1. 自定义颜色系

import matplotlib.pyplot as plt
import matplotlib as mplfig, ax = plt.subplots(figsize=(6, 1))
fig.subplots_adjust(bottom=0.5)cmap = mpl.cm.viridis
norm = mpl.colors.Normalize(vmin=5, vmax=10)fig.colorbar(mpl.cm.ScalarMappable(norm=norm, cmap=cmap), cax=ax, orientation='horizontal', label='Some Units')

2. 带离散区间的（两端带箭头的）

fig, ax = plt.subplots(figsize=(6, 1))
fig.subplots_adjust(bottom=0.5)cmap = mpl.cm.viridis
bounds = [-1, 2, 5, 7, 12, 15]
norm = mpl.colors.BoundaryNorm(bounds, cmap.N, extend='both')
fig.colorbar(mpl.cm.ScalarMappable(norm=norm, cmap=cmap),cax=ax, orientation='horizontal',label="Discrete intervals with extend='both' keyword")

3. 修改 extendfrac 为自动

fig.colorbar(mpl.cm.ScalarMappable(norm=norm, cmap=cmap),cax=ax, orientation='horizontal',extendfrac='auto',label="Discrete intervals with extend='both' keyword")

4. 非均匀色带

import cmaps
import matplotlib as mplprocess_data = pd.read_excel(r".\text_data.xlsx")
process_data.head()
# 任取两列数据
x_data = process_data.iloc[:,14]
y_data = process_data.iloc[:,13]# 自定义色带分布
bounds = [1, 2, 3, 5, 7,10,14,20,30,50]
norm = mpl.colors.BoundaryNorm(bounds, cmap.N)nbins =150
H, xedges, yedges = np.histogram2d(x_data, y_data, bins=nbins)
H = np.rot90(H)
H = np.flipud(H)
Hmasked = np.ma.masked_where(H==0,H) 
#开始绘图
fig,ax = plt.subplots(figsize=(4,3.5),dpi=100,facecolor="w")
density_scatter = ax.pcolormesh(xedges, yedges, Hmasked, cmap=cmaps.GMT_seis,norm=norm)
colorbar = fig.colorbar(density_scatter,aspect=17,orientation='horizontal',extendfrac='auto',extend='both',label="Number of points per pixel")
colorbar.ax.tick_params(left=True,direction="in",width=.4,labelsize=10)
colorbar.ax.tick_params(which="minor",bottom=False)
colorbar.outline.set_linewidth(.4)
ax.set_xlim(-30,30)
ax.set_ylim(-7.5,7.5)

5. 自定义两端箭头颜色

import cmaps
import matplotlib as mplprocess_data = pd.read_excel(r".\text_data.xlsx")
process_data.head()
# 任取两列数据
x_data = process_data.iloc[:,14]
y_data = process_data.iloc[:,13]cmap = mpl.cm.get_cmap("GMT_seis").copy()
cmap.set_extremes(over="black", under='w')
bounds = [1, 2, 3, 5, 7,10,14,20,30,50]
norm = mpl.colors.BoundaryNorm(bounds, cmap.N)nbins =150
H, xedges, yedges = np.histogram2d(x_data, y_data, bins=nbins)
H = np.rot90(H)
H = np.flipud(H)
Hmasked = np.ma.masked_where(H==0,H) 
#开始绘图
fig,ax = plt.subplots(figsize=(4,3.5),dpi=100,facecolor="w")
density_scatter = ax.pcolormesh(xedges, yedges, Hmasked, cmap=cmap,norm=norm)
colorbar = fig.colorbar(density_scatter,aspect=17,orientation='horizontal',extendfrac='auto',extend='both',label="Number of points per pixel")
colorbar.ax.tick_params(left=True,direction="in",width=.4,labelsize=10)
colorbar.ax.tick_params(which="minor",bottom=False)
colorbar.outline.set_linewidth(.4)
ax.set_xlim(-30,30)
ax.set_ylim(-7.5,7.5)
plt.savefig(r'.\custom_example3.png', bbox_inches='tight',dpi=300)