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Once the normalization process is complete, a single time series sampled at a uniform interval is given.
SimpleMetrics
Simple metrics form the 'base' of the Metrics system. They are defined on a specific Type and reference timeseries data stored within.
Essentially, the Simple metric defines:
- How to find the timeseries data on the Type
- Configuration of the Normalization engine
CompoundMetrics
Evaluating Metrics
Not all SimpleMetrics are defined on all types. Types on which you can evaluate a metric mixin the Type 'MetricEvaluatable' (C3 Docs here: https://developer.c3.ai/docs/7.12.0/type/MetricEvaluatable)
This bestows the function 'listMetrics' to that type, so if you're unsure what kind of metrics are available for a given type, execute that function to get a list, for example:
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var metrics = SmartBulb.listMetrics()
c3Grid(metrics) |
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pd.DataFrame(c3.SmartBulb.listMetrics().toJson()) |
Once you have the metric you want to evaluate in mind, you
Conclusion
To get started quickly, focus on 'CompoundMetrics'. They're the easiest to use, and for most cases, the 'AVG' treatment works well.
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- Timeseries Normalization: https://developer.c3.ai/docs/7.12.0/guide/guide-c3aisuite-basic/ts-normalization-engine
- Timeseries Treatments: https://developer.c3.ai/docs/7.12.0/guide/guide-c3aisuite-basic/ts-treatments-home
- Timeseries metrics:https://developer.c3.ai/docs/7.12.0/guide/guide-c3aisuite-basic/metrics-home
- SimpleMetrics: https://developer.c3.ai/docs/7.12.0/guide/guide-c3aisuite-basic/metrics-simple-metrics
- CompoundMetrics: https://developer.c3.ai/docs/7.12.0/guide/guide-c3aisuite-basic/metrics-compound-metrics
Review and Next Steps
Principals from this Primer are