And if I try to “preetify” it with json.dumps and jq I get this:
{
"spParams": {
"columnCount": 2048,
"spVerbosity": 0,
"localAreaDensity": -1,
"spatialImp": "cpp",
"inputWidth": 946,
"synPermInactiveDec": 0.005,
"synPermConnected": 0.1,
"synPermActiveInc": 0.04,
"seed": 1956,
"numActiveColumnsPerInhArea": 40,
"boostStrength": 3,
"globalInhibition": 1,
"potentialPct": 0.85
},
"predictAheadTime": null,
"seconds": 0,
"tmParams": {
"columnCount": 2048,
"pamLength": 1,
"permanenceInc": 0.1,
"outputType": "normal",
"initialPerm": 0.21,
"seed": 1960,
"maxSegmentsPerCell": 128,
"temporalImp": "cpp",
"activationThreshold": 16,
"cellsPerColumn": 32,
"permanenceDec": 0.1,
"minThreshold": 12,
"verbosity": 0,
"maxSynapsesPerSegment": 32,
"globalDecay": 0,
"newSynapseCount": 20,
"maxAge": 0,
"inputWidth": 2048
},
"tmEnable": true,
"years": 0,
"hours": 1,
"modelParams": null,
"inferenceType": "TemporalMultiStep",
"model": "HTMPrediction",
"sensorParams": {
"verbosity": 0,
"encoders": {
"timestamp_timeOfDay": {
"fieldname": "timestamp",
"timeOfDay": [
21,
1
],
"type": "DateEncoder",
"name": "timestamp_timeOfDay"
},
"consumption": {
"fieldname": "consumption",
"seed": 1,
"resolution": 0.88,
"name": "consumption",
"type": "RandomDistributedScalarEncoder"
},
"timestamp_weekend": {
"fieldname": "timestamp",
"type": "DateEncoder",
"name": "timestamp_weekend",
"weekend": 21
}
},
"sensorAutoReset": null
},
"trainSPNetOnlyIfRequested": false,
"clParams": {
"steps": "1,5",
"maxCategoryCount": 1000,
"implementation": "cpp",
"alpha": 0.1,
"verbosity": 0,
"regionName": "SDRClassifierRegion"
},
"fields": [
[
"consumption",
"mean"
]
],
"months": 0,
"days": 0,
"aggregationInfo": null,
"version": 1,
"spEnable": true,
"microseconds": 0,
"weeks": 0,
"minutes": 0,
"milliseconds": 0
}