在jupyter笔记本的matplotlib中初始绘制后移动注释框

Question

我希望在matplotlib绘图中绘制注释图像，并能够在绘图后移动它们

为此，我从演示开始： https://matplotlib.org/3.2.1/gallery/text_labels_and_annotations/demo_annotation_box.html

使用笔记本电脑后端：

%matplotlib notebook
import matplotlib.pyplot as plt
import numpy as np

from matplotlib.patches import Circle
from matplotlib.offsetbox import (TextArea, DrawingArea, OffsetImage,
                                  AnnotationBbox)
from matplotlib.cbook import get_sample_data


fig, ax = plt.subplots()

# Define a 1st position to annotate (display it with a marker)
xy = (0.5, 0.7)
ax.plot(xy[0], xy[1], ".r")

# Annotate the 1st position with a text box ('Test 1')
offsetbox = TextArea("Test 1", minimumdescent=False)

ab = AnnotationBbox(offsetbox, xy,
                    xybox=(-20, 40),
                    xycoords='data',
                    boxcoords="offset points",
                    arrowprops=dict(arrowstyle="->"))
ax.add_artist(ab)

# Annotate the 1st position with another text box ('Test')
offsetbox = TextArea("Test", minimumdescent=False)

ab = AnnotationBbox(offsetbox, xy,
                    xybox=(1.02, xy[1]),
                    xycoords='data',
                    boxcoords=("axes fraction", "data"),
                    box_alignment=(0., 0.5),
                    arrowprops=dict(arrowstyle="->"))
ax.add_artist(ab)

# Define a 2nd position to annotate (don't display with a marker this time)
xy = [0.3, 0.55]

# Annotate the 2nd position with a circle patch
da = DrawingArea(20, 20, 0, 0)
p = Circle((10, 10), 10)
da.add_artist(p)

ab = AnnotationBbox(da, xy,
                    xybox=(1.02, xy[1]),
                    xycoords='data',
                    boxcoords=("axes fraction", "data"),
                    box_alignment=(0., 0.5),
                    arrowprops=dict(arrowstyle="->"))

ax.add_artist(ab)

# Annotate the 2nd position with an image (a generated array of pixels)
arr = np.arange(100).reshape((10, 10))
im = OffsetImage(arr, zoom=2)
im.image.axes = ax

ab = AnnotationBbox(im, xy,
                    xybox=(-50., 50.),
                    xycoords='data',
                    boxcoords="offset points",
                    pad=0.3,
                    arrowprops=dict(arrowstyle="->"))

ax.add_artist(ab)

# Annotate the 2nd position with another image (a Grace Hopper portrait)
with get_sample_data("grace_hopper.png") as file:
    arr_img = plt.imread(file, format='png')

imagebox = OffsetImage(arr_img, zoom=0.2)
imagebox.image.axes = ax

ab = AnnotationBbox(imagebox, xy,
                    xybox=(120., -80.),
                    xycoords='data',
                    boxcoords="offset points",
                    pad=0.5,
                    arrowprops=dict(
                        arrowstyle="->",
                        connectionstyle="angle,angleA=0,angleB=90,rad=3")
                    )

ax.add_artist(ab)

# Fix the display limits to see everything
ax.set_xlim(0, 1)
ax.set_ylim(0, 1)

plt.show()

为了测试如何移动东西，我在下一个单元格中执行：

rnd = fig.canvas.renderer
print(rnd)
print(im.get_window_extent(rnd))
print(im.get_window_extent(rnd).get_points())
print(ab.xybox)
ab.xybox = (130, -70)
im._offset = (135.46666666666667, 301.6355555555555)
im.set_zoom(.5)
ab.update_positions(rnd)
print(ab.xybox)
print(im.get_window_extent(rnd).get_points())
ab.draw(rnd)
im.draw(rnd)
fig.draw(rnd)
ax.plot([0, 1], [0, 1])
plt.show()
fig.canvas.draw_idle()

我看到的是，我确实在绘制的线中得到了一个中断，显示annotationbbox被移动了，但它的所有内容都没有移动。（此处先绘制直线（蓝色），然后执行所有移位，再绘制另一条直线（橙色）） 任何关于我如何实际移动Grace Hopper形象的建议都将受到高度赞赏

Answer 1

这不是对您的问题的直接回答，但我想知道一个类似的问题（而且matplotlib文档也缺乏），所以我对这个示例进行了修改，它似乎是可行的。关键似乎是在每次更改后使用fig.canvas.draw（）。此外，我正在使用matplotlib版本3.1.3

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.offsetbox import OffsetImage, AnnotationBbox

def onpick(evt):
    x = (evt.xdata, evt.ydata)
    ab.xybox = x
    print(ab.xybox)
    fig.canvas.draw()

pix = np.linspace(0, 1, 20)
x, y = np.meshgrid(pix, pix)
p = np.cos(2*np.pi*x)*np.sin(8*np.pi*y)

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

im = OffsetImage(p, zoom=1, cmap = 'gray')
ab = AnnotationBbox(im, (0.5, 0.5), xycoords='data', frameon=False)
ax.add_artist(ab)

fig.canvas.mpl_connect('button_press_event', onpick)
plt.show()