How would one reverse the order on the z axis of a 3D plot (i.e. negative is up, and positive is down)? The following code produces a cone with the base pointing downward; is there a command (like ax.reverse_zlim3d(True)
or something?) that can be used to change the tick order?
The following code plots a cone with the base pointing downward. I would like to reverse the z-axis order so that it plots with the base pointing up, like an ice cream cone, with -1 at the top of the graph instead of the bottom.
from matplotlib import pyplot as p
from mpl_toolkits.mplot3d import Axes3D # @UnusedImport
import numpy as np
from math import pi, cos, sin
z = np.arange(0, 1, 0.02)
theta = np.arange(0, 2 * pi + pi / 50, pi / 50)
fig = p.figure()
axes1 = fig.add_subplot(111, projection='3d')
for zval in z:
x = zval * np.array([cos(q) for q in theta])
y = zval * np.array([sin(q) for q in theta])
axes1.plot(x, y, -zval, 'b-')
axes1.set_xlabel("x label")
axes1.set_ylabel("y label")
axes1.set_zlabel("z label")
p.show()
By using ylim() method ylim() method is also used to invert axes of a plot in Matplotlib. Generally, this method is used to set limits for the axes.
In Matplotlib we can reverse axes of a graph using multiple methods. Most common method is by using invert_xaxis() and invert_yaxis() for the axes objects. Other than that we can also use xlim() and ylim(), and axis() methods for the pyplot object.
The mplot3d toolkit adds simple 3D plotting capabilities to matplotlib by supplying an axes object that can create a 2D projection of a 3D scene. The resulting graph will have the same look and feel as regular 2D plots. The interactive backends also provide the ability to rotate and zoom the 3D scene.
Use the invert_zaxis
method of the Axes3D
:
from matplotlib import pyplot as p
from mpl_toolkits.mplot3d import Axes3D # @UnusedImport
import numpy as np
from math import pi, cos, sin
z = np.arange(0, 1, 0.02)
theta = np.arange(0, 2 * pi + pi / 50, pi / 50)
fig = p.figure()
axes1 = fig.add_subplot(111, projection='3d')
for zval in z:
x = zval * np.array([cos(q) for q in theta])
y = zval * np.array([sin(q) for q in theta])
axes1.plot(x, y, -zval, 'b-')
axes1.set_xlabel("x label")
axes1.set_ylabel("y label")
axes1.set_zlabel("z label")
axes1.invert_zaxis()
p.show()
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