Matplotlib对齐图像和子图

Question

我不熟悉python的matplotlib，必须绘制一些东西，显示图像并在下面添加文本。 到目前为止，我所做的是（简化示例）：

from matplotlib import pyplot as plt
from matplotlib import image as img

fig = plt.figure()
pic = img.imread("image path")

ax1 = fig.add_subplot(121)
ax1.plot()
ax1.set_yticks([0, 1, 2, 3, 4, 5])
ax1.set_xticks([0, 1, 2, 3, 4, 5])

ax1.annotate("Text", xy=(0, -0.12), xycoords="axes fraction")
ax1.annotate("More text", xy=(0, -0.17), xycoords="axes fraction")
ax1.annotate("Even more text", xy=(0, -0.22), xycoords="axes fraction")
ax1.annotate("1", xy=(1, -0.12), xycoords="axes fraction", ha="right")
ax1.annotate("2", xy=(1, -0.17), xycoords="axes fraction", ha="right")
ax1.annotate("3", xy=(1, -0.22), xycoords="axes fraction", ha="right")

ax2 = fig.add_subplot(122)
ax2.imshow(pic)
ax2.axis("off")

ax2.annotate("Text", xy=(0, -0.1), xycoords="axes fraction")
ax2.annotate("More text", xy=(0, -0.2), xycoords="axes fraction")
ax2.annotate("Even more text", xy=(0, -0.3), xycoords="axes fraction")
ax2.annotate("1", xy=(1, -0.1), xycoords="axes fraction", ha="right")
ax2.annotate("2", xy=(1, -0.2), xycoords="axes fraction", ha="right")
ax2.annotate("3", xy=(1, -0.3), xycoords="axes fraction", ha="right")

plt.subplots_adjust(bottom=0.18)
plt.show()

问题：我希望两个子图都垂直对齐，这样两个子图下面的文本也垂直对齐。但是图像总是出现在“中间”（red pic in the middle of left plot and not same x axis）。是否有可能将图像放在绘图的x轴上，或者是否有人知道更好的方法在两个子绘图下面添加文本（无注释）

我尝试的是：

• 变化figsize：闭合但仍未对齐（仅压缩绘图）
• ax2.imshow（pic，aspect=“auto”）：这会扭曲我的图像

Answer 1

Blended transformationsRef在我的代码中用于根据需要对齐两个轴上的注释项

from matplotlib import pyplot as plt
from matplotlib import image as img
import matplotlib.transforms as transforms

fig = plt.figure()
pic = img.imread("testimg1.png")  #use your image

ax1 = fig.add_subplot(121)
ax1.plot((1,5,3,2,1,4))           #sample data that fit xy-ticks below
ax1.set_yticks([0, 1, 2, 3, 4, 5])
ax1.set_xticks([0, 1, 2, 3, 4, 5])

# Blended transformation for handling annotation coordinates on `ax1`
trans1 = transforms.blended_transform_factory(ax1.transData, ax1.transAxes)
topy1 = -0.20
dy1 = - 0.07
lx1 = 0
rx1 = 5.0   # max value of x

ax1.annotate("Text1", xy=(lx1, topy1), xycoords=trans1)
ax1.annotate("More text1", xy=(lx1, topy1+dy1), xycoords=trans1)
ax1.annotate("Even more text1", xy=(lx1, topy1+dy1*2), xycoords=trans1)
ax1.annotate("11", xy=(rx1, topy1), xycoords=trans1, ha="right")
ax1.annotate("21", xy=(rx1, topy1+dy1), xycoords=trans1, ha="right")
ax1.annotate("31", xy=(rx1, topy1+dy1*2), xycoords=trans1, ha="right")

ax2 = fig.add_subplot(122)
ax2.axis("off")
ax2.imshow(pic)

# Blended transformation for handling annotation coordinates on `ax2`, ...
#  note that it uses y-axis of `ax1`, thus, make it easy to align items in
#  both axes (vertically)
trans2 = transforms.blended_transform_factory(ax2.transData, ax1.transAxes)
topy2 = topy1   # possible with `trans2`
dy2 = dy1
lx2 = 0
rx2 = pic.shape[1]  #width of `pic` image

ax2.annotate("Text2", xy=(lx2, topy2), xycoords=trans2)
ax2.annotate("More text2", xy=(lx2, topy2+dy2), xycoords=trans2)
ax2.annotate("Even more text2", xy=(lx2, topy2+dy2*2), xycoords=trans2)
ax2.annotate("12", xy=(rx2, topy2), xycoords=trans2, ha="right")
ax2.annotate("22", xy=(rx2, topy2+dy2), xycoords=trans2, ha="right")
ax2.annotate("32", xy=(rx2, topy2+dy2*2), xycoords=trans2, ha="right")

plt.subplots_adjust(bottom=0.18)
plt.show()

输出曲线图：