1 | #!/usr/bin/env python
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2 | #
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3 | # Hack to show image generation realtime, sample tile server implementation.
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4 | #
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5 | # Rick van der Zwet <info@rickvanderzwet.nl>
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6 | from django.core.management import setup_environ
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7 | from django.db.models import Max
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8 | from django.http import HttpResponse
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9 | from gheat.models import *
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10 | import logging
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11 | import pygame
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12 | import sys
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13 | import tempfile
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14 |
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15 | # Rending with PIL and computation with numpy has proven to be to slow to be
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16 | # usable, but is still in here for refence purposes.
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17 | try:
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18 | from PIL import Image
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19 | import ImageDraw
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20 | import numpy as np
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21 | except ImportError:
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22 | pass
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23 |
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24 | logging.basicConfig(level=logging.WARNING)
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25 | log = logging.getLogger('tile')
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26 |
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27 | class PyGamePicture():
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28 | """ Basic PyGame class, allowing simple image manipulations """
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29 | def __init__(self, method, size):
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30 | self.surf = pygame.Surface(size,flags=pygame.SRCALPHA)
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31 |
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32 | def center_crop(self,size):
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33 | """ Resize to make centered rectange from image """
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34 | new_surf = pygame.Surface(size, flags=pygame.SRCALPHA)
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35 | curr_size = self.surf.get_size()
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36 | new_surf.blit(self.surf,(0,0),
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37 | ((curr_size[0] - size[0]) / 2, (curr_size[1] - size[1]) / 2, size[0], size[1]))
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38 | self.surf = new_surf
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39 |
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40 | def write(self, fh,format='png'):
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41 | # XXX: How to get a PNG stream directly to the output
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42 | f = tempfile.NamedTemporaryFile(suffix=format)
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43 | pygame.image.save(self.surf,f.name)
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44 | f.seek(0)
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45 | fh.write(f.read())
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46 |
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47 |
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48 | def add_circle(self, center, radius, colour=(255,0,0), transparancy=0):
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49 | """
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50 | Hack to add lineair gradient circles and merge with the parent. The
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51 | transparancy can be configured to make the circles to fade out in the
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52 | beginning
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53 | """
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54 | # Make calculations and ranges a whole bunch more easy
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55 | radius = int(math.ceil(radius))
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56 |
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57 | new_surf = pygame.Surface(self.surf.get_size(),flags=pygame.SRCALPHA)
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58 | alpha_per_radius = float(2.55 * (100 - transparancy)) / radius
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59 | for r in range(radius,1,-1):
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60 | alpha = (radius - r) * alpha_per_radius
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61 | pygame.draw.circle(new_surf,colour + (alpha,),center,r,0)
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62 | self.surf.blit(new_surf,(0,0),special_flags=pygame.BLEND_RGBA_MAX)
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63 |
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64 |
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65 | class PILPicture():
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66 | """ Basic PIL class, allowing simple image manipulations """
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67 | im = None
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68 | def __init__(self, method, size):
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69 | self.im = Image.new(method, size)
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70 | self.data = np.array(self.im)
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71 |
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72 | def write(self,fh,format='png'):
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73 | self.im.save(fh,format)
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74 |
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75 | def make_circle(self,draw, center, radius,colour=(0,255,0)):
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76 | """ Cicle gradient is created by creating smaller and smaller cicles """
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77 | (center_x, center_y) = center
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78 | for i in range(0,radius):
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79 | draw.ellipse(
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80 | (center_x - radius + i,
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81 | center_y - radius + i,
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82 | center_x + radius - i,
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83 | center_y + radius - i
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84 | ),
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85 | colour +(255 * i/(radius * 2),)
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86 | )
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87 |
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88 | def add_circle(self, center, radius, colour):
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89 | """ Adding a new cicle is a matter of creating a new one in a empty layer
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90 | and merging it with the current one
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91 |
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92 | XXX: Very heavy code, should actually only work on the data arrays, instead
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93 | of doing all the magic with high-level images """
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94 |
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95 | im_new = Image.new("RGBA", self.im.size)
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96 | draw = ImageDraw.Draw(im_new)
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97 | self.make_circle(draw, center, radius, colour)
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98 |
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99 | data2 = np.array(im_new)
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100 |
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101 | # Add channels to make new images
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102 | self.data = self.data + data2
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103 | self.im = Image.fromarray(self.data)
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104 |
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105 |
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106 |
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107 | class LatLonDeg():
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108 | """ Helper class for coordinate conversions """
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109 | def __init__(self,lat_deg, lon_deg):
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110 | self.lat = lat_deg
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111 | self.lon = lon_deg
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112 | def __str__(self):
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113 | return "%.5f,%.5f" % (self.lat, self.lon)
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114 |
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115 | def deg_per_pixel(self,other,pixel_max):
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116 | return(LatLonDeg(abs(self.lat - other.lat) / pixel_max, abs(self.lon - other.lon) / pixel_max))
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117 |
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118 |
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119 |
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120 | # Convertions of tile XYZ to WSG coordinates stolen from:
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121 | # http://wiki.openstreetmap.org/wiki/Slippy_map_tilenames
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122 | # <stolen>
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123 | import math
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124 | def deg2num(lat_deg, lon_deg, zoom):
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125 | lat_rad = math.radians(lat_deg)
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126 | n = 2.0 ** zoom
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127 | xtile = int((lon_deg + 180.0) / 360.0 * n)
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128 | ytile = int((1.0 - math.log(math.tan(lat_rad) + (1 / math.cos(lat_rad))) / math.pi) / 2.0 * n)
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129 | return(xtile, ytile)
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130 |
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131 | def num2deg(xtile, ytile, zoom):
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132 | n = 2.0 ** zoom
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133 | lon_deg = xtile / n * 360.0 - 180.0
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134 | lat_rad = math.atan(math.sinh(math.pi * (1 - 2 * ytile / n)))
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135 | lat_deg = math.degrees(lat_rad)
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136 | return(LatLonDeg(lat_deg,lon_deg))
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137 | # </stolen>
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138 |
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139 |
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140 | def boundbox_deg(x,y,z):
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141 | """ Calculate the boundingbox for a image """
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142 | return (num2deg(x,y,z), num2deg(x+1,y+1,z))
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143 |
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144 |
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145 |
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146 | def make_tile(x,y,z):
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147 | """
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148 | Crude attempt to generate tiles, by placing a gradient circle on a
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149 | coordinate point. Generate a larger tile and make sure to plot related
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150 | points first and then crop it to the required size (250x250).
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151 |
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152 | Many stuff NOT implemented yet, like:
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153 | - Caching Images.
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154 | - Conditional Filtering of Meting to allow display of sub-results.
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155 | - Defining a extra level of transparency if you like to layer multiple tiles
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156 | on top of each-other.
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157 | - Color variation, allow the user to dynamically choose a the colour the
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158 | points to be.
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159 | - Advanced data plotting, like trying to guess the remainder points.
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160 | """
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161 |
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162 | SIZE = 250
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163 |
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164 | nw_deg,se_deg = boundbox_deg(x,y,z)
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165 |
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166 |
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167 | Picture = PyGamePicture
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168 | resolution_deg = nw_deg.deg_per_pixel(se_deg, SIZE)
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169 | # Converting LatLon to Meters is discussed here:
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170 | # http://stackoverflow.com/questions/3024404/transform-longitude-latitude-into-meters
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171 | tile_height = float(40008000) / (2 ** z)
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172 | meters_per_pixel = float(tile_height) / SIZE
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173 |
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174 | # Worst case scenario could a circle with 100% 'outside' our 250x250 range
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175 | # also add data to the picture as circles are used
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176 | border_pixels = 100 / meters_per_pixel / 2
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177 |
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178 | im = Picture("RGBA", (SIZE + border_pixels * 2,) * 2)
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179 |
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180 | nw_deg.lat += resolution_deg.lat * border_pixels
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181 | nw_deg.lon -= resolution_deg.lon * border_pixels
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182 | se_deg.lat -= resolution_deg.lat * border_pixels
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183 | se_deg.lon += resolution_deg.lon * border_pixels
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184 |
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185 | lat_min = 999
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186 | lon_min = 999
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187 | lat_max = 0
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188 | lon_max = 0
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189 |
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190 | # TODO: This is currently hard-coded to display _all_ metingen
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191 | metingen = Meting.objects.select_related().filter(
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192 | latitude__lte=nw_deg.lat,latitude__gte=se_deg.lat,
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193 | longitude__lte=se_deg.lon,longitude__gte=nw_deg.lon)
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194 |
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195 | # XXX: Signal is not normalized in the database making it unknown when a
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196 | # signal is said to be 100% or when it is actually less, currently seems to
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197 | # copy the raw reported values
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198 | MAX_SIGNAL = 50
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199 | # XXX: The radius relates to the zoom-level we are in, and should represent
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200 | # a fixed distance, given the scale. Assume signal/distance to be lineair
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201 | # such that signal 100% = 100m and 1% = 1m.
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202 | #
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203 | # XXX: The relation is not lineair but from a more logeritmic scape, as we
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204 | # are dealing with radio signals
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205 | #
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206 | MAX_RANGE = 100
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207 |
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208 | def dif(x,y):
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209 | """ Return difference between two points """
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210 | return max(x,y) - min(x,y)
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211 |
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212 | for meting in metingen:
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213 | lat_min = min(lat_min, meting.latitude)
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214 | lat_max = max(lat_max, meting.latitude)
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215 | lon_min = min(lon_min, meting.longitude)
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216 | lon_max = max(lon_max, meting.longitude)
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217 | xcoord = dif(nw_deg.lon,meting.longitude) / (resolution_deg.lon)
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218 | ycoord = dif(nw_deg.lat,meting.latitude) / (resolution_deg.lat)
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219 | log.info(meting.accespoint.ssid, meting.latitude, meting.longitude, xcoord, ycoord)
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220 |
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221 | # TODO: Please note that this 'logic' technically does apply to WiFi signals,
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222 | # if you are plotting from the 'source'. When plotting 'measurement' data you
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223 | # get different patterns and properly need to start looking at techniques like:
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224 | # Multilateration,Triangulation or Trilateration to recieve 'source' points.
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225 | #
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226 | # Also you can treat all points as seperate and use techniques like
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227 | # Multivariate interpolation to make the graphs. A nice overview at:
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228 | # http://en.wikipedia.org/wiki/Multivariate_interpolation
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229 | #
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230 | # One very intersting one to look at will be Inverse distance weighting
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231 | # with examples like this:
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232 | # http://stackoverflow.com/questions/3104781/inverse-distance-weighted-idw-interpolation-with-python
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233 | signal_normalized = MAX_RANGE - (MAX_SIGNAL - meting.signaal)
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234 | im.add_circle((xcoord,ycoord),float(signal_normalized) / meters_per_pixel,(255,0,0), MAX_SIGNAL - meting.signaal)
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235 |
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236 | log.info("BoundingBox NW: %s" % nw_deg)
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237 | log.info("BoundingBox SE: %s" % se_deg)
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238 | log.info("")
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239 | log.info("MetingBox NW: %.5f,%.5f" % (lat_max, lon_min))
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240 | log.info("MetingBox SE: %.5f,%.5f" % (lat_min, lon_max))
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241 | log.info("")
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242 | log.info("Metingen Count: %s" % metingen.count())
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243 |
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244 | im.center_crop((SIZE,SIZE))
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245 | return im
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246 |
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247 |
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248 | # Create your views here.
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249 | def serve_tile(request,zoom,x,y):
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250 | im = make_tile(int(x),int(y),int(zoom))
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251 | response = HttpResponse(mimetype="image/png")
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252 | im.write(response,'png')
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253 | return response
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