import numpy as np import my_class import matplotlib.pyplot as plt import cartopy.crs as ccrs file = r"D:\lunwen\lunwenshuju\各種作業數據\H500.txt" f = open(file, "r") data = np.loadtxt(file, dtype=str,delimiter='\n') lines = f.readlines() dataset = [] for line in lines:data = line.strip("\n")data = data.split('\t')dataset.append(data) dataset = np.array(dataset) a = np.zeros(48) i = 0 b = 0 while i < 48:a[i] = bi = i+1b = b+18 a = a.astype(int) # 化為整數 dataset = np.delete(dataset, a, axis=0) # 刪除空格 # 建立一個37*17*48的三維數組 hgt = np.zeros((17, 37, 48)) # 將二維變成三維 for k in range(48):for i in range(17):c = dataset[i][0]c = c.replace(" ", "")w = 6for j in range(37):hgt[i, j, k] = float(c[w-6:w])w = w+6 # 對hgt進行處理 # 畫出氣候場 hgt_qihou = hgt.mean(2) # 畫出距平場 hgt_juping = hgt for i in range(48):hgt_juping[:, :, i] = hgt_juping[:,:,i]-hgt_qihou hgt_juping = hgt_juping.mean(2) # 畫出均方差場 hgt_junfangcha = hgt for i in range(48):hgt_junfangcha[:,:,i] =hgt_junfangcha[:,:,i]+np.power((hgt_junfangcha[:,:,i] - hgt_qihou), 2) hgt_junfangcha = hgt_junfangcha.mean(2) hgt_junfangcha = np.sqrt(hgt_junfangcha)hgt_max = np.max(hgt_qihou) # 算出最大值 hgt_min = np.min(hgt_qihou) # 算出最小值 # print(hgt_qihou.shape) # print(hgt_min) # print(hgt_max)# 畫圖 lon = np.arange(60, 150+2.5, 2.5) # 設立經度 lat = np.arange(0, 40+2.5, 2.5) # 設立緯度 lon, lat = np.meshgrid(lon, lat) # 畫圖設置 plt.rcParams.update({'font.size': 13}) # 解決中文亂碼問題 plt.rcParams['font.sans-serif'] = ['KaiTi'] # 解決負號亂碼問題 plt.rcParams['axes.unicode_minus'] = False fig = plt.figure(figsize=[8, 8]) ax = fig.add_subplot(111, projection=ccrs.PlateCarree()) # 設置x, y軸標簽 ax.set_xticks(np.arange(60, 150+7.5, 7.5), crs=ccrs.PlateCarree()) ax.set_yticks(np.arange(0, 40+2.5, 5), crs=ccrs.PlateCarree()) xtick_str = ['60', ' ', '75',' ', '90',' ', '105',' ', '120',' ', '135',' ', '150'] ax.set_xticklabels(xtick_str, fontsize=18) ytick_str = ['0', ' ', '10', ' ', '20', ' ', '30', ' ', '40'] ax.set_yticklabels(ytick_str, fontsize=18) my_class.readshapefile(r"D:\lunwen\lunwenshuju\Shp\ocean_shp\Pacific\Export_Output_5.shp", linewidth=1, ax=ax) # 太平洋 my_class.readshapefile(r"D:\lunwen\lunwenshuju\Shp\ne_10m_admin_0_countries\ne_10m_admin_0_countries.shp", linewidth=1, ax=ax) #世界地圖 my_class.readshapefile(r"D:\lunwen\lunwenshuju\Shp\ocean_shp\Indian\iho.shp", linewidth=1, ax=ax) # 印度洋 my_class.readshapefile(r"D:\lunwen\lunwenshuju\Shp\china\china.shp", linewidth=1, ax=ax) levels = np.arange(5310, 5890, 1) precipRateESurface_conf = ax.contourf(lon, lat, hgt_qihou, cmap='RdBu_r', extend='both', levels=levels) T_cb = fig.colorbar(precipRateESurface_conf, orientation='vertical', shrink=0.75) # 標簽字體設置 font = {'family': 'Times New Roman','weight': 'normal','size': 20 } T_cb.set_label("gpm", fontdict=font) ax.set_title("500hP高度場的氣候場") plt.show()

dat數據將后綴改成txt后長這樣：

?上面沒有經緯度，只有對應經緯度的數據，因此先進行數據處理。

思路：首先每行讀取數據按照經緯度，數據是由北向南，由西向東的。通過np.delete()刪除每行年份和月份。然后將字符轉化成數字讀取轉化成三維數據，最后進行數據處理后繪圖就行

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