---
title: "Run a first GEModelR simulation"
author: "GEModelR maintainers"
output:
  rmarkdown::html_vignette:
    toc: true
vignette: >
  %\VignetteIndexEntry{Run a first GEModelR simulation}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

This guide runs a small, deterministic model through the supported
GEModelR workflow. It creates the TABLO text and input arrays locally, so the
example does not need external HAR files or GTAP data.

```{r setup, include=FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  warning = FALSE,
  message = FALSE
)
helperPath = if (file.exists("helpers.R")) {
  "helpers.R"
} else {
  file.path("vignettes", "helpers.R")
}
source(helperPath, local = knitr::knit_global())
```

## Prepare a small model

Create the model object, parse its TABLO equations, define the closure, and
load the in-memory data with the sparse engine.

```{r prepare-model}
fixture = makeFirstSimulationFixture()
model = GEModelR::GEModel$new()
model$loadTablo(fixture$tabloPath)
model$setClosure("tax")
model$loadData(fixture$inputData, engine = "sparse")
```

## Apply a shock and solve

The indexed shock changes the tax variable in the south region. The example
selects the supported Matrix sparse backend explicitly and disables
post-simulation updates so the reported values are only the solver result.

```{r solve-model}
model$setShocks(setNames(4, 'tax["south"]'))
model$solveModel(
  iter = 1,
  steps = 1,
  engine = "sparse",
  postsim = FALSE,
  diagnostics = TRUE,
  output = "full",
  backend = "Matrix",
  reduction = "off"
)
```

## Inspect the result

The solution follows the fixture's region order. The diagnostics envelope
records which engine and backend handled the solve.

```{r inspect-result}
data.frame(
  region = fixture$regions,
  solution = unname(model$solution)
)
model$lastDiagnostics[c("status", "engine", "requested_backend")]
```