Python numpy 데이터피팅, 함수의 해 graph

◎Python - Numpy 를 사용하여 데이터 피팅

#curve_fit code (figure2)

import numpy as np

import matplotlib.pyplot as plt

from scipy.optimize import curve_fit

#최소자승법사용

def func(x, a, b, c):

return a*np.exp(-(x-b)**2/(2*c**2))

x = np.linspace(0,10,100)

y = func(x, 1, 5, 2)

yn = y + 0.2 * np.random.normal(size=len(x))

popt, pcov = curve_fit(func, x, yn)

cur_y = func(x, popt[0], popt[1], popt[2])

#그래프그리기

g1, = plt.plot(x, y, 'k')

g2, = plt.plot(x, yn, 'b.')

g3, = plt.plot(x, cur_y, 'r')

plt.legend([g1,g3], ['Funtion', 'Best fit'], loc = 2)

plt.axis([-2,12,-0.5,1.5])

plt.show()

◎Python - Numpy를 이용하여 함수의 해 도출

#code (figure5)

import numpy as np

import matplotlib.pyplot as plt

from scipy.optimize import fsolve

def findIntersection(func1, func2, x0):

    return fsolve(lambda x : func1(x) - func2(x), x0)

funky = lambda x : np.cos(x/5) * np.sin(x /2)

line = lambda x : 0.01 * x - 0.5

x = np.linspace(0,45,10000)

result = findIntersection(funky, line, [15,20,30,35,40,45])

funky_v = funky(x)

line_v = line(x)

#그래프그리기

g1, = plt.plot(x, funky_v, 'b')

g2, = plt.plot(x, line_v , 'k')

g3, = plt.plot(result, line(result), 'ro')

plt.legend([g1,g2], ['Funky func', 'Line func'], loc = 3)

plt.axis([0,45,-1.0,1.0])

plt.show()