用 Python Matplotlib 结合图片和绘图
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Combine picture and plot with Python Matplotlib
提问by Sney
I have a plot which has timestamps on the x-axis and some signal data on the y-axis. As a documentation I want to put timestamped pictures in relation to specific points in the plot. Is it possible to draw a line in a plot to a picture in a sequence of pictures below the plot?
我有一个图，它在 x 轴上有时间戳，在 y 轴上有一些信号数据。作为文档，我想将带时间戳的图片与图中的特定点相关联。是否可以在绘图中绘制一条线到绘图下方的一系列图片中的图片？
采纳答案by tom10
Thisdemo from the matplotlib gallery shows how to insert pictures, draw lines to them, etc. I'll post the image from the gallery, and you can follow the linkto see the code.
matplotlib 库中的这个演示展示了如何插入图片、为它们画线等。我将从库中发布图像，您可以按照链接查看代码。
And here's the code (from version 2.1.2):
这是代码（来自版本 2.1.2）：
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
if 1:
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)
fn = get_sample_data("grace_hopper.png", asfileobj=False)
arr_img = plt.imread(fn, 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()
回答by Steve Tjoa
If I understand the question correctly, then perhaps this may help:
如果我正确理解了这个问题，那么这可能会有所帮助：
import scipy
import pylab
fig = pylab.figure()
axplot = fig.add_axes([0.07,0.25,0.90,0.70])
axplot.plot(scipy.randn(100))
numicons = 8
for k in range(numicons):
axicon = fig.add_axes([0.07+0.11*k,0.05,0.1,0.1])
axicon.imshow(scipy.rand(4,4),interpolation='nearest')
axicon.set_xticks([])
axicon.set_yticks([])
fig.show()
fig.savefig('iconsbelow.png')
