sfxDataQualityExt

Look for missing or strange values in your data.
sfxDataQualityExt

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v1.0.8

Axon functions

sfxDQFindNulls
sfxDQFindNulls(thePoint, dates, interval: 15min)

Find Missing Values

  • This rule runs at the point level.
  • Do rollups of the expected interval of the data. Then, look for empty periods.
  • sfxDQTSGap() does the same thing, but is more advanced.
  • Side Effects: None.
  • Input: A point, a date/date range, and an expected interval.
  • Output: hisDurGrid
  • sfxDQFindNulls(read(temp and discharge), pastMonth, 20min)
sfxDQFindOddities
sfxDQFindOddities(thePoint, dates)

Find Oddities

  • This rule runs at the point level.
  • Finds nulls, NAs, or numbers less than or equal to 0.
  • Side Effects: None.
  • Input: A point and a date/date range.
  • Output: hisDurGrid
  • sfxDQFindOddities(read(temp and discharge), pastMonth)
sfxDQFindOutliers
sfxDQFindOutliers(thePoint, dates, sDs: 3)

Find Outliers Based on Standard Deviation

  • This rule runs at the point level.
  • This rule has been modified to rely on the hisDQAverage tag that comes from the DQJob.
  • sDs is the number of standard deviations you want this rule to allow for before a spark is detected. If a history record is below or above 3 stdDev, it will cause a spark in this form (you can change this).
  • Side Effects: None.
  • Input: A point, a date/date range, and optionally, how many standard deviations to go out.
  • Output: hisDurGrid
  • sfxDQFindOutliers(read(temp and discharge), pastMonth, 4)
sfxDQJob
sfxDQJob(reInitialize: 1mo, dateRange: pastYear)

Data Quality Job

  • Adds Descriptive Tags to Numeric Points
  • Run this as a job weekly
  • reInitialize tells SkySpark how often to update tags
  • Descriptive tags can be modified by user on the fly or with tuning function.
  • Monthly running yearly total normalizes for many things.
  • Dependencies: Calculus and Signal Analysis Pods.
  • Side Effects: Adds several statistical tags to all numeric points that can be used for complex rules.
  • Input: Optional reInitialize interval and option how far back to go (default is 1mo and pastYear).
  • Output: None.
  • sfxDQJob()
sfxDQOutofRange
sfxDQOutofRange(thePoint, dates, buffer: 0.8)

Find Outliers

  • This rule runs at the point level.
  • Use tags from data quality job to look for outliers.
  • Side Effects: None.
  • Input: A point, a date/date range, and optional buffer.
  • The buffer determines what percentage of the pastYear's absolute min or max is acceptable.
  • if old: {min: 50, max: 100, buffer: 0.8} then run against: {minThresh: 62.5, maxThresh: 80} (50/0.8 = 62.5 and 100*0.8 = 80)
  • Output: hisDurGrid
  • sfxDQOutofRange(read(temp and discharge), pastMonth, 0.7)
sfxDQRateofChange
sfxDQRateofChange(thePoint, dates, buffer: 0.8)

Find Rate of Change too High

  • This rule runs at the point level.
  • sfxDQRateofChange() does the same thing, but is more advanced.
  • Use tags from data quality job to look for rate-of-change outliers.
  • Dependencies: Calculus and Signal Analysis Pods.
  • Side Effects: None.
  • Input: A point, a date/date range, and an optional buffer.
  • The buffer determines what percentage of the pastYear's absolute max negative or max positive rate of change is acceptable.
  • if oldROC: {maxNegROC: -10, maxPosROC: 10, buffer: 0.8} then run against: {maxNegROCThresh: -8, maxPosROCThresh: 8} (-10*0.8 = -8 and 10*0.8 = 8)
  • Output: hisDurGrid
  • sfxDQRateofChange(read(temp and discharge), pastMonth, 0.7)
sfxDQRateofChangeThresh
sfxDQRateofChangeThresh(thePoint, dates, threshold: 5)

Find Rate of Change too High

  • This rule runs at the point level.
  • Use tags from data quality job to look for rate-of-change outliers.
  • Dependencies: Calculus and Signal Analysis Pods.
  • Side Effects: None.
  • Input: A point, a date/date range, and a threshold.
  • Output: hisDurGrid
  • sfxDQRateofChangeThresh(read(temp and discharge), pastMonth, 10)
sfxDQTSGap
sfxDQTSGap(thePoint, dates, buffer: 1.9)

Find Gaps in Data

  • This rule runs at the point level.
  • Use tags from data quality job to look for missing data/intervals.
  • Side Effects: None.
  • Input: A point, a date/date range, and an optional buffer.
  • The buffer determines what percentage of the pastYear's median ts interval is acceptable.
  • if oldTSInt: {medTSInt: 15min, buffer: 1.9} then run against: {medTSIntThresh: 28.5min} (15min*1.9 = 28.5min)
  • Output: hisDurGrid
  • sfxDQTSGap(read(temp and discharge), pastMonth, 1.8)
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