从python中的峰值数据点绘制315度角

Question

我试图让红线（Vector）从数据集中的黄色峰值数据点（在100处）以315度角朝向图表的右侧。

只是想不出怎么做。

import matplotlib.pyplot as plt
import numpy as np
from scipy import signal

data = np.array([19.639999,19.049999,19.959999,19.950001,21.549999,21.110001,20.73,19.139999,20,20.280001,20.41,       21.190001,22.82,23.799999,23.190001,20.92,19.700001,18.85,21.67,22.75,22.549999])

for number in data:

    signal_max = (data > np.roll(data,1)) & (data > np.roll(data,-1))
    signal_min = (data < np.roll(data,1)) & (data < np.roll(data,-1))


degree = range(len(data))

line = np.poly1d(np.polyfit(degree, data, 1))(degree)

slope = (degree[-1] - degree[0]) / (data[-1] - data[0])

#angle = np.rad2deg(slope)
angle = np.rad2deg(np.arctan2(degree[-1] - degree[0], data[-1] -data[0]))


plt.figure(figsize=(8,6))
plt.plot(data)
plt.plot(line, '--', color='r')
plt.plot(signal_max.nonzero()[0], data[signal_max], 'yv')
plt.plot(signal_min.nonzero()[0], data[signal_min], 'r^')
plt.show()

Answer 1

我不知道为什么你想要315，所以我做了两个版本：一个从最高点（版本1，见下文）做315角度，一个使回归线通过最大值（版本2，见下文） 。如果不清楚，请评论。

VERSION1：

import matplotlib.pyplot as plt
import numpy as np
from scipy import signal
from math import pi

data = np.array([19.639999,19.049999,19.959999,19.950001,21.549999,21.110001,20.73,19.139999,20,20.280001,20.41,
         21.190001,22.82,23.799999,23.190001,20.92,19.700001,18.85,21.67,22.75,22.549999,22.889999,24.139999,
         25.02,24.77,24.469999,24.84,24.299999,33.669998,46.98,52.669998,55.419998,55.23,57.830002,61.299999,
         61.880001,59.689999,73.949997,75.330002,81.410004,99.019997,89.980003,86.870003])

for number in data:

    signal_max = (data > np.roll(data,1)) & (data > np.roll(data,-1))
    signal_min = (data < np.roll(data,1)) & (data < np.roll(data,-1))


degree = range(len(data))

line = np.poly1d(np.polyfit(degree, data, 1))(degree)

plt.figure(figsize=(8,6))
plt.plot(data)

xm = np.argmax(data)
ym = np.amax(data)
angle = 315
plt.plot( [ xm - ym/np.tan(angle/(2*pi)), xm ], [0, ym ], '--', color='r')

plt.plot(signal_max.nonzero()[0], data[signal_max], 'yv')
plt.plot(signal_min.nonzero()[0], data[signal_min], 'r^')
plt.show()

版本2：

import matplotlib.pyplot as plt
import numpy as np
from scipy import signal
from math import pi

data = np.array([19.639999,19.049999,19.959999,19.950001,21.549999,21.110001,20.73,19.139999,20,20.280001,20.41,
         21.190001,22.82,23.799999,23.190001,20.92,19.700001,18.85,21.67,22.75,22.549999,22.889999,24.139999,
         25.02,24.77,24.469999,24.84,24.299999,33.669998,46.98,52.669998,55.419998,55.23,57.830002,61.299999,
         61.880001,59.689999,73.949997,75.330002,81.410004,99.019997,89.980003,86.870003])

for number in data:

    signal_max = (data > np.roll(data,1)) & (data > np.roll(data,-1))
    signal_min = (data < np.roll(data,1)) & (data < np.roll(data,-1))


degree = range(len(data))

line = np.poly1d(np.polyfit(degree, data, 1))(degree)

plt.figure(figsize=(8,6))
plt.plot(data)

xm = np.argmax(data)
line = line - (line[xm] - data[xm])
plt.plot( line, '--', color='g')

plt.plot(signal_max.nonzero()[0], data[signal_max], 'yv')
plt.plot(signal_min.nonzero()[0], data[signal_min], 'r^')
plt.show()