fix for #109 with unit test
fix for #113
fixed problem with older pickled detectors, and a real bug with
Refactored OpTrainRandomForestBlocked into multiple operators:
- OpFeatureMatrixCache: Extracts label points and features into a feature matrix, and CACHES them blockwise.
- OpConcatenateFeatureMatrices: Concatenate the output of OpFeatureMatrixCache for multiple images
- OpTrainFromFeatures: Simply train the RF using the feature matrix (and max label)
These changes were originally proposed in ilastik/ilastik#768.
TODO: Provide progress notifications.
OpTrainRandomForestBlocked, OpFeatureMatrixCache: Progress reporting.
Added code cleanup to-dos.
Merge branch 'feature-matrix-cache'
tests: Fixed testOpConcatenateFeatureMatrices
improved singleton z handling, removed possible deadlock
more abstraction to acommodate lazy CC
opFeatureMatrixCache: Fixed bug that caused the wrong feature points to be sampled.
Merge branch 'master' into OpLabelVolume-optimization
tests: Fixed testOpFeatureMatrixCache.py
tests: When opening a file to check an exported result, close the file before exit.
BlockwiseFileset: Not tested (and therefore not supported) on Windows and Darwin.
tests: skip RESTfulBlockwiseFileset tests on mac and windows.
submodules: Updated dvidclient
tests: More cleanup of data checking operators before exit.
OpTrainRandomForestBlocked: If there aren't enough labels to train with, return None.
OpSlicedBlockedArrayCache: Don't mark everything dirty if the blockshape is dirty.  That's an error anyway.