spaa (version 0.2.2)

plotlowertri: Plotting lower semi matrix

Description

Function for plotting lower semi matrix. These plots are often used to illustrate the relationship in Pearson's correlation, similarity or dissimilarity index between sites or species.

Usage

plotlowertri(input, valuename = "r", 
pchlist = c(19, 17, 15, 1, 5, 2, 7), interval = 6, 
cex = 1, ncex = 1, int =1.2, add.number = TRUE, 
size = FALSE, add.text = FALSE, show.legend = TRUE, 
digits = 2)

Arguments

input

The input data, often the results of correlation matrix, can also be class dist object.

valuename

Value name that will be used in the legend.

pchlist

The types of point shape to plot see pch par().

interval

Number of intervals to illustrate the shape of points

cex

Point size

ncex

Text size for the add.number, which appeared at the top of each column.

int

Row space between lines in legend

add.number

Species number for each column.

size

Whether the size of points would change according to value.

add.text

To add value to the grid.

show.legend

Whether the legend should be drawn.

digits

Number of digits of for each interval

Value

lower matrix plot

Details

If the matrix contains less than 15 rows/columns, you may have to adjust the row space between the text lines in the legend, using argument int. Data in class dist can be include, and will be converted to matrix at first internally.

The lower matrix plot illustrating Pearson's Correlation between each pair of species. Note some value didn't appeared in the plots, may have appeared the legend. This is due to the distribution of data. Be careful in selection of intervals. In this situation you may set show.legend = FALSE, and add the legend manually. This may be fixed in the future.

References

Zhang Qiaoying, Peng Shaolin, Zhang Sumei, Zhang Yunchun, Hou Yuping.(2008). Association of dormintant species in Guia hill Municipal Park of Macao. Ecology and Environment. 17:1541-1547

See Also

See Also plotnetwork

Examples

data(testdata)
spmatrix <- data2mat(testdata)
result <- sp.pair(spmatrix)

## Check the legend for 0.00 to 0.33 (Unwanted label)
plotlowertri(result$Pearson, int = 0.5, cex=1.5)
title("Pearson Correlation Lower Matrix Plot")

## Change the size of points and reset the intervals.
## Warning: The lower matrix plot illustrating Pearson 
## Correlation between each pair of species. Note the 
## triangle didn't appeared in the plots, but have been 
## added to the legend. This is due to the distribution 
## of data. Be careful in selection of intervals.


plotlowertri(result$Pearson, int = 0.5, cex=1.5, 
interval = 4, pchlist = c(19, 17, 15, 1, 5), size = TRUE)

title("Pearson Correlation Lower Matrix Plot")

## "Pure" dots, may have to add legend manually...
plotlowertri(result$Pearson, int = 0.5, cex=2.5, 
interval = 4, pchlist = rep(19, 5), size = TRUE, 
show.legend = FALSE)

title("Pearson Correlation Lower Matrix Plot")


## Using BCI data
library(vegan)
data(BCI)
## select the top 30 species according to relative frequency.
sub <- sub.sp.matrix(BCI, common = 30)
## Original 
plotlowertri(cor(sub))

## Change size
plotlowertri(cor(sub), size = TRUE, cex = 3)

## Set the digits to 1
plotlowertri(cor(sub), size = TRUE, cex = 3, digits = 1,
ncex = 0.7)