def run(inputFiles,
networkConfigsFile,
plotResults,
runClustering):
with open(networkConfigsFile, 'rb') as jsonFile:
networkConfigurations = simplejson.load(jsonFile)
expResults = []
for networkConfig in networkConfigurations:
for inputFile in inputFiles:
expResult = runExperiment(networkConfig, inputFile, runClustering)
expResults.append(expResult)
if plotResults:
# traces = loadTraces(fileName)
traces = expResult['expTrace']
tmParams = networkConfig['tmRegionConfig']['regionParams']
numCells = tmParams['cellsPerColumn'] * tmParams['inputWidth']
numClusters = len(set(traces['actualCategory']))
if os.path.exists(OUTPUT_DIR):
shutil.rmtree(OUTPUT_DIR)
os.makedirs(OUTPUT_DIR)
cellsType = CELLS_TO_CLUSTER
numSteps = len(traces['recordNumber'])
pointsToPlot = numSteps / 10
vizInterCategoryClusters(traces,
OUTPUT_DIR,
cellsType,
numCells,
pointsToPlot)
vizInterSequenceClusters(traces, OUTPUT_DIR, cellsType, numCells,
numClusters)
xl = None
plotTemporalMemoryStates = False
title = inputFile.split('/')[-1]
outputFile = '%s.png' % inputFile[:-4]
plotTraces(xl, traces, title, ANOMALY_SCORE, outputFile,
runClustering)
traceOutputDir = os.path.join(OUTPUT_DIR, 'traces')
if not os.path.exists(traceOutputDir):
os.makedirs(traceOutputDir)
saveTraces(os.path.join(traceOutputDir, '%s.csv'), expResults)
def run(inputFiles, networkConfigsFile, plotResults, runClustering):
with open(networkConfigsFile, 'rb') as jsonFile:
networkConfigurations = simplejson.load(jsonFile)
expResults = []
for networkConfig in networkConfigurations:
for inputFile in inputFiles:
expResult = runExperiment(networkConfig, inputFile, runClustering)
expResults.append(expResult)
if plotResults:
# traces = loadTraces(fileName)
traces = expResult['expTrace']
tmParams = networkConfig['tmRegionConfig']['regionParams']
numCells = tmParams['cellsPerColumn'] * tmParams['inputWidth']
numClusters = len(set(traces['actualCategory']))
if os.path.exists(OUTPUT_DIR):
shutil.rmtree(OUTPUT_DIR)
os.makedirs(OUTPUT_DIR)
cellsType = CELLS_TO_CLUSTER
numSteps = len(traces['recordNumber'])
pointsToPlot = numSteps / 10
vizInterCategoryClusters(traces, OUTPUT_DIR, cellsType,
numCells, pointsToPlot)
vizInterSequenceClusters(traces, OUTPUT_DIR, cellsType,
numCells, numClusters)
xl = None
plotTemporalMemoryStates = False
title = inputFile.split('/')[-1]
outputFile = '%s.png' % inputFile[:-4]
plotTraces(xl, traces, title, outputFile,
plotTemporalMemoryStates)
traceOutputDir = os.path.join(OUTPUT_DIR, 'traces')
if not os.path.exists(traceOutputDir):
os.makedirs(traceOutputDir)
saveTraces(os.path.join(traceOutputDir, '%s.csv'), expResults)
dest="numTmCells",
help="Number of cells in the Temporal Memory")
(options, remainder) = parser.parse_args()
return options, remainder
if __name__ == "__main__":
(_options, _args) = _getArgs()
inputFile = _options.fileName
plotTemporalMemoryStates = _options.plotTemporalMemoryStates
if _options.xl:
xl = [int(x) for x in _options.xl.split(',')]
else:
xl = _options.xl
print inputFile
traces = loadTraces(inputFile)
numTmCells = _options.numTmCells
title = inputFile.split('/')[-1]
outputFile = '%s.png' % inputFile[:-4]
plt = plotTraces(xl, traces, title, ANOMALY_SCORE, outputFile, CLUSTERING,
numTmCells, plotTemporalMemoryStates)
plt.show()
default=None,
dest="xl",
help="x-axis range")
parser.add_option("--numTmCells",
type=int,
default=32 * 2048,
dest="numTmCells",
help="Number of cells in the Temporal Memory")
(options, remainder) = parser.parse_args()
return options, remainder
if __name__ == "__main__":
(_options, _args) = _getArgs()
fileName = _options.fileName
if _options.xl:
xl = [float(x) for x in _options.xl.split(',')]
else:
xl = _options.xl
traces = loadTraces(fileName)
title = fileName
numTmCells = _options.numTmCells
plotTraces(numTmCells, title, xl, traces)
default=32 * 2048,
dest="numTmCells",
help="Number of cells in the Temporal Memory")
(options, remainder) = parser.parse_args()
return options, remainder
if __name__ == "__main__":
(_options, _args) = _getArgs()
inputFile = _options.fileName
plotTemporalMemoryStates = _options.plotTemporalMemoryStates
if _options.xl:
xl = [int(x) for x in _options.xl.split(',')]
else:
xl = _options.xl
print inputFile
traces = loadTraces(inputFile)
numTmCells = _options.numTmCells
title = inputFile.split('/')[-1]
outputFile = '%s.png' % inputFile[:-4]
plotTraces(xl, traces, title, ANOMALY_SCORE, outputFile, numTmCells,
plotTemporalMemoryStates)
