Add spinner

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: INLAvaan
 Type: Package
 Title: Bayesian Structural Equation Modelling with INLA
-Version: 0.1.0.9012
+Version: 0.1.0.9013
 Authors@R: 
     c(person("Haziq", "Jamil", 
              email = "[email protected]",

R/21-rgeneric_cached.R

@@ -91,6 +91,8 @@ inla_sem_cached <- function(
     sd_z <- sqrt(exp(theta[idx_psi]))  # sd_z = sd_z ^ 2 (latent sd)
     lvrho <- theta_to_rho(theta[idx_lvrho])
 
+    if (!is.null(sp)) sp$spin()
+
     list(
       lambda = lambda,
       beta = beta,

R/30-inlavaan.R

@@ -565,11 +565,25 @@ inlavaan <- function(
 
       # >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
       if (target == "INLA") {
+
+        sp <- NULL
+        if (!verbose) {
+          current_cli.progress_show_after <- options("cli.progress_show_after")
+          options("cli.progress_show_after" = 0)
+          sp <- cli::make_spinner(
+            which = cli::get_spinner("bouncingBall"),
+            template = paste("{spin}", sample(cli_messages, 1)),
+            stream = "message",
+            static = "silent"
+          )
+        }
+
         jagtrans <- try(
           lav2inla(
             lavobject = LAV,
             lavdata = lavdata,
-            dp = dp
+            dp = dp,
+            sp = sp
             # inits = initsin
           )
         )
@@ -824,27 +838,7 @@ inlavaan <- function(
         res <- try(do.call(rjcall, rjarg))
       } else {
         # >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
-        # spinner <- cli::make_spinner(
-        #   # which = "simpleDotsScrolling",
-        #   template = paste(sample(cli_messages, 1), "{spin}")
-        # )
-        # spinner$spin()
-        #
-        # f <- future({
-        #   invisible({
-        #     sink(tempfile())  # Redirect output to a temporary file
-        #     require("INLA")
-        #     result <- do.call("inla", rjarg)
-        #     sink(NULL)
-        #     result
-        #   })
-        # }, seed = TRUE)
-        # while (!resolved(f)) {
-        #   Sys.sleep(0.1)  # Briefly pause to avoid hogging CPU
-        #   spinner$spin() # The spinner automatically updates
-        # }
-        # res <- value(f)
-        # spinner$finish()
+
         res <- do.call("inla", rjarg)
 
         # >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
@@ -1268,6 +1262,10 @@ inlavaan <- function(
   #   }
   # }
 
+  if (!verbose) {
+    options("cli.progress_show_after" = current_cli.progress_show_after)
+  }
+
   out
 }
 

R/40-lav_export_INLA.R

@@ -2,6 +2,7 @@ lav2inla <- function(
     lavobject,
     lavdata = NULL,
     dp = NULL,
+    sp = NULL,
     n.chains = 1,
     mcmcextra = "",
     inits = "prior",
@@ -1301,7 +1302,8 @@ lav2inla <- function(
     q = pta$nfac[[1]],
     init = inlastart,
     partable = partable,
-    theta_to_rho = theta_to_rho # utility function, see 10-utilities.R
+    theta_to_rho = theta_to_rho,  # utility function, see 10-utilities.R
+    sp = sp
     # safe_solve = safe_solve
     # optimize = TRUE
   )

inst/demo.R

@@ -7,17 +7,6 @@ true_model <- "
   eta1 =~ 1*y1 + 1.2*y2 + 1.5*y3
   eta2 =~ 1*y4 + 1.2*y5 + 1.5*y6
   eta2 ~~ 0.3*eta1
-
-  y1 ~~ 0.05*y4
-  y2 ~~ 0.05*y5
-  y3 ~~ 0.05*y6
-
-  y1 ~~ 0.1*y1
-  y2 ~~ 0.1*y2
-  y3 ~~ 0.1*y3
-  y4 ~~ 0.1*y4
-  y5 ~~ 0.1*y5
-  y6 ~~ 0.1*y6
 "
 dat <- lavaan::simulateData(true_model, sample.nobs = 1000)
 
@@ -29,7 +18,8 @@ mod <- "
   # y2 ~~ y5
   # y3 ~~ y6
 "
-fit <- isem(model = mod, data = dat, meanstructure = FALSE, verbose = TRUE); summary(fit)
+fit <- isem(model = mod, data = dat, meanstructure = FALSE, verbose = TRUE)
+summary(fit)
 
 # Political democracy SEM example ----------------------------------------------
 myModel <- '

inst/spinner.R

@@ -0,0 +1,49 @@
+# Spinner in INLAvaan ----------------------------------------------------------
+# devtools::install_github("haziqj/INLAvaan")
+library(INLAvaan)
+library(lavaan)
+
+myModel <- '
+  # latent variables
+  dem60 =~ y1 + y2 + y3 + y4
+  dem65 =~ y5 + y6 + y7 + y8
+  ind60 =~ x1 + x2 + x3
+
+  # latent regressions
+  dem60 ~ ind60
+  dem65 ~ ind60 + dem60
+
+  # residual covariances
+  y1 ~~ y5
+  y2 ~~ y4 + y6
+  y3 ~~ y7
+  y4 ~~ y8
+  y6 ~~ y8
+'
+# About 10 seconds
+fit <- isem(model = myModel, data = PoliticalDemocracy)
+
+# Example using cli progressbar ------------------------------------------------
+fun <- function() {
+  # Setup
+  options(cli.spinner = "boxBounce")
+  options(cli.progress_show_after = 0)
+  cli_progress_bar(
+    name = "Laplace-ing through p dimensions",
+    format = "{cli::pb_spin} {cli::pb_name} [{cli::pb_elapsed}]",
+    clear = FALSE
+  )
+
+  # Simulating an inla call
+  while (TRUE) {
+    if (runif(1) < 0.01) break
+    Sys.sleep(0.05)
+    cli_progress_update()
+  }
+  cli_progress_update(force = TRUE)
+
+  # Defaults
+  options(cli.spinner = "dots")
+  options(cli.progress_show_after = 2)
+}
+fun()