Example Dataset: Oregon Level 3 Ecoregion Shapefile

Description

An object of class 'SpatialPolygonsDataFrame' that was created from a shapefile detailing boundaries of the level 3 ecoregion borders of Oregon.

Format

The format is: Formal class 'SpatialPointsDataFrame' [package "sp"].

Note

This is just an example data set.

Examples

data(OrEcoLevel3)
spplot(OrEcoLevel3, zcol="US_L3NAME", col.regions=rainbow(9, s=0.75))

Example Dataset: U.S. States Polygons

Description

An object of class 'SpatialPolygonsDataFrame' that was created from a shapefile of U.S. state borders.

Format

The format is: Formal class 'SpatialPolygonsDataFrame' [package "sp"].

Note

This is just an example data set.

Examples

data(USstates)
plot(USstates)

Example Dataset: Major U.S. EcoRegions

Description

An object of class 'SpatialPolygonsDataFrame' that was created from a shapefile of the U.S. level 3 ecoregion boundaries.

Format

The format is: Formal class 'SpatialPointsDataFrame' [package "sp"].

Note

This is just an example data set.

Examples

data(WSA3)
spplot(WSA3, zcol="WSA_3_NM", col.regions=rainbow(3, s=0.75))

Insert a Median Line

Description

Adds a median line to the DF table.

Usage

alterForMedian(DF, a)

Arguments

Value

Returns the DF table.

Note

See the Introduction Guide for a full list of the options available for altering micromaps.

Author(s)

Quinn Payton Payton.Quinn@epa.gov

Cleans a User Made Panel

Description

Sends a user made panel out to the graph "cleaning functions" in lmplot in order to properly display a user made panel seemlessly into the rest of an lmplot.

Usage

assimilatePlot(pl, i, a, limsx = NA, limsy = NA)

Arguments

Value

Returns a cleaned plot object.

Note

See the Introduction Guide for a full list of the options available for altering micromaps.

Author(s)

Quinn Payton Payton.Quinn@epa.gov

Prepares A Polygon Table

Description

Takes the user supplied polygon table and prepares it to be plotted correctly with the lmplot function.

Usage

create_map_table(tmp.map, IDcolumn = NA, poly.thresh = 1e-04)

Arguments

Value

A flat table of all the polygons in the shapefile with an entry for each vertice.

Author(s)

Quinn Payton Payton.Quinn@epa.gov

Examples

data("USstates")
head(USstates@data)
statePolys <- create_map_table(USstates, IDcolumn="ST")
head(statePolys)

Example Dataset: Education and Poverty Levels

Description

A datset comparing education and poverty levels among the states.

Format

A data frame with 51 rows and the following 5 columns:

state

full state name.

ed

education rate.

pov

poverty rate.

region

major us region.

StateAb

abbreviated state name.

Note

This is just an example data set.

Examples

data(edPov)
head(edPov)

Internal lmplot Functions

Description

These functions are internal lmplot functions.

Details

These functions are not to be called by the user. Includes all_atts, all_attsb, all_equal2, axis_opts, CatMaps, create_DF_rank, create_DF_cat, dot_legend_att, dot_legend_build, graph_opts, list_att, make.string, plot_opts, RankMaps, subplot

Default Attribute Lists

Description

Creates a list of default attribute lists for each panel type.

Usage

labels_att(show = FALSE)

Arguments

Value

A list of defaults to be stored in the overall attribute list.

Author(s)

Quinn Payton Payton.Quinn@epa.gov

Builds panels

Description

Creates a panel of the user specified type using the attribute list to make adjustments.

Usage

labels_build(pl, p, DF, att)

Arguments

Value

Returns a ggplot object to be printed later in the lmplot function.

Author(s)

Quinn Payton Payton.Quinn@epa.gov

Linked Micromaps

Description

Creates a linked micromap, displaying specified polygons and their associated statistical summary displays; differentiated by color.

Usage

lmgroupedplot(
  stat.data,
  map.data,
  panel.types,
  panel.data,
  map.link = NULL,
  nPanels = length(panel.types),
  grp.by,
  cat,
  colors = brewer.pal(10, "Spectral"),
  map.color = "lightyellow",
  map.all = FALSE,
  print.file = "no",
  print.res = NA,
  panel.att = vector("list", nPanels),
  plot.header = NA,
  plot.header.size = NA,
  plot.header.color = NA,
  plot.footer = NA,
  plot.footer.size = NA,
  plot.footer.color = NA,
  plot.width = 7,
  plot.height = 7,
  map.spacing = 1,
  plot.grp.spacing = 1,
  plot.panel.spacing = 1,
  plot.panel.margins = c(0, 0, 1, 0),
  ...
)

lmplot(
  stat.data,
  map.data = NULL,
  panel.types,
  panel.data,
  map.link = NULL,
  nPanels = length(panel.types),
  ord.by,
  rev.ord = FALSE,
  grouping,
  median.row = FALSE,
  vertical.align = "top",
  median.color = gray(0.5),
  colors = brewer.pal(max(grouping), "Spectral"),
  map.all = FALSE,
  map.color2 = "lightgray",
  two.ended.maps = FALSE,
  print.file = "no",
  print.res = 300,
  panel.att = vector("list", nPanels),
  plot.header = NA,
  plot.header.size = NA,
  plot.header.color = NA,
  plot.footer = NA,
  plot.footer.size = NA,
  plot.footer.color = NA,
  plot.width = 7,
  plot.height = 7,
  map.spacing = 1,
  plot.pGrp.spacing = 1,
  plot.panel.spacing = 1,
  plot.panel.margins = c(0, 0, 1, 0),
  ...
)

mmgroupedplot(
  stat.data,
  map.data,
  panel.types,
  panel.data,
  map.link = NULL,
  nPanels = length(panel.types),
  grp.by,
  cat,
  colors = brewer.pal(10, "Spectral"),
  map.color = "lightyellow",
  map.all = FALSE,
  print.file = "no",
  print.res = NA,
  panel.att = vector("list", nPanels),
  plot.header = NA,
  plot.header.size = NA,
  plot.header.color = NA,
  plot.footer = NA,
  plot.footer.size = NA,
  plot.footer.color = NA,
  plot.width = 7,
  plot.height = 7,
  map.spacing = 1,
  plot.grp.spacing = 1,
  plot.panel.spacing = 1,
  plot.panel.margins = c(0, 0, 1, 0)
)

mmplot(map.data, ...)

## S3 method for class 'SpatialPolygonsDataFrame'
mmplot(map.data, ...)

## S3 method for class 'sf'
mmplot(map.data, ...)

## Default S3 method:
mmplot(
  map.data,
  stat.data,
  panel.types,
  panel.data,
  map.link,
  nPanels = length(panel.types),
  ord.by,
  rev.ord = FALSE,
  grouping,
  median.row = FALSE,
  vertical.align = "top",
  median.color = gray(0.5),
  median.text.color = "black",
  median.text.size = 1,
  median.text.label = "Median",
  colors = brewer.pal(max(grouping), "Spectral"),
  map.all = FALSE,
  map.color2 = "lightgray",
  two.ended.maps = FALSE,
  trans = "identity",
  print.file = "no",
  print.res = 300,
  panel.att = vector("list", nPanels),
  plot.header = NA,
  plot.header.size = NA,
  plot.header.color = NA,
  plot.footer = NA,
  plot.footer.size = NA,
  plot.footer.color = NA,
  plot.width = 7,
  plot.height = 7,
  map.spacing = 1,
  plot.pGrp.spacing = 1,
  plot.panel.spacing = 1,
  plot.panel.margins = c(0, 0, 1, 0),
  ...
)

Arguments

Value

A list of ggplot2 objects with entries for each individual panel.

Note

See the Introduction Guide for a full list of the options available for altering micromaps.

Author(s)

Quinn Payton Payton.Quinn@epa.gov

Examples

# initial example

data("USstates")
head(USstates@data)
statePolys <- create_map_table(USstates, 'ST')
head(statePolys)

data("edPov")

# basic figure 1
lmplot(stat.data = edPov,
  	map.data = statePolys,
	panel.types = c('labels', 'dot', 'dot','map'),
	panel.data = list('state','pov','ed', NA),
	ord.by = 'pov',   
	grouping = 5, median.row = TRUE,
	map.link = c('StateAb','ID'))

## Not run: 
# publication figure 1a
lmplot(stat.data = edPov,  map.data = statePolys ,
	panel.types = c('labels', 'dot', 'dot','map'),
	panel.data = list('state','pov','ed', NA),
	ord.by = 'pov',  
	grouping = 5, 
  	median.row = TRUE,
	map.link = c('StateAb','ID'),
	
  	plot.height = 9,							
	colors = c('red','orange','green','blue','purple'), 
	map.color2 = 'lightgray',
       
	panel.att = list(
	    list(1, header = 'States', panel.width = .8, align = 'left', 
	      text.size = .9),
			list(2, header = 'Percent Living Below \n Poverty Level',
				graph.bgcolor = 'lightgray', point.size = 1.5,
				xaxis.ticks = list(10,15,20), xaxis.labels = list(10,15,20),
				xaxis.title = 'Percent'),
			list(3, header = 'Percent Adults With\n4+ Years of College',
				graph.bgcolor = 'lightgray', point.size = 1.5,
				xaxis.ticks = list(0,20,30,40), xaxis.labels = list(0,20,30,40),
				xaxis.title = 'Percent'),
			list(4, header = 'Light Gray Means\nHighlighted Above',  
				inactive.border.color = gray(.7), inactive.border.size = 2,	
				panel.width = .8)))

edPov$points <- 0	

# publication figure 1b
lmplot (stat.data = edPov, map.data = statePolys,
	panel.types = c('dot',  'labels', 'dot', 'dot', 'map'),
	panel.data = list('points', 'state', 'pov', 'ed', NA),
	map.link = c('StateAb','ID'),
	ord.by = 'pov', 
	grouping = 5, 
	median.row = TRUE, 
	
	plot.height = 9, 
	
	colors = c('red','orange','green','blue','purple'),
	map.color2 = 'lightgray', 

	panel.att = list(list(1, panel.width = .15, point.type = 20,
					graph.border.color = 'white',
					xaxis.text.display = FALSE, xaxis.line.display = FALSE,
					graph.grid.major = FALSE),
	
				list(2, header = 'States', panel.width = .8, 
					align = 'left', text.size = .9),

				list(3, header = 'Percent Living Below\nPoverty Level',
					graph.bgcolor = 'lightgray', point.size = 1.5,
					xaxis.ticks = list(10,15,20), 
					xaxis.labels = list(10,15,20),
					xaxis.title = 'Percent'),

				list(4, header = 'Percent Adults With\n4+ Years of College',
					graph.bgcolor = 'lightgray', point.size = 1.5,
					xaxis.ticks = list(20,30,40), 
					xaxis.labels = list(20,30,40), 
					xaxis.title = 'Percent'),
	
				list(5, header = 'Light Gray Means\nHighlighted Above', 
					inactive.border.color = gray(.7), inactive.border.size = 2, 
					panel.width = .8)))

# publication figure 1c
myPlot <- lmplot(stat.data = edPov, map.data = statePolys,
	panel.types = c('map', 'dot',  'labels', 'dot', 'dot'),
	panel.data = list(NA, 'points', 'state', 'pov', 'ed'),
	map.link = c('StateAb','ID'),
	ord.by = 'pov', 
	grouping = 5, 
	median.row = TRUE,

	plot.height = 9, 
	
	colors = c('red','orange','green','blue','purple'),
	map.color2 = 'lightgray', 

	panel.att = list(list(2, panel.width = .15, point.type = 20,
				graph.border.color = 'white',
				xaxis.text.display = FALSE, xaxis.line.display = FALSE,
				graph.grid.major = FALSE),

			list(3, header = 'States', panel.width = .8, 
				align = 'left', text.size = .9),

			list(4, header = 'Percent Living Below\nPoverty Level',
				graph.bgcolor = 'lightgray', point.size = 1.5,
				xaxis.ticks = list(10,15,20), xaxis.labels = list(10,15,20),
				xaxis.title = 'Percent'),

			list(5, header = 'Percent Adults With\n4+ Years of College',
				graph.bgcolor = 'lightgray', point.size = 1.5,
				xaxis.ticks = list(20,30,40), 
				xaxis.labels = list(20,30,40), 
				xaxis.title = 'Percent'),
	
			list(1, header = 'Light Gray Means\nHighlighted Above', 
				inactive.border.color = gray(.7), inactive.border.size = 2, 
				panel.width = .8)))

print(myPlot, name = 'myExhibit.tiff', res = 300)

## End(Not run)

Example Dataset: Lung Cancer Mortality

Description

Lung mortality rates for all 50 states and Washington D.C.

Format

A data frame with 51 rows and the following 14 columns:

StateAb

abbreviation of state name.

Rate_95

mortality rate estimate for 1995.

Count_95

estimated number of cases in 1995.

Lower_95

lower bound of a 95 percent confidence interval for 1995 mortality rate.

Upper_95

lower bound of a 95 percent confidence interval for 1995 mortality rate.

Pop_95

population in 1995.

StdErr_95

estimated stadard error of the estimated mortality rate in 2000.

Rate_00

mortality rate estimate for 2000.

Count_00

estimated number of cases in 2000.

Lower_00

lower bound of a 95 percent confidence interval for 2000 mortality rate.

Upper_00

lower bound of a 95 percent confidence interval for 2000 mortality rate.

Pop_00

population in 2000.

StdErr_00

estimated stadard error of the estimated mortality rate in 2000.

State

full state name.

Note

This is just an example data set.

Examples

data(lungMort)
head(lungMort)

Print lmplot Object to a File

Description

Takes a stored lmplot object of class mm and prints to a file whose type is implied by the file name.

Usage

## S3 method for class 'mm'
print(x, name = NULL, res = 300, ...)

Arguments

Value

Returns nothing.

Author(s)

Quinn Payton Payton.Quinn@epa.gov

Print lmplot Object to a File

Description

Takes a stored lmplot object and uses the print method for objects of class mm to print to a file whose type is implied by the file name.

Usage

printLMPlot(plobject, name = NULL, res = 300)

Arguments

Value

Returns nothing.

Author(s)

Quinn Payton Payton.Quinn@epa.gov

Substring Function

Description

Mimics the Excel Function of the Same Name

Usage

right(txt, i)

Arguments

Value

A character value containing the substring.

Author(s)

Quinn Payton Payton.Quinn@epa.gov

Sample Attribute List Creator

Description

Creates a sample attribute list for use in the creation of new panel types.

Usage

sample_att(
  size = 1,
  type = rep("standard", size),
  ord.by = NA,
  grouping = 5,
  colors = brewer.pal(max(grouping), "Spectral"),
  plot.pGrp.spacing = 0.05,
  plot.panel.margins = c(0, 1, 0, 0),
  panel.data = list(NA),
  median.row = FALSE,
  show = FALSE
)

Arguments

Value

A list of attributes to be used in the creation of a panel

Note

See the Introduction Guide for a full list of the options available for altering micromaps.

Author(s)

Quinn Payton Payton.Quinn@epa.gov

Example Dataset: A Table of State Polygons

Description

Polygon vertices for each state.

Format

A data frame with 434 rows and the following 4 columns:

ID

abbreviation or state name.

coordsx

x coordinates for each polygon vertice.

coordsy

y coordinates for each polygon vertice.

poly

individual polygon identifier within each state.

Note

This is just an example data set.

Examples

data(statesFlatfile)
head(statesFlatfile)

Example Dataset: Vegetation Coverage Percentages

Description

A subset of a larger vegetation coverage analysis dataset.

Format

A data frame with 12 rows and the following 13 columns:

Type

the population name.

Subpopulation

the subpopulation name, either national or level 3 ecoregion.

Indicator

the ecological variable (indicator)

Category

category of disturbance.

NResp

sample size.

Estimate.P

estimated percentage of vegetation coverage with a given classification.

StdError.P

standard error of the percentage estimate.

LCB95Pct.P

lower bound of a 95 percent confidence interval for the estimated percentage.

UCB95Pct.P

upper bound of a 95 percent confidence interval for the estimated percentage.

Estimate.U

estimated area of vegetation coverage with a given classification.

StdError.U

standard error of the area estimate.

LCB95Pct.U

lower bound of a 95 percent confidence interval for the estimated area.

UCB95Pct.U

upper bound of a 95 percent confidence interval for the estimated area.

Note

This is just an example data set.

Examples

data(vegCov)
head(vegCov)