GammafromCTM_test-input-output.Rmd

---
title: "Testing the input and output of Area"
author: "Judith Neve"
date: "20/01/2022"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(CTmeta)
```

This document tests what can be used as input and output for the function Area. Each argument is examined in turn, and at the end some additional checks are done to verify plots can be made for different configurations of the model.

Where the function runs, the output is compared to the expected output.

After every attempt to "break" the function, a diagnostic is written as a comment in the code chunk, and the code chunk is followed by a "to do" list to indicate what needs to be specified/improved/changed in the function documentation or the function itself.

Original example:

```{r}
# library(CTmeta)

## Example 1 ##
#
Drift <- myDrift
#
q <- dim(Drift)[1]
Sigma <- diag(q) # for ease
#
gammafromCTM <- CTmeta::Gamma.fromCTM(Drift, Sigma)
gammafromCTM.mod <- Gamma.fromCTM(Drift, Sigma)

## Example 2: input from fitted object of class "ctsemFit" ##
#
#data <- myData
#if (!require("ctsemFit")) install.packages("ctsemFit")
#library(ctsemFit)
#out_CTM <- ctFit(...)
#Gamma.fromCTM(out_CTM)

#  #
#  if (!require("ctsem")) install.packages("ctsem")
library(ctsem)
library(ctsemOMX)
#  #
library(mlVAR)
# outcome <- list()
# for (s in 1:50) {
#   set.seed(s)
# 
# n <- 5
# t <- 100
# ctfit.data <- matrix(NA, nrow = t*n, ncol = 5)
# ctfit.data[,1] <- rep(1:n, each = t)
# ctfit.data[,2] <- rep(0:(t-1), n)
# ctfit.data[,5] <- 1
# for (i in 0:(n-1)*t) {
#   temp <- simulateVAR(pars = myPhi[1:2,],  means = 0, lags = 1, Nt = t, init = 0, residuals = mySigmaVAR[1:2,], burnin = 100)
#   ctfit.data[(i+1):(i+t), 3] <- temp[,1]
#   ctfit.data[(i+1):(i+t), 4] <- temp[,2]
# }
# 
# colnames(ctfit.data) <- c("idcol", "time", "V1", "V2", "d")
# 
# ctfit.data <- as.data.frame(ctfit.data) %>%
#   pivot_wider(names_from = time,
#               names_prefix = "T",
#               values_from = c("V1", "V2", "d")) %>%
#   select(-idcol, -d_T0)
# 
# colnames(ctfit.data)[(2*t+1):ncol(ctfit.data)] <- paste0("dT", 1:(t-1))
# 
# 
#  model <- ctModel(n.manifest=2, n.latent=2, Tpoints=t, LAMBDA=diag(2),
#                   manifestNames=c('V1', 'V2'),
#                   latentNames=c('V1', 'V2'))
#  out_CTM <- ctFit(dat=ctfit.data, ctmodelobj=model)
# 
#  outcome[[s]] <- Gamma.fromCTM(out_CTM) %>% try()
# }
# set.seed(3)
# 
# n <- 100
# t <- 5
# ctfit.data <- matrix(NA, nrow = t*n, ncol = 5)
# ctfit.data[,1] <- rep(1:n, each = t)
# ctfit.data[,2] <- rep(0:(t-1), n)
# ctfit.data[,5] <- 1
# for (i in 0:(t-1)*n+1) {
#   temp <- simulateVAR(pars = myPhi[1:2,],  means = 0, lags = 1, Nt = t, init = 0, residuals = mySigmaVAR[1:2,], burnin = 100)
#   ctfit.data[i:(i+n-1), 3] <- temp[,1]
#   ctfit.data[i:(i+n-1), 4] <- temp[,2]
# }
# 
# colnames(ctfit.data) <- c("idcol", "time", "V1", "V2", "d")
# 
# library(tidyverse)
# ctfit.data <- as.data.frame(ctfit.data) %>%
#   pivot_wider(names_from = time,
#               names_prefix = "T",
#               values_from = c("V1", "V2", "d")) %>%
#   select(-idcol, -d_T0)
# 
# colnames(ctfit.data)[(2*t+1):ncol(ctfit.data)] <- paste0("dT", 1:(t-1))
# 
# 
#  model <- ctModel(n.manifest=2, n.latent=2, Tpoints=t, LAMBDA=diag(2),
#                   manifestNames=c('V1', 'V2'),
#                   latentNames=c('V1', 'V2'))
#  out_CTM <- ctFit(dat=ctfit.data, ctmodelobj=model)
#  
#  summary(out_CTM)
# 
#  Gamma.fromCTM(out_CTM) %>% try()
 
 
 
if (!require("ctsem")) install.packages("ctsem")
library(ctsem)
library(ctsemOMX)
#
############ adapted from https://rdrr.io/cran/ctsemOMX/man/ctFit.html ############
data(ctExample1)
model <- ctModel(n.manifest=2, n.latent=2, Tpoints=6, LAMBDA=diag(2),
                manifestNames=c('LeisureTime', 'Happiness'),
                latentNames=c('LeisureTime', 'Happiness'), TRAITVAR="auto")
out_CTM <- ctFit(dat=ctExample1, ctmodelobj=model)
##################################################################################
#
Gamma.fromCTM(out_CTM)
```

# Drift

## Drift with NA

```{r}
Drift.break <- Drift
Drift.break[1,2] <- NA

Gamma.fromCTM(Drift = Drift.break, Sigma = Sigma) %>% try()
```

Added an error

## Non-numeric Drift

```{r}
Drift.break <- Drift
Drift.break[1,2] <- "text"

Gamma.fromCTM(Drift = Drift.break, Sigma = Sigma) %>% try()
```

## Drift with one more row

```{r}
Drift.break <- rbind(Drift, c(0,1))

Gamma.fromCTM(Drift = Drift.break, Sigma = Sigma) %>% try()
```

Correct error

## Drift with one more col

```{r}
Drift.break <- cbind(Drift, c(0,1))

Gamma.fromCTM(Drift = Drift.break, Sigma = Sigma) %>% try()
```
Correct error

## Drift with one more row and one more col

```{r}
Drift.break <- matrix(data = c(16, -8, -4, -8, 29, 12, -4, 12, 41), nrow = 3, ncol = 3, byrow = TRUE)

Gamma.fromCTM(Drift = Drift.break, Sigma = Sigma) %>% try()
```

Corrected error so it is about the mismatch of sizes


# Sigma

## Sigma with NA

```{r}
Sigma.break <- Sigma
Sigma.break[1,2] <- NA

Gamma.fromCTM(Drift = Drift, Sigma = Sigma.break) %>% try()
```

It does return something full of NAs - appropriate

## Non-numeric Sigma

```{r}
Sigma.break <- Sigma
Sigma.break[1,2] <- "text"

Gamma.fromCTM(Drift = Drift, Sigma = Sigma.break) %>% try()
```

Made the error be in Check_Sigma.

## Sigma with one more row

```{r}
Sigma.break <- rbind(Sigma, c(1,1))

Gamma.fromCTM(Drift = Drift, Sigma = Sigma.break) %>% try()
```

## Sigma with one more col

```{r}
Sigma.break <- cbind(Sigma, c(1,1))

Gamma.fromCTM(Drift = Drift, Sigma = Sigma.break) %>% try()
```

## Sigma with one more row and one more col

```{r}
Sigma.break <- cbind(rbind(Sigma, c(1,1)), c(1,1,1))

Gamma.fromCTM(Drift = Drift, Sigma = Sigma.break) %>% try()
```