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Feb 6, 2025
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Attempting to reduce runtime of several code examples #141

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2 changes: 1 addition & 1 deletion DESCRIPTION
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
Package: stochtree
Title: Stochastic tree Ensembles (XBART and BART) for Supervised Learning and Causal Inference
Title: Stochastic Tree Ensembles (XBART and BART) for Supervised Learning and Causal Inference
Version: 0.1.0
Authors@R:
c(
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32 changes: 21 additions & 11 deletions R/bart.R
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Expand Up @@ -97,7 +97,8 @@
#' X_train <- X[train_inds,]
#' y_test <- y[test_inds]
#' y_train <- y[train_inds]
#' bart_model <- bart(X_train = X_train, y_train = y_train, X_test = X_test)
#' bart_model <- bart(X_train = X_train, y_train = y_train, X_test = X_test,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10)
#' plot(rowMeans(bart_model$y_hat_test), y_test, xlab = "predicted", ylab = "actual")
#' abline(0,1,col="red",lty=3,lwd=3)
bart <- function(X_train, y_train, leaf_basis_train = NULL, rfx_group_ids_train = NULL,
Expand Down Expand Up @@ -990,7 +991,8 @@ bart <- function(X_train, y_train, leaf_basis_train = NULL, rfx_group_ids_train
#' X_train <- X[train_inds,]
#' y_test <- y[test_inds]
#' y_train <- y[train_inds]
#' bart_model <- bart(X_train = X_train, y_train = y_train)
#' bart_model <- bart(X_train = X_train, y_train = y_train,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10)
#' y_hat_test <- predict(bart_model, X_test)$y_hat
#' plot(rowMeans(y_hat_test), y_test, xlab = "predicted", ylab = "actual")
#' abline(0,1,col="red",lty=3,lwd=3)
Expand Down Expand Up @@ -1150,7 +1152,7 @@ predict.bartmodel <- function(object, X, leaf_basis = NULL, rfx_group_ids = NULL
#' rfx_group_ids_test = rfx_group_ids_test,
#' rfx_basis_train = rfx_basis_train,
#' rfx_basis_test = rfx_basis_test,
#' num_gfr = 100, num_burnin = 0, num_mcmc = 100)
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10)
#' rfx_samples <- getRandomEffectSamples(bart_model)
getRandomEffectSamples.bartmodel <- function(object, ...){
result = list()
Expand Down Expand Up @@ -1200,7 +1202,8 @@ getRandomEffectSamples.bartmodel <- function(object, ...){
#' X_train <- X[train_inds,]
#' y_test <- y[test_inds]
#' y_train <- y[train_inds]
#' bart_model <- bart(X_train = X_train, y_train = y_train)
#' bart_model <- bart(X_train = X_train, y_train = y_train,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10)
#' bart_json <- saveBARTModelToJson(bart_model)
saveBARTModelToJson <- function(object){
jsonobj <- createCppJson()
Expand Down Expand Up @@ -1309,7 +1312,8 @@ saveBARTModelToJson <- function(object){
#' X_train <- X[train_inds,]
#' y_test <- y[test_inds]
#' y_train <- y[train_inds]
#' bart_model <- bart(X_train = X_train, y_train = y_train)
#' bart_model <- bart(X_train = X_train, y_train = y_train,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10)
#' tmpjson <- tempfile(fileext = ".json")
#' saveBARTModelToJsonFile(bart_model, file.path(tmpjson))
#' unlink(tmpjson)
Expand Down Expand Up @@ -1348,7 +1352,8 @@ saveBARTModelToJsonFile <- function(object, filename){
#' X_train <- X[train_inds,]
#' y_test <- y[test_inds]
#' y_train <- y[train_inds]
#' bart_model <- bart(X_train = X_train, y_train = y_train)
#' bart_model <- bart(X_train = X_train, y_train = y_train,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10)
#' bart_json_string <- saveBARTModelToJsonString(bart_model)
saveBARTModelToJsonString <- function(object){
# Convert to Json
Expand Down Expand Up @@ -1387,7 +1392,8 @@ saveBARTModelToJsonString <- function(object){
#' X_train <- X[train_inds,]
#' y_test <- y[test_inds]
#' y_train <- y[train_inds]
#' bart_model <- bart(X_train = X_train, y_train = y_train)
#' bart_model <- bart(X_train = X_train, y_train = y_train,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10)
#' bart_json <- saveBARTModelToJson(bart_model)
#' bart_model_roundtrip <- createBARTModelFromJson(bart_json)
createBARTModelFromJson <- function(json_object){
Expand Down Expand Up @@ -1501,7 +1507,8 @@ createBARTModelFromJson <- function(json_object){
#' X_train <- X[train_inds,]
#' y_test <- y[test_inds]
#' y_train <- y[train_inds]
#' bart_model <- bart(X_train = X_train, y_train = y_train)
#' bart_model <- bart(X_train = X_train, y_train = y_train,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10)
#' tmpjson <- tempfile(fileext = ".json")
#' saveBARTModelToJsonFile(bart_model, file.path(tmpjson))
#' bart_model_roundtrip <- createBARTModelFromJsonFile(file.path(tmpjson))
Expand Down Expand Up @@ -1545,7 +1552,8 @@ createBARTModelFromJsonFile <- function(json_filename){
#' X_train <- X[train_inds,]
#' y_test <- y[test_inds]
#' y_train <- y[train_inds]
#' bart_model <- bart(X_train = X_train, y_train = y_train)
#' bart_model <- bart(X_train = X_train, y_train = y_train,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10)
#' bart_json <- saveBARTModelToJsonString(bart_model)
#' bart_model_roundtrip <- createBARTModelFromJsonString(bart_json)
#' y_hat_mean_roundtrip <- rowMeans(predict(bart_model_roundtrip, X_train)$y_hat)
Expand Down Expand Up @@ -1590,7 +1598,8 @@ createBARTModelFromJsonString <- function(json_string){
#' X_train <- X[train_inds,]
#' y_test <- y[test_inds]
#' y_train <- y[train_inds]
#' bart_model <- bart(X_train = X_train, y_train = y_train)
#' bart_model <- bart(X_train = X_train, y_train = y_train,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10)
#' bart_json <- list(saveBARTModelToJson(bart_model))
#' bart_model_roundtrip <- createBARTModelFromCombinedJson(bart_json)
createBARTModelFromCombinedJson <- function(json_object_list){
Expand Down Expand Up @@ -1735,7 +1744,8 @@ createBARTModelFromCombinedJson <- function(json_object_list){
#' X_train <- X[train_inds,]
#' y_test <- y[test_inds]
#' y_train <- y[train_inds]
#' bart_model <- bart(X_train = X_train, y_train = y_train)
#' bart_model <- bart(X_train = X_train, y_train = y_train,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10)
#' bart_json_string_list <- list(saveBARTModelToJsonString(bart_model))
#' bart_model_roundtrip <- createBARTModelFromCombinedJsonString(bart_json_string_list)
createBARTModelFromCombinedJsonString <- function(json_string_list){
Expand Down
24 changes: 13 additions & 11 deletions R/bcf.R
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Expand Up @@ -137,7 +137,8 @@
#' tau_train <- tau_x[train_inds]
#' bcf_model <- bcf(X_train = X_train, Z_train = Z_train, y_train = y_train,
#' propensity_train = pi_train, X_test = X_test, Z_test = Z_test,
#' propensity_test = pi_test)
#' propensity_test = pi_test, num_gfr = 10,
#' num_burnin = 0, num_mcmc = 10)
#' plot(rowMeans(bcf_model$mu_hat_test), mu_test, xlab = "predicted",
#' ylab = "actual", main = "Prognostic function")
#' abline(0,1,col="red",lty=3,lwd=3)
Expand Down Expand Up @@ -1438,7 +1439,8 @@ bcf <- function(X_train, Z_train, y_train, propensity_train = NULL, rfx_group_id
#' tau_test <- tau_x[test_inds]
#' tau_train <- tau_x[train_inds]
#' bcf_model <- bcf(X_train = X_train, Z_train = Z_train, y_train = y_train,
#' propensity_train = pi_train)
#' propensity_train = pi_train, num_gfr = 10,
#' num_burnin = 0, num_mcmc = 10)
#' preds <- predict(bcf_model, X_test, Z_test, pi_test)
#' plot(rowMeans(preds$mu_hat), mu_test, xlab = "predicted",
#' ylab = "actual", main = "Prognostic function")
Expand Down Expand Up @@ -1632,7 +1634,7 @@ predict.bcfmodel <- function(object, X, Z, propensity = NULL, rfx_group_ids = NU
#' Z_test = Z_test, propensity_test = pi_test,
#' rfx_group_ids_test = rfx_group_ids_test,
#' rfx_basis_test = rfx_basis_test,
#' num_gfr = 100, num_burnin = 0, num_mcmc = 100,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10,
#' mu_forest_params = mu_params,
#' tau_forest_params = tau_params)
#' rfx_samples <- getRandomEffectSamples(bcf_model)
Expand Down Expand Up @@ -1723,7 +1725,7 @@ getRandomEffectSamples.bcfmodel <- function(object, ...){
#' Z_test = Z_test, propensity_test = pi_test,
#' rfx_group_ids_test = rfx_group_ids_test,
#' rfx_basis_test = rfx_basis_test,
#' num_gfr = 100, num_burnin = 0, num_mcmc = 100,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10,
#' mu_forest_params = mu_params,
#' tau_forest_params = tau_params)
#' # bcf_json <- saveBCFModelToJson(bcf_model)
Expand Down Expand Up @@ -1888,7 +1890,7 @@ saveBCFModelToJson <- function(object){
#' Z_test = Z_test, propensity_test = pi_test,
#' rfx_group_ids_test = rfx_group_ids_test,
#' rfx_basis_test = rfx_basis_test,
#' num_gfr = 100, num_burnin = 0, num_mcmc = 100,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10,
#' mu_forest_params = mu_params,
#' tau_forest_params = tau_params)
#' # saveBCFModelToJsonFile(bcf_model, "test.json")
Expand Down Expand Up @@ -1966,7 +1968,7 @@ saveBCFModelToJsonFile <- function(object, filename){
#' Z_test = Z_test, propensity_test = pi_test,
#' rfx_group_ids_test = rfx_group_ids_test,
#' rfx_basis_test = rfx_basis_test,
#' num_gfr = 100, num_burnin = 0, num_mcmc = 100,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10,
#' mu_forest_params = mu_params,
#' tau_forest_params = tau_params)
#' # saveBCFModelToJsonString(bcf_model)
Expand Down Expand Up @@ -2046,7 +2048,7 @@ saveBCFModelToJsonString <- function(object){
#' Z_test = Z_test, propensity_test = pi_test,
#' rfx_group_ids_test = rfx_group_ids_test,
#' rfx_basis_test = rfx_basis_test,
#' num_gfr = 100, num_burnin = 0, num_mcmc = 100,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10,
#' mu_forest_params = mu_params,
#' tau_forest_params = tau_params)
#' bcf_json <- saveBCFModelToJson(bcf_model)
Expand Down Expand Up @@ -2211,7 +2213,7 @@ createBCFModelFromJson <- function(json_object){
#' Z_test = Z_test, propensity_test = pi_test,
#' rfx_group_ids_test = rfx_group_ids_test,
#' rfx_basis_test = rfx_basis_test,
#' num_gfr = 100, num_burnin = 0, num_mcmc = 100,
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10,
#' mu_forest_params = mu_params,
#' tau_forest_params = tau_params)
#' # saveBCFModelToJsonFile(bcf_model, "test.json")
Expand Down Expand Up @@ -2292,7 +2294,7 @@ createBCFModelFromJsonFile <- function(json_filename){
#' Z_test = Z_test, propensity_test = pi_test,
#' rfx_group_ids_test = rfx_group_ids_test,
#' rfx_basis_test = rfx_basis_test,
#' num_gfr = 100, num_burnin = 0, num_mcmc = 100)
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10)
#' # bcf_json <- saveBCFModelToJsonString(bcf_model)
#' # bcf_model_roundtrip <- createBCFModelFromJsonString(bcf_json)
createBCFModelFromJsonString <- function(json_string){
Expand Down Expand Up @@ -2372,7 +2374,7 @@ createBCFModelFromJsonString <- function(json_string){
#' Z_test = Z_test, propensity_test = pi_test,
#' rfx_group_ids_test = rfx_group_ids_test,
#' rfx_basis_test = rfx_basis_test,
#' num_gfr = 100, num_burnin = 0, num_mcmc = 100)
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10)
#' # bcf_json_list <- list(saveBCFModelToJson(bcf_model))
#' # bcf_model_roundtrip <- createBCFModelFromCombinedJson(bcf_json_list)
createBCFModelFromCombinedJson <- function(json_object_list){
Expand Down Expand Up @@ -2584,7 +2586,7 @@ createBCFModelFromCombinedJson <- function(json_object_list){
#' Z_test = Z_test, propensity_test = pi_test,
#' rfx_group_ids_test = rfx_group_ids_test,
#' rfx_basis_test = rfx_basis_test,
#' num_gfr = 100, num_burnin = 0, num_mcmc = 100)
#' num_gfr = 10, num_burnin = 0, num_mcmc = 10)
#' # bcf_json_string_list <- list(saveBCFModelToJsonString(bcf_model))
#' # bcf_model_roundtrip <- createBCFModelFromCombinedJsonString(bcf_json_string_list)
createBCFModelFromCombinedJsonString <- function(json_string_list){
Expand Down
5 changes: 3 additions & 2 deletions cran-comments.md
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@@ -1,6 +1,7 @@
## R CMD check results

0 errors | 0 warnings | 2 notes
0 errors | 0 warnings | 3 notes

* This is a new release.
* checking installed package size ... NOTE installed size is 46.3Mb (linux-only)
* Checking installed package size ... NOTE installed size is 46.3Mb (linux-only)
* Possibly misspelled words in DESCRIPTION: All of the words are proper nouns or technical terms (BCF, Carvalho, Chipman, McCulloch, XBART)
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