Please reply here as to your success or failure using the below install script - Its been moderately tested on Windows, but needs more Mac OS and Linux Testing
Installing greta requires the successful configuration of a compatible conda Python environment. The default configurations offered by any out-of-the-box R functions like tensorflow::install_tensorflow() do not provide for greta-compatible configurations.
I have had much success in the past with my textbook’s install instructions (robust install instructions link) as hundreds of students get things working properly without issue using these instructions. The challenge with those instructions is that students have to leave the comfort of RStudio and venture to using command prompts which setup environments that RStudio then needs to find.
To make things easier and to avoid students venturing into using the command prompt, I have created a greta-installation script to LOCALLY install greta and that can be run interactively on any OS and all within RStudio. The script is now a separate section within my textbook (experimental install script link) and is pasted below (note: script will also install the causact package which I developed and provides R functions for visualizing and running inference via greta on generative directed acyclic graphs).
## INSTALLATION SCRIPT TO GET GRETA, CAUSACT,
## and TENSORFLOW ALL WORKING TOGETHER HAPPILY
## NOTE: Run each line one at a time using CTRL+ENTER.
## Await completion of one line
## before running the next.
## If prompted to "Restart R", say YES.
#### STEP 0: Restart R in a Clean Session
#### use RStudio menu: SESSION -> RESTART R
#### STEP 1: INSTALL PACKAGES WITH PYTHON DEPENDENCIES
install.packages("reticulate",dependencies = TRUE)
install.packages("greta",dependencies = TRUE)
install.packages("causact",dependencies = TRUE)
#### STEP 2: INSTALL & UPDATE MINICONDA AS NEEDED
## test for available conda binary
condaPath = try(reticulate::conda_binary()) #error is OK
if (is.null(condaPath) | class(condaPath) == "try-error") {
## install miniconda in default location if possible
condaInstall = try(reticulate::install_miniconda())
condaPath = try(reticulate::miniconda_path())
## if install still fails install miniconda in C:\miniconda
if(class(condaInstall) == "try-error") {
condaPath = file.path("/", "miniconda")
reticulate::install_miniconda(path = condaPath,
force = TRUE)}
reticulate::miniconda_update(path = condaPath) #update new install
newCondaInstall = TRUE ## flag to update env var if needed
} else {
reticulate::miniconda_update() ## update existing conda
newCondaInstall = FALSE
### this environment is added automatically by install_miniconda()
reticulate::conda_create(envname = "r-reticulate") ## add environment
}
#### STEP 3: RESTART R WITH CONDA ENVIRONMENT HINT
#### GIVEN IN EDITED .Rprofile FILE
## capture environment variable for inclusion in .Rprofile
newProfileLines = c() ## initialize config lines for .Rprofile
if(newCondaInstall) { ## help R find new install location
newProfileLines = c(
newProfileLines,
paste0("Sys.setenv(RETICULATE_MINICONDA_PATH = '",
condaPath, "')")
)
rProfilePath = file.path("~", ".Rprofile")
profileLines = c() ## init blank lines
if (file.exists(rProfilePath)) {
## is there a .RProfile file?
profileLines = readLines(rProfilePath)# get rProfile
}
## add new line to top of file
profileLines = c(newProfileLines, profileLines)
writeLines(profileLines, rProfilePath)
.rs.restartR() ## run & wait for R session to resume
## (at least 15 seconds) before continuing
}
#### STEP 4: Update "r-reticulate" CONDA ENVIRONMENT
#### FOR TENSORFLOW
## Install the specific versions of modules
## for the TensorFlow installation via CONDA.
## this line takes a few minutes to execute
reticulate::conda_install(envname = "r-reticulate",
packages =
c(
"python=3.7",
"tensorflow=1.14",
"pyyaml",
"requests",
"Pillow",
"pip",
"numpy=1.16",
"h5py=2.8",
"tensorflow-probability=0.7"
))
#### STEP 4: TEST THE INSTALLATION
library(greta) ## should work now
library(causact)
graph = dag_create() %>%
dag_node("Normal RV",
rhs =normal(0,10))
graph %>% dag_render() ## see oval
drawsDF = graph %>% dag_greta() ## see "running X chains..."
drawsDF %>% dagp_plot(densityPlot = TRUE) ## see plot
