Matplotlib 离散颜色条，用于绘制不同的土地利用类别

Question

我尝试定义一个离散的颜色条来为每个类别使用不同的颜色来绘制不同的土地类别。我尝试使用以下代码。我没有得到第一个选择的类别的红色/番茄颜色，即“城市”。彩条以李子色开始。我该如何解决？

我的另一个问题是我们可以将颜色条刻度线放在颜色条上离散颜色代码的中间吗？

我没有在此处附加我的数据集。如果需要，可以创建任何随机数组。土地利用类别只不过是我们用很少的特定数字表示不同的类别（例如：1 代表城市，13 代表森林，9 代表雪等）

import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import matplotlib.colors
from matplotlib.colors import ListedColormap
import numpy as np

col_dict = {
    1:"tomato",
    2:"plum",
    7:"lightgreen",
    11:"green",
    15:"maroon",
    16:"aqua",
    17:"navy",
    19:"goldenrod",
    22:"white",
}
labels = np.array([
    "Urban",
    "I Cropland",
    "Grassland",
    "B Deciduous",
    "Mixed Forest",
    "Water Bodies",
    "H Wetland", 
    "Barren",
    "Tundra",
])
crs = ccrs.PlateCarree()
ax = plt.subplot(111, projection=crs)
cm = ListedColormap([col_dict[x] for x in col_dict.keys()])
conf = ax.contourf(lonn, latt, lu_index, cmap=cm)

Answer 1

因此，您只是使用颜色图的一部分。您需要为轮廓定义级别，并且需要使用 BoundaryNorm。将您的投影排除在问题之外并制作相等的条纹，我已经使轮廓水平正好在您的离散值之间的一半。如果你不这样做，数据之间的线性插值会将轮廓朝向一侧或另一侧。

import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
from matplotlib.colors import ListedColormap
import numpy as np

col_dict = {
    1:"tomato",
    2:"plum",
    7:"lightgreen",
    11:"green",
    15:"maroon",
    16:"aqua",
    17:"navy",
    19:"goldenrod",
    22:"white",
}
labels = np.array([
    "Urban",
    "I Cropland",
    "Grassland",
    "B Deciduous",
    "Mixed Forest",
    "Water Bodies",
    "H Wetland", 
    "Barren",
    "Tundra",
])
cm = ListedColormap([col_dict[x] for x in col_dict.keys()])
np.random.seed(2112)
lu_index = np.zeros((9, 9))
for nn,k in enumerate(col_dict.keys()):
    lu_index[nn, :] = k

bounds = np.array([k for k in col_dict.keys()])
bounds = bounds[:-1] + np.diff(bounds) / 2
bounds = np.concatenate((np.array([0]), bounds, np.array([24])))
norm = mcolors.BoundaryNorm(bounds, 9)

fig, axs = plt.subplots(1, 3, constrained_layout=True, figsize=(6, 4))
ax = axs[0]
conf = ax.contourf(lu_index, cmap=cm)
ax.set_title('No Boundary Norm, \nno levels')

ax = axs[1]
conf = ax.contourf(lu_index, cmap=cm, levels=bounds)
ax.set_title('No Boundary Norm, \nlevels')

ax = axs[2]
conf = ax.contourf(lu_index, cmap=cm, norm=norm, levels=bounds)
ax.set_title('Boundary Norm, \nlevels')