Closedown

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)

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)
+