synr

An R package for handling synesthesia consistency test data. Explore, validate and summarize data.

https://github.com/datalowe/synr

Science Score: 23.0%

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  • CITATION.cff file
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    Found 2 DOI reference(s) in README
  • Academic publication links
    Links to: ncbi.nlm.nih.gov
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    Low similarity (13.3%) to scientific vocabulary

Keywords

data-cleaning synesthesia
Last synced: 6 months ago · JSON representation

Repository

An R package for handling synesthesia consistency test data. Explore, validate and summarize data.

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  • Watchers: 1
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  • Open Issues: 1
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Topics
data-cleaning synesthesia
Created almost 6 years ago · Last pushed about 2 years ago
Metadata Files
Readme License

README.md

synr

Build Status

This is an R package for working with data resulting from grapheme-color synesthesia-related consistency tests. synr provides tools for exploring test data, including visualizing a single participant's data, and applying summarizing functions such as calculating color variation/consistency scores or classifying participant data as valid or invalid.

Installation

synr is available on CRAN, meaning you can simply:

r install.packages('synr')

Note that this will also install packages that synr depends on unless you already have them (dbscan, data.table and ggplot2).

Usage

Once data are in an appropriately formatted data frame/tibble ('long format' - see vignettes for more information), everything starts with rolling up participant data into a 'ParticipantGroup' object with create_participantgroup_widedata:

```r library(synr)

pgroup <- createparticipantgroup( formatteddf, # data frame/tibble to use, with data in 'long format' ntrialspergrapheme=3, # number of trials that grapheme was used for participantcolname="participantid", # name of column which holds participant ID's symbolcolname='symbol', # name of column which holds grapheme symbol strings colorcolname='color', # rname of column which holds response color HEX codes colorspacespec = "Luv" # color space to use for all calculations with participant group ) ```

Using the resulting object (pgroup), you can call various methods. A few examples follow.

Example group-level method: getmeanconsistency_scores

pgroup$get_mean_consistency_scores(symbol_filter=LETTERS) would return a vector of CIELUV-based consistency scores, using only data from trials involving capital letters.

Example group-level method: checkvalidgettwcvscores

pgroup$check_valid_get_twcv_scores(symbol_filter=0:9) would return a data frame which describes classifications of all participant data, where each data set is classified as 'invalid' or 'valid', based largely on DBSCAN clustering. This may be used to identify participants who varied their responses too little, e. g. by responding with an orange color on every trial.

Example participant-level method: get_plot

pgroup$participants[[1]]$get_plot(symbol_filter=LETTERS) would produce a bar plot of per-grapheme consistency scores for a single participant, using only data from trials involving capital letters. You can see an example below.

Example bar plot of grapheme-level consistency scores

Detailed usage information

More details on required data format and how to use the above functions and more can be found in the package's vignettes, some of which are also included in the package itself (run help(synr) to find them). Additional information is available in the following article:

Wilsson, L., van Leeuwen, T.M. & Neufeld, J. synr: An R package for handling synesthesia consistency test data. Behav Res 55, 4086–4098 (2023). https://doi.org/10.3758/s13428-022-02007-y

Feedback

If you have any suggestions on improvements you are very welcome to directly raise issues or commit code improvements to the github repository at https://github.com/datalowe/synr.

Owner

  • Name: Lowe Wilsson
  • Login: datalowe
  • Kind: user
  • Location: Stockholm, Sweden
  • Company: Karolinska Institutet

I do programming and data science. I use Python, R, JavaScript, PHP and Java, often with containerization.

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Last synced: over 2 years ago

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  • Total Commits: 88
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  • Avg Commits per committer: 44.0
  • Development Distribution Score (DDS): 0.011
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Name Email Commits
datalowe d****e@p****e 87
Working man w****n@L****l 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 8 months ago

All Time
  • Total issues: 14
  • Total pull requests: 10
  • Average time to close issues: 2 months
  • Average time to close pull requests: 27 minutes
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 0.64
  • Average comments per pull request: 0.4
  • Merged pull requests: 10
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
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  • Average time to close issues: N/A
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  • Average comments per issue: 0
  • Average comments per pull request: 0
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Top Authors
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  • datalowe (14)
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  • datalowe (11)
Top Labels
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enhancement (10) bug (1) question (1)
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Packages

  • Total packages: 1
  • Total downloads:
    • cran 296 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 3
  • Total maintainers: 1
cran.r-project.org: synr

Explore and Process Synesthesia Consistency Test Data

  • Versions: 3
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 296 Last month
Rankings
Forks count: 28.8%
Dependent packages count: 29.8%
Stargazers count: 35.2%
Dependent repos count: 35.5%
Average: 35.9%
Downloads: 50.4%
Maintainers (1)
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.6.0 depends
  • data.table >= 1.12 imports
  • dbscan >= 1.1 imports
  • ggplot2 >= 3.3.0 imports
  • methods >= 3.6 imports
  • dplyr >= 1.0.0 suggests
  • knitr * suggests
  • plotly * suggests
  • rmarkdown * suggests
  • testthat >= 2.1.0 suggests
  • tidyr * suggests