slimming down vignette .RData

docs/pkgdown.yml

@@ -7,7 +7,7 @@ articles:
   apis: apis.html
   audio-data-concepts: audio-data-concepts.html
   introduction: introduction.html
-last_built: 2023-10-12T19:44Z
+last_built: 2023-10-16T19:41Z
 urls:
   reference: https://abbiodiversity.github.io/wildRtrax/reference
   article: https://abbiodiversity.github.io/wildRtrax/articles

vignettes/acoustic-data-wrangling.Rmd

@@ -20,7 +20,7 @@ knitr::opts_chunk$set(
   comment = '#>'
 )
 
-load("book.RData")
+load("package.RData")
 ```
 
 ```{r setup, echo=FALSE, include=FALSE, eval=TRUE}
@@ -33,7 +33,7 @@ library(tidyverse)
 # Start by getting everything you need
 Sys.setenv(WT_USERNAME = 'guest', WT_PASSWORD = 'Apple123')
 wt_auth()
-my_report <- wt_download_report(project_id = 379, sensor_id = 'ARU', reports = "main", weather_cols = F) %>%
+my_report <- wt_download_report(project_id = 605, sensor_id = 'ARU', reports = "main", weather_cols = F) %>%
   tibble::as_tibble()
 ```
 

vignettes/acoustic-pre-processing.Rmd

@@ -25,7 +25,7 @@ library(wildRtrax)
 library(tidyverse)
 
 # Set the directory path
-load("book.RData")
+load("package.RData")
 #save.image("book.RData")
 
 ```
@@ -156,6 +156,8 @@ wt_kaleidoscope_tags(
   tz, 
   freq_bump = T) # Add a frequency buffer to the tag, e.g. 20000 kHz
 
+songscope_tags
+
 ```
 
 If you've already uploaded recordings to WildTrax, scan your media using `wt_audio_scanner()` and a relative folder path.

vignettes/apis.Rmd

@@ -57,12 +57,12 @@ Using the project_id number in the download summary you can then use `wt_downloa
 
 ```{r echo=TRUE, include=TRUE, eval=F, warning = FALSE, message = FALSE}
 # Download the project report
-my_report <- wt_download_report(project_id = 379, sensor_id = 'ARU', reports = "main", weather_cols = F) %>%
+my_report <- wt_download_report(project_id = 605, sensor_id = 'ARU', reports = "main", weather_cols = F) %>%
   tibble::as_tibble()
 ```
 ```{r echo=F, include=F, eval=T, warning = FALSE, message = FALSE}
 # Download the project report
-my_report <- wt_download_report(project_id = 379, sensor_id = 'ARU', reports = "main", weather_cols = F) %>%
+my_report <- wt_download_report(project_id = 605, sensor_id = 'ARU', reports = "main", weather_cols = F) %>%
   tibble::as_tibble()
 ```
 ```{r}
@@ -100,11 +100,11 @@ WildTrax also pre-formats ARU to point count (PC) data depending on the type of
 
 ```{r, echo=T, include=T, eval=F, warning=F, message = FALSE}
 # As point count format
-aru_as_aru <- wt_download_report(project_id = 379 , sensor_id = 'ARU', reports = "main", weather_cols = F)
+aru_as_aru <- wt_download_report(project_id = 605 , sensor_id = 'ARU', reports = "main", weather_cols = F)
 ```
 ```{r, echo=F, include=F, eval=T, warning=F, message = FALSE}
 # As point count format
-aru_as_aru <- wt_download_report(project_id = 379, sensor_id = 'ARU', reports = "main", weather_cols = F)
+aru_as_aru <- wt_download_report(project_id = 605, sensor_id = 'ARU', reports = "main", weather_cols = F)
 ```
 ```{r}
 # As point count format
@@ -113,11 +113,11 @@ head(aru_as_aru)
 ```
 ```{r, echo=T, include=T, eval=F, warning=F, message = FALSE}
 # As ARU format
-aru_as_pc <- wt_download_report(project_id = 379, sensor_id = 'PC', reports = "main", weather_cols = F)
+aru_as_pc <- wt_download_report(project_id = 605, sensor_id = 'PC', reports = "main", weather_cols = F)
 ```
 ```{r, echo=F, include=F, eval=T, warning=F, message = FALSE}
 # As ARU format
-aru_as_pc <- wt_download_report(project_id = 379, sensor_id = 'PC', reports = "main", weather_cols = F)
+aru_as_pc <- wt_download_report(project_id = 605, sensor_id = 'PC', reports = "main", weather_cols = F)
 ```
 ```{r}
 # As point count format