def fit_gauss(lroi, imp, p, peak_id, id_, type_, rm):
lroi.setName("{}_{}_{}".format(str(id_), peak_id, type_))
imp.setRoi(lroi)
rm.addRoi(lroi)
prof = ProfilePlot(imp)
y = prof.getProfile()
x = xrange(len(y))
fitter = CurveFitter(x, y)
fitter.doFit(CurveFitter.GAUSSIAN)
param_values = fitter.getParams()
std = param_values[3]
fwhm = 2.3548 * std
r2 = fitter.getFitGoodness()
y_ = [fitter.f(x_) for x_ in x]
area_profile = sum(y) - len(y) *min(y)
area_gauss = sum(y_) - len(y_)*min(y_)
output = {}
output["x_pos"] = p.x
output["y_pos"] = p.y
output["fwhm"] = fwhm
output["fwhm_nm"] = pixel_size_nm * fwhm
output["r2_GoF"] = r2
output["id"] = id_
output["peak_id"] = peak_id
output["type"] = type_
# yai, excel maagic :-)
output["avg_fwhm"] = '=AVERAGEIFS(F:F,B:B,B{},F:F,"<>"&"")'.format(id_+2)
output["area_profile"] = area_profile
output["area_gauss"] = area_gauss
if peak_id == DEBUG:
plot = Plot("ROI peak {} type {}".format(peak_id, type_), "X (gray)", "Y (fit window)")
plot.setLineWidth(2)
plot.setColor(Color.RED)
plot.addPoints(x, y, Plot.LINE)
plot.setColor(Color.BLUE)
plot.addPoints(x, y_, Plot.LINE)
plot.show()
return output
cv = CurveFitter([a[0] for a in spshifts],
[8 - a[1] for a in spshifts])
# fit the distortion measurements
cv.doFit(CurveFitter.EXP_WITH_OFFSET)
# cv.doFit(CurveFitter.EXPONENTIAL)
# cv.doFit(CurveFitter.POLY2)
# cv.doFit(CurveFitter.POLY3)
plot = cv.getPlot()
plot.show()
8 / 0
plot_images.append(plot.getImagePlus())
IJ.log('sFOV ' + str(sFOV))
IJ.log('fitGoodness ' + str(cv.getFitGoodness()))
IJ.log('formula ' + str(cv.getFormula()))
fit_params = cv.getParams()
IJ.log('fit_params' + str(fit_params))
# write the fit results to file
g.write('sFOV\t' + str(sFOV) + '\t' + 'a\t' + str(fit_params[0]) +
'\t' + 'b\t' + str(fit_params[1]) + '\t' + 'c\t' +
str(fit_params[2]) + '\t' + 'formula\t' +
str(cv.getFormula()) + '\t' + 'fitGoodness\t' +
str(cv.getFitGoodness()) + '\n')
# # # # # The following commented code applies a scan correction using bigwarp.
# # # # # A grid of landmarks is generated, saved into bigwarp format, then applied.
# # # # # It is slow and needs to be optimized.
