From 434daa84de13363424904fe78946e9bc2987e8ae Mon Sep 17 00:00:00 2001 From: gac-S_Changer Date: Tue, 20 Sep 2016 14:45:10 +0200 Subject: [PATCH] Closedown --- script/ExposureScan.py | 22 ++++++++++++++++ script/local.py | 59 ++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 81 insertions(+) diff --git a/script/ExposureScan.py b/script/ExposureScan.py index e69de29..c381f07 100644 --- a/script/ExposureScan.py +++ b/script/ExposureScan.py @@ -0,0 +1,22 @@ +import ch.psi.pshell.imaging.Data as Data +class Exposure(Writable): + def write(self,pos): + cam.setExposure(pos) +exposure=Exposure() + + +class Contrast(Readable): + def read(self): + data = img.getData() + roi = Data(data.getRectSelection(500,300,700,600)) + return roi.getGradientVariance() +contrast=Contrast() + + +#a= lscan(exposure,img.getContrast(), 0.5, 1.0, 0.01, 0.5) +a= lscan(exposure,contrast, 0.2, 0.4, 0.01, 0.7) + +(n, m, s) = fit(a.getReadable(0), xdata=a.getPositions(0)) +if m is not None: + print "Setting exposure = ", m + exposure.write(m) \ No newline at end of file diff --git a/script/local.py b/script/local.py index b23c823..4a13210 100644 --- a/script/local.py +++ b/script/local.py @@ -60,3 +60,62 @@ g[0]=0x80;r[0]=0x80; g[1]=0xFF ; r[1] = 0x80; b[1] = 0x80 outline_lut2 = (r,g,b) + + + +from mathutils import estimate_peak_indexes, fit_gaussians, create_fit_point_list, Gaussian +import java.awt.Color as Color + +import mathutils +mathutils.MAX_ITERATIONS = 100000 + +def fit(ydata, xdata = None, draw_plot = True): + if xdata is None: + xdata = frange(0, len(ydata), 1) + max_y= max(ydata) + index_max = ydata.index(max_y) + max_x= xdata[index_max] + print "Max index:" + str(index_max), + print " x:" + str(max_x), + print " y:" + str(max_y) + + if draw_plot: + plots = plot([ydata],["data"],[xdata], title="Fit" ) + p = None if plots is None else plots[0] + + gaussians = fit_gaussians(ydata, xdata, [index_max,]) + if gaussians[0] is None: + if draw_plot and (p is not None): + p.addMarker(max_x, None, "Max="+str(round(max_x,4)), Color.GRAY) + print "Fitting error" + return (None, None, None) + + (norm, mean, sigma) = gaussians[0] + if draw_plot: + fitted_gaussian_function = Gaussian(norm, mean, sigma) + scale_x = [float(min(xdata)), float(max(xdata)) ] + points = max((len(xdata)+1), 100) + resolution = (scale_x[1]-scale_x[0]) / points + fit_y = [] + fit_x = frange(scale_x[0],scale_x[1],resolution, True) + for x in fit_x: + fit_y.append(fitted_gaussian_function.value(x)) + #Server + if p is None: + plot([ydata,fit_y],["data","fit"],[xdata,fit_x], title="Fit") + draw_plot = False + else: + p.addSeries(LinePlotSeries("fit")) + p.getSeries(1).setData(fit_x, fit_y) + + if abs(mean - xdata[index_max]) < abs((scale_x[0] + scale_x[1])/2): + if draw_plot: + p.addMarker(mean, None, "Mean="+str(round(mean,4)), Color.MAGENTA.darker()) + print "Mean -> " + str(mean) + return (norm, mean, sigma) + else: + if draw_plot: + p.addMarker(max_x, None, "Max="+str(round(max_x,4)), Color.GRAY) + print "Invalid gaussian fit: " + str(mean) + return (None, None, None) +