good working findxtal.py

python/findxtal.py

@@ -81,7 +81,7 @@ def ffttest2(phi=45.,frq=4.2,amp=1.,n=256.):
 
   pass
 
-def findGrid(image,numPeak=2):
+def findGrid(image,numPeak=2,limFrq=None,debug=255):
   d2r=np.pi/180.
   #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
   s=image.shape
@@ -97,21 +97,28 @@ def findGrid(image,numPeak=2):
   fft2 = np.fft.fft2(image)
   fft2=np.fft.fftshift(fft2)
   fa =abs(fft2)
-  plt.figure(num='log of fft: hamming wnd*image')
+  if debug&1:
-  hi=plt.imshow(fa, interpolation="nearest",norm=mpl.colors.LogNorm(vmin=.1, vmax=fa.max()))
+    plt.figure(num='log of fft: hamming wnd*image')
-  #plt.xlim(s[1]/2-50, s[1]/2+50);plt.ylim(s[0]/2-50, s[0]/2+50)
+    hi=plt.imshow(fa, interpolation="nearest",norm=mpl.colors.LogNorm(vmin=.1, vmax=fa.max()))
+    #plt.xlim(s[1]/2-50, s[1]/2+50);plt.ylim(s[0]/2-50, s[0]/2+50)
 
   ctr=np.array(image.shape,dtype=np.int16)/2
   fa[ctr[0] - 1:ctr[0] + 2, ctr[1] - 1:ctr[1] + 2]=0 # set dc to 0
-  hi.set_data(fa)
+  # limit to maximal frequency
-  gen = np.zeros(fft2.shape)
+  if limFrq is not None:
+    fa[:ctr[0]-limFrq,:]=0;fa[ctr[0]+limFrq:,:]=0
+    fa[:,:ctr[1]-limFrq]=0;fa[:,ctr[1]+limFrq:]=0
   x=np.arange(s[1])/float(s[1])*2.*np.pi
   y=np.arange(s[0])/float(s[0])*2.*np.pi
-  #x=np.linspace(0,2*np.pi,s[1],endpoint=False)
+  if debug&1:
-  #y=np.linspace(0,2*np.pi,s[0],endpoint=False)
+    hi.set_data(fa)
+    gen = np.zeros(fft2.shape)
+    #x=np.linspace(0,2*np.pi,s[1],endpoint=False)
+    #y=np.linspace(0,2*np.pi,s[0],endpoint=False)
+    xx, yy = np.meshgrid(x, y)
+
   my=int(s[0]/2)
   mx=int(s[1]/2)
-  xx, yy = np.meshgrid(x, y)
 
   res=[] #list of tuples (freq_x,freq_y, phase)
   for i in range(numPeak):
@@ -119,8 +126,9 @@ def findGrid(image,numPeak=2):
     maxAmpPos=np.array(divmod(maxAmpIdx,fa.shape[1]),dtype=np.int16)
     peakPos=maxAmpPos-ctr
     peak=fft2[maxAmpPos[0] - 1:maxAmpPos[0] + 2, maxAmpPos[1] - 1:maxAmpPos[1] + 2]
-    print(peakPos)
+    if debug&2:
-    print(abs(peak))
+      print(peakPos)
+      print(abs(peak))
     (vn, v0, vp)=np.log(fa[maxAmpPos[0], maxAmpPos[1] - 1:maxAmpPos[1] + 2]) #using log for interpolation is more precise
     freq_x=peakPos[1]+(vn-vp)/(2.*(vp+vn-2*v0))
     (vn, v0, vp)=np.log(fa[maxAmpPos[0]-1:maxAmpPos[0]+2,maxAmpPos[1]])
@@ -137,9 +145,10 @@ def findGrid(image,numPeak=2):
         fy=peakPos[0]+iy
         amp=np.abs(v)/n; ang=np.angle(v)
         sumAmp+=amp
-        sumCos+=amp*np.cos(fx*x[mx] + fy*y[my] + ang)
+        sumCos+=amp*np.cos(fx*x[mx+ix] + fy*y[my+iy] + ang)
-        sumSin+=amp*np.sin(fx*x[mx] + fy*y[my] + ang)
+        sumSin+=amp*np.sin(fx*x[mx+ix] + fy*y[my+iy] + ang)
-        gen+=amp*np.cos(fx*xx + fy*yy + ang)
+        if debug&1:
+          gen+=amp*np.cos(fx*xx + fy*yy + ang)
     sumAmp*=2. #double because of conjugate part
     sumCos*=2.
     sumSin*=2.
@@ -148,32 +157,82 @@ def findGrid(image,numPeak=2):
     if sumSin<0: w=-w
     phi_= freq_x*x[mx]+freq_y*y[my]-w
     phi_%=(np.pi*2)
+    #have main frequency positive and phase positive (for convinient)
+    if (freq_x<0 and abs(freq_x)> abs(freq_y)) or \
+       (freq_y<0 and abs(freq_y)> abs(freq_x)):
+      freq_x = -freq_x; freq_y = -freq_y; phi_=-phi_
+    if phi_<0: phi_+=2*np.pi
+
     res.append((freq_x,freq_y,phi_))
     fa[maxAmpPos[0]-1:maxAmpPos[0]+2,maxAmpPos[1]-1:maxAmpPos[1]+2]=0 # clear peak
     maxAmpPos_=2*ctr-maxAmpPos
     fa[maxAmpPos_[0]-1:maxAmpPos_[0]+2,maxAmpPos_[1]-1:maxAmpPos_[1]+2]=0 # clear conjugated peak
-    hi.set_data(fa)
+    if debug&1:
+      hi.set_data(fa)
 
-  gen*=2. # double because of conjugate part
+  if debug&1:
-  for fx,fy,phase in res:
+    gen*=2. # double because of conjugate part
-    print('fx: %g fy: %g phase: %g deg'%(fx,fy,phase/d2r))
+  if debug&2:
+    for fx,fy,phase in res:
+      print('fx: %g fy: %g phase: %g deg'%(fx,fy,phase/d2r))
+
+  if debug&1:
+    plt.xlim(s[1]/2-50, s[1]/2+50)
+    plt.ylim(s[0]/2-50, s[0]/2+50)
+    plt.figure('image*wnd')
+    plt.imshow(image,interpolation="nearest")
+    plt.figure('reconstruct')
+    plt.imshow(gen,interpolation="nearest")
+
+    plt.figure()
+    x=range(s[1])
+    y=int(s[0]/2)-1
+    plt.plot(x,image[y,:],'r')
+    plt.plot(x,gen[y,:],'g')
+  return res
+
+def plotGrid(grid,shape):
+  #x=np.linspace(0,2*np.pi,shape[1],endpoint=False)
+  #y=np.linspace(0,2*np.pi,shape[0],endpoint=False)
+  #for (freq_x, freq_y, phase) in grid:
+  #find points were: np.cos(freq_x*xx + freq_y*yy - phase) is max
+  #freq_x*xx + freq_y*yy - phase = 0 2pi, 4pi
+  # grid should have 2 entries
+  # -> 2 equations to solve
+  # points for:
+  # entry1 entry2 = (0 0), (0, 2*pi), (2*pi 0)
+  (fx0,fy0,p0)=grid[0]
+  (fx1,fy1,p1)=grid[1]
+  A=np.array([[fx0,fy0],[fx1,fy1]])
+  A*=np.array([2*np.pi/shape[1],2*np.pi/shape[0]])
+  Ai=np.asmatrix(A).I
 
 
-  plt.xlim(s[1]/2-50, s[1]/2+50)
+  na=int(max(abs(fx0),abs(fy0)))+1
-  plt.ylim(s[0]/2-50, s[0]/2+50)
+  nb=int(max(abs(fx1),abs(fy1)))+1
-  plt.figure('image*wnd')
+  p=np.ndarray((na*nb,2))
-  plt.imshow(image,interpolation="nearest")
+  #p=np.ndarray((3,2))
-  plt.figure('reconstruct')
+  #i=0
-  plt.imshow(gen,interpolation="nearest")
+  #for x,y in ((0,0),(1,0),(0,1)):
+  #  v = np.array([p0+x*2.*np.pi, p1+y*2.*np.pi]).reshape(-1, 1)
+  #  p[i,:]=(Ai*v).reshape(-1)
+  #  i+=1
 
-  plt.figure()
+  i=0
-  x=range(s[1])
+  for b in range(nb):
-  y=int(s[0]/2)-1
+    for a in range(na):
-  plt.plot(x,image[y,:],'r')
+      v = np.array([p0+a*2.*np.pi, p1+b*2.*np.pi]).reshape(-1, 1)
-  plt.plot(x,gen[y,:],'g')
+      p[i,:]=(Ai*v).reshape(-1)
+      i+=1
+
+
+
+
+  #plt.plot([400,500],[400,500],'r+',markeredgewidth=2, markersize=10)
+  plt.plot(p[:,0],p[:,1],'r+',markeredgewidth=2, markersize=10)
+  plt.axis('image')
   pass
-
+def findObj(image,objSize=150,tol=0,debug=0):
-def findObj(image,objSize=150,tol=0,viz=0):
 
   #objSiz is the rough diameter of the searched features in pixels
   #tol      = tolerance in object size (not yet implemented)
@@ -188,7 +247,7 @@ def findObj(image,objSize=150,tol=0,viz=0):
   #img2=ndi.filters.convolve1d(img2,box.reshape(-1),1)
   img2=ndi.filters.uniform_filter(np.float32(image),objSize*2)
 
-  if viz&32:
+  if debug&32:
     plt.imshow(image, interpolation="nearest", cmap='gray')
     plt.figure()
     plt.imshow(img2, interpolation="nearest", cmap='gray')
@@ -196,14 +255,14 @@ def findObj(image,objSize=150,tol=0,viz=0):
   w=np.where(img2>image)
   img2[w]=image[w]
   img3=image-img2
-  if viz&16:
+  if debug&16:
     plt.figure()
     plt.imshow(img3, interpolation="nearest", cmap='gray')
     #plt.show()
   l=int(objSize/30)
   if l>0:
     img4=ndi.binary_fill_holes(img3, structure=np.ones((l,l)))
-    if viz&8:
+    if debug&8:
       plt.figure()
       plt.imshow(img4, interpolation="nearest", cmap='gray')
       #plt.show()
@@ -215,7 +274,7 @@ def findObj(image,objSize=150,tol=0,viz=0):
     #img5=ndi.binary_opening(img4, structure=np.ones((l,l)))
     #img5=ndi.binary_erosion(img4, structure=np.ones((l,l)))
     img5=ndi.binary_erosion(img4, iterations=l)
-    if viz&4:
+    if debug&4:
       plt.figure()
       plt.imshow(img5, interpolation="nearest", cmap='gray')
       #plt.show()
@@ -237,7 +296,7 @@ def findObj(image,objSize=150,tol=0,viz=0):
   m=cv2.moments(contours[0])
 
   lbl = ndi.label(img5)
-  if viz&2:
+  if debug&2:
     plt.figure()
     plt.imshow(lbl[0], interpolation="nearest")
     #plt.show()
@@ -259,7 +318,7 @@ def findObj(image,objSize=150,tol=0,viz=0):
       pass
        #ctr2[i, :]=c[0,0]
 
-  if viz&1:
+  if debug&1:
     plt.figure()
     plt.imshow(image, interpolation="nearest", cmap='gray')
     plt.plot(ctr[:,1],ctr[:,0],'or',markeredgewidth=2, markersize=10)
@@ -281,32 +340,56 @@ def genImg(shape,*args):
       image = dc+np.cos(freq_x*xx + freq_y*yy - phase)
     else:
       image += np.cos(freq_x * xx + freq_y * yy - phase)
-
-  plt.imshow(image, interpolation="nearest")
   return image
 
 if __name__ == '__main__':
   #plt.ion()
   #ffttest()
-  image = ndimage.imread('/home/zamofing_t/Documents/prj/SwissFEL/epics_ioc_modules/ESB_MX/python/images/grid_20180409_115332.png')
+
-  #image = ndimage.imread('/home/zamofing_t/Documents/prj/SwissFEL/epics_ioc_modules/ESB_MX/python/images/grid_20180409_115332_45deg.png')
+  image = ndimage.imread('/home/zamofing_t/Documents/prj/SwissFEL/epics_ioc_modules/ESB_MX/python/images/honeycomb.png')
   image=-image
-  #image = ndimage.imread('/home/zamofing_t/Documents/prj/SwissFEL/epics_ioc_modules/ESB_MX/python/images/honeycomb.png')
+  grid=findGrid(image,numPeak=2,limFrq=25,debug=2)
+  plt.imshow(image, interpolation="nearest", cmap='gray')
+  plotGrid(grid,image.shape)
+  plt.show()
+
+  image = ndimage.imread('/home/zamofing_t/Documents/prj/SwissFEL/epics_ioc_modules/ESB_MX/python/images/grid_20180409_115332.png')
+  image=-image
+  grid=findGrid(image,numPeak=2,debug=2)
+  plt.imshow(image, interpolation="nearest", cmap='gray')
+  plotGrid(grid,image.shape)
+  plt.show()
+
+  image = ndimage.imread('/home/zamofing_t/Documents/prj/SwissFEL/epics_ioc_modules/ESB_MX/python/images/grid_20180409_115332_45deg.png')
+  image=-image
+  grid=findGrid(image,numPeak=2,debug=2)
+  plt.imshow(image, interpolation="nearest", cmap='gray')
+  plotGrid(grid,image.shape)
+  plt.show()
+
+  objPos=findObj(image,debug=1)
+  plt.show()
+
 
   d2r=np.pi/180.
   #for phi in np.arange(0.,180.,10.):
   #  image = genImg((600, 800), (4.5, .2, phi*d2r))
   #  plt.show()
   #image=genImg((600,800),(4.,1.0,10.*d2r))
-  #image=genImg((600,800),(4.5,.2,20.*d2r))
+  #image=genImg((600,800),(4.5,-3.2,70.*d2r))
+  #image=genImg((600,800),(-4.5,3.2,290.*d2r)) #same image
   #findGrid(image,numPeak=1)
+  #findGrid(image,numPeak=1,debug=2)
 
-  #image=genImg((600,800),(9.5,.2,20.*d2r),(.4,5.2,60.*d2r))
+  #for v in np.arange(0,2,.3):
-  #image=genImg((600,800),(3.5,0.,0.*d2r),(0,5.,0.*d2r))
+  #  image=genImg((600,800),(8,.2+v,40.*d2r),(.4,5.2,30.*d2r))
-  findGrid(image,numPeak=2)
+  #  grid=findGrid(image,numPeak=2,debug=2)
-
+  #  plt.figure(1);plt.cla()
+  #  plt.imshow(image, interpolation="nearest", cmap='gray')
+  #  plotGrid(grid,image.shape)
+  #  plt.show()
   #image=genImg((600,800),(9.5,.2,0),(.4,5.2,0),(4,8,0))
   #findObj(image,viz=1)
   #findObj(image,viz=255)
   #print(findObj(image))
-  plt.show()
+