?1. 導(dǎo)入庫

import cartopy
import numpy as np
import pandas as pd
import proplot as pplt
import geopandas as gpd
import matplotlib.pyplot as plt
from proplot import rc
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import matplotlib.path as mpath
import cmaps
seis = cmaps.GMT_seis

# 導(dǎo)出指北針的庫
import gma
import gma.extend.mapplottools as mpt
import gma.extend.arrayenhancement as aec

# 導(dǎo)入自定義色帶
from colormaps import parula

rc["font.family"] = "TeX Gyre Schola"
rc['tick.labelsize'] = 10
rc["axes.labelsize"] = 12
rc["axes.labelweight"] = "light"
rc["tick.labelweight"] = "light"

2. 導(dǎo)入數(shù)據(jù)

# 加載數(shù)據(jù)
import geopandas as gpd
file = r".\China map\中國(guó)省級(jí)地圖GS（2019）1719號(hào).geojson"
nine = r".\China map\九段線GS（2019）1719號(hào).geojson"
china_main = gpd.read_file(file)
china_nine = gpd.read_file(nine)
china_main.head()

china_shp = "./nc data/Data_ipynb/country1"

from netCDF4 import Dataset 
import xarray as xr
nc_file = r".\nc data\EC-Interim_monthly_2018.nc" 
ds = xr.open_dataset(nc_file) 
lat = ds.latitude 
lon = ds.longitude 
data = (ds['t2m'][0,::-1,:] - 273.15) # 把溫度轉(zhuǎn)換為℃

3. 南海九段線部分?jǐn)?shù)據(jù)預(yù)處理

開始繪圖之前需進(jìn)行數(shù)據(jù)選擇，即中國(guó)區(qū)域的數(shù)據(jù)，特別是繪制南海小地圖的更需要，可避免一些問題(小地圖上方出現(xiàn)完整地圖)

#中國(guó)整體范圍
lon_range1=lon[(lon>=70)&(lon<=138)]
lat_range1=lat[(lat>=3)&(lat<=55)]
#南海九段線范圍
lon_range2=lon[(lon>=104)&(lon<=125)]
lat_range2=lat[(lat>=0)&(lat<=27)]

china_full = data.sel(longitude=lon_range1,latitude=lat_range1)
china_sub = data.sel(longitude=lon_range2,latitude=lat_range2)


china_full_lon = china_full.longitude.values
china_full_lat = china_full.latitude.values
china_full_data = china_full.values

china_sub_lon = china_sub.longitude.values
china_sub_lat = china_sub.latitude.values
china_sub_data = china_sub.values

levels = np.arange(-25, 25 + 1, 1)  

4. 定義掩膜方法，從全球的nc數(shù)據(jù)中，裁出中國(guó)地圖部分的數(shù)據(jù)（根據(jù)shp文件裁剪nc數(shù)據(jù)）

def maskout_areas(originfig, ax, shp_path, proj=None):
    import shapefile
    import cartopy.crs as ccrs
    from matplotlib.path import Path
    #from cartopy.mpl.clip_path
    from matplotlib.patches import PathPatch
    #sf = shapefile.Reader(shp_path)
    sf = shapefile.Reader(shp_path,encoding='gbk')
    vertices = []
    codes = []
    for shape_rec in sf.shapeRecords():
        if shape_rec.record[2] == 'China':
            pts = shape_rec.shape.points
            prt = list(shape_rec.shape.parts) + [len(pts)]
            for i in range(len(prt) - 1):
                for j in range(prt[i], prt[i + 1]):
                    if proj:
                        vertices.append(proj.transform_point(pts[j][0], pts[j][1], ccrs.Geodetic()))
                    else:
                        vertices.append((pts[j][0], pts[j][1]))
                codes += [Path.MOVETO]
                codes += [Path.LINETO] * (prt[i + 1] - prt[i] - 2)
                codes += [Path.CLOSEPOLY]
            clip = Path(vertices, codes)
            clip = PathPatch(clip, transform=ax.transData)
    for contour in originfig.collections:
        contour.set_clip_path(clip)

5. 繪制填色地圖

levels = np.arange(-25, 25 + 1, 1)  

projn = ccrs.LambertConformal(central_longitude=107.5, 
                              central_latitude=36,
                              standard_parallels=(25.0, 47.0)
                            )
fig = plt.figure(figsize=(4,3.5),dpi=120,facecolor="w")
ax = fig.add_subplot(projection=projn)
# cs = data.plot.contourf(ax=ax,levels=levels,cbar_kwargs=cbar_kwargs,
#                         cmap=parula,transform=ccrs.PlateCarree(),
#                        )
#自定義colorbar 參數(shù)
cs = china_full.plot.contourf(ax=ax,levels=levels,add_colorbar=False,
                        cmap=parula,transform=ccrs.PlateCarree(),
                       )
# #basemask(ax=ax, cs=cs,shp=china_shp)
maskout_areas(originfig=cs,ax=ax,shp_path=china_shp,proj=projn)

ax.set_facecolor('#BEE8FF')
ax.spines['geo'].set_linewidth(0.5)
#ax.stock_img()
ax.set_extent([80, 130, 16, 52.5], crs=ccrs.PlateCarree())
ax.coastlines(linewidth=0.3,zorder=20)
ax.add_feature(cfeature.LAND, facecolor='white')
ax.add_feature(cfeature.LAKES.with_scale('110m'), facecolor='#BEE8FF')
#添加geopandas 讀取的地理文件
ax.add_geometries(china_main["geometry"],crs=ccrs.PlateCarree(),
                  fc="None",ec="k",linewidth=.2)
ax.add_geometries(china_nine["geometry"],crs=ccrs.PlateCarree(),
                  fc="None",ec="black",linewidth=.3)
#設(shè)置標(biāo)題
ax.set_title("Example Of China Lambert Projection")
gls = ax.gridlines(draw_labels=True, crs=ccrs.PlateCarree(), 
                   color='gray', linestyle='dashed', linewidth=0.2, 
                   y_inline=False, x_inline=False,
                   rotate_labels=0,xpadding=5,
                   xlocs=range(-180,180,10), ylocs=range(-90,90,5),
                   xlabel_style={"size":8,"weight":"bold"},
                   ylabel_style={"size":8,"weight":"bold"}
                  )
gls.top_labels= False                      
gls.right_labels=False

#添加南海小地圖
# 定位南海子圖的位置，四個(gè)數(shù)字需要調(diào)整
# 四個(gè)數(shù)字分別是(left, bottom, width, height)：
# 子圖左下角水平方向相對(duì)位置，左下角垂直方向相對(duì)位置，子圖寬，子圖高
ax2 = fig.add_axes([0.74, 0.24, 0.1, 0.25], projection = projn)
ax2.set_extent([104.5, 124, 0, 26],crs=ccrs.PlateCarree())
#ax2.set(xlim=(104.5, 125),ylim=(0, 26))
ax2.set_facecolor('#BEE8FF')
ax2.spines['geo'].set_linewidth(0.4)

cs2 = china_sub.plot.contourf(ax=ax2,levels=levels,add_colorbar=False,
                        cmap=parula,transform=ccrs.PlateCarree(),
                       )
#basemask(ax=ax2, cs=cs2,shp=china_shp)
maskout_areas(originfig=cs2,ax=ax2,shp_path=china_shp,proj=projn)
ax2.set_title("")

# 設(shè)置網(wǎng)格點(diǎn)
lb=ax2.gridlines(draw_labels=False,x_inline=False, y_inline=False,
                 linewidth=0.1, color='gray', alpha=0.8, 
                 linestyle='--' )
ax2.add_geometries(china_main["geometry"],crs=ccrs.PlateCarree(),
                  fc="None",ec="k",linewidth=.3)
ax2.add_geometries(china_nine["geometry"],crs=ccrs.PlateCarree(),
                  fc="None",ec="black",linewidth=.5)
ax2.add_feature(cfeature.LAND, facecolor='w')

## n.1 添加指北針
mpt.AddCompass(ax, LOC = (0.07, 0.86), SCA = 0.04, FontSize = 8)
## n.2 添加比例尺
mpt.AddScaleBar(ax, LOC = (0.2, 0.05), SCA = 0.12, FontSize = 6, 
                UnitPad = 0.2, BarWidth = 0.6)

cbar = fig.colorbar(cs,ax=ax,orientation='horizontal',
                    shrink=0.65,aspect=25,pad=.08)
cbar.ax.tick_params(labelsize=7.5,direction="in")
cbar.ax.tick_params(which="minor",direction="in")
#cbar.ax.xaxis.set_ticks_position('top')
cbar.set_label("Temperature (℃)",fontsize=9)
#cbar.ax.set_title("Sea Surface Temperature(m)",fontsize=9)
cbar.outline.set_linewidth(.4)
#plt.tight_layout()

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