Slight reworking of rescaling. Makes fitting more robust.

fsl_mrs/core.py

@@ -246,6 +246,23 @@ class MRS(object):
 
         
     # Helper functions
+    def processForFitting(self,ppmlim=(.2,4.2),):
+        """ Apply rescaling and run the conjugation checks"""
+        self.check_FID(ppmlim=ppmlim,repair=True)
+        self.check_Basis(ppmlim=ppmlim,repair=True)
+        self.rescaleForFitting()
+
+    def rescaleForFitting(self,scale=100):
+        """ Apply rescaling across data, basis and H20"""
+        
+        scaledFID,scaling = misc.rescale_FID(self.FID,scale=scale)
+        self.set_FID(scaledFID)
+        if self.H2O is not None:
+            self.H2O *= scaling
+
+        if self.basis is not None:
+            self.basis,_ = misc.rescale_FID(self.basis,scale=scale)
+
     def check_FID(self,ppmlim=(.2,4.2),repair=False):
         """
            Check if FID needs to be conjugated

fsl_mrs/scripts/fsl_mrs

@@ -160,16 +160,8 @@ def main():
     FID,dataheader            = mrs_io.read_FID(args.data)
     basis, names, basisheader = mrs_io.read_basis(args.basis)
         
-    
-    # Rescale FID and basis to have nice range
-    if not args.no_rescale:
-        FID   = misc.rescale_FID(FID,scale=100)
-        basis = misc.rescale_FID(basis,scale=100)
-    
     if args.h2o is not None:
         H2O,_                 = mrs_io.read_FID(args.h2o)
-        if not args.no_rescale:
-            H2O   = misc.rescale_FID(H2O,scale=100)
     else:
         H2O = None
       
@@ -221,6 +213,10 @@ def main():
             if conjugated == 1:
                 warnings.warn('Basis has been checked and conjugated. Please check!',UserWarning)
     
+    # Rescale FID, H2O and basis to have nice range
+    if not args.no_rescale:
+        mrs.rescaleForFitting()
+
     # Do phase correction
     if args.phase_correct:
         if args.verbose:

fsl_mrs/utils/fitting.py

@@ -398,6 +398,7 @@ def fit_FSLModel(mrs,
                                 verbose=False,
                                 monitor=True,
                                 args=args)
+        results.optim_out = res_vb
 
         # de-log
         if model.lower()=='lorentzian':

fsl_mrs/utils/misc.py

@@ -434,7 +434,7 @@ def rescale_FID(x,scale=100):
     else:
         factor = np.linalg.norm(np.mean(y,axis=1),axis=0)        
     y =  y / factor * scale
-    return y
+    return y,1/factor * scale
 
 
 def create_peak(mrs,ppm,gamma=0,sigma=0):