227 lines
6.7 KiB
Python
Executable File
227 lines
6.7 KiB
Python
Executable File
#!/usr/bin/env python
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#*-----------------------------------------------------------------------*
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#| Copyright (c) 2018 by Paul Scherrer Institute (http://www.psi.ch) |
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#| Author Thierry Zamofing (thierry.zamofing@psi.ch) |
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#*-----------------------------------------------------------------------*
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'''
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implements an image alalyser for ESB MX
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'''
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from scipy import fftpack, ndimage
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import scipy.ndimage as ndi
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import matplotlib.pyplot as plt
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import numpy as np
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#plt.ion()
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def ffttest():
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#find the main frequency and phase in 1-D
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d2r=np.pi/180.
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n=16.
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x=np.arange(n)
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amp=1.
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frq=4.5
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phi=40.*d2r
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y=amp*np.cos(phi+frq*x/n*2.*np.pi)
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#y*=np.hamming(n)
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y*=np.hanning(n)
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#y*=1.-np.cos(x/(n-1.)*2.*np.pi)
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#y=[1,-1,1,-1,1,-1,1,-1,1,-1,1,-1,1,-1,1,-1]
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plt.ion()
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plt.figure()
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plt.stem(x,y)
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fy=np.fft.fft(y)
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fya=np.abs(fy)
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plt.figure()
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plt.subplot(211)
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plt.stem(x,fya)
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plt.subplot(212)
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plt.stem(x,np.angle(fy)/d2r)
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print(np.angle(fy[frq])/d2r)
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i=(fya.reshape(2,-1)[0,:]).argmax()
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(vn,v0,vp)=fya[i-1:i+2]
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frq2=i+(vn-vp)/(2.*(vp+vn-2*v0))
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print('freq: %g phase %g'%(frq2,np.angle(fy[i])/d2r))
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#TODO: THE PHASE CALCULATION IS NOT YET WORKING!!!
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#y_inv=np.fft.fft(fy)
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#plt.figure()
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#plt.plot(x,np.abs(y_inv))
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pass
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def findGrid(image,numPeak=2):
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#image = ndimage.imread('/home/zamofing_t/Documents/prj/SwissFEL/epics_ioc_modules/ESB_MX/python/images/grid_20180409_115332.png', flatten=True) # flatten=True gives a greyscale image
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s=image.shape
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w1=np.hamming(s[0]).reshape((-1,1))
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w2=np.hamming(s[1]).reshape((1,-1))
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wnd=w1*w2
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#plt.figure(num='hamming window')
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#plt.imshow(wnd, interpolation="nearest")
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image=wnd*image
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#plt.figure(num='hamming window*img')
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#plt.imshow(image, interpolation="nearest")
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fft2 = fftpack.fft2(image)
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fft2=np.fft.fftshift(fft2)
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fa =abs(fft2)
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fal =np.log(fa)
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#img=fft3;
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ofs=int(fal.min())
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mx2=(image.shape[0]/2,image.shape[1]/2)
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fal[mx2[0] - 1:mx2[0] + 2, mx2[1] - 1:mx2[1] + 2]=ofs
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for i in range(numPeak*2):
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mx=fal .argmax()
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mx2=divmod(mx,fal .shape[1])
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peakPos=(mx2[0] - image.shape[0] / 2, mx2[1] - image.shape[1] / 2)
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peak=fal[mx2[0] - 1:mx2[0] + 2, mx2[1] - 1:mx2[1] + 2]
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print(peakPos)
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print(peak)
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(vn, v0, vp)=fal[mx2[0], mx2[1] - 1:mx2[1] + 2]
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frq1x=peakPos[1]+(vn-vp)/(2.*(vp+vn-2*v0))
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(vn, v0, vp)=fal[mx2[0]-1:mx2[0]+2,mx2[1]]
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frq1y=peakPos[0]+(vn-vp)/(2.*(vp+vn-2*v0))
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print((frq1x,frq1y))
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fal[mx2[0]-1:mx2[0]+2,mx2[1]-1:mx2[1]+2]=i+ofs
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plt.figure(num='fft of hamming window*img')
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plt.imshow(fal, interpolation="nearest")
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plt.xlim(s[1]/2-50, s[1]/2+50)
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plt.ylim(s[0]/2-50, s[0]/2+50)
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plt.show()
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pass
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def findObj(image,objSize=150,tol=0,viz=0):
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#objSiz is the rough diameter of the searched features in pixels
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#tol = tolerance in object size (not yet implemented)
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#tolShape = roudness tolerance in object roundness (not yet implemented)
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from scipy.signal import convolve2d
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#plt.ion()
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s=image.shape
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#box=np.ones((1,objSize*3),dtype=np.float32)/500.
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#img2=ndi.filters.convolve1d(image,box.reshape(-1),0)
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#img2=ndi.filters.convolve1d(img2,box.reshape(-1),1)
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img2=ndi.filters.uniform_filter(np.float32(image),objSize*2)
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if viz&32:
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plt.imshow(image, interpolation="nearest", cmap='gray')
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plt.figure()
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plt.imshow(img2, interpolation="nearest", cmap='gray')
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#plt.show()
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w=np.where(img2>image)
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img2[w]=image[w]
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img3=image-img2
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if viz&16:
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plt.figure()
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plt.imshow(img3, interpolation="nearest", cmap='gray')
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#plt.show()
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l=int(objSize/30)
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if l>0:
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img4=ndi.binary_fill_holes(img3, structure=np.ones((l,l)))
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if viz&8:
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plt.figure()
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plt.imshow(img4, interpolation="nearest", cmap='gray')
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#plt.show()
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else:
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img4=img3
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l=int(objSize/5)#=int(objSize/10)
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if l>=3:
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#img5=ndi.binary_opening(img4, structure=np.ones((l,l)))
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#img5=ndi.binary_erosion(img4, structure=np.ones((l,l)))
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img5=ndi.binary_erosion(img4, iterations=l)
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if viz&4:
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plt.figure()
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plt.imshow(img5, interpolation="nearest", cmap='gray')
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#plt.show()
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else:
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img5=img4
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import cv2
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#cvi1=np.zeros(shape=img5.shape+(3,), dtype=np.uint8)
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#cvi1[:,:,0]=image
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#image*np.array([1,1,1]).reshape(-1,1,1)
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s=image.shape+(1,)
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cvi1=image.reshape(s)*np.ones((1,1,3),dtype=np.uint8)
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#cvi1=np.ones((3,1,1),dtype=np.uint8)image
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contours, hierarchy=cv2.findContours(np.uint8(img5),cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
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#contours,hierarchy=cv2.findContours(np.uint8(img5),1,2)
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cv2.drawContours(cvi1, contours, -1, (0,255,0), 3)
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plt.figure()
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plt.imshow(cvi1 , interpolation="nearest", cmap='gray')
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m=cv2.moments(contours[0])
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lbl = ndi.label(img5)
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if viz&2:
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plt.figure()
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plt.imshow(lbl[0], interpolation="nearest")
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#plt.show()
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ctr=ndi.measurements.center_of_mass(image, lbl[0],range(lbl[1]))
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ctr=np.array(ctr)
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ctr2=np.ndarray(shape=(len(contours),2),dtype=np.uint16)
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i=0
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for c in contours:
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m=cv2.moments(c)
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try:
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m00=m['m00']
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m10=m['m10']
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m01=m['m01']
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print m00
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if m00>1000 and m00<7000:
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ctr2[i,:]=(m10/m00,m01/m00)
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i+=1
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except ZeroDivisionError:
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pass
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#ctr2[i, :]=c[0,0]
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if viz&1:
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plt.figure()
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plt.imshow(image, interpolation="nearest", cmap='gray')
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plt.plot(ctr[:,1],ctr[:,0],'or',markeredgewidth=2, markersize=10)
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plt.plot(ctr2[:i,0],ctr2[:i,1],'+y',markeredgewidth=2, markersize=10)
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plt.show()
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return ctr
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def genImg(shape,*args):
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'''args is a list of tuples (freq_x,freq_y, phase) multiple args can be added'''
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image=np.ndarray(shape)#,dtype=np.uint8)
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x=np.linspace(0,2*np.pi,shape[1])
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y=np.linspace(0,2*np.pi,shape[0])
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#xx, yy = np.meshgrid(x, y, sparse=True)
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xx, yy = np.meshgrid(x, y)
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for i,f in enumerate(args):
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(freq_x, freq_y, phase)=f
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if i==0:
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image = np.cos(freq_x*xx + freq_y*yy + phase)
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else:
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image += np.cos(freq_x * xx + freq_y * yy + phase)
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plt.imshow(image, interpolation="nearest")
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plt.show()
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return image
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if __name__ == '__main__':
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#ffttest()
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#image = ndimage.imread('/home/zamofing_t/Documents/prj/SwissFEL/epics_ioc_modules/ESB_MX/python/images/grid_20180409_115332.png')
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#image = ndimage.imread('/home/zamofing_t/Documents/prj/SwissFEL/epics_ioc_modules/ESB_MX/python/images/grid_20180409_115332_45deg.png')
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#image=-image
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image=genImg((600,800),(9.5,.2,0))
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#image=genImg((600,800),(9.5,.2,0),(.4,5.2,0))
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#image=genImg((600,800),(9.5,.2,0),(.4,5.2,0),(4,8,0))
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findGrid(image,numPeak=1)
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#findObj(image,viz=1)
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#findObj(image,viz=255)
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#print(findObj(image))
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