plot: Graphically visualize 'pgeometry' objects

In accarniel/fsr: Handling Fuzzy Spatial Data

Graphically visualize pgeometry objects

Description

The fsr_plot() function (and the S4 method plot()) plots a pgeometry object.

Usage

fsr_plot(pgo, base_poly = NULL, add_base_poly = TRUE, low = "white", high = "black", 
         crs = NA, clip = FALSE, line_lwd = 1, region_lwd = 1, ...)

## S4 method for signature 'pgeometry,missing'
plot(x, y, ...)

Arguments

pgo	A pgeometry object of any type.
base_poly	An sfg object of the type POLYGON or MULTIPOLYGON. It can also be an sfc object with only one element of the type POLYGON or MULTIPOLYGON.
add_base_poly	A Boolean value that indicates whether base_poly will added to the visualization.
low	A character value that indicates the color for the lowest membership degree (i.e., 0). Default is "white".
high	A character value that indicates the color for the highest membership degree (i.e., 1). Default is "black".
crs	A numerical value that denotes the coordinate reference system (i.e., EPSG code) of the visualization. Default is NA.
clip	A Boolean value that indicates whether the boundaries of the components must be clipped by the sfg object base_poly (if it is not null).
line_lwd	A numeric value that specifies the line width of linear components.
region_lwd	A numeric value that specifies the line width of the boundaries of polygonal components.
...	<dynamic-dots> Optional parameters. They can be the same as the parameters of geom_sf() function from ggplot2.
x	A pgeometry object of any type.
y	Not applicable.

Details

The fsr_plot() function uses a ggplot2 package to built the resulting plot. It receives a pgeometry object as input (if it is empty, an empty graphics in obtained).

The low and high parameters are the colors for the minimum and maximum limits of the membership degrees. The default colors are "white" and "black", respectively. Other colors can be given in the same way that colors are informed to visualizations produced by the ggplot2 package.

It is possible to clip the geometric format of the components by using the parameter base_poly. The boundaries of this object can also be included in the visualization if the parameter add_base_poly is TRUE.

Since the returned value is a ggplot object, it can be further be customized (see examples below).

Value

A ggplot object.

References

Carniel, A. C.; Venâncio, P. V. A. B; Schneider, M. fsr: An R package for fuzzy spatial data handling. Transactions in GIS, vol. 27, no. 3, pp. 900-927, 2023.

Examples

library(sf)

pts <- rbind(c(0, 2), c(4, 2))
# Point components
pcp1 <- create_component(st_multipoint(pts), 0.3)
pcp2 <- create_component("MULTIPOINT((2 2), (2 4), (2 0))", 0.5)
pcp3 <- create_component("MULTIPOINT((1 1), (3 1), (1 3), (3 3))", 0.9)
# Line components
lcp1 <- create_component("LINESTRING(0 0, 1 1.5)", 0.2)
lcp2 <- create_component("LINESTRING(1 3, 1 2, 2 0.5)", 0.5)
lcp3 <- create_component("LINESTRING(2 1.2, 3 1.6, 4 4)", 0.7)
lcp4 <- create_component("LINESTRING(1 1.5, 2 1.2)", 1.0)
# Polygon components
rcp1 <- create_component("POLYGON((0 0, 1 4, 2 2, 0 0))", 0.4)
rcp2 <- create_component("POLYGON((2 0.5, 4 1, 4 0, 2 0.5))", 0.8)
# Creating spatial plateau objects
pp <- create_pgeometry(list(pcp1, pcp2, pcp3), "PLATEAUPOINT")
pl <- create_pgeometry(list(lcp1, lcp3, lcp4), "PLATEAULINE")
pr <- create_pgeometry(list(rcp1, rcp2), "PLATEAUREGION")
pcm <- create_pgeometry(list(pcp1, pcp2, lcp1, lcp2, lcp3, rcp2), "PLATEAUCOMPOSITION")
pcl <- create_pgeometry(list(pp, pr, pcm), "PLATEAUCOLLECTION")

# Displaying their textual representations
pp
pl
pr
pcm
pcl

# Plotting them
plot(pp)
plot(pl)
plot(pr)
plot(pcm)
plot(pcl)
## Not run: 
# Custom colors
fsr_plot(pr, low = "green", high = "blue")

# Changing the line width of line components
fsr_plot(pl, line_lwd = 2)

# Changing the line width of boundary lines of region components
fsr_plot(pr, region_lwd = 2)

# Changing the line width of boundary lines of region components and its color
fsr_plot(pr, region_lwd = 2, color = "blue")

# You can customize the whole visualization using ggplot
library(ggplot2)

fsr_plot(pp, size = 5) +   
  theme(legend.position = "none") +
  theme(text=element_text(size=20, family = "serif", color = "black"),
        axis.text=element_text(color="black")) +
  scale_x_continuous(breaks = c(0, 1, 2, 3, 4)) +
  scale_y_continuous(breaks = c(0, 1, 2, 3, 4))

## End(Not run)

accarniel/fsr documentation built on Jan. 29, 2024, 5:38 a.m.