问使用Metpython和底图进行点插值

EN

# Copyright (c) 2016 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""   
[Point_Interpolation](https://unidata.github.io/MetPy/latest/examples/gridding/Point_Interpolation.html?highlight=basic_map)

"""

import cartopy.crs as ccrs
import cartopy.feature as cfeature
from matplotlib.colors import BoundaryNorm
import matplotlib.pyplot as plt
from matplotlib import cm as CM
from mpl_toolkits.basemap import Basemap
from matplotlib.patches import Polygon
from metpy.cbook import get_test_data
from metpy.gridding.gridding_functions import (interpolate, remove_nan_observations,
                                               remove_repeat_coordinates)
import pandas as pd
import numpy as np
import numpy.ma as ma

def basic_map(proj):
    """Make our basic default map for plotting"""
    fig = plt.figure(figsize=(15, 10))
    #add_metpy_logo(fig, 0, 80, size='large')
    view = fig.add_axes([0, 0, 1, 1], projection=proj)
    view.set_extent([100, 130, 20, 50])
    view.add_feature(cfeature.STATES.with_scale('50m'))
    view.add_feature(cfeature.OCEAN)
    view.add_feature(cfeature.COASTLINE)
    view.add_feature(cfeature.BORDERS, linestyle=':')
    return fig, view

def station_test_data(variable_names, proj_from=None, proj_to=None):
    #with get_test_data('station_data.txt') as f:
    all_data = np.loadtxt('2016072713.000', skiprows=1,
    #     all_data = np.loadtxt(f, skiprows=1,delimiter=',',
    
                              usecols=(0,1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11),
                              dtype=np.dtype([('stid', '5S'), ('lat', 'f'), ('lon', 'f'),
                                              ('aqi', 'f'), ('grade', 'f'),
                                              ('pm25', 'f'), ('pm10', 'f'),
                                              ('co', 'f'),('no2','f'),('o3','f'),
                                              ('o38h', 'f'), ('so2', 'f')]))
   
    all_stids = [s.decode('ascii') for s in all_data['stid']]
    data = np.concatenate([all_data[all_stids.index(site)].reshape(1, ) for site in all_stids])

    value = data[variable_names]
    lon = data['lon']
    lat = data['lat']

    if proj_from is not None and proj_to is not None:

        try:

            proj_points = proj_to.transform_points(proj_from, lon, lat)
            return proj_points[:, 0], proj_points[:, 1], value

        except Exception as e:

            print(e)
            return None

    return lon, lat, value
def remove_inf_x(x, y, z):
    x_ = x[~np.isinf(x)]
    y_ = y[~np.isinf(x)]
    z_ = z[~np.isinf(x)]

    return x_, y_, z_
def remove_inf_y(x, y, z):
    x_ = x[~np.isinf(y)]
    y_ = y[~np.isinf(y)]
    z_ = z[~np.isinf(y)]

    return x_, y_, z_

def plot_rec(map,lower_left,upper_left,upper_right,lower_right,text):
    lon_poly = np.array([lower_left[0], upper_left[0],upper_right[0], lower_right[0]])
    lat_poly = np.array([lower_left[1], upper_left[1],upper_right[1], lower_right[1]])
    X, Y  = map(lon_poly, lat_poly)
    xy = np.vstack([X,Y]).T

    poly = Polygon(xy, closed=True, \
            facecolor='None',edgecolor='red', \
            linewidth=1.\
            )
    ax, ay = map(lower_left[0],lower_left[1])
    plt.text(ax, ay,text,fontsize=6,fontweight='bold',
                    ha='left',va='bottom',color='k')
    plt.gca().add_patch(poly)

from_proj = ccrs.Geodetic()
to_proj = ccrs.AlbersEqualArea(central_longitude=110.0000, central_latitude=32.0000)
x, y, temp = station_test_data('pm25', from_proj, to_proj)

x, y, temp = remove_nan_observations(x, y, temp)
x, y, temp = remove_inf_x(x, y, temp)
x, y, temp = remove_inf_y(x, y, temp)
x, y, temp = remove_repeat_coordinates(x, y, temp)

###########################################

gx, gy, img1 = interpolate(x, y, temp, interp_type='barnes', hres=75000, search_radius=100000)
img1 = np.ma.masked_where(np.isnan(img1), img1)

fig = plt.figure(figsize=(8, 8))
#fig, view = basic_map(to_proj)
m = Basemap(width=8000000,height=7000000,
            resolution='l',projection='aea',\
            lat_1=0.,lat_2=40,lon_0=110,lat_0=20)
#m.shadedrelief()
m.drawparallels(np.arange(20.,40,2.5),linewidth=1, dashes=[4, 2], labels=[1,0,0,0], color= 'gray',zorder=0, fontsize=10)
m.drawmeridians(np.arange(100.,125.,2.),linewidth=1, dashes=[4, 2], labels=[0,0,0,1], color= 'gray',zorder=0, fontsize=10)
m.readshapefile('dijishi_2004','state',color='gray')
levels = list(range(0, 200, 10))
cmap = plt.get_cmap('viridis')
norm = BoundaryNorm(levels, ncolors=cmap.N, clip=True)
mmb = m.pcolormesh(gx, gy, img1, cmap=cmap, norm=norm)
plt.colorbar(label=r'$PM_{2.5}(\mu g/m^3 $)') 
plt.show()