Hi,
Well hopefully doing what you suggested correctly...
numrows = 17
numcols = 16
ulat, llat, ulon, llon = 15.61, 15.15, -1.32, -1.74
m = Basemap(projection='geos', lon_0=0.0, llcrnrlon=llon,
llcrnrlat=llat, urcrnrlon=ulon, urcrnrlat=ulat,
resolution='c')
data2 = np.random.sample((17,16))
x = np.linspace(-1.74, -1.32, 16)
y = np.linspace(15.15, 15.61, 17)
px, py = m(x, y)
X, Y = np.meshgrid(px, py)
m.contourf(X, Y, data2, colors='black')
plt.show()
Doesn't seem to work either?
thanks,
Martin
Ryan May-3 wrote:
>
> On Mon, Sep 13, 2010 at 7:45 AM, mdekauwe <mdeka...@gmail.com> wrote:
>>
>> Hi,
>>
>> If I set up a random example and plot it as a contour it seems to work
>> fine...e.g.
>>
>> import matplotlb.pyplot as plt
>> import numpy as np
>>
>> data2 = np.random.sample((17,16))
>> x = np.linspace(-1.74, -1.32, 16)
>> y = np.linspace(15.15, 15.61, 17)
>> X, Y = np.meshgrid(x, y)
>> plt.contour(X, Y, data2, colors='black')
>> plt.show()
>>
>> However if instead I try use a basemap projection to do the contouring I
>> run
>> into trouble. For example...
>>
>> import numpy as np
>> from mpl_toolkits.basemap import Basemap
>>
>> ulat, llat, ulon, llon = 15.61, 15.15, -1.32, -1.74
>> m = Basemap(projection='geos', lon_0=0.0, llcrnrlon=llon,
>> llcrnrlat=llat, urcrnrlon=ulon, urcrnrlat=ulat,
>> resolution='c')
>>
>> data2 = np.random.sample((17,16))
>> x = np.linspace(-1.74, -1.32, 16)
>> y = np.linspace(15.15, 15.61, 17)
>> X, Y = m(x, y)
>> m.contourf(X, Y, data2, colors='black')
>> plt.show()
>
> You replaced the call to meshgrid with a call to the Basemap object.
> You need to use both:
>
> px,py = m(x, y)
> X,Y = np.meshgrid(px, py)
>
> Ryan
>
> --
> Ryan May
> Graduate Research Assistant
> School of Meteorology
> University of Oklahoma
>
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