update package description and readme

ropensci · Jan 14, 2021 · deffd9d · deffd9d
1 parent 7e54c52
commit deffd9d
Show file tree

Hide file tree

Showing 13 changed files with 67 additions and 65 deletions.
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -18,14 +18,14 @@ Authors@R:
              email = "[email protected]",
              comment = c(ORCID = "0000-0002-1944-3755"))
       )
-Description: Tools to import, clean, and visualize 
-    animal movement data from motion capture systems such as Optitrack's 
+Description: Tools to import, clean, and visualize movement data,
+    particularly from motion capture systems such as Optitrack's 
     Motive, the Straw Lab's Flydra, or from other sources. We provide 
     functions to remove artifacts, standardize tunnel position and tunnel 
     axes, select a region of interest, isolate specific trajectories, fill
     gaps in trajectory data, and calculate 3D and per-axis velocity. For 
     experiments of visual guidance, we also provide functions that use 
-    animal position to estimate perception of visual stimuli. 
+    subject position to estimate perception of visual stimuli. 
 Maintainer: Vikram B. Baliga <[email protected]>
 License: GPL-3
 Encoding: UTF-8

diff --git a/README.Rmd b/README.Rmd
@@ -22,15 +22,15 @@ knitr::opts_chunk$set(
 [![](https://badges.ropensci.org/409_status.svg)](https://github.com/ropensci/software-review/issues/409)
 <!-- badges: end -->
 
-`pathviewR` offers tools to import, clean, and visualize animal movement data
-from motion capture systems such as 
+`pathviewR` offers tools to import, clean, and visualize movement data,
+particularly from motion capture systems such as 
 [Optitrack's Motive](https://optitrack.com/software/motive/), the 
-[Straw Lab's Flydra](https://github.com/strawlab/flydra), 
-or other sources. We provide functions to remove artifacts, standardize
-tunnel position and tunnel axes, select a region of interest, isolate specific
-trajectories, fill gaps in trajectory data, and calculate 3D and per-axis
-velocity. For experiments of visual guidance, we also provide functions that 
-use animal position to estimate perception of visual stimuli.
+[Straw Lab's Flydra](https://github.com/strawlab/flydra), or other sources. We
+provide functions to remove artifacts, standardize tunnel position and tunnel
+axes, select a region of interest, isolate specific trajectories, fill gaps in
+trajectory data, and calculate 3D and per-axis velocity. For experiments of
+visual guidance, we also provide functions that use subject position to estimate
+perception of visual stimuli.
 
 ## Installation
 
@@ -43,7 +43,8 @@ devtools::install_github("vbaliga/pathviewR")
 ## Example
 
 #### Data import and cleaning via `pathviewR`
-We'll also load two `tidyverse` packages for wrangling & plotting.
+We'll also load two `tidyverse` packages for wrangling & plotting in this 
+readme.
 
 ```{r package_loading, message=FALSE, warning=FALSE}
 library(pathviewR)
@@ -55,7 +56,7 @@ library(magrittr)
 We will import and clean a sample data set from `.csv` files exported by
 [Optitrack's Motive](https://optitrack.com/software/motive/) software. For
 examples of how to import and clean other types of data, 
-[see the data import and cleaning vignette](https://vbaliga.github.io/pathviewR/articles/data-import-cleaning.html).
+[see the Basics of data import and cleaning vignette](https://vbaliga.github.io/pathviewR/articles/data-import-cleaning.html).
 
 ```{r import_motive}
 ## Import the Motive example data included in 
@@ -72,7 +73,7 @@ motive_data <-
 Several functions to clean and wrangle data are available, and we have a
 suggested pipeline for how these steps should be handled. For this example, we
 will use one of two "all-in-one" functions: `clean_viewr()`. 
-[See the Data Import and Cleaning vignette](https://vbaliga.github.io/pathviewR/articles/data-import-cleaning.html)
+[See the Basics of data import and cleaning vignette](https://vbaliga.github.io/pathviewR/articles/data-import-cleaning.html)
 for the full pipeline and the other "all-in-one" function.
 
 ```{r all_in_one, fig.height=3, fig.width=6, dpi=300}
@@ -118,14 +119,14 @@ str(motive_allinone)
 
 An important aspect of how `pathviewR` defines trajectories is by managing gaps
 in the data. 
-[See the Managing Frame Gaps vignette](https://vbaliga.github.io/pathviewR/articles/managing-frame-gaps.html)
+[See the vignette on Managing frame gaps](https://vbaliga.github.io/pathviewR/articles/managing-frame-gaps.html)
 for more information on trajectory definition and frame gaps.
 
 Now that the data is cleaned, `pathviewR` includes functions that estimate
 visual perceptions based on the distance between the subject/observer and visual
 stimuli on the walls of the experimental tunnel. For a complete description of
 these functions, 
-[see the Visual Perception Functions vignette](https://vbaliga.github.io/pathviewR/articles/visual-perception-functions.html).
+[see the vignette on Estimating visual perceptions from tracking data](https://vbaliga.github.io/pathviewR/articles/visual-perception-functions.html).
 
 
 #### Add more info about experiments
@@ -175,8 +176,7 @@ motive_V_sf <-
 
 Visualizing the calculations provides an more intuitive understanding of how
 these visual perceptions change as the subject moves throughout the tunnel.
-Please [see the Visual Perception Functions vignette](https://vbaliga.github.io/pathviewR/articles/visual-perception-functions.html) 
-for more examples of visualizing calculations.
+Please [see the vignette on Estimating visual perceptions from tracking data](https://vbaliga.github.io/pathviewR/articles/visual-perception-functions.html)  for more examples of visualizing calculations.
 
 ```{r motive_V_sf_pos, fig.height=3, fig.width=6, dpi=300}
 ggplot(motive_V_sf, aes(x = position_width, y = position_height)) +

diff --git a/README.md b/README.md
@@ -15,15 +15,15 @@ coverage](https://codecov.io/gh/vbaliga/pathviewR/graph/badge.svg)](https://code
 [![](https://badges.ropensci.org/409_status.svg)](https://github.com/ropensci/software-review/issues/409)
 <!-- badges: end -->
 
-`pathviewR` offers tools to import, clean, and visualize animal movement
-data from motion capture systems such as [Optitrack’s
+`pathviewR` offers tools to import, clean, and visualize movement data,
+particularly from motion capture systems such as [Optitrack’s
 Motive](https://optitrack.com/software/motive/), the [Straw Lab’s
 Flydra](https://github.com/strawlab/flydra), or other sources. We
 provide functions to remove artifacts, standardize tunnel position and
 tunnel axes, select a region of interest, isolate specific trajectories,
 fill gaps in trajectory data, and calculate 3D and per-axis velocity.
 For experiments of visual guidance, we also provide functions that use
-animal position to estimate perception of visual stimuli.
+subject position to estimate perception of visual stimuli.
 
 ## Installation
 
@@ -38,7 +38,8 @@ devtools::install_github("vbaliga/pathviewR")
 
 #### Data import and cleaning via `pathviewR`
 
-We’ll also load two `tidyverse` packages for wrangling & plotting.
+We’ll also load two `tidyverse` packages for wrangling & plotting in
+this readme.
 
 ``` r
 library(pathviewR)
@@ -49,7 +50,7 @@ library(magrittr)
 We will import and clean a sample data set from `.csv` files exported by
 [Optitrack’s Motive](https://optitrack.com/software/motive/) software.
 For examples of how to import and clean other types of data, [see the
-data import and cleaning
+Basics of data import and cleaning
 vignette](https://vbaliga.github.io/pathviewR/articles/data-import-cleaning.html).
 
 ``` r
@@ -66,7 +67,7 @@ motive_data <-
 Several functions to clean and wrangle data are available, and we have a
 suggested pipeline for how these steps should be handled. For this
 example, we will use one of two “all-in-one” functions: `clean_viewr()`.
-[See the Data Import and Cleaning
+[See the Basics of data import and cleaning
 vignette](https://vbaliga.github.io/pathviewR/articles/data-import-cleaning.html)
 for the full pipeline and the other “all-in-one” function.
 
@@ -139,7 +140,7 @@ str(motive_data)
 #>  - attr(*, ".internal.selfref")=<externalptr> 
 #>  - attr(*, "pathviewR_steps")= chr "viewr"
 #>  - attr(*, "file_id")= chr "pathviewR_motive_example_data.csv"
-#>  - attr(*, "file_mtime")= POSIXct[1:1], format: "2021-01-09 16:14:48"
+#>  - attr(*, "file_mtime")= POSIXct[1:1], format: "2021-01-14 11:04:23"
 #>  - attr(*, "frame_rate")= num 100
 #>  - attr(*, "header")='data.frame':   11 obs. of  2 variables:
 #>   ..$ metadata: chr [1:11] "Format Version" "Take Name" "Take Notes" "Capture Frame Rate" ...
@@ -182,7 +183,7 @@ str(motive_allinone)
 #>  $ end_length_sign  : num [1:449] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 ...
 #>  $ direction        : chr [1:449] "leftwards" "leftwards" "leftwards" "leftwards" ...
 #>  - attr(*, "file_id")= chr "pathviewR_motive_example_data.csv"
-#>  - attr(*, "file_mtime")= POSIXct[1:1], format: "2021-01-09 16:14:48"
+#>  - attr(*, "file_mtime")= POSIXct[1:1], format: "2021-01-14 11:04:23"
 #>  - attr(*, "frame_rate")= num 100
 #>  - attr(*, "header")='data.frame':   11 obs. of  2 variables:
 #>   ..$ metadata: chr [1:11] "Format Version" "Take Name" "Take Notes" "Capture Frame Rate" ...
@@ -213,16 +214,16 @@ str(motive_allinone)
 ```
 
 An important aspect of how `pathviewR` defines trajectories is by
-managing gaps in the data. [See the Managing Frame Gaps
-vignette](https://vbaliga.github.io/pathviewR/articles/managing-frame-gaps.html)
+managing gaps in the data. [See the vignette on Managing frame
+gaps](https://vbaliga.github.io/pathviewR/articles/managing-frame-gaps.html)
 for more information on trajectory definition and frame gaps.
 
 Now that the data is cleaned, `pathviewR` includes functions that
 estimate visual perceptions based on the distance between the
 subject/observer and visual stimuli on the walls of the experimental
-tunnel. For a complete description of these functions, [see the Visual
-Perception Functions
-vignette](https://vbaliga.github.io/pathviewR/articles/visual-perception-functions.html).
+tunnel. For a complete description of these functions, [see the vignette
+on Estimating visual perceptions from tracking
+data](https://vbaliga.github.io/pathviewR/articles/visual-perception-functions.html).
 
 #### Add more info about experiments
 
@@ -272,8 +273,9 @@ motive_V_sf <-
 
 Visualizing the calculations provides an more intuitive understanding of
 how these visual perceptions change as the subject moves throughout the
-tunnel. Please [see the Visual Perception Functions
-vignette](https://vbaliga.github.io/pathviewR/articles/visual-perception-functions.html)
+tunnel. Please [see the vignette on Estimating visual perceptions from
+tracking
+data](https://vbaliga.github.io/pathviewR/articles/visual-perception-functions.html)
 for more examples of visualizing calculations.
 
 ``` r

diff --git a/codemeta.json b/codemeta.json
@@ -5,7 +5,7 @@
   ],
   "@type": "SoftwareSourceCode",
   "identifier": "pathviewR",
-  "description": "Tools to import, clean, and visualize \n    animal movement data from motion capture systems such as Optitrack's \n    Motive, the Straw Lab's Flydra, or from other sources. We provide \n    functions to remove artifacts, standardize tunnel position and tunnel \n    axes, select a region of interest, isolate specific trajectories, fill\n    gaps in trajectory data, and calculate 3D and per-axis velocity. For \n    experiments of visual guidance, we also provide functions that use \n    animal position to estimate perception of visual stimuli. ",
+  "description": "Tools to import, clean, and visualize movement data,\n    particularly from motion capture systems such as Optitrack's \n    Motive, the Straw Lab's Flydra, or from other sources. We provide \n    functions to remove artifacts, standardize tunnel position and tunnel \n    axes, select a region of interest, isolate specific trajectories, fill\n    gaps in trajectory data, and calculate 3D and per-axis velocity. For \n    experiments of visual guidance, we also provide functions that use \n    subject position to estimate perception of visual stimuli. ",
   "name": "pathviewR: Wrangle, Analyze, and Visualize Animal Movement Data",
   "codeRepository": "https://github.com/vbaliga/pathviewR",
   "issueTracker": "https://github.com/vbaliga/pathviewR/issues",
@@ -258,7 +258,7 @@
     }
   ],
   "readme": "https://github.com/vbaliga/pathviewR/blob/master/README.md",
-  "fileSize": "11559.219KB",
+  "fileSize": "11558.996KB",
   "contIntegration": "https://codecov.io/gh/vbaliga/pathviewR?branch=master",
   "developmentStatus": "https://www.repostatus.org/#active",
   "citation": [

diff --git a/docs/articles/data-import-cleaning.html b/docs/articles/data-import-cleaning.html
diff --git a/docs/articles/managing-frame-gaps.html b/docs/articles/managing-frame-gaps.html
diff --git a/docs/articles/visual-perception-functions.html b/docs/articles/visual-perception-functions.html