merge, match to and from file, other

Author: francescorandi

dsmm/dsmm.cpp

@@ -360,6 +360,17 @@ void dsmm::_dsmm(double *X, double *Y, int M, int N, int D,
         // Find average of minimum distance between any Y and X.
         double mindist;
         double avgmindist=0.0;
+        
+        /**for(int m=0;m<M;m++){
+            mindist = pwise_dist[m*N];
+            for(int m2=0;m2<M;m2++){
+                if(mindist>pwise_dist[m*N+m2]){
+                    mindist=pwise_dist[m*N+m2];
+                }
+            }
+            avgmindist += mindist;
+        }
+        avgmindist /= M;**/
 
 		for(int m=0;m<M;m++){
             mindist = pwise_dist[m*N];
@@ -395,22 +406,25 @@ void dsmm::_dsmm(double *X, double *Y, int M, int N, int D,
             Match[m] = -1;
         }
     }
-		
-	// "Denormalize" in Vemuri's language. Since Y has been moved onto X,
-	// denormalize both with the parameters originally used to normalize X.
-	for(int n=0;n<N;n++){
-		for(int d=0;d<D;d++) {
-			X[n*D+d] *= MaxX[d];
-			X[n*D+d] += AvgX[d];
-		}
-	}
+	
+	bool denormalize = true;
+	if(denormalize) {	
+	    // "Denormalize" in Vemuri's language. Since Y has been moved onto X,
+	    // denormalize both with the parameters originally used to normalize X.
+	    for(int n=0;n<N;n++){
+		    for(int d=0;d<D;d++) {
+			    X[n*D+d] *= MaxX[d];
+			    X[n*D+d] += AvgX[d];
+		    }
+	    }
 
-	for(int m=0;m<M;m++){
-		for(int d=0;d<D;d++) {
-			Y[m*D+d] *= MaxX[d];
-			Y[m*D+d] += AvgX[d];
-		}
-	}
+	    for(int m=0;m<M;m++){
+		    for(int d=0;d<D;d++) {
+			    Y[m*D+d] *= MaxX[d];
+			    Y[m*D+d] += AvgX[d];
+		    }
+	    }
+    }
 
 	delete[] AvgX;
 	delete[] MaxX;

wormbrain/brains.py

@@ -63,7 +63,7 @@ def __init__(self, coordZYX, nInVolume, zOfFrame=None, properties={},
                     nPlane=self.boxNPlane, boxIndices=self.boxIndices,
                     method="xyMaxCurvature")
 
-            self.coord = np.rint(self.coord)
+                self.coord = np.rint(self.coord)
 
         self.coord = self.coord.astype(int)
 
@@ -89,6 +89,12 @@ def from_find_neurons(cls, coord, volFrame0=None, *args, **kwargs):
         '''
         if volFrame0 is None:
             volFrame0 = np.arange(len(coord)+1,dtype=int)
+        try:
+            rectype = kwargs.pop('rectype')
+        except:
+            rectype = "3d"
+        if rectype == "2d":
+            kwargs['stabilize_z'] = False
 
         coordZYX, nInVolume, nInFrame = cls._conv_coord_2d_to_3d(coord, 
                                         volFrame0, dtype=int)
@@ -136,7 +142,27 @@ def from_file(cls, folder, filename=""):
         stabilize_z = False 
 
         return cls(coordZYX, nInVolume, zOfFrame, properties, stabilize_z)
-
+    
+    def append(self, brains2):
+        '''Append to this object the content of another instance of Brains.
+        It does not perform any z-stabilization. Assumes the curvature in 
+        brains2 was extracted the same way as in this instance.
+        (Modify stuff mimicking __init__()).
+        '''
+        self.nInVolume = np.append(self.nInVolume, brains2.nInVolume)
+        self.coord = np.append(self.coord, brains2.coord, axis=0)
+        self.coord = irrarray(self.coord, [self.nInVolume], strideNames=["vol"])
+        
+        # Concatenate
+        self.zOfFrame = self.zOfFrame + brains2.zOfFrame
+        
+        self.curvature = np.append(self.curvature, brains2.curvature)
+        self.curvature = irrarray(self.curvature, self.nInVolume, 
+                                        strideNames=["vol"])
+        
+        self.coord = self.coord.astype(int)
+        
+    
     def __getitem__(self, i):
         '''
         Allow for direct indexing of the class to access the coordinates.
@@ -369,9 +395,14 @@ def _stabilize_z(coord, curvature, nPlane=7, boxIndices=
                 centralIndices[pl] = boxIndices[pl][sh0//2]
             curv = curvature[:,centralIndices] #look just along z
 
-        coord[:,z_index] = coord[:,z_index].astype(float) + np.sum(z*curv,axis=1)/np.sum(curv,axis=1)
+        coord_3d_out = np.zeros_like(coord,dtype=np.float)
+        if coord_3d_ordering=="zyx":
+            coord_3d_out[:,1:3] = coord[:,1:3]
+        else:
+            coord_3d_out[:,0:2] = coord[:,0:2]
+        coord_3d_out[:,z_index] = coord[:,z_index].astype(np.float) + np.sum(z*curv,axis=1)/np.sum(curv,axis=1)
 
-        return coord
+        return coord_3d_out
 
     def fit_sphere(self):
         curvature = self.curvature

wormbrain/match.py

@@ -3,6 +3,8 @@
 from mpl_toolkits.mplot3d import Axes3D
 import wormbrain as wormb
 
+filename_matches = "matches.txt"
+
 def pairwise_distance(A,B,returnAll=False,squared=False,thresholdDz=0.0):
     '''
     Calculates the pairwise distance between points belonging to two sets of 
@@ -119,6 +121,28 @@ def _match_nearest(A, B, **kwargs): #TODO implement it on multiple As
 
     return Match
 
+def save_matches(MMatch, folder):
+    if folder[-1]!="/": folder+="/"
+    f = open(folder+filename_matches,"w")
+    
+    if type(MMatch)!=list: MMatch = [MMatch]
+    
+    for Match in MMatch:
+        Match.tofile(f,sep=" ")
+        f.write("\n")
+    f.close()
+    
+def load_matches(folder):
+    if folder[-1]!="/": folder+="/"
+    f = open(folder+filename_matches,"r")
+    
+    MMatch = []
+    for line in f.readlines():
+        Match = np.fromstring(line,dtype=int,sep=" ")
+        MMatch.append(Match)
+        
+    return MMatch
+    
 
 def plot_matches(A, B, Match, mode='3d',plotNow=True,**kwargs):