fixed 16-bit TIFFs, added error handling kludge

filelist/filesettings.py

@@ -1,4 +1,4 @@
-IMG_LOCS = {"pixis":"C:\\Dropbox\\imgpixis\\","pflyold":"C:\\Dropbox\\imgpflyold"}
+IMG_LOCS = {"pixis":"C:\\Dropbox\\imgpixis\\","pflyold":"C:\\Dropbox\\imgpflyold", "pfly":"C:\\Dropbox\\imgpfly", "andor":"C:\\Dropbox\\imgandor"}
 RL_LOCS = {"crunlogs":"C:\\runlogs\\"}
 STATIC_DIR = "./static/"
 #THUMB_DIR = "C:\\thumb\\"

filelist/models.py

@@ -55,27 +55,31 @@ def makeRawFrames(self):
 	def deleteProcFrames(self):
 		ProcessedFrame.objects.filter(sourceimage=self).delete()
 	def ProcessImage(self): 
-		for method in self.imgtype.methods.all():
-			procmodule = __import__(method.modulename)
-			reload(procmodule)
-			procmethod = getattr(procmodule, method.name)
-			argdict = {}
-			for param in TypeParameters.objects.filter(imagetype=self.imgtype, methodargument__method=method):
-				argdict[param.methodargument.name]=param.value
-			for ROIparam in TypeROI.objects.filter(imagetype=self.imgtype, methodargument__method=method):
-				argdict[ROIParam.methodargument.name]=ROIparam.ToDict()
-			result=procmethod(self.path, **argdict)
-			if not isinstance(result,tuple):
-				result = (result,)
-			for ii in range(len(result)):
-				if isarray(result[ii]):
-					filename=os.path.splitext(os.path.split(self.path)[1])[0]+'_'+method.name+'_'+str(ii)+'.png'						
-					newrecord = ProcessedFrame(sourceimage=self, method=method, framenumber=ii) 
-					newrecord.saveframe(result[ii], filename, cmin=0, cmax=1)
-					newrecord.save()
-				else:
-					newrecord = ProcessedValue(sourceimage=self, method=method, value=float(item[ii]), index=ii)
-					newrecord.save()
+		if self.imgtype:
+			for method in self.imgtype.methods.all():
+				procmodule = __import__(method.modulename)
+				reload(procmodule)
+				procmethod = getattr(procmodule, method.name)
+				argdict = {}
+				for param in TypeParameters.objects.filter(imagetype=self.imgtype, methodargument__method=method):
+					argdict[param.methodargument.name]=param.value
+				for ROIparam in TypeROI.objects.filter(imagetype=self.imgtype, methodargument__method=method):
+					argdict[ROIParam.methodargument.name]=ROIparam.ToDict()
+				try:
+					result=procmethod(self.path, **argdict)
+					if not isinstance(result,tuple):
+						result = (result,)
+					for ii in range(len(result)):
+						if isarray(result[ii]):
+							filename=os.path.splitext(os.path.split(self.path)[1])[0]+'_'+method.name+'_'+str(ii)+'.png'						
+							newrecord = ProcessedFrame(sourceimage=self, method=method, framenumber=ii) 
+							newrecord.saveframe(result[ii], filename, cmin=0, cmax=1)
+							newrecord.save()
+						else:
+							newrecord = ProcessedValue(sourceimage=self, method=method, value=float(item[ii]), index=ii)
+							newrecord.save()
+				except: 
+					pass
 	def getClosestSequence(self):
 		sql = "SELECT * FROM filelist_runloginfo ORDER BY ABS(TIMESTAMPDIFF(SECOND, time,'" + self.time.strftime('%Y-%m-%d %H:%M:%S') + "')-sequenceduration) LIMIT 1"
 		for retrunlog in RunLogInfo.objects.raw(sql):

filelist/odysseus/imageio.py

@@ -10,6 +10,7 @@
 """
 
 import os
+
 import numpy as np
 import scipy as sp
 # if available, use Zach Pincus' pil_lite which has correct 16-bit TIFF loading
@@ -18,6 +19,7 @@
 except ImportError:
     import Image
 #import tables
+import tifffile
 
 
 def list_of_frames(img_name):
@@ -26,21 +28,17 @@ def list_of_frames(img_name):
     Details are as described in the imgimport_intelligent docstring.
 
     """
-
-    img = Image.open(img_name)
+    img = tifffile.TiffFile(img_name)
+    #img = Image.open(img_name)
     imglist = []
 
     try:
-        for i in xrange(8):
-            if img.mode == 'I':
-                imdata = np.asarray(img, dtype=np.int16)
-            else:
-                imdata = np.asarray(img, dtype=np.float32)
-            # fix 3-channel TIFF images
+        for i in range(np.size(img)):
+            imdata = img[i].asarray()
+	    imdata = imdata.astype(np.float32)
             if np.rank(imdata)==3:
                 imdata = imdata[:,:,0] + 256*imdata[:,:,1] + 65536*imdata[:,:,2]
             imglist.append(imdata)
-            img.seek(i+1) # next frame
     except EOFError:
         pass
 
@@ -49,23 +47,6 @@ def list_of_frames(img_name):
     else:
         return imglist
 
-def trans_nonorm(img_name):
-    raw_frames=imgimport_intelligent(img_name)
-
-    pwa = raw_frames[:, :, 0]
-    pwoa = raw_frames[:, :, 1]
-    df = raw_frames[:, :, 2]
-
-    nom = pwa - df
-    den = pwoa - df
-
-    nom = np.where(nom<1, 1, nom)
-    den = np.where(den<1, 1, den)
-
-    transimg = nom.astype(float)/den
-
-    return transimg/1.35
-
 
 def imgimport_intelligent(img_name, foo=3, bar=4, roi_baz=[12,24,56,78]):
     """Opens an image file containing one or more frames
@@ -131,9 +112,7 @@ def imgimport_intelligent(img_name, foo=3, bar=4, roi_baz=[12,24,56,78]):
 
     transimg = nom.astype(float)/den
 
-    return 5
-
-
+    return img_array
 
 def import_rawframes(img_name):
     """Opens an image file containing three frames
@@ -328,12 +307,29 @@ def load_hdfimage(fname, dirname=None, ext_replace=True):
         pwa = np.asarray(h5file.root.rawframes.pwa)
         pwoa = np.asarray(h5file.root.rawframes.pwoa)
         df = np.asarray(h5file.root.rawframes.df)
-        imgarray = np.dstack([pwa, pwao, df])
+        imgarray = np.dstack([pwa, pwoa, df])
         return imgarray
 
     finally:
         h5file.close()
 
+def trans_nonorm(img_name):
+    raw_frames=imgimport_intelligent(img_name)
+
+    pwa = raw_frames[:, :, 0]
+    pwoa = raw_frames[:, :, 1]
+    df = raw_frames[:, :, 2]
+
+    nom = pwa - df
+    den = pwoa - df
+
+    nom = np.where(nom<1, 1, nom)
+    den = np.where(den<1, 1, den)
+
+    transimg = nom.astype(float)/den
+
+    return transimg/1.35
+
 
 def convert_xcamera_to_hdf5(imglist, ext='xraw'):
     """Convert every file in imglist to an hdf5 file.