1 | def latinterv (area): |
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2 | if area == "Europe": |
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3 | wlat = [20.,80.] |
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4 | wlon = [-50.,50.] |
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5 | elif area == "Central_America": |
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6 | wlat = [-10.,40.] |
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7 | wlon = [230.,300.] |
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8 | elif area == "Africa": |
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9 | wlat = [-20.,50.] |
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10 | wlon = [-50.,50.] |
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11 | elif area == "Whole": |
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12 | wlat = [-90.,90.] |
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13 | wlon = [-180.,180.] |
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14 | elif area == "Southern_Hemisphere": |
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15 | wlat = [-90.,60.] |
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16 | wlon = [-180.,180.] |
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17 | elif area == "Northern_Hemisphere": |
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18 | wlat = [-60.,90.] |
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19 | wlon = [-180.,180.] |
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20 | elif area == "Tharsis": |
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21 | wlat = [-30.,60.] |
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22 | wlon = [-170.,-10.] |
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23 | elif area == "Whole_No_High": |
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24 | wlat = [-60.,60.] |
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25 | wlon = [-180.,180.] |
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26 | elif area == "Chryse": |
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27 | wlat = [-60.,60.] |
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28 | wlon = [-60.,60.] |
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29 | elif area == "North_Pole": |
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30 | wlat = [60.,90.] |
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31 | wlon = [-180.,180.] |
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32 | elif area == "Close_North_Pole": |
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33 | wlat = [75.,90.] |
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34 | wlon = [-180.,180.] |
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35 | return wlon,wlat |
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36 | |
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37 | def ptitle (name): |
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38 | from matplotlib.pyplot import title |
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39 | title(name) |
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40 | print name |
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41 | |
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42 | def simplinterv (lon2d,lat2d): |
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43 | import numpy as np |
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44 | return [[np.min(lon2d),np.max(lon2d)],[np.min(lat2d),np.max(lat2d)]] |
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45 | |
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46 | def makeplotpngres (filename,res,pad_inches_value=0.25,folder='',disp=True): |
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47 | import matplotlib.pyplot as plt |
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48 | res = int(res) |
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49 | if folder != '': name = folder+'/'+filename+str(res)+".png" |
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50 | else: name = filename+str(res)+".png" |
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51 | plt.savefig(name,dpi=res,bbox_inches='tight',pad_inches=pad_inches_value) |
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52 | if disp: display(name) |
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53 | return |
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54 | |
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55 | def makeplotpng (filename,pad_inches_value=0.25,minres=100.,folder=''): |
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56 | makeplotpngres(filename,minres, pad_inches_value=pad_inches_value,folder=folder) |
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57 | makeplotpngres(filename,minres+200.,pad_inches_value=pad_inches_value,folder=folder,disp=False) |
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58 | return |
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59 | |
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60 | def getcoord2d (nc,nlat='XLAT',nlon='XLONG'): |
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61 | import numpy as np |
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62 | lat = nc.variables[nlat][0,:,:] |
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63 | lon = nc.variables[nlon][0,:,:] |
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64 | if np.array(lat).ndim != 2: [lon2d,lat2d] = np.meshgrid(lon,lat) |
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65 | else: [lon2d,lat2d] = [lon,lat] |
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66 | return lon2d,lat2d |
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67 | |
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68 | def smooth (field, coeff): |
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69 | ## actually blur_image could work with different coeff on x and y |
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70 | if coeff > 1: result = blur_image(field,int(coeff)) |
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71 | else: result = field |
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72 | return result |
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73 | |
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74 | def gauss_kern(size, sizey=None): |
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75 | import numpy as np |
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76 | ## FROM COOKBOOK http://www.scipy.org/Cookbook/SignalSmooth |
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77 | # Returns a normalized 2D gauss kernel array for convolutions |
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78 | size = int(size) |
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79 | if not sizey: |
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80 | sizey = size |
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81 | else: |
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82 | sizey = int(sizey) |
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83 | x, y = np.mgrid[-size:size+1, -sizey:sizey+1] |
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84 | g = np.exp(-(x**2/float(size)+y**2/float(sizey))) |
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85 | return g / g.sum() |
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86 | |
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87 | def blur_image(im, n, ny=None) : |
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88 | from scipy.signal import convolve |
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89 | ## FROM COOKBOOK http://www.scipy.org/Cookbook/SignalSmooth |
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90 | # blurs the image by convolving with a gaussian kernel of typical size n. |
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91 | # The optional keyword argument ny allows for a different size in the y direction. |
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92 | g = gauss_kern(n, sizey=ny) |
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93 | improc = convolve(im, g, mode='same') |
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94 | return improc |
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95 | |
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96 | def vectorfield (u, v, x, y, stride=3, scale=15., factor=250., color='black', csmooth=1): |
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97 | ## scale regle la reference du vecteur |
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98 | ## factor regle toutes les longueurs (dont la reference). l'AUGMENTER pour raccourcir les vecteurs. |
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99 | import matplotlib.pyplot as plt |
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100 | import numpy as np |
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101 | posx = np.max(x)*0.90 |
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102 | posy = np.mean(y) |
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103 | u = smooth(u,csmooth) |
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104 | v = smooth(v,csmooth) |
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105 | q = plt.quiver( x[::stride,::stride],\ |
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106 | y[::stride,::stride],\ |
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107 | u[::stride,::stride],\ |
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108 | v[::stride,::stride],\ |
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109 | angles='xy',color=color,\ |
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110 | scale=factor,width=0.003 ) |
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111 | if color=='white': kcolor='black' |
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112 | elif color=='yellow': kcolor=color |
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113 | else: kcolor=color |
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114 | p = plt.quiverkey(q,posx,posy,scale,\ |
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115 | str(int(scale)),coordinates='data',color=kcolor) |
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116 | return p |
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117 | |
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118 | def display (name): |
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119 | from os import system |
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120 | system("eog "+name+" > /dev/null 2> /dev/null &") |
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121 | return name |
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122 | |
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123 | def findstep (wlon): |
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124 | steplon = int((wlon[1]-wlon[0])/3.) |
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125 | step = 60. |
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126 | if steplon < 60.: step = 30. |
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127 | if steplon < 30.: step = 15. |
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128 | if steplon < 15.: step = 10. |
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129 | if steplon < 10.: step = 5. |
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130 | if steplon < 5.: step = 1. |
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131 | return step |
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132 | |
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133 | def define_proj (char,wlon,wlat,back="."): |
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134 | from mpl_toolkits.basemap import Basemap |
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135 | import numpy as np |
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136 | import matplotlib as mpl |
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137 | meanlon = 0.5*(wlon[0]+wlon[1]) |
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138 | meanlat = 0.5*(wlat[0]+wlat[1]) |
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139 | h = 2000. |
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140 | if char == "cyl": m = Basemap(projection='cyl',llcrnrlat=wlat[0],urcrnrlat=wlat[1],llcrnrlon=wlon[0],urcrnrlon=wlon[1])#,suppress_ticks=False) |
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141 | elif char == "moll": m = Basemap(projection='moll',lon_0=meanlon) |
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142 | elif char == "ortho": m = Basemap(projection='ortho',lon_0=meanlon,lat_0=meanlat) |
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143 | elif char == "lcc": m = Basemap(projection='lcc',lat_1=meanlat,lat_0=meanlat,lon_0=meanlon,\ |
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144 | llcrnrlat=wlat[0],urcrnrlat=wlat[1],llcrnrlon=wlon[0],urcrnrlon=wlon[1]) |
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145 | elif char == "npstere": m = Basemap(projection='npstere', boundinglat=wlat[0], lon_0=0.) |
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146 | elif char == "spstere": m = Basemap(projection='spstere', boundinglat=wlat[0], lon_0=0.) |
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147 | elif char == "nsper": m = Basemap(projection='nsper',lon_0=meanlon,lat_0=meanlat,satellite_height=h*1000.) |
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148 | fontsizemer = int(mpl.rcParams['font.size']*2./3.) |
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149 | if char in ["cyl","lcc"]: step = findstep(wlon) |
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150 | else: step = 10. |
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151 | m.drawmeridians(np.r_[-180.:180.:step*2.], labels=[0,0,0,1], color='grey', fontsize=fontsizemer) |
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152 | m.drawparallels(np.r_[-90.:90.:step], labels=[1,0,0,0], color='grey', fontsize=fontsizemer) |
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153 | if back == ".": m.warpimage(marsmap(),scale=0.75) |
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154 | elif back == None: pass |
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155 | else: m.warpimage(marsmap(back),scale=0.75) |
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156 | return m |
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157 | |
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158 | def marsmap (whichone="vishires"): |
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159 | whichlink = { \ |
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160 | "vis": "http://maps.jpl.nasa.gov/pix/mar0kuu2.jpg",\ |
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161 | "vishires": "http://users.info.unicaen.fr/~karczma/TEACH/InfoGeo/Images/Planets/MarsMap_2500x1250.jpg",\ |
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162 | "mola": "http://www.lns.cornell.edu/~seb/celestia/mars-mola-2k.jpg",\ |
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163 | "molabw": "http://users.info.unicaen.fr/~karczma/TEACH/InfoGeo/Images/Planets/MarsElevation_2500x1250.jpg",\ |
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164 | } |
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165 | if whichone not in whichlink: |
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166 | print "marsmap: choice not defined... you'll get the default one... " |
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167 | whichone = "vishires" |
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168 | return whichlink[whichone] |
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169 | |
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170 | def earthmap (whichone): |
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171 | if whichone == "contrast": whichlink="http://users.info.unicaen.fr/~karczma/TEACH/InfoGeo/Images/Planets/EarthMapAtmos_2500x1250.jpg" |
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172 | elif whichone == "bw": whichlink="http://users.info.unicaen.fr/~karczma/TEACH/InfoGeo/Images/Planets/EarthElevation_2500x1250.jpg" |
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173 | elif whichone == "nice": whichlink="http://users.info.unicaen.fr/~karczma/TEACH/InfoGeo/Images/Planets/earthmap1k.jpg" |
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174 | return whichlink |
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175 | |
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