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Copy file name to clipboardExpand all lines: validator/PLANS.md
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* This test is partially captured by checking avgs in source vs reference data, unless erroneous zeroes continue for more than a week
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* Also partially captured by outlier checking. If zeroes aren't outliers, then it's hard to say that they're erroneous at all.
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* Easier suppression of many errors at once
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* Maybe store errors as dict of dicts. Keys could be check strings (e.g. "check_bad_se"), then next layer geo type, etc
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* Nicer formatting for error “report”.
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* E.g. if a single type of error is raised for many different datasets, summarize all error messages into a single message? But it still has to be clear how to suppress each individually
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* Use known erroneous/anomalous days of source data to tune static thresholds and test behavior
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