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)
