Section 10: Call Count

In section 6 we reviewed the life cycle of BigChunkLoaders and SmallChunkCollectors.

In regular intervals:

1. The scheduler selects a patient from the dataset.
2. A BigChunkLoader extracts a big chunk from the patient’s records. The BigChunkLoader has access to the patient by self.patient.
3. The extracted big chunk is passed to a SmallChunkCollector. The SmallChunkCollector has access to the patient by self.patient.

In previous section we introduced the functions set_checkpoint and get_checkpoint. Now we introduce the argument call_count which is passed to the SmallChunkCollector. Once the SmallChunkCollector starts, the passed call_count is zero. The argument call_count is the number of calls to the SmallChunkCollector’s extract_smallchunk function since the SmallChunkCollector has started working.

class SampleSmallchunkCollector(SmallChunkCollector):

    @abstractmethod 
    def extract_smallchunk(self, call_count, bigchunk, last_message_fromroot):
        '''
        Inputs:
            - call_count: The number of calls to `extract_smallchunk`
                 since the `SmallChunkCollector` has started working.
            - bigchunk: introduces before.
            - last_message_fromroot: to be covered.
        
        '''
        '''
        .
        .
        .
        same as before 
        .
        .
        .
        '''
        return smallchunk

Please note that unlike a “checkpoint”, the call_count argument is related to the SmallChunkCollector rather than the Patient.

Here is a sample notebook that combines call_count, set_checkpoint and get_checkpoint to explore each whole-slide-image in a circular path.

Here are the results (high-quality .eps images are provided in this folder):