从GRIB2文件中转移数据

Question

我已经成功地从NCEP打开了一个grib2文件，但是我无法使用本文中的自定义matplotlib函数使用convertXY来转换坐标以使用xmin绘制坐标{ {3}}。

我达到了我的期望，但是仅在世界的一半地区，我可以通过从我的xmax和shiftgrid中减去180.0来解决它，但是我失去了坐标转换，我想这是问题所在是不是我可能没有使用mpl_toolkits中的xmin来移动数据，但是我也无法使函数正常工作，有任何建议吗？

这是不带减法的地图图像：

Plot GDAL raster using matplotlib Basemap

这是我从xmax和from mpl_toolkits.basemap import Basemap import osr, gdal import matplotlib.pyplot as plt import numpy as np def convertXY(xy_source, inproj, outproj): # function to convert coordinates shape = xy_source[0,:,:].shape size = xy_source[0,:,:].size # the ct object takes and returns pairs of x,y, not 2d grids # so the the grid needs to be reshaped (flattened) and back. ct = osr.CoordinateTransformation(inproj, outproj) xy_target = np.array(ct.TransformPoints(xy_source.reshape(2, size).T)) xx = xy_target[:,0].reshape(shape) yy = xy_target[:,1].reshape(shape) return xx, yy # Read the data and metadata ds = gdal.Open(r'D:\Downloads\flxf2018101912.01.2018101912.grb2') data = ds.ReadAsArray() gt = ds.GetGeoTransform() proj = ds.GetProjection() xres = gt[1] yres = gt[5] # get the edge coordinates and add half the resolution # to go to center coordinates xmin = gt[0] + xres * 0.5 xmin -= 180.0 xmax = gt[0] + (xres * ds.RasterXSize) - xres * 0.5 xmax -= 180.0 ymin = gt[3] + (yres * ds.RasterYSize) + yres * 0.5 ymax = gt[3] - yres * 0.5 ds = None # create a grid of xy coordinates in the original projection xy_source = np.mgrid[xmin:xmax+xres:xres, ymax+yres:ymin:yres] # Create the figure and basemap object fig = plt.figure(figsize=(12, 6)) m = Basemap(projection='robin', lon_0=0, resolution='c') # Create the projection objects for the convertion # original (Albers) inproj = osr.SpatialReference() inproj.ImportFromWkt(proj) # Get the target projection from the basemap object outproj = osr.SpatialReference() outproj.ImportFromProj4(m.proj4string) # Convert from source projection to basemap projection xx, yy = convertXY(xy_source, inproj, outproj) # plot the data (first layer) im1 = m.pcolormesh(xx, yy, data[0,:,:].T, cmap=plt.cm.jet) # annotate m.drawcountries() m.drawcoastlines(linewidth=.5) plt.show() 变量中减去180.0时得到的结果：

您可以从以下位置下载我正在使用的grib2文件：

OsProfile: compute.OSProfile{
	ComputerName:  to.StringPtr(p.InstanceName),
	AdminUsername: to.StringPtr(p.UserName),
	LinuxConfiguration: compute.LinuxConfiguration{
		SSH: compute.SSHConfiguration{
			PublicKeys: []compute.SSHPublicKey{
				{
					Path: to.StringPtr(
						fmt.Sprintf("/home/%s/.ssh/authorized_keys",
							p.UserName)),
					KeyData: to.StringPtr(p.SshPublicKey),
				},
			},
		},
	},
	CustomData: to.StringPtr(base64.StdEncoding.EncodeToString([]byte(p.UserData))),
},

Answer 1

这是我自带的，适用于所有投影：

from mpl_toolkits.basemap import Basemap
from mpl_toolkits.basemap import shiftgrid
import osr, gdal
import matplotlib.pyplot as plt
import numpy as np

# Read the data and metadata
# Pluviocidad.
#ds = gdal.Open( 'C:\Users\Paula\Downloads\enspost.t00z.prcp_24hbc (1).grib2', gdal.GA_ReadOnly )
# Sea Ice
ds = gdal.Open( 'D:\Downloads\seaice.t00z.grb.grib2', gdal.GA_ReadOnly )
data = ds.ReadAsArray()
gt = ds.GetGeoTransform()
proj = ds.GetProjection()

xres = gt[1]
yres = gt[5]

xsize = ds.RasterXSize
ysize = ds.RasterYSize

# get the edge coordinates and add half the resolution 
# to go to center coordinates
xmin = gt[0] + xres * 0.5
xmax = gt[0] + (xres * xsize) - xres * 0.5
ymin = gt[3] + (yres * ysize) + yres * 0.5
ymax = gt[3] - yres * 0.5

ds = None

xx = np.arange( xmin, xmax + xres, xres )
yy = np.arange( ymax + yres, ymin, yres )

data, xx = shiftgrid( 180.0, data, xx, start = False )

# Mercator
m = Basemap(projection='merc',llcrnrlat=-85,urcrnrlat=85,\
            llcrnrlon=-180,urcrnrlon=180,lat_ts=0,resolution='c')

x, y = m(*np.meshgrid(xx,yy))

# plot the data (first layer) data[0,:,:].T
im1 = m.pcolormesh( x, y, data, shading = "flat", cmap=plt.cm.jet )

# annotate
m.drawcountries()
m.drawcoastlines(linewidth=.5)

plt.show()