scikit-step
1-D step detection algorithms.
Example
Basic usage
from skstep import GaussStepFinder
sf = GaussStepFinder() # initialize
result = sf.fit(data) # fitting
result.plot() # plot result
result.step_positions # step positions
result.means # mean values at each constant region
result.step_sizes # change between adjacent constant regions
result.lengths # length of each constant region
Chunkwise fitting
Computation time of step finding algorithms are usually around O(N^1.5). This means that fragmenting large data makes computation faster while does not affect the result a lot.
All the step finding algorithms are implemented with chunkwise fitting with parallel processing using dask.
sf.fit_chunkwise(data)
1 maintainer
Metadata
1 maintainer
Release files for scikit-step 0.1.0
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