>CRUISE6</th>\n <th>LATITUDE</th>\n <th>LONGITUDE</th>\n <th>A_14</th>\n <th>B_14</th>\n <th>A_15</th>\n <th>B_15</th>\n <th>A_25</th>\n <th>B_25</th>\n <th>A_63</th>\n <th>B_63</th>\n <th>A_72</th>\n <th>B_72</th>\n <th>A_78</th>\n <th>B_78</th>\n <th>A_104</th>\n <th>B_104</th>\n <th>A_112</th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td> 6</td>\n <td> FALL</td>\n <td> 201105</td>\n <td> 36.977443</td>\n <td>-74.630740</td>\n <td> 228</td>\n <td> 5.785</td>\n <td> 5</td>\n <td> 0.593</td>\n <td> 2</td>\n <td> 0.518</td>\n <td> 6</td>\n <td> 0.813</td>\n <td> 3</td>\n <td> 0.345</td>\n <td> 190</td>\n <td> 19.103</td>\n <td> 6</td>\n <td> 0.662</td>\n <td> 7</td>\n <td>...</td>\n </tr>\n <tr>\n <th>1</th>\n <td> 7</td>\n <td> FALL</td>\n <td> 201105</td>\n <td> 36.955818</td>\n <td>-74.920427</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 13</td>\n <td> 1.552</td>\n <td> 412</td>\n <td> 24.329</td>\n <td> 62</td>\n <td> 5.666</td>\n <td> 0</td>\n <td>...</td>\n </tr>\n <tr>\n <th>2</th>\n <td> 8</td>\n <td> FALL</td>\n <td> 201105</td>\n <td> 36.848960</td>\n <td>-75.008222</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 54</td>\n <td> 2.916</td>\n <td> 2</td>\n <td> 0.184</td>\n <td> 0</td>\n <td>...</td>\n </tr>\n <tr>\n <th>3</th>\n <td> 9</td>\n <td> FALL</td>\n <td> 201105</td>\n <td> 36.753893</td>\n <td>-74.965790</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 130</td>\n <td> 6.416</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 0</td>\n <td>...</td>\n </tr>\n <tr>\n <th>4</th>\n <td> 10</td>\n <td> FALL</td>\n <td> 201105</td>\n <td> 36.804232</td>\n <td>-74.701542</td>\n <td> 5</td>\n <td> 1.135</td>\n <td> 0</td>\n <td> 0.000</td>\n <td> 20</td>\n <td> 4.402</td>\n <td> 2</td>\n <td> 0.832</td>\n <td> 5</td>\n <td> 0.944</td>\n <td> 123</td>\n <td> 10.238</td>\n <td> 7</td>\n <td> 0.883</td>\n <td> 0</td>\n <td>...</td>\n </tr>\n </tbody>\n</table>\n<p>5 rows × 479 columns</p>\n</div>",
"output_type": "pyout",
"metadata": {},
"prompt_number": 9
}
],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "features = df2feature(df=df)",
"prompt_number": 10,
"outputs": [
{
"output_type": "stream",
"text": "done\n",
"stream": "stdout"
}
],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "dump = geojson.dumps(FeatureCollection(features), sort_keys=True) ",
"prompt_number": 11,
"outputs": [],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "f = open('data_points.geojson', 'w')\nf.write(dump)\nf.close()",
"prompt_number": 12,
"outputs": [],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "fields = [x for x in df.columns]",
"prompt_number": 13,
"outputs": [],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "# Style for Vector1 \"EPU\" type : Polygon\nstylefields = {\n'GOM' : {'StrokeColor':'(0,0,0)','FillColor': '(0,255,0)', 'Opacity':1.0, 'LineWidth':0.26},\n'MAB' : {'StrokeColor':'(0,0,0)','FillColor': '(0,170,255)', 'Opacity':1.0, 'LineWidth':0.26},\n'SS' : {'StrokeColor':'(0,0,0)','FillColor': '(0,0,255)', 'Opacity':1.0, 'LineWidth':0.26},\n'GB' : {'StrokeColor':'(0,0,0)','FillColor': '(255,0,0)', 'Opacity':1.0, 'LineWidth':0.26}\n}\n\n# Style for Vector2 \"Fall_2011\" type : Point\nsinglestyle = {\n'singlestyle' : {'pointRadius':2, 'strokeColor': '(255,85,0)', 'strokeOpacity':1.0, 'fillColor':(218,218,0), 'fillOpacity':1.0}\n}\n\nvector1 = {'name': 'EPU', 'fields': ['ID','LABEL','GRIDCODE'], 'style': stylefields, 'url':'/files/ESR/Abundance_Biomass/EPU.geojson', 'type': 'polygon'}\nvectorlist1 = [vector1]\n\nvector2 = {'name': 'Fall_2011', 'fields': fields, 'style': singlestyle, 'url':'/files/ESR/Abundance_Biomass/data_points.geojson', 'type': 'point'}\nvectorlist2 = [vector2]\n\nvectorlist = [vector1, vector2]",
"prompt_number": 14,
"outputs": [],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "style = makeStyle3(vectorlist1)\npstyle = makeSingleStyle(vectorlist2)\nquery = makeQuery3(vectorlist)\ncontrol = control3(vectorlist)",
"prompt_number": 15,
"outputs": [],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "def makeMap3(epsg1=4326, epsg2=900913, lon=52.52, lat=13.41, zoom=15, style='', pstyle='', query='', control=''):\n stringa='''<!DOCTYPE HTML>\n <title>OpenLayers Simplest Example</title>\n <div id=\"basicMap\" style=\"height:550px\"></div>\n <script src=\"/nbextensions/openlayers/lib/OpenLayers.js\"></script>\n <script>\n map = new OpenLayers.Map(\"basicMap\");\n %s\n %s\n %s \n %s\n var mapnik = new OpenLayers.Layer.OSM(\"OpenStreetMap Mapnik\", \"http://tile.openstreetmap.org/${z}/${x}/${y}.png\");\n var fromProjection = new OpenLayers.Projection('EPSG:%s'); \n var toProjection = new OpenLayers.Projection('EPSG:%s'); \n var position = new OpenLayers.LonLat(%s,%s).transform( fromProjection, toProjection);\n var zoom = %s;\n map.addLayer(mapnik);\n map.setBaseLayer(mapnik);\n var ls= new OpenLayers.Control.LayerSwitcher(); \n map.addControl(ls); \n ls.maximizeControl(); \n map.setCenter(position, zoom );\n map.addControl(new OpenLayers.Control.MousePosition());\n map.addControl(new OpenLayers.Control.OverviewMap());\n map.addControl(new OpenLayers.Control.KeyboardDefaults());\n </script>''' % (style, pstyle, query, control, epsg1,epsg2,lon,lat,zoom)\n return stringa",
"prompt_number": 16,
"outputs": [],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "html = makeMap3(epsg1=4326, \n epsg2=900913, \n lat=42, lon=-68, \n zoom=5, \n style=style, \n pstyle=pstyle,\n query=query, \n control=control)\ndisplay(HTML(html), metadata={'isolated' : True})",
"prompt_number": 17,
"outputs": [
{
"html": "<!DOCTYPE HTML>\n <title>OpenLayers Simplest Example</title>\n <div id=\"basicMap\" style=\"height:550px\"></div>\n <script src=\"/nbextensions/openlayers/lib/OpenLayers.js\"></script>\n <script>\n map = new OpenLayers.Map(\"basicMap\");\n \n var EPU_style = new OpenLayers.Style(\n OpenLayers.Util.applyDefaults({ \n strokeColor: \"${getStrokeColor}\",\n strokeOpacity: \"${getOpacity}\",\n strokeWidth: \"${getLineWidth}\",\n fillColor: \"${getFillColor}\",\n fillOpacity: \"${getOpacity}\"\n }, OpenLayers.Feature.Vector.style[\"default\"]), {\n context: {\n \n getOpacity: function(feature) {\n \n if (feature.attributes.LABEL==\"GOM\"){\n element=1.0;\n }\n \n else if (feature.attributes.LABEL==\"SS\"){\n element=1.0;\n }\n \n else if (feature.attributes.LABEL==\"MAB\"){\n element=1.0;\n }\n \n else if (feature.attributes.LABEL==\"GB\"){\n element=1.0;\n }\n \n else {\n element=\"NULL\";\n }\n return element;\n },\n \n getStrokeColor: function(feature) {\n \n if (feature.attributes.LABEL==\"GOM\"){\n element=\"rgb(0,0,0)\";\n }\n \n else if (feature.attributes.LABEL==\"SS\"){\n element=\"rgb(0,0,0)\";\n }\n \n else if (feature.attributes.LABEL==\"MAB\"){\n element=\"rgb(0,0,0)\";\n }\n \n else if (feature.attributes.LABEL==\"GB\"){\n element=\"rgb(0,0,0)\";\n }\n \n else {\n element=\"NULL\";\n }\n return element;\n },\n \n getFillColor: function(feature) {\n \n if (feature.attributes.LABEL==\"GOM\"){\n element=\"rgb(0,255,0)\";\n }\n \n else if (feature.attributes.LABEL==\"SS\"){\n element=\"rgb(0,0,255)\";\n }\n \n else if (feature.attributes.LABEL==\"MAB\"){\n element=\"rgb(0,170,255)\";\n }\n \n else if (feature.attributes.LABEL==\"GB\"){\n element=\"rgb(255,0,0)\";\n }\n \n else {\n element=\"NULL\";\n }\n return element;\n },\n \n getLineWidth: function(feature) {\n \n if (feature.attributes.LABEL==\"GOM\"){\n element=0.26;\n }\n \n else if (feature.attributes.LABEL==\"SS\"){\n element=0.26;\n }\n \n else if (feature.attributes.LABEL==\"MAB\"){\n element=0.26;\n }\n \n else if (feature.attributes.LABEL==\"GB\"){\n element=0.26;\n }\n \n else {\n element=\"NULL\";\n }\n return element;\n },\n \n }\n }\n );\n \n var Fall_2011_template = {\n pointRadius: 2,\n strokeColor: \"rgb(255,85,0)\",\n strokeOpacity: 1.0,\n fillColor: \"rgb(218, 218, 0)\",\n fillOpacity: 1.0\n }\n var Fall_2011_style = new OpenLayers.Style(Fall_2011_template)\n \n \n function onPopupCloseEPU(evt) {\n selectControl.unselect(selectedFeature);\n }\n function onFeatureSelectEPU(feature){\n selectedFeature = feature;\n tablevector=\"<html><meta http-equiv='Content-Type' content='text/html; charset=UTF-8'><body><table><tr><td><b>ID:</b></td><td><i>\"+feature.attributes.ID+\"</i></td></tr><tr><td><b>LABEL:</b></td><td><i>\"+feature.attributes.LABEL+\"</i></td></tr><tr><td><b>GRIDCODE:</b></td><td><i>\"+feature.attributes.GRIDCODE+\"</i></td></tr></table></body></html>\";\n popup = new OpenLayers.Popup.FramedCloud(\"chicken\", \n feature.geometry.getBounds().getCenterLonLat(),\n new OpenLayers.Size(1000,500),\n tablevector,\n null,\n true,\n onPopupCloseEPU\n ); \n feature.popup = popup;\n map.addPopup(popup);\n }\n function onFeatureUnselectEPU(feature) {\n map.removePopup(feature.popup);\n feature.popup.destroy();\n feature.popup = null; \n } \n var EPU = new OpenLayers.Layer.Vector(\"EPU\", {\n styleMap: EPU_style,\n projection: \"EPSG:4326\",\n strategies: [new OpenLayers.Strategy.Fixed()],\n protocol: new OpenLayers.Protocol.HTTP({\n url: \"/files/ESR/Abundance_Biomass/EPU.geojson\",\n format: new OpenLayers.Format.GeoJSON()\n })\n });\n map.addLayer(EPU);\n \n function onPopupCloseFall_2011(evt) {\n selectControl.unselect(selectedFeature);\n }\n function onFeatureSelectFall_2011(feature){\n selectedFeature = feature;\n tablevector=\"<html><meta http-equiv='Content-Type' content='text/html; charset=UTF-8'><body><table><tr><td><b>STATION:</b></td><td><i>\"+feature.attributes.STATION+\"</i></td></tr><tr><td><b>SEASON:</b></td><td><i>\"+feature.attributes.SEASON+\"</i></td></tr><tr><td><b>CRUISE6:</b></td><td><i>\"+feature.attributes.CRUISE6+\"</i></td></tr><tr><td><b>LATITUDE:</b></td><td><i>\"+feature.attributes.LATITUDE+\"</i></td></tr><tr><td><b>LONGITUDE:</b></td><td><i>\"+feature.attributes.LONGITUDE+\"</i></td></tr><tr><td><b>A_14:</b></td><td><i>\"+feature.attributes.A_14+\"</i></td></tr><tr><td><b>B_14:</b></td><td><i>\"+feature.attributes.B_14+\"</i></td></tr><tr><td><b>A_15:</b></td><td><i>\"+feature.attributes.A_15+\"</i></td></tr><tr><td><b>B_15:</b></td><td><i>\"+feature.attributes.B_15+\"</i></td></tr><tr><td><b>A_25:</b></td><td><i>\"+feature.attributes.A_25+\"</i></td></tr><tr><td><b>B_25:</b></td><td><i>\"+feature.attributes.B_25+\"</i></td></tr><tr><td><b>A_63:</b></td><td><i>\"+feature.attributes.A_63+\"</i></td></tr><tr><td><b>B_63:</b></td><td><i>\"+feature.attributes.B_63+\"</i></td></tr><tr><td><b>A_72:</b></td><td><i>\"+feature.attributes.A_72+\"</i></td></tr><tr><td><b>B_72:</b></td><td><i>\"+feature.attributes.B_72+\"</i></td></tr><tr><td><b>A_78:</b></td><td><i>\"+feature.attributes.A_78+\"</i></td></tr><tr><td><b>B_78:</b></td><td><i>\"+feature.attributes.B_78+\"</i></td></tr><tr><td><b>A_104:</b></td><td><i>\"+feature.attributes.A_104+\"</i></td></tr><tr><td><b>B_104:</b></td><td><i>\"+feature.attributes.B_104+\"</i></td></tr><tr><td><b>A_112:</b></td><td><i>\"+feature.attributes.A_112+\"</i></td></tr><tr><td><b>B_112:</b></td><td><i>\"+feature.attributes.B_112+\"</i></td></tr><tr><td><b>A_156:</b></td><td><i>\"+feature.attributes.A_156+\"</i></td></tr><tr><td><b>B_156:</b></td><td><i>\"+feature.attributes.B_156+\"</i></td></tr><tr><td><b>A_158:</b></td><td><i>\"+feature.attributes.A_158+\"</i></td></tr><tr><td><b>B_158:</b></td><td><i>\"+feature.attributes.B_158+\"</i></td></tr><tr><td><b>A_197:</b></td><td><i>\"+feature.attributes.A_197+\"</i></td></tr><tr><td><b>B_197:</b></td><td><i>\"+feature.attributes.B_197+\"</i></td></tr><tr><td><b>A_263:</b></td><td><i>\"+feature.attributes.A_263+\"</i></td></tr><tr><td><b>B_263:</b></td><td><i>\"+feature.attributes.B_263+\"</i></td></tr><tr><td><b>A_313:</b></td><td><i>\"+feature.attributes.A_313+\"</i></td></tr><tr><td><b>B_313:</b></td><td><i>\"+feature.attributes.B_313+\"</i></td></tr><tr><td><b>A_318:</b></td><td><i>\"+feature.attributes.A_318+\"</i></td></tr><tr><td><b>B_318:</b></td><td><i>\"+feature.attributes.B_318+\"</i></td></tr><tr><td><b>A_502:</b></td><td><i>\"+feature.attributes.A_502+\"</i></td></tr><tr><td><b>B_502:</b></td><td><i>\"+feature.attributes.B_502+\"</i></td></tr><tr><td><b>A_503:</b></td><td><i>\"+feature.attributes.A_503+\"</i></td></tr><tr><td><b>B_503:</b></td><td><i>\"+feature.attributes.B_503+\"</i></td></tr><tr><td><b>A_108:</b></td><td><i>\"+feature.attributes.A_108+\"</i></td></tr><tr><td><b>B_108:</b></td><td><i>\"+feature.attributes.B_108+\"</i></td></tr><tr><td><b>A_109:</b></td><td><i>\"+feature.attributes.A_109+\"</i></td></tr><tr><td><b>B_109:</b></td><td><i>\"+feature.attributes.B_109+\"</i></td></tr><tr><td><b>A_131:</b></td><td><i>\"+feature.attributes.A_131+\"</i></td></tr><tr><td><b>B_131:</b></td><td><i>\"+feature.attributes.B_131+\"</i></td></tr><tr><td><b>A_181:</b></td><td><i>\"+feature.attributes.A_181+\"</i></td></tr><tr><td><b>B_181:</b></td><td><i>\"+feature.attributes.B_181+\"</i></td></tr><tr><td><b>A_321:</b></td><td><i>\"+feature.attributes.A_321+\"</i></td></tr><tr><td><b>B_321:</b></td><td><i>\"+feature.attributes.B_321+\"</i></td></tr><tr><td><b>A_401:</b></td><td><i>\"+feature.attributes.A_401+\"</i></td></tr><tr><td><b>B_401:</b></td><td><i>\"+feature.attributes.B_401+\"</i></td></tr><tr><td><b>A_998:</b></td><td><i>\"+feature.attributes.A_998+\"</i></td></tr><tr><td><b>B_998:</b></td><td><i>\"+feature.attributes.B_998+\"</i></td></tr><tr><td><b>A_31:</b></td><td><i>\"+feature.attributes.A_31+\"</i></td></tr><tr><td><b>B_31:</b></td><td><i>\"+feature.attributes.B_31+\"</i></td></tr><tr><td><b>A_171:</b></td><td><i>\"+feature.attributes.A_171+\"</i></td></tr><tr><td><b>B_171:</b></td><td><i>\"+feature.attributes.B_171+\"</i></td></tr><tr><td><b>A_24:</b></td><td><i>\"+feature.attributes.A_24+\"</i></td></tr><tr><td><b>B_24:</b></td><td><i>\"+feature.attributes.B_24+\"</i></td></tr><tr><td><b>A_141:</b></td><td><i>\"+feature.attributes.A_141+\"</i></td></tr><tr><td><b>B_141:</b></td><td><i>\"+feature.attributes.B_141+\"</i></td></tr><tr><td><b>A_172:</b></td><td><i>\"+feature.attributes.A_172+\"</i></td></tr><tr><td><b>B_172:</b></td><td><i>\"+feature.attributes.B_172+\"</i></td></tr><tr><td><b>A_90:</b></td><td><i>\"+feature.attributes.A_90+\"</i></td></tr><tr><td><b>B_90:</b></td><td><i>\"+feature.attributes.B_90+\"</i></td></tr><tr><td><b>A_194:</b></td><td><i>\"+feature.attributes.A_194+\"</i></td></tr><tr><td><b>B_194:</b></td><td><i>\"+feature.attributes.B_194+\"</i></td></tr><tr><td><b>A_301:</b></td><td><i>\"+feature.attributes.A_301+\"</i></td></tr><tr><td><b>B_301:</b></td><td><i>\"+feature.attributes.B_301+\"</i></td></tr><tr><td><b>A_312:</b></td><td><i>\"+feature.attributes.A_312+\"</i></td></tr><tr><td><b>B_312:</b></td><td><i>\"+feature.attributes.B_312+\"</i></td></tr><tr><td><b>A_319:</b></td><td><i>\"+feature.attributes.A_319+\"</i></td></tr><tr><td><b>B_319:</b></td><td><i>\"+feature.attributes.B_319+\"</i></td></tr><tr><td><b>A_390:</b></td><td><i>\"+feature.attributes.A_390+\"</i></td></tr><tr><td><b>B_390:</b></td><td><i>\"+feature.attributes.B_390+\"</i></td></tr><tr><td><b>A_46:</b></td><td><i>\"+feature.attributes.A_46+\"</i></td></tr><tr><td><b>B_46:</b></td><td><i>\"+feature.attributes.B_46+\"</i></td></tr><tr><td><b>A_69:</b></td><td><i>\"+feature.attributes.A_69+\"</i></td></tr><tr><td><b>B_69:</b></td><td><i>\"+feature.attributes.B_69+\"</i></td></tr><tr><td><b>A_77:</b></td><td><i>\"+feature.attributes.A_77+\"</i></td></tr><tr><td><b>B_77:</b></td><td><i>\"+feature.attributes.B_77+\"</i></td></tr><tr><td><b>A_107:</b></td><td><i>\"+feature.attributes.A_107+\"</i></td></tr><tr><td><b>B_107:</b></td><td><i>\"+feature.attributes.B_107+\"</i></td></tr><tr><td><b>A_129:</b></td><td><i>\"+feature.attributes.A_129+\"</i></td></tr><tr><td><b>B_129:</b></td><td><i>\"+feature.attributes.B_129+\"</i></td></tr><tr><td><b>A_173:</b></td><td><i>\"+feature.attributes.A_173+\"</i></td></tr><tr><td><b>B_173:</b></td><td><i>\"+feature.attributes.B_173+\"</i></td></tr><tr><td><b>A_221:</b></td><td><i>\"+feature.attributes.A_221+\"</i></td></tr><tr><td><b>B_221:</b></td><td><i>\"+feature.attributes.B_221+\"</i></td></tr><tr><td><b>A_232:</b></td><td><i>\"+feature.attributes.A_232+\"</i></td></tr><tr><td><b>B_232:</b></td><td><i>\"+feature.attributes.B_232+\"</i></td></tr><tr><td><b>A_900:</b></td><td><i>\"+feature.attributes.A_900+\"</i></td></tr><tr><td><b>B_900:</b></td><td><i>\"+feature.attributes.B_900+\"</i></td></tr><tr><td><b>A_16:</b></td><td><i>\"+feature.attributes.A_16+\"</i></td></tr><tr><td><b>B_16:</b></td><td><i>\"+feature.attributes.B_16+\"</i></td></tr><tr><td><b>A_213:</b></td><td><i>\"+feature.attributes.A_213+\"</i></td></tr><tr><td><b>B_213:</b></td><td><i>\"+feature.attributes.B_213+\"</i></td></tr><tr><td><b>A_21:</b></td><td><i>\"+feature.attributes.A_21+\"</i></td></tr><tr><td><b>B_21:</b></td><td><i>\"+feature.attributes.B_21+\"</i></td></tr><tr><td><b>A_56:</b></td><td><i>\"+feature.attributes.A_56+\"</i></td></tr><tr><td><b>B_56:</b></td><td><i>\"+feature.attributes.B_56+\"</i></td></tr><tr><td><b>A_111:</b></td><td><i>\"+feature.attributes.A_111+\"</i></td></tr><tr><td><b>B_111:</b></td><td><i>\"+feature.attributes.B_111+\"</i></td></tr><tr><td><b>A_127:</b></td><td><i>\"+feature.attributes.A_127+\"</i></td></tr><tr><td><b>B_127:</b></td><td><i>\"+feature.attributes.B_127+\"</i></td></tr><tr><td><b>A_517:</b></td><td><i>\"+feature.attributes.A_517+\"</i></td></tr><tr><td><b>B_517:</b></td><td><i>\"+feature.attributes.B_517+\"</i></td></tr><tr><td><b>A_617:</b></td><td><i>\"+feature.attributes.A_617+\"</i></td></tr><tr><td><b>B_617:</b></td><td><i>\"+feature.attributes.B_617+\"</i></td></tr><tr><td><b>A_759:</b></td><td><i>\"+feature.attributes.A_759+\"</i></td></tr><tr><td><b>B_759:</b></td><td><i>\"+feature.attributes.B_759+\"</i></td></tr><tr><td><b>A_856:</b></td><td><i>\"+feature.attributes.A_856+\"</i></td></tr><tr><td><b>B_856:</b></td><td><i>\"+feature.attributes.B_856+\"</i></td></tr><tr><td><b>A_899:</b></td><td><i>\"+feature.attributes.A_899+\"</i></td></tr><tr><td><b>B_899:</b></td><td><i>\"+feature.attributes.B_899+\"</i></td></tr><tr><td><b>A_764:</b></td><td><i>\"+feature.attributes.A_764+\"</i></td></tr><tr><td><b>B_764:</b></td><td><i>\"+feature.attributes.B_764+\"</i></td></tr><tr><td><b>A_897:</b></td><td><i>\"+feature.attributes.A_897+\"</i></td></tr><tr><td><b>B_897:</b></td><td><i>\"+feature.attributes.B_897+\"</i></td></tr><tr><td><b>A_67:</b></td><td><i>\"+feature.attributes.A_67+\"</i></td></tr><tr><td><b>B_67:</b></td><td><i>\"+feature.attributes.B_67+\"</i></td></tr><tr><td><b>A_228:</b></td><td><i>\"+feature.attributes.A_228+\"</i></td></tr><tr><td><b>B_228:</b></td><td><i>\"+feature.attributes.B_228+\"</i></td></tr><tr><td><b>A_242:</b></td><td><i>\"+feature.attributes.A_242+\"</i></td></tr><tr><td><b>B_242:</b></td><td><i>\"+feature.attributes.B_242+\"</i></td></tr><tr><td><b>A_323:</b></td><td><i>\"+feature.attributes.A_323+\"</i></td></tr><tr><td><b>B_323:</b></td><td><i>\"+feature.attributes.B_323+\"</i></td></tr><tr><td><b>A_512:</b></td><td><i>\"+feature.attributes.A_512+\"</i></td></tr><tr><td><b>B_512:</b></td><td><i>\"+feature.attributes.B_512+\"</i></td></tr><tr><td><b>A_601:</b></td><td><i>\"+feature.attributes.A_601+\"</i></td></tr><tr><td><b>B_601:</b></td><td><i>\"+feature.attributes.B_601+\"</i></td></tr><tr><td><b>A_114:</b></td><td><i>\"+feature.attributes.A_114+\"</i></td></tr><tr><td><b>B_114:</b></td><td><i>\"+feature.attributes.B_114+\"</i></td></tr><tr><td><b>A_124:</b></td><td><i>\"+feature.attributes.A_124+\"</i></td></tr><tr><td><b>B_124:</b></td><td><i>\"+feature.attributes.B_124+\"</i></td></tr><tr><td><b>A_135:</b></td><td><i>\"+feature.attributes.A_135+\"</i></td></tr><tr><td><b>B_135:</b></td><td><i>\"+feature.attributes.B_135+\"</i></td></tr><tr><td><b>A_136:</b></td><td><i>\"+feature.attributes.A_136+\"</i></td></tr><tr><td><b>B_136:</b></td><td><i>\"+feature.attributes.B_136+\"</i></td></tr><tr><td><b>A_143:</b></td><td><i>\"+feature.attributes.A_143+\"</i></td></tr><tr><td><b>B_143:</b></td><td><i>\"+feature.attributes.B_143+\"</i></td></tr><tr><td><b>A_145:</b></td><td><i>\"+feature.attributes.A_145+\"</i></td></tr><tr><td><b>B_145:</b></td><td><i>\"+feature.attributes.B_145+\"</i></td></tr><tr><td><b>A_149:</b></td><td><i>\"+feature.attributes.A_149+\"</i></td></tr><tr><td><b>B_149:</b></td><td><i>\"+feature.attributes.B_149+\"</i></td></tr><tr><td><b>A_195:</b></td><td><i>\"+feature.attributes.A_195+\"</i></td></tr><tr><td><b>B_195:</b></td><td><i>\"+feature.attributes.B_195+\"</i></td></tr><tr><td><b>A_211:</b></td><td><i>\"+feature.attributes.A_211+\"</i></td></tr><tr><td><b>B_211:</b></td><td><i>\"+feature.attributes.B_211+\"</i></td></tr><tr><td><b>A_212:</b></td><td><i>\"+feature.attributes.A_212+\"</i></td></tr><tr><td><b>B_212:</b></td><td><i>\"+feature.attributes.B_212+\"</i></td></tr><tr><td><b>A_375:</b></td><td><i>\"+feature.attributes.A_375+\"</i></td></tr><tr><td><b>B_375:</b></td><td><i>\"+feature.attributes.B_375+\"</i></td></tr><tr><td><b>A_429:</b></td><td><i>\"+feature.attributes.A_429+\"</i></td></tr><tr><td><b>B_429:</b></td><td><i>\"+feature.attributes.B_429+\"</i></td></tr><tr><td><b>A_931:</b></td><td><i>\"+feature.attributes.A_931+\"</i></td></tr><tr><td><b>B_931:</b></td><td><i>\"+feature.attributes.B_931+\"</i></td></tr><tr><td><b>A_132:</b></td><td><i>\"+feature.attributes.A_132+\"</i></td></tr><tr><td><b>B_132:</b></td><td><i>\"+feature.attributes.B_132+\"</i></td></tr><tr><td><b>A_201:</b></td><td><i>\"+feature.attributes.A_201+\"</i></td></tr><tr><td><b>B_201:</b></td><td><i>\"+feature.attributes.B_201+\"</i></td></tr><tr><td><b>A_865:</b></td><td><i>\"+feature.attributes.A_865+\"</i></td></tr><tr><td><b>B_865:</b></td><td><i>\"+feature.attributes.B_865+\"</i></td></tr><tr><td><b>A_913:</b></td><td><i>\"+feature.attributes.A_913+\"</i></td></tr><tr><td><b>B_913:</b></td><td><i>\"+feature.attributes.B_913+\"</i></td></tr><tr><td><b>A_44:</b></td><td><i>\"+feature.attributes.A_44+\"</i></td></tr><tr><td><b>B_44:</b></td><td><i>\"+feature.attributes.B_44+\"</i></td></tr><tr><td><b>A_146:</b></td><td><i>\"+feature.attributes.A_146+\"</i></td></tr><tr><td><b>B_146:</b></td><td><i>\"+feature.attributes.B_146+\"</i></td></tr><tr><td><b>A_376:</b></td><td><i>\"+feature.attributes.A_376+\"</i></td></tr><tr><td><b>B_376:</b></td><td><i>\"+feature.attributes.B_376+\"</i></td></tr><tr><td><b>A_18:</b></td><td><i>\"+feature.attributes.A_18+\"</i></td></tr><tr><td><b>B_18:</b></td><td><i>\"+feature.attributes.B_18+\"</i></td></tr><tr><td><b>A_126:</b></td><td><i>\"+feature.attributes.A_126+\"</i></td></tr><tr><td><b>B_126:</b></td><td><i>\"+feature.attributes.B_126+\"</i></td></tr><tr><td><b>A_142:</b></td><td><i>\"+feature.attributes.A_142+\"</i></td></tr><tr><td><b>B_142:</b></td><td><i>\"+feature.attributes.B_142+\"</i></td></tr><tr><td><b>A_316:</b></td><td><i>\"+feature.attributes.A_316+\"</i></td></tr><tr><td><b>B_316:</b></td><td><i>\"+feature.attributes.B_316+\"</i></td></tr><tr><td><b>A_320:</b></td><td><i>\"+feature.attributes.A_320+\"</i></td></tr><tr><td><b>B_320:</b></td><td><i>\"+feature.attributes.B_320+\"</i></td></tr><tr><td><b>A_428:</b></td><td><i>\"+feature.attributes.A_428+\"</i></td></tr><tr><td><b>B_428:</b></td><td><i>\"+feature.attributes.B_428+\"</i></td></tr><tr><td><b>A_444:</b></td><td><i>\"+feature.attributes.A_444+\"</i></td></tr><tr><td><b>B_444:</b></td><td><i>\"+feature.attributes.B_444+\"</i></td></tr><tr><td><b>A_516:</b></td><td><i>\"+feature.attributes.A_516+\"</i></td></tr><tr><td><b>B_516:</b></td><td><i>\"+feature.attributes.B_516+\"</i></td></tr><tr><td><b>A_557:</b></td><td><i>\"+feature.attributes.A_557+\"</i></td></tr><tr><td><b>B_557:</b></td><td><i>\"+feature.attributes.B_557+\"</i></td></tr><tr><td><b>A_627:</b></td><td><i>\"+feature.attributes.A_627+\"</i></td></tr><tr><td><b>B_627:</b></td><td><i>\"+feature.attributes.B_627+\"</i></td></tr><tr><td><b>A_651:</b></td><td><i>\"+feature.attributes.A_651+\"</i></td></tr><tr><td><b>B_651:</b></td><td><i>\"+feature.attributes.B_651+\"</i></td></tr><tr><td><b>A_652:</b></td><td><i>\"+feature.attributes.A_652+\"</i></td></tr><tr><td><b>B_652:</b></td><td><i>\"+feature.attributes.B_652+\"</i></td></tr><tr><td><b>A_745:</b></td><td><i>\"+feature.attributes.A_745+\"</i></td></tr><tr><td><b>B_745:</b></td><td><i>\"+feature.attributes.B_745+\"</i></td></tr><tr><td><b>A_749:</b></td><td><i>\"+feature.attributes.A_749+\"</i></td></tr><tr><td><b>B_749:</b></td><td><i>\"+feature.attributes.B_749+\"</i></td></tr><tr><td><b>A_768:</b></td><td><i>\"+feature.attributes.A_768+\"</i></td></tr><tr><td><b>B_768:</b></td><td><i>\"+feature.attributes.B_768+\"</i></td></tr><tr><td><b>A_794:</b></td><td><i>\"+feature.attributes.A_794+\"</i></td></tr><tr><td><b>B_794:</b></td><td><i>\"+feature.attributes.B_794+\"</i></td></tr><tr><td><b>A_866:</b></td><td><i>\"+feature.attributes.A_866+\"</i></td></tr><tr><td><b>B_866:</b></td><td><i>\"+feature.attributes.B_866+\"</i></td></tr><tr><td><b>A_582:</b></td><td><i>\"+feature.attributes.A_582+\"</i></td></tr><tr><td><b>B_582:</b></td><td><i>\"+feature.attributes.B_582+\"</i></td></tr><tr><td><b>A_196:</b></td><td><i>\"+feature.attributes.A_196+\"</i></td></tr><tr><td><b>B_196:</b></td><td><i>\"+feature.attributes.B_196+\"</i></td></tr><tr><td><b>A_209:</b></td><td><i>\"+feature.attributes.A_209+\"</i></td></tr><tr><td><b>B_209:</b></td><td><i>\"+feature.attributes.B_209+\"</i></td></tr><tr><td><b>A_360:</b></td><td><i>\"+feature.attributes.A_360+\"</i></td></tr><tr><td><b>B_360:</b></td><td><i>\"+feature.attributes.B_360+\"</i></td></tr><tr><td><b>A_435:</b></td><td><i>\"+feature.attributes.A_435+\"</i></td></tr><tr><td><b>B_435:</b></td><td><i>\"+feature.attributes.B_435+\"</i></td></tr><tr><td><b>A_786:</b></td><td><i>\"+feature.attributes.A_786+\"</i></td></tr><tr><td><b>B_786:</b></td><td><i>\"+feature.attributes.B_786+\"</i></td></tr><tr><td><b>A_820:</b></td><td><i>\"+feature.attributes.A_820+\"</i></td></tr><tr><td><b>B_820:</b></td><td><i>\"+feature.attributes.B_820+\"</i></td></tr><tr><td><b>A_188:</b></td><td><i>\"+feature.attributes.A_188+\"</i></td></tr><tr><td><b>B_188:</b></td><td><i>\"+feature.attributes.B_188+\"</i></td></tr><tr><td><b>A_530:</b></td><td><i>\"+feature.attributes.A_530+\"</i></td></tr><tr><td><b>B_530:</b></td><td><i>\"+feature.attributes.B_530+\"</i></td></tr><tr><td><b>A_573:</b></td><td><i>\"+feature.attributes.A_573+\"</i></td></tr><tr><td><b>B_573:</b></td><td><i>\"+feature.attributes.B_573+\"</i></td></tr><tr><td><b>A_625:</b></td><td><i>\"+feature.attributes.A_625+\"</i></td></tr><tr><td><b>B_625:</b></td><td><i>\"+feature.attributes.B_625+\"</i></td></tr><tr><td><b>A_640:</b></td><td><i>\"+feature.attributes.A_640+\"</i></td></tr><tr><td><b>B_640:</b></td><td><i>\"+feature.attributes.B_640+\"</i></td></tr><tr><td><b>A_769:</b></td><td><i>\"+feature.attributes.A_769+\"</i></td></tr><tr><td><b>B_769:</b></td><td><i>\"+feature.attributes.B_769+\"</i></td></tr><tr><td><b>A_770:</b></td><td><i>\"+feature.attributes.A_770+\"</i></td></tr><tr><td><b>B_770:</b></td><td><i>\"+feature.attributes.B_770+\"</i></td></tr><tr><td><b>A_950:</b></td><td><i>\"+feature.attributes.A_950+\"</i></td></tr><tr><td><b>B_950:</b></td><td><i>\"+feature.attributes.B_950+\"</i></td></tr><tr><td><b>A_659:</b></td><td><i>\"+feature.attributes.A_659+\"</i></td></tr><tr><td><b>B_659:</b></td><td><i>\"+feature.attributes.B_659+\"</i></td></tr><tr><td><b>A_174:</b></td><td><i>\"+feature.attributes.A_174+\"</i></td></tr><tr><td><b>B_174:</b></td><td><i>\"+feature.attributes.B_174+\"</i></td></tr><tr><td><b>A_317:</b></td><td><i>\"+feature.attributes.A_317+\"</i></td></tr><tr><td><b>B_317:</b></td><td><i>\"+feature.attributes.B_317+\"</i></td></tr><tr><td><b>A_439:</b></td><td><i>\"+feature.attributes.A_439+\"</i></td></tr><tr><td><b>B_439:</b></td><td><i>\"+feature.attributes.B_439+\"</i></td></tr><tr><td><b>A_489:</b></td><td><i>\"+feature.attributes.A_489+\"</i></td></tr><tr><td><b>B_489:</b></td><td><i>\"+feature.attributes.B_489+\"</i></td></tr><tr><td><b>A_510:</b></td><td><i>\"+feature.attributes.A_510+\"</i></td></tr><tr><td><b>B_510:</b></td><td><i>\"+feature.attributes.B_510+\"</i></td></tr><tr><td><b>A_871:</b></td><td><i>\"+feature.attributes.A_871+\"</i></td></tr><tr><td><b>B_871:</b></td><td><i>\"+feature.attributes.B_871+\"</i></td></tr><tr><td><b>A_307:</b></td><td><i>\"+feature.attributes.A_307+\"</i></td></tr><tr><td><b>B_307:</b></td><td><i>\"+feature.attributes.B_307+\"</i></td></tr><tr><td><b>A_787:</b></td><td><i>\"+feature.attributes.A_787+\"</i></td></tr><tr><td><b>B_787:</b></td><td><i>\"+feature.attributes.B_787+\"</i></td></tr><tr><td><b>A_793:</b></td><td><i>\"+feature.attributes.A_793+\"</i></td></tr><tr><td><b>B_793:</b></td><td><i>\"+feature.attributes.B_793+\"</i></td></tr><tr><td><b>A_748:</b></td><td><i>\"+feature.attributes.A_748+\"</i></td></tr><tr><td><b>B_748:</b></td><td><i>\"+feature.attributes.B_748+\"</i></td></tr><tr><td><b>A_134:</b></td><td><i>\"+feature.attributes.A_134+\"</i></td></tr><tr><td><b>B_134:</b></td><td><i>\"+feature.attributes.B_134+\"</i></td></tr><tr><td><b>A_147:</b></td><td><i>\"+feature.attributes.A_147+\"</i></td></tr><tr><td><b>B_147:</b></td><td><i>\"+feature.attributes.B_147+\"</i></td></tr><tr><td><b>A_206:</b></td><td><i>\"+feature.attributes.A_206+\"</i></td></tr><tr><td><b>B_206:</b></td><td><i>\"+feature.attributes.B_206+\"</i></td></tr><tr><td><b>A_554:</b></td><td><i>\"+feature.attributes.A_554+\"</i></td></tr><tr><td><b>B_554:</b></td><td><i>\"+feature.attributes.B_554+\"</i></td></tr><tr><td><b>A_853:</b></td><td><i>\"+feature.attributes.A_853+\"</i></td></tr><tr><td><b>B_853:</b></td><td><i>\"+feature.attributes.B_853+\"</i></td></tr><tr><td><b>A_449:</b></td><td><i>\"+feature.attributes.A_449+\"</i></td></tr><tr><td><b>B_449:</b></td><td><i>\"+feature.attributes.B_449+\"</i></td></tr><tr><td><b>A_486:</b></td><td><i>\"+feature.attributes.A_486+\"</i></td></tr><tr><td><b>B_486:</b></td><td><i>\"+feature.attributes.B_486+\"</i></td></tr><tr><td><b>A_43:</b></td><td><i>\"+feature.attributes.A_43+\"</i></td></tr><tr><td><b>B_43:</b></td><td><i>\"+feature.attributes.B_43+\"</i></td></tr><tr><td><b>A_504:</b></td><td><i>\"+feature.attributes.A_504+\"</i></td></tr><tr><td><b>B_504:</b></td><td><i>\"+feature.attributes.B_504+\"</i></td></tr><tr><td><b>A_527:</b></td><td><i>\"+feature.attributes.A_527+\"</i></td></tr><tr><td><b>B_527:</b></td><td><i>\"+feature.attributes.B_527+\"</i></td></tr><tr><td><b>A_694:</b></td><td><i>\"+feature.attributes.A_694+\"</i></td></tr><tr><td><b>B_694:</b></td><td><i>\"+feature.attributes.B_694+\"</i></td></tr><tr><td><b>A_103:</b></td><td><i>\"+feature.attributes.A_103+\"</i></td></tr><tr><td><b>B_103:</b></td><td><i>\"+feature.attributes.B_103+\"</i></td></tr><tr><td><b>A_402:</b></td><td><i>\"+feature.attributes.A_402+\"</i></td></tr><tr><td><b>B_402:</b></td><td><i>\"+feature.attributes.B_402+\"</i></td></tr><tr><td><b>A_148:</b></td><td><i>\"+feature.attributes.A_148+\"</i></td></tr><tr><td><b>B_148:</b></td><td><i>\"+feature.attributes.B_148+\"</i></td></tr><tr><td><b>A_19:</b></td><td><i>\"+feature.attributes.A_19+\"</i></td></tr><tr><td><b>B_19:</b></td><td><i>\"+feature.attributes.B_19+\"</i></td></tr><tr><td><b>A_36:</b></td><td><i>\"+feature.attributes.A_36+\"</i></td></tr><tr><td><b>B_36:</b></td><td><i>\"+feature.attributes.B_36+\"</i></td></tr><tr><td><b>A_198:</b></td><td><i>\"+feature.attributes.A_198+\"</i></td></tr><tr><td><b>B_198:</b></td><td><i>\"+feature.attributes.B_198+\"</i></td></tr><tr><td><b>A_314:</b></td><td><i>\"+feature.attributes.A_314+\"</i></td></tr><tr><td><b>B_314:</b></td><td><i>\"+feature.attributes.B_314+\"</i></td></tr><tr><td><b>A_322:</b></td><td><i>\"+feature.attributes.A_322+\"</i></td></tr><tr><td><b>B_322:</b></td><td><i>\"+feature.attributes.B_322+\"</i></td></tr><tr><td><b>A_646:</b></td><td><i>\"+feature.attributes.A_646+\"</i></td></tr><tr><td><b>B_646:</b></td><td><i>\"+feature.attributes.B_646+\"</i></td></tr><tr><td><b>A_270:</b></td><td><i>\"+feature.attributes.A_270+\"</i></td></tr><tr><td><b>B_270:</b></td><td><i>\"+feature.attributes.B_270+\"</i></td></tr><tr><td><b>A_13:</b></td><td><i>\"+feature.attributes.A_13+\"</i></td></tr><tr><td><b>B_13:</b></td><td><i>\"+feature.attributes.B_13+\"</i></td></tr><tr><td><b>A_4:</b></td><td><i>\"+feature.attributes.A_4+\"</i></td></tr><tr><td><b>B_4:</b></td><td><i>\"+feature.attributes.B_4+\"</i></td></tr><tr><td><b>A_657:</b></td><td><i>\"+feature.attributes.A_657+\"</i></td></tr><tr><td><b>B_657:</b></td><td><i>\"+feature.attributes.B_657+\"</i></td></tr><tr><td><b>A_978:</b></td><td><i>\"+feature.attributes.A_978+\"</i></td></tr><tr><td><b>B_978:</b></td><td><i>\"+feature.attributes.B_978+\"</i></td></tr><tr><td><b>A_26:</b></td><td><i>\"+feature.attributes.A_26+\"</i></td></tr><tr><td><b>B_26:</b></td><td><i>\"+feature.attributes.B_26+\"</i></td></tr><tr><td><b>A_403:</b></td><td><i>\"+feature.attributes.A_403+\"</i></td></tr><tr><td><b>B_403:</b></td><td><i>\"+feature.attributes.B_403+\"</i></td></tr><tr><td><b>A_105:</b></td><td><i>\"+feature.attributes.A_105+\"</i></td></tr><tr><td><b>B_105:</b></td><td><i>\"+feature.attributes.B_105+\"</i></td></tr><tr><td><b>A_231:</b></td><td><i>\"+feature.attributes.A_231+\"</i></td></tr><tr><td><b>B_231:</b></td><td><i>\"+feature.attributes.B_231+\"</i></td></tr><tr><td><b>A_698:</b></td><td><i>\"+feature.attributes.A_698+\"</i></td></tr><tr><td><b>B_698:</b></td><td><i>\"+feature.attributes.B_698+\"</i></td></tr><tr><td><b>A_751:</b></td><td><i>\"+feature.attributes.A_751+\"</i></td></tr><tr><td><b>B_751:</b></td><td><i>\"+feature.attributes.B_751+\"</i></td></tr><tr><td><b>A_229:</b></td><td><i>\"+feature.attributes.A_229+\"</i></td></tr><tr><td><b>B_229:</b></td><td><i>\"+feature.attributes.B_229+\"</i></td></tr><tr><td><b>A_252:</b></td><td><i>\"+feature.attributes.A_252+\"</i></td></tr><tr><td><b>B_252:</b></td><td><i>\"+feature.attributes.B_252+\"</i></td></tr><tr><td><b>A_604:</b></td><td><i>\"+feature.attributes.A_604+\"</i></td></tr><tr><td><b>B_604:</b></td><td><i>\"+feature.attributes.B_604+\"</i></td></tr><tr><td><b>A_505:</b></td><td><i>\"+feature.attributes.A_505+\"</i></td></tr><tr><td><b>B_505:</b></td><td><i>\"+feature.attributes.B_505+\"</i></td></tr><tr><td><b>A_187:</b></td><td><i>\"+feature.attributes.A_187+\"</i></td></tr><tr><td><b>B_187:</b></td><td><i>\"+feature.attributes.B_187+\"</i></td></tr><tr><td><b>A_118:</b></td><td><i>\"+feature.attributes.A_118+\"</i></td></tr><tr><td><b>B_118:</b></td><td><i>\"+feature.attributes.B_118+\"</i></td></tr><tr><td><b>A_121:</b></td><td><i>\"+feature.attributes.A_121+\"</i></td></tr><tr><td><b>B_121:</b></td><td><i>\"+feature.attributes.B_121+\"</i></td></tr><tr><td><b>A_848:</b></td><td><i>\"+feature.attributes.A_848+\"</i></td></tr><tr><td><b>B_848:</b></td><td><i>\"+feature.attributes.B_848+\"</i></td></tr><tr><td><b>A_620:</b></td><td><i>\"+feature.attributes.A_620+\"</i></td></tr><tr><td><b>B_620:</b></td><td><i>\"+feature.attributes.B_620+\"</i></td></tr><tr><td><b>A_662:</b></td><td><i>\"+feature.attributes.A_662+\"</i></td></tr><tr><td><b>B_662:</b></td><td><i>\"+feature.attributes.B_662+\"</i></td></tr><tr><td><b>A_164:</b></td><td><i>\"+feature.attributes.A_164+\"</i></td></tr><tr><td><b>B_164:</b></td><td><i>\"+feature.attributes.B_164+\"</i></td></tr><tr><td><b>A_556:</b></td><td><i>\"+feature.attributes.A_556+\"</i></td></tr><tr><td><b>B_556:</b></td><td><i>\"+feature.attributes.B_556+\"</i></td></tr><tr><td><b>A_176:</b></td><td><i>\"+feature.attributes.A_176+\"</i></td></tr><tr><td><b>B_176:</b></td><td><i>\"+feature.attributes.B_176+\"</i></td></tr><tr><td><b>A_74:</b></td><td><i>\"+feature.attributes.A_74+\"</i></td></tr><tr><td><b>B_74:</b></td><td><i>\"+feature.attributes.B_74+\"</i></td></tr><tr><td><b>A_193:</b></td><td><i>\"+feature.attributes.A_193+\"</i></td></tr><tr><td><b>B_193:</b></td><td><i>\"+feature.attributes.B_193+\"</i></td></tr><tr><td><b>A_151:</b></td><td><i>\"+feature.attributes.A_151+\"</i></td></tr><tr><td><b>B_151:</b></td><td><i>\"+feature.attributes.B_151+\"</i></td></tr><tr><td><b>A_490:</b></td><td><i>\"+feature.attributes.A_490+\"</i></td></tr><tr><td><b>B_490:</b></td><td><i>\"+feature.attributes.B_490+\"</i></td></tr><tr><td><b>A_60:</b></td><td><i>\"+feature.attributes.A_60+\"</i></td></tr><tr><td><b>B_60:</b></td><td><i>\"+feature.attributes.B_60+\"</i></td></tr><tr><td><b>A_1:</b></td><td><i>\"+feature.attributes.A_1+\"</i></td></tr><tr><td><b>B_1:</b></td><td><i>\"+feature.attributes.B_1+\"</i></td></tr><tr><td><b>A_310:</b></td><td><i>\"+feature.attributes.A_310+\"</i></td></tr><tr><td><b>B_310:</b></td><td><i>\"+feature.attributes.B_310+\"</i></td></tr><tr><td><b>A_305:</b></td><td><i>\"+feature.attributes.A_305+\"</i></td></tr><tr><td><b>B_305:</b></td><td><i>\"+feature.attributes.B_305+\"</i></td></tr><tr><td><b>A_35:</b></td><td><i>\"+feature.attributes.A_35+\"</i></td></tr><tr><td><b>B_35:</b></td><td><i>\"+feature.attributes.B_35+\"</i></td></tr><tr><td><b>A_339:</b></td><td><i>\"+feature.attributes.A_339+\"</i></td></tr><tr><td><b>B_339:</b></td><td><i>\"+feature.attributes.B_339+\"</i></td></tr><tr><td><b>A_76:</b></td><td><i>\"+feature.attributes.A_76+\"</i></td></tr><tr><td><b>B_76:</b></td><td><i>\"+feature.attributes.B_76+\"</i></td></tr><tr><td><b>A_83:</b></td><td><i>\"+feature.attributes.A_83+\"</i></td></tr><tr><td><b>B_83:</b></td><td><i>\"+feature.attributes.B_83+\"</i></td></tr><tr><td><b>A_110:</b></td><td><i>\"+feature.attributes.A_110+\"</i></td></tr><tr><td><b>B_110:</b></td><td><i>\"+feature.attributes.B_110+\"</i></td></tr><tr><td><b>A_154:</b></td><td><i>\"+feature.attributes.A_154+\"</i></td></tr><tr><td><b>B_154:</b></td><td><i>\"+feature.attributes.B_154+\"</i></td></tr><tr><td><b>A_268:</b></td><td><i>\"+feature.attributes.A_268+\"</i></td></tr><tr><td><b>B_268:</b></td><td><i>\"+feature.attributes.B_268+\"</i></td></tr><tr><td><b>A_500:</b></td><td><i>\"+feature.attributes.A_500+\"</i></td></tr><tr><td><b>B_500:</b></td><td><i>\"+feature.attributes.B_500+\"</i></td></tr><tr><td><b>A_546:</b></td><td><i>\"+feature.attributes.A_546+\"</i></td></tr><tr><td><b>B_546:</b></td><td><i>\"+feature.attributes.B_546+\"</i></td></tr><tr><td><b>A_862:</b></td><td><i>\"+feature.attributes.A_862+\"</i></td></tr><tr><td><b>B_862:</b></td><td><i>\"+feature.attributes.B_862+\"</i></td></tr><tr><td><b>A_22:</b></td><td><i>\"+feature.attributes.A_22+\"</i></td></tr><tr><td><b>B_22:</b></td><td><i>\"+feature.attributes.B_22+\"</i></td></tr><tr><td><b>A_23:</b></td><td><i>\"+feature.attributes.A_23+\"</i></td></tr><tr><td><b>B_23:</b></td><td><i>\"+feature.attributes.B_23+\"</i></td></tr><tr><td><b>A_75:</b></td><td><i>\"+feature.attributes.A_75+\"</i></td></tr><tr><td><b>B_75:</b></td><td><i>\"+feature.attributes.B_75+\"</i></td></tr><tr><td><b>A_106:</b></td><td><i>\"+feature.attributes.A_106+\"</i></td></tr><tr><td><b>B_106:</b></td><td><i>\"+feature.attributes.B_106+\"</i></td></tr><tr><td><b>A_163:</b></td><td><i>\"+feature.attributes.A_163+\"</i></td></tr><tr><td><b>B_163:</b></td><td><i>\"+feature.attributes.B_163+\"</i></td></tr><tr><td><b>A_32:</b></td><td><i>\"+feature.attributes.A_32+\"</i></td></tr><tr><td><b>B_32:</b></td><td><i>\"+feature.attributes.B_32+\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popup = new OpenLayers.Popup.FramedCloud(\"chicken\", \n feature.geometry.getBounds().getCenterLonLat(),\n new OpenLayers.Size(1000,500),\n tablevector,\n null,\n true,\n onPopupCloseFall_2011\n ); \n feature.popup = popup;\n map.addPopup(popup);\n }\n function onFeatureUnselectFall_2011(feature) {\n map.removePopup(feature.popup);\n feature.popup.destroy();\n feature.popup = null; \n } \n var Fall_2011 = new OpenLayers.Layer.Vector(\"Fall_2011\", {\n styleMap: Fall_2011_style,\n projection: \"EPSG:4326\",\n strategies: [new OpenLayers.Strategy.Fixed()],\n protocol: new OpenLayers.Protocol.HTTP({\n url: \"/files/ESR/Abundance_Biomass/data_points.geojson\",\n format: new OpenLayers.Format.GeoJSON()\n })\n });\n map.addLayer(Fall_2011);\n \n \nselectControl = new OpenLayers.Control.SelectFeature(\n [EPU,Fall_2011, ],\n {\n clickout: true, toggle: false, \n multiple: false, hover: false, \n toggleKey: \"ctrlKey\", // ctrl key removes from selection\n multipleKey: \"shiftKey\" // shift key adds to selection\n }\n );\n map.addControl(selectControl);\n selectControl.activate();\n \n EPU.events.on({\n \"featureselected\": function(e) {\n onFeatureSelectEPU(e.feature);\n },\n \"featureunselected\": function(e) {\n onFeatureUnselectEPU(e.feature);\n }\n });\n Fall_2011.events.on({\n \"featureselected\": function(e) {\n onFeatureSelectFall_2011(e.feature);\n },\n \"featureunselected\": function(e) {\n onFeatureUnselectFall_2011(e.feature);\n }\n });\n var mapnik = new OpenLayers.Layer.OSM(\"OpenStreetMap Mapnik\", \"http://tile.openstreetmap.org/${z}/${x}/${y}.png\");\n var fromProjection = new OpenLayers.Projection('EPSG:4326'); \n var toProjection = new OpenLayers.Projection('EPSG:900913'); \n var position = new OpenLayers.LonLat(-68,42).transform( fromProjection, toProjection);\n var zoom = 5;\n map.addLayer(mapnik);\n map.setBaseLayer(mapnik);\n var ls= new OpenLayers.Control.LayerSwitcher(); \n map.addControl(ls); \n ls.maximizeControl(); \n map.setCenter(position, zoom );\n map.addControl(new OpenLayers.Control.MousePosition());\n map.addControl(new OpenLayers.Control.OverviewMap());\n map.addControl(new OpenLayers.Control.KeyboardDefaults());\n </script>",
"text": "<IPython.core.display.HTML at 0x7f58a8577510>",
"output_type": "display_data",
"metadata": {
"isolated": true
}
}
],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "!gist -p EPU.geojson",
"prompt_number": 18,
"outputs": [
{
"output_type": "stream",
"text": "https://gist.github.com/268691071989484d32c7\r\n",
"stream": "stdout"
}
],
"language": "python",
"trusted": true,
"collapsed": false
},
{
"metadata": {},
"cell_type": "code",
"input": "!gist -p data_points.geojson",
"prompt_number": 19,
"outputs": [
{
"output_type": "stream",
"text": "https://gist.github.com/870086f34a2ca12d3435\r\n",
"stream": "stdout"
}
],
"language": "python",
"trusted": true,
"collapsed": false
}
],
"metadata": {}
}
],
"metadata": {
"gist_id": "9087115",
"name": "",
"signature": "sha256:3ed2a4b6eab0cc3e8b9e703ef4ecafbf4dff0bdaef55370e0d912fd8a44d07ac"
},
"nbformat": 3
}
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Trawl_Fall_2011_abundance_biomass.ipynb
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Untitled0.ipynb
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