绘图

PPI绘图不叠加地图：

from pycwr.io import read_auto
import matplotlib.pyplot as plt
from pycwr.draw.RadarPlot import Graph

filename = r"./data/Z_RADR_I_Z9898_20190828181529_O_DOR_SAD_CAP_FMT.bin.bz2"
PRD = read_auto(filename)
fig, ax = plt.subplots()
graph = Graph(PRD)
graph.plot_ppi(ax, 0, "dBZ", cmap="CN_ref") ## 0代表第一层, dBZ代表反射率产品
graph.add_rings(ax, [0, 50, 100, 150, 200, 250, 300])
ax.set_title("PPI Plot", fontsize=16)
ax.set_xlabel("Distance From Radar In East (km)", fontsize=14)
ax.set_ylabel("Distance From Radar In North (km)", fontsize=14)
plt.show()

PPI绘图叠加地图：

from pycwr.io import read_auto
import matplotlib.pyplot as plt
from pycwr.draw.RadarPlot import GraphMap
import cartopy.crs as ccrs
filename = r"./data/Z_RADR_I_Z9898_20190828181529_O_DOR_SAD_CAP_FMT.bin.bz2"
PRD = read_auto(filename)

ax = plt.axes(projection=ccrs.PlateCarree())
graph = GraphMap(PRD, ccrs.PlateCarree())
graph.plot_ppi_map(ax, 0, "dBZ", cmap="CN_ref") ## 0代表第一层, dBZ代表反射率产品，cmap
ax.set_title("PPI Plot with Map", fontsize=16)
plt.tight_layout()
plt.show()

雷达RHI绘图:

from pycwr.io import read_auto
import matplotlib.pyplot as plt
from pycwr.draw.RadarPlot import Graph

filename = r"./data/NUIST.20170323.142921.AR2"
PRD = read_auto(filename)

fig, ax = plt.subplots()
graph = Graph(PRD)
graph.plot_rhi(ax, 0, field_name="dBZ", cmap="CN_ref", clabel="Radar Reflectivity")
ax.set_ylim([0, 10]) #设置rhi的高度范围 （units：km）
ax.set_xlabel("distance from radar (km)", fontsize=14)
ax.set_ylabel("Height (km)", fontsize=14)
plt.tight_layout()
plt.show()

天气雷达剖面图：

from pycwr.io import read_auto
import matplotlib.pyplot as plt
from pycwr.draw.RadarPlot import Graph

filename = r"./data/Z_RADR_I_Z9898_20190828181529_O_DOR_SAD_CAP_FMT.bin.bz2"
PRD = read_auto(filename)

fig, ax = plt.subplots()
graph = Graph(PRD)
graph.plot_vcs(ax, (0,0), (150, 0), "dBZ", cmap="copy_pyart_NWSRef") #起点，终点 （units: km）
ax.set_ylim([0, 15])
ax.set_xlim([0, 80])
ax.set_ylabel("Height (km)", fontsize=14)
ax.set_xlabel("Distance From Section Start (Uints:km)", fontsize=14)
ax.set_title("VCS Plot", fontsize=16)
plt.tight_layout()
plt.show()