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python - 选择在图形的 "edge"上绘制线(并循环),而不是在图形上绘制

转载 作者:行者123 更新时间:2023-12-04 08:37:14 25 4
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所以,我有一个键的二面角图。 y 轴仅从 0-360,x 轴是框架(想想时间步长)。如果值超过 360,我需要绘图“循环”回零,并绘制两点之间的最短距离(如果需要越过图形的边缘并“循环”返回而不是穿过图形)。
two plots: d5 and d3
d3 的图看起来不错,但实际上需要跳过图形的边缘而不是跨越它。
d5 的情节有一个重大问题,对于一个小的旋转有一个巨大的跳跃只是因为它恰好低于零度。
我希望这两个图都向底部(向零)绘制并重新出现在图的顶部,从而有效地选择数据点之间的最短距离。我不希望解决方案涉及图的翻译以消除这些人工制品(它有效,我已经完成了,但是您丢失了有关角度真实值的信息)。可以绘制“低于零”(因此 y 轴从 300 到 360|0 到 200 到 300)的解决方案也很棒。使用其他库的解决方案非常好。如果需要,我可以提供数据集。
我希望它做什么的示例(绿线)
Example of what I'd like it to do (green line)
我试图找到类似的解决方案无济于事。关于周期性边界的问题使用 numpy 数据集掩码来隐藏某些跳跃,但它们具有连续功能(而我的则是“跳跃”)。
谢谢你的帮助,我真的很感激。
数据集(使它们比图表小一点,只保留跳过):
D3:

x = [41.0, 43.0, 45.0, 47.0, 49.0, 51.0, 53.0, 55.0, 57.0, 59.0, 61.0, 63.0, 65.0, 67.0, 69.0, 71.0, 73.0, 75.0, 77.0, 79.0, 81.0, 83.0, 85.0, 87.0, 89.0, 91.0, 93.0, 95.0, 97.0, 99.0, 101.0, 103.0, 105.0, 107.0, 109.0, 111.0, 113.0, 115.0, 117.0, 119.0, 121.0, 123.0, 125.0, 127.0, 129.0, 131.0, 133.0, 135.0, 137.0, 139.0, 141.0, 143.0, 145.0, 147.0, 149.0, 151.0, 153.0, 155.0, 157.0, 159.0]

y = [45.6501, 37.4855, 40.4035, 51.4948, 55.8648, 48.9723, 60.4494, 42.7136, 20.6929, 36.7847, 44.4601, 54.04, 52.4895, 45.1991, 46.8203, 44.5827, 65.8803, 53.5398, 69.5158, 46.5372, 37.1557, 43.9031, 39.9325, 35.5248, 34.3531, 57.8377, 37.9208, 26.6508, 27.2333, 49.3798, 47.8627, 54.2795, 50.0892, 40.9849, 37.4014, 300.7947, 299.4254, 288.5113, 313.2906, 319.0095, 291.0726, 308.075, 298.451, 311.1485, 320.4832, 303.9229, 310.4584, 325.6287, 307.7328, 301.5581, 308.7813, 308.6791, 305.1343, 307.5148, 334.6374, 310.476, 315.6943, 326.0586, 298.6766, 305.6225]
最低工作示例:
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot(x, y, linewidth = 1.2, label = 'd3')
ax.set_yticks([t for t in range(0,390,30)])
ax.set_xticks([t for t in range(50,200,50)])
ax.legend(loc='lower right',prop={'size': 14})
plt.show()

最佳答案

使用基本 Python,如您的列表所示,而不是更高的库,如 numpy ,您可以使用基本函数将绘图的两个部分分开。但是,考虑到您的具体问题,您可能更喜欢极坐标图:

from matplotlib import pyplot as plt

#two subplots with two different approaches
fig, (ax1, ax2) = plt.subplots(2, figsize=(5, 10))

#first approach - separating the list at the jump point
ymin = 0
ymax = 360

#pseudo-threshold calculation, just the first index in your list with a value above the threshold
threshold = 100
breakpoint = next(a[0] for a in enumerate(y) if a[1] > threshold)

#separating the lists at this breakpoint, creating intermediate point
y1 = y[:breakpoint] + [ymin]
y2 = [ymax] + y[breakpoint:]
x12 = 0.5 * (x[breakpoint-1] + x[breakpoint])
x1 = x[:breakpoint] + [x12]
x2 = [x12] + x[breakpoint:]

#plotting of the upper subplot
ax1.plot(x1, y1, c="r", label="jump")
ax1.plot(x2, y2, c="r")
ax1.legend()
ax1.set_ylim(ymin, ymax)


#second approach - a polar plot
#convert deg into rad, here with numpy
import numpy as np
angle = np.deg2rad(y)

#plot the second subplot using polar coordinates
ax2 = plt.subplot(212, projection='polar')
ax2.plot(angle, x, c="r", label = "same jump")

#making it look nicer with clockwise rotation and 0 degree at the top
ax2.set_theta_direction(-1)
ax2.set_theta_zero_location('N')
ax2.set_rlabel_position(180)
ax2.set_ylim(0.9 * x[0], 1.1 * x[-1])
ax2.legend(loc=(-0.07,0.97))


plt.show()
这为您提供了两个 View 进行比较:
enter image description here

关于python - 选择在图形的 "edge"上绘制线(并循环),而不是在图形上绘制,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/64742934/

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