36 lines
1.1 KiB
Python
36 lines
1.1 KiB
Python
from mathutils import fit_polynomial
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from mathutils import PolynomialFunction
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import math
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from plotutils import plot_function
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print "Starting"
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#Creating averaging devices
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av_hamp_y = create_averager(hamp_y, count = 10, interval = -1, name = "av_hamp_y")
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av_xbpm_y = create_averager(xbpm_y, count = 10, interval = -1, name = "av_xbpm_y")
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av_xbpm_y.monitored = True
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#The actuals scan
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r=lscan(pbpg_my, [av_hamp_y, av_xbpm_y], -0.5, 0.5, 20, latency = 0.0)
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#Fitting
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values = to_array(r.getReadable(0), 'd')
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positions = r.getPositions(0)
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pars_polynomial = (a0, a1) = fit_polynomial(values, positions, 1)
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#Writing metadata to data file
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path = get_exec_pars().scanPath
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set_attribute(path, "a0", a0)
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set_attribute(path, "a1", a1)
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#et_attribute(path, "a2", a2)
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#Plotting fit and writing fitting parameters
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outp = "a0="+ ("%0.4f" % a0) + "a1="+ ("%0.4f" % a1) # "a2="+ ("%0.4f" % a2)
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print outp
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p = get_plots()[0]
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p.addText((min(positions) + max(positions))/2, max(values), outp, Color.BLACK)
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plot_function(p, PolynomialFunction(pars_polynomial), "Fit",positions, show_points = False, show_lines = True, color = Color.BLUE)
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