Changeset 4587 for trunk

Timestamp:

Oct 8, 2020 9:59:00 AM (3 years ago)

Author:

vondreele

Message:

New version of GetTthAzmDsp? to use det2theta

File:

• trunk/GSASIIimage.py (modified) (4 diffs)

trunk/GSASIIimage.py

@@ -522 +522 @@
     return GetDetectorXY(dsp,Azm,data)
                     
-def GetTthAzmDsp(x,y,data): #expensive
+def GetTthAzmDsp2(x,y,data): #expensive
     '''Computes a 2theta, etc. from a detector position and calibration constants - checked
     OK for ellipses & hyperbola.
@@ -553 +553 @@
     return np.array([tth,azm,G,dsp])
     
+def GetTthAzmDsp(x,y,data): #expensive
+    '''Computes a 2theta, etc. from a detector position and calibration constants - checked
+    OK for ellipses & hyperbola.
+
+    :returns: np.array(tth,azm,G,dsp) where tth is 2theta, azm is the azimutal angle,
+       G is ? and dsp is the d-space
+    '''
+    
+    def costth(xyz):
+        u = xyz/nl.norm(xyz,axis=-1)[:,:,nxs]
+        return np.dot(u,np.array([0.,0.,1.]))
+        
+#zero detector 2-theta: tested with tilted images - perfect integrations
+    wave = data['wavelength']
+    dx = x-data['center'][0]
+    dy = y-data['center'][1]
+    tilt = data['tilt']
+    dist = data['distance']/npcosd(tilt)    #sample-beam intersection point
+    T = makeMat(tilt,0)
+    R = makeMat(data['rotation'],2)
+    MN = np.inner(R,np.inner(R,T))
+    dxyz0 = np.inner(np.dstack([dx,dy,np.zeros_like(dx)]),MN)    #correct for 45 deg tilt
+    dxyz0 += np.array([0.,0.,dist])
+    if data['DetDepth']:
+        ctth0 = costth(dxyz0)
+        tth0 = npacosd(ctth0)
+        dzp = peneCorr(tth0,data['DetDepth'],dist)
+        dxyz0[:,:,2] += dzp
+#non zero detector 2-theta:
+    if data['det2theta']:        
+        tthMat = makeMat(data['det2theta'],1)
+        dxyz = np.inner(dxyz0,tthMat.T)
+    else:
+        dxyz = dxyz0
+    ctth = costth(dxyz)
+    tth = npacosd(ctth)
+    dsp = wave/(2.*npsind(tth/2.))
+    azm = (npatan2d(dxyz[:,:,1],dxyz[:,:,0])+data['azmthOff']+720.)%360.        
+# G-calculation        
+    x0 = data['distance']*nptand(tilt)
+    x0x = x0*npcosd(data['rotation'])
+    x0y = x0*npsind(data['rotation'])
+    distsq = data['distance']**2
+    G = ((dx-x0x)**2+(dy-x0y)**2+distsq)/distsq       #for geometric correction = 1/cos(2theta)^2 if tilt=0.
+    return np.array([tth,azm,G,dsp])
+    
 def GetTth(x,y,data):
     'Give 2-theta value for detector x,y position; calibration info in data'
@@ -589 +635 @@
      calibration info in data - only used in integration
      checked OK for ellipses & hyperbola
-     '''
-     
+     This is the slow step in image integration
+     '''     
     def costth(xyz):
         u = xyz/nl.norm(xyz,axis=-1)[:,:,nxs]
@@ -610 +656 @@
         dzp = peneCorr(tth0,data['DetDepth'],dist)
         dxyz0[:,:,2] += dzp
-#non zero detector 2-theta:    
-    tthMat = makeMat(data['det2theta'],1)
-    dxyz = np.inner(dxyz0,tthMat.T)
+#non zero detector 2-theta:
+    if data['det2theta']:        
+        tthMat = makeMat(data['det2theta'],1)
+        dxyz = np.inner(dxyz0,tthMat.T)
+    else:
+        dxyz = dxyz0
     ctth = costth(dxyz)
     tth = npacosd(ctth)
-    azm = (npatan2d(dxyz[:,:,1],dxyz[:,:,0])+data['azmthOff']+720.)%360.
+    azm = (npatan2d(dxyz[:,:,1],dxyz[:,:,0])+data['azmthOff']+720.)%360.        
 # G-calculation        
     x0 = data['distance']*nptand(tilt)