R/ZZZ_Disjunction_Test_Stimuli_Generator.R
In likanzhan/acqr: Functions Helping You understand Statistics Easily
Defines functions
Generate_Test_Audio
Generate_Test_Image
Generate_Stimuli_List
Disjunction_Generate_Test_Audio
Disjunction_Generate_Test_Image
Disjunction_Generate_Stimuli_List
Documented in
Disjunction_Generate_Stimuli_List
Disjunction_Generate_Test_Audio
Disjunction_Generate_Test_Image
#' import magick
#' import tuneR
#' Generate Test Stimuli List for the Disjunctions and the Modality Experiments
#' @export
Disjunction_Generate_Stimuli_List <- function(...){
Generate_Stimuli_List(...)
}
#' Generate Test Images for the Disjunctions and the Modality Experiments
#' @export
Disjunction_Generate_Test_Image <- function(row, ...) {
invisible(Generate_Test_Image(row, ...))
}
#' Generate Test Audios for the Disjunctions and the Modality Experiments
#' @export
Disjunction_Generate_Test_Audio <- function(row, ...){
invisible(Generate_Test_Audio(row, ...))
}
################################################################################
################################################################################
#### 1. Generate Stimuli List ##################################################
#################################################################################
#################################################################################
Generate_Stimuli_List <- function(
Root_Directory = "~/Desktop/Modality_NEW",
Stimuli_List_Name = "Modailty_Test_Stimuli_List.csv",
Information_File = "Audio_Info.txt",
Animal_Audio_Folder = "Animal_Audios",
Object_Audio_Folder = "Object_Audios",
Animal_Image_Folder = "Animal_Images",
Object_Image_Folder = "Object_Images"
){
#sapply(list.files("Boxes/", pattern = ".pdf$", full.names = TRUE), function(i)magick::image_info(magick::image_read(i))$height/magick::image_info(magick::image_read(i))$width)
#### 1. Define Relevant Dirs #################################################################################
Information_File_Dir <- file.path(Root_Directory, Animal_Audio_Folder, Information_File)
Animal_Audio_Directory <- file.path(Root_Directory, Animal_Audio_Folder)
Object_Audio_Directory <- file.path(Root_Directory, Object_Audio_Folder)
Animal_Image_Directory <- file.path(Root_Directory, Animal_Image_Folder)
Object_Image_Directory <- file.path(Root_Directory, Object_Image_Folder)
Output_File_Directory <- file.path(Root_Directory, Stimuli_List_Name)
#### 2. Establish Box Layouts #################################################################################
Box_Category <- c("First_Mentioned", "Second_Mentioned", "Small_Closed", "Big_Open")
Box_Layout <- acqr::Create_Latin_Square_Matrix(length(Box_Category))
Box_Layout[] <- Box_Category[Box_Layout]
Box_Layout <- as.data.frame(Box_Layout, stringsAsFactors = FALSE)
names(Box_Layout) <- c("Top_Left", "Top_Right", "Bottom_Left", "Bottom_Right")
Box_Layout$Spatial_Order <- paste0(
substr(gsub("_.*$", "", Box_Layout$Top_Left ), 1, 1), substr(gsub(".*_", "", Box_Layout$Top_Left ), 1, 1), "_",
substr(gsub("_.*$", "", Box_Layout$Top_Right ), 1, 1), substr(gsub(".*_", "", Box_Layout$Top_Right ), 1, 1), "_",
substr(gsub("_.*$", "", Box_Layout$Bottom_Left ), 1, 1), substr(gsub(".*_", "", Box_Layout$Bottom_Left ), 1, 1), "_",
substr(gsub("_.*$", "", Box_Layout$Bottom_Right), 1, 1), substr(gsub(".*_", "", Box_Layout$Bottom_Right), 1, 1)
)
##### 3. Retract Information about Audio files ##################################################################
Audio_Names <- read.table(Information_File_Dir, header = TRUE, stringsAsFactors = FALSE)
Audio_Names$Audio_File <- as.character(Audio_Names$Audio_File)
Animal_Audio_Files <- list.files(Animal_Audio_Directory, pattern = ".wav$", full.names = FALSE)
Object_Audio_Files <- list.files(Object_Audio_Directory, pattern = ".wav$", full.names = FALSE)
Audio_Files <- c(Animal_Audio_Files, Object_Audio_Files)
Audio_Files <- gsub("(\\.wav$)|(.*(//))", "", Audio_Files)
Audio_Files <- data.frame(Audio_File = Audio_Files, stringsAsFactors = FALSE)
Audio_Files <- merge(Audio_Files, Audio_Names, all.x = TRUE)
Audio_Files <- Audio_Files[complete.cases(Audio_Files), ]
##### 4. Image files ######################################################################
Animal_Image_Files <- list.files(Animal_Image_Directory, pattern = ".png$", full.names = FALSE)
Object_Image_Files <- list.files(Object_Image_Directory, pattern = ".png$", full.names = FALSE)
Image_Files <- c(Animal_Image_Files, Object_Image_Files)
Image_Files <- gsub("(\\.png$)|(.*(//))", "", Image_Files)
Image_Files <- data.frame(Audio_Content = Image_Files, stringsAsFactors = FALSE)
##### 5. Combine All Files ######################################################################
All_Files <- merge(Audio_Files, Image_Files, all.x = TRUE)
Split_Files <- split(All_Files, All_Files$Category)
##### 6. Create First mentioned and Second Mentioned Animals ########################################
##### 6.1. Animal Category
Animal_First_Mentioned <- Split_Files$Animal
SEED <- acqr::Search_Sample_Seed(1:nrow(Animal_First_Mentioned))
set.seed(SEED)
Animal_Second_Mentioned <- Animal_First_Mentioned[sample(nrow(Animal_First_Mentioned)), ]
names(Animal_First_Mentioned)[1:3] <- paste0("First_Mentioned_", names(Animal_First_Mentioned)[1:3])
names(Animal_Second_Mentioned)[1:3] <- paste0("Second_Mentioned_", names(Animal_Second_Mentioned)[1:3])
Animals <- cbind(Animal_First_Mentioned, Animal_Second_Mentioned)
Animals <- Animals[, unique(names(Animals))]
nrow(Animals[Animals$First_Mentioned_Audio_Content == Animals$Second_Mentioned_Audio_Content, ])
##### 6.2. Object Category
Object_First_Mentioned <- Split_Files$Object[1:85, ]
SEED <- acqr::Search_Sample_Seed(1:nrow(Object_First_Mentioned))
set.seed(SEED)
Object_Second_Mentioned <- Object_First_Mentioned[sample(nrow(Object_First_Mentioned)), ]
names(Object_First_Mentioned)[1:3] <- paste0("First_Mentioned_", names(Object_First_Mentioned)[1:3])
names(Object_Second_Mentioned)[1:3] <- paste0("Second_Mentioned_", names(Object_Second_Mentioned)[1:3])
Objects <- cbind(Object_First_Mentioned, Object_Second_Mentioned)
Objects <- Objects[, unique(names(Objects))]
nrow(Objects[Objects$First_Mentioned_Audio_Content == Objects$Second_Mentioned_Audio_Content, ])
##### 6.3. Combine the two Categories
Combined_Files <- rbind(Animals, Objects)
Combined_Files$Number <- sprintf("T%03d", 1:nrow(Combined_Files))
Combined_Files <- Combined_Files[, c(8, 1:3, 5:7, 4)]
##### 7. Combine File Information and Box_Layouts ########################################
Test_Image_List <- cbind(Combined_Files, Box_Layout)
Test_Image_List$Test_Image <- paste0(Test_Image_List$Number, ".png")
names(Test_Image_List) <- gsub("_Audio_Content", "", names(Test_Image_List))
names(Test_Image_List) <- gsub("_File", "", names(Test_Image_List))
##### 8. ########################################
Sentential_Connectives <- data.frame(Sentential_Connective = c("And", "Or", "But", "Not"), stringsAsFactors = FALSE)
Test_Stimuli_List <- merge(Test_Image_List, Sentential_Connectives)
Test_Stimuli_List <- Test_Stimuli_List[order(Test_Stimuli_List$Number, Test_Stimuli_List$Sentential_Connective), ]
Test_Stimuli_List$Group <- LETTERS[acqr::Create_Latin_Square_Matrix(nrow(Sentential_Connectives))]
Test_Stimuli_List$Test_Audio <- paste0(Test_Stimuli_List$Number, "_", Test_Stimuli_List$Sentential_Connective, ".wav")
##### 9. ########################################
write.csv(Test_Stimuli_List, file = Output_File_Directory, row.names = FALSE)
}
################################################################################
################################################################################
#### 2. Generate Test Images ##################################################
#################################################################################
#################################################################################
Generate_Test_Image <- function(
row,
Add_Grid_Lines = FALSE,
Root_Directory = "~/Desktop/Modality_NEW",
Test_Image_Folder = "Test_Images",
Stimuli_List = "Modailty_Test_Stimuli_List.csv"
){
########## 1. Define the varibles ###################################################################################
suppressMessages(library(magick))
### 1.0. Select the data
Data_File <- read.csv(file.path(Root_Directory, Stimuli_List), stringsAsFactors = FALSE)
Data_File <- Data_File[!duplicated(Data_File$Number), ]
Current_Trial <- Data_File[row, ] #Cols: Top_Left, Top_Right,Bottom_Left, Bottom_Right, Spatial_Order, First_Mentioned, Second_Mentioned
Input_Box_Folder <- "Boxes"
Input_Box_Directory <- file.path(Root_Directory, Input_Box_Folder)
Input_Object_Folder <- paste0(Current_Trial[["Category"]], "_Images")
Input_Object_Directory <- file.path(Root_Directory, Input_Object_Folder)
Output_Image_Directory <- file.path(Root_Directory, Test_Image_Folder)
dir.create(Output_Image_Directory, showWarnings = FALSE)
### 1.1. Define Originals
Grid <- 40 / 3
HL <- c(0, 45, 6 * Grid, 4 * Grid, 8 * Grid, 198, 6 * Grid, 4 * Grid, 8 * Grid, 45)
VL <- c(0, 88, 4 * Grid, 16 * Grid, 4 * Grid, 208, 4 * Grid, 16 * Grid, 4 * Grid, 88)
HP <- cumsum(HL)
VP <- cumsum(VL)
HL_Pos <- (HP[-1] + HP[-length(HP)]) / 2
VL_Pos <- (VP[-1] + VP[-length(VP)]) / 2
### 1.2. Define Box Offsets
Box_Offset_Top_Left <- paste0("+", VP[2], "+", HP[2]) # "+ 88 + 45"
Box_Offset_Top_Right <- paste0("+", VP[6], "+", HP[2]) # "+ 616 + 45"
Box_Offset_Bottom_Right <- paste0("+", VP[6], "+", HP[6]) # "+ 616 + 483"
Box_Offset_Bottom_Left <- paste0("+", VP[2], "+", HP[6]) # "+ 88 + 483"
### 1.3. Define Annotation Offsets
Annotate_Location_A <- paste0("+", - 208/2 - 12 * Grid, "+", - 198/2 - 4 * Grid)
Annotate_Location_B <- paste0("+", + 208/2 + 12 * Grid, "+", - 198/2 - 4 * Grid)
Annotate_Location_C <- paste0("+", - 208/2 - 12 * Grid, "+", + 198/2 + 14 * Grid)
Annotate_Location_D <- paste0("+", + 208/2 + 12 * Grid, "+", + 198/2 + 14 * Grid)
### 1.4. Define Animal Offsets
Spatial_Order <- rep(c("FM_SM_BO_SC", "SM_SC_FM_BO", "SC_BO_SM_FM", "BO_FM_SC_SM"), each = 4)
X_Scale <- list(3:4, 3:4, 3:4, 7:8, 7:8, 7:8, 3:4, 3:4, 7:8, 7:8, 7:8, 3:4, 3:4, 3:4, 7:8, 7:8)
Y_Scale <- list( 6, 6, 2, 2, 6, 6, 6, 2, 2, 2, 6, 6, 2, 2, 2, 6)
Current_Animal <- rep(c("1st_Mentioned_1", "2nd_Mentioned_1", "1st_Mentioned_2", "2nd_Mentioned_2"), 4)
All_Animal_Offsets <- data.frame(
Spatial_Order = Spatial_Order, Current_Animal = Current_Animal,
X_Scale = I(X_Scale), Y_Scale = I(Y_Scale), stringsAsFactors = FALSE)
Current_Trial_Offset <- All_Animal_Offsets[All_Animal_Offsets[, "Spatial_Order"] == Current_Trial[["Spatial_Order"]], ]
Animal_1st_Mentioned_1_X_Offset <- mean(VP[subset(Current_Trial_Offset, Current_Animal=="1st_Mentioned_1")[["X_Scale"]][[1]]]) - 5 - 100
Animal_1st_Mentioned_2_X_Offset <- mean(VP[subset(Current_Trial_Offset, Current_Animal=="1st_Mentioned_2")[["X_Scale"]][[1]]]) - 100/2
Animal_2nd_Mentioned_1_X_Offset <- mean(VP[subset(Current_Trial_Offset, Current_Animal=="2nd_Mentioned_1")[["X_Scale"]][[1]]]) + 5
Animal_2nd_Mentioned_2_X_Offset <- mean(VP[subset(Current_Trial_Offset, Current_Animal=="2nd_Mentioned_2")[["X_Scale"]][[1]]]) - 100/2
Animal_1st_Mentioned_1_Y_Offset <- HP[subset(Current_Trial_Offset, Current_Animal=="1st_Mentioned_1")[["Y_Scale"]][[1]]] + 3 * Grid
Animal_1st_Mentioned_2_Y_Offset <- HP[subset(Current_Trial_Offset, Current_Animal=="1st_Mentioned_2")[["Y_Scale"]][[1]]] + 3 * Grid
Animal_2nd_Mentioned_1_Y_Offset <- HP[subset(Current_Trial_Offset, Current_Animal=="2nd_Mentioned_1")[["Y_Scale"]][[1]]] + 3 * Grid
Animal_2nd_Mentioned_2_Y_Offset <- HP[subset(Current_Trial_Offset, Current_Animal=="2nd_Mentioned_2")[["Y_Scale"]][[1]]] + 3 * Grid
Animal_Offset_FM1 <- paste0("+", Animal_1st_Mentioned_1_X_Offset, "+", Animal_1st_Mentioned_1_Y_Offset)
Animal_Offset_FM2 <- paste0("+", Animal_1st_Mentioned_2_X_Offset, "+", Animal_1st_Mentioned_2_Y_Offset)
Animal_Offset_SM1 <- paste0("+", Animal_2nd_Mentioned_1_X_Offset, "+", Animal_2nd_Mentioned_1_Y_Offset)
Animal_Offset_SM2 <- paste0("+", Animal_2nd_Mentioned_2_X_Offset, "+", Animal_2nd_Mentioned_2_Y_Offset)
########## 2. Define Functions ###################################################################
Read_Box <- function(Box_Name) {
Box_Name <- paste0(Input_Box_Directory, "/", Box_Name, ".pdf")
Load_Box <- magick::image_read(Box_Name, density = 72)
Load_Box <- magick::image_transparent(Load_Box, color = "white") # Remove background
Load_Box <- magick::image_resize(Load_Box, geometry = "320x240")
return(Load_Box)
}
Load_Box <- function(Box_Name) {
Box_Name <- ifelse(Box_Name %in% c("First_Mentioned", "Second_Mentioned"), "Small_Open", Box_Name)
Read_Box(Box_Name)
}
Load_Front <- function(Box_Name) {
Box_Name <- ifelse(Box_Name %in% c("Big_Open", "Big_Closed"), "Big_Front", "Small_Front")
Read_Box(Box_Name)
}
Load_Animal <- function(Animal_Name) {
Animal_File <- paste0(Input_Object_Directory, "/", Animal_Name, ".png")
Animal_Image <- magick::image_read(Animal_File, density = 72)
Animal_Image <- magick::image_resize(Animal_Image, geometry = "100x100")
#Animal_Image <- magick::image_background(Animal_Image, color = "blue")
return(Animal_Image)
}
########## 2. Load Objects ######################################################################
Box_Top_Left <- Load_Box(Current_Trial[["Top_Left"]])
Box_Top_Right <- Load_Box(Current_Trial[["Top_Right"]])
Box_Bottom_Left <- Load_Box(Current_Trial[["Bottom_Left"]])
Box_Bottom_Right <- Load_Box(Current_Trial[["Bottom_Right"]])
Animal_First_Mentioned <- Load_Animal(Current_Trial[["First_Mentioned"]])
Animal_Second_Mentioned <- Load_Animal(Current_Trial[["Second_Mentioned"]])
Front_Top_Left <- Load_Front(Current_Trial[["Top_Left"]])
Front_Top_Right <- Load_Front(Current_Trial[["Top_Right"]])
Front_Bottom_Left <- Load_Front(Current_Trial[["Bottom_Left"]])
Front_Bottom_Right <- Load_Front(Current_Trial[["Bottom_Right"]])
########## 3. Do the Plotting ###################################################################
`%>%` <- magrittr::`%>%`
IMAGE <- magick::image_blank(width = 1024, height = 768, color = "whitesmoke") %>%
magick::image_composite(Box_Top_Left, offset = Box_Offset_Top_Left) %>%
magick::image_composite(Box_Top_Right, offset = Box_Offset_Top_Right) %>%
magick::image_composite(Box_Bottom_Left, offset = Box_Offset_Bottom_Left) %>%
magick::image_composite(Box_Bottom_Right, offset = Box_Offset_Bottom_Right) %>%
magick::image_composite(Animal_First_Mentioned, offset = Animal_Offset_FM1) %>%
magick::image_composite(Animal_Second_Mentioned, offset = Animal_Offset_SM1) %>%
magick::image_composite(Animal_First_Mentioned, offset = Animal_Offset_FM2) %>%
magick::image_composite(Animal_Second_Mentioned, offset = Animal_Offset_SM2) %>%
magick::image_composite(Front_Top_Left, offset = Box_Offset_Top_Left) %>%
magick::image_composite(Front_Top_Right, offset = Box_Offset_Top_Right) %>%
magick::image_composite(Front_Bottom_Left, offset = Box_Offset_Bottom_Left) %>%
magick::image_composite(Front_Bottom_Right, offset = Box_Offset_Bottom_Right) %>%
magick::image_annotate("A", font = "Times", size = 30, gravity = "Center", location = Annotate_Location_A) %>%
magick::image_annotate("B", font = "Times", size = 30, gravity = "Center", location = Annotate_Location_B) %>%
magick::image_annotate("C", font = "Times", size = 30, gravity = "Center", location = Annotate_Location_C) %>%
magick::image_annotate("D", font = "Times", size = 30, gravity = "Center", location = Annotate_Location_D)
if (Add_Grid_Lines) {
Rgh_Size <- 60
Btm_Size <- Rgh_Size / 2
IMAGE_BG <- magick::image_blank(width = 1024 + Rgh_Size, height = 768 + Btm_Size, color = "white")
IMAGE <- magick::image_composite(IMAGE_BG, IMAGE)
IMAGE <- image_draw(IMAGE)
invisible(sapply(HP, function(LL) abline(h = LL, col = 'blue', lwd = 1, lty = "dashed")))
invisible(sapply(VP, function(LL) abline(v = LL, col = 'blue', lwd = 1, lty = "dashed")))
f1 <- function(N)text(1024 + Rgh_Size / 2, HL_Pos[N] , paste0(round(HL[N+1]), "px"), cex = 1)
f2 <- function(N)text(VL_Pos[N] , 768 + Btm_Size / 2, paste0(round(VL[N+1]), "px"), cex = 1)
sapply(1:length(HL_Pos), f1)
sapply(1:length(VL_Pos), f2)
rect(VP[2], HP[2], VP[5], HP[5], border = "red", lwd = 2)
rect(VP[6], HP[2], VP[9], HP[5], border = "red", lwd = 2)
rect(VP[2], HP[6], VP[5], HP[9], border = "red", lwd = 2)
rect(VP[6], HP[6], VP[9], HP[9], border = "red", lwd = 2)
invisible(dev.off())
image_browse(IMAGE)
}
print(Current_Trial[["Number"]])
IMAGE_NAME <- ifelse(Add_Grid_Lines, paste0("Exp_", Current_Trial[["Test_Image"]]), Current_Trial[["Test_Image"]])
image_write(IMAGE, paste0(Output_Image_Directory, "/", IMAGE_NAME), density = 300)
}
################################################################################
################################################################################
#### 3. Generate Test Audios ##################################################
################################################################################
################################################################################
Generate_Test_Audio <- function(
row,
Root_Directory = "~/Desktop/Modality_NEW",
Stimuli_List = "Modailty_Test_Stimuli_List.csv",
Test_Audio_Folder = "Test_Audios",
Animal_Audio_Folder = "Animal_Audios",
Object_Audio_Folder = "Object_Audios",
Shared_Audio_Folder = "Shared_Audios",
Mentioned_Expected_Length = 1400
){
#### 0. Read Information #####################################################################################
library(tuneR)
Data_File <- read.csv(file.path(Root_Directory, Stimuli_List), stringsAsFactors = FALSE)
#### 1. Retract Current Trial ##################################################################################
#### 1.1. Create Output Dir ###############################################################################
Test_Audios_Output_Directory <- file.path(Root_Directory, Test_Audio_Folder)
dir.create(Test_Audios_Output_Directory, showWarnings = FALSE)
#### 1.1. Retract Information ###############################################################################
Current_Trial <- Data_File[row, ]
Current_Trial_Folder <- ifelse(Current_Trial[["Category"]] == "Animal", Animal_Audio_Folder, Object_Audio_Folder)
Current_Sentence_Type <- Current_Trial[["Sentential_Connective"]]
Current_Test_Audio_Name <- Current_Trial[["Test_Audio"]]
#### 2. Define Relevant Functions ##############################################################################
#### 2.1. Load Mentioned Object #############################################################################
Mentioned <- function(Which) {
Mentioned_Name <- paste0(Current_Trial[[paste0(Which, "_Mentioned_Audio")]], ".wav")
Mentioned_File <- file.path(Root_Directory, Current_Trial_Folder, Mentioned_Name)
Mentioned <- tuneR::readWave(Mentioned_File)
Mentioned_Actual_Length <- ((length(Mentioned @ left) / Mentioned @ samp.rate))
Silence_Length <- Mentioned_Expected_Length / 1000 - Mentioned_Actual_Length
if (Silence_Length > 0) {
Slience_Added <- tuneR::silence(Silence_Length, xunit = "time", pcm = TRUE, bit = 16)
Mentioned <- tuneR::bind(Mentioned, Slience_Added)
} else {
Mentioned <- Mentioned
}
#tuneR::play(Mentioned, player = '/usr/bin/afplay')
return(Mentioned)
}
#### 2.2. Load Shared Object #################################################################################
Shared <- function(Name){
Shared_Name <- paste0(Name, ".wav")
Shared_File <- file.path(Root_Directory, Shared_Audio_Folder, Shared_Name)
Shared <- tuneR::readWave(Shared_File)
#tuneR::play(Shared, player = '/usr/bin/afplay')
return(Shared)
}
#### 2.2. Create Current Test Audio############################################################################
Current_Test_Audio <- function(type = c("And", "Or", "But", "Not")) {
switch(match.arg(type),
And = tuneR::bind(XiaoMingDe, XiangZiLi, You , YiZhi, First_Mentioned, He , YiZhi , Second_Mentioned),
Or = tuneR::bind(XiaoMingDe, XiangZiLi, You , YiZhi, First_Mentioned, Huo, YiZhi , Second_Mentioned),
But = tuneR::bind(XiaoMingDe, XiangZiLi, You , YiZhi, First_Mentioned, Dan, MeiYou, Second_Mentioned),
Not = tuneR::bind(XiaoMingDe, XiangZiLi, MeiYou, YiZhi, First_Mentioned, Dan, YouZhi, Second_Mentioned)
)
}
#### 3. Load Objects ###############################################################################################
First_Mentioned <- Mentioned("First")
Second_Mentioned <- Mentioned("Second")
XiaoMingDe <- Shared("XiaoMingDe")
XiangZiLi <- Shared("XiangZiLi")
You <- Shared("You")
MeiYou <- Shared("MeiYou")
YiZhi <- Shared("YiZhi")
Dan <- Shared("Dan")
He <- Shared("He")
Huo <- Shared("Huo")
YouZhi <- Shared("YouZhi")
#### 4. Generate Sentence #######################################################################################
Current_Test_Sentence_Audio <- Current_Test_Audio(Current_Sentence_Type)
#### 5. Write Wave ###########################################################################################
Test_Audios_Output_Name <- file.path(Test_Audios_Output_Directory, Current_Test_Audio_Name)
print(Current_Test_Audio_Name)
tuneR::writeWave(Current_Test_Sentence_Audio, Test_Audios_Output_Name, extensible = FALSE)
}
likanzhan/acqr documentation built on Dec. 2, 2020, 10:14 a.m.
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Defines functions Generate_Test_Audio Generate_Test_Image Generate_Stimuli_List Disjunction_Generate_Test_Audio Disjunction_Generate_Test_Image Disjunction_Generate_Stimuli_List
Documented in Disjunction_Generate_Stimuli_List Disjunction_Generate_Test_Audio Disjunction_Generate_Test_Image
#' import magick
#' import tuneR
#' Generate Test Stimuli List for the Disjunctions and the Modality Experiments
#' @export
Disjunction_Generate_Stimuli_List <- function(...){
Generate_Stimuli_List(...)
}
#' Generate Test Images for the Disjunctions and the Modality Experiments
#' @export
Disjunction_Generate_Test_Image <- function(row, ...) {
invisible(Generate_Test_Image(row, ...))
}
#' Generate Test Audios for the Disjunctions and the Modality Experiments
#' @export
Disjunction_Generate_Test_Audio <- function(row, ...){
invisible(Generate_Test_Audio(row, ...))
}
################################################################################
################################################################################
#### 1. Generate Stimuli List ##################################################
#################################################################################
#################################################################################
Generate_Stimuli_List <- function(
Root_Directory = "~/Desktop/Modality_NEW",
Stimuli_List_Name = "Modailty_Test_Stimuli_List.csv",
Information_File = "Audio_Info.txt",
Animal_Audio_Folder = "Animal_Audios",
Object_Audio_Folder = "Object_Audios",
Animal_Image_Folder = "Animal_Images",
Object_Image_Folder = "Object_Images"
){
#sapply(list.files("Boxes/", pattern = ".pdf$", full.names = TRUE), function(i)magick::image_info(magick::image_read(i))$height/magick::image_info(magick::image_read(i))$width)
#### 1. Define Relevant Dirs #################################################################################
Information_File_Dir <- file.path(Root_Directory, Animal_Audio_Folder, Information_File)
Animal_Audio_Directory <- file.path(Root_Directory, Animal_Audio_Folder)
Object_Audio_Directory <- file.path(Root_Directory, Object_Audio_Folder)
Animal_Image_Directory <- file.path(Root_Directory, Animal_Image_Folder)
Object_Image_Directory <- file.path(Root_Directory, Object_Image_Folder)
Output_File_Directory <- file.path(Root_Directory, Stimuli_List_Name)
#### 2. Establish Box Layouts #################################################################################
Box_Category <- c("First_Mentioned", "Second_Mentioned", "Small_Closed", "Big_Open")
Box_Layout <- acqr::Create_Latin_Square_Matrix(length(Box_Category))
Box_Layout[] <- Box_Category[Box_Layout]
Box_Layout <- as.data.frame(Box_Layout, stringsAsFactors = FALSE)
names(Box_Layout) <- c("Top_Left", "Top_Right", "Bottom_Left", "Bottom_Right")
Box_Layout$Spatial_Order <- paste0(
substr(gsub("_.*$", "", Box_Layout$Top_Left ), 1, 1), substr(gsub(".*_", "", Box_Layout$Top_Left ), 1, 1), "_",
substr(gsub("_.*$", "", Box_Layout$Top_Right ), 1, 1), substr(gsub(".*_", "", Box_Layout$Top_Right ), 1, 1), "_",
substr(gsub("_.*$", "", Box_Layout$Bottom_Left ), 1, 1), substr(gsub(".*_", "", Box_Layout$Bottom_Left ), 1, 1), "_",
substr(gsub("_.*$", "", Box_Layout$Bottom_Right), 1, 1), substr(gsub(".*_", "", Box_Layout$Bottom_Right), 1, 1)
)
##### 3. Retract Information about Audio files ##################################################################
Audio_Names <- read.table(Information_File_Dir, header = TRUE, stringsAsFactors = FALSE)
Audio_Names$Audio_File <- as.character(Audio_Names$Audio_File)
Animal_Audio_Files <- list.files(Animal_Audio_Directory, pattern = ".wav$", full.names = FALSE)
Object_Audio_Files <- list.files(Object_Audio_Directory, pattern = ".wav$", full.names = FALSE)
Audio_Files <- c(Animal_Audio_Files, Object_Audio_Files)
Audio_Files <- gsub("(\\.wav$)|(.*(//))", "", Audio_Files)
Audio_Files <- data.frame(Audio_File = Audio_Files, stringsAsFactors = FALSE)
Audio_Files <- merge(Audio_Files, Audio_Names, all.x = TRUE)
Audio_Files <- Audio_Files[complete.cases(Audio_Files), ]
##### 4. Image files ######################################################################
Animal_Image_Files <- list.files(Animal_Image_Directory, pattern = ".png$", full.names = FALSE)
Object_Image_Files <- list.files(Object_Image_Directory, pattern = ".png$", full.names = FALSE)
Image_Files <- c(Animal_Image_Files, Object_Image_Files)
Image_Files <- gsub("(\\.png$)|(.*(//))", "", Image_Files)
Image_Files <- data.frame(Audio_Content = Image_Files, stringsAsFactors = FALSE)
##### 5. Combine All Files ######################################################################
All_Files <- merge(Audio_Files, Image_Files, all.x = TRUE)
Split_Files <- split(All_Files, All_Files$Category)
##### 6. Create First mentioned and Second Mentioned Animals ########################################
##### 6.1. Animal Category
Animal_First_Mentioned <- Split_Files$Animal
SEED <- acqr::Search_Sample_Seed(1:nrow(Animal_First_Mentioned))
set.seed(SEED)
Animal_Second_Mentioned <- Animal_First_Mentioned[sample(nrow(Animal_First_Mentioned)), ]
names(Animal_First_Mentioned)[1:3] <- paste0("First_Mentioned_", names(Animal_First_Mentioned)[1:3])
names(Animal_Second_Mentioned)[1:3] <- paste0("Second_Mentioned_", names(Animal_Second_Mentioned)[1:3])
Animals <- cbind(Animal_First_Mentioned, Animal_Second_Mentioned)
Animals <- Animals[, unique(names(Animals))]
nrow(Animals[Animals$First_Mentioned_Audio_Content == Animals$Second_Mentioned_Audio_Content, ])
##### 6.2. Object Category
Object_First_Mentioned <- Split_Files$Object[1:85, ]
SEED <- acqr::Search_Sample_Seed(1:nrow(Object_First_Mentioned))
set.seed(SEED)
Object_Second_Mentioned <- Object_First_Mentioned[sample(nrow(Object_First_Mentioned)), ]
names(Object_First_Mentioned)[1:3] <- paste0("First_Mentioned_", names(Object_First_Mentioned)[1:3])
names(Object_Second_Mentioned)[1:3] <- paste0("Second_Mentioned_", names(Object_Second_Mentioned)[1:3])
Objects <- cbind(Object_First_Mentioned, Object_Second_Mentioned)
Objects <- Objects[, unique(names(Objects))]
nrow(Objects[Objects$First_Mentioned_Audio_Content == Objects$Second_Mentioned_Audio_Content, ])
##### 6.3. Combine the two Categories
Combined_Files <- rbind(Animals, Objects)
Combined_Files$Number <- sprintf("T%03d", 1:nrow(Combined_Files))
Combined_Files <- Combined_Files[, c(8, 1:3, 5:7, 4)]
##### 7. Combine File Information and Box_Layouts ########################################
Test_Image_List <- cbind(Combined_Files, Box_Layout)
Test_Image_List$Test_Image <- paste0(Test_Image_List$Number, ".png")
names(Test_Image_List) <- gsub("_Audio_Content", "", names(Test_Image_List))
names(Test_Image_List) <- gsub("_File", "", names(Test_Image_List))
##### 8. ########################################
Sentential_Connectives <- data.frame(Sentential_Connective = c("And", "Or", "But", "Not"), stringsAsFactors = FALSE)
Test_Stimuli_List <- merge(Test_Image_List, Sentential_Connectives)
Test_Stimuli_List <- Test_Stimuli_List[order(Test_Stimuli_List$Number, Test_Stimuli_List$Sentential_Connective), ]
Test_Stimuli_List$Group <- LETTERS[acqr::Create_Latin_Square_Matrix(nrow(Sentential_Connectives))]
Test_Stimuli_List$Test_Audio <- paste0(Test_Stimuli_List$Number, "_", Test_Stimuli_List$Sentential_Connective, ".wav")
##### 9. ########################################
write.csv(Test_Stimuli_List, file = Output_File_Directory, row.names = FALSE)
}
################################################################################
################################################################################
#### 2. Generate Test Images ##################################################
#################################################################################
#################################################################################
Generate_Test_Image <- function(
row,
Add_Grid_Lines = FALSE,
Root_Directory = "~/Desktop/Modality_NEW",
Test_Image_Folder = "Test_Images",
Stimuli_List = "Modailty_Test_Stimuli_List.csv"
){
########## 1. Define the varibles ###################################################################################
suppressMessages(library(magick))
### 1.0. Select the data
Data_File <- read.csv(file.path(Root_Directory, Stimuli_List), stringsAsFactors = FALSE)
Data_File <- Data_File[!duplicated(Data_File$Number), ]
Current_Trial <- Data_File[row, ] #Cols: Top_Left, Top_Right,Bottom_Left, Bottom_Right, Spatial_Order, First_Mentioned, Second_Mentioned
Input_Box_Folder <- "Boxes"
Input_Box_Directory <- file.path(Root_Directory, Input_Box_Folder)
Input_Object_Folder <- paste0(Current_Trial[["Category"]], "_Images")
Input_Object_Directory <- file.path(Root_Directory, Input_Object_Folder)
Output_Image_Directory <- file.path(Root_Directory, Test_Image_Folder)
dir.create(Output_Image_Directory, showWarnings = FALSE)
### 1.1. Define Originals
Grid <- 40 / 3
HL <- c(0, 45, 6 * Grid, 4 * Grid, 8 * Grid, 198, 6 * Grid, 4 * Grid, 8 * Grid, 45)
VL <- c(0, 88, 4 * Grid, 16 * Grid, 4 * Grid, 208, 4 * Grid, 16 * Grid, 4 * Grid, 88)
HP <- cumsum(HL)
VP <- cumsum(VL)
HL_Pos <- (HP[-1] + HP[-length(HP)]) / 2
VL_Pos <- (VP[-1] + VP[-length(VP)]) / 2
### 1.2. Define Box Offsets
Box_Offset_Top_Left <- paste0("+", VP[2], "+", HP[2]) # "+ 88 + 45"
Box_Offset_Top_Right <- paste0("+", VP[6], "+", HP[2]) # "+ 616 + 45"
Box_Offset_Bottom_Right <- paste0("+", VP[6], "+", HP[6]) # "+ 616 + 483"
Box_Offset_Bottom_Left <- paste0("+", VP[2], "+", HP[6]) # "+ 88 + 483"
### 1.3. Define Annotation Offsets
Annotate_Location_A <- paste0("+", - 208/2 - 12 * Grid, "+", - 198/2 - 4 * Grid)
Annotate_Location_B <- paste0("+", + 208/2 + 12 * Grid, "+", - 198/2 - 4 * Grid)
Annotate_Location_C <- paste0("+", - 208/2 - 12 * Grid, "+", + 198/2 + 14 * Grid)
Annotate_Location_D <- paste0("+", + 208/2 + 12 * Grid, "+", + 198/2 + 14 * Grid)
### 1.4. Define Animal Offsets
Spatial_Order <- rep(c("FM_SM_BO_SC", "SM_SC_FM_BO", "SC_BO_SM_FM", "BO_FM_SC_SM"), each = 4)
X_Scale <- list(3:4, 3:4, 3:4, 7:8, 7:8, 7:8, 3:4, 3:4, 7:8, 7:8, 7:8, 3:4, 3:4, 3:4, 7:8, 7:8)
Y_Scale <- list( 6, 6, 2, 2, 6, 6, 6, 2, 2, 2, 6, 6, 2, 2, 2, 6)
Current_Animal <- rep(c("1st_Mentioned_1", "2nd_Mentioned_1", "1st_Mentioned_2", "2nd_Mentioned_2"), 4)
All_Animal_Offsets <- data.frame(
Spatial_Order = Spatial_Order, Current_Animal = Current_Animal,
X_Scale = I(X_Scale), Y_Scale = I(Y_Scale), stringsAsFactors = FALSE)
Current_Trial_Offset <- All_Animal_Offsets[All_Animal_Offsets[, "Spatial_Order"] == Current_Trial[["Spatial_Order"]], ]
Animal_1st_Mentioned_1_X_Offset <- mean(VP[subset(Current_Trial_Offset, Current_Animal=="1st_Mentioned_1")[["X_Scale"]][[1]]]) - 5 - 100
Animal_1st_Mentioned_2_X_Offset <- mean(VP[subset(Current_Trial_Offset, Current_Animal=="1st_Mentioned_2")[["X_Scale"]][[1]]]) - 100/2
Animal_2nd_Mentioned_1_X_Offset <- mean(VP[subset(Current_Trial_Offset, Current_Animal=="2nd_Mentioned_1")[["X_Scale"]][[1]]]) + 5
Animal_2nd_Mentioned_2_X_Offset <- mean(VP[subset(Current_Trial_Offset, Current_Animal=="2nd_Mentioned_2")[["X_Scale"]][[1]]]) - 100/2
Animal_1st_Mentioned_1_Y_Offset <- HP[subset(Current_Trial_Offset, Current_Animal=="1st_Mentioned_1")[["Y_Scale"]][[1]]] + 3 * Grid
Animal_1st_Mentioned_2_Y_Offset <- HP[subset(Current_Trial_Offset, Current_Animal=="1st_Mentioned_2")[["Y_Scale"]][[1]]] + 3 * Grid
Animal_2nd_Mentioned_1_Y_Offset <- HP[subset(Current_Trial_Offset, Current_Animal=="2nd_Mentioned_1")[["Y_Scale"]][[1]]] + 3 * Grid
Animal_2nd_Mentioned_2_Y_Offset <- HP[subset(Current_Trial_Offset, Current_Animal=="2nd_Mentioned_2")[["Y_Scale"]][[1]]] + 3 * Grid
Animal_Offset_FM1 <- paste0("+", Animal_1st_Mentioned_1_X_Offset, "+", Animal_1st_Mentioned_1_Y_Offset)
Animal_Offset_FM2 <- paste0("+", Animal_1st_Mentioned_2_X_Offset, "+", Animal_1st_Mentioned_2_Y_Offset)
Animal_Offset_SM1 <- paste0("+", Animal_2nd_Mentioned_1_X_Offset, "+", Animal_2nd_Mentioned_1_Y_Offset)
Animal_Offset_SM2 <- paste0("+", Animal_2nd_Mentioned_2_X_Offset, "+", Animal_2nd_Mentioned_2_Y_Offset)
########## 2. Define Functions ###################################################################
Read_Box <- function(Box_Name) {
Box_Name <- paste0(Input_Box_Directory, "/", Box_Name, ".pdf")
Load_Box <- magick::image_read(Box_Name, density = 72)
Load_Box <- magick::image_transparent(Load_Box, color = "white") # Remove background
Load_Box <- magick::image_resize(Load_Box, geometry = "320x240")
return(Load_Box)
}
Load_Box <- function(Box_Name) {
Box_Name <- ifelse(Box_Name %in% c("First_Mentioned", "Second_Mentioned"), "Small_Open", Box_Name)
Read_Box(Box_Name)
}
Load_Front <- function(Box_Name) {
Box_Name <- ifelse(Box_Name %in% c("Big_Open", "Big_Closed"), "Big_Front", "Small_Front")
Read_Box(Box_Name)
}
Load_Animal <- function(Animal_Name) {
Animal_File <- paste0(Input_Object_Directory, "/", Animal_Name, ".png")
Animal_Image <- magick::image_read(Animal_File, density = 72)
Animal_Image <- magick::image_resize(Animal_Image, geometry = "100x100")
#Animal_Image <- magick::image_background(Animal_Image, color = "blue")
return(Animal_Image)
}
########## 2. Load Objects ######################################################################
Box_Top_Left <- Load_Box(Current_Trial[["Top_Left"]])
Box_Top_Right <- Load_Box(Current_Trial[["Top_Right"]])
Box_Bottom_Left <- Load_Box(Current_Trial[["Bottom_Left"]])
Box_Bottom_Right <- Load_Box(Current_Trial[["Bottom_Right"]])
Animal_First_Mentioned <- Load_Animal(Current_Trial[["First_Mentioned"]])
Animal_Second_Mentioned <- Load_Animal(Current_Trial[["Second_Mentioned"]])
Front_Top_Left <- Load_Front(Current_Trial[["Top_Left"]])
Front_Top_Right <- Load_Front(Current_Trial[["Top_Right"]])
Front_Bottom_Left <- Load_Front(Current_Trial[["Bottom_Left"]])
Front_Bottom_Right <- Load_Front(Current_Trial[["Bottom_Right"]])
########## 3. Do the Plotting ###################################################################
`%>%` <- magrittr::`%>%`
IMAGE <- magick::image_blank(width = 1024, height = 768, color = "whitesmoke") %>%
magick::image_composite(Box_Top_Left, offset = Box_Offset_Top_Left) %>%
magick::image_composite(Box_Top_Right, offset = Box_Offset_Top_Right) %>%
magick::image_composite(Box_Bottom_Left, offset = Box_Offset_Bottom_Left) %>%
magick::image_composite(Box_Bottom_Right, offset = Box_Offset_Bottom_Right) %>%
magick::image_composite(Animal_First_Mentioned, offset = Animal_Offset_FM1) %>%
magick::image_composite(Animal_Second_Mentioned, offset = Animal_Offset_SM1) %>%
magick::image_composite(Animal_First_Mentioned, offset = Animal_Offset_FM2) %>%
magick::image_composite(Animal_Second_Mentioned, offset = Animal_Offset_SM2) %>%
magick::image_composite(Front_Top_Left, offset = Box_Offset_Top_Left) %>%
magick::image_composite(Front_Top_Right, offset = Box_Offset_Top_Right) %>%
magick::image_composite(Front_Bottom_Left, offset = Box_Offset_Bottom_Left) %>%
magick::image_composite(Front_Bottom_Right, offset = Box_Offset_Bottom_Right) %>%
magick::image_annotate("A", font = "Times", size = 30, gravity = "Center", location = Annotate_Location_A) %>%
magick::image_annotate("B", font = "Times", size = 30, gravity = "Center", location = Annotate_Location_B) %>%
magick::image_annotate("C", font = "Times", size = 30, gravity = "Center", location = Annotate_Location_C) %>%
magick::image_annotate("D", font = "Times", size = 30, gravity = "Center", location = Annotate_Location_D)
if (Add_Grid_Lines) {
Rgh_Size <- 60
Btm_Size <- Rgh_Size / 2
IMAGE_BG <- magick::image_blank(width = 1024 + Rgh_Size, height = 768 + Btm_Size, color = "white")
IMAGE <- magick::image_composite(IMAGE_BG, IMAGE)
IMAGE <- image_draw(IMAGE)
invisible(sapply(HP, function(LL) abline(h = LL, col = 'blue', lwd = 1, lty = "dashed")))
invisible(sapply(VP, function(LL) abline(v = LL, col = 'blue', lwd = 1, lty = "dashed")))
f1 <- function(N)text(1024 + Rgh_Size / 2, HL_Pos[N] , paste0(round(HL[N+1]), "px"), cex = 1)
f2 <- function(N)text(VL_Pos[N] , 768 + Btm_Size / 2, paste0(round(VL[N+1]), "px"), cex = 1)
sapply(1:length(HL_Pos), f1)
sapply(1:length(VL_Pos), f2)
rect(VP[2], HP[2], VP[5], HP[5], border = "red", lwd = 2)
rect(VP[6], HP[2], VP[9], HP[5], border = "red", lwd = 2)
rect(VP[2], HP[6], VP[5], HP[9], border = "red", lwd = 2)
rect(VP[6], HP[6], VP[9], HP[9], border = "red", lwd = 2)
invisible(dev.off())
image_browse(IMAGE)
}
print(Current_Trial[["Number"]])
IMAGE_NAME <- ifelse(Add_Grid_Lines, paste0("Exp_", Current_Trial[["Test_Image"]]), Current_Trial[["Test_Image"]])
image_write(IMAGE, paste0(Output_Image_Directory, "/", IMAGE_NAME), density = 300)
}
################################################################################
################################################################################
#### 3. Generate Test Audios ##################################################
################################################################################
################################################################################
Generate_Test_Audio <- function(
row,
Root_Directory = "~/Desktop/Modality_NEW",
Stimuli_List = "Modailty_Test_Stimuli_List.csv",
Test_Audio_Folder = "Test_Audios",
Animal_Audio_Folder = "Animal_Audios",
Object_Audio_Folder = "Object_Audios",
Shared_Audio_Folder = "Shared_Audios",
Mentioned_Expected_Length = 1400
){
#### 0. Read Information #####################################################################################
library(tuneR)
Data_File <- read.csv(file.path(Root_Directory, Stimuli_List), stringsAsFactors = FALSE)
#### 1. Retract Current Trial ##################################################################################
#### 1.1. Create Output Dir ###############################################################################
Test_Audios_Output_Directory <- file.path(Root_Directory, Test_Audio_Folder)
dir.create(Test_Audios_Output_Directory, showWarnings = FALSE)
#### 1.1. Retract Information ###############################################################################
Current_Trial <- Data_File[row, ]
Current_Trial_Folder <- ifelse(Current_Trial[["Category"]] == "Animal", Animal_Audio_Folder, Object_Audio_Folder)
Current_Sentence_Type <- Current_Trial[["Sentential_Connective"]]
Current_Test_Audio_Name <- Current_Trial[["Test_Audio"]]
#### 2. Define Relevant Functions ##############################################################################
#### 2.1. Load Mentioned Object #############################################################################
Mentioned <- function(Which) {
Mentioned_Name <- paste0(Current_Trial[[paste0(Which, "_Mentioned_Audio")]], ".wav")
Mentioned_File <- file.path(Root_Directory, Current_Trial_Folder, Mentioned_Name)
Mentioned <- tuneR::readWave(Mentioned_File)
Mentioned_Actual_Length <- ((length(Mentioned @ left) / Mentioned @ samp.rate))
Silence_Length <- Mentioned_Expected_Length / 1000 - Mentioned_Actual_Length
if (Silence_Length > 0) {
Slience_Added <- tuneR::silence(Silence_Length, xunit = "time", pcm = TRUE, bit = 16)
Mentioned <- tuneR::bind(Mentioned, Slience_Added)
} else {
Mentioned <- Mentioned
}
#tuneR::play(Mentioned, player = '/usr/bin/afplay')
return(Mentioned)
}
#### 2.2. Load Shared Object #################################################################################
Shared <- function(Name){
Shared_Name <- paste0(Name, ".wav")
Shared_File <- file.path(Root_Directory, Shared_Audio_Folder, Shared_Name)
Shared <- tuneR::readWave(Shared_File)
#tuneR::play(Shared, player = '/usr/bin/afplay')
return(Shared)
}
#### 2.2. Create Current Test Audio############################################################################
Current_Test_Audio <- function(type = c("And", "Or", "But", "Not")) {
switch(match.arg(type),
And = tuneR::bind(XiaoMingDe, XiangZiLi, You , YiZhi, First_Mentioned, He , YiZhi , Second_Mentioned),
Or = tuneR::bind(XiaoMingDe, XiangZiLi, You , YiZhi, First_Mentioned, Huo, YiZhi , Second_Mentioned),
But = tuneR::bind(XiaoMingDe, XiangZiLi, You , YiZhi, First_Mentioned, Dan, MeiYou, Second_Mentioned),
Not = tuneR::bind(XiaoMingDe, XiangZiLi, MeiYou, YiZhi, First_Mentioned, Dan, YouZhi, Second_Mentioned)
)
}
#### 3. Load Objects ###############################################################################################
First_Mentioned <- Mentioned("First")
Second_Mentioned <- Mentioned("Second")
XiaoMingDe <- Shared("XiaoMingDe")
XiangZiLi <- Shared("XiangZiLi")
You <- Shared("You")
MeiYou <- Shared("MeiYou")
YiZhi <- Shared("YiZhi")
Dan <- Shared("Dan")
He <- Shared("He")
Huo <- Shared("Huo")
YouZhi <- Shared("YouZhi")
#### 4. Generate Sentence #######################################################################################
Current_Test_Sentence_Audio <- Current_Test_Audio(Current_Sentence_Type)
#### 5. Write Wave ###########################################################################################
Test_Audios_Output_Name <- file.path(Test_Audios_Output_Directory, Current_Test_Audio_Name)
print(Current_Test_Audio_Name)
tuneR::writeWave(Current_Test_Sentence_Audio, Test_Audios_Output_Name, extensible = FALSE)
}
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