Swarming create model_params.py Seems to have problems, can not accurately predict!

Engineering NuPIC
1

search_def_sar.json below:

{
  "includedFields": [
    {
      "fieldName": "ddt",
      "fieldType": "datetime"
    },
    {
      "fieldName": "txkB",
      "fieldType": "float"
    }
  ],
  "streamDef": {
    "info": "sar",
    "version": 1,
    "streams": [
      {
        "info": "sar.csv",
        "source": "file://sar.csv",
        "columns": [
          "*"
        ]
      }
    ],
    "aggregation": {
      "hours": 0,
      "microseconds": 0,
      "seconds": 0,
      "fields": [
        [
          "txkB",
          "sum"
        ],
        [
          "ddt",
          "first"
        ]
      ],
      "weeks": 1,
      "months": 0,
      "mimutes": 0,
      "days": 0,
      "milliseconds": 0,
      "years": 0
    }
  },
  "inferenceType": "TemporalAnomaly",
  "inferenceArgs": {
    "predictionSteps": [
      1
    ],
    "predictedField": "txkB"
  },
  "iterationCount": -1,
  "swarmSize": "medium"

}

model_params.py below:

MODEL_PARAMS = {
    'aggregationInfo': {
        'days': 0,
        'fields': [],
        'hours': 0,
        'microseconds': 0,
        'milliseconds': 0,
        'minutes': 0,
        'months': 0,
        'seconds': 0,
        'weeks': 1,
        'years': 0
    },
    'model': 'HTMPrediction',
    'modelParams': {
        'anomalyParams': {
            u'anomalyCacheRecords': None,
            u'autoDetectThreshold': None,
            u'autoDetectWaitRecords': None
        },
        'clParams': {
            'alpha': 0.0001,
            'regionName': 'SDRClassifierRegion',
            'steps': '1',
            'verbosity': 0
        },
        'inferenceType': 'TemporalAnomaly',
        'sensorParams': {
            'encoders': {
                u'ddt_dayOfWeek': None,
                u'ddt_timeOfDay': {
                    'fieldname': 'ddt',
                    'name': 'timestamp',
                    'timeOfDay': (21, 6.0903),
                    'type': 'DateEncoder'
                },
                u'ddt_weekend': {
                    'fieldname': 'ddt',
                    'name': 'timestamp',
                    'type': 'DateEncoder',
                    'weekend': (21, 1)
                },
                u'txkB': {
                    'clipInput': True,
                    'fieldname': 'txkB',
                    'n': 22,
                    'name': 'txkB',
                    'type': 'AdaptiveScalarEncoder',
                    'w': 21
                }
            },
            'sensorAutoReset': None,
            'verbosity': 0
        },
        'spEnable': True,
        'spParams': {
            'boostStrength': 0.0,
            'columnCount': 2048,
            'globalInhibition': 1,
            'inputWidth': 0,
            'numActiveColumnsPerInhArea': 40,
            'potentialPct': 0.8,
            'seed': 1956,
            'spVerbosity': 0,
            'spatialImp': 'cpp',
            'synPermActiveInc': 0.05,
            'synPermConnected': 0.1,
            'synPermInactiveDec': 0.1
        },
        'tmEnable': True,
        'tmParams': {
            'activationThreshold': 12,
            'cellsPerColumn': 32,
            'columnCount': 2048,
            'globalDecay': 0.0,
            'initialPerm': 0.21,
            'inputWidth': 2048,
            'maxAge': 0,
            'maxSegmentsPerCell': 128,
            'maxSynapsesPerSegment': 32,
            'minThreshold': 9,
            'newSynapseCount': 20,
            'outputType': 'normal',
            'pamLength': 1,
            'permanenceDec': 0.1,
            'permanenceInc': 0.1,
            'seed': 1960,
            'temporalImp': 'cpp',
            'verbosity': 0
        },
        'trainSPNetOnlyIfRequested': False
    },
    'predictAheadTime': None,
    'version': 1
}
2

What does the input data look like? Can you include a chart of ddt moving over time?