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在python底图中绘制gebco数据

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我已经下载了一些gebco测深数据作为netCDF文件 . 我想用python-basemap绘制它 . 我试过了，

import netCDF4
from mpl_toolkits.basemap import Basemap


# Load data
dataset = netCDF4.Dataset('/home/david/Desktop/GEBCO/gebco_08_-30_45_5_65.nc')

# Extract variables
x = dataset.variables['x_range']
y = dataset.variables['y_range']
spacing = dataset.variables['spacing']

# Data limits
nx = (x[-1]-x[0])/spacing[0]   # num pts in x-dir
ny = (y[-1]-y[0])/spacing[1]   # num pts in y-dir

# Reshape data
zz = dataset.variables['z']
Z = zz[:].reshape(ny, nx)



# setup basemap.
m = Basemap(llcrnrlon=-30,llcrnrlat=45.0,urcrnrlon=5.0,urcrnrlat=65.0,
            resolution='i',projection='stere',lon_0=-15.0,lat_0=55.0)


# Set up grid
lons, lats = m.makegrid(nx, ny)
x, y = m(lons, lats)

m.contourf(x, y, flipud(Z))
m.fillcontinents(color='grey')
m.drawparallels(np.arange(10,70,10), labels=[1,0,0,0])
m.drawmeridians(np.arange(-80, 5, 10), labels=[0,0,0,1])

这给出了下图，显然不正确 . 问题源于如何定义区域 . 底图区域由左下角lat，lon和右上角lat，lon定义 . 但是gebco数据采用沿中心线定义的最大和最小lon / lat . 任何人都有gebco数据的经验或看到解决方案？

谢谢D
map

python netcdf matplotlib-basemap

1 回答

  • 3

    所以只是为了记录，这里的答案是有效的，使用上面的评论：

    import netCDF4
from mpl_toolkits.basemap import Basemap

# Load data
dataset = netCDF4.Dataset('/usgs/data1/rsignell/bathy/gebco_08_-30_-45_5_65.nc')

# Extract variables
x = dataset.variables['x_range']
y = dataset.variables['y_range']
spacing = dataset.variables['spacing']

# Compute Lat/Lon
nx = (x[-1]-x[0])/spacing[0]   # num pts in x-dir
ny = (y[-1]-y[0])/spacing[1]   # num pts in y-dir

lon = np.linspace(x[0],x[-1],nx)
lat = np.linspace(y[0],y[-1],ny)

# Reshape data
zz = dataset.variables['z']
Z = zz[:].reshape(ny, nx)

# setup basemap.
m = Basemap(llcrnrlon=-30,llcrnrlat=45.0,urcrnrlon=5.0,urcrnrlat=65.0,
            resolution='i',projection='stere',lon_0=-15.0,lat_0=55.0)

x,y = m(*np.meshgrid(lon,lat))

m.contourf(x, y, flipud(Z));
m.fillcontinents(color='grey');
m.drawparallels(np.arange(10,70,10), labels=[1,0,0,0]);
m.drawmeridians(np.arange(-80, 5, 10), labels=[0,0,0,1]);

    产生这个情节 .
    enter image description here

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