Python – Path Diagram of Plateau Vortex or Typhoon Movement

Python – Plateau Vortex or Typhoon

Movement Path Diagram

–Complete code at the end

Author: Eighth Galaxy – Xin Meier~

Contact Email: [email protected]

Import Library Functions

importnumpy as np

import cartopy

import cartopy.crs as ccrs

import cartopy.feature as cfeature

from cartopy.io.shapereader import Reader

import cartopy.feature as cfeature

from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter

from cartopy.io.shapereader import Reader

import cartopy.crs as ccrs

import cartopy.feature as cfeature

import matplotlib.pyplot as plt

import cartopy.mpl.ticker as cticker

import cartopy.io.shapereader as shpreader

Define Background for Path Diagram

def contour_map(fig,img_extent,spec): fig.set_extent(img_extent,crs=ccrs.PlateCarree()) fig.add_feature(cfeature.COASTLINE.with_scale(’50m’))# Add coastline fig.add_feature(cfeature.LAKES,alpha=0.5)# Add lakes and adjust transparency

#fig.add_feature(cfeature.LAND) fig.set_xticks(np.arange(leftlon,rightlon+spec,spec),crs=ccrs.PlateCarree())# Set X-axis ticks and intervals fig.set_yticks(np.arange(lowerlat,upperlat+spec,spec),crs=ccrs.PlateCarree())# Set Y-axis ticks and intervals lon_formatter=cticker.LongitudeFormatter() lat_formatter=cticker.LatitudeFormatter() fig.xaxis.set_major_formatter(lon_formatter)

fig.yaxis.set_major_formatter(lat_formatter)

Read Qinghai-Tibet Plateau SHP File

reader = cartopy.io.shapereader.Reader(‘D:\PAPER\date\qingzhangshp\qingzang.shp’)# Read file

# Input the latitude and longitude of the plateau vortex (for large datasets, it is recommended to read directly from the file)

x=np.array([89.05,96.47,99.89,100.08,102.05,105.01,107.49,108.66,110.91,111.46,113.93,114.00,120.00,121.97,122.02,122.97,123.49,124.05,122.99])

y=np.array([36.02,34.99,34.98,34.56,35.00,34.99,35.02,36.66,35.56,36.42,36.00,35.90,36.00,37.00,38.00,39.00,40.00,42.00,42.99])

Create Canvas

fig=plt.figure(figsize=(20,18))

proj=ccrs.PlateCarree(central_longitude=90)# Determine the central longitude of the canvas

leftlon,rightlon,lowerlat,upperlat=(70,140,0,45)# Determine the longitude and latitude range of the canvas

img_extent=[leftlon,rightlon,lowerlat,upperlat]

ax=fig.add_axes([0.1,0.1,0.4,0.3],projection=proj)

contour_map(ax,img_extent,10)

Mark the Range of the Qinghai-Tibet Plateau

provinces = cartopy.feature.ShapelyFeature(reader.geometries(),crs=ccrs.PlateCarree(),edgecolor=’k’,facecolor=’w’,alpha=0.4)# Adjust boundary color, fill color, and transparency

ax.add_feature(provinces, linewidth=0.9, zorder=2)# Adjust line width

ax.plot(x1,y1,linewidth=2,transform=ccrs.PlateCarree())# Draw the trajectory line of the plateau vortex

ax.scatter(x1,y1,transform=ccrs.PlateCarree())# Plot the positions of the plateau vortex at different times

plt.savefig(‘road2.png’,dpi=500)# Set image save location, format, and precision

plt.show()

Trajectory Diagram

Scan to join the group!

# Trajectory Diagram
# Import Library Functions
import numpy as np
import cartopy
import cartopy.crs as ccrs
import cartopy.feature as cfeature
from cartopy.io.shapereader import Reader
import cartopy.feature as cfeature
from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter
from cartopy.io.shapereader import Reader
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import matplotlib.pyplot as plt
import cartopy.mpl.ticker as cticker
import cartopy.io.shapereader as shpreader

def contour_map(fig,img_extent,spec):
    fig.set_extent(img_extent,crs=ccrs.PlateCarree())
    fig.add_feature(cfeature.COASTLINE.with_scale('50m'))# Add coastline
    fig.add_feature(cfeature.LAKES,alpha=0.5)# Add lakes and adjust transparency
    #fig.add_feature(cfeature.LAND)

    fig.set_xticks(np.arange(leftlon,rightlon+spec,spec),crs=ccrs.PlateCarree())# Set X-axis ticks and intervals
    fig.set_yticks(np.arange(lowerlat,upperlat+spec,spec),crs=ccrs.PlateCarree())# Set Y-axis ticks and intervals
    lon_formatter=cticker.LongitudeFormatter()
    lat_formatter=cticker.LatitudeFormatter()
    fig.xaxis.set_major_formatter(lon_formatter)
    fig.yaxis.set_major_formatter(lat_formatter)

# Read Qinghai-Tibet Plateau SHP file
reader = cartopy.io.shapereader.Reader('D:\PAPER\date\qingzhangshp\qingzang.shp')# Read file
# Input the latitude and longitude of the plateau vortex (for large datasets, it is recommended to read directly from the file)
x=np.array([89.05,96.47,99.89,100.08,102.05,105.01,107.49,108.66,110.91,111.46,113.93,114.00,120.00,121.97,122.02,122.97,123.49,124.05,122.99])
y=np.array([36.02,34.99,34.98,34.56,35.00,34.99,35.02,36.66,35.56,36.42,36.00,35.90,36.00,37.00,38.00,39.00,40.00,42.00,42.99])


# Create Canvas
fig=plt.figure(figsize=(20,18))
proj=ccrs.PlateCarree(central_longitude=90)# Determine the central longitude of the canvas
leftlon,rightlon,lowerlat,upperlat=(70,140,0,45)# Determine the longitude and latitude range of the canvas
img_extent=[leftlon,rightlon,lowerlat,upperlat]
ax=fig.add_axes([0.1,0.1,0.4,0.3],projection=proj)
contour_map(ax,img_extent,10)


# Mark the Range of the Qinghai-Tibet Plateau
provinces = cartopy.feature.ShapelyFeature(reader.geometries(),crs=ccrs.PlateCarree(),edgecolor='k',facecolor='w',alpha=0.4)# Adjust boundary color, fill color, and transparency
ax.add_feature(provinces, linewidth=0.9, zorder=2)# Adjust line width
ax.plot(x1,y1,linewidth=2,transform=ccrs.PlateCarree())# Draw the trajectory line of the plateau vortex
ax.scatter(x1,y1,transform=ccrs.PlateCarree())# Plot the positions of the plateau vortex at different times

plt.savefig('road2.png',dpi=500)# Set image save location, format, and precision
plt.show()

Editor: myp