Documenting code fixes

[dillancellier]

• features/burst.py/compute_monotonicity : might be able to change monotonicity = np.ones(cycles) * np.nan so that the np.ones is not being initialized just to be replaced by nans
• features/burst.py/compute_monotonicity : can convert dataframe to dictionary temporarily to loop through rows. df.iterrows() seems to be slowest possible option (which is what the code currently does) see this page-- https://towardsdatascience.com/heres-the-most-efficient-way-to-iterate-through-your-pandas-dataframe-4dad88ac92ee

[mwprestonjr]

Other functions in features/burst.py have the the same initialization issue as compute_monotonicity() (line 288), including compute_amp_consistency() (line 163) and compute_period_consistency() (line 239),

[dillancellier]

• features/burst.py/compute_amp_consistency : might be able to change all instances of np.nanmin or nanmax to commands using Bottleneck https://pypi.org/project/Bottleneck/0.4.2/ but might be an issue of adding dependencies?