f921a41292d13178a6eca168b8bd261f190b76b4,ilastik-shell/applets/dataSelection/dataSelectionSerializer.py,DataSelectionSerializer,_serializeToHdf5,#DataSelectionSerializer#Any#Any#Any#,39

Before Change

            del infoDir[infoName]
                
        // Rebuild the list of infos
        for index, slot in enumerate(self.mainOperator.Dataset):
            infoGroup = infoDir.create_group("info{:04d}".format(index))
            datasetInfo = slot.value
            locationString = self.LocationStrings[datasetInfo.location]
            infoGroup.create_dataset("location", data=locationString)
            infoGroup.create_dataset("filePath", data=datasetInfo.filePath)
            infoGroup.create_dataset("datasetId", data=datasetInfo.datasetId)
            infoGroup.create_dataset("allowLabels", data=datasetInfo.allowLabels)
        
        // Write any missing local datasets to the local_data group
        localDataGroup = self.getOrCreateGroup(topGroup, "local_data")
        wroteInternalData = False
        for index, slot in enumerate(self.mainOperator.Dataset):
            info = slot.value

After Change

        self.mainOperator.Dataset.notifyInserted( bind(handleNewDataset) )
        
    def _serializeToHdf5(self, topGroup, hdf5File, projectFilePath):
        with Tracer(traceLogger):
            // If the operator has a some other project file, something"s wrong
            if self.mainOperator.ProjectFile.connected():
                assert self.mainOperator.ProjectFile.value == hdf5File
            
            // Access the info group
            infoDir = self.getOrCreateGroup(topGroup, "infos")
            
            // Delete all infos
            for infoName in infoDir.keys():
                del infoDir[infoName]
                    
            // Rebuild the list of infos
            for index, slot in enumerate(self.mainOperator.Dataset):
                infoGroup = infoDir.create_group("info{:04d}".format(index))
                datasetInfo = slot.value
                locationString = self.LocationStrings[datasetInfo.location]
                infoGroup.create_dataset("location", data=locationString)
                infoGroup.create_dataset("filePath", data=datasetInfo.filePath)
                infoGroup.create_dataset("datasetId", data=datasetInfo.datasetId)
                infoGroup.create_dataset("allowLabels", data=datasetInfo.allowLabels)
            
            // Write any missing local datasets to the local_data group
            localDataGroup = self.getOrCreateGroup(topGroup, "local_data")
            wroteInternalData = False
            for index, slot in enumerate(self.mainOperator.Dataset):
                info = slot.value
                // If this dataset should be stored in the project, but it isn"t there yet
                if  info.location == DatasetInfo.Location.ProjectInternal \
                and info.datasetId not in localDataGroup.keys():
                    // Obtain the data from the corresponding output and store it to the project.
                    // TODO: Optimize this for large datasets by streaming it chunk-by-chunk.
                    dataSlot = self.mainOperator.Image[index]
                    data = dataSlot[...].wait()
    
                    // Vigra thinks its okay to reorder the data if it has axistags,
                    //  but we don"t want that. To avoid reordering, we write the data
                    //  ourselves and attach the axistags afterwards.
                    dataset = localDataGroup.create_dataset(info.datasetId, data=data)
                    dataset.attrs["axistags"] = dataSlot.meta.axistags.toJSON()
                    wroteInternalData = True
    
            // Construct a list of all the local dataset ids we want to keep
            localDatasetIds = [ slot.value.datasetId
                                 for index, slot 
                                 in enumerate(self.mainOperator.Dataset)
                                 if slot.value.location == DatasetInfo.Location.ProjectInternal ]
    
            // Delete any datasets in the project that aren"t needed any more
            for datasetName in localDataGroup.keys():
                if datasetName not in localDatasetIds:
                    del localDataGroup[datasetName]
    
            if wroteInternalData:
                // Force the operator to setupOutputs() again so it gets data from the project, not external files
                // TODO: This will cause a slew of "dirty" operators for any inputs we saved.
                //       Is that a problem?
                infoCopy = copy.copy(self.mainOperator.Dataset[0].value)
                self.mainOperator.Dataset[0].setValue(infoCopy)
            
            self._dirty = False

    def _deserializeFromHdf5(self, topGroup, groupVersion, hdf5File, projectFilePath):
        with Tracer(traceLogger):
            // The "working directory" for the purpose of constructing absolute 
            //  paths from relative paths is the project file"s directory.

Instances