'''
created by: my friend shenXie

'''

import numpy as np
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import matplotlib.pyplot as plt
from eofs.standard import Eofa
import xarray as xr
from cartopy.mpl import ticker

#读取数据
path="D:\Date\SSTA\sst3.nc"
SST=xr.open_dataset(path).sel(latitude=slice(66,-20),longitude=slice(120,270),time=slice("2014","2015"))
sst1=SST.sst[:]
sst2=np.array(sst1)
lat=SST.latitude[:]
lon=SST.longitude[:]
 
 
sst=np.array(sst1)
ano=sst1.groupby('time.month')-sst1.groupby('time.month').mean('time', skipna=True)
ano1=np.array(ano)

#计算纬度权重
lat=np.array(lat)
coslat=np.cos(np.deg2rad(lat))
wgts = np.sqrt(coslat)[..., np.newaxis]
#创建EOF分解器
solver=Eof(ano1,weights=wgts)
eof=solver.eofsAsCorrelation(neofs=4)
pc=solver.pcs(npcs=4,pcscaling=1)
var=solver.varianceFraction(neigs=4)
 
fig=plt.figure(figsize=(15,15))
proj=ccrs.PlateCarree(central_longitude=180)
leftlon,rightlon,lowerlat,upperlat=(120,270,-20,66)
lon_formatter=ticker.LongitudeFormatter()
lat_formatter=ticker.LatitudeFormatter()
# 绘制第一模态
fig_ax1=fig.add_axes([0.1,0.95,0.5,0.3],projection=proj)
fig_ax1.set_extent([leftlon,rightlon,lowerlat,upperlat],crs=ccrs.PlateCarree())
fig_ax1.add_feature(cfeature.OCEAN,edgecolor='black')
fig_ax1.add_feature(cfeature.LAKES,alpha=0.5)
fig_ax1.add_feature(cfeature.COASTLINE,lw=1)
fig_ax1.set_xticks(np.arange(leftlon,rightlon,20),crs=ccrs.PlateCarree())
fig_ax1.set_yticks(np.arange(lowerlat,upperlat+5,5),crs=ccrs.PlateCarree())
fig_ax1.xaxis.set_major_formatter(lon_formatter)
fig_ax1.yaxis.set_major_formatter(lat_formatter)
rivers_110m = cfeature.NaturalEarthFeature('physical', 'rivers_lake_centerlines', '110m')
fig_ax1.set_title('(a) EOF1(HadISSTA from 1979-2004)',loc='left',fontsize =15)
fig_ax1.set_title( '%.2f%%' % (var[0]*100),loc='right',fontsize =15)
c1=fig_ax1.contourf(lon,lat, eof[0,:,:], levels=np.arange(-0.9,1.0,0.1     ), zorder=0, extend = 'both',transform=ccrs.PlateCarree(), cmap=plt.cm.RdBu_r)
 
fig_ax2=fig.add_axes([0.1,0.7,0.5,0.3],projection=proj)
fig_ax2.set_extent([leftlon,rightlon,lowerlat,upperlat],crs=ccrs.PlateCarree())
fig_ax2.add_feature(cfeature.OCEAN,edgecolor='black')
fig_ax2.add_feature(cfeature.LAKES,alpha=0.5)
fig_ax2.add_feature(cfeature.COASTLINE,lw=1)
fig_ax2.set_xticks(np.arange(leftlon,rightlon,20),crs=ccrs.PlateCarree())
fig_ax2.set_yticks(np.arange(lowerlat,upperlat+5,5),crs=ccrs.PlateCarree())
fig_ax2.xaxis.set_major_formatter(lon_formatter)
fig_ax2.yaxis.set_major_formatter(lat_formatter)
rivers_110m = cfeature.NaturalEarthFeature('physical', 'rivers_lake_centerlines', '110m')
fig_ax2.set_title('(c) EOF2(HadISSTA from 1979-2004)',loc='left',fontsize =15)
fig_ax2.set_title( '%.2f%%' % (var[1]*100),loc='right',fontsize =15)
c2=fig_ax2.contourf(lon,lat, eof[1,:,:], levels=np.arange(-0.9,1.0,0.1), zorder=0, extend = 'both',transform=ccrs.PlateCarree(), cmap=plt.cm.RdBu_r)
 
fig_ax3=fig.add_axes([0.1,0.45,0.5,0.3],projection=proj)
fig_ax3.set_extent([leftlon,rightlon,lowerlat,upperlat],crs=ccrs.PlateCarree())
fig_ax3.add_feature(cfeature.OCEAN,edgecolor='black')
fig_ax3.add_feature(cfeature.LAKES,alpha=0.5)
fig_ax3.add_feature(cfeature.COASTLINE,lw=1)
fig_ax3.set_xticks(np.arange(leftlon,rightlon,20),crs=ccrs.PlateCarree())
fig_ax3.set_yticks(np.arange(lowerlat,upperlat+5,5),crs=ccrs.PlateCarree())
fig_ax3.xaxis.set_major_formatter(lon_formatter)
fig_ax3.yaxis.set_major_formatter(lat_formatter)
rivers_110m = cfeature.NaturalEarthFeature('physical', 'rivers_lake_centerlines', '110m')
fig_ax3.set_title('(e) EOF3(HadISSTA from 1979-2004)',loc='left',fontsize =15)
fig_ax3.set_title( '%.2f%%' % (var[2]*100),loc='right',fontsize =15)
c3=fig_ax3.contourf(lon,lat, eof[2,:,:], levels=np.arange(-0.9,1.0,0.1), zorder=0, extend = 'both', transform=ccrs.PlateCarree(), cmap=plt.cm.RdBu_r)
 
fig_ax4=fig.add_axes([0.1,0.2,0.5,0.3],projection=proj)
fig_ax4.set_extent([leftlon,rightlon,lowerlat,upperlat],crs=ccrs.PlateCarree())
fig_ax4.add_feature(cfeature.OCEAN,edgecolor='black')
fig_ax4.add_feature(cfeature.LAKES,alpha=0.5)
fig_ax4.add_feature(cfeature.COASTLINE,lw=1)
fig_ax4.set_xticks(np.arange(leftlon,rightlon,20),crs=ccrs.PlateCarree())
fig_ax4.set_yticks(np.arange(lowerlat,upperlat+5,5),crs=ccrs.PlateCarree())
fig_ax4.xaxis.set_major_formatter(lon_formatter)
fig_ax4.yaxis.set_major_formatter(lat_formatter)
rivers_110m = cfeature.NaturalEarthFeature('physical', 'rivers_lake_centerlines', '110m')
fig_ax4.set_title('(g) EOF4(HadISSTA from 1979-2004)',loc='left',fontsize =15)
fig_ax4.set_title( '%.2f%%' % (var[3]*100),loc='right',fontsize =15)
c4=fig_ax4.contourf(lon,lat, eof[3,:,:], levels=np.arange(-0.9,1.0,0.1), zorder=0, transform=ccrs.PlateCarree(), cmap=plt.cm.RdBu_r)
 
cbposition=fig.add_axes([0.1, 0.2, 0.5, 0.015])
fig.colorbar(c1,cax=cbposition,orientation='horizontal',format='%.1f')
 
fig_ax5=fig.add_axes([0.65,0.99,0.47,0.2])
fig_ax5.set_title('(b) PC1',loc='left',fontsize = 15)
fig_ax5.set_ylim(-3.5,3.5)
fig_ax5.axhline(0,linestyle="--")
fig_ax5.plot(np.arange(1979,2005,1/12),pc[:,0],color='blue')
 
 
fig_ax6 = fig.add_axes([0.65, 0.74, 0.47, 0.2])
fig_ax6.set_title('(d) PC2',loc='left',fontsize = 15)
fig_ax6.set_ylim(-3.5,3.5)
fig_ax6.axhline(0,linestyle="--")
fig_ax6.plot(np.arange(1979,2005,1/12),pc[:,1],color='blue')
 
 
fig_ax7 = fig.add_axes([0.65, 0.49, 0.47, 0.2])
fig_ax7.set_title('(f) PC3',loc='left',fontsize = 15)
fig_ax7.set_ylim(-3.5,3.5)
fig_ax7.axhline(0,linestyle="--")
fig_ax7.plot(np.arange(1979,2005,1/12),pc[:,2],color='blue')
 
fig_ax8 = fig.add_axes([0.65, 0.24, 0.47, 0.2])
fig_ax8.set_title('(h) PC4',loc='left',fontsize = 15)
fig_ax8.set_ylim(-3.5,3.5)
fig_ax8.axhline(0,linestyle="--")
fig_ax8.plot(np.arange(1979,2005,1/12),pc[:,3],color='blue') 
plt.show()
 
fig=plt.figure(figsize=(10,6))
ax=fig.add_axes([0,0,1,1])
 
ax.plot(np.arange(1979,2005,1/12),pc[:,0],linewidth=1,linestyle='-',color='r',label='PC1')
bar=ax.bar(np.arange(1979,2005,1/12),height=pc[:,1],color='blue',align="center",width=0.1,linewidth=0.1,bottom=None,edgecolor='black',label='PC2')
ax.plot(np.arange(1979,2005,1/12),pc[:,2],linestyle='--',linewidth=1,color='black',label='PC3')
ax.set_ylim(-4,4)
ax.set_title("PC")
ax.set_xlabel("Time")
ax.set_ylabel("y")
plt.legend()
plt.grid() 
plt.show()