The Run Method

Input:

chunk_specification

- a dictionary specifying how to determine the number of chunks to run the model in (see Section ).

dataset

- an object of class Dataset along whose elements the model will be chunked.

dataset_index

- an index of elements within dataset that are to be chunked.

result_array_type

- a type of the resulting array. It can be any numerical type of numpy array. The default value is float32.

...

- optional additional arguments that are passed to the method run_chunk(). They are expected to be keyword arguments.

Algorithm: 
For each chunk (determined by the chunk_specification) the model calls the method run_chunk() and passes as arguments the corresponding portion of dataset_index, the whole dataset and all additional arguments. By default the order of elements in dataset_index is preserved. This can be changed by redefining the method get_agents_order(). This method takes a dataset as argument which is an object of class DatasetSubset containing only those elements of the original dataset that are defined by dataset_index. It returns an index of elements in the given dataset determining the order in which the elements should be processed. For example, if this method returns a randomized index, the elements passed into run_chunk() will be processed in randomized order.

Output: 
The class returns result_array (passed to the method as input) filled by values returned by run_chunk() are filled into. This requires that the method run_chunk() returns an array of the same type as result_array and its size corresponds to the number of elements in one chunk.