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Check analytical outputs for drift against a certified baseline

Source: R/certify.R
check_drift.Rd

Re-hashes a set of named R objects and compares them against a previously stored certification. Reports which outputs are unchanged ("ok"), have changed ("drifted"), are present in the baseline but not supplied ("missing"), or are new outputs not in the baseline ("new").

Usage

check_drift(
  outputs,
  against = "latest",
  file = ".reproducr",
  tolerance = 1e-10
)

Arguments

outputs

A fully named list of current R objects – the same names used in the certify() call being compared against.

against

character(1). The certification tag to compare against. Use "latest" (the default) to automatically select the most recently added certification.

file

character(1). Base path of the certification store. Default ".reproducr" (reads .reproducr.rds).

tolerance

numeric(1). Numeric tolerance applied to hash comparison. When > 0, outputs whose hashes differ are also compared element-wise (for numeric vectors/matrices), and flagged as "ok" if the maximum absolute difference is within tolerance. Set to 0 for exact matching only. Default 1e-10.

Value

Invisibly returns a data.frame of class c("drift_report", "data.frame") with columns output, status ("ok", "drifted", "missing", "new"), max_delta, and note. Also prints a summary to the console.

See also

certify() to create a baseline; list_certs() to see available tags.

Examples

cert_file <- tempfile()
model <- lm(mpg ~ wt, data = mtcars)

certify(list(coefs = coef(model)), tag = "v1", file = cert_file)
#> reproducr: certified 1 output(s) [2026-06-10] under tag 'v1'

# Same outputs -- should report "ok"
result <- check_drift(list(coefs = coef(model)),
  against = "v1", file = cert_file
)
#> 
#> -- reproducr drift check vs 'v1' --
#> 
#>   Verdict  : ALL OUTPUTS MATCH
#>   OK       : 1
#>   Drifted  : 0
#>   Missing  : 0
#>   New      : 0
#> 
print(result)
#> 
#> -- reproducr drift report --
#> 
#> [OK]      coefs
#> 

# Different model -- should report "drifted"
model2 <- lm(mpg ~ hp, data = mtcars)
check_drift(list(coefs = coef(model2)),
  against = "v1", file = cert_file
)
#> 
#> -- reproducr drift check vs 'v1' --
#> 
#>   Verdict  : DRIFT DETECTED
#>   OK       : 0
#>   Drifted  : 1
#>   Missing  : 0
#>   New      : 0
#> 
#>   Drifted outputs:
#>     - coefs
#>