您可以手动设置要显示的级别。只要零的左侧和右侧的间隔间距相同,就可以很好地工作。
levels = [-50,-40,-30,-20,-10,10,20,30,40,50]
ax.contourf(X,Y,Z, levels)
Example:
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(-6.3,6.3)
y = np.linspace(-3.1,3.1)
X,Y = np.meshgrid(x,y)
Z = -np.cos(X)*np.cos(Y)*45
levels = [-50,-40,-30,-20,-10,10,20,30,40,50]
fig, ax = plt.subplots(figsize=(4,2))
cont = ax.contourf(X,Y,Z,levels, cmap="seismic")
fig.colorbar(cont, orientation="horizontal")
plt.show()
或者,如果您希望颜色条与数据成比例,
fig.colorbar(cont, orientation="horizontal", spacing="proportional")
如果级别不相等,则需要指定vmin
and vmax
.
levels = [-50,-40,-30,-20,-10,10,30,50,80,100]
cont = ax.contourf(X,Y,Z,levels, cmap="seismic", vmin=-50, vmax=50)
缺点是会降低分辨率,因此您可以使用 BoundaryNorm 为不等间距的标签选择等间距的颜色。
import matplotlib.pyplot as plt
import matplotlib.colors
import numpy as np
x = np.linspace(-6.3,6.3)
y = np.linspace(-3.1,3.1)
X,Y = np.meshgrid(x,y)
Z = -np.cos(X)*np.cos(Y)*45
levels = [-50,-40,-30,-20,-10,10,30,50,80,100]
norm = matplotlib.colors.BoundaryNorm(levels, len(levels)-1)
fig, ax = plt.subplots(figsize=(4,2))
cont = ax.contourf(X,Y,Z,levels,cmap=plt.get_cmap("seismic",len(levels)-1), norm=norm)
fig.colorbar(cont, orientation="horizontal")
plt.show()
要更改颜色栏上的刻度标签,以便更改级别以外的其他内容,或者如果它们太密集,您可以使用ticks
争论。
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(-6.3,6.3)
y = np.linspace(-3.1,3.1)
X,Y = np.meshgrid(x,y)
Z = -np.cos(X)*np.cos(Y)*45
levels = np.arange(-45,50,5)
levels = levels[levels!=0]
ticks=np.arange(-40,50,10)
fig, ax = plt.subplots(figsize=(4,2))
cont = ax.contourf(X,Y,Z,levels,cmap="seismic", spacing="proportional")
fig.colorbar(cont, orientation="horizontal", ticks=ticks, spacing="proportional")
plt.show()