Add code for nmf_space_transitions and big_nmf_space_transitions to Study
Refactor big_nmf_space_transitions so can still get the original transitions with nmf_space_transitions
don't use this - debugging minimum cells/phenotype for NMF space'
Properly filter for at least 5 cells per phenotype, per event for NMF space position and transition calculation
Make sure nmf space calculation doesn't get called if nmf_space=False for plot_feature
return nmf space transitions, whitespace fixes
Remove events from big_nmf_transitions that didn't have phenotype groups together that were specified in the phenotype_transitions
Add call to splicing's nmf space positions
update plot_feature to plot all features on a single figure object, rather than separate ones
Make big_nmf_space_transitions cutoff be based off of all columns of the input data
Add option to specify how many samples per phenotype group need to be there for each event, for that event to count for a phenotype group
Add normally distributed numpy array and pandas dataframe to arsenal of testing objects
Move test_dataframePCA to test_basedata since it was really testing BaseData.reduce(), add "featurewise" test
Initial testing of modality detection
Fix TestDataFramePCA to only use DataFramePCA, add parameterization for number of components, add test for NMF
param --> params (typo)
Add RANDOM_STATE and nonnegative df fixtures
Add psi which gets binned to every possible combination of bins to testing
concatenate test and traini indices instead of adding
typo: concatentate --> concatenate