def exportTransformedCoordinates_triggered(self): '''export coordinate file list of tranformed points for all layers''' for i in xrange(1,self.ui.fileWidget.count()): listItem = self.ui.fileWidget.item(i) filename = listItem.data(QtCore.Qt.DisplayRole).toString() name = QtCore.QFileInfo(filename).fileName() # without path newfilename = QtGui.QFileDialog.getSaveFileName(self.main_window, "Save Coordinate List %s" % name, filter="Coordinate List (*.txt)") if not newfilename.contains('.'): newfilename += ".txt" # add default extension dimensions, points = coords.readfile(filename) p_transformed = self.transformcontroller.doTransform(points[:,0:2], i) points[:,0:2] = p_transformed coords.writefile(newfilename, dimensions[0:2], points)
beadMeans, beadScatter = detectBeads(dims, cc) print "number of beads: ", len(beadMeans) #~ print singleConsidered, "single detections considered." #~ print skipped, "beads skipped." print "mean variance: %f" % (np.mean(beadScatter, axis=0)[1]) #plot: import matplotlib.pyplot as plt xx,yy=np.hsplit(np.array(beadScatter),np.array([1])) plt.plot(xx,yy,'rx') plt.xlabel('Beat Intensity') plt.ylabel('stddev of detected position') plt.title('STORM: localisation precision at different beat intensities') plt.ylabel('stddev of detected position') plt.savefig(filename+"_beadVariance.png") plt.figure() xx,yy=np.hsplit(np.array(beadMeans),np.array([1])) plt.plot(xx,yy,'ro') plt.title(filename) plt.xlabel('x') plt.ylabel('y') plt.savefig(filename+"_beads.png") plt.show() if len(beadMeans) > 0: meanData_np = np.array(beadMeans) outData = np.hstack([meanData_np, np.arange(len(meanData_np)).reshape(-1,1)]) # add index column coord2im.writefile(filename+"_beads.txt", dims, outData)