from netCDF4 import Dataset
import numpy as np
import pandas as pd
import os
import matplotlib.pyplot as plt

path = "F:\\OCO2.SIF.all.daily.2001.nc"
csv_path = "F:\\test.csv"
dst = Dataset(path, mode='r', format="netCDF4")

 print(dst.variables.keys())
    data = dst.variables['all_daily_sif'][:]
    print(data.shape)
    # 輸出結(jié)果如下:
    # dict_keys(['lat', 'lon', 'doy', 'all_daily_sif'])
    # (92, 360, 720)
    #可見(jiàn)有92個(gè)時(shí)間序列，經(jīng)度(lon)、緯度(lat)的取值有720,360個(gè)

    # # 查看數(shù)據(jù)經(jīng)緯度范圍，經(jīng)度-179.75~179.75，其中負(fù)值為西經(jīng)，正值為東經(jīng)；緯度正為北緯，負(fù)為南緯
    # # 格點(diǎn)分辨率為0.5度
    long = dst.variables['lon'][:]
    lati = dst.variables['lat'][:]
    print(long[0], long[-1], lati[0], lati[-1])
    print(long.shape, lati.shape)

 # plt對(duì)某個(gè)doy的全球sif值作圖。左半部分為西半球，右邊是東半球
    # 選了doy為10的sif數(shù)據(jù)作圖
    plt.contourf(long, lati, data[10, :, :] )
    plt.colorbar(label="Sif", orientation="horizontal")
    plt.show()

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt

    lat = dst.variables['lat'][:]
    lon = dst.variables['lon'][:]
    data = dst.variables['all_daily_sif'][:]    
    data[10] = data[10]
    # use .shape function to check that arrays have
    # the correct size.
    # e.g. lon.shape
    print(data[10].shape)

    lon0 = lon.mean()
    lat0 = lat.mean()
    # 設(shè)置投影方式：cyl為圓柱投影、還可設(shè)置merc為mercator投影 llcrnrlat為起始lat；urcrnrlat為終止lat
    # m = Basemap(projection='merc', llcrnrlat=lat[0], urcrnrlat=lat[-1], \
    #              llcrnrlon=lon[0], urcrnrlon=lon[-1], ax=ax1)
   # 參數(shù) "resolution" 用于控制地圖面積邊緣的精細(xì)程度，有'l'和'h'兩種取值
    m = Basemap(lat_0=lat0, lon_0=lon0,projection='cyl',resolution='l')
    # 繪制等經(jīng)緯度線 緯度每隔20度畫(huà)一條線，且標(biāo)注經(jīng)緯度
    m.drawparallels(np.arange(-90., 91., 20.), labels=[1, 0, 0, 0], fontsize=10)
    m.drawmeridians(np.arange(-180., 181., 40.), labels=[0, 0, 0, 1], fontsize=10)
    m.drawcoastlines()# 繪制海岸線
    # m.drawcountries(linewidth=0.25)  # 繪制國(guó)界線
    # m.readshapefile('F:\E\data\grass_yield\shp\quhua\\省', 'states')  # 讀取中國(guó)各省邊界，并繪圖

    lon, lat = np.meshgrid(lon, lat)
    xi, yi = m(lon, lat)
    # cmap是顏色，還可選‘jet'、‘spring'、‘winter'、'summer'、'autumn'
    cs = m.contourf(xi, yi, data[10],  cmap='summer')
    # pad指位置，
    cbar = m.colorbar(cs, location='bottom', pad="10%",format='%.1f')
    # cbar = m.colorbar(C, 'right', ticks=np.arange(-128, 128, 40), format='%.1f')
    font1 = {'family': 'DejaVu Sans', 'weight': 'normal', 'size': 16}
    plt.title('CSIF', font1)
    plt.show()