├── data ├── dem.tiff ├── llamps.dbf ├── llamps.ods ├── llamps.shp ├── llamps.shx ├── comarcas.dbf ├── comarcas.shp ├── comarcas.shx ├── ortofoto.jpg ├── XXX_RN1_20131117_0000_CMPAC1C_1h.tif ├── XXX_RN1_20131117_0100_CMPAC1C_1h.tif ├── XXX_RN1_20131117_0200_CMPAC1C_1h.tif ├── XXX_RN1_20131117_0300_CMPAC1C_1h.tif ├── XXX_RN1_20131117_0400_CMPAC1C_1h.tif ├── XXX_RN1_20131117_0500_CMPAC1C_1h.tif ├── XXX_RN1_20131117_0600_CMPAC1C_1h.tif ├── XXX_RN1_20131117_0700_CMPAC1C_1h.tif ├── XXX_RN1_20131117_0800_CMPAC1C_1h.tif ├── XXX_RN1_20131117_0900_CMPAC1C_1h.tif ├── llamps.prj ├── comarcas.prj ├── README.md ├── llamps.csv └── llamps.txt ├── hillshade.py ├── README.md ├── mayavi_examples.py ├── mayavi_ejemplos.py ├── osr_examples.py ├── osr_ejemplos.py ├── fiona_examples.py ├── fiona_ejemplos.py ├── gdal_examples.py ├── gdal_ejemplos.py └── LICENSE /data/dem.tiff: -------------------------------------------------------------------------------- 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GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]] -------------------------------------------------------------------------------- /data/comarcas.prj: -------------------------------------------------------------------------------- 1 | GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]] -------------------------------------------------------------------------------- /data/README.md: -------------------------------------------------------------------------------- 1 | Archivos de ejemplo para el taller 2 | ========= 3 | 8as Jornadas Sig Libre 4 | 5 | 26 de Marzo de 2014 6 | 7 | Introducción a Python para usos geoespaciales 8 | 9 | Los siguientes archivos para los ejemplos del taller han sido cedidos por el [Servei Metrorològic de Catalunya](http://www.meteo.cat) y el [Institut Cartogràfic de Catalunya](http://www.icc.es/) 10 | 11 | - **llamps.shp** Descargas de rayos para el dia 17/11/2013 de la red de detección de descargas eléctricas del SMC (XDDE) 12 | - **XXX_RN1_20131117_0000_CMPAC1C_1h.tif** Datos de acumulación horaria de la red de radares del SMC 13 | - **comarcas.shp** Polígonos con las comarcas de Catalunya 14 | - **dem.tiff** Modelo digital de elevaciones a 5m para la zona de Montserrat, descargado de la [web vissir del ICC](http://www.icc.cat/vissir/) 15 | - **ortofoto.jpg** Ortofoto de la misma zona de Montserrat que la del archivo dem.tiff, descargada usando la capa orto5m el servicio WMS del ICC -------------------------------------------------------------------------------- /hillshade.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | 8as Jornadas Sig Libre 4 | 26 de Marzo de 2014 5 | Introducción a Python para usos geoespaciales 6 | 7 | Creación de un archivo hillshade a partir de un MDE 8 | """ 9 | 10 | from osgeo import gdal 11 | from numpy import gradient 12 | from numpy import pi 13 | from numpy import arctan 14 | from numpy import arctan2 15 | from numpy import sin 16 | from numpy import cos 17 | from numpy import sqrt 18 | from numpy import zeros 19 | from numpy import uint8 20 | import matplotlib.pyplot as plt 21 | 22 | # --- stop --- 23 | def hillshade(array, azimuth, angle_altitude): 24 | azimuth = 360.0 - azimuth 25 | 26 | x, y = gradient(array) 27 | slope = pi/2. - arctan(sqrt(x*x + y*y)) 28 | aspect = arctan2(-x, y) 29 | azimuthrad = azimuth*pi / 180. 30 | altituderad = angle_altitude*pi / 180. 31 | 32 | 33 | shaded = sin(altituderad) * sin(slope)\ 34 | + cos(altituderad) * cos(slope)\ 35 | * cos((azimuthrad - pi/2.) - aspect) 36 | return 255*(shaded + 1)/2 37 | 38 | # --- stop --- 39 | ds = gdal.Open('data/dem.tiff') 40 | band = ds.GetRasterBand(1) 41 | arr = band.ReadAsArray() 42 | 43 | hs_array = hillshade(arr,315, 45) 44 | plt.imshow(hs_array,cmap='Greys') 45 | plt.show() 46 | # --- stop --- -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | Archivos de ejemplo para el taller 2 | ========= 3 | 8as Jornadas Sig Libre 4 | 5 | 26 de Marzo de 2014 6 | 7 | Introducción a Python para usos geoespaciales 8 | 9 | Los archivos de este directorio contienen los ejemplos para el taller y El directorio *data* contiene los archivos de datos para usar los ejemplos. 10 | 11 | - **gdal_ejemplos.py** Ejemplos del uso de la librería *gdal python*, para el tratamiento de archivos tipo raster 12 | - **osr_ejemplos.py** Ejemplos del uso de la librería *osr python*, para la consulta y transformación de coordenadas 13 | - **fiona_ejemplos** Ejemplos del uso de la librería *fiona* para el tratamiento de archivos vectoriales 14 | - **mayavi_ejemplos.py** Ejemplos del uso de la librería *mayavi2* para la generaciónd e imágenes en 3D 15 | 16 | 17 | Example files for the workshop 18 | ========= 19 | 8as Jornadas Sig Libre 20 | 21 | March 26th 2014 22 | 23 | Introduction to Python for geospatial uses 24 | 25 | The files in this directory have the examples for the workshop, and the *data* directory has the data files to be used with the examples. 26 | 27 | 28 | - **gdal_examples.py** *gdal python* library usage examples, for working with raster files 29 | - **osr_examples.py** *osr python* library usage examples, for coordinates querying and transformation 30 | - **fiona_examples** *fiona* library usage examples, for processing vectorial files 31 | - **mayavi_examples.py** *mayavi2* library usage examples, for 3D image generation -------------------------------------------------------------------------------- /mayavi_examples.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | 8as Jornadas Sig Libre 4 | 26 de Marzo de 2014 5 | Introduction to Python for geospatial uses 6 | 7 | Examples for using mayavi to create 3d images 8 | """ 9 | 10 | #The libraries used are: 11 | from osgeo import gdal 12 | import numpy as np 13 | from tvtk.api import tvtk 14 | from mayavi import mlab 15 | import Image 16 | 17 | # --- stop --- 18 | #The data is loaded as usual, but it has to be converted to float32 19 | ds = gdal.Open('data/dem.tiff') 20 | data = ds.ReadAsArray() 21 | 22 | data = data.astype(np.float32) 23 | 24 | # --- stop --- 25 | #Creating a 3d representation is simple 26 | mlab.figure(size=(640, 800), bgcolor=(0.16, 0.28, 0.46)) 27 | 28 | surf = mlab.surf(data, warp_scale=0.2) 29 | mlab.show() 30 | # --- stop --- 31 | 32 | #To draw a picture on the elevation, use the following steps: 33 | #The image must be rotated 90 degrees: 34 | im1 = Image.open("data/ortofoto.jpg") 35 | im2 = im1.rotate(90) 36 | im2.save("/tmp/ortofoto90.jpg") 37 | #The image must be loaded with the tvtk library 38 | bmp1 = tvtk.JPEGReader() 39 | bmp1.file_name="/tmp/ortofoto90.jpg" #any jpeg file 40 | 41 | my_texture=tvtk.Texture() 42 | my_texture.interpolate=0 43 | my_texture.set_input(0,bmp1.get_output()) 44 | 45 | 46 | mlab.figure(size=(640, 800), bgcolor=(0.16, 0.28, 0.46)) 47 | ##A color must be defined 48 | surf = mlab.surf(data, color=(1,1,1), warp_scale=0.2) 49 | surf.actor.actor.mapper.scalar_visibility = False 50 | surf.actor.enable_texture = True 51 | surf.actor.tcoord_generator_mode = 'plane' 52 | surf.actor.actor.texture = my_texture 53 | mlab.show() 54 | 55 | #mlab.view(-5.9, 83, 570, [5.3, 20, 238]) 56 | #mlab.savefig('test.png') 57 | 58 | -------------------------------------------------------------------------------- /mayavi_ejemplos.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | 8as Jornadas Sig Libre 4 | 26 de Marzo de 2014 5 | Introducción a Python para usos geoespaciales 6 | 7 | Ejemplos para trabajar con GDAL/python 8 | """ 9 | 10 | #Las librerías que usaremos son las siguientes: 11 | from osgeo import gdal 12 | import numpy as np 13 | from tvtk.api import tvtk 14 | from mayavi import mlab 15 | import Image 16 | 17 | # --- stop --- 18 | #Los datos se cargan de la forma habitual, pero hay que convertirlos a float32 19 | ds = gdal.Open('data/dem.tiff') 20 | data = ds.ReadAsArray() 21 | 22 | data = data.astype(np.float32) 23 | 24 | # --- stop --- 25 | #Hacer una representación 3d es sencillo 26 | mlab.figure(size=(640, 800), bgcolor=(0.16, 0.28, 0.46)) 27 | 28 | surf = mlab.surf(data, warp_scale=0.2) 29 | mlab.show() 30 | # --- stop --- 31 | 32 | #Para añadir una foto encima de la elevación, hay que seguir los siguientes pasos: 33 | #La imagen debe estar rotada 90 grados: 34 | im1 = Image.open("data/ortofoto.jpg") 35 | im2 = im1.rotate(90) 36 | im2.save("/tmp/ortofoto90.jpg") 37 | #Hay qque cargarla con la librería tvtk 38 | bmp1 = tvtk.JPEGReader() 39 | bmp1.file_name="/tmp/ortofoto90.jpg" #any jpeg file 40 | 41 | my_texture=tvtk.Texture() 42 | my_texture.interpolate=0 43 | my_texture.set_input(0,bmp1.get_output()) 44 | 45 | 46 | mlab.figure(size=(640, 800), bgcolor=(0.16, 0.28, 0.46)) 47 | ##Hay que definir color 48 | surf = mlab.surf(data, color=(1,1,1), warp_scale=0.2) 49 | surf.actor.actor.mapper.scalar_visibility = False 50 | surf.actor.enable_texture = True 51 | surf.actor.tcoord_generator_mode = 'plane' 52 | surf.actor.actor.texture = my_texture 53 | mlab.show() 54 | 55 | #mlab.view(-5.9, 83, 570, [5.3, 20, 238]) 56 | #mlab.savefig('test.png') 57 | 58 | -------------------------------------------------------------------------------- /osr_examples.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | 8as Jornadas Sig Libre 4 | 26 de Marzo de 2014 5 | Introduction to Python for geospatial uses 6 | 7 | Examples for using fiona to work with projections (osr/python) 8 | """ 9 | 10 | from osgeo import gdal 11 | from osgeo import osr 12 | 13 | #Open a dataset 14 | ds = gdal.Open('data/XXX_RN1_20131117_0000_CMPAC1C_1h.tif') 15 | # --- stop --- 16 | 17 | #Reading the projection metadata: 18 | #Projection: 19 | proj_in = ds.GetProjection() 20 | 21 | print proj_in 22 | #Information about the used format: 23 | #http://www.geoapi.org/3.0/javadoc/org/opengis/referencing/doc-files/WKT.html 24 | 25 | # --- stop --- 26 | #Geotransform 27 | gt = ds.GetGeoTransform() 28 | 29 | """ 30 | geotransform[0] = East/West location of Upper Left corner 31 | geotransform[1] = X pixel size 32 | geotransform[2] = X pixel rotation 33 | geotransform[3] = North/South location of Upper Left corner 34 | geotransform[4] = Y pixel rotation 35 | geotransform[5] = Y pixel size 36 | 37 | Xgeo = gt(0) + Xpixel*gt(1) + Yline*gt(2) 38 | Ygeo = gt(3) + Xpixel*gt(4) + Yline*gt(5) 39 | """ 40 | 41 | print gt 42 | 43 | # --- stop --- 44 | 45 | #Projection change for a point: 46 | 47 | proj_out = osr.SpatialReference() 48 | proj_out.ImportFromEPSG(4326) 49 | 50 | #proj_in is a String, so it must be converted to a SpatialReference object: 51 | proj_in = osr.SpatialReference(proj_in) 52 | 53 | transf = osr.CoordinateTransformation(proj_in, proj_out) 54 | 55 | punto = transf.TransformPoint(gt[0], gt[3]) 56 | 57 | print punto 58 | 59 | # --- stop --- 60 | #using the geotransform functions 61 | #Pixel to coordinates: 62 | gt = (1,1,0,1,0,1) 63 | gdal.ApplyGeoTransform(gt,1,1) 64 | 65 | #Coordinates to pixel 66 | result, inv_gt = gdal.InvGeoTransform(gt) 67 | gdal.ApplyGeoTransform(inv_gt,1,1) 68 | 69 | # --- stop --- 70 | -------------------------------------------------------------------------------- /osr_ejemplos.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | 8as Jornadas Sig Libre 4 | 26 de Marzo de 2014 5 | Introducción a Python para usos geoespaciales 6 | 7 | Ejemplos para trabajar con las proyecciones (osr/python) 8 | """ 9 | 10 | from osgeo import gdal 11 | from osgeo import osr 12 | 13 | #Abrir un dataset 14 | ds = gdal.Open('data/XXX_RN1_20131117_0000_CMPAC1C_1h.tif') 15 | # --- stop --- 16 | 17 | #Ver todos los métodos disponibles: 18 | help(ds) 19 | # --- stop --- 20 | 21 | 22 | #Leer los metadatos de la proyección: 23 | #Proyección: 24 | proj_in = ds.GetProjection() 25 | 26 | print proj_in 27 | #Información sobre el formato: 28 | #http://www.geoapi.org/3.0/javadoc/org/opengis/referencing/doc-files/WKT.html 29 | 30 | # --- stop --- 31 | #Geotransform 32 | gt = ds.GetGeoTransform() 33 | 34 | """ 35 | geotransform[0] = East/West location of Upper Left corner 36 | geotransform[1] = X pixel size 37 | geotransform[2] = X pixel rotation 38 | geotransform[3] = North/South location of Upper Left corner 39 | geotransform[4] = Y pixel rotation 40 | geotransform[5] = Y pixel size 41 | 42 | Xgeo = gt(0) + Xpixel*gt(1) + Yline*gt(2) 43 | Ygeo = gt(3) + Xpixel*gt(4) + Yline*gt(5) 44 | """ 45 | 46 | print gt 47 | 48 | # --- stop --- 49 | 50 | #Cambio de proyección para un punto: 51 | 52 | proj_out = osr.SpatialReference() 53 | proj_out.ImportFromEPSG(4326) 54 | 55 | #proj_in es texto por defecto, y hay que convertirlo en un objeto SpatialReference: 56 | proj_in = osr.SpatialReference(proj_in) 57 | 58 | transf = osr.CoordinateTransformation(proj_in, proj_out) 59 | 60 | punto = transf.TransformPoint(gt[0], gt[3]) 61 | 62 | print punto 63 | 64 | # --- stop --- 65 | #Usar las funciones de GeoTransform 66 | #Píxel a coordenadas: 67 | gt = (1,1,0,1,0,1) 68 | gdal.ApplyGeoTransform(gt,1,1) 69 | 70 | #Coordenadas a pixel 71 | result, inv_gt = gdal.InvGeoTransform(gt) 72 | gdal.ApplyGeoTransform(inv_gt,1,1) 73 | 74 | # --- stop --- 75 | -------------------------------------------------------------------------------- /fiona_examples.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | 8as Jornadas Sig Libre 4 | 26 de Marzo de 2014 5 | Introduction to Python for geospatial uses 6 | 7 | Examples for using fiona to work with vectorial files 8 | """ 9 | 10 | #Using fiona to read a file: 11 | 12 | import fiona 13 | 14 | c = fiona.open('data/llamps.shp') 15 | 16 | print c 17 | # --- stop --- 18 | 19 | 20 | #It's possible to get the OGR driver name with the property: 21 | print c.driver 22 | # --- stop --- 23 | 24 | #And the projection: 25 | print c.crs 26 | 27 | # --- stop --- 28 | 29 | #The schema indicates the other file properties: 30 | print c.schema 31 | # --- stop --- 32 | 33 | #To see the record, it's possible to use the iterators: 34 | print c.next() 35 | # --- stop --- 36 | 37 | #It's possible to iterate all the elements using 38 | for record in c: 39 | print record['properties']['Data i hor'] 40 | # --- stop --- 41 | 42 | #It's possible to filter the data for a bounding box in a very simple way: 43 | filtered_data = c.filter(bbox=(2.0, 40.8, 2.1, 40.9)) 44 | for record in filtered_data: 45 | print record 46 | 47 | #To close the file, use: 48 | c.close() 49 | # --- stop --- 50 | 51 | #Vectorial files writting: 52 | 53 | #To create a file: 54 | crs = {u'no_defs': True, u'datum': u'WGS84', u'proj': u'longlat'} 55 | driver = 'ESRI Shapefile' 56 | schema = {'geometry': 'Point', 'properties': [('nombre', 'str'), ('valor', 'str')]} 57 | of = fiona.open('test.shp','w', driver = driver, crs=crs, schema=schema) 58 | # --- stop --- 59 | 60 | #It's possible to add records to the existing files using: 61 | rec = {'geometry': {'type': 'Point', 'coordinates': (1.8890812, 40.889)}, 'type': 'Feature', 'id': '0', 'properties': {'nombre': 'punto1', 'valor': 'valor1'}} 62 | 63 | of.write(rec) 64 | 65 | # --- stop --- 66 | 67 | #Operations with geometries using shapely 68 | 69 | #To transform the read data with fiona into a shapely object, we use shape: 70 | from shapely.geometry import shape 71 | import fiona 72 | c = fiona.open('data/llamps.shp') 73 | for point in c: 74 | print shape(point['geometry']) 75 | # --- stop --- 76 | 77 | #Once the object is a shape object, it's possible to operate on the geometries 78 | for point in c: 79 | print shape(point['geometry']).buffer(1) 80 | 81 | #And the inverse operation, to save the geometries with fiona, is mapping 82 | # --- stop --- 83 | #Distance between two points 84 | a = {'type': 'Point', 'coordinates': ((1, 40))} 85 | b = {'type': 'Point', 'coordinates': ((0.5, 40))} 86 | print shape(a).distance(shape(b)) 87 | 88 | # --- stop --- 89 | 90 | #Two LineString intersection 91 | a = {'type': 'LineString', 'coordinates': ((1, 40),(2,41))} 92 | b = {'type': 'LineString', 'coordinates': ((0.5, 40),(2.5,41))} 93 | print shape(a).crosses(shape(b)) 94 | print shape(a).intersection(shape(b)) 95 | 96 | # --- stop --- 97 | #A more complicated example: Calculate how many lighnings have fallen in each comarca 98 | from shapely.geometry import shape 99 | import fiona 100 | comarcas = fiona.open('data/comarcas.shp') 101 | rayos = fiona.open('data/llamps.shp') 102 | informe = {} 103 | for comarca in comarcas: 104 | nombre_comarca = comarca['properties']['nombre'] 105 | codigo_comarca = comarca['properties']['codigo'] 106 | informe[codigo_comarca] = {'nombre': nombre_comarca, 'numero_rayos': 0} 107 | shape_comarca = shape(comarca['geometry']) 108 | rayos_bbox = rayos.filter(bbox=shape_comarca.bounds) 109 | for rayo in rayos_bbox: 110 | if shape(rayo['geometry']).within(shape_comarca): 111 | informe[codigo_comarca]['numero_rayos'] += 1 112 | 113 | print informe 114 | rayos.close() 115 | comarcas.close() 116 | # --- stop --- 117 | 118 | #Data representation 119 | 120 | from osgeo import gdal 121 | from mpl_toolkits.basemap import Basemap 122 | import matplotlib.pyplot as plt 123 | import fiona 124 | import numpy 125 | 126 | 127 | m = Basemap(width = 272257.508, \ 128 | height = 269254.668, \ 129 | resolution = 'h', \ 130 | projection = 'tmerc', \ 131 | lon_0 = 1.727858333, \ 132 | lat_0 = 41.715877778) 133 | # --- stop --- 134 | 135 | x = numpy.linspace(0, 272257.508, 272) 136 | y = numpy.linspace(269254.668, 0, 269) 137 | 138 | xx, yy = numpy.meshgrid(x, y) 139 | 140 | m.drawmapboundary(fill_color=(0.8,0.8,1)) 141 | m.fillcontinents(color='beige', zorder=0) 142 | 143 | c = fiona.open('data/llamps.shp') 144 | for point in c: 145 | xp, yp = m(point['geometry']['coordinates'][0],point['geometry']['coordinates'][1]) 146 | m.plot(xp, yp,'bo') 147 | 148 | plt.show() 149 | 150 | # --- stop --- 151 | -------------------------------------------------------------------------------- /fiona_ejemplos.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | 8as Jornadas Sig Libre 4 | 26 de Marzo de 2014 5 | Introducción a Python para usos geoespaciales 6 | 7 | Ejemplos para trabajar con archivos vectoriales usando fiona 8 | """ 9 | 10 | #Usando fiona para leer un fichero: 11 | 12 | import fiona 13 | 14 | c = fiona.open('data/llamps.shp') 15 | 16 | print c 17 | # --- stop --- 18 | 19 | 20 | #Se puede saber el driver OGR usado con la propiedad: 21 | print c.driver 22 | # --- stop --- 23 | 24 | #Y la proyección: 25 | print c.crs 26 | 27 | # --- stop --- 28 | 29 | #El schema indica las otras propiedades del archivo: 30 | print c.schema 31 | # --- stop --- 32 | 33 | #Para ver los registros, podemos usar el iterador: 34 | print c.next() 35 | # --- stop --- 36 | 37 | #Podemos iterar todos los elementos usando 38 | for record in c: 39 | print record['properties']['Data i hor'] 40 | # --- stop --- 41 | 42 | #Podemos filtrar los datos para una bounding box de manera muy sencilla: 43 | 44 | filtered_data = c.filter(bbox=(2.0, 40.8, 2.1, 40.9)) 45 | for record in filtered_data: 46 | print record 47 | #El archivo se puede cerrar usando: 48 | c.close() 49 | # --- stop --- 50 | 51 | #Escritura de archivos vectoriales: 52 | 53 | #Para crear un archivo, 54 | 55 | crs = {u'no_defs': True, u'datum': u'WGS84', u'proj': u'longlat'} 56 | driver = 'ESRI Shapefile' 57 | schema = {'geometry': 'Point', 'properties': [('nombre', 'str'), ('valor', 'str')]} 58 | of = fiona.open('test.shp','w', driver = driver, crs=crs, schema=schema) 59 | # --- stop --- 60 | 61 | 62 | #Se pueden añadir registros a los archivos existentes de la siguiente forma: 63 | rec = {'geometry': {'type': 'Point', 'coordinates': (1.8890812, 40.889)}, 'type': 'Feature', 'id': '0', 'properties': {'nombre': 'punto1', 'valor': 'valor1'}} 64 | 65 | of.write(rec) 66 | 67 | # --- stop --- 68 | 69 | #Operaciones con geometrías usando shapely 70 | 71 | #Para transformar los datos leídos con fiona al objeto shapely, usamos shape: 72 | 73 | from shapely.geometry import shape 74 | import fiona 75 | c = fiona.open('data/llamps.shp') 76 | for point in c: 77 | print shape(point['geometry']) 78 | # --- stop --- 79 | 80 | #Una vez se tiene como objeto shape, se puede operar sobre las geometrías. 81 | 82 | for point in c: 83 | print shape(point['geometry']).buffer(1) 84 | 85 | #La operación inversa, para guardar las geometrías con fiona, es mapping 86 | # --- stop --- 87 | #Distancia entre dos puntos 88 | a = {'type': 'Point', 'coordinates': ((1, 40))} 89 | b = {'type': 'Point', 'coordinates': ((0.5, 40))} 90 | print shape(a).distance(shape(b)) 91 | 92 | # --- stop --- 93 | #Intersección de dos LineString 94 | 95 | a = {'type': 'LineString', 'coordinates': ((1, 40),(2,41))} 96 | b = {'type': 'LineString', 'coordinates': ((0.5, 40),(2.5,41))} 97 | print shape(a).crosses(shape(b)) 98 | print shape(a).intersection(shape(b)) 99 | 100 | # --- stop --- 101 | #Un ejemplo un poco más complicado: Determinar cuantos rayos han caído en cada comarca 102 | 103 | from shapely.geometry import shape 104 | import fiona 105 | comarcas = fiona.open('data/comarcas.shp') 106 | rayos = fiona.open('data/llamps.shp') 107 | informe = {} 108 | for comarca in comarcas: 109 | nombre_comarca = comarca['properties']['nombre'] 110 | codigo_comarca = comarca['properties']['codigo'] 111 | informe[codigo_comarca] = {'nombre': nombre_comarca, 'numero_rayos': 0} 112 | shape_comarca = shape(comarca['geometry']) 113 | rayos_bbox = rayos.filter(bbox=shape_comarca.bounds) 114 | for rayo in rayos_bbox: 115 | if shape(rayo['geometry']).within(shape_comarca): 116 | informe[codigo_comarca]['numero_rayos'] += 1 117 | 118 | print informe 119 | rayos.close() 120 | comarcas.close() 121 | # --- stop --- 122 | 123 | 124 | #Representación de los datos 125 | 126 | from osgeo import gdal 127 | from mpl_toolkits.basemap import Basemap 128 | import matplotlib.pyplot as plt 129 | import fiona 130 | import numpy 131 | 132 | 133 | m = Basemap(width = 272257.508, \ 134 | height = 269254.668, \ 135 | resolution = 'h', \ 136 | projection = 'tmerc', \ 137 | lon_0 = 1.727858333, \ 138 | lat_0 = 41.715877778) 139 | # --- stop --- 140 | 141 | x = numpy.linspace(0, 272257.508, 272) 142 | y = numpy.linspace(269254.668, 0, 269) 143 | 144 | xx, yy = numpy.meshgrid(x, y) 145 | 146 | m.drawmapboundary(fill_color=(0.8,0.8,1)) 147 | m.fillcontinents(color='beige', zorder=0) 148 | 149 | c = fiona.open('data/llamps.shp') 150 | for point in c: 151 | xp, yp = m(point['geometry']['coordinates'][0],point['geometry']['coordinates'][1]) 152 | m.plot(xp, yp,'bo') 153 | 154 | plt.show() 155 | 156 | # --- stop --- 157 | -------------------------------------------------------------------------------- /gdal_examples.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | 8as Jornadas Sig Libre 4 | 26 de Marzo de 2014 5 | Introduction to Python for geospatial uses 6 | 7 | Examples for using GDAL/python to work with vectorial files 8 | 9 | """ 10 | 11 | 12 | #To work with this example, we will need the modules: 13 | 14 | from osgeo import gdal 15 | from mpl_toolkits.basemap import Basemap 16 | import matplotlib.pyplot as plt 17 | import numpy 18 | 19 | #How to open a dataset 20 | ds = gdal.Open('data/XXX_RN1_20131117_0000_CMPAC1C_1h.tif') 21 | # --- stop --- 22 | # auto 23 | 24 | #Get all the possible methods (quit using the q key): 25 | help(ds) 26 | # --- stop --- 27 | 28 | """ 29 | Reading the metadata: 30 | 31 | """ 32 | #Projection: 33 | print ds.GetProjection() 34 | # --- stop --- 35 | 36 | #Geotransform 37 | print ds.GetGeoTransform() 38 | # --- stop --- 39 | 40 | 41 | #To read the bands data: 42 | #All at once 43 | 44 | data = ds.ReadAsArray() 45 | 46 | print data 47 | # --- stop --- 48 | 49 | #Only one band: 50 | band = ds.GetRasterBand(1) 51 | data = band.ReadAsArray() 52 | 53 | print data 54 | 55 | # --- stop --- 56 | 57 | #Drawing the band using basemap 58 | m = Basemap(width = 272257.508, \ 59 | height = 269254.668, \ 60 | resolution = 'h', \ 61 | projection = 'tmerc', \ 62 | lon_0 = 1.727858333, \ 63 | lat_0 = 41.715877778) 64 | 65 | #The equivalent to geotransform. Starting with 0 and finishing with 272257.508, we want 272 elements 66 | x = numpy.linspace(0, 272257.508, 272) 67 | y = numpy.linspace(269254.668, 0, 269) 68 | 69 | #A matrix with the x and y values is created, to pass it to Basemap 70 | xx, yy = numpy.meshgrid(x, y) 71 | 72 | #contourf draws the colored isolines 73 | cs = m.contourf(xx,yy,data) 74 | 75 | plt.show() 76 | 77 | # --- stop --- 78 | 79 | #The map can be more complicated 80 | 81 | #Starting from 0.1 and finishing with 25, paint a color each 3 acumulated liters. 82 | m.contourf(xx,yy,data,numpy.arange(0.1,25,3)) 83 | 84 | #Drawing the land and sea zones as the map background 85 | m.drawmapboundary(fill_color=(0.8,0.8,1)) 86 | m.fillcontinents(color='beige', zorder=0) 87 | 88 | #Drawing the comarques 89 | #The file comarcas.shp will be opened, but the file extension must be removed from the parameter 90 | m.readshapefile('data/comarcas', 'comarcas') 91 | 92 | #And finally, the title and legend 93 | cbar = m.colorbar(cs,location='bottom',pad="5%") 94 | cbar.set_label(u'precipitación (mm)') 95 | 96 | plt.show() 97 | # --- stop --- 98 | 99 | #Raster calculations 100 | 101 | #Opening another raster to play with the data 102 | ds2 = gdal.Open('data/XXX_RN1_20131117_0100_CMPAC1C_1h.tif') 103 | data2 = ds2.ReadAsArray() 104 | 105 | #Summing two mateixes with numpy is easy 106 | suma = data + data2 107 | 108 | m.contourf(xx,yy,suma,numpy.arange(0.1,35,3)) 109 | m.drawmapboundary(fill_color=(0.8,0.8,1)) 110 | m.fillcontinents(color='beige', zorder=0) 111 | 112 | m.readshapefile('data/comarcas', 'comarcas') 113 | 114 | plt.show() 115 | 116 | # --- stop --- 117 | 118 | #Zones wih more than 6 liters of rain at 00 hours (the first opened file) 119 | data_condicion = (data > 6) 120 | cs = m.pcolormesh(xx,yy,data_condicion) 121 | plt.show() 122 | 123 | # --- stop --- 124 | 125 | #Zones where it didn't rain at 00 and it did at 01 hours 126 | data_condicion = (data < 0.1) * (data2 > 0.1) 127 | cs = m.pcolormesh(xx,yy,data_condicion) 128 | plt.show() 129 | 130 | # --- stop --- 131 | 132 | #Zones where it rained all the day 133 | 134 | from osgeo import gdal 135 | from mpl_toolkits.basemap import Basemap 136 | import matplotlib.pyplot as plt 137 | import numpy 138 | 139 | m = Basemap(width = 272257.508, \ 140 | height = 269254.668, \ 141 | resolution = 'h', \ 142 | projection = 'tmerc', \ 143 | lon_0 = 1.727858333, \ 144 | lat_0 = 41.715877778) 145 | 146 | x = numpy.linspace(0, 272257.508, 272) 147 | y = numpy.linspace(269254.668, 0, 269) 148 | 149 | xx, yy = numpy.meshgrid(x, y) 150 | 151 | # --- stop --- 152 | 153 | #For each hour, the file is opened 154 | horas_lluvia = None 155 | for i in range(0,10): 156 | ds = gdal.Open('data/XXX_RN1_20131117_%02d00_CMPAC1C_1h.tif'%i) 157 | datos_hora = ds.ReadAsArray() 158 | #El valor del píxel será 1 si datos_hora tiene un valor > 0.1 (False * 1 = 0 y True * 1 = 1) 159 | zonas_lluvia = 1 * (datos_hora > 0.1) 160 | if horas_lluvia == None: 161 | horas_lluvia = zonas_lluvia 162 | else: 163 | horas_lluvia = horas_lluvia + zonas_lluvia 164 | 165 | # --- stop --- 166 | 167 | #Drawing the number of raining hours is very similar to the previous example 168 | cs = m.pcolormesh(xx,yy,horas_lluvia) 169 | m.drawmapboundary(fill_color=(0.8,0.8,1)) 170 | m.fillcontinents(color='beige', zorder=0) 171 | m.readshapefile('data/comarcas', 'comarcas') 172 | cbar = m.colorbar(cs,location='bottom',pad="5%") 173 | cbar.set_label(u'horas de lluvia') 174 | 175 | plt.figure() 176 | # --- stop --- 177 | 178 | #Drawing only the zones where the value is 10 (it rained in every image) is quite simple as well 179 | cs = m.pcolormesh(xx,yy,horas_lluvia == 10) 180 | m.drawmapboundary(fill_color=(0.8,0.8,1)) 181 | m.fillcontinents(color='beige', zorder=0) 182 | m.readshapefile('data/comarcas', 'comarcas') 183 | cbar = m.colorbar(cs,location='bottom',pad="5%") 184 | cbar.set_label(u'horas de lluvia') 185 | plt.show() 186 | # --- stop --- 187 | -------------------------------------------------------------------------------- /gdal_ejemplos.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | 8as Jornadas Sig Libre 4 | 26 de Marzo de 2014 5 | Introducción a Python para usos geoespaciales 6 | 7 | Ejemplos para trabajar con GDAL/python 8 | """ 9 | 10 | 11 | 12 | #Para este ejemplo, necesitaremos los siguientes módulos: 13 | 14 | from osgeo import gdal 15 | from mpl_toolkits.basemap import Basemap 16 | import matplotlib.pyplot as plt 17 | import numpy 18 | 19 | 20 | #Como abrir un dataset 21 | ds = gdal.Open('data/XXX_RN1_20131117_0000_CMPAC1C_1h.tif') 22 | # --- stop --- 23 | # auto 24 | 25 | #Todos los métodos posibles (salir usando la tecla q): 26 | help(ds) 27 | # --- stop --- 28 | 29 | """ 30 | Leer los metadatos: 31 | 32 | """ 33 | #Proyección: 34 | print ds.GetProjection() 35 | # --- stop --- 36 | 37 | #Geotransform 38 | print ds.GetGeoTransform() 39 | # --- stop --- 40 | 41 | 42 | #Para leer los datos de las bandas: 43 | #Todas a la vez 44 | 45 | data = ds.ReadAsArray() 46 | 47 | print data 48 | # --- stop --- 49 | 50 | #Una sola banda (capa): 51 | band = ds.GetRasterBand(1) 52 | data = band.ReadAsArray() 53 | 54 | print data 55 | 56 | # --- stop --- 57 | 58 | 59 | #Dibujar la banda usando basemap 60 | m = Basemap(width = 272257.508, \ 61 | height = 269254.668, \ 62 | resolution = 'h', \ 63 | projection = 'tmerc', \ 64 | lon_0 = 1.727858333, \ 65 | lat_0 = 41.715877778) 66 | 67 | #El equivalente al geotransform. Empezando po 0 y acabando por 272257.508, de suma 272 a cada elemento 68 | x = numpy.linspace(0, 272257.508, 272) 69 | y = numpy.linspace(269254.668, 0, 269) 70 | 71 | #Se crea la matriz con los valores de x e y, para poder pasarla a Basemap 72 | xx, yy = numpy.meshgrid(x, y) 73 | 74 | #contourf dibuja curvas de nivel coloreadas por dentro "isobandas" 75 | cs = m.contourf(xx,yy,data) 76 | 77 | plt.show() 78 | 79 | # --- stop --- 80 | 81 | 82 | #El mapa se puede complicar un poco más 83 | 84 | #Empezando por 0.1 y acabando por 25, pintamos un color cada 3 litros acumulados. 85 | m.contourf(xx,yy,data,numpy.arange(0.1,25,3)) 86 | 87 | #Dibujamos las zonas de tierra y mar como fondo del maps 88 | m.drawmapboundary(fill_color=(0.8,0.8,1)) 89 | m.fillcontinents(color='beige', zorder=0) 90 | 91 | #Dibujamos las comarcas 92 | #Se abrirá el archivo comarcas.shp, pero se tiene que quitar la extensión 93 | m.readshapefile('data/comarcas', 'comarcas') 94 | 95 | #Y finalmente, la leyenda y el título 96 | cbar = m.colorbar(cs,location='bottom',pad="5%") 97 | cbar.set_label(u'precipitación (mm)') 98 | 99 | plt.show() 100 | # --- stop --- 101 | 102 | 103 | #Cálculos entre rasters 104 | 105 | #Abrimos otro raster para poder jugar con los datos 106 | ds2 = gdal.Open('data/XXX_RN1_20131117_0100_CMPAC1C_1h.tif') 107 | data2 = ds2.ReadAsArray() 108 | 109 | #Sumar dos matrices con numpy es inmediato 110 | suma = data + data2 111 | 112 | m.contourf(xx,yy,suma,numpy.arange(0.1,35,3)) 113 | m.drawmapboundary(fill_color=(0.8,0.8,1)) 114 | m.fillcontinents(color='beige', zorder=0) 115 | 116 | m.readshapefile('data/comarcas', 'comarcas') 117 | 118 | plt.show() 119 | 120 | # --- stop --- 121 | 122 | 123 | #Zonas con lluvia de más de 6 litros en la hora 00 (primer archivo abierto) 124 | data_condicion = (data > 6) 125 | cs = m.pcolormesh(xx,yy,data_condicion) 126 | plt.show() 127 | 128 | # --- stop --- 129 | 130 | #Zonas donde no llovió a las 00 y si que llovió a las 01 131 | data_condicion = (data < 0.1) * (data2 > 0.1) 132 | cs = m.pcolormesh(xx,yy,data_condicion) 133 | plt.show() 134 | 135 | # --- stop --- 136 | 137 | #Zonas en las que ha llovido todo el dia 138 | 139 | from osgeo import gdal 140 | from mpl_toolkits.basemap import Basemap 141 | import matplotlib.pyplot as plt 142 | import numpy 143 | 144 | m = Basemap(width = 272257.508, \ 145 | height = 269254.668, \ 146 | resolution = 'h', \ 147 | projection = 'tmerc', \ 148 | lon_0 = 1.727858333, \ 149 | lat_0 = 41.715877778) 150 | 151 | x = numpy.linspace(0, 272257.508, 272) 152 | y = numpy.linspace(269254.668, 0, 269) 153 | 154 | xx, yy = numpy.meshgrid(x, y) 155 | 156 | # --- stop --- 157 | 158 | #Para cada hora, se abre el archivo 159 | horas_lluvia = None 160 | for i in range(0,10): 161 | ds = gdal.Open('data/XXX_RN1_20131117_%02d00_CMPAC1C_1h.tif'%i) 162 | datos_hora = ds.ReadAsArray() 163 | #El valor del píxel será 1 si datos_hora tiene un valor > 0.1 (False * 1 = 0 y True * 1 = 1) 164 | zonas_lluvia = 1 * (datos_hora > 0.1) 165 | if horas_lluvia == None: 166 | horas_lluvia = zonas_lluvia 167 | else: 168 | horas_lluvia = horas_lluvia + zonas_lluvia 169 | 170 | # --- stop --- 171 | 172 | #Dibujar el número de horas de lluvia es identico a los ejemplos anteriores 173 | cs = m.pcolormesh(xx,yy,horas_lluvia) 174 | m.drawmapboundary(fill_color=(0.8,0.8,1)) 175 | m.fillcontinents(color='beige', zorder=0) 176 | m.readshapefile('data/comarcas', 'comarcas') 177 | cbar = m.colorbar(cs,location='bottom',pad="5%") 178 | cbar.set_label(u'horas de lluvia') 179 | 180 | plt.figure() 181 | # --- stop --- 182 | 183 | #Dibujar solo las zonas donde el valor es 10 (ha llovido en cada imagen), también es sencillo 184 | cs = m.pcolormesh(xx,yy,horas_lluvia == 10) 185 | m.drawmapboundary(fill_color=(0.8,0.8,1)) 186 | m.fillcontinents(color='beige', zorder=0) 187 | m.readshapefile('data/comarcas', 'comarcas') 188 | cbar = m.colorbar(cs,location='bottom',pad="5%") 189 | cbar.set_label(u'horas de lluvia') 190 | plt.show() 191 | # --- stop --- 192 | 193 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 2, June 1991 3 | 4 | Copyright (C) 1989, 1991 Free Software Foundation, Inc., 5 | 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA 6 | Everyone is permitted to copy and distribute verbatim copies 7 | of this license document, but changing it is not allowed. 8 | 9 | Preamble 10 | 11 | The licenses for most software are designed to take away your 12 | freedom to share and change it. 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For example, if a patent 205 | license would not permit royalty-free redistribution of the Program by 206 | all those who receive copies directly or indirectly through you, then 207 | the only way you could satisfy both it and this License would be to 208 | refrain entirely from distribution of the Program. 209 | 210 | If any portion of this section is held invalid or unenforceable under 211 | any particular circumstance, the balance of the section is intended to 212 | apply and the section as a whole is intended to apply in other 213 | circumstances. 214 | 215 | It is not the purpose of this section to induce you to infringe any 216 | patents or other property right claims or to contest validity of any 217 | such claims; this section has the sole purpose of protecting the 218 | integrity of the free software distribution system, which is 219 | implemented by public license practices. Many people have made 220 | generous contributions to the wide range of software distributed 221 | through that system in reliance on consistent application of that 222 | system; it is up to the author/donor to decide if he or she is willing 223 | to distribute software through any other system and a licensee cannot 224 | impose that choice. 225 | 226 | This section is intended to make thoroughly clear what is believed to 227 | be a consequence of the rest of this License. 228 | 229 | 8. If the distribution and/or use of the Program is restricted in 230 | certain countries either by patents or by copyrighted interfaces, the 231 | original copyright holder who places the Program under this License 232 | may add an explicit geographical distribution limitation excluding 233 | those countries, so that distribution is permitted only in or among 234 | countries not thus excluded. In such case, this License incorporates 235 | the limitation as if written in the body of this License. 236 | 237 | 9. The Free Software Foundation may publish revised and/or new versions 238 | of the General Public License from time to time. Such new versions will 239 | be similar in spirit to the present version, but may differ in detail to 240 | address new problems or concerns. 241 | 242 | Each version is given a distinguishing version number. If the Program 243 | specifies a version number of this License which applies to it and "any 244 | later version", you have the option of following the terms and conditions 245 | either of that version or of any later version published by the Free 246 | Software Foundation. If the Program does not specify a version number of 247 | this License, you may choose any version ever published by the Free Software 248 | Foundation. 249 | 250 | 10. If you wish to incorporate parts of the Program into other free 251 | programs whose distribution conditions are different, write to the author 252 | to ask for permission. For software which is copyrighted by the Free 253 | Software Foundation, write to the Free Software Foundation; we sometimes 254 | make exceptions for this. Our decision will be guided by the two goals 255 | of preserving the free status of all derivatives of our free software and 256 | of promoting the sharing and reuse of software generally. 257 | 258 | NO WARRANTY 259 | 260 | 11. BECAUSE THE PROGRAM IS LICENSED FREE OF CHARGE, THERE IS NO WARRANTY 261 | FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN 262 | OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES 263 | PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED 264 | OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF 265 | MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS 266 | TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE 267 | PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, 268 | REPAIR OR CORRECTION. 269 | 270 | 12. IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING 271 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY AND/OR 272 | REDISTRIBUTE THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, 273 | INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING 274 | OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED 275 | TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY 276 | YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER 277 | PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE 278 | POSSIBILITY OF SUCH DAMAGES. 279 | 280 | END OF TERMS AND CONDITIONS 281 | 282 | How to Apply These Terms to Your New Programs 283 | 284 | If you develop a new program, and you want it to be of the greatest 285 | possible use to the public, the best way to achieve this is to make it 286 | free software which everyone can redistribute and change under these terms. 287 | 288 | To do so, attach the following notices to the program. It is safest 289 | to attach them to the start of each source file to most effectively 290 | convey the exclusion of warranty; and each file should have at least 291 | the "copyright" line and a pointer to where the full notice is found. 292 | 293 | {description} 294 | Copyright (C) {year} {fullname} 295 | 296 | This program is free software; you can redistribute it and/or modify 297 | it under the terms of the GNU General Public License as published by 298 | the Free Software Foundation; either version 2 of the License, or 299 | (at your option) any later version. 300 | 301 | This program is distributed in the hope that it will be useful, 302 | but WITHOUT ANY WARRANTY; without even the implied warranty of 303 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 304 | GNU General Public License for more details. 305 | 306 | You should have received a copy of the GNU General Public License along 307 | with this program; if not, write to the Free Software Foundation, Inc., 308 | 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. 309 | 310 | Also add information on how to contact you by electronic and paper mail. 311 | 312 | If the program is interactive, make it output a short notice like this 313 | when it starts in an interactive mode: 314 | 315 | Gnomovision version 69, Copyright (C) year name of author 316 | Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 317 | This is free software, and you are welcome to redistribute it 318 | under certain conditions; type `show c' for details. 319 | 320 | The hypothetical commands `show w' and `show c' should show the appropriate 321 | parts of the General Public License. Of course, the commands you use may 322 | be called something other than `show w' and `show c'; they could even be 323 | mouse-clicks or menu items--whatever suits your program. 324 | 325 | You should also get your employer (if you work as a programmer) or your 326 | school, if any, to sign a "copyright disclaimer" for the program, if 327 | necessary. Here is a sample; alter the names: 328 | 329 | Yoyodyne, Inc., hereby disclaims all copyright interest in the program 330 | `Gnomovision' (which makes passes at compilers) written by James Hacker. 331 | 332 | {signature of Ty Coon}, 1 April 1989 333 | Ty Coon, President of Vice 334 | 335 | This General Public License does not permit incorporating your program into 336 | proprietary programs. If your program is a subroutine library, you may 337 | consider it more useful to permit linking proprietary applications with the 338 | library. If this is what you want to do, use the GNU Lesser General 339 | Public License instead of this License. 340 | -------------------------------------------------------------------------------- /data/llamps.csv: -------------------------------------------------------------------------------- 1 | Data i hora tipus UTMx UTMy latitud longitud Amplitud(kA) Risetime maxrisetime 2 | 2013-11-17 01:08:14.464866 nt 837812.51 4333940.3 39.0885400 6.9052806 -214.5630 363 0 3 | 2013-11-17 01:09:45.490369 nt 757914.95 4441378.9 40.0825270 6.0247726 101.5840 200 0 4 | 2013-11-17 01:10:42.130141 nt 406408.36 4527107.8 40.8890000 1.8890812 9.3610 276 0 5 | 2013-11-17 01:10:42.18388 nt 411069.73 4528550.2 40.9025100 1.9441953 72.8715 224 0 6 | 2013-11-17 01:10:42.771957 nt 423257.53 4536485.8 40.9752200 2.0878906 6.1050 80 0 7 | 2013-11-17 01:16:04.600467 nt 849897.29 4332699.8 39.0726300 7.0440297 -162.3010 124 0 8 | 2013-11-17 01:17:04.461124 nt 754530.04 4449418.4 40.1558880 5.9882940 131.8120 492 0 9 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06:29:01.457833 nt 521032.56 4619219.0 41.7237630 3.2528600 -14.6150 80 0 142 | 2013-11-17 06:33:11.386328 nt 517618.78 4624730.6 41.7734870 3.2119820 -107.7260 180 0 143 | 2013-11-17 06:34:01.368648 nt 526947.78 4626104.9 41.7856030 3.3242857 8.7690 68 0 144 | 2013-11-17 06:34:01.371424 nt 515458.95 4623806.9 41.7652130 3.1859720 8.8615 228 0 145 | 2013-11-17 06:35:44.898602 nt 504886.37 4626302.7 41.7878270 3.0588040 8.6765 228 0 146 | 2013-11-17 06:35:44.906485 nt 519214.53 4624506.0 41.7714270 3.2311740 7.0670 180 0 147 | 2013-11-17 06:36:30.851368 nt 511222.06 4625058.2 41.7765540 3.1350257 -9.2315 52 0 148 | 2013-11-17 06:37:36.476472 nt 517397.08 4628331.0 41.8059200 3.2094202 13.7825 180 0 149 | 2013-11-17 06:40:02.201121 nt 128438.34 4061731.3 36.6281240 -1.1545805� 200.5590 328 0 150 | 2013-11-17 06:40:26.325512 nt 525479.52 4617523.6 41.7083630 3.3062496 -12.5430 48 0 151 | 2013-11-17 06:40:26.50675 nt 520499.65 4616636.4 41.7005160 3.2463644 -11.0815 44 0 152 | 2013-11-17 06:41:24.78906 nt 511953.04 4630518.0 41.8257180 3.1439310 -109.6130 200 0 153 | 2013-11-17 06:42:12.766072 nt 510535.52 4629140.3 41.8133300 3.1268377 -9.8235 92 0 154 | 2013-11-17 06:43:30.535196 nt 506792.94 4629232.2 41.8141980 3.0817816 -10.6560 252 0 155 | 2013-11-17 06:43:30.578199 nt 510836.45 4628969.8 41.8117900 3.1304574 -9.1760 64 0 156 | 2013-11-17 06:48:30.323151 nt 503312.02 4631310.1 41.8329350 3.0398858 -204.3330 212 0 157 | 2013-11-17 06:49:48.149475 nt 517084.19 4619279.3 41.7244000 3.2053936 8.1400 72 0 158 | 2013-11-17 06:52:36.515696 nt 524478.92 4622851.6 41.7563820 3.2944422 -117.6600 116 0 159 | 2013-11-17 06:52:36.535776 nt 527449.71 4625269.3 41.7780600 3.3302872 -16.0025 316 0 160 | 2013-11-17 06:52:36.575347 nt 531047.27 4623071.5 41.7581330 3.3734589 -15.8730 60 0 161 | 2013-11-17 06:52:36.610598 nt 530196.91 4622820.0 41.7559000 3.3632176 -12.1730 36 0 162 | 2013-11-17 06:52:36.662988 nt 525558.36 4622308.9 41.7514600 3.3074026 -10.5265 40 0 163 | 2013-11-17 06:52:36.797775 nt 527270.25 4622905.4 41.7567750 3.3280194 -11.8400 44 0 164 | 2013-11-17 06:54:59.326638 nt 524053.44 4624010.7 41.7668340 3.2893713 -9.9345 40 0 165 | 2013-11-17 06:54:59.345966 nt 527234.45 4624286.4 41.7692150 3.3276520 -13.0980 44 0 166 | 2013-11-17 06:54:59.357888 nt 526939.74 4624305.2 41.7693940 3.3241074 -9.4905 180 0 167 | 2013-11-17 06:58:20.588656 nt 503781.06 4628721.2 41.8096160 3.0455177 -11.4700 56 0 168 | 2013-11-17 07:04:43.664877 nt 503393.88 4638222.2 41.8951900 3.0409112 8.0660 188 0 169 | 2013-11-17 07:05:00.912299 nt 347896.61 4549015.8 41.0774700 1.1894337 -70.3925 396 0 170 | 2013-11-17 07:08:37.92535 nt 503909.29 4644148.5 41.9485630 3.0471635 14.4485 328 0 171 | 2013-11-17 07:09:26.238521 nt 348983.41 4547468.3 41.0637400 1.2027439 6.1975 116 0 172 | 2013-11-17 07:09:26.238994 nt 347552.69 4544318.0 41.0351100 1.1865042 12.2100 176 0 173 | 2013-11-17 07:13:23.98432 nt 494880.05 4650306.8 42.0040200 2.9381770 -8.3435 84 0 174 | 2013-11-17 07:13:24.097215 nt 496878.10 4642873.2 41.9370800 2.9623427 -9.8235 264 0 175 | 2013-11-17 07:15:49.295289 nt 345225.94 4550816.0 41.0931740 1.1572060 8.2695 164 0 176 | 2013-11-17 07:15:49.296835 nt 345260.55 4553261.3 41.1151960 1.1570023 8.9355 572 0 177 | 2013-11-17 07:18:41.195004 nt 346194.40 4543621.9 41.0285870 1.1705275 10.2490 120 0 178 | 2013-11-17 07:32:08.639268 nt 490624.08 4651776.8 42.0172200 2.8867630 -10.4525 56 0 179 | 2013-11-17 07:32:08.688079 nt 493641.49 4653088.5 42.0290640 2.9231913 -10.7485 68 0 180 | 2013-11-17 07:32:08.72437 nt 491879.97 4652506.9 42.0238100 2.9019208 -9.2685 76 0 181 | 2013-11-17 07:52:18.415438 nt 505701.37 4638813.3 41.9005000 3.0687323 -8.0845 52 0 182 | 2013-11-17 07:55:21.624944 nt 471948.11 4655681.8 42.0519450 2.6610210 -6.5675 32 0 183 | 2013-11-17 07:55:21.647278 nt 471693.46 4656010.9 42.0549000 2.6579280 -10.9335 40 0 184 | 2013-11-17 07:55:21.657806 nt 472532.24 4656651.6 42.0607000 2.6680340 -11.1925 40 0 185 | 2013-11-17 07:56:39.423389 nt 507247.20 4642643.0 41.9349800 3.0874150 -15.2995 64 0 186 | 2013-11-17 07:56:39.459534 nt 525717.04 4651050.5 42.0103150 3.3105620 8.0660 116 0 187 | 2013-11-17 07:56:42.066877 nt 591516.62 4547448.5 41.0724300 4.0893030 21.9410 116 0 188 | 2013-11-17 08:16:07.143347 nt 523593.27 4644260.7 41.9492300 3.2846430 11.3220 268 0 189 | 2013-11-17 08:19:19.928979 nt 468103.63 4661343.4 42.1027870 2.6142566 -11.5255 152 0 190 | 2013-11-17 08:19:19.987699 nt 476013.03 4670596.2 42.1864000 2.7095280 -11.5810 64 0 191 | 2013-11-17 08:24:31.103804 nt 502129.15 4655429.4 42.0501700 3.0257280 -104.5440 268 0 192 | 2013-11-17 08:26:23.132532 nt 477488.38 4676433.0 42.2390100 2.7271676 -11.7660 60 0 193 | 2013-11-17 08:27:15.758201 nt 499813.33 4656668.6 42.0613330 2.9977440 -8.8060 64 0 194 | 2013-11-17 08:27:15.801884 nt 500186.91 4656897.3 42.0633930 3.0022590 -12.9315 64 0 195 | 2013-11-17 08:27:15.873846 nt 501798.04 4655336.6 42.0493350 3.0217266 14.1525 171 0 196 | 2013-11-17 08:32:28.25112 nt 487316.50 4666334.6 42.1482850 2.8465004 9.1390 76 0 197 | 2013-11-17 08:36:26.905326 nt 462098.20 4666353.0 42.1476360 2.5413058 -6.3640 128 0 198 | 2013-11-17 08:36:49.997763 nt 491391.08 4661883.5 42.1082530 2.8958778 -95.6265 468 0 199 | 2013-11-17 08:36:50.024096 nt 496478.92 4663927.4 42.1267000 2.9574013 -14.2450 76 0 200 | 2013-11-17 08:38:00.933677 nt 490020.95 4658397.0 42.0768360 2.8793660 7.4370 236 0 201 | 2013-11-17 08:38:00.933853 nt 513919.52 4673790.9 42.2154160 3.1686366 -9.8975 148 0 202 | 2013-11-17 08:38:01.51326 nt 500873.23 4673091.5 42.2092400 3.0105782 8.4915 80 0 203 | 2013-11-17 08:38:53.606205 nt 476682.59 4681660.0 42.2860600 2.7171915 -9.3610 52 0 204 | 2013-11-17 08:38:53.793687 nt 466518.96 4676557.9 42.2397420 2.5942178 16.6130 264 0 205 | 2013-11-17 07:18:41.197735 nt 339019.86 4547547.4 41.0625420 1.0842079 5.1245 44 0 206 | 2013-11-17 07:20:16.856561 nt 350991.48 4548776.7 41.0758900 1.2263144 6.6600 424 0 207 | 2013-11-17 07:20:16.857189 nt 338210.58 4537603.7 40.9728600 1.0771880 5.1245 92 0 208 | 2013-11-17 07:22:05.91373 nt 445558.21 4638127.3 41.8924670 2.3437657 -4.5695 44 0 209 | 2013-11-17 07:26:43.866529 nt 337755.11 4542779.6 41.0193670 1.0704190 14.7630 236 0 210 | 2013-11-17 08:52:53.538191 nt 485696.25 4673237.3 42.2104230 2.8267220 -15.9285 124 0 211 | 2013-11-17 08:53:54.185193 nt 330105.71 4537281.2 40.9683100 0.9810087 -13.1165 148 0 212 | 2013-11-17 08:53:54.200272 nt 330187.79 4537553.7 40.9707800 0.9819087 -9.6755 56 0 213 | 2013-11-17 08:54:23.719084 nt 440740.53 4682308.1 42.2899930 2.2812200 79.2355 536 0 214 | 2013-11-17 08:54:24.086387 nt 410809.15 4674901.9 42.2204550 1.9193627 9.3425 52 0 215 | 2013-11-17 08:40:09.615604 nt 496842.79 4665589.9 42.1416740 2.9617944 -7.6960 52 0 216 | 2013-11-17 08:41:33.96905 nt 496251.66 4663993.0 42.1272900 2.9546514 -10.6190 56 0 217 | 2013-11-17 08:42:48.837287 nt 469101.80 4676854.1 42.2425160 2.6255047 -8.3250 76 0 218 | 2013-11-17 08:42:49.12701 nt 451773.57 4685714.5 42.3214300 2.4147522 56.6285 192 0 219 | 2013-11-17 08:44:17.34047 nt 492310.68 4671833.3 42.1978720 2.9068687 -11.8400 72 0 220 | 2013-11-17 08:47:12.663975 nt 479752.21 4679907.9 42.2703670 2.7544827 -10.2860 76 0 221 | 2013-11-17 08:47:13.135998 nt 463783.72 4674622.5 42.2221900 2.5611890 -6.6970 60 0 222 | 2013-11-17 08:47:25.002104 nt 486831.33 4670257.9 42.1836100 2.8405400 -14.5965 116 0 223 | 2013-11-17 08:47:25.011527 nt 491056.67 4671823.5 42.1977700 2.8916807 -11.7660 52 0 224 | 2013-11-17 08:48:36.718503 nt 481334.51 4683474.9 42.3025300 2.7735540 -8.0845 60 0 225 | 2013-11-17 08:48:42.918649 nt 325545.00 4537261.4 40.9671700 0.9268490 -11.4145 80 0 226 | 2013-11-17 08:49:25.473242 nt 487974.01 4673379.5 42.2117420 2.8543122 -8.3805 56 0 227 | 2013-11-17 08:49:25.520378 nt 488342.01 4675003.1 42.2263700 2.8587377 -16.6315 72 0 228 | 2013-11-17 08:49:25.55843 nt 487548.87 4672032.0 42.1996000 2.8491907 -14.6890 72 0 229 | 2013-11-17 08:49:57.231947 nt 469658.37 4687736.3 42.3405400 2.6316798 14.8925 72 0 230 | 2013-11-17 08:50:26.847766 nt 325855.07 4538807.6 40.9811550 0.9300963 14.5965 44 0 231 | 2013-11-17 08:50:26.858582 nt 325347.58 4537443.8 40.9687700 0.9244530 -10.7300 88 0 232 | 2013-11-17 08:56:48.276987 nt 320897.51 4536625.5 40.9604400 0.8718401 -15.0960 96 0 233 | 2013-11-17 08:57:08.665284 nt 481782.47 4673731.7 42.2147940 2.7792947 -10.6930 56 0 234 | 2013-11-17 08:57:55.369575 nt 491694.00 4679790.7 42.2695300 2.8992858 -10.4155 60 0 235 | 2013-11-17 08:57:55.798542 nt 479965.92 4678974.9 42.2619700 2.7571063 -20.7200 448 0 236 | 2013-11-17 08:57:55.902435 nt 479253.73 4678063.2 42.2537400 2.7485044 -12.6170 64 0 237 | 2013-11-17 08:59:01.882237 nt 493904.84 4680623.0 42.2770460 2.9260845 -11.4700 52 0 238 | 2013-11-17 09:00:38.281589 nt 322353.93 4541939.6 41.0085950 0.8876079 -223.5170 280 0 239 | 2013-11-17 09:02:43.827974 nt 321323.42 4543583.0 41.0231630 0.8748866 -10.0640 52 0 240 | 2013-11-17 09:04:11.93949 nt 323217.32 4543750.6 41.0250850 0.8973494 -7.9365 60 0 241 | 2013-11-17 09:05:07.278578 nt 322043.62 4541757.3 41.0068860 0.8839730 -14.2820 72 0 242 | 2013-11-17 09:05:53.204292 nt 322035.96 4542739.7 41.0157280 0.8835989 -12.9500 52 0 243 | 2013-11-17 09:05:53.228727 nt 318215.48 4539469.4 40.9854470 0.8391572 -7.2150 44 0 244 | 2013-11-17 09:05:53.250392 nt 318736.16 4538852.2 40.9800070 0.8455232 -13.4865 120 0 245 | 2013-11-17 09:05:53.27399 nt 321869.59 4542016.6 41.0091820 0.8818302 -9.6385 120 0 246 | 2013-11-17 09:05:53.317184 nt 320915.78 4540195.9 40.9925840 0.8710235 -10.6375 56 0 247 | 2013-11-17 09:05:53.377402 nt 321952.81 4542136.5 41.0102800 0.8827846 -7.6035 112 0 248 | 2013-11-17 09:06:57.976603 nt 482154.07 4681103.5 42.2811930 2.7835698 -15.2810 76 0 249 | 2013-11-17 09:06:58.227623 nt 480759.27 4679812.7 42.2695350 2.7666970 -7.7330 52 0 250 | 2013-11-17 09:07:23.995969 nt 569135.51 4611296.4 41.6496850 3.8302128 -12.6355 44 0 251 | 2013-11-17 09:10:07.029736 nt 320355.07 4544402.5 41.0303270 0.8631384 -5.1430 44 0 252 | 2013-11-17 09:10:50.574656 nt 395495.08 4192684.2 37.8750300 1.8117907 101.2690 240 0 253 | 2013-11-17 09:11:14.01608 nt 487827.88 4688234.6 42.3455240 2.8522296 14.9110 348 0 254 | 2013-11-17 09:12:03.872506 nt 578322.68 4615337.3 41.6852260 3.9410532 -11.6920 64 0 255 | 2013-11-17 09:12:21.327239 nt 321354.49 4544428.1 41.0307770 0.8750113 -17.1310 84 0 256 | 2013-11-17 09:12:21.666355 nt 316794.12 4547068.9 41.0535350 0.8200181 -7.2150 120 0 257 | 2013-11-17 09:12:21.823079 nt 313950.80 4543297.6 41.0189440 0.7873467 -6.9005 48 0 258 | 2013-11-17 09:13:29.023337 nt 430008.75 4570735.4 41.2843060 2.1642168 -9.1575 76 0 259 | 2013-11-17 09:13:29.037121 nt 429727.55 4571622.3 41.2922700 2.1607570 -24.3645 132 0 260 | 2013-11-17 09:14:13.478038 nt 580217.52 4616964.4 41.6996900 3.9640355 -11.9510 44 0 261 | 2013-11-17 09:14:13.654831 nt 577063.10 4619295.3 41.7209930 3.9264326 -11.6735 40 0 262 | 2013-11-17 09:14:30.292711 nt 394003.14 4203442.5 37.9717980 1.7932476 88.1710 220 0 263 | 2013-11-17 09:15:42.030824 nt 563965.11 4625484.7 41.7778970 3.7696526 -10.6930 36 0 264 | 2013-11-17 09:16:04.328074 nt 482322.83 4688343.0 42.3463940 2.7853950 -72.9825 240 0 265 | 2013-11-17 09:16:04.340983 nt 482389.11 4689086.3 42.3530900 2.7861770 -18.1300 96 0 266 | 2013-11-17 09:18:02.165126 nt 578931.17 4629431.1 41.8120880 3.9502332 -12.5430 28 0 267 | 2013-11-17 09:18:02.311968 nt 608555.30 4633657.9 41.8466450 4.3075680 -12.2840 64 0 268 | 2013-11-17 09:19:59.007398 nt 576966.80 4631050.6 41.8268660 3.9267979 -13.2275 40 0 269 | 2013-11-17 09:20:35.498438 nt 479724.81 4691827.5 42.3777120 2.7537322 -119.4730 388 0 270 | 2013-11-17 09:23:22.740256 nt 483599.90 4692963.7 42.3880350 2.8007674 -19.1845 100 0 271 | 2013-11-17 09:29:16.396154 nt 479929.19 4694551.9 42.4022520 2.7561197 -28.5270 164 0 272 | 2013-11-17 09:32:48.081239 nt 539657.71 4652804.0 42.0255280 3.4790250 -14.6335 44 0 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| 2013-11-17 00:00:29.876342 nt 582245.72 4624650.5 41.7687000 3.9894683 -13.7270 40 0 285 | 2013-11-17 00:03:08.256199 nt 576847.88 4622779.1 41.7523880 3.9242954 -110.0930 264 0 286 | 2013-11-17 00:04:22.468129 nt 565592.38 4620605.9 41.7338260 3.7886927 -12.6910 60 0 287 | 2013-11-17 00:05:49.745688 nt 579526.33 4623533.1 41.7589150 3.9566073 -12.8020 44 0 288 | 2013-11-17 00:06:39.347816 nt 573557.71 4625035.3 41.7730180 3.8850064 -124.1720 316 0 289 | 2013-11-17 00:06:39.581649 nt 569527.69 4623842.6 41.7626400 3.8363850 -12.4320 48 0 290 | 2013-11-17 00:06:39.646041 nt 565136.37 4623689.6 41.7616350 3.7835476 -11.2665 44 0 291 | 2013-11-17 00:06:58.137875 nt 694112.64 4464156.6 40.3046950 5.2840366 91.3345 160 0 292 | 2013-11-17 00:06:59.452962 nt 675050.27 4486936.3 40.5139920 5.0661483 -131.9600 320 0 293 | 2013-11-17 00:08:43.385853 nt 630127.85 4630795.6 41.8176230 4.5666986 29.1930 68 0 294 | 2013-11-17 00:08:43.388099 nt 568965.18 4622730.5 41.7526740 3.8294900 -153.1800 224 0 295 | 2013-11-17 00:08:43.414214 nt 590276.14 4622825.8 41.7513960 4.0857863 -12.6725 44 0 296 | 2013-11-17 00:10:18.032247 nt 568602.20 4622985.8 41.7550050 3.8251540 -117.3820 176 0 297 | 2013-11-17 00:10:18.110063 nt 573354.73 4622492.8 41.7501400 3.8822508 -16.7795 52 0 298 | 2013-11-17 00:13:04.374615 nt 562855.79 4623632.0 41.7613000 3.7561100 -142.5610 200 0 299 | 2013-11-17 00:18:28.256894 nt 477227.41 4496561.7 40.6188660 2.7307823 153.9390 212 0 300 | 2013-11-17 00:18:28.93023 nt 465541.88 4500707.4 40.6558070 2.5924115 18.7590 84 0 301 | 2013-11-17 00:30:47.587001 nt 579479.73 4637727.4 41.8867450 3.9579504 -17.2420 116 0 302 | 2013-11-17 00:51:34.196025 nt 757776.00 4425812.7 39.9425200 6.0169670 148.6290 168 0 303 | 2013-11-17 00:54:22.553497 nt 687920.38 4471567.5 40.3728260 5.2134075 100.5660 200 0 304 | 2013-11-17 00:57:14.962149 nt 417220.66 4518290.7 40.8107500 2.0185750 8.1585 352 0 305 | 2013-11-17 00:57:15.003103 nt 421819.10 4523559.6 40.8586580 2.0724254 184.5560 288 0 306 | 2013-11-17 01:04:11.939345 nt 844323.99 4333711.8 39.0839420 6.9802730 -154.6600 323 0 307 | 2013-11-17 01:04:18.385615 nt 414800.47 4527506.8 40.8935100 1.9886240 18.7220 544 0 308 | 2013-11-17 01:04:18.405042 nt 417336.83 4525114.2 40.8722200 2.0190463 99.6225 348 0 309 | 2013-11-17 01:05:26.280343 nt 850154.47 4329424.8 39.0430900 7.0453124 94.6090 296 0 -------------------------------------------------------------------------------- /data/llamps.txt: -------------------------------------------------------------------------------- 1 | Data i hora tipus UTMx UTMy latitud longitud Amplitud(kA) Risetime maxrisetime 2 | 2013-11-17 01:08:14.464866 nt 837812.51 4333940.3 39.0885400 6.9052806 -214.5630 363 0 3 | 2013-11-17 01:09:45.490369 nt 757914.95 4441378.9 40.0825270 6.0247726 101.5840 200 0 4 | 2013-11-17 01:10:42.130141 nt 406408.36 4527107.8 40.8890000 1.8890812 9.3610 276 0 5 | 2013-11-17 01:10:42.18388 nt 411069.73 4528550.2 40.9025100 1.9441953 72.8715 224 0 6 | 2013-11-17 01:10:42.771957 nt 423257.53 4536485.8 40.9752200 2.0878906 6.1050 80 0 7 | 2013-11-17 01:16:04.600467 nt 849897.29 4332699.8 39.0726300 7.0440297 -162.3010 124 0 8 | 2013-11-17 01:17:04.461124 nt 754530.04 4449418.4 40.1558880 5.9882940 131.8120 492 0 9 | 2013-11-17 01:20:22.083761 nt 418590.17 4287639.6 38.7330300 2.0634040 -150.1090 212 0 10 | 2013-11-17 01:21:05.338443 nt 805200.64 4415231.3 39.8316100 6.5661410 312.7800 340 0 11 | 2013-11-17 01:21:19.654241 nt 417737.06 4292364.6 38.7755240 2.0530280 -70.1150 128 0 12 | 2013-11-17 01:22:17.753625 nt 418745.82 4295525.7 38.8041000 2.0642667 -103.5810 68 0 13 | 2013-11-17 01:23:26.571892 nt 419525.83 4293080.9 38.7821430 2.0735335 -77.8480 88 0 14 | 2013-11-17 01:25:21.905603 nt 420189.39 4293329.1 38.7844400 2.0811431 -71.9280 96 0 15 | 2013-11-17 01:31:07.597395 nt 423133.46 4268367.1 38.5597800 2.1177993 -131.3500 328 0 16 | 2013-11-17 01:31:30.847965 nt 684869.41 4092472.6 36.9596060 5.0764256 -69.4120 124 0 17 | 2013-11-17 01:35:43.118667 nt 422356.55 4290078.0 38.7553400 2.1064563 -111.3520 204 0 18 | 2013-11-17 01:37:14.372734 nt 782586.36 4444679.9 40.1043050 6.3151183 142.7460 196 0 19 | 2013-11-17 01:37:57.791208 nt 653355.23 4627248.3 41.7815360 4.8453030 -15.6140 32 0 20 | 2013-11-17 01:45:22.039649 nt 647310.36 4630906.1 41.8156100 4.7735080 -119.2320 240 0 21 | 2013-11-17 01:46:22.959763 nt 806700.27 4422029.9 39.8922040 6.5868170 202.7040 184 0 22 | 2013-11-17 01:50:02.236188 nt 648848.09 4633993.5 41.8431170 4.7927880 -155.4190 332 0 23 | 2013-11-17 01:59:07.209802 nt 877821.06 4317892.5 38.9279600 7.3577414 -95.7560 104 0 24 | 2013-11-17 02:00:18.262888 nt 863450.29 4337426.0 39.1095700 7.2028110 -73.7410 212 0 25 | 2013-11-17 02:01:06.961377 nt 807567.10 4435165.4 40.0100020 6.6031356 130.2400 140 0 26 | 2013-11-17 02:03:32.517592 nt 759377.33 4485608.4 40.4799800 6.0598030 -134.2170 80 0 27 | 2013-11-17 02:23:48.579048 nt 457351.79 4536465.2 40.9775280 2.4930923 31.5980 212 0 28 | 2013-11-17 02:23:48.769477 nt 458749.61 4532495.3 40.9418400 2.5099704 -15.3365 60 0 29 | 2013-11-17 02:24:57.205526 nt 484937.61 4533655.1 40.9531900 2.8210370 -77.8850 112 0 30 | 2013-11-17 02:24:57.422627 nt 484309.84 4534675.3 40.9623680 2.8135524 -6.4195 20 0 31 | 2013-11-17 02:29:54.645188 nt 452737.10 4536261.6 40.9754400 2.4382610 21.4970 120 0 32 | 2013-11-17 02:29:54.865156 nt 452209.65 4544177.3 41.0467100 2.4313796 -12.1175 40 0 33 | 2013-11-17 02:29:54.971506 nt 454051.69 4541539.5 41.0230560 2.4534922 -8.4175 28 0 34 | 2013-11-17 02:35:28.738743 nt 467775.92 4543356.0 41.0400770 2.6166286 7.5850 240 0 35 | 2013-11-17 02:44:59.090166 nt 875798.45 4319014.4 38.9389080 7.3350900 -56.1105 248 0 36 | 2013-11-17 03:07:04.770018 nt 471858.54 4542183.1 41.0296630 2.6652524 18.5000 276 0 37 | 2013-11-17 03:12:02.32602 nt 446639.83 4559278.1 41.1823800 2.3638005 173.6220 340 0 38 | 2013-11-17 03:15:59.189605 nt 446238.09 4551798.1 41.1149800 2.3596668 42.9200 171 0 39 | 2013-11-17 03:19:54.176914 nt 457939.00 4551498.3 41.1129700 2.4990456 -4.8655 28 0 40 | 2013-11-17 03:20:49.410976 nt 465610.99 4550960.9 41.1084900 2.5904481 11.5255 68 0 41 | 2013-11-17 03:20:49.741768 nt 460691.20 4551756.1 41.1154300 2.5318072 -6.3825 32 0 42 | 2013-11-17 03:23:36.434535 nt 459766.88 4550003.7 41.0996000 2.5209131 14.0045 256 0 43 | 2013-11-17 03:23:36.764853 nt 423839.14 4562098.0 41.2059560 2.0916305 24.0870 136 0 44 | 2013-11-17 03:32:28.28289 nt 450628.74 4398434.9 39.7337000 2.4238690 -55.1115 44 0 45 | 2013-11-17 03:37:39.052866 nt 438821.39 4472359.4 40.3989000 2.2791078 11.8030 100 0 46 | 2013-11-17 03:37:39.053183 nt 452299.97 4399652.6 39.7447660 2.4432820 -192.3440 320 0 47 | 2013-11-17 03:37:39.096372 nt 450726.03 4402578.2 39.7710340 2.4246938 -77.1080 100 0 48 | 2013-11-17 03:37:39.104847 nt 460502.74 4387410.6 39.6348880 2.5397482 -20.3130 188 0 49 | 2013-11-17 03:37:39.111065 nt 449996.71 4403698.2 39.7810820 2.4160936 -20.0910 224 0 50 | 2013-11-17 03:39:31.66732 nt 451663.41 4402368.2 39.7691960 2.4356532 34.7615 120 0 51 | 2013-11-17 03:39:31.667798 nt 453536.35 4398534.5 39.7347600 2.4577904 -208.7540 328 0 52 | 2013-11-17 03:39:31.687889 nt 451710.72 4401079.7 39.7575900 2.4363003 -46.7680 40 0 53 | 2013-11-17 03:39:31.707671 nt 452955.44 4399376.3 39.7423130 2.4509516 -23.6615 56 0 54 | 2013-11-17 03:39:31.721628 nt 452108.49 4404014.6 39.7840540 2.4407294 -14.6520 64 0 55 | 2013-11-17 03:39:32.583286 nt 453970.66 4404717.0 39.7904850 2.4624255 -14.3930 44 0 56 | 2013-11-17 03:44:16.369706 nt 452856.74 4407661.2 39.8169500 2.4492050 45.4175 548 0 57 | 2013-11-17 03:45:54.876578 nt 493242.47 4559457.1 41.1857220 2.9194274 -14.2080 164 0 58 | 2013-11-17 03:48:02.718452 nt 928010.61 4308160.6 38.8175740 7.9286885 -63.6215 280 0 59 | 2013-11-17 03:52:53.45962 nt 896806.23 4406861.5 39.7186620 7.6285530 69.5785 156 0 60 | 2013-11-17 04:03:43.361035 nt 488042.38 4574396.8 41.3202320 2.8571320 12.9685 408 0 61 | 2013-11-17 04:03:43.369632 nt 492132.73 4571591.5 41.2950130 2.9060392 9.2130 132 0 62 | 2013-11-17 04:03:43.690183 nt 475487.65 4570599.0 41.2857400 2.7072842 -7.1780 52 0 63 | 2013-11-17 04:08:07.239035 nt 479443.17 4572686.9 41.3046570 2.7544484 5.5315 116 0 64 | 2013-11-17 04:08:07.262923 nt 473586.99 4577846.9 41.3509640 2.6842728 4.2550 28 0 65 | 2013-11-17 04:11:01.542814 nt 472312.61 4578936.2 41.3607330 2.6689901 10.4710 196 0 66 | 2013-11-17 04:15:23.532787 nt 463719.55 4573281.7 41.3094600 2.5665980 -15.9655 108 0 67 | 2013-11-17 04:13:21.783213 nt 480560.14 4583114.6 41.3986100 2.7674565 7.2520 488 0 68 | 2013-11-17 04:22:04.627643 nt 484247.92 4583803.5 41.4048960 2.8115523 -4.9765 96 0 69 | 2013-11-17 04:26:40.709601 nt 430575.16 4577668.4 41.3467980 2.1701882 -13.3015 104 0 70 | 2013-11-17 04:32:32.393353 nt 497251.06 4571200.3 41.2915230 2.9671705 -10.2675 376 0 71 | 2013-11-17 04:32:38.553955 nt 430602.03 4571708.3 41.2931200 2.1711898 24.5495 300 0 72 | 2013-11-17 04:34:00.903456 nt 495626.30 4572327.1 41.3016660 2.9477584 5.3095 40 0 73 | 2013-11-17 04:40:19.559655 nt 387999.19 4565234.3 41.2300340 1.6636866 5.4575 44 0 74 | 2013-11-17 04:40:19.580337 nt 390381.75 4566622.3 41.2428600 1.6918572 197.7470 316 0 75 | 2013-11-17 04:40:19.703354 nt 381482.73 4569839.3 41.2705730 1.5850644 -6.6785 68 0 76 | 2013-11-17 04:40:19.748797 nt 381475.84 4569411.5 41.2667200 1.5850654 -10.6005 52 0 77 | 2013-11-17 04:42:53.128261 nt 415944.00 4578670.0 41.3544240 1.9951917 14.5965 244 0 78 | 2013-11-17 04:46:16.250774 nt 364293.18 4589243.5 41.4425800 1.3755792 127.5580 584 0 79 | 2013-11-17 04:46:16.342379 nt 353764.90 4588052.4 41.4300080 1.2498975 6.8635 44 0 80 | 2013-11-17 04:46:28.943689 nt 426619.77 4573148.6 41.3057400 2.1234617 43.0125 504 0 81 | 2013-11-17 04:47:44.392615 nt 424880.03 4576868.2 41.3390800 2.1022230 11.9140 176 0 82 | 2013-11-17 04:49:00.592391 nt 426583.04 4574556.5 41.3184170 2.1228530 51.2820 240 0 83 | 2013-11-17 04:49:00.895782 nt 426573.19 4574293.2 41.3160440 2.1227672 -17.9080 44 0 84 | 2013-11-17 04:49:43.364113 nt 425754.90 4574213.8 41.3152540 2.1130018 55.4630 228 0 85 | 2013-11-17 04:49:43.602739 nt 417853.49 4585890.2 41.4196470 2.0170357 -77.3855 196 0 86 | 2013-11-17 04:49:43.794151 nt 418695.62 4583457.5 41.3978230 2.0274380 -11.9695 72 0 87 | 2013-11-17 04:49:43.802062 nt 419676.99 4583438.1 41.3977470 2.0391781 -14.1525 40 0 88 | 2013-11-17 04:51:15.778578 nt 422473.65 4574139.9 41.3142800 2.0738153 15.1700 284 0 89 | 2013-11-17 04:57:03.770048 nt 383050.72 4566194.9 41.2379840 1.6044774 7.1595 140 0 90 | 2013-11-17 04:57:03.770586 nt 383292.08 4562344.5 41.2033460 1.6080922 10.0825 400 0 91 | 2013-11-17 04:53:51.904848 nt 372336.46 4573355.7 41.3008420 1.4751690 15.0220 100 0 92 | 2013-11-17 04:53:51.966241 nt 383782.10 4565596.4 41.2327000 1.6133163 -13.8195 44 0 93 | 2013-11-17 04:53:51.992806 nt 383904.64 4565305.7 41.2301000 1.6148332 -23.5505 44 0 94 | 2013-11-17 05:01:02.025738 nt 418383.26 4583542.8 41.3985600 2.0236905 89.7620 500 0 95 | 2013-11-17 05:04:05.63773 nt 415592.66 4584438.7 41.4063400 1.9901891 13.6715 160 0 96 | 2013-11-17 05:05:09.273515 nt 419013.23 4577115.6 41.3407400 2.0320837 9.3610 152 0 97 | 2013-11-17 05:08:37.352963 nt 409566.06 4581735.4 41.3813400 1.9185051 -5.9570 128 0 98 | 2013-11-17 05:08:37.353848 nt 403246.43 4579566.5 41.3610730 1.8432893 9.9900 376 0 99 | 2013-11-17 05:08:37.384211 nt 409796.62 4588451.9 41.4418530 1.9202607 -8.4175 284 0 100 | 2013-11-17 05:08:37.430504 nt 412741.75 4582020.9 41.3842620 1.9564357 60.0510 152 0 101 | 2013-11-17 05:10:52.168201 nt 579419.17 4534753.4 40.9593600 3.9436965 -106.5600 171 0 102 | 2013-11-17 05:13:30.339131 nt 470218.55 4595779.4 41.5123670 2.6431255 -4.6620 168 0 103 | 2013-11-17 05:13:30.472253 nt 473878.98 4594135.8 41.4976900 2.6870594 -8.1955 44 0 104 | 2013-11-17 05:15:49.505375 nt 515996.39 4584017.6 41.4068200 3.1913762 14.2635 180 0 105 | 2013-11-17 05:18:59.891063 nt 411727.33 4581702.4 41.3812830 1.9443521 15.7065 76 0 106 | 2013-11-17 05:18:59.892586 nt 411805.07 4581651.5 41.3808330 1.9452891 -84.1380 156 0 107 | 2013-11-17 05:20:48.005811 nt 496804.67 4588524.0 41.4475630 2.9617481 -236.8930 448 0 108 | 2013-11-17 05:20:48.220082 nt 498324.61 4589445.1 41.4558640 2.9799410 -6.7895 36 0 109 | 2013-11-17 05:22:44.605348 nt 497709.61 4589805.6 41.4591100 2.9725764 -6.2345 40 0 110 | 2013-11-17 05:23:16.018988 nt 408410.50 4583300.7 41.3953060 1.9044516 -23.3470 168 0 111 | 2013-11-17 05:23:16.022834 nt 408477.36 4583414.7 41.3963400 1.9052339 -8.2510 280 0 112 | 2013-11-17 05:25:28.5817 nt 497077.69 4591714.3 41.4763000 2.9650010 -156.6210 180 0 113 | 2013-11-17 05:25:28.602343 nt 496566.03 4591465.9 41.4740600 2.9588745 8.8060 132 0 114 | 2013-11-17 05:35:10.176312 nt 495602.31 4594620.7 41.5024720 2.9473100 6.0495 88 0 115 | 2013-11-17 05:35:10.434487 nt 489778.22 4599609.1 41.5473500 2.8774452 -10.5820 48 0 116 | 2013-11-17 05:35:10.510501 nt 492348.13 4599293.6 41.5445370 2.9082613 -9.6755 48 0 117 | 2013-11-17 05:35:10.528219 nt 489402.03 4599827.3 41.5493100 2.8729310 -10.9890 52 0 118 | 2013-11-17 05:35:10.623148 nt 488699.51 4599444.5 41.5458530 2.8645150 -7.2520 40 0 119 | 2013-11-17 05:38:34.025647 nt 503673.60 4594037.6 41.4972230 3.0440110 16.6500 300 0 120 | 2013-11-17 05:38:34.027527 nt 474512.67 4592518.9 41.4831470 2.6947196 10.7485 168 0 121 | 2013-11-17 05:41:20.043266 nt 498797.10 4597895.6 41.5319800 2.9855812 17.8155 80 0 122 | 2013-11-17 05:41:20.043951 nt 489835.11 4597638.6 41.5296020 2.8781605 -173.9920 232 0 123 | 2013-11-17 05:46:16.570356 nt 490587.08 4598157.3 41.5342830 2.8871658 9.3795 48 0 124 | 2013-11-17 05:46:16.830713 nt 485011.33 4605188.7 41.5975300 2.8201530 -7.8810 60 0 125 | 2013-11-17 06:01:08.825965 nt 527753.90 4609282.9 41.6340640 3.3332030 110.1860 352 0 126 | 2013-11-17 06:07:13.60184 nt 525839.54 4607239.4 41.6157230 3.3101320 -10.8040 56 0 127 | 2013-11-17 06:10:12.217694 nt 526754.94 4614860.4 41.6843340 3.3214598 8.0660 348 0 128 | 2013-11-17 06:16:12.563683 nt 496992.92 4612378.1 41.6624200 2.9638822 -11.1000 348 0 129 | 2013-11-17 06:19:09.917977 nt 533937.86 4613634.6 41.6730200 3.4076908 -13.4865 76 0 130 | 2013-11-17 06:20:30.888856 nt 550630.70 4620065.5 41.7300530 3.6087565 13.0610 180 0 131 | 2013-11-17 06:21:56.059416 nt 518519.12 4619194.7 41.7236060 3.2226422 -14.6335 68 0 132 | 2013-11-17 06:21:56.129742 nt 522761.02 4619056.1 41.7222480 3.2736337 -8.7690 44 0 133 | 2013-11-17 06:22:47.204084 nt 522265.54 4619721.6 41.7282560 3.2677020 24.1795 140 0 134 | 2013-11-17 06:23:33.688538 nt 555029.09 4618763.0 41.7180300 3.6615167 18.7775 176 0 135 | 2013-11-17 06:24:18.701393 nt 522444.21 4621451.1 41.7438280 3.2699153 -14.4300 56 0 136 | 2013-11-17 06:24:19.099885 nt 531245.15 4606526.0 41.6091040 3.3749730 -9.8235 44 0 137 | 2013-11-17 06:26:07.779829 nt 523089.33 4622894.9 41.7568130 3.2777295 -13.0980 80 0 138 | 2013-11-17 06:26:07.882591 nt 524623.43 4623054.0 41.7582000 3.2961888 -7.8070 52 0 139 | 2013-11-17 06:29:00.938061 nt 512751.15 4626606.3 41.7904740 3.1534572 14.3560 363 0 140 | 2013-11-17 06:29:00.962667 nt 521367.31 4621168.2 41.7413100 3.2569544 11.6920 268 0 141 | 2013-11-17 06:29:01.457833 nt 521032.56 4619219.0 41.7237630 3.2528600 -14.6150 80 0 142 | 2013-11-17 06:33:11.386328 nt 517618.78 4624730.6 41.7734870 3.2119820 -107.7260 180 0 143 | 2013-11-17 06:34:01.368648 nt 526947.78 4626104.9 41.7856030 3.3242857 8.7690 68 0 144 | 2013-11-17 06:34:01.371424 nt 515458.95 4623806.9 41.7652130 3.1859720 8.8615 228 0 145 | 2013-11-17 06:35:44.898602 nt 504886.37 4626302.7 41.7878270 3.0588040 8.6765 228 0 146 | 2013-11-17 06:35:44.906485 nt 519214.53 4624506.0 41.7714270 3.2311740 7.0670 180 0 147 | 2013-11-17 06:36:30.851368 nt 511222.06 4625058.2 41.7765540 3.1350257 -9.2315 52 0 148 | 2013-11-17 06:37:36.476472 nt 517397.08 4628331.0 41.8059200 3.2094202 13.7825 180 0 149 | 2013-11-17 06:40:02.201121 nt 128438.34 4061731.3 36.6281240 -1.1545805� 200.5590 328 0 150 | 2013-11-17 06:40:26.325512 nt 525479.52 4617523.6 41.7083630 3.3062496 -12.5430 48 0 151 | 2013-11-17 06:40:26.50675 nt 520499.65 4616636.4 41.7005160 3.2463644 -11.0815 44 0 152 | 2013-11-17 06:41:24.78906 nt 511953.04 4630518.0 41.8257180 3.1439310 -109.6130 200 0 153 | 2013-11-17 06:42:12.766072 nt 510535.52 4629140.3 41.8133300 3.1268377 -9.8235 92 0 154 | 2013-11-17 06:43:30.535196 nt 506792.94 4629232.2 41.8141980 3.0817816 -10.6560 252 0 155 | 2013-11-17 06:43:30.578199 nt 510836.45 4628969.8 41.8117900 3.1304574 -9.1760 64 0 156 | 2013-11-17 06:48:30.323151 nt 503312.02 4631310.1 41.8329350 3.0398858 -204.3330 212 0 157 | 2013-11-17 06:49:48.149475 nt 517084.19 4619279.3 41.7244000 3.2053936 8.1400 72 0 158 | 2013-11-17 06:52:36.515696 nt 524478.92 4622851.6 41.7563820 3.2944422 -117.6600 116 0 159 | 2013-11-17 06:52:36.535776 nt 527449.71 4625269.3 41.7780600 3.3302872 -16.0025 316 0 160 | 2013-11-17 06:52:36.575347 nt 531047.27 4623071.5 41.7581330 3.3734589 -15.8730 60 0 161 | 2013-11-17 06:52:36.610598 nt 530196.91 4622820.0 41.7559000 3.3632176 -12.1730 36 0 162 | 2013-11-17 06:52:36.662988 nt 525558.36 4622308.9 41.7514600 3.3074026 -10.5265 40 0 163 | 2013-11-17 06:52:36.797775 nt 527270.25 4622905.4 41.7567750 3.3280194 -11.8400 44 0 164 | 2013-11-17 06:54:59.326638 nt 524053.44 4624010.7 41.7668340 3.2893713 -9.9345 40 0 165 | 2013-11-17 06:54:59.345966 nt 527234.45 4624286.4 41.7692150 3.3276520 -13.0980 44 0 166 | 2013-11-17 06:54:59.357888 nt 526939.74 4624305.2 41.7693940 3.3241074 -9.4905 180 0 167 | 2013-11-17 06:58:20.588656 nt 503781.06 4628721.2 41.8096160 3.0455177 -11.4700 56 0 168 | 2013-11-17 07:04:43.664877 nt 503393.88 4638222.2 41.8951900 3.0409112 8.0660 188 0 169 | 2013-11-17 07:05:00.912299 nt 347896.61 4549015.8 41.0774700 1.1894337 -70.3925 396 0 170 | 2013-11-17 07:08:37.92535 nt 503909.29 4644148.5 41.9485630 3.0471635 14.4485 328 0 171 | 2013-11-17 07:09:26.238521 nt 348983.41 4547468.3 41.0637400 1.2027439 6.1975 116 0 172 | 2013-11-17 07:09:26.238994 nt 347552.69 4544318.0 41.0351100 1.1865042 12.2100 176 0 173 | 2013-11-17 07:13:23.98432 nt 494880.05 4650306.8 42.0040200 2.9381770 -8.3435 84 0 174 | 2013-11-17 07:13:24.097215 nt 496878.10 4642873.2 41.9370800 2.9623427 -9.8235 264 0 175 | 2013-11-17 07:15:49.295289 nt 345225.94 4550816.0 41.0931740 1.1572060 8.2695 164 0 176 | 2013-11-17 07:15:49.296835 nt 345260.55 4553261.3 41.1151960 1.1570023 8.9355 572 0 177 | 2013-11-17 07:18:41.195004 nt 346194.40 4543621.9 41.0285870 1.1705275 10.2490 120 0 178 | 2013-11-17 07:32:08.639268 nt 490624.08 4651776.8 42.0172200 2.8867630 -10.4525 56 0 179 | 2013-11-17 07:32:08.688079 nt 493641.49 4653088.5 42.0290640 2.9231913 -10.7485 68 0 180 | 2013-11-17 07:32:08.72437 nt 491879.97 4652506.9 42.0238100 2.9019208 -9.2685 76 0 181 | 2013-11-17 07:52:18.415438 nt 505701.37 4638813.3 41.9005000 3.0687323 -8.0845 52 0 182 | 2013-11-17 07:55:21.624944 nt 471948.11 4655681.8 42.0519450 2.6610210 -6.5675 32 0 183 | 2013-11-17 07:55:21.647278 nt 471693.46 4656010.9 42.0549000 2.6579280 -10.9335 40 0 184 | 2013-11-17 07:55:21.657806 nt 472532.24 4656651.6 42.0607000 2.6680340 -11.1925 40 0 185 | 2013-11-17 07:56:39.423389 nt 507247.20 4642643.0 41.9349800 3.0874150 -15.2995 64 0 186 | 2013-11-17 07:56:39.459534 nt 525717.04 4651050.5 42.0103150 3.3105620 8.0660 116 0 187 | 2013-11-17 07:56:42.066877 nt 591516.62 4547448.5 41.0724300 4.0893030 21.9410 116 0 188 | 2013-11-17 08:16:07.143347 nt 523593.27 4644260.7 41.9492300 3.2846430 11.3220 268 0 189 | 2013-11-17 08:19:19.928979 nt 468103.63 4661343.4 42.1027870 2.6142566 -11.5255 152 0 190 | 2013-11-17 08:19:19.987699 nt 476013.03 4670596.2 42.1864000 2.7095280 -11.5810 64 0 191 | 2013-11-17 08:24:31.103804 nt 502129.15 4655429.4 42.0501700 3.0257280 -104.5440 268 0 192 | 2013-11-17 08:26:23.132532 nt 477488.38 4676433.0 42.2390100 2.7271676 -11.7660 60 0 193 | 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