Мобильная версияОднако, когда я сейчас запускаю тот же код, карты показывают слишком светлую окраску, которая не соответствует ни значениям данных, ни цветовой шкале ( см. изображение ниже справа). Я предполагаю, что это как-то связано с обновлением версии, но не могу понять, как это исправить, чтобы данные отображались на карте правильными цветами.
[img]https: //i.sstatic.net/2qxOKM6N.png[/img]
Если есть более простой способ отобразить значения в логарифмическом масштабе, я тоже прислушиваюсь!Это мой код:
import cartopy.crs as ccrs
import numpy as np
from shapely.geometry import Polygon
import cartopy
from cartopy.io import shapereader
import matplotlib
import pandas
import geopandas
projection = ccrs.Mercator()
transform = ccrs.PlateCarree()
extent = [4.5, 31.9, 54.7, 71.24]
cmap = matplotlib.cm.get_cmap('Reds')
facecolor_landmask = '#f3f8ff'
facecolor_polygon = 'none'
edgecolor_landmask = 'none'
edgecolor_polygon = 'black'
# Get borders
resolution = '10m'
category = 'cultural'
name = 'admin_0_countries'
shpfilename = shapereader.natural_earth(resolution, category, name)
shpfilenamemunicipalities = 'path/to/ScandinaviaKommuner.shp'
# Read the shapefile using geopandas
df = geopandas.read_file(shpfilename)
df2 = geopandas.read_file(shpfilenamemunicipalities)
# Select the countries of interest
scan3 = df[ df['ADMIN'].isin(['Norway', 'Finland', 'Sweden']) ]
scan3_dissolved = scan3.dissolve(by='LEVEL')
poly = [scan3_dissolved['geometry'].values[0]]
# Create the mask
stamen_terrain = cimgt.Stamen('terrain_background')
st_proj = stamen_terrain.crs #projection used by Stamen images
ll_proj = ccrs.PlateCarree()
def rect_from_bound(xmin, xmax, ymin, ymax):
"""Returns list of (x,y)'s for a rectangle"""
xs = [xmax, xmin, xmin, xmax, xmax]
ys = [ymax, ymax, ymin, ymin, ymax]
return [(x, y) for x, y in zip(xs, ys)]
pad1 = .1 #padding, degrees unit
exts = [poly[0].bounds[0] - pad1, poly[0].bounds[2] + pad1, poly[0].bounds[1] - pad1, poly[0].bounds[3] + pad1];
msk = Polygon(rect_from_bound(*exts)).difference(poly[0].simplify(0.01))
msk_stm = st_proj.project_geometry(msk, ll_proj) # project geometry to the projection used by stamen
# Load the .csv data
firedata = pandas.read_csv('/path/to/CountryLevel_FireData.csv', delimiter=';', decimal='.')
firedatamunicipalities = pandas.read_csv('/path/to/MunicipalityLevel_FireData.csv', delimiter=';', decimal='.')
# Subset .csv data
countries = firedata['Country'].tolist()
municipalities = firedatamunicipalities['Municipality'].tolist()
fireextents = firedatamunicipalities['FireIntensity'].tolist()
# Normalise the fire data to between 0 and 1 to extract the colour and log transform
fireextents_log = list(range(0,966))
for fireextent, log in zip(fireextents, fireextents_log):
if fireextent>0:
fireextents_log[log] = np.log(fireextent)
else:
fireextents_log[log] = np.nan
fireextents_norm = (fireextents_log-np.nanmin(fireextents_log))/(np.nanmax(fireextents_log) - np.nanmin(fireextents_log))
# Create a plot
fig, axs = plt.subplots(nrows = 1, ncols = 1,
subplot_kw = {'projection': projection},
layout='constrained')
axs.set_extent(extent)
axs.add_feature(feature.BORDERS, linewidth=linewidth_countrylines, zorder=zorder_countrylines)
axs.set_extent(extent)
axs.axis('off')
axs.add_geometries(shapely.get_parts(poly[0]), crs=transform, facecolor=facecolor_polygon,
edgecolor=edgecolor_polygon, linewidth=linewidth_polygon, zorder=18)
axs.add_geometries(msk_stm, st_proj, facecolor=facecolor_landmask, edgecolor=edgecolor_landmask,
zorder=16)
for municipality, fireextent_norm in zip(municipalities, fireextents_norm):
poly3 = df2.loc[df2['Municipali'] == municipality]['geometry'].values
if fireextent_norm > 0:
rgba2 = cmap(fireextent_norm)
else:
rgba2 = 'white'
axs.add_geometries(poly3, crs=transform, facecolor=rgba2, edgecolor='black', linewidth=linewidth_municipality, zorder=14)
dummy_scat = axs.scatter(fireextents, fireextents, c=fireextents, cmap=cmap, zorder=0,
norm=matplotlib.colors.LogNorm())
cbar = fig.colorbar(dummy_scat, ax=axs, orientation='horizontal', shrink=1, pad=0.01)
cbar.set_label(colorbarlabel1, size=fontsize, labelpad=15)
cbar.ax.tick_params(labelsize=labelsize)
plt.show()
Часть данных о размерах пожара показывает большой диапазон значений ниже. Как можно видеть, значения достигают диапазона 10³ и должны отображаться следующим образом:
print(fireextents)
>>> [4183.6667, 1378.0, 1065.0, 991.6, 908.0, 612.0, 548.0625, 520.0, 412.7778, 331.0, 324.0, 280.5, 259.3333, 259.0, 234.0, 222.0, 212.6667, 199.0, 169.0, 158.3333, 153.5, 148.6, 147.5, 145.0, 133.8, 130.0, 108.3333, 105.25, 103.0, 103.0, 90.0, 86.0, 84.3, 82.1667, 80.6, 80.0, 79.8571, 75.0, 74.0, 71.0, 65.3, 63.0, 59.6, 58.0, 58.0, 57.6667, 55.0, 55.0, 54.9, 54.8636, 53.25, 51.0, 50.4667, 49.0, 49.0, 49.0, 48.7143, 48.0, 47.1071, 47.0, 46.5, 46.0, 45.0, 43.0, 42.2, 42.0, 41.0, 40.0, 38.2, 35.4, 34.9, 34.9, 34.5, 34.0, 34.0, 34.0, 33.8, 33.0, 33.0, 33.0, 32.8, 32.0, 31.0, 30.3333, 30.0, 30.0, 30.0, 29.6667, 29.5, 29.4, 29.3, 29.2857, 28.1667, 28.0, 28.0, 28.0, 27.0, 27.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 25.8, 25.0, 25.0, 25.0, 25.0, 24.6, 24.5, 24.0, 24.0, 23.5, 23.1429, 23.0, 23.0, 22.0, 21.3, 19.0, 19.0, 19.0, 19.0, 19.0, 18.0, 17.5, 17.0, 16.5, 15.9167, 15.8, 15.5, 15.5, 15.3, 15.0714, 15.0, 15.0, 15.0, 14.5, 14.0, 13.5, 13.3333, 13.0, 12.5, 12.5, 12.2941, 12.0588, 12.0, 12.0, 12.0, 11.6, 11.0, 10.6667, 10.0, 9.6667, 9.6667, 9.5, 9.5, 9.0, 8.5714, 8.5, 8.3, 7.1667, 7.0, 7.0, 7.0, 6.6, 6.0, 6.0, 6.0, 6.0, 5.5, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 4.5, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 3.75, 3.5, 3.5, 3.4, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 2.5, 2.2, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 1.5, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... 0.0, 0.0, 0.0]
Подробнее здесь: https://stackoverflow.com/questions/790 ... ht-colours
