* Generic interactive visualizer for 3 and 4D float numpy arrays.
* No need to handle h5py datasets, compound datasets, complex datasets etc.
* Add features time permitting.
* Consider implementing doSVD as a Process. Maybe the Decomposition and Cluster classes could extend Process?
* Simplify and demystify analyis / optimize. Use parallel_compute instead of optimize and gues_methods and fit_methods
* multi-node computing capability in parallel_compute
* Data Generators
* Consistency in the naming of and placement of attributes (chan or meas group) in all translators
GUI
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* Need to be able to run a visualizer even on sliced data. What would this object be? (sliced Main data + vectors for each axis + axis labels ....). Perhaps the slice() function should return this object instead of a numpy array? As it stands, the additional information (for the visualizer) is not returned by the slice function.
* Generic visualizer in plot.lly / dash? that can use the PycroDataset class
