WRF后处理：图片美化

MeteoAI

发布于 2021-11-12 16:58:52

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代码可运行

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代码可运行

做WRF后处理软件的过程中主要关注了整体流程拉通和产品输出，画的图片比较粗糙，今天静下心来（被迫营业）慢慢修图，经过小组会议的讨论，总结的问题主要可以归纳为以下几点：

y轴的纬度标签长短不一
省界过于突出
数据分辨率过高，整体不美观
色标标签值太长
图片边缘留白过大

这里以能见度为例：

以下是具体的修改内容：

调整y轴纬度标签格式

; res@pmTickMarkDisplayMode = "Always" 先取消默认的设置
xlonval = ispan(toint(10*res@mpMinLonF),toint(10*res@mpMaxLonF),5) *.1
ylatval = ispan(toint(10*res@mpMinLatF),toint(10*res@mpMaxLatF),5) *.1

res@tmXBMode    = "Explicit"
res@tmXBValues  = xlonval
res@tmXBLabels  = sprintf("%4.1f",xlonval) + "~S~o~N~E"

res@tmYLMode    = "Explicit"
res@tmYLValues  =  ylatval
res@tmYLLabels  =  sprintf("%4.1f",ylatval) + "~S~o~N~N"

调整行政边界

;res@mpOutlineOn           = False   
;>--------------增加行政边界------------------------------<
shp_city                   ="xxx/boundary/city.shp"
city_res                   = True
city_res@gsLineColor       = "DimGray"
city_res@gsLineDashPattern = 0
city_res@gsLineThicknessF  = 2.0
city_plot                  = gsn_add_shapefile_polylines(wks,plot,shp_city,city_res)

shp_prov                   = "xxx/boundary/province.shp"
prov_res                   = True
prov_res@gsLineColor       = "black"
prov_res@gsLineDashPattern = 0
prov_res@gsLineThicknessF  = 3.0
prov_plot                  = gsn_add_shapefile_polylines(wks,plot,shp_prov,prov_res)

数据平滑

wrf_smooth_2d(vis, 9)

数据量级调整&色标标签格式设置

vis = vis / 1000.
res@cnLevels        = (/200, 500, 1000, 1500, 2000, 3000, 4000, 5000, 10000/)  / 1000.
res@lbLabelStrings  = sprintf("%4.1f",res@cnLevels)

添加mark

;>--------------增加站点------------------------------<
mstring    = "z"
fontnum    = 35
xoffset    = 0.0
yoffset    = 0.0625
ratio      = 1.0
size       = 0.5
angle      = 0.0
solidstar  = NhlNewMarker(wks2,mstring,fontnum,xoffset,yoffset,ratio,size,angle)

pmres                = True
pmres@gsMarkerColor  = "red"
pmres@gsMarkerSizeF  = 0.028    
pmres@gsMarkerIndex  = solidstar
plat = xxx
plon = xxx
dum  = gsn_add_polymarker(wks,plot,plon,plat,pmres)

裁减图片白边

这里主要是利用python的PIL库来进行图片白边的裁减

import sys, os
from PIL import Image, ImageOps

def crop_margin(img_fileobj, out, padding=(0, 0, 0, 0)):
    image = Image.open(img_fileobj).convert('RGB')
    ivt_image = ImageOps.invert(image)
    bbox = ivt_image.getbbox()
    left = bbox[0] - padding[0]
    top = bbox[1] - padding[1]
    right = bbox[2] + padding[2]
    bottom = bbox[3] + padding[3]
    cropped_image = image.crop([left, top, right, bottom])
    cropped_image.save(out)
    return 

dirs = r"C:\Users\jiaobf\Desktop\ZJ"
fils = os.listdir(dirs)

for fn in fils:
    if not fn.endswith('png'):continue
    fp = os.path.join(dirs, fn)
    crop_margin(fp,fp)

修改后的图片：