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Table of Contents

Phi-beta fit function

pyimgalgos/src/FiberAngles.py

y = funcy_l1_v1(x, phi_deg, bet_deg, DoR=392/913.27, sgnrt=-1.)

Two solutions of quadratic equation

POS: y = -B + sqrt(B*B-C)
NEG: y = -B - sqrt(B*B-C)

Legend:

dot curves for negative beta
black bold curve for beta=0
solid curves for positive beta

Arc region

wide range of x:

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narrow range of x:

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Equatorial region

Problem with two roots is resolved for EQU region; sign of the root is selected the same as sign of parameter B;

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For |beta|>~48 solution does not exist for entire range of x

Data

exp=cxif5315:run=169

Fit in the processing script

Example of Here we discuss how to apply fit to data using absolute errors on peak position, get fit parameters with errors, estimate fit quality.

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exp=cxif5315:run=169

Fit in the processing script

cxif5315/proc-cxif5315-r0169-peaks-from-file-v4.py, v5, v6

Code Block

title	essential code

from scipy.optimize import curve_fit
from scipy.stats import chi2

        xn = np.array([pk.x/L for pk in sp.lst_equ_evt_peaks], dtype=np.double)
        yn = np.array([pk.y/L for pk in sp.lst_equ_evt_peaks], dtype=np.double)
        en = np.array([pk.csigma*sp.PIXEL_SIZE/L for pk in sp.lst_equ_evt_peaks], dtype=np.double)
        #en = np.array([max(pk.rsigma,pk.csigma)*sp.PIXEL_SIZE/L for pk in sp.lst_equ_evt_peaks], dtype=np.double)

        p0 = [-3.2,-16.0] # phi, beta angle central values

            popt, pcov = curve_fit(funcy, xn, yn, p0, en, absolute_sigma=True)
 
            sp.fib_chi2 = np.sum(((funcy(xn, *popt) - yn) / en)**2)
            sp.fib_ndof = len(xn) - 1
            sp.fib_prob = chi2.sf(sp.fib_chi2, sp.fib_ndof, loc=0, scale=1)

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