# Generate a graphs showing correlation matrix (lower semi matrix) (Deprecated)

`plotlowertri.Rd`

Generate graphs (lower semi matrix) showing lower semi matrix. These graphs are often used to show the structure of a correlation, similarity or dissimilarity matrix.

    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`, often a correlation or a distance matrix.
valuename | Name of the value that to show in the legend.
pchlist | A numberic vector specifying the shapes of points, see `pch par()`.
interval | Types of point shapes to show
cex | A number specifying the text size in the legend
ncex | Size of the text shown above each column.
int | Space between lines within the legend
add.number | If the column number should be shown
size | Whether the size of points should change with the value
add.text | Logical, If the number should be shown in the grid.
show.legend | Logical, If the legend should be appear.
digits | Number of digits for the label of each interval.

## Details

In the legend, space between lines could be adjusted by specifying `int`.

## Value

lower matrix plot

## 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

## Author

Jinlong Zhang jinlongzhang01@gmail.com

## 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)
    #> Warning: Too few rows, please adjust the legend using "cex" and "int".
    #>  Some of the points may be missing due to the distribution of data.
    #>  You may also have to choose an appropriate number of intervals
    #>  using "interval" and "pchlist".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)
    #> Warning: Too few rows, please adjust the legend using "cex" and "int".
    #>  Some of the points may be missing due to the distribution of data.
    #>  You may also have to choose an appropriate number of intervals
    #>  using "interval" and "pchlist".
    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)
    #> Warning: Too few rows, please adjust the legend using "cex" and "int".
    #>  Some of the points may be missing due to the distribution of data.
    #>  You may also have to choose an appropriate number of intervals
    #>  using "interval" and "pchlist".
    title("Pearson Correlation Lower Matrix Plot")

    ## Using BCI data
    library(vegan)
    #> Loading required package: permute#> Loading required package: lattice#> This is vegan 2.5-7data(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)