Package 'micromap'

Insert a Median Line

Description

Adds a median line to the DF table.

Usage

alterForMedian(DF, a)

Arguments

DF	the DF table created by create_DF_rank.
a	the attributes list, which contains the user specified choice of whether to include a median row.

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 [email protected]

---

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

pl	the lmplot object.
i	the panel number.
a	the attribute list.
limsx	limits of the x axis if desired.
limsy	limits of the y axis if desired.

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 [email protected]

---

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

tmp.map	a shapefile to be parsed into a flat table for use with ggplot2.
IDcolumn	specify which column in the data file to use as a unique identifier.
poly.thresh	specify the minimum polygon area which to keep. All polygons with less area will be dropped.

Value

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

Author(s)

Quinn Payton [email protected]

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)

---

Default Attribute Lists

Description

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

Usage

labels_att(show = FALSE)

Arguments

show	If show equals FALSE, then the resulting list is returned invisibly.

Value

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

Author(s)

Quinn Payton [email protected]

---

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

pl	the lmplot object being constructed.
p	number of the panel within the plot.
DF	the data table of statistics to be referenced.
att	the attribute list to specify visual and graphical characteristics.

Value

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

Author(s)

Quinn Payton [email protected]

---

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

stat.data	table of statistics for display
map.data	table of polygons to be associated with each item in stat.data.
panel.types	vector of panel types to specify the layout of the plot, e.g., c('map', 'labels', 'dot.cl'). Nine possible types are available: 'map', 'labels', 'dot', 'dot_cl' (dotplots with confidence limits), 'dot_legend', 'bar', 'bar_cl' (barplots with confidence limits), 'box_summary', and 'ranks'.
panel.data	a list (of lists) of data to be used with each panel (e.g. list(NA, 'Names', list('lower.bound','estimate','upper.bound')).
map.link	a vector with the name of the columns from stat.data and map.data, respectively, on which to join.
nPanels	the number of panels, which is not expected to be set by the user. The default is the length of panel.types.
grp.by	The column name from stat.data with which to order the lines of the output graphic for a standard lmPLot or identifier column on which to group the categorized lmPLot.
cat	category column within stats table for a categorization type lmplot.
colors	a vector of colors for the perceptual groups. The default is brewer.pal(max(grouping), 'Spectral') for lmplot and brewer.pal(10, 'Spectral') for lmgroupedplot). The colors are passed to colorRampPalette to create a continuous color vector equal in length to the groupings.
map.color	the color to fill in previously displayed polygons.
map.all	by default, lmplot will only plot the polygons associated with data in the stats table; map.all = TRUE will show all the polygons in the polygon table regardless of whether they are actively referred to.
print.file	name of the file being created. The extension (.pdf, .tiff, .jpeg, .png) tells lmplot which image creation tool to use.
print.res	the resolution of the image to use.
panel.att	a list of panel specific attributes to be altered (see lmplot documentation).
plot.header	the overall title to be placed on the lmPLot.
plot.header.size	size of the overall title to be placed on the lmPLot.
plot.header.color	color of the overall title to be placed on the lmPLot.
plot.footer	the overall footer to be placed under the lmPLot.
plot.footer.size	size of the overall footer to be placed under the lmPLot.
plot.footer.color	color of the overall footer to be placed under the lmPLot.
plot.width	width of the overall plot in inches. Defaults to 7.
plot.height	height of the overall plot in inches. Defaults to 7.
map.spacing	the vertical spacing between maps measured in lines. Perceptual group spacing does not affect map spacing so as to leave the maps as large as possible. The user can increase map spacing using this argument. Defaults to 1.
plot.grp.spacing	the vertical spacing between groups measured in lines. Defaults to 1.
plot.panel.spacing	the vertical spacing between panels measured in lines. Defaults to 1.
plot.panel.margins	the horizontal spacing between panels measured in lines. THIS IS LEGACY CODE AND SHOULD NOT BE USED.
...	Additional arguments passed to or from other methods.
ord.by	The column name from stat.data with which to order the lines of the output graphic for a standard lmPLot or identifier column on which to group the categorized lmPLot.
rev.ord	specifies whether the plot should be displayed in reverse order of the ranking column. The default is FALSE.
grouping	the number of lines per perceptual group (for the standard lmplot only). Can be a single number to have the same numer in each group or a vector of numbers for unequal groupings.
median.row	specifies whether a median row should be included. If an odd number of data lines are supplied, a data line itself will be used as the median, otherwise median entries will be calculated from the supplied data. Note that without a median row maps are forced into proper size.
vertical.align	controls vertical alignment of the median row.
median.color	specifies color of the median row.
map.color2	the color to fill in previously displayed polygons.
two.ended.maps	the resulting micromaps will highlight previously referenced polygons (see map.color2) up to the median perceptual group then switch to highlighting all polygons that are still to be referenced later.
plot.pGrp.spacing	the vertical spacing between perceptual groups measured in lines. Defaults to 1.
median.text.color	specifies color of text in the median row.
median.text.size	specifies size of text in the median row.
median.text.label	specifies the label for text in the median row.
trans	chr string for axis transformations, passed to scale_x_continuous. Acceptable values are "asn", "atanh", "boxcox", "exp", "identity", "log", "log10", "log1p", "log2", "logit", "probability", "probit", "reciprocal", "reverse" or "sqrt". One value will be recycled to all panels as needed, otherwise one per panel can be used in a combined string. Applies only to panels with axes.

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 [email protected]

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)

---

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))

---

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

x	name of the lmplot object.
name	name of the file to be produced. tiff, png, jpeg, and pdf are recognized.
res	resolution in dpi.
...	Additional arguments. (Currently ignored.)

Value

Returns nothing.

Author(s)

Quinn Payton [email protected]

---

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

plobject	name of the lmplot object.
name	name of the file to be produced. Tiff, png, jpeg, and pdf are recognized.
res	resolution in dpi.

Value

Returns nothing.

Author(s)

Quinn Payton [email protected]

---

Substring Function

Description

Mimics the Excel Function of the Same Name

Usage

right(txt, i)

Arguments

txt	string to be substringed.
i	number of characters to substring.

Value

A character value containing the substring.

Author(s)

Quinn Payton [email protected]

---

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

size	specify the number of attibutes lists to be created.
type	match the attributes to which type of default panel.
ord.by	argument inhereted from lmplot/lmGroupedplot.
grouping	argument inhereted from lmplot/lmGroupedplot.
colors	argument inhereted from lmplot/lmGroupedplot.
plot.pGrp.spacing	argument inhereted from lmplot/lmGroupedplot.
plot.panel.margins	argument inhereted from lmplot/lmGroupedplot.
panel.data	argument inhereted from lmplot/lmGroupedplot.
median.row	argument inhereted from lmplot/lmGroupedplot.
show	controls whether to print the resulting attribute list.

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 [email protected]

---

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: 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: 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)

---

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))

---