站点数据绘制等值线需要首先将站点数据插值为格点数据，MeteoInfo中提供了反距离权法（IDW）和cressman两个方法，其中IDW方法可以有插值半径的选项。这里示例读取一个MICAPS第一类数据（地面全要素观测），获取6小时累积降水数据（Precipitation6h），然后用站点数据的griddata函数将站点数据插值为格点数据，再利用contourfm函数创建等值线填色图层（等值线间隔和颜色可以自定义）。
脚本程序（经纬度投影）：
#Set data folders basedir = 'D:/MyProgram/Distribution/java/MeteoInfo/MeteoInfo' datadir = os.path.join(basedir, 'sample/MICAPS') mapdir = os.path.join(basedir, 'map') #Read shape files bou2_layer = shaperead(os.path.join(mapdir, 'bou2_4p.shp')) bou1_layer = shaperead(os.path.join(mapdir, 'bou1_4l.shp')) china_layer = shaperead(os.path.join(mapdir, 'china.shp')) city_layer = shaperead(os.path.join(mapdir, 'res1_4m.shp')) #Read station data f = addfile_micaps(os.path.join(datadir, '10101414.000')) pr = f.stationdata('Precipitation6h') #griddata function - interpolate x = arange(75, 135, 0.5) y = arange(18, 55, 0.5) prg = pr.griddata((x, y), method='idw', radius=3) #Plot axesm() geoshow(bou2_layer, edgecolor='lightgray') geoshow(bou1_layer, facecolor=(0,0,255)) geoshow(city_layer, facecolor='r', size=4, labelfield='NAME', fontname=u'楷体', fontsize=16, yoffset=15) geoshow(china_layer, visible=False) levs = [0.1, 1, 2, 5, 10, 20, 25, 50, 100] cols = [(255,255,255),(170,240,255),(120,230,240),(200,220,50),(240,220,20),(255,120,10),(255,90,10), (240,40,0),(180,10,0),(120,10,0)] layer = contourfm(prg, levs, colors=cols) masklayer(china_layer, [layer]) colorbar(layer) xlim(72, 136) ylim(16, 55) text(95, 52, u'全国降水量实况图', fontname=u'黑体', fontsize=16) text(95, 50, u'(2010-10-14 08:00 至 2010-10-14 14:00)', fontname=u'黑体', fontsize=14) #Add south China Sea sc_layer = bou1_layer.clone() axesm(position=[0.14,0.18,0.15,0.2], axison=False) geoshow(sc_layer, facecolor=(0,0,255)) xlim(106, 123) ylim(2, 23)
脚本程序（Lambert投影）：
#Set data folders basedir = 'D:/MyProgram/Distribution/java/MeteoInfo/MeteoInfo' datadir = os.path.join(basedir, 'sample/MICAPS') mapdir = os.path.join(basedir, 'map') #Read shape files bou2_layer = shaperead(os.path.join(mapdir, 'bou2_4p.shp')) bou1_layer = shaperead(os.path.join(mapdir, 'bou1_4l.shp')) china_layer = shaperead(os.path.join(mapdir, 'china.shp')) city_layer = shaperead(os.path.join(mapdir, 'res1_4m.shp')) #Read station data f = addfile_micaps(os.path.join(datadir, '10101414.000')) pr = f.stationdata('Precipitation6h') #griddata function - interpolate x = arange(75, 135, 0.5) y = arange(18, 55, 0.5) prg = pr.griddata((x, y), method='idw', radius=3) #Plot proj = projinfo(proj='lcc', lon_0=105, lat_1=25, lat_2=47) axesm(projinfo=proj, position=[0, 0, 0.9, 1], axison=False, gridlabel=False, frameon=False) geoshow(bou2_layer, edgecolor='lightgray') geoshow(bou1_layer, facecolor=(0,0,255)) geoshow(city_layer, facecolor='r', size=4, labelfield='NAME', fontname=u'楷体', fontsize=16, yoffset=15) geoshow(china_layer, visible=False) levs = [0.1, 1, 2, 5, 10, 20, 25, 50, 100] cols = [(255,255,255),(170,240,255),(120,230,240),(200,220,50),(240,220,20),(255,120,10),(255,90,10), (240,40,0),(180,10,0),(120,10,0)] layer = contourfm(prg, levs, colors=cols) masklayer(china_layer, [layer]) colorbar(layer, shrink=0.5, aspect=15) axism([78, 130, 14, 53]) text(95, 53, u'全国降水量实况图', fontname=u'黑体', fontsize=18) text(95, 51, u'(2010-10-14 08:00 至 2010-10-14 14:00)', fontname=u'黑体', fontsize=16) #Add south China Sea sc_layer = bou1_layer.clone() axesm(position=[0.1,0.05,0.15,0.2], axison=False) geoshow(sc_layer, facecolor=(0,0,255)) xlim(106, 123) ylim(2, 23)
运行结果：
