Linked plotly
display, global view of data and attribution space.
Source: R/2_visualization.r
global_view.Rd
from a cheem_ls() list, create a linked plotly
of the global data-
and attribution- spaces. Typically consumed directly by shiny app.
Usage
global_view(
cheem_ls,
primary_obs = NULL,
comparison_obs = NULL,
color = c("default", "residual", "log_maha.data", "cor_attr_proj.y"),
height_px = 480,
width_px = 1440,
as_ggplot = FALSE
)
Arguments
- cheem_ls
A return from
cheem_ls()
, a list of data frames.- primary_obs
The rownumber of the primary observation. Its local attribution becomes the 1d projection basis, and the point it highlighted as a dashed line. Defaults to NULL, no highlighting applied.
- comparison_obs
The rownumber of the comparison observation. Point is highlighted as a dotted line. Defaults to NULL, no highlighting applied.
- color
The name of the column in cheem_ls$global_view_df to map to color. Expects c("default", "residual", "log_maha.data", "cor_attr_proj.y"). Defaults to "default"; predicted_class for classification, dummy class for regression.
- height_px
The height in pixels of the returned
plotly
plot. Defaults to 480, does nothing whenas_ggplot
is TRUE.- width_px
The width in pixels of the returned
plotly
plot. Defaults to 1440, does nothing whenas_ggplot
is TRUE.- as_ggplot
Logical, if TRUE returns the plots before being passed to
plotly
functions.
Value
A plotly
plot, an interactive html widget of the global view,
first two components of the basis of the data- and attribution- spaces.
See also
Other cheem consumers:
global_view_legwork()
,
radial_cheem_tour()
,
run_app()
Examples
library(cheem)
## Regression setup:
dat <- amesHousing2018_NorthAmes
X <- dat[, 1:9]
Y <- dat$SalePrice
clas <- dat$SubclassMS
## global_view()
ames_rf_chm <- cheem_ls(X, Y, ames_rf_shap, ames_rf_pred, clas,
label = "North Ames, RF, SHAP")
if(interactive()){
global_view(ames_rf_chm, as_ggplot = TRUE) ## early return of ggplot
global_view(ames_rf_chm) ## uses ggplot facets %>% plotly
## Different color mappings, especially for regression
global_view(ames_rf_chm, color = "residual")
global_view(ames_rf_chm, color = "log_maha.data")
global_view(ames_rf_chm, color = "cor_attr_proj.y")
}
## Also consumed by: ?run_app()