Fixing readme and vignettes

README.md

@@ -68,16 +68,16 @@ default_template_directory()
 
 **N27** template folder resides inside of this directory.
 
-Let's view this subject using the `freesurfer_brain2` function.
+Let's view this subject using the `threeBrain` function.
 
 1. Import subject
 ```r
 library(threeBrain)
 
 n27_path <- file.path(default_template_directory(), "N27")
 
-x <- freesurfer_brain2( fs_subject_folder = n27_path,
-  subject_name = 'N27', surface_types = 'pial')
+x <- threeBrain( path = n27_path,
+  subject_code = 'N27', surface_types = 'pial')
 ```
 2. Visualize
 ```r
@@ -86,7 +86,7 @@ plot(x)       # alternatively, you can use x$plot()`
 
 ## C. Subject Setup
 
-The sample subject (`N27`) is a sample generated by `FreeSurfer` ([download](https://surfer.nmr.mgh.harvard.edu/fswiki/DownloadAndInstall)). If you have any subjects processed by `FreeSurfer`, use function `freesurfer_brain2` to visualize. 
+The sample subject (`N27`) is a sample generated by `FreeSurfer` ([download](https://surfer.nmr.mgh.harvard.edu/fswiki/DownloadAndInstall)). If you have any subjects processed by `FreeSurfer`, use function `threeBrain` to visualize. 
 
 ## D. Add/Render Electrodes
 

vignettes/A-getting-started.Rmd

@@ -41,11 +41,11 @@ In the following context, I will use `~/Downloads/N27` as an example
 
 ## Generate Viewer Object
 
-```{r setup}
+```{r setup, eval=FALSE}
 library(threeBrain)
 subject_code <- "N27"
 subject_path <- "~/Downloads/N27"
-brain <- freesurfer_brain2(subject_path, subject_code)
+brain <- threeBrain(subject_path, subject_code)
 print(brain)
 #> Subject - N27 
 #> Transforms:
@@ -93,7 +93,7 @@ If this is the first time, it might take a while to import and generate cache fi
 
 Visualizing the viewer is simply just one line.
 
-```{r}
+```{r, eval=FALSE}
 brain$plot()
 ```
 
@@ -126,8 +126,8 @@ The atlas type can be selected from `aparc+aseg`, `aparc.a2009s+aseg`, `aparc.DK
 
 The following example loads `pial` and `smoothwm`, with `aseg` as atlas. The viewer shows 'Coronal' plane, smoothed white matter, 'Ventricle', and 'Cerebellum' all together in one scene.
 
-```{r}
-brain <- freesurfer_brain2(
+```{r, eval=FALSE}
+brain <- threeBrain(
   subject_path, subject_code, 
   surface_types = c('pial', 'smoothwm'), 
   atlas_types = 'aseg')

vignettes/B-data-visualization.Rmd

@@ -20,11 +20,11 @@ knitr::opts_chunk$set(
 
 This article uses `N27` sample files mentioned by the previous vignettes. If you are using this example, please execute the following R code to set up. Alternatively, you can substitute variables `subject_code` and `subject_path` accordingly.
 
-```{r setup}
+```{r setup, eval=FALSE}
 library(threeBrain)
 subject_code <- "N27"
 subject_path <- "~/Downloads/N27"
-brain <- freesurfer_brain2(subject_path, subject_code)
+brain <- threeBrain(subject_path, subject_code)
 ```
 
 ## Add Electrodes
@@ -38,7 +38,7 @@ If you have performed electrode localization (see the previous article) and expo
 
 For demonstration purposes, this [electrode table](https://raw.githubusercontent.com/dipterix/threeBrain-sample/master/vignettes/electrodes.csv) will be used. Please download this file and place it at `~/Downloads/N27/electrodes.csv`
 
-```{r}
+```{r, eval=FALSE}
 electrode_table <- `~/Downloads/N27/electrodes.csv`
 brain$set_electrodes(electrode_table)
 brain$plot()
@@ -83,7 +83,7 @@ The column names are case-sensitive, and should only contain letters, digits and
 
 Download sample value table from [here](https://github.com/dipterix/threeBrain-sample/blob/master/vignettes/values.csv) and save it to `~/Downloads/N27/values.csv`
 
-```{r}
+```{r, eval=FALSE}
 electrode_table <- `~/Downloads/N27/electrodes.csv`
 value_table <- `~/Downloads/N27/values.csv`
 brain$set_electrodes(electrode_table)
@@ -104,7 +104,7 @@ In the example above, the p-value legend shows the range is from `-0.5` to `0.5`
 
 In the following code, `value_ranges` is a named list of such value ranges. `"p_value"=c(0,1)` suggests that the `p_value` variable should range from 0 to 1. All other variables adopt the default ranges. `palettes` is a named list of color palettes. In this specific case, variable `pal` is a vector of 64 colors. `colorRampPalette` is a base-R function to interpolate colors. Please use `help("colorRampPalette")` to see the documentation.
 
-```{r}
+```{r, eval=FALSE}
 pal <- c(
   colorRampPalette(c("red", "#FFC6C6"))(8),
   colorRampPalette(c("#FFC6C6", "white"))(56)