## ----label="data", fig.show='hold', fig.height=4, fig.width=7, warning=FALSE, message=FALSE----
library(PhylogeneticEM)
data(monkeys)

plot(params_BM(p = 2),
     data = monkeys$dat, phylo = monkeys$phy,
     show.tip.label = TRUE, cex = 0.5, no.margin = TRUE)

## ----label="Fit_EM", warning=FALSE, message=FALSE, eval=FALSE-----------------
# res <- PhyloEM(phylo = monkeys$phy,
#                Y_data = monkeys$dat,
#                process = "scOU",                   ## scalar OU model
#                random.root = TRUE,                 ## Root is stationary
#                stationary.root = TRUE,
#                nbr_alpha = 4,                      ## Number of alpha values tested (should be raised)
#                K_max = 10,                         ## Maximal number of shifts
#                parallel_alpha = TRUE,              ## This can be set to TRUE for
#                Ncores = 2)                         ## parallel computations
# res

## ----label="Fit_EM_int", echo=FALSE, warning=FALSE, message=FALSE-------------
res <- PhyloEM(phylo = monkeys$phy,
               Y_data = monkeys$dat,
               process = "scOU",                   ## scalar OU model
               random.root = TRUE,                 ## Root is stationary
               stationary.root = TRUE,
               nbr_alpha = 4,                      ## Number of alpha values tested (should be raised)
               K_max = 10,                         ## Maximal number of shifts
               parallel_alpha = FALSE)              ## This can be set to TRUE for
res

## ----fig.show='hold', fig.height=4, fig.width=7, warning=FALSE----------------
plot(res)

## ----fig.show='hold', fig.height=4, fig.width=4, warning=FALSE----------------
plot_criterion(res)

## ----fig.show='hold', fig.height=4, fig.width=7, warning=FALSE----------------
plot(res, params = params_process(res, K = 5))

## ----echo=FALSE---------------------------------------------------------------
params_5 <- params_process(res, K = 5)

## ----fig.show='hold', fig.height=4, fig.width=8, warning=FALSE----------------
plot(equivalent_shifts(monkeys$phy, params_process(res, K = 5)),
     show_shifts_values = FALSE, shifts_cex = 0.5)

## ----label="Fit_EM_rot", warning=FALSE, message=FALSE, eval = FALSE-----------
# # An arbitrary rotation
# theta <- pi/4
# rot <- matrix(c(cos(theta), -sin(theta), sin(theta), cos(theta)),
#               nrow = 2, ncol = 2)
# 
# # Rotate data
# Yrot <- t(rot) %*% monkeys$dat
# rownames(Yrot) <- rownames(monkeys$dat)
# 
# # PhyloEM on rotated data
# res_rot <- PhyloEM(phylo = monkeys$phy,
#                    Y_data = Yrot,                      ## rotated data
#                    process = "scOU",
#                    random.root = TRUE,
#                    stationary.root = TRUE,
#                    nbr_alpha = 4,
#                    K_max = 10,
#                    parallel_alpha = TRUE,
#                    Ncores = 2)

## ----label="Fit_EM_rot_int", echo=FALSE, warning=FALSE, message=FALSE---------
# An arbitrary rotation
theta <- pi/4
rot <- matrix(c(cos(theta), -sin(theta), sin(theta), cos(theta)),
              nrow = 2, ncol = 2)

# Rotate data
Yrot <- t(rot) %*% monkeys$dat
rownames(Yrot) <- rownames(monkeys$dat)

# PhyloEM on rotated data
res_rot <- PhyloEM(phylo = monkeys$phy,
                   Y_data = Yrot,                      ## rotated data
                   process = "scOU",                   
                   random.root = TRUE,                 
                   stationary.root = TRUE,
                   nbr_alpha = 4,
                   K_max = 10,                         
                   parallel_alpha = FALSE)              

## ----fig.show='hold', fig.height=4, fig.width=7, warning=FALSE----------------
plot(res_rot)

## ----fig.show='hold', fig.height=3, fig.width=3, warning=FALSE----------------
plot(res, params = params_process(res, K = 3), no.margin = TRUE)
plot(res_rot, params = params_process(res, K = 3), no.margin = TRUE)

## ----fig.show='hold', fig.height=4, fig.width=4, warning=FALSE----------------
plot_criterion(res, "log_likelihood")
plot_criterion(res_rot, "log_likelihood", pch = "+", add = TRUE)

## ----fig.show='hold', fig.height=4, fig.width=4, warning=FALSE----------------
plot_criterion(res)
plot_criterion(res_rot, pch = "+", add = TRUE)

## ----label="merge", warning=FALSE---------------------------------------------
res_merge <- merge_rotations(res, res_rot)

## ----fig.show='hold', fig.height=4, fig.width=4, warning=FALSE----------------
plot_criterion(res_merge)

## ----label="Fit_EM_rot2", warning=FALSE, message = FALSE, eval = FALSE--------
# # An other rotation
# theta <- pi/3
# rot2 <- matrix(c(cos(theta), -sin(theta), sin(theta), cos(theta)),
#               nrow = 2, ncol = 2)
# 
# # Rotate data
# Yrot2 <- t(rot2) %*% monkeys$dat
# rownames(Yrot2) <- rownames(monkeys$dat)
# 
# # PhyloEM on rotated data
# res_rot2 <- PhyloEM(phylo = monkeys$phy,
#                    Y_data = Yrot2,
#                    process = "scOU",
#                    random.root = TRUE,
#                    stationary.root = TRUE,
#                    nbr_alpha = 2,           ## Note that this can also be different
#                    K_max = 10,
#                    parallel_alpha = TRUE,
#                    Ncores = 2)
# 
# # Merge
# res_merge2 <- merge_rotations(res, res_rot, res_rot2)

## ----label="Fit_EM_rot2_int", echo=FALSE, warning=FALSE, message=FALSE--------
# An other rotation
theta <- pi/3
rot2 <- matrix(c(cos(theta), -sin(theta), sin(theta), cos(theta)),
              nrow = 2, ncol = 2)

# Rotate data
Yrot2 <- t(rot2) %*% monkeys$dat
rownames(Yrot2) <- rownames(monkeys$dat)

# PhyloEM on rotated data
res_rot2 <- PhyloEM(phylo = monkeys$phy,
                    Y_data = Yrot2,
                    process = "scOU",                   
                    random.root = TRUE,                 
                    stationary.root = TRUE,
                    nbr_alpha = 2,           ## Note that this can also be different
                    K_max = 10,                        
                    parallel_alpha = FALSE)       
# Merge
res_merge2 <- merge_rotations(res, res_rot, res_rot2)

## ----fig.show='hold', fig.height=4, fig.width=4, warning=FALSE----------------
plot_criterion(res_merge2)

## ----label="Fit_EM_negative", warning=FALSE, message = FALSE, eval = FALSE----
# res_neg <- PhyloEM(phylo = monkeys$phy,
#                    Y_data = monkeys$dat,
#                    process = "scOU",
#                    random.root = FALSE,      ## root needs to be fixed
#                    K_max = 10,
#                    parallel_alpha = TRUE,
#                    Ncores = 2,
#                    nbr_alpha = 4,            ## 2 negative, 2 positive (should be more)
#                    allow_negative = TRUE)    ## allow negative alpha in the grid

## ----label="Fit_EM_negative_int", echo=FALSE, warning=FALSE, message=FALSE----
res_neg <- PhyloEM(phylo = monkeys$phy,
                   Y_data = monkeys$dat,
                   process = "scOU",
                   random.root = FALSE,      ## root needs to be fixed
                   K_max = 10,
                   parallel_alpha = FALSE,
                   nbr_alpha = 4,            ## 2 negative, 2 positive (should be more)
                   allow_negative = TRUE)    ## allow negative alpha in the grid      

## -----------------------------------------------------------------------------
params_process(res_neg, K = 0)

## ----fig.show='hold', fig.height=4, fig.width=4, warning=FALSE----------------
plot_criterion(res_neg, "BGHmlraw")

