Add run time and memory usage

For each analysis module, add to get estimated run time and use of memory

Want to include info on how this might scale depending on the amount of data inputted

Maybe use crude approach?
```
import time

# Get the time at the start of the run
start_time = time.time()

# Analysis code to run

# Get the time at the end of the run
end_time = time.time()

# Calculate the total time of the run
total_time = end_time - start_time
print(total_time)
```

No files, tests, or module entry points are named. Start by locating each analysis module and checking how modules currently report results, then assess the proposed timing approach and how memory usage could be measured. Done should provide runtime and memory information for every module, with an explanation of how those measurements vary with input size.

Written by the indexing model from the issue text.