| 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 getproj (nc): |
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| 38 | map_proj = getattr(nc, 'MAP_PROJ') |
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| 39 | cen_lat = getattr(nc, 'CEN_LAT') |
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| 40 | if map_proj == 2: |
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| 41 | if cen_lat > 10.: |
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| 42 | proj="npstere" |
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| 43 | print "NP stereographic polar domain" |
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| 44 | else: |
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| 45 | proj="spstere" |
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| 46 | print "SP stereographic polar domain" |
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| 47 | elif map_proj == 1: |
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| 48 | print "lambert projection domain" |
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| 49 | proj="lcc" |
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| 50 | elif map_proj == 3: |
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| 51 | print "mercator projection" |
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| 52 | proj="merc" |
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| 53 | return proj |
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| 54 | |
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| 55 | def ptitle (name): |
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| 56 | from matplotlib.pyplot import title |
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| 57 | title(name) |
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| 58 | print name |
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| 59 | |
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| 60 | def simplinterv (lon2d,lat2d): |
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| 61 | import numpy as np |
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| 62 | return [[np.min(lon2d),np.max(lon2d)],[np.min(lat2d),np.max(lat2d)]] |
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| 63 | |
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| 64 | def wrfinterv (lon2d,lat2d): |
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| 65 | nx = len(lon2d[0,:])-1 |
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| 66 | ny = len(lon2d[:,0])-1 |
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| 67 | return [[lon2d[0,0],lon2d[nx,ny]],[lat2d[0,0],lat2d[nx,ny]]] |
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| 68 | |
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| 69 | def makeplotpngres (filename,res,pad_inches_value=0.25,folder='',disp=True): |
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| 70 | import matplotlib.pyplot as plt |
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| 71 | res = int(res) |
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| 72 | if folder != '': name = folder+'/'+filename+str(res)+".png" |
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| 73 | else: name = filename+str(res)+".png" |
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| 74 | plt.savefig(name,dpi=res,bbox_inches='tight',pad_inches=pad_inches_value) |
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| 75 | if disp: display(name) |
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| 76 | return |
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| 77 | |
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| 78 | def makeplotpng (filename,pad_inches_value=0.25,minres=100.,folder=''): |
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| 79 | makeplotpngres(filename,minres, pad_inches_value=pad_inches_value,folder=folder) |
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| 80 | makeplotpngres(filename,minres+200.,pad_inches_value=pad_inches_value,folder=folder,disp=False) |
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| 81 | return |
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| 82 | |
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| 83 | def dumpbdy (field): |
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| 84 | nx = len(field[0,:])-1 |
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| 85 | ny = len(field[:,0])-1 |
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| 86 | return field[5:ny-5,5:nx-5] |
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| 87 | |
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| 88 | def getcoord2d (nc,nlat='XLAT',nlon='XLONG',is1d=False): |
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| 89 | import numpy as np |
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| 90 | if is1d: |
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| 91 | lat = nc.variables[nlat][:] |
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| 92 | lon = nc.variables[nlon][:] |
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| 93 | [lon2d,lat2d] = np.meshgrid(lon,lat) |
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| 94 | else: |
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| 95 | lat = nc.variables[nlat][0,:,:] |
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| 96 | lon = nc.variables[nlon][0,:,:] |
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| 97 | [lon2d,lat2d] = [lon,lat] |
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| 98 | return lon2d,lat2d |
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| 99 | |
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| 100 | def smooth (field, coeff): |
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| 101 | ## actually blur_image could work with different coeff on x and y |
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| 102 | if coeff > 1: result = blur_image(field,int(coeff)) |
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| 103 | else: result = field |
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| 104 | return result |
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| 105 | |
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| 106 | def gauss_kern(size, sizey=None): |
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| 107 | import numpy as np |
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| 108 | ## FROM COOKBOOK http://www.scipy.org/Cookbook/SignalSmooth |
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| 109 | # Returns a normalized 2D gauss kernel array for convolutions |
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| 110 | size = int(size) |
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| 111 | if not sizey: |
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| 112 | sizey = size |
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| 113 | else: |
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| 114 | sizey = int(sizey) |
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| 115 | x, y = np.mgrid[-size:size+1, -sizey:sizey+1] |
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| 116 | g = np.exp(-(x**2/float(size)+y**2/float(sizey))) |
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| 117 | return g / g.sum() |
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| 118 | |
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| 119 | def blur_image(im, n, ny=None) : |
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| 120 | from scipy.signal import convolve |
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| 121 | ## FROM COOKBOOK http://www.scipy.org/Cookbook/SignalSmooth |
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| 122 | # blurs the image by convolving with a gaussian kernel of typical size n. |
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| 123 | # The optional keyword argument ny allows for a different size in the y direction. |
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| 124 | g = gauss_kern(n, sizey=ny) |
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| 125 | improc = convolve(im, g, mode='same') |
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| 126 | return improc |
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| 127 | |
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| 128 | def vectorfield (u, v, x, y, stride=3, scale=15., factor=250., color='black', csmooth=1, key=True): |
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| 129 | ## scale regle la reference du vecteur |
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| 130 | ## factor regle toutes les longueurs (dont la reference). l'AUGMENTER pour raccourcir les vecteurs. |
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| 131 | import matplotlib.pyplot as plt |
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| 132 | import numpy as np |
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| 133 | posx = np.max(x) + np.std(x) / 3. ## pb pour les domaines globaux ... |
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| 134 | posy = np.mean(y) |
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| 135 | #posx = np.min(x) |
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| 136 | #posy = np.max(x) |
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| 137 | u = smooth(u,csmooth) |
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| 138 | v = smooth(v,csmooth) |
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| 139 | widthvec = 0.005 #0.003 |
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| 140 | q = plt.quiver( x[::stride,::stride],\ |
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| 141 | y[::stride,::stride],\ |
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| 142 | u[::stride,::stride],\ |
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| 143 | v[::stride,::stride],\ |
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| 144 | angles='xy',color=color,\ |
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| 145 | scale=factor,width=widthvec ) |
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| 146 | if color=='white': kcolor='black' |
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| 147 | elif color=='yellow': kcolor=color |
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| 148 | else: kcolor=color |
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| 149 | if key: p = plt.quiverkey(q,posx,posy,scale,\ |
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| 150 | str(int(scale)),coordinates='data',color=kcolor) |
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| 151 | return |
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| 152 | |
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| 153 | def display (name): |
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| 154 | from os import system |
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| 155 | system("display "+name+" > /dev/null 2> /dev/null &") |
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| 156 | return name |
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| 157 | |
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| 158 | def findstep (wlon): |
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| 159 | steplon = int((wlon[1]-wlon[0])/4.) #3 |
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| 160 | step = 120. |
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| 161 | while step > steplon and step > 15. : step = step / 2. |
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| 162 | if step <= 15.: |
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| 163 | while step > steplon and step > 5. : step = step - 5. |
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| 164 | if step <= 5.: |
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| 165 | while step > steplon and step > 1. : step = step - 1. |
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| 166 | if step <= 1.: |
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| 167 | step = 1. |
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| 168 | return step |
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| 169 | |
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| 170 | def define_proj (char,wlon,wlat,back="."): |
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| 171 | from mpl_toolkits.basemap import Basemap |
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| 172 | import numpy as np |
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| 173 | import matplotlib as mpl |
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| 174 | meanlon = 0.5*(wlon[0]+wlon[1]) |
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| 175 | meanlat = 0.5*(wlat[0]+wlat[1]) |
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| 176 | if wlat[0] >= 80.: blat = 40. |
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| 177 | elif wlat[0] <= -80.: blat = -40. |
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| 178 | else: blat = wlat[0] |
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| 179 | h = 2000. |
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| 180 | radius = 3397200 |
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| 181 | if char == "cyl": m = Basemap(rsphere=radius,projection='cyl',\ |
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| 182 | llcrnrlat=wlat[0],urcrnrlat=wlat[1],llcrnrlon=wlon[0],urcrnrlon=wlon[1]) |
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| 183 | elif char == "moll": m = Basemap(rsphere=radius,projection='moll',lon_0=meanlon) |
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| 184 | elif char == "ortho": m = Basemap(rsphere=radius,projection='ortho',lon_0=meanlon,lat_0=meanlat) |
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| 185 | elif char == "lcc": m = Basemap(rsphere=radius,projection='lcc',lat_1=meanlat,lat_0=meanlat,lon_0=meanlon,\ |
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| 186 | llcrnrlat=wlat[0],urcrnrlat=wlat[1],llcrnrlon=wlon[0],urcrnrlon=wlon[1]) |
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| 187 | elif char == "npstere": m = Basemap(rsphere=radius,projection='npstere', boundinglat=blat, lon_0=0.) |
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| 188 | elif char == "spstere": m = Basemap(rsphere=radius,projection='spstere', boundinglat=blat, lon_0=0.) |
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| 189 | elif char == "nsper": m = Basemap(rsphere=radius,projection='nsper',lon_0=meanlon,lat_0=meanlat,satellite_height=h*1000.) |
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| 190 | elif char == "merc": m = Basemap(rsphere=radius,projection='merc',lat_ts=0.,\ |
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| 191 | llcrnrlat=wlat[0],urcrnrlat=wlat[1],llcrnrlon=wlon[0],urcrnrlon=wlon[1]) |
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| 192 | fontsizemer = int(mpl.rcParams['font.size']*3./4.) |
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| 193 | if char in ["cyl","lcc","merc"]: step = findstep(wlon) |
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| 194 | else: step = 10. |
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| 195 | m.drawmeridians(np.r_[-180.:180.:step*2.], labels=[0,0,0,1], color='grey', fontsize=fontsizemer) |
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| 196 | m.drawparallels(np.r_[-90.:90.:step], labels=[1,0,0,0], color='grey', fontsize=fontsizemer) |
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| 197 | if back == ".": m.warpimage(marsmap(),scale=0.75) |
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| 198 | elif back == None: pass |
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| 199 | else: m.warpimage(marsmap(back),scale=0.75) |
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| 200 | return m |
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| 201 | |
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| 202 | def marsmap (whichone="vishires"): |
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| 203 | whichlink = { \ |
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| 204 | "vis": "http://maps.jpl.nasa.gov/pix/mar0kuu2.jpg",\ |
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| 205 | "vishires": "http://users.info.unicaen.fr/~karczma/TEACH/InfoGeo/Images/Planets/MarsMap_2500x1250.jpg",\ |
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| 206 | "mola": "http://www.lns.cornell.edu/~seb/celestia/mars-mola-2k.jpg",\ |
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| 207 | "molabw": "http://users.info.unicaen.fr/~karczma/TEACH/InfoGeo/Images/Planets/MarsElevation_2500x1250.jpg",\ |
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| 208 | } |
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| 209 | if whichone not in whichlink: |
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| 210 | print "marsmap: choice not defined... you'll get the default one... " |
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| 211 | whichone = "vishires" |
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| 212 | return whichlink[whichone] |
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| 213 | |
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| 214 | def earthmap (whichone): |
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| 215 | if whichone == "contrast": whichlink="http://users.info.unicaen.fr/~karczma/TEACH/InfoGeo/Images/Planets/EarthMapAtmos_2500x1250.jpg" |
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| 216 | elif whichone == "bw": whichlink="http://users.info.unicaen.fr/~karczma/TEACH/InfoGeo/Images/Planets/EarthElevation_2500x1250.jpg" |
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| 217 | elif whichone == "nice": whichlink="http://users.info.unicaen.fr/~karczma/TEACH/InfoGeo/Images/Planets/earthmap1k.jpg" |
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| 218 | return whichlink |
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| 219 | |
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