explore the possibility of speeding up IO:
many_results = pool.map(...)
#for each element, maptype:
res = [i for i in many_results if i is calcium]
Ended up taking a different approach, using a results proxy to store and update numpy arrays in memory. Those arrays are not written to file until data processing has completed.