To run the cloud-tracking algorithm, use

python run_tracker.py [Input_dir]

where [Input_dir] is the address of the input directory. The model parameters will automatically be retrieved from the given files.

The cloud-tracking requires Python 3.5.

• Make run_tracker.py run with command arg
• Get rid of config.cfg
• Read model parameters from xray dataset
• Write model parameters to HDF5 dataset

• Implement/benchmark asyncio operations on ~ 30,000 cloudlet computations
• Numba/Cython for the expansion algorithm (cloudtracker.utility_functions)
• Wrap up with dask -> HDF5 output

• Filter noisy cloudlets out for speedup
• Threaded HDF5 file read for speed

• Wrap file I/O with dask

To profile the cloud-tracking algorithm using line_profiler, do

python -O -B -m kernprof -l -v run_tracker.py > line_stats.txt

or, to run with a memory profiler instead,

python -O -B -m memory_profiler run_tracker.py > memory_stats.txt