| Version: | 1.0.0 |
| Title: | Multiset Intersection Generator |
| Date: | 2019-03-7 |
| Author: | Ivan Tomic  [aut,
cre, cph],
Adriana Tomic
[aut, ctb] |
| Description: | Computes efficient data distributions from highly inconsistent datasets with many missing values using multi-set intersections. Based upon hash functions, 'mulset' can quickly identify intersections from very large matrices of input vectors across columns and rows and thus provides scalable solution for dealing with missing values. Tomic et al. (2019) <doi:10.1101/545186>. |
| Maintainer: | Ivan Tomic <info@ivantomic.com> |
| Packaged: | 2019-03-07 20:24:54 UTC; login |
| Imports: | gtools, digest, stats |
| Depends: | R (≥ 3.4.0) |
| URL: | https://github.com/LogIN-/mulset |
| BugReports: | https://github.com/LogIN-/mulset/issues |
| License: | EUPL (≥ 1.2) |
| Encoding: | UTF-8 |
| LazyLoad: | yes |
| LazyData: | yes |
| RoxygenNote: | 6.1.1.9000 |
| NeedsCompilation: | no |
| Repository: | CRAN |
| Date/Publication: | 2019-03-08 16:50:03 UTC |
A intersection function
Description
intersection() returns all intersections it found.
Usage
intersection(...)
Arguments
... |
Vector with master values to check and vector to compare values against |
Value
Character vector of all common attributes
Examples
input1 <- seq(50, 100, by=10)
input2 <- seq(70, 130, by=10)
intersection(input1, input2)
A mulset function
Description
mulset() returns all multi-set intersections
Usage
mulset(data, exclude = NULL, include = c("samples", "samples_count",
"datapoints"), maxIntersections = NULL, hashMethod = "md5")
Arguments
data |
Data frame containing your data |
exclude |
Vector containing one or more variable names from |
include |
List of attributes which will be shown in results. Possible values are: c("samples", "samples_count", "datapoints"). If parameter is set to NULL only c("features", "feature_count") will be returned. |
maxIntersections |
Maximum number of unique datasets to generate, if NULL all datasets will be generated |
hashMethod |
Hashing method to use for unique sets identification. Available choices: md5(default), sha1, crc32, sha256, sha512, xxhash32, xxhash64, murmur32 |
Details
This function allows you to generate specific type of multi-set intersections. It searches for multi set intersections between rows and column identifiers. If no NA values are present only 1 dataset is returned as expected.
Value
If any intersections are found it returns a list that contains all available multi-set intersections You can convert this to data-frame following example provided or use it as it is.
Examples
data(mulsetDemo)
print(head(mulsetDemo))
resamples <- mulset(mulsetDemo, exclude = c("outcome", "age", "gender"), maxIntersections = 250)
## Loop through returned list or convert it to data-frame
## resamplesFrame <- as.data.frame(t(sapply(resamples,c)))
Demo data set from mulset package. This data is used in this package examples. It consist of 4x4 feature matrix + additional dummy columns that can be used for testing.
Description
Demo data set from mulset package. This data is used in this package examples. It consist of 4x4 feature matrix + additional dummy columns that can be used for testing.
Usage
data(mulsetDemo)
Format
An object of class data.frame with 4 rows and 7 columns.
Examples
data(mulsetDemo)
print(head(mulsetDemo))
resamples <- mulset(mulsetDemo, exclude = c("outcome", "age", "gender"))