Lets assume I have the following numpy array:
import numpy as np
import matplotlib.pyplot as plt
x = np.array([11.53333333, 11.86666667, 11.1, 10.66666667, 1
I was looking for this answer too. This is one way how to find inflection point in python:
How to find the inflection point in a noisy curve?
The inflection point is [x0, y0]
#!/usr/bin/env python2.7
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import numpy as np
from scipy.ndimage import gaussian_filter
def generate_fake_data():
"""Generate data that looks like an example given."""
xs = np.arange(0, 25, 0.05)
ys = - 20 * 1./(1 + np.exp(-(xs - 5.)/0.3))
m = xs > 7.
ys[m] = -20.*np.exp(-(xs - 7.)[m] / 5.)
# add noise
ys += np.random.normal(0, 0.2, xs.size)
return xs, ys
def main():
xs, ys = generate_fake_data()
# smooth out noise
smoothed = gaussian_filter(ys, 3.)
# find the point where the signal goes above the background noise
# level (assumed to be zero here).
base = 0.
std = (ys[xs < 3] - base).std()
m = smoothed < (base - 3. * std)
x0 = xs[m][0]
y0 = ys[m][0]
plt.plot(xs, ys, '.')
plt.plot(xs, smoothed, '-')
plt.plot(x0, y0, 'o')
plt.show()
if __name__ == '__main__':
main()
Example output of how to find inflection point in python