- Windows support
- Serialization work
- Moved SWIG out into nupic.core
- Major build changes
- Raise explicit exception if user passes non-str path
- SP: simplify local inhibition
- SP: adapt tests, sort winning columns output
- SP: simplify active columns assignment
- SP: simplify global inhibition
- file Rename as hello_tm.py and modifications in comments
- Added src/nupic/frameworks/opf/common_models/cluster_params.py and supporting files from numenta-apps htmengine. A separate numenta-apps PR will remove this code from htmengine.
- fixes #2592
- fix for #2265
- fix for bug #2265
- Fixup Dockerfile to install nupic.bindings, and other cleanup
- Adding C++ compiler requirement to README.
- Fix for test failure
- Fixed stream definition reference error.
- Reduce default reestimation period.
- Remove greedy reestimation of distribution
- Pointing README to proper bindings version.
- Continuing work on 0.3.4.dev0.
- removing a test that depends on nupic.vision
- PCA_Node test: some fixes, WIP
- formatting
- test for PCANode region
- remove Pillow from requirements.txt as it was used for vision only
- fix merge mistake in csv file
- move test from PCANode to nupic.vision unittest
- Include additional file types in MANIFEST.in, consistent with setup.py
- Pattern and Sequence machines using nupic::Random
- Wrap sparse matrix implementations with cortical column-centric semantics as a way to abstract away the underlying implementation
- Re-enable testHotgymRegression
- Update to nupic.bindings version with fix for platform differences
- Rename nupic directory to src/nupic
- Updated S3 URL to nupic.bindings for Linux install
- Fix paths for data files in an integration test
- Fix issue with storing temporary file in wrong location in integration test
- Specify nupic.bindings version to match commit sha (0.2).
- Use logging.debug for emitting the message about not being able to import matplotlib; we log it at debug level to avoid polluting the logs of apps and services that don't care about plotting.
- Add Dockerfile ready to perform swarming.
- Removes PCANode
- Updated Linux binary install instructions.
- Updated comment about greedy stats refresh when likelihood > 0.99
- Implemented unit tests for the new features in AnomalyLikelihood class.
- Convert AnomalyLikelihood._historicalScores to a user-configurable sliding window, instead of accumulating all of the incoming data points. This improved performance a ton! Added AnomalyLikelihood.forceModelRefresh() method.
- Update nupic.core to include backwards compatibility fix for RandomImpl.
- Uninstall pycapnp to avoid running tests that utilize the functionality and currently fail with Duplicate ID error.
- Makes pycapnp and corresponding serialization optional. If pycapnp is not installed then the corresponding serialization tests will be skipped.
- Add Multiple Prediction Test for NegLL Metric
- Add test for NegLL Error Metric
- Fix Orphan Decay Bug in temporal memory test
- Change decreasing overlaps test for coordinate encoder to not require a strict decrease (staying the same is ok).
- Allow specifying MonitoredTemporalMemory as TM implementation through OPF
- include bucket likelihood and classifier input in clamodel
- update metrics managers to pass model results to metrics
- introducting a computeFlag to prevent double-computation. * The flag is used to prevent double computation in the event that customCompute() is called at the same time as compute()
- Added
numRecords
param for consitency with the newly addedinfer
method in FastCLACLassifier - checking if classifier has a
maxCategoryCount
attribute. If not, set it to solve backward compatibilities issues - renaming numCategories to maxCategoryCount to be constistent between KNN and CLA classifier
- made new experimentutils file containing InferenceElement, InferenceType, and ModelResult duplicates which we will want to change in the future
- Updating nupic.core sha.
- Updated location of NuPIC Linux wheel on S3.
- Updating bindings version.
- Added pip install command for linux bindings.
- Change term predictedColumns to predictedActiveColumns in the TemporalMemory
- Updated to correct pypi license string.
- Changed all copyright headers on all files to AGPL.
- split up pip wheel to multiple commands
- Fixed fast_temporal_memory cellsForColumn calculation. Column is an int (specifically a numpy.int64 and getCellIndex would fail in this), not a cell
- Broke out model record encoding functionality from RecordStreamIface into ModelRecordEncoder class.
- Convert nupic to namespace
- updated include statements in swig files
- added dict utils to hypersearch specific utils file and modified dependencies accordingly
- Updated to AGPL.
- Remove tweepy.
- KNNClassifier input multiple categories, and integration test
- enable multiple categories in Network API
- Makes nupic a namespace package that other projects can extend.
- Added NRMSE metric
- Allow Connections to be serialized.
- Added ability to unregister python regions and updated core sha
- Remove unused synapses in Temporal Memory
- Fix: TemporalMemory.getCellIndex doesn't work correctly when running through OPF
- Sets zip-safe to false to make sure relative capnp schema imports will work and importing .capnp files will work.
- Clean up capnp imports.
- Changes to TM test to accommodate changes in the default value of predictedSegmentDecrement
- Merge remote-tracking branch 'upstream/master'
- Change default value of predictedSegmentDecrement to be 0 to be backward compatible
- Change default value of predictedSegmentDecrement to be 0 to be backward compatible
- Change default value of predictedSegmentDecrement to be 0 to be backward compatible
- Merge remote-tracking branch 'upstream/master'
- Rename testconsoleprinter_output.txt so as to not be picked up by py.test as a test during discovery
- likelihood test: fix raw-value must be int
- Fix broken TPShim
- Revert "Fix TP Shim"
- Anomaly serialization verify complex anomaly instance
- Likelihood pickle serialization test
- MovingAverage pickle serialization test
- Fix TP Shim
- Removed stripUnlearnedColumns-from-SPRegion
- Updated comment describing activeArray paramater of stripUnlearnedColumns method in SP
- Revert "MovingAvera: remove unused pickle serialization method"
- Updated NUPIC_CORE_COMMITISH to use the core without stripNeverLearned
- Removed stripNeverLearned from SP.compute
- MovingAverage has getter for current value
- Fixes bug in mmGetCellActivityPlot
- Merge remote-tracking branch 'upstream/master'
- Fixes bug in mmGetCellActivityPlot
- Fixes bug in mmGetCellActivityPlot
- addressing scott's cr
- addressing cr; docstring formatting and minor
- Continuing work on 0.2.6.dev0.
- minor
- first version of knn tests
- Update SHA and fix files
- Rename cpp_region to py_region
- pylint
- fix likelihood equals problem when default timestamp
- Likelihood: @param docstring
- AnomalyLikelihood: add str
- ANomalyLikelihood equals test case
- Anomaly: add eq test
- add MovingAverage eq test
- anomaly likelihood, MA, Anomaly: review - better eq statement
- Anomaly: code review - use instance access
- improving constructor docs
- AnomalyLikelihood: add eq
- Anomaly: compare likelihood in eq
- improve anomaly serialization test - use eq
- MovingAvera: remove unused pickle serialization method
- Anomaly & MovingAverage : change cmp to eq
- define equals operator (cmp) for anomaly & MovingAverage
- anomaly serialize test - comment out parts
- Anomaly: add serialization test
- Fix MANIFEST.in capnp include.
- Update documentation related to PyRegion serialization introduction.
- Updates nupic.core and adds function definitions for read/write in PyRegion
- Fix a minor bug in the algorithm
- Implement orphan synapse decay
- register python regions in Region class method
- moved registration of python regions to nupic.core
- date encoder bug fix
- Implement orphan synapse decay
- changed default regions to tuples
- fill predictedActiveCells with 0
- removing irrelevant files
- removing old network api demo 2
- modified PyRegion to accept custom classes
- renamed unionMode to computePredictedActiveCellIndices
- set the output size for active indices and predicted+active indices to max possible size
- converting union pooler input to right format
- Port AnomalyRegion serialization
- Rename "enc" to "encoder"
- updated custom region methods and example to be static
- demo for custom regions
- Improve docstring for 'save' method and others.
- allows custom regions
- moved encoder changes to network_api_demo
- updated network_api_demo in new file to make swapping out encoders easier
- bit more explanation for MultiEncoder
- Use different logic for determining whether or not to translate back into actual values from bucket indices
- Switch over to C++ SpatialPooler where possible to speed up tests/build.
- Finish implementation of TemporalMemory serialization
- Fixed equality test for Connections class
- Removing learning radius parameter from nupic
- Add Cap'n Proto serialization to Python Connections
- Remove FDRCSpatial2.py
- Replace the use of FDRCSpatial2 to SpatialPooler
- SP profile implemented from tp_large
- TP profile: can use args from command-line, random data used
- Adds AnomalyRegion for computing the raw anomaly score. Updates the network api example to use the new anomaly region. Updates PyRegion to have better error messages.
- Remove FlatSpatialPooler
- Add delete segment/synapse functionality to Connections data structure
- Adding dependency listing with licenses.
- Bump pycapnp to latest (0.5.5) for security update
- Remove redundant encoderMap operations
- Remove redundant index, and EncoderDetails in favor of using the outer union directly
- Use union in capnp schema per feedback
- MultiEncoder capnp implementation, including a switch to relative imports as a workaround for an issue described in capnproto/pycapnp#59
- SparsePassThroughEncoder capnp implementation
- PassThroughEncoder capnp implementation
- LogEncoder capnproto implementation
- GeospatialCoordinateEncoder capnp implementation
- DeltaEncoder capnp implementation
- CoordinateEncoder capnp implementation
- AdaptiveScalarEncoder capnp implementation
- SDRCategoryEncoder capnproto implementation
- CategoryEncoder capnproto serialization, fixes #1964
- Change anomaly score to always be zero when there are no active columns.
- Date encoder capnproto implementation
- RDSE capnproto implementation w/ bugfix in encoder base
- Remove redundant radius and resolution in favor of relying on them to be recalculated based on n.
- Remove explicit int casts and update tests to allow ints or longs.
- Integrate capnproto serialization into ScalarEncoder re: #1715
- Allowing relative paths for input files in swarm desc.
- accepts anomaly records as both lists and tuples
- Moved data pkg_resource data into nupic/datafiles.
- Replaces datasethelpers with pkg_resources.
- refactor submetrics computation handling None
- Adding numpy to README requirements.
- Move pattern/sequence machine tests to proper location.
- Moves pattern_machine and sequence_machine files into generators module.
- Get cell indices methods added an amazing super cool docstring formatting
- Updates data generator tool filename and adds executable bit.
- Moves anomalyzer to nupic.data.generators module
- Move data generators to nupic.data.generators module
- fixme burn-in for multi metric addInstance()
- fix AggregateMetric with None metricSpec
- add MetricMulti class
- AggregateMetric sets id from params (if specified)
- Removes isDelta method from encoder base class.
- fixed predicted active cells in tm-mm
- rename --enable-optimizations to --optimizations-native
- add --optimizations-lto option to setup.py to enable Link Time Optimizations
- Simplify docker setup to single Dockerfile at root
- Adding cell activity plt and improving metrics table
- add python setup.py --enable-optimization
- enable -Wextra warnings
- sane optimization defaults for binary published builds
- Revert "default make with -j4"
- add Ofast linker flag for gcc
- fix: remove inline - let LTO decide
- Code changes required for a Windows build.
- Updates nupic.core to d233c58b64e8064d4d12684634dc5e5e78c7ce0b.
- Implements capnp serialization for Python spatial pooler. Also implements temporary hack for putting .capnp files into the source tree since the build seems to be set up to install in-tree.
- Remove unnecessary build flag and fix a bug that was causing duplicated definition names.
- Added warning in README for OS X.
- Doc updates
- Include additional libs in common libs
- Use gcc in default docker configuration to match nupic.core binary release. Increase resources in coreos configuration.
- Fixed ValueError When coordinate encoder is used with DateEncoder
- Add library path for capnp libraries to linker.
- Adds capnp libraries to linker args.
- Adds interface file for converting from pycapnp schema to compiled in schema and uses it with SWIGed C++ SpatialPooler class's read and write methods.
- Discard NTA_PLATFORM_* in favor of NTA_OS_* and NTA_ARCH_* macro variables
- Raises exception when enableInference was not called, or when predicted field missing from input row.
- Add archflags env var before deploy command on OSX
- Removal of CMakeLists.txt
- Removes fake C extension from setup.
- Adds warning on darwin platform when ARCHFLAGS not set.
- Cleanup re: #1579. Fixup namespace conflicts with builtins (file, dir, etc.) as well as minor alignment issues
- Switch from cmake to distutils extensions for nupic installation
- Cleaned up README and CHANGELOG for 0.1 release.
- SWIG optimizations.
- Script to deploy linux wheel to S3 on release.
- Publishing select artifacts to pypi on release.
- Changed dev version pattern to match what python wants.
- Cleaned up setup and manifest for proper sdists.
- Faking extensions to get platform-specific wheels.
- Added core capnp files to bindings.
- GCE now encodes altitude using a 3D coordinate system.
- Distributing
*.i
files fromnupic.bindings
in binary packages. - Updates test entry points to pure python. README instructions for running tests were updated.
- Missing configuration files are no longer ignored. A runtime exception is raised immediately when an expected configuration file is not found.
- Updated deployment logic to account for both deployment scenarios (iterative and release).
- Configured pypi deployment on all branches with tags.
- Added pypi deployment configuration for binary releases.
- Parsing python requirements in setuptools so they are included within published packages (working toward releases).
- Setting up python wheels packaging and upload to S3 for future distribution.
- Implemented logic for reusing segments, to enforce a fixed-size connectivity (nupic.core).