Applying snake_case module name standards (PART 3)

docs/README.md

@@ -80,7 +80,7 @@ nupic
 │   ├── sdr_classifier_factory.py [OK]
 │   ├── backtracking_tm.py [TODO]
 │   ├── backtracking_tm_cpp.py [TODO]
-│   ├── BacktrackingTM_shim.py [TODO]
+│   ├── backtracking_tm_shim.py [TODO]
 │   ├── connections.py [TODO]
 │   ├── fdrutilities.py [TODO]
 │   ├── monitor_mixin

examples/prediction/experiments/generated_data/description.py

@@ -2,7 +2,7 @@
 
 from nupic.data import FunctionSource
 from nupic.frameworks.prediction.callbacks import displaySPCoincidences, printSPCoincidences
-from nupic.data.dictutils import DictObj
+from nupic.data.dict_utils import DictObj
 
 
 nCoincidences = 30

src/nupic/algorithms/CLAClassifier.py → src/nupic/algorithms/cla_classifier.py

@@ -33,7 +33,7 @@
 # This must be less than float32 size since storage is float32 size
 DUTY_CYCLE_UPDATE_INTERVAL = numpy.finfo(numpy.float32).max / (2 ** 20)
 
-g_debugPrefix = "CLAClassifier"
+g_debugPrefix = "cla_classifier"
 
 
 def _pFormatArray(array_, fmt="%.2f"):
@@ -249,8 +249,8 @@ class CLAClassifier(object):
   "activationPattern") and information from the sensor and encoders (the
   "classification") describing the input to the system at that time step.
 
-  When learning, for every bit in activation pattern, it records a history of 
-  the classification each time that bit was active. The history is weighted so 
+  When learning, for every bit in activation pattern, it records a history of
+  the classification each time that bit was active. The history is weighted so
   that more recent activity has a bigger impact than older activity. The alpha
   parameter controls this weighting.
 
@@ -382,7 +382,7 @@ def compute(self, recordNum, patternNZ, classification, learn, infer):
     self._patternNZHistory.append((self._learnIteration, patternNZ))
 
     # To allow multi-class classification, we need to be able to run learning
-    # without inference being on. So initialize retval outside 
+    # without inference being on. So initialize retval outside
     # of the inference block.
     retval = None
 
@@ -392,7 +392,7 @@ def compute(self, recordNum, patternNZ, classification, learn, infer):
     # votes
     if infer:
       retval = self.infer(patternNZ, classification)
-      
+
     # ------------------------------------------------------------------------
     # Learning:
     # For each active bit in the activationPattern, store the classification
@@ -468,13 +468,13 @@ def compute(self, recordNum, patternNZ, classification, learn, infer):
       print
 
     return retval
-  
-  
+
+
   def infer(self, patternNZ, classification):
     """
-    Return the inference value from one input sample. The actual 
-    learning happens in compute(). The method customCompute() is here to 
-    maintain backward compatibility. 
+    Return the inference value from one input sample. The actual
+    learning happens in compute(). The method customCompute() is here to
+    maintain backward compatibility.
 
     Parameters:
     --------------------------------------------------------------------
@@ -493,7 +493,7 @@ def infer(self, patternNZ, classification):
                     1 : [0.1, 0.3, 0.2, 0.7]
                     4 : [0.2, 0.4, 0.3, 0.5]}
     """
-    
+
     # Return value dict. For buckets which we don't have an actual value
     # for yet, just plug in any valid actual value. It doesn't matter what
     # we use because that bucket won't have non-zero likelihood anyways.
@@ -540,9 +540,9 @@ def infer(self, patternNZ, classification):
           sumVotes /= sumVotes.size
 
       retval[nSteps] = sumVotes
-    
+
     return retval
-    
+
 
   def __getstate__(self):
     return self.__dict__

src/nupic/algorithms/cla_classifier_diff.py

@@ -29,7 +29,7 @@
 import cPickle as pickle
 import numbers
 
-from nupic.algorithms.CLAClassifier import CLAClassifier
+from nupic.algorithms.cla_classifier import CLAClassifier
 from nupic.bindings.algorithms import FastCLAClassifier
 
 

src/nupic/algorithms/cla_classifier_factory.py

@@ -21,7 +21,7 @@
 
 """Module providing a factory for instantiating a CLA classifier."""
 
-from nupic.algorithms.CLAClassifier import CLAClassifier
+from nupic.algorithms.cla_classifier import CLAClassifier
 from nupic.algorithms.cla_classifier_diff import CLAClassifierDiff
 from nupic.bindings.algorithms import FastCLAClassifier
 from nupic.support.configuration import Configuration

src/nupic/data/__init__.py

@@ -29,4 +29,4 @@
 
 SENTINEL_VALUE_FOR_MISSING_DATA = None
 
-from functionsource import FunctionSource
+from function_source import FunctionSource

src/nupic/data/jsonhelpers.py → src/nupic/data/json_helpers.py

@@ -121,7 +121,7 @@ def test():
   import sys
 
   schemaDict = {
-    "description":"JSON schema for jsonhelpers.py test code",
+    "description":"JSON schema for json_helpers.py test code",
     "type":"object",
     "additionalProperties":False,
     "properties":{

src/nupic/data/stream_reader.py

@@ -28,7 +28,7 @@
 from nupic.data.aggregator import Aggregator
 from nupic.data.field_meta import FieldMetaInfo, FieldMetaType, FieldMetaSpecial
 from nupic.data.file_record_stream import FileRecordStream
-from nupic.data import jsonhelpers
+from nupic.data import json_helpers
 from nupic.data.record_stream import RecordStreamIface
 from nupic.frameworks.opf import jsonschema
 import nupic.support
@@ -137,8 +137,8 @@ def __init__(self, streamDef, bookmark=None, saveOutput=False,
 
     loggerPrefix = 'com.numenta.nupic.data.StreamReader'
     self._logger = logging.getLogger(loggerPrefix)
-    jsonhelpers.validate(streamDef,
-                         schemaPath=pkg_resources.resource_filename(
+    json_helpers.validate(streamDef,
+                          schemaPath=pkg_resources.resource_filename(
                              jsonschema.__name__, "stream_def.json"))
     assert len(streamDef['streams']) == 1, "Only 1 source stream is supported"
 

src/nupic/database/ClientJobsDAO.py → src/nupic/database/client_jobs_dao.py

@@ -31,7 +31,7 @@
 import uuid
 
 from nupic.support.decorators import logExceptions #, logEntryExit
-from nupic.database.Connection import ConnectionFactory
+from nupic.database.connection import ConnectionFactory
 from nupic.support.configuration import Configuration
 from nupic.support import pymysqlhelpers
 

src/nupic/frameworks/opf/exp_description_helpers.py

@@ -22,7 +22,7 @@
 import os
 import imp
 
-from nupic.data.dictutils import rUpdate
+from nupic.data.dict_utils import rUpdate
 
 
 # This file contains utility functions that are used

src/nupic/frameworks/opf/experiment_runner.py

@@ -35,7 +35,7 @@
 import random
 import numpy
 
-from nupic.data import jsonhelpers
+from nupic.data import json_helpers
 from nupic.frameworks.opf import opf_basic_environment, opf_helpers
 from nupic.frameworks.opf.exp_description_api import OpfEnvironment
 from nupic.frameworks.opf.model_factory import ModelFactory
@@ -373,8 +373,8 @@ def _runExperimentImpl(options, model=None):
       is provided to aid with debugging) or None, if none was
       created.
   """
-  jsonhelpers.validate(options.privateOptions,
-                       schemaDict=g_parsedPrivateCommandLineOptionsSchema)
+  json_helpers.validate(options.privateOptions,
+                        schemaDict=g_parsedPrivateCommandLineOptionsSchema)
 
   # Load the experiment's description.py module
   experimentDir = options.experimentDir

src/nupic/frameworks/opf/opf_utils.py

@@ -30,7 +30,7 @@
 import re
 from collections import namedtuple
 
-import nupic.data.jsonhelpers as jsonhelpers
+import nupic.data.json_helpers as jsonhelpers
 from nupic.support.enum import Enum
 
 

src/nupic/regions/KNNClassifierRegion.py

@@ -26,7 +26,7 @@
 """
 import numpy
 from nupic.bindings.regions.PyRegion import PyRegion
-from nupic.algorithms import KNNClassifier
+from nupic.algorithms import knn_classifier
 from nupic.bindings.math import Random
 
 
@@ -574,7 +574,7 @@ def _initEphemerals(self):
     self._protoScores = None
     self._categoryDistances = None
 
-    self._knn = KNNClassifier.KNNClassifier(**self.knnParams)
+    self._knn = knn_classifier.KNNClassifier(**self.knnParams)
 
     for x in ('_partitions', '_useAuxiliary', '_doSphering',
               '_scanInfo', '_protoScores'):

src/nupic/regions/TMRegion.py

@@ -24,7 +24,7 @@
 from nupic.bindings.regions.PyRegion import PyRegion
 
 from nupic.algorithms import (anomaly, backtracking_tm, backtracking_tm_cpp,
-                              BacktrackingTM_shim)
+                              backtracking_tm_shim)
 from nupic.support import getArgumentDescriptions
 
 gDefaultTemporalImp = 'py'
@@ -40,13 +40,13 @@ def _getTPClass(temporalImp):
   elif temporalImp == 'cpp':
     return backtracking_tm_cpp.BacktrackingTMCPP
   elif temporalImp == 'tm_py':
-    return BacktrackingTM_shim.TMShim
+    return backtracking_tm_shim.TMShim
   elif temporalImp == 'tm_cpp':
-    return BacktrackingTM_shim.TMCPPShim
+    return backtracking_tm_shim.TMCPPShim
   elif temporalImp == 'tm_py_fast':
-    return BacktrackingTM_shim.FastTMShim
+    return backtracking_tm_shim.FastTMShim
   elif temporalImp == 'monitored_tm_py':
-    return BacktrackingTM_shim.MonitoredTMShim
+    return backtracking_tm_shim.MonitoredTMShim
   else:
     raise RuntimeError("Invalid temporalImp '%s'. Legal values are: 'py', "
               "'cpp', 'tm_py', 'monitored_tm_py'" % (temporalImp))

src/nupic/regions/TestRegion.py

@@ -27,7 +27,7 @@
 
 from nupic.bindings.regions.PyRegion import PyRegion
 
-from nupic.data.dictutils import DictObj
+from nupic.data.dict_utils import DictObj
 
 
 

src/nupic/swarming/HypersearchV2.py

@@ -43,7 +43,7 @@
 from nupic.swarming.utils import sortedJSONDumpS, rApply, rCopy
 from nupic.swarming.utils import clippedObj
 from nupic.swarming.utils import (runModelGivenBaseAndParams, runDummyModel)
-from nupic.database.ClientJobsDAO import (
+from nupic.database.client_jobs_dao import (
     ClientJobsDAO, InvalidConnectionException)
 from nupic.swarming.exp_generator.ExpGenerator import expGenerator
 

src/nupic/swarming/HypersearchWorker.py

@@ -36,7 +36,7 @@
 from nupic.swarming.hypersearch.ExtendedLogger import ExtendedLogger
 from nupic.swarming.hypersearch.errorcodes import ErrorCodes
 from nupic.swarming.utils import clippedObj, validate
-from nupic.database.ClientJobsDAO import ClientJobsDAO
+from nupic.database.client_jobs_dao import ClientJobsDAO
 from HypersearchV2 import HypersearchV2
 
 
@@ -267,7 +267,7 @@ def run(self):
       wID = options.workerID
     else:
       wID = self._workerID
-    
+
     buildID = Configuration.get('nupic.software.buildNumber', 'N/A')
     logPrefix = '<BUILDID=%s, WORKER=HW, WRKID=%s, JOBID=%s> ' % \
                 (buildID, wID, options.jobID)
@@ -332,7 +332,7 @@ def run(self):
             # changed and new models, and sends those to the Hypersearch
             # implementation's self._hs.recordModelProgress() method.
             self._processUpdatedModels(cjDAO)
-  
+
             # --------------------------------------------------------------------
             # Create a new batch of models
             (exit, newModels) = self._hs.createModels(numModels = batchSize)
@@ -344,13 +344,13 @@ def run(self):
             #  orphan if it detects one.
             if len(newModels) == 0:
               continue
-  
+
             # Try and insert one that we will run
             for (modelParams, modelParamsHash, particleHash) in newModels:
               jsonModelParams = json.dumps(modelParams)
               (modelID, ours) = cjDAO.modelInsertAndStart(options.jobID,
                                   jsonModelParams, modelParamsHash, particleHash)
-  
+
               # Some other worker is already running it, tell the Hypersearch object
               #  so that it doesn't try and insert it again
               if not ours:
@@ -359,16 +359,16 @@ def run(self):
                 results = mResult.results
                 if results is not None:
                   results = json.loads(results)
-  
+
                 modelParams = json.loads(mParamsAndHash.params)
-                particleHash = cjDAO.modelsGetFields(modelID, 
+                particleHash = cjDAO.modelsGetFields(modelID,
                                   ['engParticleHash'])[0]
                 particleInst = "%s.%s" % (
                           modelParams['particleState']['id'],
                           modelParams['particleState']['genIdx'])
                 self.logger.info("Adding model %d to our internal DB " \
                       "because modelInsertAndStart() failed to insert it: " \
-                      "paramsHash=%s, particleHash=%s, particleId='%s'", modelID, 
+                      "paramsHash=%s, particleHash=%s, particleId='%s'", modelID,
                       mParamsAndHash.engParamsHash.encode('hex'),
                       particleHash.encode('hex'), particleInst)
                 self._hs.recordModelProgress(modelID = modelID,
@@ -382,14 +382,14 @@ def run(self):
               else:
                 modelIDToRun = modelID
                 break
-  
+
           else:
             # A specific modelID was passed on the command line
             modelIDToRun = int(options.modelID)
             mParamsAndHash = cjDAO.modelsGetParams([modelIDToRun])[0]
             modelParams = json.loads(mParamsAndHash.params)
             modelParamsHash = mParamsAndHash.engParamsHash
-            
+
             # Make us the worker
             cjDAO.modelSetFields(modelIDToRun,
                                      dict(engWorkerConnId=self._workerID))
@@ -413,12 +413,12 @@ def run(self):
               if not success:
                 raise RuntimeError("Unexpected failure to change paramsHash and "
                                    "particleHash of orphaned model")
-              
+
               (modelIDToRun, ours) = cjDAO.modelInsertAndStart(options.jobID,
                                   mParamsAndHash.params, modelParamsHash)
 
-            
-            
+
+
             # ^^^ end while modelIDToRun ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
         # ---------------------------------------------------------------
@@ -597,7 +597,7 @@ def main(argv):
   buildID = Configuration.get('nupic.software.buildNumber', 'N/A')
   logPrefix = '<BUILDID=%s, WORKER=HS, WRKID=N/A, JOBID=N/A> ' % buildID
   ExtendedLogger.setLogPrefix(logPrefix)
-  
+
   try:
     main(sys.argv)
   except:

src/nupic/swarming/ModelRunner.py

@@ -33,7 +33,7 @@
 from nupic.swarming.hypersearch import regression
 from nupic.swarming.hypersearch.errorcodes import ErrorCodes
 
-from nupic.database.ClientJobsDAO import ClientJobsDAO
+from nupic.database.client_jobs_dao import ClientJobsDAO
 from nupic.frameworks.opf import opf_helpers
 from nupic.frameworks.opf.model_factory import ModelFactory
 from nupic.frameworks.opf.opf_basic_environment import BasicPredictionLogger

src/nupic/swarming/api.py

@@ -27,7 +27,7 @@
 import tempfile
 
 from nupic.frameworks.opf import opf_helpers
-from nupic.database.ClientJobsDAO import ClientJobsDAO
+from nupic.database.client_jobs_dao import ClientJobsDAO
 from nupic.support.configuration import Configuration
 
 

src/nupic/swarming/permutations_runner.py

@@ -32,7 +32,7 @@
 
 from nupic.swarming.hypersearch import object_json as json
 
-import nupic.database.ClientJobsDAO as cjdao
+import nupic.database.client_jobs_dao as cjdao
 from nupic.swarming import HypersearchWorker
 from nupic.swarming.HypersearchV2 import HypersearchV2
 from nupic.swarming.exp_generator.ExpGenerator import expGenerator
@@ -1423,7 +1423,7 @@ class JobStatus(object):
     """ @private
     Our Nupic Job Info abstraction class"""
 
-    # Job Status values (per ClientJobsDAO.py):
+    # Job Status values (per client_jobs_dao.py):
     __nupicJobStatus_NotStarted  = cjdao.ClientJobsDAO.STATUS_NOTSTARTED
     __nupicJobStatus_Starting    = cjdao.ClientJobsDAO.STATUS_STARTING
     __nupicJobStatus_running     = cjdao.ClientJobsDAO.STATUS_RUNNING