plotEigenvalues {cfda} R Documentation

## Plot Eigenvalues

Plot Eigenvalues

### Usage

```plotEigenvalues(x, cumulative = FALSE, normalize = FALSE, ...)
```

### Arguments

 `x` output of `compute_optimal_encoding` function `cumulative` if TRUE, plot the cumualtive eigenvalues `normalize` if TRUE eigenvalues are normalized for summing to 1 `...` `geom_point` parameters

### Value

a `ggplot` object that can be modified using `ggplot2` package.

### Author(s)

Quentin Grimonprez

### Examples

```# Simulate the Jukes-Cantor model of nucleotide replacement
K <- 4
Tmax <- 6
PJK <- matrix(1/3, nrow = K, ncol = K) - diag(rep(1/3, K))
lambda_PJK <- c(1, 1, 1, 1)
d_JK <- generate_Markov(n = 10, K = K, P = PJK, lambda = lambda_PJK, Tmax = Tmax)
d_JK2 <- cut_data(d_JK, Tmax)

# create basis object
m <- 6
b <- create.bspline.basis(c(0, Tmax), nbasis = m, norder = 4)

# compute encoding
encoding <- compute_optimal_encoding(d_JK2, b, computeCI = FALSE, nCores = 1)

# plot eigenvalues
plotEigenvalues(encoding, cumulative = TRUE, normalize = TRUE)

# modify the plot using ggplot2
library(ggplot2)
plotEigenvalues(encoding, shape = 23) +
labs(caption = "Jukes-Cantor model of nucleotide replacement")

```

[Package cfda version 0.9.9 Index]