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)