forked from containers/bootc
-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Merge pull request containers#456 from RishabhSaini/issue/4012
Improving the encapsulation (chunking) algorithm
- Loading branch information
Showing
11 changed files
with
745 additions
and
88 deletions.
There are no files selected for viewing
Large diffs are not rendered by default.
Oops, something went wrong.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Binary file not shown.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,109 @@ | ||
| //! This module holds implementations of some basic statistical properties, such as mean and standard deviation. | ||
| pub(crate) fn mean(data: &[u64]) -> Option<f64> { | ||
| if data.is_empty() { | ||
| None | ||
| } else { | ||
| Some(data.iter().sum::<u64>() as f64 / data.len() as f64) | ||
| } | ||
| } | ||
|
|
||
| pub(crate) fn std_deviation(data: &[u64]) -> Option<f64> { | ||
| match (mean(data), data.len()) { | ||
| (Some(data_mean), count) if count > 0 => { | ||
| let variance = data | ||
| .iter() | ||
| .map(|value| { | ||
| let diff = data_mean - (*value as f64); | ||
| diff * diff | ||
| }) | ||
| .sum::<f64>() | ||
| / count as f64; | ||
| Some(variance.sqrt()) | ||
| } | ||
| _ => None, | ||
| } | ||
| } | ||
|
|
||
| //Assumed sorted | ||
| pub(crate) fn median_absolute_deviation(data: &mut [u64]) -> Option<(f64, f64)> { | ||
| if data.is_empty() { | ||
| None | ||
| } else { | ||
| //Sort data | ||
| //data.sort_by(|a, b| a.partial_cmp(b).unwrap()); | ||
|
|
||
| //Find median of data | ||
| let median_data: f64 = match data.len() % 2 { | ||
| 1 => data[data.len() / 2] as f64, | ||
| _ => 0.5 * (data[data.len() / 2 - 1] + data[data.len() / 2]) as f64, | ||
| }; | ||
|
|
||
| //Absolute deviations | ||
| let mut absolute_deviations = Vec::new(); | ||
| for size in data { | ||
| absolute_deviations.push(f64::abs(*size as f64 - median_data)) | ||
| } | ||
|
|
||
| absolute_deviations.sort_by(|a, b| a.partial_cmp(b).unwrap()); | ||
| let l = absolute_deviations.len(); | ||
| let mad: f64 = match l % 2 { | ||
| 1 => absolute_deviations[l / 2], | ||
| _ => 0.5 * (absolute_deviations[l / 2 - 1] + absolute_deviations[l / 2]), | ||
| }; | ||
|
|
||
| Some((median_data, mad)) | ||
| } | ||
| } | ||
|
|
||
| #[test] | ||
| fn test_mean() { | ||
| assert_eq!(mean(&[]), None); | ||
| for v in [0u64, 1, 5, 100] { | ||
| assert_eq!(mean(&[v]), Some(v as f64)); | ||
| } | ||
| assert_eq!(mean(&[0, 1]), Some(0.5)); | ||
| assert_eq!(mean(&[0, 5, 100]), Some(35.0)); | ||
| assert_eq!(mean(&[7, 4, 30, 14]), Some(13.75)); | ||
| } | ||
|
|
||
| #[test] | ||
| fn test_std_deviation() { | ||
| assert_eq!(std_deviation(&[]), None); | ||
| for v in [0u64, 1, 5, 100] { | ||
| assert_eq!(std_deviation(&[v]), Some(0 as f64)); | ||
| } | ||
| assert_eq!(std_deviation(&[1, 4]), Some(1.5)); | ||
| assert_eq!(std_deviation(&[2, 2, 2, 2]), Some(0.0)); | ||
| assert_eq!( | ||
| std_deviation(&[1, 20, 300, 4000, 50000, 600000, 7000000, 80000000]), | ||
| Some(26193874.56387471) | ||
| ); | ||
| } | ||
|
|
||
| #[test] | ||
| fn test_median_absolute_deviation() { | ||
| //Assumes sorted | ||
| assert_eq!(median_absolute_deviation(&mut []), None); | ||
| for v in [0u64, 1, 5, 100] { | ||
| assert_eq!(median_absolute_deviation(&mut [v]), Some((v as f64, 0.0))); | ||
| } | ||
| assert_eq!(median_absolute_deviation(&mut [1, 4]), Some((2.5, 1.5))); | ||
| assert_eq!( | ||
| median_absolute_deviation(&mut [2, 2, 2, 2]), | ||
| Some((2.0, 0.0)) | ||
| ); | ||
| assert_eq!( | ||
| median_absolute_deviation(&mut [ | ||
| 1, 2, 3, 3, 4, 4, 4, 5, 5, 6, 6, 6, 7, 7, 7, 8, 9, 12, 52, 90 | ||
| ]), | ||
| Some((6.0, 2.0)) | ||
| ); | ||
|
|
||
| //if more than half of the data has the same value, MAD = 0, thus any | ||
| //value different from the residual median is classified as an outlier | ||
| assert_eq!( | ||
| median_absolute_deviation(&mut [0, 1, 1, 1, 1, 1, 1, 1, 0]), | ||
| Some((1.0, 0.0)) | ||
| ); | ||
| } |
Oops, something went wrong.