fixed a bug where the noise added to the movie pixels was identical rather than uncorrelated! also some refactoring
much cruder initialization of C0, but guarantees that n >=0. pre-subtracting the baseline from F speeds up computing D
improved initialization of n0 with a hack that is unlikely to be robust - n0 needs to be scaled according to noise levels
minor tweaks to termination conditions
smiley mask!
added some code for making fancy plots
trivial
implemented backtracking line search on parameters, yet somehow made it worse (at least for 1D case). when F is 1D, tnds to wildly overestimate sigma.
better initialization of beta, marginal speedup of gradient computation, increased default spike & param tolerances
cleaned up old direction calculation code
option to set random seed when generating fake data
decrement step size and barrier term slower, increase C_hat as a hack to avoid local minima. overall improvements to robustness and quality, still breaks on some edge cases (v. high/low noise, fails to learn sigma nicely)
changes to help string for deconvolve(), updated apply_all_cells() to work on movies
removed make_fake_data() - use make_fake_movie(..., mask_shape=(1, 1)) to get 1D data. simplified code for generating demo plots.
make sure alpha and beta are >= 1D arrays
moved some misc functions into utils
updated documentation
merge with head