37 lines
1.3 KiB
Python
Executable File
37 lines
1.3 KiB
Python
Executable File
###################################################################################################
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# Multiple Gaussians peak search with mathutils.py
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###################################################################################################
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from mathutils import estimate_peak_indexes, fit_gaussians, create_fit_point_list
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import java.awt.Color as Color
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start = 0
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end = 50
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step_size = 0.2
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result= lscan(ao1,ai1,start,end,[step_size,])
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readable = result.getReadable(0)
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positions = result.getPositions(0)
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threshold = (min(readable) + max(readable))/2
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min_peak_distance = 5.0
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peaks = estimate_peak_indexes(readable, positions, threshold, min_peak_distance)
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print "Peak indexes: " + str(peaks)
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print "Peak x: " + str(map(lambda x:positions[x], peaks))
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print "Peak y: " + str(map(lambda x:readable[x], peaks))
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gaussians = fit_gaussians(readable, positions, peaks)
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plots = plot([readable],["sin"],[positions], title="Data" )
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for i in range(len(peaks)):
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peak = peaks[i]
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(normalization, mean_val, sigma) = gaussians[i]
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if abs(mean_val - positions[peak]) < min_peak_distance:
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print "Peak -> " + str(mean_val)
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plots[0].addMarker(mean_val, None, "N="+str(round(normalization,2)), Color(210,0,0))
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else:
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print "Invalid gaussian fit: " + str(mean_val)
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