Xb = pyl.imread(filenameBk) X=Xi-Xb Xc=imgtl.RemoveEdge(X, 0) plt.imshow(Xc) IMGf=imgtl.AutoCrop(Xc, 2000) histx, histy, x, y = imgtl.GetImageProjection(IMGf,cal) x=x-x[np.argmax(histx)] y=y-y[np.argmax(histy)] p2X= imgtl.FitProfile(histx, x) p2Y= imgtl.FitProfile(histy, y) print("fitX: ", p2X) print("fitY: ", p2Y) plt.figure() disp=filenameIm.split('/') print(disp) print(len(disp))
import ImageTool as imtl import numpy as np import pylab as pyl import matplotlib.pyplot as plt import pydefaults # directory upperfile = "/Users/piot/ASTA_commissioning/quadscan/X121_20150601//tight_focus/" filename = "nml-2015-06-01-2205-23-13076.png" # in um/pixel cal = 9. thres = 0.02 A = imtl.Load(upperfile + filename) B = imtl.AutoCrop(A, 100) C = imtl.Threshold(B, thres) #imtl.DisplayCalibrated(B, cal) imtl.DisplayCalibratedProj(B, cal, 0.3) plt.xlabel('x ($\mu$m)', fontsize=24) plt.ylabel('y ($\mu$m)', fontsize=24) plt.title(filename, fontsize=24) plt.tight_layout() plt.show()
data = imtl.Normalize(data) #experimental data_rot = data.copy() data_rot = rotate(data, skew, reshape=False) x, y = imtl.ImageFit(data_rot, 1.0, True) print "Image center is at: ", int(x[0]), int(y[0]) print "Gaussian fit sizes (px): ", int(x[2]), int(y[2]) print "Gaussian fit sizes (m): ", cal * x[2], cal * y[2] sigma_max = int(np.max((x[2], y[2]))) sigma_min = int(np.min((x[2], y[2]))) #initial crop box = int(4.7 * sigma_max) data = imtl.AutoCrop(data, box, box) data = imtl.Denoise(data) #x,y = imtl.ImageFit(data,cal) #print "Gaussian fit: ",x,y if (quiet != True): plt.figure() extent = (0, len(data[:, 0]), 0, len(data[:, 1])) plt.imshow(data, extent=extent) plt.xlabel('x (px)') plt.ylabel('y (px)') plt.tight_layout() plt.show() xx, yy, xy = image_moments(data, int(x[2]), int(y[2]))