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]))
