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To make the annotation line visible or preserved while panning/zooming in Matplotlib, you can use the bbox parameter in the annotate() function. The bbox parameter specifies the properties of the bounding box around the text, including its position, width, and height. By setting the fc (facecolor) and alpha (transparency) parameters of the bounding box to 1, you can make it opaque and visible even when zooming or panning.

Here is an example code snippet showing how to use bbox parameter to make annotation line visible or preserved in Matplotlib:

import matplotlib.pyplot as plt fig, ax = plt.subplots() x = [1, 2, 3, 4, 5] y = [2, 4, 1, 3, 5] ax.plot(x, y) annot = ax.annotate("Max value", xy=(3, 5), xytext=(4, 4), arrowprops=dict(facecolor='red', shrink=0.05), bbox=dict(boxstyle='round,pad=0.5', fc='white', alpha=1)) plt.show() 

In this example, the bbox parameter is set to dict(boxstyle='round,pad=0.5', fc='white', alpha=1) in the annotate() call. This specifies a rectangular bounding box with rounded corners (boxstyle='round'), a padding of 0.5 units (pad=0.5), a white background (fc='white'), and an opacity of 1 (alpha=1). As a result, the annotation line and its text will remain visible even when zooming or panning.

To make the annotation line visible or preserved while panning/zooming in Matplotlib, you can use the bbox parameter in the annotate() function. The bbox parameter specifies the properties of the bounding box around the text, including its position, width, and height. By setting the fc (facecolor) and alpha (transparency) parameters of the bounding box to 1, you can make it opaque and visible even when zooming or panning.

Here is an example code snippet showing how to use bbox parameter to make annotation line visible or preserved in Matplotlib:

import matplotlib.pyplot as plt fig, ax = plt.subplots() x = [1, 2, 3, 4, 5] y = [2, 4, 1, 3, 5] ax.plot(x, y) annot = ax.annotate("Max value", xy=(3, 5), xytext=(4, 4), arrowprops=dict(facecolor='red', shrink=0.05), bbox=dict(boxstyle='round,pad=0.5', fc='white', alpha=1)) plt.show() import matplotlib.pyplot as plt

fig, ax = plt.subplots()

x = [1, 2, 3, 4, 5]
y = [2, 4, 1, 3, 5]

ax.plot(x, y)

annot = ax.annotate("Max value", xy=(3, 5), xytext=(4, 4),
                     arrowprops=dict(facecolor='red', shrink=0.05),
                     bbox=dict(boxstyle='round,pad=0.5',
                               fc='white', alpha=1))

plt.show()