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jupyter-notebooks/Folium-Basic.ipynb

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import folium\n",
"import matplotlib\n",
"import numpy as np\n",
"import branca\n",
"from matplotlib.pyplot import imread\n",
"from matplotlib.colors import Normalize\n",
"from matplotlib.colors import ListedColormap\n",
"from folium import raster_layers"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"image = '/notebooks/resources/gpm/gpm_1d.20190531.tif'"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10.0 -180.0\n",
"-60.0 -180.0\n",
"-60.0 -30.0\n",
"10.0 -30.0\n",
"ext = [[10.0, -180.0], [-60.0, -180.0], [-60.0, -30.0], [10.0, -30.0]]\n",
"geo_ext = [[10.0, -180.0], [-60.0, -180.0], [-60.0, -30.0], [10.0, -30.0]]\n"
]
}
],
"source": [
"from osgeo import gdal,ogr,osr\n",
"\n",
"def GetExtent(gt,cols,rows):\n",
" ''' Return list of corner coordinates from a geotransform\n",
"\n",
" @type gt: C{tuple/list}\n",
" @param gt: geotransform\n",
" @type cols: C{int}\n",
" @param cols: number of columns in the dataset\n",
" @type rows: C{int}\n",
" @param rows: number of rows in the dataset\n",
" @rtype: C{[float,...,float]}\n",
" @return: coordinates of each corner\n",
" '''\n",
" ext=[]\n",
" xarr=[0,cols]\n",
" yarr=[0,rows]\n",
"\n",
" for px in xarr:\n",
" for py in yarr:\n",
" x=gt[0]+(px*gt[1])+(py*gt[2])\n",
" y=gt[3]+(px*gt[4])+(py*gt[5])\n",
" ext.append([y,x])\n",
" print (y,x)\n",
" yarr.reverse()\n",
" return ext\n",
"\n",
"def ReprojectCoords(coords,src_srs,tgt_srs):\n",
" ''' Reproject a list of x,y coordinates.\n",
"\n",
" @type geom: C{tuple/list}\n",
" @param geom: List of [[x,y],...[x,y]] coordinates\n",
" @type src_srs: C{osr.SpatialReference}\n",
" @param src_srs: OSR SpatialReference object\n",
" @type tgt_srs: C{osr.SpatialReference}\n",
" @param tgt_srs: OSR SpatialReference object\n",
" @rtype: C{tuple/list}\n",
" @return: List of transformed [[x,y],...[x,y]] coordinates\n",
" '''\n",
" trans_coords=[]\n",
" transform = osr.CoordinateTransformation( src_srs, tgt_srs)\n",
" for x,y in coords:\n",
" x,y,z = transform.TransformPoint(x,y)\n",
" trans_coords.append([x,y])\n",
" return trans_coords\n",
"\n",
"raster=image\n",
"ds=gdal.Open(raster)\n",
"\n",
"gt=ds.GetGeoTransform()\n",
"cols = ds.RasterXSize\n",
"rows = ds.RasterYSize\n",
"\n",
"ext=GetExtent(gt,cols,rows)\n",
"print(\"ext = \" + str(ext))\n",
"\n",
"src_srs=osr.SpatialReference()\n",
"src_srs.ImportFromWkt(ds.GetProjection())\n",
"# tgt_srs=osr.SpatialReference()\n",
"# tgt_srs.ImportFromEPSG(3857)\n",
"tgt_srs = src_srs.CloneGeogCS()\n",
"\n",
"geo_ext=ReprojectCoords(ext,src_srs,tgt_srs)\n",
"print(\"geo_ext = \" + str(geo_ext))"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# # Choose colormap\n",
"# cmap = matplotlib.cm.cool\n",
"\n",
"# # Get the colormap colors\n",
"# my_cmap = cmap(np.arange(cmap.N))\n",
"\n",
"\n",
"# # Set alpha\n",
"# my_cmap[:,-1] = np.linspace(0, 1, cmap.N)\n",
"\n",
"# # Create new colormap\n",
"# my_cmap = ListedColormap(my_cmap)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# # Choose colormap\n",
"# cmap = matplotlib.cm.cool\n",
"\n",
"# min_x = 0\n",
"# max_x = 256\n",
"\n",
"# def my_cmap(x):\n",
"# x = np.clip((x - min_x)/(max_x - min_x), 0, 1)\n",
"# c = cmap(x)\n",
"# # multiplying alpha by 10 to make a sharper transition to the colors in the lower range\n",
"# return c[:3] + (np.clip(x*10, 0, 1),) "
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"colormap = branca.colormap.StepColormap(\n",
" ['#64abb0','#9dd3a7', '#c7e9ad', '#edf8b9', '#ffedaa', '#fec980', '#f99e59', '#e85b3a', '#d7191c'],\n",
" vmin=0, vmax=10000,\n",
" index=[0, 25, 50, 100, 250, 500, 1000, 2500, 5000, 10000],\n",
" caption='step'\n",
")\n",
"\n",
"my_cmap = colormap\n",
"\n",
"# # Get the colormap colors\n",
"# my_cmap = colormap(np.arange(colormap.N))\n",
"\n",
"\n",
"# # Set alpha\n",
"# my_cmap[:,-1] = np.linspace(0, 1, colormap.N)\n",
"\n",
"# # Create new colormap\n",
"# my_cmap = ListedColormap(my_cmap)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"scrolled": false
},
"outputs": [
{
"ename": "IndexError",
"evalue": "tuple index out of range",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-11-1cdfaf3b95d4>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[0;34m,\u001b[0m \u001b[0mbounds\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mext\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mext\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[0;34m,\u001b[0m \u001b[0mmercator_project\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 17\u001b[0;31m \u001b[0;34m,\u001b[0m \u001b[0mcolormap\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmy_cmap\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 18\u001b[0m )\n\u001b[1;32m 19\u001b[0m )\n",
"\u001b[0;32m/usr/local/lib/python3.5/dist-packages/folium/raster_layers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, image, bounds, origin, colormap, mercator_project, pixelated, name, overlay, control, show, **kwargs)\u001b[0m\n\u001b[1;32m 274\u001b[0m origin=origin)\n\u001b[1;32m 275\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 276\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0murl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mimage_to_url\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mimage\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morigin\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morigin\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolormap\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcolormap\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 277\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 278\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbounds\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mjson\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloads\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjson\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdumps\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbounds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.5/dist-packages/folium/utilities.py\u001b[0m in \u001b[0;36mimage_to_url\u001b[0;34m(image, colormap, origin)\u001b[0m\n\u001b[1;32m 109\u001b[0m \u001b[0murl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'data:image/{};base64,{}'\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfileformat\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mb64encoded\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 110\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0;34m'ndarray'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mimage\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 111\u001b[0;31m \u001b[0mimg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mwrite_png\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mimage\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morigin\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morigin\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolormap\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcolormap\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 112\u001b[0m \u001b[0mb64encoded\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbase64\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mb64encode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mimg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdecode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'utf-8'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 113\u001b[0m \u001b[0murl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'data:image/png;base64,{}'\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mb64encoded\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.5/dist-packages/folium/utilities.py\u001b[0m in \u001b[0;36mwrite_png\u001b[0;34m(data, origin, colormap)\u001b[0m\n\u001b[1;32m 172\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mnblayers\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 173\u001b[0m \u001b[0marr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcolormap\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0marr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 174\u001b[0;31m \u001b[0mnblayers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0marr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 175\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mnblayers\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m4\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 176\u001b[0m raise ValueError('colormap must provide colors of r'\n",
"\u001b[0;31mIndexError\u001b[0m: tuple index out of range"
]
}
],
"source": [
"m = folium.Map(\n",
" location = [-22, -114]\n",
" , zoom_start = 2\n",
" , control_scale = True \n",
" , tiles = 'Stamen Terrain'\n",
")\n",
"\n",
"data = matplotlib.pyplot.imread(image)\n",
"\n",
"# Image bounds on the map in the form\n",
"# [[lat_min, lon_min], [lat_max, lon_max]]\n",
"m.add_child(raster_layers.ImageOverlay(\n",
" data\n",
" , opacity = 0.7\n",
" , bounds = [ext[2], ext[0]]\n",
" , mercator_project = True\n",
" , colormap = my_cmap\n",
")\n",
" )\n",
"\n",
"m"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}