Scientific Computing Examples

[NUMA01]

Curve fitting and plotting

import numpy as np
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt

x = [20,40,80,160]          # nr of beads (N)
y = [66.7,193,549,1555]     # simulation data ree2

def ree(x, a, v):           # ree = a*N**v
    return a*x**v

popt, pcov = curve_fit(ree, x, y)       # solves variable a and v
a,v = popt                              # v here is 2v

plt.title('High temperature polymer size')
plt.xlabel('nr of beads (N)')
plt.ylabel('r2/a2')
plt.yscale("log")
plt.xscale("log")
plt.plot(x, y , "*",c='black')               # plots discrete points 
plt.grid(True,which="both",ls="-")

xrange = np.array([10,100,1000])
yrange = a*xrange**v

plt.plot(xrange, yrange,c='black') # plots solution of curve fit

print("Parameter v is", popt[1]/2)