---
title: "Comparing redistribution methods"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Comparing redistribution methods}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

```{r setup}
library(sdc.redistribute)
```

Both methods estimate target values from source values; they differ in the
weight each assigns to a piece of a source polygon.

- **`redistribute_direct`** assumes the measure is spread *uniformly by area*
  within each source polygon. It needs only the two polygon layers.
- **`redistribute_parcels`** assumes the measure follows a *point layer* (e.g.
  parcels), which usually tracks where people and housing actually are. It is
  more accurate where such points exist, at the cost of needing that layer.

```{r}
library(sdc.redistribute)
data(sdc_example)

direct  <- redistribute_direct(sdc_example$source, sdc_example$target,
                               extensive = "pop", suffix = "_direct")
parcels <- redistribute_parcels(sdc_example$source, sdc_example$target,
                                sdc_example$parcels, extensive = "pop",
                                suffix = "_parcels")

cbind(sf::st_drop_geometry(direct["pop_direct"]),
      sf::st_drop_geometry(parcels["pop_parcels"]))
```

Both preserve the source total; they differ in how they place it.