In [1]:
import numpy as np
import sys
import matplotlib.pyplot as plt
import cartopy
import cartopy.crs as ccrs
from metpy.gridding.gridding_functions import (interpolate, remove_nan_observations,
remove_repeat_coordinates)
from metpy.cbook import get_test_data
from matplotlib.colors import BoundaryNorm
%matplotlib inline
plt.rcParams['figure.figsize'] = (15, 10)
In [2]:
def make_string_list(arr):
return [s.decode('ascii') for s in arr]
def station_test_data(variable_names, proj_from=None, proj_to=None):
f = get_test_data('station_data.txt')
all_data = np.loadtxt(f, skiprows=1, delimiter=',',
usecols=(1, 2, 3, 4, 5, 6, 7, 17, 18, 19),
dtype=np.dtype([('stid', '3S'), ('lat', 'f'), ('lon', 'f'),
('slp', 'f'), ('air_temperature', 'f'),
('cloud_fraction', 'f'), ('dewpoint', 'f'),
('weather', '16S'),
('wind_dir', 'f'), ('wind_speed', 'f')]))
all_stids = make_string_list(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']
# lon = lon[~np.isnan(value)]
# lat = lat[~np.isnan(value)]
# value = value[~np.isnan(value)]
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
In [3]:
from_proj = ccrs.Geodetic()
to_proj = ccrs.AlbersEqualArea(central_longitude=-97.0000, central_latitude=38.0000)
levels = list(range(-20, 20, 1))
cmap = plt.get_cmap('magma')
norm = BoundaryNorm(levels, ncolors=cmap.N, clip=True)
x, y, temp = station_test_data("air_temperature", from_proj, to_proj)
x, y, temp = remove_nan_observations(x, y, temp)
x, y, temp = remove_repeat_coordinates(x, y, temp)
In [4]:
gx, gy, img = interpolate(x, y, temp, interp_type='linear', hres=75000)
img = np.ma.masked_where(np.isnan(img), img)
view = plt.axes([0,0,1,1], projection=to_proj)
view.set_extent([-120, -70, 20, 50])
view.add_feature(cartopy.feature.NaturalEarthFeature(
category='cultural',
name='admin_1_states_provinces_lakes',
scale='50m',
facecolor='none'))
view.add_feature(cartopy.feature.OCEAN)
view.add_feature(cartopy.feature.COASTLINE)
view.add_feature(cartopy.feature.BORDERS, linestyle=':')
mmb = view.pcolormesh(gx, gy, img, cmap=cmap, norm=norm)
plt.colorbar(mmb, shrink=.4, pad=0, boundaries=levels)
Out[4]:
In [5]:
gx, gy, img = interpolate(x, y, temp, interp_type='natural_neighbor', hres=75000)
img = np.ma.masked_where(np.isnan(img), img)
view = plt.axes([0,0,1,1], projection=to_proj)
view.set_extent([-120, -70, 20, 50])
view.add_feature(cartopy.feature.NaturalEarthFeature(
category='cultural',
name='admin_1_states_provinces_lakes',
scale='50m',
facecolor='none'))
view.add_feature(cartopy.feature.OCEAN)
view.add_feature(cartopy.feature.COASTLINE)
view.add_feature(cartopy.feature.BORDERS, linestyle=':')
mmb = view.pcolormesh(gx, gy, img, cmap=cmap, norm=norm)
plt.colorbar(mmb, shrink=.4, pad=0, boundaries=levels)
Out[5]:
In [6]:
gx, gy, img = interpolate(x, y, temp, interp_type='cressman', minimum_neighbors=1, hres=75000, search_radius=100000)
img = np.ma.masked_where(np.isnan(img), img)
view = plt.axes([0,0,1,1], projection=to_proj)
view.set_extent([-120, -70, 20, 50])
view.add_feature(cartopy.feature.NaturalEarthFeature(
category='cultural',
name='admin_1_states_provinces_lakes',
scale='50m',
facecolor='none'))
view.add_feature(cartopy.feature.OCEAN)
view.add_feature(cartopy.feature.COASTLINE)
view.add_feature(cartopy.feature.BORDERS, linestyle=':')
mmb = view.pcolormesh(gx, gy, img, cmap=cmap, norm=norm)
plt.colorbar(mmb, shrink=.4, pad=0, boundaries=levels)
Out[6]:
In [7]:
gx, gy, img1 = interpolate(x, y, temp, interp_type='barnes', hres=75000, search_radius=100000)
img1 = np.ma.masked_where(np.isnan(img1), img1)
view = plt.axes([0,0,1,1], projection=to_proj)
view.set_extent([-120, -70, 20, 50])
view.add_feature(cartopy.feature.NaturalEarthFeature(
category='cultural',
name='admin_1_states_provinces_lakes',
scale='50m',
facecolor='none'))
view.add_feature(cartopy.feature.OCEAN)
view.add_feature(cartopy.feature.COASTLINE)
view.add_feature(cartopy.feature.BORDERS, linestyle=':')
mmb = view.pcolormesh(gx, gy, img1, cmap=cmap, norm=norm)
plt.colorbar(mmb, shrink=.4, pad=0, boundaries=levels)
Out[7]:
In [8]:
gx, gy, img = interpolate(x, y, temp, interp_type='rbf', hres=75000, rbf_func='linear', rbf_smooth=0)
img = np.ma.masked_where(np.isnan(img), img)
view = plt.axes([0,0,1,1], projection=to_proj)
view.set_extent([-120, -70, 20, 50])
view.add_feature(cartopy.feature.NaturalEarthFeature(
category='cultural',
name='admin_1_states_provinces_lakes',
scale='50m',
facecolor='none'))
view.add_feature(cartopy.feature.OCEAN)
view.add_feature(cartopy.feature.COASTLINE)
view.add_feature(cartopy.feature.BORDERS, linestyle=':')
mmb = view.pcolormesh(gx, gy, img, cmap=cmap, norm=norm)
plt.colorbar(mmb, shrink=.4, pad=0, boundaries=levels)
Out[8]: