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  • angle phi is evaluated using two peak positions and sample-to-detector distance
  • angle beta is evaluated using one !!! peak position and angle phi.
  • peak and event selection need to be improved
  • it could be nice to have explanation to this formalism...

Angles phi and beta from fit

Solving equation for tan(theta) we may get functional dependence between x and y peak position for angles phi and theta,

Code Block
funy(x,phi,beta)

(warning) this function presents a solution of quadratic equation which has two roots. The root is selected depending on sign of theta angle...(question)

This function is parameterized in python script fiber_angles.py and can be plotted for different angles:


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Similar function is used in data processing to fit peak (x,y) positions in equatorial region and use two angles as a fit parameters.

Code Block
from scipy.optimize import curve_fit

def funcy(x, phi_deg, bet_deg) :
    # ATTENTION! x is treated as numpy array..., 
    # so function should also return numpy array of the same size
    <some parameterization>

def procEventEqu() :
    # summary for event
    if sp.count_equ_pks_sel > 1 :
        yn = [-line[4] / L for line in sp.lst_equ_evt_peaks]
        xn = [ line[5] / L for line in sp.lst_equ_evt_peaks]
        #? yn.append(0)
        #? xn.append(0)
        en = np.ones_like(xn)
        p0 = [-3.1,-5.1]
        popt, pcov = curve_fit(funcy, xn, yn, p0, en)

results of the fit to peaks found in each event gives distributions for two angles:

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References

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