fixes #29 : Modified setup.py to run using 'spatial_ornstein_uhlenbeck.py' and 'fit_timeseries.py'
fixes #2 ?
fixes #31 : Addition of parser functions in fit_timeseries which generates optimized functions based on PCoA input. Does not accept single-point observations.
fixes #10 : Moved benchmarking test into fit_timeseries, and configured the script to benchmark if no input is provided.
Modified test_fit_timeseries.py to attempt flaky test three times to prevent TravisCI failures from RNG. Added log support for benchmarking.
Update 7/1/2018
Updated fit_timeseries and moved benchmarking to its own script.
Addition of testing for new benchmarking file
Addition of installation support for benchmarking script under "fit_timeseries_benchmark.py"
Addition of aic function
Addition of visualization support for benchmarking. Outputs three PNG files displaying the timepoints vs magnitude of error for each sigma, lambda, theta, for each local optimizer tested.
SLPeoples
commented
6 years ago 
fixes #29 : Modified setup.py to run using 'spatial_ornstein_uhlenbeck.py' and 'fit_timeseries.py'
fixes #2 ? fixes #31 : Addition of parser functions in fit_timeseries which generates optimized functions based on PCoA input. Does not accept single-point observations.
fixes #10 : Moved benchmarking test into fit_timeseries, and configured the script to benchmark if no input is provided.
Modified test_fit_timeseries.py to attempt flaky test three times to prevent TravisCI failures from RNG. Added log support for benchmarking.
Updated fit_timeseries and moved benchmarking to its own script.
Addition of testing for new benchmarking file
Addition of installation support for benchmarking script under "fit_timeseries_benchmark.py"
Addition of aic function
Addition of visualization support for benchmarking. Outputs three PNG files displaying the timepoints vs magnitude of error for each sigma, lambda, theta, for each local optimizer tested.