格点插值为站点数据批量处理

qiaody

感谢楼主！非常有用

零陵路

感谢楼主！

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zaqbob

wuyu 发表于 2017-8-25 15:48
王老师，我运行了如下：
#Open station file as table data
stdata = readtable('F:/MeteoInfo/sample/Lo ...

我也遇到了这个问题，请问你的解决了吗？

gyq1991

多时次的模式资料只能处理成grads的形式吗？

gyq1991

请教一下，读取ctl时报错。
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "E:\MeteoInfo_1.7.1\MeteoInfo\pylib\mipylib\dataset\midata.py", line 103, in addfile
    return addfile_grads(fname, False)
  File "E:\MeteoInfo_1.7.1\MeteoInfo\pylib\mipylib\dataset\midata.py", line 169, in addfile_grads
    meteodata.openGrADSData(fname)
        at java.lang.NumberFormatException.forInputString(Unknown Source)

        at java.lang.Integer.parseInt(Unknown Source)

        at java.lang.Integer.parseInt(Unknown Source)

        at org.meteoinfo.data.meteodata.grads.GrADSDataInfo.readDataInfo(GrADSDataInfo.java:877)

        at org.meteoinfo.data.meteodata.grads.GrADSDataInfo.readDataInfo(GrADSDataInfo.java:296)

        at org.meteoinfo.data.meteodata.MeteoDataInfo.openGrADSData(MeteoDataInfo.java:503)

        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)

        at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)

        at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)

        at java.lang.reflect.Method.invoke(Unknown Source)

java.lang.NumberFormatException: java.lang.NumberFormatException: For input string: "0,100,50000"

但是用grads是能打开这个ctl，不知道问题出在哪里

MeteoInfo

gyq1991 发表于 2019-2-12 18:42
请教一下，读取ctl时报错。
Traceback (most recent call last):
  File "", line 1, in

把脚本贴出来看看，不行的话把数据文件贴出来。

gyq1991

MeteoInfo 发表于 2019-2-12 23:45
把脚本贴出来看看，不行的话把数据文件贴出来。

ctl的脚本
dset G:/TCC/GPV_1DAY/GPV_1DAY/20180919/p500_Pahh_em.20180919
index G:/TCC/GPV_1DAY/GPV_1DAY/20180919/p500_Pahh_em.20180919.idx
undef 9.999E+20
title G:/TCC/GPV_1DAY/GPV_1DAY/20180919/p500_Pahh_em.20180919
*  produced by g2ctl v0.0.3d
* griddef=1.1:0:(144 x 73):grid_template=0:winds(N/S): lat-lon grid:(144 x 73) units 1e-06 input WE:NS output WE:SN res 48 lat 90.000000 to -90.000000 by 2.500000 lon 0.000000 to 357.500000 by 2.500000 #points=10512

dtype grib2
ydef 73 linear -90.000000 2.5
xdef 144 linear 0.000000 2.500000
tdef 31 linear 00Z21sep2018 1dy
zdef 1 linear 1 1
vars 1
GPA500mb  0,100,50000   0,3,9,0 ** 500 mb ave Geopotential Height Anomaly [gpm]
ENDVARS

MI的脚本
#Open station file as table data
stdata = readtable('C:/Users/wrcc-gyq/Desktop/China_Prec_2010101420.csv', delimiter=',', format='%s%f%f')
x = stdata['Longitude']
y = stdata['Latitude']
#Add data file
f = addfile('G:/TCC/GPV_1DAY/GPV_1DAY/20180919/p500_Pahh_em.20180919.ctl')
#Get data variable
psv = f['GPA500mb']
#Get time dimension length
tn = psv.dimlen(0)
#Loop
for i in range(0, tn):
    #Get dimension array
    ps = psv[i,'10:60','60:140']
    #Interpolate to stations
    ps_st = ps.tostation(x, y)
    #Add column to table data
    colname = 'PS' + str(i)
    stdata.addcoldata(colname, '%d', ps_st)
#Save table data to a file
fn = 'D:/Temp/test_st.csv'
stdata.savefile(fn)
print 'Finish...'

麻烦您了

MeteoInfo

gyq1991 发表于 2019-2-13 15:53
ctl的脚本
dset G:/TCC/GPV_1DAY/GPV_1DAY/20180919/p500_Pahh_em.20180919
index G:/TCC/GPV_1DAY/GPV ...

这个是grib格式的数据，MeteoInfo打开grib格式数据不需要ctl文件，可以用addfile函数直接打开，参考此脚本：

1. fn = 'D:/Temp/grib/p500_Pahh_em.20180919'
   
2. f = addfile(fn)
   
3. data = f['Geopotential_height_anomaly_isobaric_5_Day_Average_unweightedMean'][0,0,:,:]
   
4. axesm()
   
5. geoshow('country', edgecolor='k')
   
6. layer = contourfm(data, 20)
   
7. colorbar(layer)

fn = 'D:/Temp/grib/p500_Pahh_em.20180919'<br /> f = addfile(fn)<br /> data = f['Geopotential_height_anomaly_isobaric_5_Day_Average_unweightedMean'][0,0,:,:]<br /> axesm()<br /> geoshow('country', edgecolor='k')<br /> layer = contourfm(data, 20)<br /> colorbar(layer)

gyq1991

MeteoInfo 发表于 2019-2-13 16:52
这个是grib格式的数据，MeteoInfo打开grib格式数据不需要ctl文件，可以用addfile函数直接打开，参考此脚 ...

感谢老师的帮助，完成了第一个脚本

235653320

老师，我的这个脚本报错您能看一下吗？
#Open station file as table data
stdata = readtable('D:/daqihuanliu/China_Prec_2010101420.csv', delimiter=',', format='%s%f%f')
x = stdata['Longitude']
y = stdata['Latitude']
#Add data file
f = addfile('D:/daqihuanliu/hur_A1_2000_to_2049.nc')
#Get data variable
psv = f['hur']
#Get time dimension length
tn = psv.dimlen(0)
#Loop
for i in range(0, tn):
    #Get dimension array
    ps = psv[i,'10:60','60:140']
    #Interpolate to stations
    ps_st = ps.tostation(x, y)
    #Add column to table data
    colname = 'hur' + str(i)
    stdata.addcoldata(colname, '%d', ps_st)

#Save table data to a file
fn = 'D:/Temp/test_st.csv'
stdata.savefile(fn)
print 'Finish...'
报错如下
>>> run script...
indices must be 4 dimensions!
Traceback (most recent call last):
  File "<iostream>", line 16, in <module>
AttributeError: 'NoneType' object has no attribute 'tostation'
>>>