使用Python Matplotlib将图片和绘图组合在一起

Question

我有一个在x轴上有时间戳的图和在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图中一系列图片中的图片？

Answer 1

来自matplotlib画廊的This演示了如何插入图片，为它们画线等。我将从图库中发布图像，您可以按照link查看代码。

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()

Answer 2

如果我正确理解了这个问题，那么也许这可能会有所帮助：

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')