def LoadImage(self):
global Image
print('loading image...')
fnametmp = QFileDialog.getOpenFileName(self, 'Open file', './')
fname = fnametmp[0]
print("filename", fname)
Image = imgtl.Load(fname)
Refresh()
def LoadBackground(self):
global Background
print('background')
fnametmp = QFileDialog.getOpenFileName(self, 'Open file', './')
fname = fnametmp[0]
print("filename", fname)
Background = imgtl.Load(fname)
Refresh()
# parameters
bbox = 200
cal = 1
fudge = 0.3
threshold = 0.
# scan over the number of data point
# fileonly = rootname+"-"+str(1+i)+".png"
# filename = UpperDir+"/"+SubDir+"/"+fileonly
filenameBeam = FileDir + FilenameBeam
filenameBkgd = FileDir + FilenameBkgd
# load the image
if test == 0:
IMGbeam = imgtl.Load(filenameBeam)
IMGbkgd = imgtl.Load(filenameBkgd)
IMG = 1. * IMGbeam - IMGbkgd
# IMG=ndimage.gaussian_filter(IMGT, 2)
# ndimage.gaussian_filter(IMGT, sigma=3)
if test == 1:
# this makes a test image
# a gaussian curve
# IMG = 10.+np.random.rand((1296,1606))
IMGT = np.zeros((1296, 1606))
BKGD = np.zeros((1296, 1606))
IMG = np.zeros((1296, 1606))
s = np.shape(IMG)
v = np.linspace(0, s[0], s[0])
h = np.linspace(0, s[1], s[1])
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()
#A. Halavanau. DeKalb, IL (2017) / Menlo Park, CA (2018) import numpy as np import matplotlib.pyplot as plt from scipy.ndimage import rotate import ImageTool as imtl from statistical import * from parameters import * i = 1 pwd = 'examples/Normal_quad_scan_L2/' filename = pwd + 'X111_YAG_' + str(i) + '_bkg_0.png' filenamebg = pwd + 'X111_YAG_' + str(i) + '_img_0.png' data = imtl.Load(filename) bg = imtl.Load(filenamebg) data = data - bg data = data[0:2000, 0:2000] 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])))
