plot(lon,lat,linewidth=2) s1 = ax1.scatter(lon,lat,c=pressure,s=(level+1)*13,cmap='Reds_r',vmax=1050,vmin=900,alpha=1) fig.colorbar(s1,ax=ax1,fraction=0.04) #绘制台风路径 ax2 = fig.add_subplot(1,2,2, projection=ccrs
在地图上绘制一个点 通常使用 plot 方法在地图上添加一个点: from mpl_toolkits.basemap import Basemap import matplotlib.pyplot as...plt map = Basemap(projection='ortho', lat_0=0, lon_0=0) map.drawmapboundary(fill_color...', lat_0=0, lon_0=3, llcrnrlon=1.819757266426611, llcrnrlat......
lat_0=0, lon_0=0) #Fill the globe with a blue color map.drawmapboundary(fill_color='aq...
接下来设置 curve 函数,进而使用 .FuncAnimation 让它动起来: def buildmebarchart(i=int): plt.legend(df1.columns) p = plt.plot(df1[:i].index, df1[:i].values) #note it only returns the dataset, up to the point i for i in range(0,4): p[i].set_color(color[i]) #set the colour...
#将插值网格数据整理 df_grid =pd.DataFrame(dict(long=xgrid.flatten(),lat=ygrid.flatten())) #这里将数组转成列表 grid_lon_list = df_grid["long"].tolist() grid_lat_list = df_grid["lat"].tolist() pm_idw = IDW(know_lon,know_lat,know_z,grid_lon_list,grid_lat_list) IDW_grid_df...
%matplotlib inline %config InlineBackend.figure_format = 'retina' import matplotlib.pyplot as plt import numpy as np x = np.linspace(0,1,300) for w in range(2,6,2): plt.plot(x, np.sin(np.pi*x)*np.sin(2*w*np.pi*x)) <Figure size 640x480 with 1 Axes> ...
lat, lon = cities['latd'], cities['longd'] population, area = cities['population_total'], cities['area_total_km2'] # 将点绘制为散点图,使用尺寸和颜色,但没有标签 plt.scatter(lon, lat, label=None, c=np.log10(population), cmap='viridis', ...
1#将插值网格数据整理2df_grid =pd.DataFrame(dict(long=xgrid.flatten(),lat=ygrid.flatten()))3#这里将数组转成列表4grid_lon_list = df_grid["long"].tolist()5grid_lat_list = df_grid["lat"].tolist()67pm_idw =IDW(know_lon,know_lat,know_z,grid_lon_list,grid_lat_list)8IDW_grid_...
ax.plot(xx, np.sin(xx))# 于 offset 处新建一条纵坐标offset = (40,0) new_axisline = ax.get_grid_helper().new_fixed_axis ax.axis["新建2"] = new_axisline(loc="right", offset=offset, axes=ax) ax.axis["新建2"].label.set_text("新建纵坐标") ...
plt.plot(x, np.sin(x -4), color=(1.0,0.2,0.3))# RGB元组的颜色值,每个值介于0-1 plt.plot(x, np.sin(x -5), color='chartreuse');# 能支持所有HTML颜色名称值 如果没有指定颜色,Matplotlib 会在一组默认颜色值中循环使用来绘制每一...