Tim Michelsen wrote:
> Hello,
> thanks.
> I checked again from contour_demo.py of the basemap distribution.
>
> There lats, lons are uniquely monoton increasing from 0-360 and from -90 to
> 90.
> In my case data is written row-by-row:
> * increasing from lowest latitude western most longitude to easternmost
> longitude and then increasing each rows in the same manner to the northermost
> latitude (see below).
>
> So, as you said, it's a question of re-aranging the data. that it fits the to
> the way m.contour expects the 2-D array.
> Also, since the grid is still coarse, I would need to apply some smoothing
> afterwards. What do you recommend for that?
>
Timme: Here's one way to do it
from matplotlib.mlab import load
import matplotlib.pyplot as plt
import numpy as np
data = load("data.txt")
# need to know nlons and nlats beforehand!
nlons = 8; nlats = 25
X = data[0::nlats,0]
Y = data[0:nlats,1]
# data is in nlons,nlats order in file, need to transpose
Z = data[:,2].reshape(nlons,nlats).transpose()
X,Y = np.meshgrid(X,Y)
CS = plt.contourf(X,Y,Z,20)
plt.show()
I don't have any recommendations for smoothing - why don't you plot the
raw data first and see if you really need it?
> I don't know how I can do this easily by hand. May you give me some guidance
> here, please?
>
> But I may just convert it to a shape file using GIS then load it with the
> shapefile interface you wrote.
> What would you see as most convenient way?
> If I produce maps with a GIS but want to use matplotlib for the map plotting,
> what would be the preferred export format? Any gdal format?
>
I prefer netCDF format for gridded data (basemap contains a function for
reading netCDF files - NetCDFFile).
-Jeff
> Many thanks in advance,
> Timmie
>
> ### data example
>
> Latitude Longitude value
> 45 7 7.65251434
> 45 7.25 6.841345477
> 45 7.5 3.923153289
> 45 7.75 3.644313708
> 45 8 3.550977951
> 45 8.25 3.352525137
> 45 8.5 3.080082094
> 45 8.75 2.971992657
> 45 9 2.998723785
> 45 9.25 3.080082094
> 45 9.5 3.185687405
> 45 9.75 3.102075854
> 45 10 3.185687405
> 45 10.25 3.213960325
> 45 10.5 3.32326373
> 45 10.75 3.465643983
> 45 11 3.612980369
> 45 11.25 3.644313708
> 45 11.5 3.701277511
> 45 11.75 3.923153289
> 45 12 3.797848342
> 45 12.25 3.612980369
> 45 12.5 3.435577844
> 45 12.75 3.294210812
> 45 13 3.26536503
> 45.25 7 6.485050223
> 45.25 7.25 6.343081631
> 45.25 7.5 3.856783573
> 45.25 7.75 3.405725407
> 45.25 8 3.550977951
> 45.25 8.25 3.294210812
> 45.25 8.5 3.294210812
> 45.25 8.75 3.185687405
> 45.25 9 3.15761656
> 45.25 9.25 3.213960325
> 45.25 9.5 3.15761656
> 45.25 9.75 3.32326373
> 45.25 10 3.405725407
> 45.25 10.25 3.495925216
> 45.25 10.5 3.465643983
> 45.25 10.75 3.550977951
> 45.25 11 3.465643983
> 45.25 11.25 3.765429652
> 45.25 11.5 3.95669157
> 45.25 11.75 3.797848342
> 45.25 12 3.923153289
> 45.25 12.25 3.733239867
> 45.25 12.5 3.550977951
> 45.25 12.75 3.520306012
> 45.25 13 3.376085288
> 45.5 7 6.383367092
> 45.5 7.25 6.383367092
> 45.5 7.5 6.009422688
> 45.5 7.75 4.679469855
> 45.5 8 3.435577844
> 45.5 8.25 3.435577844
> 45.5 8.5 3.236725042
> 45.5 8.75 3.236725042
> 45.5 9 3.185687405
> 45.5 9.25 3.102075854
> 45.5 9.5 3.102075854
> 45.5 9.75 3.185687405
> 45.5 10 3.352525137
> 45.5 10.25 3.405725407
> 45.5 10.5 3.376085288
> 45.5 10.75 3.612980369
> 45.5 11 3.520306012
> 45.5 11.25 3.352525137
> 45.5 11.5 3.823949103
> 45.5 11.75 3.856783573
> 45.5 12 3.856783573
> 45.5 12.25 3.765429652
> 45.5 12.5 3.669541114
> 45.5 12.75 3.550977951
> 45.5 13 3.435577844
> 45.75 7 5.309043916
> 45.75 7.25 6.057519881
> 45.75 7.5 5.030958443
> 45.75 7.75 4.836570243
> 45.75 8 4.836570243
> 45.75 8.25 2.724965001
> 45.75 8.5 2.607751091
> 45.75 8.75 3.26536503
> 45.75 9 2.898163214
> 45.75 9.25 2.872155245
> 45.75 9.5 1.893252754
> 45.75 9.75 2.043669061
> 45.75 10 1.75488883
> 45.75 10.25 2.004264146
> 45.75 10.5 2.971992657
> 45.75 10.75 1.804949998
> 45.75 11 2.846334614
> 45.75 11.25 5.519419657
> 45.75 11.5 2.517818813
> 45.75 11.75 3.733239867
> 45.75 12 3.376085288
> 45.75 12.25 3.550977951
> 45.75 12.5 3.612980369
> 45.75 12.75 3.520306012
> 45.75 13 3.495925216
> 46 7 5.06399168
> 46 7.25 4.949174095
> 46 7.5 5.266087828
> 46 7.75 5.352298328
> 46 8 4.757472437
> 46 8.25 2.800325674
> 46 8.5 3.612980369
> 46 8.75 3.185687405
> 46 9 2.323282473
> 46 9.25 1.671485743
> 46 9.5 3.856783573
> 46 9.75 4.572079662
> 46 10 4.679469855
> 46 10.25 4.679469855
> 46 10.5 5.309043916
> 46 10.75 3.294210812
> 46 11 3.405725407
> 46 11.25 3.669541114
> 46 11.5 3.495925216
> 46 11.75 4.255093726
> 46 12 3.495925216
> 46 12.25 3.185687405
> 46 12.5 3.213960325
> 46 12.75 3.550977951
> 46 13 3.520306012
> 46.25 7 1.969297411
> 46.25 7.25 4.908706364
> 46.25 7.5 3.052767233
> 46.25 7.75 3.765429652
> 46.25 8 3.95669157
> 46.25 8.25 5.06399168
> 46.25 8.5 5.266087828
> 46.25 8.75 3.669541114
> 46.25 9 3.185687405
> 46.25 9.25 3.797848342
> 46.25 9.5 3.352525137
> 46.25 9.75 5.439709782
> 46.25 10 5.69098301
> 46.25 10.25 4.949174095
> 46.25 10.5 5.736883145
> 46.25 10.75 5.105542055
> 46.25 11 4.255093726
> 46.25 11.25 3.701277511
> 46.25 11.5 4.255093726
> 46.25 11.75 4.572079662
> 46.25 12 3.98369323
> 46.25 12.25 4.148941623
> 46.25 12.5 3.129746478
> 46.25 12.75 3.236725042
> 46.25 13 3.550977951
> 46.5 7 2.872155245
> 46.5 7.25 3.701277511
> 46.5 7.5 3.15761656
> 46.5 7.75 3.765429652
> 46.5 8 5.18951259
> 46.5 8.25 6.105948261
> 46.5 8.5 5.266087828
> 46.5 8.75 5.69098301
> 46.5 9 6.009422688
> 46.5 9.25 5.147381739
> 46.5 9.5 5.829636932
> 46.5 9.75 5.654489904
> 46.5 10 6.243327668
> 46.5 10.25 5.395852976
> 46.5 10.5 5.736883145
> 46.5 10.75 6.057519881
> 46.5 11 5.147381739
> 46.5 11.25 3.520306012
> 46.5 11.5 3.856783573
> 46.5 11.75 4.148941623
> 46.5 12 4.71833512
> 46.5 12.25 4.71833512
> 46.5 12.5 3.701277511
> 46.5 12.75 3.889851131
> 46.5 13 3.32326373
> 46.75 7 1.859766825
> 46.75 7.25 2.198852355
> 46.75 7.5 2.345277833
> 46.75 7.75 2.517818813
> 46.75 8 3.856783573
> 46.75 8.25 3.856783573
> 46.75 8.5 5.06399168
> 46.75 8.75 4.184077131
> 46.75 9 5.829636932
> 46.75 9.25 3.644313708
> 46.75 9.5 3.765429652
> 46.75 9.75 5.309043916
> 46.75 10 6.009422688
> 46.75 10.25 5.147381739
> 46.75 10.5 5.609155594
> 46.75 10.75 5.783100444
> 46.75 11 5.147381739
> 46.75 11.25 3.581868928
> 46.75 11.5 4.908706364
> 46.75 11.75 3.465643983
> 46.75 12 3.465643983
> 46.75 12.25 4.148941623
> 46.75 12.5 3.98369323
> 46.75 12.75 3.581868928
> 46.75 13 3.644313708
>
>
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--
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