Adding bezier axes to matplotlib figure

问题

When using the bezier library, the Curve.plot() function returns an AxesSubplot object

nodes1 = np.array([[0.0, 0.0],[0.625, .75], [1.0, 1.0]])
curve1 = bezier.Curve(nodes1, degree=2)
ax = curve1.plot(num_pts=256)
print ax

returns an

AxesSubplot(0.125,0.11;0.775x0.77)

I know the typical way of creating a subplot is with

fig = pyplot.figure()
ax = fig.add_subplot(111)

but I can't find any documentation on adding an already created subplot to a figure.

I can display the subplot with plt.show() but can't access the figure. If I try to create a figure with plt.figure(), two different figures (in different windows) are displayed.

回答1:

On many Python third party libraries (including matplotlib), you can look at the source and see what is going on behind the scenes and often you can use that as a guide for what you want to do - maybe even an opportunity for a subclass to implement your customization or. bezier.Curve.plot source is pretty straightforward and if your intent is to just plot the curve you can use its code, in your own (bezier.Curve.evaluate_multi returns numpy.ndarray: The points on the curve. As a two dimensional NumPy array, with the rows corresponding to each *s* value and the columns to the dimension.

nodes1 = np.array([[0.0, 0.0],[0.625, .75], [1.0, 1.0]])
curve1 = bezier.Curve(nodes1, degree=2)
# if you need to create x values.
s_vals = np.linspace(0.0, 1.0, num_pts)
points = curve1.evaluate_multi(s_vals)

Where the x values are points[:, 0] and the y values are points[:, 1]. Depending on what you actually need... (from pylab_examples example code: subplots_demo.py

f, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
ax1.plot(points[:, 0], points[:, 1])
ax1.set_title('Sharing Y axis')
ax2.scatter(points[:, 0], points[:, 1])

---

I haven't actually tried this - lacking bezier on this machine.

回答2:

If the aim is to plot a curve to an existing axes ax, use the ax argument of the plotting function, bezier.Curve.plot(..., ax):

nodes1 = np.array([[0.0, 0.0],[0.625, .75], [1.0, 1.0]])
curve1 = bezier.Curve(nodes1, degree=2)

# create axes with matplotlib
fig, ax = plt.subplots()

# plot curve to existing axes
curve1.plot(num_pts=256, ax=ax)

---

Alternatively, if you have problems using the bezier package, creating a Bezier curve is not actually that hard. So you may just do it manually:

import numpy as np
from scipy.special import binom
import matplotlib.pyplot as plt

bernstein = lambda n, k, t: binom(n,k)* t**k * (1.-t)**(n-k)

def bezier(points, num=200):
    N = len(points)
    t = np.linspace(0, 1, num=num)
    curve = np.zeros((num, 2))
    for i in range(N):
        curve += np.outer(bernstein(N - 1, i, t), points[i])
    return curve


nodes1 = np.array([[0.0, 0.0],[0.625, .75], [1.0, 1.0]])
curve1 = bezier(nodes1, num=256)

fig, ax = plt.subplots()

ax.plot(curve1[:,0], curve1[:,1])

plt.show()

回答3:

First, to avoid another window to open you must "close" the plotting:

pyplot.close()

Then you can execute your

ax = curve1.plot(num_pts=256)

Now, I don't know why do you bring in subplot(111), which uses the whole window anyway (single figure). But if you still want to use a smaller subplot (e.g. 221), you can do the following:

pyplot.close()
fig = pyplot.figure()
#fig = pyplot.gcf(); # This will also do
ax = fig.add_subplot(221); curve.plot(num_pts=256,ax=ax)

(Note: I just tested both cases and they work. Only I used 2D nodes instead of 3D.)

来源：https://stackoverflow.com/questions/46901622/adding-bezier-axes-to-matplotlib-figure