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@kennytm
Created June 11, 2013 14:07
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Test NuPIC.
import nupic.frameworks.opf.modelfactory as mf
import nupic.frameworks.opf.opfutils as ou
import nupic.frameworks.opf.predictionmetricsmanager as pm
import nupic.frameworks.opf.metrics as mt
import random
import math
STEPS = 5
FIELD = 'latitude'
model_config = {
'model': 'CLA',
'version': 1,
'modelParams': {
'inferenceType': 'TemporalMultiStep',
'sensorParams': {
'verbosity': 0,
'encoders': {
FIELD: {
'type': 'ScalarEncoder',
'fieldname': FIELD,
'name': FIELD,
'minval': -1,
'maxval': 1,
'periodic': False,
'resolution': 0.02,
'w': 7,
},
},
'sensorAutoReset': None,
},
'spParams': {
'spVerbosity': 0,
'columnCount': 2048,
},
'tpParams': {
'verbosity': 0,
'columnCount': 2048,
'inputWidth': 2048,
'cellsPerColumn': 32,
},
'clParams': {
'regionName' : 'CLAClassifierRegion',
'steps': STEPS,
},
'predictedField': 'latitude',
},
}
model = mf.ModelFactory.create(model_config)
metrics_manager = pm.MetricsManager(
[
mt.MetricSpec(
field='latitude',
metric='multiStep',
inferenceElement='multiStepBestPredictions',
params={'errorMetric': 'altMAPE', 'window': 200, 'steps': STEPS}
)
],
model.getFieldInfo(),
model.getInferenceType()
)
model.enableInference({
'predictedField': FIELD,
'predictionSteps': STEPS,
})
for i in range(700):
dictionary = {'index': i, 'latitude': math.sin(i * 0.1)}
res = model.run(dictionary)
#res.metrics = metrics_manager.update(res)
print i, dictionary[FIELD], res.inferences['multiStepBestPredictions'][STEPS]
model.finishLearning()
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