ENH: Basic anomaly detector #393
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tibkiss
commented
Nov 18, 2020
tibkiss
commented
Nov 18, 2020
tibkiss
commented
Nov 18, 2020
uda/anomaly/anomaly.go
Outdated
| pctChange := make([]float64, size-1) | ||
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| // pctChange = (a - b)/a | ||
| // floats.SubTo(pctChange, columnData[1:], columnData[:size-1]) |
tibkiss
commented
Nov 18, 2020
kalmant
reviewed
Nov 18, 2020
kalmant
reviewed
Nov 18, 2020
| if _, ok := a.AnomalyIdxsByColumn[epoch]; ok { | ||
| previousValue = a.AnomalyIdxsByColumn[epoch] | ||
| } | ||
| a.AnomalyIdxsByColumn[epoch] = previousValue | 1<<columnNr |
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If columnNr is big enough (which seems very unlikely btw) then an overflow might occur.
kulcsarb
reviewed
Nov 20, 2020
| import pymarketstore as pymkts | ||
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| # Constants | ||
| DATA_TYPE_TICK = [('Epoch', 'i8'), ('Bid', 'f4'), ('Ask', 'f4'), ('Nanoseconds', 'i4')] |
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i4 is the right type for Nanoseconds, but later in the tests, all nanosec data are given as floats, so numpy trucates all of them to 0. I'm don't think it's causing much trouble, but better be on the safe side.
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wow, we need to address that
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Basic anomaly detector with Z-Score and Fixed Pct based detection for the
data columns in Marketstore. Can be used to spot price or volume outliers
in the ingested data.