Documentation ¶
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Constants ¶
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Variables ¶
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Functions ¶
Types ¶
type Config ¶
type Config struct { // Alpha is the p-value cutoff to report a change as significant. If 0 then // the default value of 0.05 is used. Alpha float64 // Order is used to sort the results. If none is supplied then results are // sorted by Delta. Order Order // IQRR, if true, causes outliers to be removed via the Interquartile Rule. IQRR bool // All, if true, returns all rows, even if no significant change was seen // for a now. If false then only return rows with significant changes. All bool // Test is the kind of statistical test to do. Defaults to UTest. Test Test }
Config controls the analysis done on the samples.
type Metrics ¶
type Metrics struct { Mean float64 StdDev float64 Values []float64 // May have outliers removed. Percent float64 }
Metrics are calculated for each test.
type Result ¶
type Result struct { // Rows, with one Row per result. Rows []Row // Skipped is the number of results we skipped, because either we couldn't // calculate the statistics, or there wasn't data in both 'before' and // 'after'. Skipped int }
Result is the resulting calculations returned from Analyze.
type Row ¶
type Row struct { // Name of sample, i.e. its trace name. Name string // The full set of Params for the trace. Params paramtools.Params // Samples are the metrics for both samples, the first is 'before', the // second is 'after'. See Analyze(). Samples [2]Metrics // The change in mean between before and after samples, as a percent. I.e. // from -100 to 100. This will be NaN if no significant change is found // between the samaple. Delta float64 // P is p-value for the specified test for the null hypothesis that the // samples are from the same population. P float64 // Note of any issues that arose during calculations. Note string }
Row is a single row in the results.
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