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Create a complete ggplot for a spatial interaction model

Source: R/sim_autoplot.R
autoplot.sim.Rd

This function represents graphical the flows of a spatial interaction model, in different direct or aggregated forms.

Usage

# S3 method for class 'sim'
autoplot(
  object,
  flows = c("full", "destination", "attractiveness"),
  with_names = FALSE,
  with_positions = FALSE,
  cut_off = 100 * .Machine$double.eps^0.5,
  ...
)

Arguments

object

a spatial interaction model object

flows

"full" (default), "destination" or "attractiveness", see details.

with_names

specifies whether the graphical representation includes location names (FALSE by default)

with_positions

specifies whether the graphical representation is based on location positions (FALSE by default)

cut_off

cut off limit for inclusion of a segment in the full flow matrix representation with with_positions = TRUE

...

additional parameters, see details

Value

a ggplot object

Details

The graphical representation depends on the values of flows and with_positions. If with_position is FALSE (default value), the graphical representations are "abstract". De pending on flows we have the following representations:

  • "full": this is the default case for which the full flow matrix is represented. It is extracted from the spatial interaction model with flows() and displayed using a matrix representation with origin locations in rows and destination locations in columns. The colour of a cell corresponds to the intensity of a flow between the corresponding locations. To mimic the standard top to bottom reading order of a flow matrix, the top row of the graphical representation corresponds to the first origin location.

  • "destination": the function computes the incoming flows for destination locations (using destination_flow()) and represents them with a bar plot (each bar is proportional to the incoming flow);

  • "attractiveness": the function uses a bar plot to represent the attractivenesses of the destination locations (as given by attractiveness()). This is interesting for dynamic models where those values are updated during the iterations (see blvim() for details). When the calculation has converged (see sim_converged()), both "destination" and "attractiveness" graphics should be almost identical.

When the with_names parameter is TRUE, the location names (location_names()) are used to label the axis of the graphical representation. If names are not specified, they are replaced by indexes.

When the with_positions parameter is TRUE, the location positions (location_positions()) are used to produce more "geographically informed" representations. Notice that if no positions are known for the locations, the use of with_positions = TRUE is an error. Depending on flows we have the following representations:

  • "full": this is the default case for which the full flow matrix is represented. Positions for both origin and destination locations are needed. The representation uses arrows from origin location positions to destination location positions. The thickness of the lines (linewidth aesthetics) is proportional to the flows. Only segments that carry a flow above the cut_off value are included. Additional parameters in ... are submitted to ggplot2::geom_segment(). This can be used to override defaults parameters used for the arrow shapes, for instance.

  • "destination": the function draws a disk at each destination location using for the size aesthetics the incoming flow at this destination location (using destination_flow()).

  • "attractiveness": the function draws a disk at each destination location using for the size aesthetics the attractiveness of the destination. When the calculation has converged (see sim_converged()), both "destination" and "attractiveness" graphics should be almost identical.

Examples

positions <- matrix(rnorm(10 * 2), ncol = 2)
distances <- as.matrix(dist(positions))
production <- rep(1, 10)
attractiveness <- c(2, rep(1, 9))
flows <- blvim(distances, production, 1.5, 4, attractiveness,
  origin_data = list(names = LETTERS[1:10], positions = positions),
  destination_data = list(names = LETTERS[1:10], positions = positions)
)
ggplot2::autoplot(flows)

## bar plots should be almost identical if convergence occurred
sim_converged(flows)
#> [1] TRUE
ggplot2::autoplot(flows, "destination")

ggplot2::autoplot(flows, "attractiveness")

## names inclusion
ggplot2::autoplot(flows, "destination", with_names = TRUE)

ggplot2::autoplot(flows, with_names = TRUE)

## positions
ggplot2::autoplot(flows, "attractiveness", with_positions = TRUE) +
  ggplot2::scale_size_continuous(range = c(0, 6))

ggplot2::autoplot(flows, with_positions = TRUE) +
  ggplot2::scale_linewidth_continuous(range = c(0, 2))