Test NuPIC.

test_nupic.py

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()