From 408c5d9d56c369c50df319952d116ddb2f0327f7 Mon Sep 17 00:00:00 2001 From: Petr Tuma Date: Mon, 6 Nov 2023 10:09:49 +0100 Subject: [PATCH] Missing pkgdown function --- _pkgdown.yml | 1 + docs/404.html | 2 +- docs/LICENSE.html | 2 +- docs/authors.html | 2 +- docs/deps/bootstrap-5.2.2/bootstrap.min.css | 4 +- docs/index.html | 25 +- docs/reference/Rplot001.png | Bin 1011 -> 0 bytes docs/reference/assert_renaissance.html | 102 -------- docs/reference/check_renaissance.html | 103 -------- .../compute_flat_percentile_cis.html | 108 --------- ...pute_flat_percentile_cis_group_helper.html | 98 -------- docs/reference/compute_trends.html | 90 ------- docs/reference/expect_renaissance.html | 102 -------- .../identify_vector_outliers_global.html | 119 ---------- .../identify_vector_outliers_window.html | 123 ---------- docs/reference/index.html | 222 ------------------ docs/reference/list_dimensions.html | 86 ------- docs/reference/list_outliers_global.html | 94 -------- .../reference/list_outliers_group_helper.html | 102 -------- docs/reference/list_outliers_window.html | 94 -------- .../list_regular_artifacts_by_interval.html | 109 --------- .../list_regular_artifacts_by_position.html | 109 --------- docs/reference/list_segment_boundaries.html | 94 -------- .../list_segment_boundaries_group_helper.html | 105 --------- docs/reference/load_file_json.html | 117 --------- docs/reference/load_path_json.html | 129 ---------- docs/reference/locate_vector_segments.html | 97 -------- docs/reference/preserve_last_n.html | 103 -------- docs/reference/preserve_last_sec.html | 112 --------- docs/reference/remove_outliers_global.html | 94 -------- docs/reference/remove_outliers_window.html | 94 -------- docs/reference/rren-package.html | 81 ------- docs/reference/rren_artificial.html | 98 -------- docs/reference/rren_example.html | 86 ------- docs/search.json | 1 - docs/sitemap.xml | 96 -------- 36 files changed, 30 insertions(+), 2974 deletions(-) delete mode 100644 docs/reference/Rplot001.png delete mode 100644 docs/reference/assert_renaissance.html delete mode 100644 docs/reference/check_renaissance.html delete mode 100644 docs/reference/compute_flat_percentile_cis.html delete mode 100644 docs/reference/compute_flat_percentile_cis_group_helper.html delete mode 100644 docs/reference/compute_trends.html delete mode 100644 docs/reference/expect_renaissance.html delete mode 100644 docs/reference/identify_vector_outliers_global.html delete mode 100644 docs/reference/identify_vector_outliers_window.html delete mode 100644 docs/reference/index.html delete mode 100644 docs/reference/list_dimensions.html delete mode 100644 docs/reference/list_outliers_global.html delete mode 100644 docs/reference/list_outliers_group_helper.html delete mode 100644 docs/reference/list_outliers_window.html delete mode 100644 docs/reference/list_regular_artifacts_by_interval.html delete mode 100644 docs/reference/list_regular_artifacts_by_position.html delete mode 100644 docs/reference/list_segment_boundaries.html delete mode 100644 docs/reference/list_segment_boundaries_group_helper.html delete mode 100644 docs/reference/load_file_json.html delete mode 100644 docs/reference/load_path_json.html delete mode 100644 docs/reference/locate_vector_segments.html delete mode 100644 docs/reference/preserve_last_n.html delete mode 100644 docs/reference/preserve_last_sec.html delete mode 100644 docs/reference/remove_outliers_global.html delete mode 100644 docs/reference/remove_outliers_window.html delete mode 100644 docs/reference/rren-package.html delete mode 100644 docs/reference/rren_artificial.html delete mode 100644 docs/reference/rren_example.html delete mode 100644 docs/search.json delete mode 100644 docs/sitemap.xml diff --git a/_pkgdown.yml b/_pkgdown.yml index c09e02c..e57377b 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -24,6 +24,7 @@ reference: contents: - rren_example - rren_artificial + - report_summaries - title: internal contents: diff --git a/docs/404.html b/docs/404.html index af74806..29e3f7d 100644 --- a/docs/404.html +++ b/docs/404.html @@ -24,7 +24,7 @@ rren - 0.0.5 + 0.0.7 - - - - - -
-
-
-

Check whether data resembles typical measurement results.

- Source: R/load.R -
assert_renaissance.Rd
-
- -
-

Check whether data resembles typical measurement results.

-
- -
-

Usage

- 
assert_renaissance(.input, .var.name = vname(.data), add = NULL, ...)
-
- -
-

Arguments

-
.input
-

Measurement results to test.

- - -
.var.name
-

Internal.

- - -
add
-

Internal.

- - -
...
-

Parameters to check_renaissance().

- -
-
-

Value

- - -

Invisible .data or an exception.

-
-
-

See also

-

check_renaissance

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/check_renaissance.html b/docs/reference/check_renaissance.html deleted file mode 100644 index bfa6053..0000000 --- a/docs/reference/check_renaissance.html +++ /dev/null @@ -1,103 +0,0 @@ - -Check whether data resembles typical measurement results. — check_renaissance • rren - Skip to contents - - -
-
-
-

Check whether data resembles typical measurement results.

- Source: R/load.R -
check_renaissance.Rd
-
- -
-

Check whether data resembles typical measurement results.

-
- -
-

Usage

- 
check_renaissance(
-  .input,
-  .check_index = TRUE,
-  .check_total = TRUE,
-  .check_metadata = TRUE
-)
-
- -
-

Arguments

-
.input
-

Measurement results to test.

- - -
.check_index
-

Check presence of index.

- - -
.check_total
-

Check presence of total.

- - -
.check_metadata
-

Check presence of descriptive metadata columns.

- -
-
-

Value

- - -

Error message or TRUE.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/compute_flat_percentile_cis.html b/docs/reference/compute_flat_percentile_cis.html deleted file mode 100644 index ec4b819..0000000 --- a/docs/reference/compute_flat_percentile_cis.html +++ /dev/null @@ -1,108 +0,0 @@ - -Compute flat percentile bootstrap confidence interval. — compute_flat_percentile_cis • rren - Skip to contents - - -
-
-
-

Compute flat percentile bootstrap confidence interval.

- Source: R/interval.R -
compute_flat_percentile_cis.Rd
-
- -
-

Uses bootstrap to compute percentile confidence interval on data summarized across runs.

-
- -
-

Usage

- 
compute_flat_percentile_cis(
-  .input,
-  .column,
-  .statistic = mean,
-  .confidence = 0.99,
-  .R = 10000
-)
-
- -
-

Arguments

-
.input
-

Data summarized across runs.

- - -
.column
-

Column to compute confidence interval for.

- - -
.statistic
-

Statistic to compute confidence interval for.

- - -
.confidence
-

Confidence level.

- - -
.R
-

Replicates.

- -
-
-

Value

- - -

Summarized tibble with confidence interval columns.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/compute_flat_percentile_cis_group_helper.html b/docs/reference/compute_flat_percentile_cis_group_helper.html deleted file mode 100644 index c1d6644..0000000 --- a/docs/reference/compute_flat_percentile_cis_group_helper.html +++ /dev/null @@ -1,98 +0,0 @@ - -Group helper for flat percentile bootstrap confidence interval. — compute_flat_percentile_cis_group_helper • rren - Skip to contents - - -
-
-
-

Group helper for flat percentile bootstrap confidence interval.

- Source: R/interval.R -
compute_flat_percentile_cis_group_helper.Rd
-
- -
-

Group helper for flat percentile bootstrap confidence interval.

-
- -
-

Usage

- 
compute_flat_percentile_cis_group_helper(.input, .statistic, .confidence, .R)
-
- -
-

Arguments

-
.input
-

Data to compute confidence interval for.

- - -
.statistic
-

Statistic to compute confidence interval for.

- - -
.confidence
-

Confidence level.

- - -
.R
-

Number of replicates.

- -
-
-

Value

- - -

Tibble with confidence interval.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/compute_trends.html b/docs/reference/compute_trends.html deleted file mode 100644 index 27c2628..0000000 --- a/docs/reference/compute_trends.html +++ /dev/null @@ -1,90 +0,0 @@ - -Compute trends. — compute_trends • rren - Skip to contents - - -
-
-
-

Compute trends.

- Source: R/trend.R -
compute_trends.Rd
-
- -
-

Uses linear least squares regression to compute trend of each run.

-
- -
-

Usage

- 
compute_trends(.input, .column)
-
- -
-

Arguments

-
.input
-

Data.

- - -
.column
-

Column to compute trend for.

- -
-
-

Value

- - -

Summarized tibble with trends column.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/expect_renaissance.html b/docs/reference/expect_renaissance.html deleted file mode 100644 index b7f39d8..0000000 --- a/docs/reference/expect_renaissance.html +++ /dev/null @@ -1,102 +0,0 @@ - -Check whether data resembles typical measurement results. — expect_renaissance • rren - Skip to contents - - -
-
-
-

Check whether data resembles typical measurement results.

- Source: R/load.R -
expect_renaissance.Rd
-
- -
-

Check whether data resembles typical measurement results.

-
- -
-

Usage

- 
expect_renaissance(.input, info = NULL, label = vname(.data), ...)
-
- -
-

Arguments

-
.input
-

Measurement results to test.

- - -
info
-

Internal.

- - -
label
-

Internal.

- - -
...
-

Parameters to check_renaissance().

- -
-
-

Value

- - -

An expectation.

-
-
-

See also

-

check_renaissance()

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/identify_vector_outliers_global.html b/docs/reference/identify_vector_outliers_global.html deleted file mode 100644 index f5a03d8..0000000 --- a/docs/reference/identify_vector_outliers_global.html +++ /dev/null @@ -1,119 +0,0 @@ - -Compute outlier flags. — identify_vector_outliers_global • rren - Skip to contents - - -
-
-
-

Compute outlier flags.

- Source: R/filter.R -
identify_vector_outliers_global.Rd
-
- -
-

The outlier detection method is based on quantiles but permits retaining short tails. -A sample is considered an outlier if it is outside an interval computed as -(lo - range * slack, hi + range * slack) with lo and hi denoting -the limit and 1 - limit quantiles and range = hi - lo.

-
- -
-

Usage

- 
identify_vector_outliers_global(.input, .limit = 0.05, .slack = 0.1)
-
- -
-

Arguments

-
.input
-

Sample vector.

- - -
.limit
-

Quantile that separates inliers from outliers.

- - -
.slack
-

Tolerated distance from limit quantile.

- -
-
-

Value

- - -

Boolean vector of outlier flags.

-
-
-

See also

-

identify_vector_outliers_window()

-
- -
-

Examples

- 
# An outlier gets flagged.
-identify_vector_outliers_global (c (1:10, 100))
-#>  [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
-
-# No outlier gets flagged with short tails.
-identify_vector_outliers_global (1:10)
-#>  [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
-
-
-
-
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/identify_vector_outliers_window.html b/docs/reference/identify_vector_outliers_window.html deleted file mode 100644 index ec45ee2..0000000 --- a/docs/reference/identify_vector_outliers_window.html +++ /dev/null @@ -1,123 +0,0 @@ - -Compute outlier flags using sliding window. — identify_vector_outliers_window • rren - Skip to contents - - -
-
-
-

Compute outlier flags using sliding window.

- Source: R/filter.R -
identify_vector_outliers_window.Rd
-
- -
-

Same as identify_vector_outliers_global() except the quantile computation is performed -in a sliding window centered on each sample. Currently the computation is not -really efficient and runs in O (n*w*log (w)) for window size w.

-
- -
-

Usage

- 
identify_vector_outliers_window(
-  .input,
-  .window = 333,
-  .limit = 0.05,
-  .slack = 0.1
-)
-
- -
-

Arguments

-
.input
-

Sample vector.

- - -
.window
-

Window size in samples.

- - -
.limit
-

Quantile that separates inliers from outliers.

- - -
.slack
-

Tolerated distance from limit quantile.

- -
-
-

Value

- - -

Boolean vector of outlier flags.

-
-
-

See also

-

identify_vector_outliers_global()

-
- -
-

Examples

- 
# A sample of 100 is considered an outlier when near
-# different values but not when near similar values.
-identify_vector_outliers_window (c (100, 15:25, 95:105, 100), .window = 10)
-#>  [1]  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
-#> [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
-
-
-
-
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/index.html b/docs/reference/index.html deleted file mode 100644 index b331d4d..0000000 --- a/docs/reference/index.html +++ /dev/null @@ -1,222 +0,0 @@ - -Function reference • rren - Skip to contents - - -
-
-
-

Function reference

-
- -
-

Loading results

- - - - -
- - - - -
- - load_file_json() -
-
Load data from given file.
-
- - load_path_json() -
-
Load data from given path recursively.
-
- - assert_renaissance() -
-
Check whether data resembles typical measurement results.
-
- - check_renaissance() -
-
Check whether data resembles typical measurement results.
-
- - expect_renaissance() -
-
Check whether data resembles typical measurement results.
-
-

Filtering results

- - - - -
- - - - -
- - identify_vector_outliers_global() -
-
Compute outlier flags.
-
- - identify_vector_outliers_window() -
-
Compute outlier flags using sliding window.
-
- - preserve_last_n() -
-
Preserve last samples in each run by count.
-
- - preserve_last_sec() -
-
Preserve last samples in each run by time.
-
- - list_outliers_global() -
-
List outliers.
-
- - list_outliers_window() -
-
List outliers using sliding window.
-
- - remove_outliers_global() -
-
Remove outliers.
-
- - remove_outliers_window() -
-
Remove outliers using sliding window.
-
-

Analyzing results

- - - - -
- - - - -
- - compute_trends() -
-
Compute trends.
-
- - compute_flat_percentile_cis() -
-
Compute flat percentile bootstrap confidence interval.
-
- - compute_flat_percentile_cis_group_helper() -
-
Group helper for flat percentile bootstrap confidence interval.
-
- - locate_vector_segments() -
-
Locate change point segments in samples.
-
- - list_dimensions() -
-
Get dimensions.
-
- - list_segment_boundaries() -
-
List segment boundaries.
-
- - list_regular_artifacts_by_interval() -
-
Identify regular occurrences based on intervals.
-
- - list_regular_artifacts_by_position() -
-
Identify regular occurrences based on position.
-
-

Miscellaneous functions

- - - - -
- - - - -
- - rren_example() -
-
Return full path to an example file.
-
- - rren_artificial() -
-
Return data frame with artificial data.
-
-
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/list_dimensions.html b/docs/reference/list_dimensions.html deleted file mode 100644 index f3f9192..0000000 --- a/docs/reference/list_dimensions.html +++ /dev/null @@ -1,86 +0,0 @@ - -Get dimensions. — list_dimensions • rren - Skip to contents - - -
-
-
-

Get dimensions.

- Source: R/regular.R -
list_dimensions.Rd
-
- -
-

Returns dimensions of the data, useful to compute relative frequencies in regular position identification.

-
- -
-

Usage

- 
list_dimensions(.input)
-
- -
-

Arguments

-
.input
-

Data.

- -
-
-

Value

- - -

Tibble with data dimensions.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/list_outliers_global.html b/docs/reference/list_outliers_global.html deleted file mode 100644 index d18fff3..0000000 --- a/docs/reference/list_outliers_global.html +++ /dev/null @@ -1,94 +0,0 @@ - -List outliers. — list_outliers_global • rren - Skip to contents - - -
-
-
-

List outliers.

- Source: R/filter.R -
list_outliers_global.Rd
-
- -
-

Uses identify_vector_outliers_global() to identify outliers in given column. Then, returns the list of outlier positions and intervals.

-
- -
-

Usage

- 
list_outliers_global(.input, .column, ...)
-
- -
-

Arguments

-
.input
-

Data.

- - -
.column
-

Column to identify outliers in.

- - -
...
-

Parameters to identify_vector_outliers_global().

- -
-
-

Value

- - -

Tibble with outlier list.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/list_outliers_group_helper.html b/docs/reference/list_outliers_group_helper.html deleted file mode 100644 index 4798fd7..0000000 --- a/docs/reference/list_outliers_group_helper.html +++ /dev/null @@ -1,102 +0,0 @@ - -Group helper for list outliers. — list_outliers_group_helper • rren - Skip to contents - - -
-
-
-

Group helper for list outliers.

- Source: R/filter.R -
list_outliers_group_helper.Rd
-
- -
-

Given the outlier flags, the index and the total time, -returns a list of outlier positions and intervals.

-
- -
-

Usage

- 
list_outliers_group_helper(.flags, .index, .total)
-
- -
-

Arguments

-
.flags
-

Outlier flags.

- - -
.index
-

Data index.

- - -
.total
-

Data total.

- -
-
-

Value

- - -

Tibble with outlier list.

-
-
-

Details

-

The computation assumes that an outlier impacts a single repetition, -the outlier interval is therefore the interval of that repetition.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/list_outliers_window.html b/docs/reference/list_outliers_window.html deleted file mode 100644 index e33da8e..0000000 --- a/docs/reference/list_outliers_window.html +++ /dev/null @@ -1,94 +0,0 @@ - -List outliers using sliding window. — list_outliers_window • rren - Skip to contents - - -
-
-
-

List outliers using sliding window.

- Source: R/filter.R -
list_outliers_window.Rd
-
- -
-

Uses identify_vector_outliers_window() to identify outliers in given column. Then, returns the list of outlier positions and intervals.

-
- -
-

Usage

- 
list_outliers_window(.input, .column, ...)
-
- -
-

Arguments

-
.input
-

Data.

- - -
.column
-

Column to identify outliers in.

- - -
...
-

Parameters to identify_vector_outliers_window().

- -
-
-

Value

- - -

Tibble with outlier list.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/list_regular_artifacts_by_interval.html b/docs/reference/list_regular_artifacts_by_interval.html deleted file mode 100644 index f7ca4e2..0000000 --- a/docs/reference/list_regular_artifacts_by_interval.html +++ /dev/null @@ -1,109 +0,0 @@ - -Identify regular occurrences based on intervals. — list_regular_artifacts_by_interval • rren - Skip to contents - - -
-
-
-

Identify regular occurrences based on intervals.

- Source: R/regular.R -
list_regular_artifacts_by_interval.Rd
-
- -
-

Identifies regular occurrences in a list of artifact positions and intervals. -An artifact is considered regular if it appears in the same interval -in certain minimum share of runs.

-
- -
-

Usage

- 
list_regular_artifacts_by_interval(
-  .artifacts,
-  .dimensions,
-  .min_share = 2/3,
-  .min_runs = 11
-)
-
- -
-

Arguments

-
.artifacts
-

Artifact positions and intervals.

- - -
.dimensions
-

Data dimensions to compute share from.

- - -
.min_share
-

Minimum share of runs to identify regular artifacts.

- - -
.min_runs
-

Minimum count of runs to compute share from.

- -
-
-

Value

- - -

Tibble with regular artifacts list.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/list_regular_artifacts_by_position.html b/docs/reference/list_regular_artifacts_by_position.html deleted file mode 100644 index 363d0f8..0000000 --- a/docs/reference/list_regular_artifacts_by_position.html +++ /dev/null @@ -1,109 +0,0 @@ - -Identify regular occurrences based on position. — list_regular_artifacts_by_position • rren - Skip to contents - - -
-
-
-

Identify regular occurrences based on position.

- Source: R/regular.R -
list_regular_artifacts_by_position.Rd
-
- -
-

Identifies regular occurrences in a list of artifact positions and intervals. -An artifact is considered regular if it appears in the same position -in certain minimum share of runs.

-
- -
-

Usage

- 
list_regular_artifacts_by_position(
-  .artifacts,
-  .dimensions,
-  .min_share = 2/3,
-  .min_runs = 11
-)
-
- -
-

Arguments

-
.artifacts
-

Artifact positions and intervals.

- - -
.dimensions
-

Data dimensions to compute share from.

- - -
.min_share
-

Minimum share of runs to identify regular artifacts.

- - -
.min_runs
-

Minimum count of runs to compute share from.

- -
-
-

Value

- - -

Tibble with regular artifacts list.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/list_segment_boundaries.html b/docs/reference/list_segment_boundaries.html deleted file mode 100644 index 7d4a918..0000000 --- a/docs/reference/list_segment_boundaries.html +++ /dev/null @@ -1,94 +0,0 @@ - -List segment boundaries. — list_segment_boundaries • rren - Skip to contents - - -
-
-
-

List segment boundaries.

- Source: R/change.R -
list_segment_boundaries.Rd
-
- -
-

Uses locate_vector_segments() to identify segments in given column. Then, returns the list of segment boundary positions and intervals.

-
- -
-

Usage

- 
list_segment_boundaries(.input, .column, ...)
-
- -
-

Arguments

-
.input
-

Data.

- - -
.column
-

Column to identify segments in.

- - -
...
-

Parameters to locate_vector_segments().

- -
-
-

Value

- - -

Tibble with segment boundary list.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/list_segment_boundaries_group_helper.html b/docs/reference/list_segment_boundaries_group_helper.html deleted file mode 100644 index 8bcb67e..0000000 --- a/docs/reference/list_segment_boundaries_group_helper.html +++ /dev/null @@ -1,105 +0,0 @@ - -Group helper for list segment boundaries. — list_segment_boundaries_group_helper • rren - Skip to contents - - -
-
-
-

Group helper for list segment boundaries.

- Source: R/change.R -
list_segment_boundaries_group_helper.Rd
-
- -
-

Given the segment positions, the index and the total time, -returns a list of segment boundary positions and intervals.

-
- -
-

Usage

- 
list_segment_boundaries_group_helper(.positions, .index, .total)
-
- -
-

Arguments

-
.positions
-

Segment positions.

- - -
.index
-

Data index.

- - -
.total
-

Data total.

- -
-
-

Value

- - -

Tibble with segment boundary list.

-
-
-

Details

-

The computation assumes that a segment boundary exists in either boundary repetition, -the boundary interval is therefore formed by the mid points of the two repetitions, -arguing that less than half of each boundary repetition is impacted -(otherwise segments would be assigned differently).

-

Head and tail boundaries are not included.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/load_file_json.html b/docs/reference/load_file_json.html deleted file mode 100644 index 8cb4f3b..0000000 --- a/docs/reference/load_file_json.html +++ /dev/null @@ -1,117 +0,0 @@ - -Load data from given file. — load_file_json • rren - Skip to contents - - -
-
-
-

Load data from given file.

- Source: R/load.R -
load_file_json.Rd
-
- -
-

Load data from given file.

-
- -
-

Usage

- 
load_file_json(data_file)
-
- -
-

Arguments

-
data_file
-

Data file to load from.

- -
-
-

Value

- - -

Tibble with loaded data.

-
-
-

Details

-

The basic timing columns are translated into canonical form:

  • time will contain individual repetition time in seconds

    • -

  • total will contain aggregate execution time at the end of repetition in seconds

    • -

  • index will contain the index of the measurement in the run starting from 1

    • -

Additional metadata is included as factor columns:

  • vm is a hash of all configuration metadata and can be used to distinguish incompatible measurement configurations

    • -

  • vm_name is the name of the virtual machine

    • -

  • vm_version is the version of the virtual machine

    • -

  • vm_configuration gives concatenated command line arguments

    • -

  • run is a unique identifier of the run

    • -

  • benchmark is the name of the benchmark

    • -
-
-

See also

-

load_path_json()

-
- -
-

Examples

- 
load_file_json (rren_example ('results-small-version-5.json'))
-#> # A tibble: 6 × 9
-#>   index  time total vm_name    vm_version vm_configuration run   vm    benchmark
-#>   <int> <dbl> <dbl> <fct>      <fct>      <fct>            <fct> <fct> <fct>    
-#> 1     1  5.41  10.4 OpenJDK 6… 17.0.3+7   ""               /hom… cec0… page-rank
-#> 2     2  2.45  14.9 OpenJDK 6… 17.0.3+7   ""               /hom… cec0… page-rank
-#> 3     3  2.33  18.5 OpenJDK 6… 17.0.3+7   ""               /hom… cec0… page-rank
-#> 4     1  7.80  30.3 OpenJDK 6… 17.0.3+7   ""               /hom… cec0… naive-ba…
-#> 5     2  1.43  31.7 OpenJDK 6… 17.0.3+7   ""               /hom… cec0… naive-ba…
-#> 6     3  1.28  33.0 OpenJDK 6… 17.0.3+7   ""               /hom… cec0… naive-ba…
-
-
-
-
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/load_path_json.html b/docs/reference/load_path_json.html deleted file mode 100644 index 8af4a07..0000000 --- a/docs/reference/load_path_json.html +++ /dev/null @@ -1,129 +0,0 @@ - -Load data from given path recursively. — load_path_json • rren - Skip to contents - - -
-
-
-

Load data from given path recursively.

- Source: R/load.R -
load_path_json.Rd
-
- -
-

Load data from given path recursively.

-
- -
-

Usage

- 
load_path_json(
-  data_path,
-  pattern = "\\.json(|\\.gz|\\.xz|\\.bz2)$",
-  cache = NULL
-)
-
- -
-

Arguments

-
data_path
-

Data path to load from.

- - -
pattern
-

Regular expression pattern to match.

- - -
cache
-

File name to use as data cache.

- -
-
-

Value

- - -

Tibble with loaded data.

-
-
-

See also

-

load_file_json()

-
- -
-

Examples

- 
load_path_json (rren_example (), pattern = '^results-small-version-[0-9]+\\.json$')
-#> # A tibble: 18 × 9
-#>    index  time total vm_name   vm_version vm_configuration run   vm    benchmark
-#>    <int> <dbl> <dbl> <fct>     <fct>      <fct>            <fct> <fct> <fct>    
-#>  1     1  7.56  7.56 OpenJDK … 25.332-b09 ""               /hom… 39b0… naive-ba…
-#>  2     2  5.47 13.0  OpenJDK … 25.332-b09 ""               /hom… 39b0… naive-ba…
-#>  3     3  5.20 18.2  OpenJDK … 25.332-b09 ""               /hom… 39b0… naive-ba…
-#>  4     1 19.2  19.2  OpenJDK … 25.332-b09 ""               /hom… 39b0… page-rank
-#>  5     2  2.76 21.9  OpenJDK … 25.332-b09 ""               /hom… 39b0… page-rank
-#>  6     3  2.77 24.7  OpenJDK … 25.332-b09 ""               /hom… 39b0… page-rank
-#>  7     1  7.91  7.91 OpenJDK … 25.332-b09 ""               /hom… 39b0… naive-ba…
-#>  8     2  5.75 13.7  OpenJDK … 25.332-b09 ""               /hom… 39b0… naive-ba…
-#>  9     3  5.51 19.2  OpenJDK … 25.332-b09 ""               /hom… 39b0… naive-ba…
-#> 10     1 21.7  21.7  OpenJDK … 25.332-b09 ""               /hom… 39b0… page-rank
-#> 11     2  2.97 24.7  OpenJDK … 25.332-b09 ""               /hom… 39b0… page-rank
-#> 12     3  2.88 27.6  OpenJDK … 25.332-b09 ""               /hom… 39b0… page-rank
-#> 13     1  5.41 10.4  OpenJDK … 17.0.3+7   ""               /hom… cec0… page-rank
-#> 14     2  2.45 14.9  OpenJDK … 17.0.3+7   ""               /hom… cec0… page-rank
-#> 15     3  2.33 18.5  OpenJDK … 17.0.3+7   ""               /hom… cec0… page-rank
-#> 16     1  7.80 30.3  OpenJDK … 17.0.3+7   ""               /hom… cec0… naive-ba…
-#> 17     2  1.43 31.7  OpenJDK … 17.0.3+7   ""               /hom… cec0… naive-ba…
-#> 18     3  1.28 33.0  OpenJDK … 17.0.3+7   ""               /hom… cec0… naive-ba…
-
-
-
-
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/locate_vector_segments.html b/docs/reference/locate_vector_segments.html deleted file mode 100644 index 0b1a525..0000000 --- a/docs/reference/locate_vector_segments.html +++ /dev/null @@ -1,97 +0,0 @@ - -Locate change point segments in samples. — locate_vector_segments • rren - Skip to contents - - -
-
-
-

Locate change point segments in samples.

- Source: R/change.R -
locate_vector_segments.Rd
-
- -
-

Treats samples as segments separated by change points. -Returns indices of the first sample of each segment.

-
- -
-

Usage

- 
locate_vector_segments(.input, .penalty)
-
- -
-

Arguments

-
.input
-

Measurement results to analyze.

- - -
.penalty
-

A numerical penalty or barrett for penalty computation from Barrett et al..

- -
-
-

Value

- - -

Vector of segment starting points.

-
-
-

Details

-

Relies on the PELT algorithm implementation in the changepoint::cpt.meanvar() function.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/preserve_last_n.html b/docs/reference/preserve_last_n.html deleted file mode 100644 index 02d15e0..0000000 --- a/docs/reference/preserve_last_n.html +++ /dev/null @@ -1,103 +0,0 @@ - -Preserve last samples in each run by count. — preserve_last_n • rren - Skip to contents - - -
-
-
-

Preserve last samples in each run by count.

- Source: R/filter.R -
preserve_last_n.Rd
-
- -
-

Useful for extracting a set of representative samples for each run, -assuming the last part of each run is the most representative. -Can specify a maximum share of samples that the function -preserves. Runs with fewer samples are removed entirely.

-
- -
-

Usage

- 
preserve_last_n(.input, .n, .max_share = 0.5)
-
- -
-

Arguments

-
.input
-

Measurement results to filter.

- - -
.n
-

How many samples taken from end to preserve.

- - -
.max_share
-

Maximum share of samples to preserve.

- -
-
-

Value

- - -

Filtered measurement results.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/preserve_last_sec.html b/docs/reference/preserve_last_sec.html deleted file mode 100644 index 64f3f87..0000000 --- a/docs/reference/preserve_last_sec.html +++ /dev/null @@ -1,112 +0,0 @@ - -Preserve last samples in each run by time. — preserve_last_sec • rren - Skip to contents - - -
-
-
-

Preserve last samples in each run by time.

- Source: R/filter.R -
preserve_last_sec.Rd
-
- -
-

Useful for extracting a set of representative samples for each run, -assuming the last part of each run is the most representative. -Can specify a maximum share of samples that the function -preserves. Runs with fewer samples are removed entirely.

-
- -
-

Usage

- 
preserve_last_sec(.input, .sec, .max_share = 0.5, .equal_count_per_run = FALSE)
-
- -
-

Arguments

-
.input
-

Measurement results to filter.

- - -
.sec
-

How old samples taken from end to preserve.

- - -
.max_share
-

Maximum share of samples to preserve.

- - -
.equal_count_per_run
-

Make sample count per run equal.

- -
-
-

Value

- - -

Filtered measurement results.

-
-
-

Details

-

When equal sample count per run is requested, -it is chosen to be the median sample count.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/remove_outliers_global.html b/docs/reference/remove_outliers_global.html deleted file mode 100644 index a5e41b3..0000000 --- a/docs/reference/remove_outliers_global.html +++ /dev/null @@ -1,94 +0,0 @@ - -Remove outliers. — remove_outliers_global • rren - Skip to contents - - -
-
-
-

Remove outliers.

- Source: R/filter.R -
remove_outliers_global.Rd
-
- -
-

Uses identify_vector_outliers_global() to identify outliers in given column. Then, removes the outlier rows.

-
- -
-

Usage

- 
remove_outliers_global(.input, .column, ...)
-
- -
-

Arguments

-
.input
-

Data.

- - -
.column
-

Column to identify outliers in.

- - -
...
-

Parameters to identify_vector_outliers_global().

- -
-
-

Value

- - -

Tibble with rows filtered.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/remove_outliers_window.html b/docs/reference/remove_outliers_window.html deleted file mode 100644 index 4789d3b..0000000 --- a/docs/reference/remove_outliers_window.html +++ /dev/null @@ -1,94 +0,0 @@ - -Remove outliers using sliding window. — remove_outliers_window • rren - Skip to contents - - -
-
-
-

Remove outliers using sliding window.

- Source: R/filter.R -
remove_outliers_window.Rd
-
- -
-

Uses identify_vector_outliers_window() to identify outliers in given column. Then, removes the outlier rows.

-
- -
-

Usage

- 
remove_outliers_window(.input, .column, ...)
-
- -
-

Arguments

-
.input
-

Data.

- - -
.column
-

Column to identify outliers in.

- - -
...
-

Parameters to identify_vector_outliers_window().

- -
-
-

Value

- - -

Tibble with rows filtered.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/rren-package.html b/docs/reference/rren-package.html deleted file mode 100644 index d3ec732..0000000 --- a/docs/reference/rren-package.html +++ /dev/null @@ -1,81 +0,0 @@ - -rren: Renaissance Benchmark Data Processing Package — rren-package • rren - Skip to contents - - -
-
-
-

rren: Renaissance Benchmark Data Processing Package

- Source: R/rren-package.R -
rren-package.Rd
-
- -
-

A utility package for processing the data produced by the Renaissance benchmark suite (https://renaissance.dev).

-
- - -
-

See also

-

Useful links:

-
-
-

Author

-

Maintainer: Petr Tuma petr.tuma@d3s.mff.cuni.cz (ORCID)

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/rren_artificial.html b/docs/reference/rren_artificial.html deleted file mode 100644 index 365079d..0000000 --- a/docs/reference/rren_artificial.html +++ /dev/null @@ -1,98 +0,0 @@ - -Return data frame with artificial data. — rren_artificial • rren - Skip to contents - - -
-
-
-

Return data frame with artificial data.

- Source: R/example.R -
rren_artificial.Rd
-
- -
-

Return data frame with artificial data.

-
- -
-

Usage

- 
rren_artificial(data, vm_count = 1L, run_count = 1L, benchmark_count = 1L)
-
- -
-

Arguments

-
data
-

Data to use.

- - -
vm_count
-

Count of VM combinations to generate.

- - -
run_count
-

Count of run combinations to generate.

- - -
benchmark_count
-

Count of benchmark combinations to generate.

- -
-
-

Value

- - -

data Frame with artificial data.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/reference/rren_example.html b/docs/reference/rren_example.html deleted file mode 100644 index 96730ab..0000000 --- a/docs/reference/rren_example.html +++ /dev/null @@ -1,86 +0,0 @@ - -Return full path to an example file. — rren_example • rren - Skip to contents - - -
-
-
-

Return full path to an example file.

- Source: R/example.R -
rren_example.Rd
-
- -
-

Return full path to an example file.

-
- -
-

Usage

- 
rren_example(file_name = "")
-
- -
-

Arguments

-
file_name
-

Example file name.

- -
-
-

Value

- - -

Example file full path.

-
- -
- - -
-

Developed by Petr Tuma.

-
- -
-

Site built with pkgdown 2.0.7.

-
- -
- - - - - - - diff --git a/docs/search.json b/docs/search.json deleted file mode 100644 index bb82a37..0000000 --- a/docs/search.json +++ /dev/null @@ -1 +0,0 @@ -[{"path":"/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"Apache License","title":"Apache License","text":"Version 2.0, January 2004 ","code":""},{"path":[]},{"path":"/LICENSE.html","id":"id_1-definitions","dir":"","previous_headings":"Terms and Conditions for use, reproduction, and distribution","what":"1. 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However, accepting obligations, may act behalf sole responsibility, behalf Contributor, agree indemnify, defend, hold Contributor harmless liability incurred , claims asserted , Contributor reason accepting warranty additional liability. END TERMS CONDITIONS","code":""},{"path":"/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Petr Tuma. Author, maintainer.","code":""},{"path":"/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Tuma P (2023). rren: Renaissance Benchmark Data Processing Package. https://renaissance.dev/utilities-r, https://github.com/renaissance-benchmarks/utilities-r.","code":"@Manual{, title = {rren: Renaissance Benchmark Data Processing Package}, author = {Petr Tuma}, year = {2023}, note = {https://renaissance.dev/utilities-r, https://github.com/renaissance-benchmarks/utilities-r}, }"},{"path":[]},{"path":"/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"Renaissance Benchmark Data Processing Package","text":"rren packages various functions useful processing measurements collected using Renaissance Benchmark Suite.","code":""},{"path":"/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"Renaissance Benchmark Data Processing Package","text":"Use load_file_json () load_path_json () load measurement data tibble. functions support multiple measurement data file versions normalize basic timing columns easier processing.","code":""},{"path":"/reference/assert_renaissance.html","id":null,"dir":"Reference","previous_headings":"","what":"Check whether data resembles typical measurement results. — assert_renaissance","title":"Check whether data resembles typical measurement results. — assert_renaissance","text":"Check whether data resembles typical measurement results.","code":""},{"path":"/reference/assert_renaissance.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check whether data resembles typical measurement results. — assert_renaissance","text":"","code":"assert_renaissance(.input, .var.name = vname(.data), add = NULL, ...)"},{"path":"/reference/assert_renaissance.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check whether data resembles typical measurement results. — assert_renaissance","text":".input Measurement results test. .var.name Internal. add Internal. ... Parameters check_renaissance().","code":""},{"path":"/reference/assert_renaissance.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check whether data resembles typical measurement results. — assert_renaissance","text":"Invisible .data exception.","code":""},{"path":[]},{"path":"/reference/check_renaissance.html","id":null,"dir":"Reference","previous_headings":"","what":"Check whether data resembles typical measurement results. — check_renaissance","title":"Check whether data resembles typical measurement results. — check_renaissance","text":"Check whether data resembles typical measurement results.","code":""},{"path":"/reference/check_renaissance.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check whether data resembles typical measurement results. — check_renaissance","text":"","code":"check_renaissance( .input, .check_index = TRUE, .check_total = TRUE, .check_metadata = TRUE )"},{"path":"/reference/check_renaissance.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check whether data resembles typical measurement results. — check_renaissance","text":".input Measurement results test. .check_index Check presence index. .check_total Check presence total. .check_metadata Check presence descriptive metadata columns.","code":""},{"path":"/reference/check_renaissance.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check whether data resembles typical measurement results. — check_renaissance","text":"Error message TRUE.","code":""},{"path":"/reference/compute_flat_percentile_cis.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute flat percentile bootstrap confidence interval. — compute_flat_percentile_cis","title":"Compute flat percentile bootstrap confidence interval. — compute_flat_percentile_cis","text":"Uses bootstrap compute percentile confidence interval data summarized across runs.","code":""},{"path":"/reference/compute_flat_percentile_cis.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute flat percentile bootstrap confidence interval. — compute_flat_percentile_cis","text":"","code":"compute_flat_percentile_cis( .input, .column, .statistic = mean, .confidence = 0.99, .R = 10000 )"},{"path":"/reference/compute_flat_percentile_cis.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute flat percentile bootstrap confidence interval. — compute_flat_percentile_cis","text":".input Data summarized across runs. .column Column compute confidence interval . .statistic Statistic compute confidence interval . .confidence Confidence level. .R Replicates.","code":""},{"path":"/reference/compute_flat_percentile_cis.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute flat percentile bootstrap confidence interval. — compute_flat_percentile_cis","text":"Summarized tibble confidence interval columns.","code":""},{"path":"/reference/compute_flat_percentile_cis_group_helper.html","id":null,"dir":"Reference","previous_headings":"","what":"Group helper for flat percentile bootstrap confidence interval. — compute_flat_percentile_cis_group_helper","title":"Group helper for flat percentile bootstrap confidence interval. — compute_flat_percentile_cis_group_helper","text":"Group helper flat percentile bootstrap confidence interval.","code":""},{"path":"/reference/compute_flat_percentile_cis_group_helper.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Group helper for flat percentile bootstrap confidence interval. — compute_flat_percentile_cis_group_helper","text":"","code":"compute_flat_percentile_cis_group_helper(.input, .statistic, .confidence, .R)"},{"path":"/reference/compute_flat_percentile_cis_group_helper.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Group helper for flat percentile bootstrap confidence interval. — compute_flat_percentile_cis_group_helper","text":".input Data compute confidence interval . .statistic Statistic compute confidence interval . .confidence Confidence level. .R Number replicates.","code":""},{"path":"/reference/compute_flat_percentile_cis_group_helper.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Group helper for flat percentile bootstrap confidence interval. — compute_flat_percentile_cis_group_helper","text":"Tibble confidence interval.","code":""},{"path":"/reference/compute_trends.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute trends. — compute_trends","title":"Compute trends. — compute_trends","text":"Uses linear least squares regression compute trend run.","code":""},{"path":"/reference/compute_trends.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute trends. — compute_trends","text":"","code":"compute_trends(.input, .column)"},{"path":"/reference/compute_trends.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute trends. — compute_trends","text":".input Data. .column Column compute trend .","code":""},{"path":"/reference/compute_trends.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute trends. — compute_trends","text":"Summarized tibble trends column.","code":""},{"path":"/reference/expect_renaissance.html","id":null,"dir":"Reference","previous_headings":"","what":"Check whether data resembles typical measurement results. — expect_renaissance","title":"Check whether data resembles typical measurement results. — expect_renaissance","text":"Check whether data resembles typical measurement results.","code":""},{"path":"/reference/expect_renaissance.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check whether data resembles typical measurement results. — expect_renaissance","text":"","code":"expect_renaissance(.input, info = NULL, label = vname(.data), ...)"},{"path":"/reference/expect_renaissance.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check whether data resembles typical measurement results. — expect_renaissance","text":".input Measurement results test. info Internal. label Internal. ... Parameters check_renaissance().","code":""},{"path":"/reference/expect_renaissance.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check whether data resembles typical measurement results. — expect_renaissance","text":"expectation.","code":""},{"path":[]},{"path":"/reference/identify_vector_outliers_global.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute outlier flags. — identify_vector_outliers_global","title":"Compute outlier flags. — identify_vector_outliers_global","text":"outlier detection method based quantiles permits retaining short tails. sample considered outlier outside interval computed (lo - range * slack, hi + range * slack) lo hi denoting limit 1 - limit quantiles range = hi - lo.","code":""},{"path":"/reference/identify_vector_outliers_global.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute outlier flags. — identify_vector_outliers_global","text":"","code":"identify_vector_outliers_global(.input, .limit = 0.05, .slack = 0.1)"},{"path":"/reference/identify_vector_outliers_global.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute outlier flags. — identify_vector_outliers_global","text":".input Sample vector. .limit Quantile separates inliers outliers. .slack Tolerated distance limit quantile.","code":""},{"path":"/reference/identify_vector_outliers_global.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute outlier flags. — identify_vector_outliers_global","text":"Boolean vector outlier flags.","code":""},{"path":[]},{"path":"/reference/identify_vector_outliers_global.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute outlier flags. — identify_vector_outliers_global","text":"","code":"# An outlier gets flagged. identify_vector_outliers_global (c (1:10, 100)) #> [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE # No outlier gets flagged with short tails. identify_vector_outliers_global (1:10) #> [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE"},{"path":"/reference/identify_vector_outliers_window.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute outlier flags using sliding window. — identify_vector_outliers_window","title":"Compute outlier flags using sliding window. — identify_vector_outliers_window","text":"identify_vector_outliers_global() except quantile computation performed sliding window centered sample. Currently computation really efficient runs O (n*w*log (w)) window size w.","code":""},{"path":"/reference/identify_vector_outliers_window.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute outlier flags using sliding window. — identify_vector_outliers_window","text":"","code":"identify_vector_outliers_window( .input, .window = 333, .limit = 0.05, .slack = 0.1 )"},{"path":"/reference/identify_vector_outliers_window.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute outlier flags using sliding window. — identify_vector_outliers_window","text":".input Sample vector. .window Window size samples. .limit Quantile separates inliers outliers. .slack Tolerated distance limit quantile.","code":""},{"path":"/reference/identify_vector_outliers_window.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute outlier flags using sliding window. — identify_vector_outliers_window","text":"Boolean vector outlier flags.","code":""},{"path":[]},{"path":"/reference/identify_vector_outliers_window.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute outlier flags using sliding window. — identify_vector_outliers_window","text":"","code":"# A sample of 100 is considered an outlier when near # different values but not when near similar values. identify_vector_outliers_window (c (100, 15:25, 95:105, 100), .window = 10) #> [1] TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE #> [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE"},{"path":"/reference/list_dimensions.html","id":null,"dir":"Reference","previous_headings":"","what":"Get dimensions. — list_dimensions","title":"Get dimensions. — list_dimensions","text":"Returns dimensions data, useful compute relative frequencies regular position identification.","code":""},{"path":"/reference/list_dimensions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get dimensions. — list_dimensions","text":"","code":"list_dimensions(.input)"},{"path":"/reference/list_dimensions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get dimensions. — list_dimensions","text":".input Data.","code":""},{"path":"/reference/list_dimensions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get dimensions. — list_dimensions","text":"Tibble data dimensions.","code":""},{"path":"/reference/list_outliers_global.html","id":null,"dir":"Reference","previous_headings":"","what":"List outliers. — list_outliers_global","title":"List outliers. — list_outliers_global","text":"Uses identify_vector_outliers_global() identify outliers given column. , returns list outlier positions intervals.","code":""},{"path":"/reference/list_outliers_global.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List outliers. — list_outliers_global","text":"","code":"list_outliers_global(.input, .column, ...)"},{"path":"/reference/list_outliers_global.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"List outliers. — list_outliers_global","text":".input Data. .column Column identify outliers . ... Parameters identify_vector_outliers_global().","code":""},{"path":"/reference/list_outliers_global.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"List outliers. — list_outliers_global","text":"Tibble outlier list.","code":""},{"path":"/reference/list_outliers_group_helper.html","id":null,"dir":"Reference","previous_headings":"","what":"Group helper for list outliers. — list_outliers_group_helper","title":"Group helper for list outliers. — list_outliers_group_helper","text":"Given outlier flags, index total time, returns list outlier positions intervals.","code":""},{"path":"/reference/list_outliers_group_helper.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Group helper for list outliers. — list_outliers_group_helper","text":"","code":"list_outliers_group_helper(.flags, .index, .total)"},{"path":"/reference/list_outliers_group_helper.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Group helper for list outliers. — list_outliers_group_helper","text":".flags Outlier flags. .index Data index. .total Data total.","code":""},{"path":"/reference/list_outliers_group_helper.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Group helper for list outliers. — list_outliers_group_helper","text":"Tibble outlier list.","code":""},{"path":"/reference/list_outliers_group_helper.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Group helper for list outliers. — list_outliers_group_helper","text":"computation assumes outlier impacts single repetition, outlier interval therefore interval repetition.","code":""},{"path":"/reference/list_outliers_window.html","id":null,"dir":"Reference","previous_headings":"","what":"List outliers using sliding window. — list_outliers_window","title":"List outliers using sliding window. — list_outliers_window","text":"Uses identify_vector_outliers_window() identify outliers given column. , returns list outlier positions intervals.","code":""},{"path":"/reference/list_outliers_window.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List outliers using sliding window. — list_outliers_window","text":"","code":"list_outliers_window(.input, .column, ...)"},{"path":"/reference/list_outliers_window.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"List outliers using sliding window. — list_outliers_window","text":".input Data. .column Column identify outliers . ... Parameters identify_vector_outliers_window().","code":""},{"path":"/reference/list_outliers_window.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"List outliers using sliding window. — list_outliers_window","text":"Tibble outlier list.","code":""},{"path":"/reference/list_regular_artifacts_by_interval.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify regular occurrences based on intervals. — list_regular_artifacts_by_interval","title":"Identify regular occurrences based on intervals. — list_regular_artifacts_by_interval","text":"Identifies regular occurrences list artifact positions intervals. artifact considered regular appears interval certain minimum share runs.","code":""},{"path":"/reference/list_regular_artifacts_by_interval.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify regular occurrences based on intervals. — list_regular_artifacts_by_interval","text":"","code":"list_regular_artifacts_by_interval( .artifacts, .dimensions, .min_share = 2/3, .min_runs = 11 )"},{"path":"/reference/list_regular_artifacts_by_interval.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify regular occurrences based on intervals. — list_regular_artifacts_by_interval","text":".artifacts Artifact positions intervals. .dimensions Data dimensions compute share . .min_share Minimum share runs identify regular artifacts. .min_runs Minimum count runs compute share .","code":""},{"path":"/reference/list_regular_artifacts_by_interval.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify regular occurrences based on intervals. — list_regular_artifacts_by_interval","text":"Tibble regular artifacts list.","code":""},{"path":"/reference/list_regular_artifacts_by_position.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify regular occurrences based on position. — list_regular_artifacts_by_position","title":"Identify regular occurrences based on position. — list_regular_artifacts_by_position","text":"Identifies regular occurrences list artifact positions intervals. artifact considered regular appears position certain minimum share runs.","code":""},{"path":"/reference/list_regular_artifacts_by_position.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify regular occurrences based on position. — list_regular_artifacts_by_position","text":"","code":"list_regular_artifacts_by_position( .artifacts, .dimensions, .min_share = 2/3, .min_runs = 11 )"},{"path":"/reference/list_regular_artifacts_by_position.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify regular occurrences based on position. — list_regular_artifacts_by_position","text":".artifacts Artifact positions intervals. .dimensions Data dimensions compute share . .min_share Minimum share runs identify regular artifacts. .min_runs Minimum count runs compute share .","code":""},{"path":"/reference/list_regular_artifacts_by_position.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify regular occurrences based on position. — list_regular_artifacts_by_position","text":"Tibble regular artifacts list.","code":""},{"path":"/reference/list_segment_boundaries.html","id":null,"dir":"Reference","previous_headings":"","what":"List segment boundaries. — list_segment_boundaries","title":"List segment boundaries. — list_segment_boundaries","text":"Uses locate_vector_segments() identify segments given column. , returns list segment boundary positions intervals.","code":""},{"path":"/reference/list_segment_boundaries.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List segment boundaries. — list_segment_boundaries","text":"","code":"list_segment_boundaries(.input, .column, ...)"},{"path":"/reference/list_segment_boundaries.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"List segment boundaries. — list_segment_boundaries","text":".input Data. .column Column identify segments . ... Parameters locate_vector_segments().","code":""},{"path":"/reference/list_segment_boundaries.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"List segment boundaries. — list_segment_boundaries","text":"Tibble segment boundary list.","code":""},{"path":"/reference/list_segment_boundaries_group_helper.html","id":null,"dir":"Reference","previous_headings":"","what":"Group helper for list segment boundaries. — list_segment_boundaries_group_helper","title":"Group helper for list segment boundaries. — list_segment_boundaries_group_helper","text":"Given segment positions, index total time, returns list segment boundary positions intervals.","code":""},{"path":"/reference/list_segment_boundaries_group_helper.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Group helper for list segment boundaries. — list_segment_boundaries_group_helper","text":"","code":"list_segment_boundaries_group_helper(.positions, .index, .total)"},{"path":"/reference/list_segment_boundaries_group_helper.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Group helper for list segment boundaries. — list_segment_boundaries_group_helper","text":".positions Segment positions. .index Data index. .total Data total.","code":""},{"path":"/reference/list_segment_boundaries_group_helper.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Group helper for list segment boundaries. — list_segment_boundaries_group_helper","text":"Tibble segment boundary list.","code":""},{"path":"/reference/list_segment_boundaries_group_helper.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Group helper for list segment boundaries. — list_segment_boundaries_group_helper","text":"computation assumes segment boundary exists either boundary repetition, boundary interval therefore formed mid points two repetitions, arguing less half boundary repetition impacted (otherwise segments assigned differently). Head tail boundaries included.","code":""},{"path":"/reference/load_file_json.html","id":null,"dir":"Reference","previous_headings":"","what":"Load data from given file. — load_file_json","title":"Load data from given file. — load_file_json","text":"Load data given file.","code":""},{"path":"/reference/load_file_json.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load data from given file. — load_file_json","text":"","code":"load_file_json(data_file)"},{"path":"/reference/load_file_json.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load data from given file. — load_file_json","text":"data_file Data file load .","code":""},{"path":"/reference/load_file_json.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load data from given file. — load_file_json","text":"Tibble loaded data.","code":""},{"path":"/reference/load_file_json.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load data from given file. — load_file_json","text":"basic timing columns translated canonical form: time contain individual repetition time seconds total contain aggregate execution time end repetition seconds index contain index measurement run starting 1 Additional metadata included factor columns: vm hash configuration metadata can used distinguish incompatible measurement configurations vm_name name virtual machine vm_version version virtual machine vm_configuration gives concatenated command line arguments run unique identifier run benchmark name benchmark","code":""},{"path":[]},{"path":"/reference/load_file_json.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load data from given file. — load_file_json","text":"","code":"load_file_json (rren_example ('results-small-version-5.json')) #> # A tibble: 6 × 9 #> index time total vm_name vm_version vm_configuration run vm benchmark #> #> 1 1 5.41 10.4 OpenJDK 6… 17.0.3+7 \"\" /hom… cec0… page-rank #> 2 2 2.45 14.9 OpenJDK 6… 17.0.3+7 \"\" /hom… cec0… page-rank #> 3 3 2.33 18.5 OpenJDK 6… 17.0.3+7 \"\" /hom… cec0… page-rank #> 4 1 7.80 30.3 OpenJDK 6… 17.0.3+7 \"\" /hom… cec0… naive-ba… #> 5 2 1.43 31.7 OpenJDK 6… 17.0.3+7 \"\" /hom… cec0… naive-ba… #> 6 3 1.28 33.0 OpenJDK 6… 17.0.3+7 \"\" /hom… cec0… naive-ba…"},{"path":"/reference/load_path_json.html","id":null,"dir":"Reference","previous_headings":"","what":"Load data from given path recursively. — load_path_json","title":"Load data from given path recursively. — load_path_json","text":"Load data given path recursively.","code":""},{"path":"/reference/load_path_json.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load data from given path recursively. — load_path_json","text":"","code":"load_path_json( data_path, pattern = \"\\\\.json(|\\\\.gz|\\\\.xz|\\\\.bz2)$\", cache = NULL )"},{"path":"/reference/load_path_json.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load data from given path recursively. — load_path_json","text":"data_path Data path load . pattern Regular expression pattern match. cache File name use data cache.","code":""},{"path":"/reference/load_path_json.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load data from given path recursively. — load_path_json","text":"Tibble loaded data.","code":""},{"path":[]},{"path":"/reference/load_path_json.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load data from given path recursively. — load_path_json","text":"","code":"load_path_json (rren_example (), pattern = '^results-small-version-[0-9]+\\\\.json$') #> # A tibble: 18 × 9 #> index time total vm_name vm_version vm_configuration run vm benchmark #> #> 1 1 7.56 7.56 OpenJDK … 25.332-b09 \"\" /hom… 39b0… naive-ba… #> 2 2 5.47 13.0 OpenJDK … 25.332-b09 \"\" /hom… 39b0… naive-ba… #> 3 3 5.20 18.2 OpenJDK … 25.332-b09 \"\" /hom… 39b0… naive-ba… #> 4 1 19.2 19.2 OpenJDK … 25.332-b09 \"\" /hom… 39b0… page-rank #> 5 2 2.76 21.9 OpenJDK … 25.332-b09 \"\" /hom… 39b0… page-rank #> 6 3 2.77 24.7 OpenJDK … 25.332-b09 \"\" /hom… 39b0… page-rank #> 7 1 7.91 7.91 OpenJDK … 25.332-b09 \"\" /hom… 39b0… naive-ba… #> 8 2 5.75 13.7 OpenJDK … 25.332-b09 \"\" /hom… 39b0… naive-ba… #> 9 3 5.51 19.2 OpenJDK … 25.332-b09 \"\" /hom… 39b0… naive-ba… #> 10 1 21.7 21.7 OpenJDK … 25.332-b09 \"\" /hom… 39b0… page-rank #> 11 2 2.97 24.7 OpenJDK … 25.332-b09 \"\" /hom… 39b0… page-rank #> 12 3 2.88 27.6 OpenJDK … 25.332-b09 \"\" /hom… 39b0… page-rank #> 13 1 5.41 10.4 OpenJDK … 17.0.3+7 \"\" /hom… cec0… page-rank #> 14 2 2.45 14.9 OpenJDK … 17.0.3+7 \"\" /hom… cec0… page-rank #> 15 3 2.33 18.5 OpenJDK … 17.0.3+7 \"\" /hom… cec0… page-rank #> 16 1 7.80 30.3 OpenJDK … 17.0.3+7 \"\" /hom… cec0… naive-ba… #> 17 2 1.43 31.7 OpenJDK … 17.0.3+7 \"\" /hom… cec0… naive-ba… #> 18 3 1.28 33.0 OpenJDK … 17.0.3+7 \"\" /hom… cec0… naive-ba…"},{"path":"/reference/locate_vector_segments.html","id":null,"dir":"Reference","previous_headings":"","what":"Locate change point segments in samples. — locate_vector_segments","title":"Locate change point segments in samples. — locate_vector_segments","text":"Treats samples segments separated change points. Returns indices first sample segment.","code":""},{"path":"/reference/locate_vector_segments.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Locate change point segments in samples. — locate_vector_segments","text":"","code":"locate_vector_segments(.input, .penalty)"},{"path":"/reference/locate_vector_segments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Locate change point segments in samples. — locate_vector_segments","text":".input Measurement results analyze. .penalty numerical penalty barrett penalty computation Barrett et al..","code":""},{"path":"/reference/locate_vector_segments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Locate change point segments in samples. — locate_vector_segments","text":"Vector segment starting points.","code":""},{"path":"/reference/locate_vector_segments.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Locate change point segments in samples. — locate_vector_segments","text":"Relies PELT algorithm implementation changepoint::cpt.meanvar() function.","code":""},{"path":"/reference/preserve_last_n.html","id":null,"dir":"Reference","previous_headings":"","what":"Preserve last samples in each run by count. — preserve_last_n","title":"Preserve last samples in each run by count. — preserve_last_n","text":"Useful extracting set representative samples run, assuming last part run representative. Can specify maximum share samples function preserves. 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