from mathutils import fit_polynomial
from mathutils import PolynomialFunction
import math
from plotutils import plot_function
print "Starting"


#Creating averaging devices
av_adc_xh1 = create_averager(adc_xh1, count = 10, interval = -1, name = "av_adc_xh1")
av_adc_xh2 = create_averager(adc_yh2, count = 10, interval = -1, name = "av_adc_xh2")
av_adc_xh2.monitored = True

#The actuals scan
r=lscan(pbpg_mx, [av_adc_xh1, av_adc_xh2], 0.0, 0.5, 10, latency = 0.0)

#Fitting 
values = to_array(r.getReadable(0), 'd')
positions = r.getPositions(0)
pars_polynomial = (a0, a1, a2) = fit_polynomial(values, positions, 2)

#Writing metadata to data file
path = get_exec_pars().scanPath
set_attribute(path, "a0", a0)      
set_attribute(path, "a1", a1)      
set_attribute(path, "a2", a2)      

#Plotting fit and writing fitting parameters
outp = "a0="+ ("%0.4f" % a0) + "a1="+  ("%0.4f" % a1) + "a2="+  ("%0.4f" % a2)
print outp
p = get_plots()[0]
p.addText((min(positions) + max(positions))/2, max(values), outp, Color.BLACK)
plot_function(p, PolynomialFunction(pars_polynomial), "Fit",positions, show_points = False, show_lines = True, color = Color.BLUE)