powerfit¶
- numeric.fitting.powerfit(x, y, func=False)¶
Power law fitting.
- Parameters:
x – (array_like) x data array.
y – (array_like) y data array.
func – (boolean) Return fit function (for predict function) or not. Default is
False
.
- Returns:
Fitting parameters and function (optional).
Examples:
from mipylib.numeric import fitting fn = 'D:/Temp/ascii/PM&vis-1.txt' ncol = numasciicol(fn) nrow = numasciirow(fn) a = asciiread(fn,shape=(nrow,ncol)) x=a[:,0] y=a[:,1] z=a[:,2] axes(tickfontsize=17) ls=scatter(x,y,s=8,c=z,cmap='NCV_jet',edgecolor=None,cnum=20) xlim(0,450) ylim(0,30) xlabel(r'$\rm{PM_{2.5}} \ (\mu g \ m^{-3})$',fontsize=17) ylabel(r'$\rm{Visibility (km)}$',fontname='Arial',fontsize=17) colorbar(ls,fontsize=17,label='RH(%)') #Pow law fitting a,b,r,f = fitting.powerfit(x, y, func=True) #Plot fitting line xx = linspace(x.min(), x.max(), 100) #yy = a*pow(xx, b) yy = fitting.predict(f, xx) plot(xx, yy, '-b', linewidth=2) text(250, 20, r'$y = ' + '%.4f' % a + 'x^{%.4f' % b + '}$', fontsize=16) text(250, 18, r'$r^2=%.4f' % r + '$', fontsize=16)