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245 changes: 245 additions & 0 deletions finalprojectcode.Rmd
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---
title: "Trial and Emotion Data Analysis"
output: html_notebook
---

```{r}
trial_data2 <- read_csv("C:/Users/huifa/Desktop/BCB Research/trial_data2.csv")
trial_data2 $ error <- trial_data2 $ actualDiff - trial_data2 $ input
trial_data2 $ absError = abs(trial_data2 $ error)
trial_data2 $ logError <- log2(abs(trial_data2 $ input - trial_data2 $ actualDiff) + 1/8)
trial_data2 $ logError <- abs(trial_data2 $ logError)
trial_data2 $ logError[trial_data2 $ logError == 3] <- 0
d <- ggplot(trial_data2, aes(chartType, logError)) + geom_point()
d + stat_summary(fun.data = "mean_cl_boot", colour = "red", size = .55) + facet_wrap(~key, ncol = 1) +
labs(title ="Log Mean Error Across Participants", subtitle="June 26, 2017 to July 28, 2017") +
theme_bw()
ggsave("trials.pdf", width = 4, height = 10, units = "in")
```

Emotion Charts Faceted by Participant
```{r}
library(tidyverse)
library(devtools)
library(ggplot2)

emo <- read.csv('C:/Users/huifa/Desktop/BCB Research/emotion_data2.csv', header=TRUE)
emo2 <- emo %>%
gather(
`emotions_joy`,
`emotions_sadness`,
`emotions_disgust`,
`emotions_contempt`,
`emotions_anger`,
`emotions_fear`,
`emotions_surprise`,
`emotions_valence`,
`emotions_engagement`,
key = "emotion",
value = "value") %>%
select(emotion, value, time, key)
ggplot(emo2) +
geom_line(aes(x=time, y=value, colour=emotion)) +
facet_wrap(~ key, ncol=1) +
labs(title ="Affectiva Emotions Across Participants", subtitle="June 26, 2017 to July 28, 2017") +
theme_bw()
ggsave("emotions.pdf", width = 20, height = 10, units = "in")
```

Survey Data Charts
```{r}
survey <- read.csv('C:/Users/huifa/Desktop/BCB Research/survey_data.csv', header=TRUE)

survey2 <- survey %>%
gather(
`joy`,
`sadness`,
`disgust`,
`contempt`,
`anger`,
`fear`,
`surprise`,
`valence`,
`engagement`,
key = "emotion",
value = "value") %>%
select(emotion, value, time, key)

ggplot(survey2, aes(x=emotion, y=value, fill=emotion)) + geom_bar(stat="identity") + facet_wrap(~ key, ncol=2) +
labs(title ="Survey Responses From Participants", subtitle="June 26, 2017 to July 28, 2017") +
theme_bw()

ggsave("survey.pdf", width = 16, height = 10, units = "in")

```

Bar Chart for Emotions
```{r}
emo <- read.csv('C:/Users/huifa/Desktop/BCB Research/emotion_data2.csv', header=TRUE)

emo$joy <- mean(emo$emotions_joy) / 100000 * 1.5
emo$sadness <- mean(emo$emotions_sadness)/100000* 1.5
emo$disgust <- mean(emo$emotions_disgust)/100000* 1.5
emo$contempt <- mean(emo$emotions_contempt)/100000* 1.5
emo$anger <- mean(emo$emotions_anger)/100000* 1.5
emo$fear <- mean(emo$emotions_fear)/100000* 1.5
emo$surprise <- mean(emo$emotions_surprise)/100000* 1.5
emo$valence <- mean(emo$emotions_valence)/ 100000* 1.5
emo$engagement <- mean(emo$emotions_engagement)/ 100000* 1.5

emo2 <- emo %>%
gather(
`joy`,
`sadness`,
`disgust`,
`contempt`,
`anger`,
`fear`,
`surprise`,
`valence`,
`engagement`,
key = "emotion",
value = "value") %>%
select(emotion, value, time, key)

ggplot(emo2) +
geom_bar(aes(x=emotion, y=value, fill=emotion), stat = "identity") +
facet_wrap(~ key, ncol=2) +
labs(title ="Mean Affectiva Emotions Across Participants", subtitle="June 26, 2017 to July 28, 2017") +
theme_bw()

ggsave("barchart.pdf", width = 14, height = 20, units = "in")
```

Negative Emotions Graphed
```{r}
library(tidyverse)
library(devtools)
library(ggplot2)

emo <- read.csv('C:/Users/huifa/Desktop/BCB Research/emotion_data2.csv', header=TRUE)
emo2 <- emo %>%
gather(
`emotions_sadness`,
`emotions_disgust`,
`emotions_contempt`,
`emotions_anger`,
`emotions_fear`,
key = "emotion",
value = "value") %>%
select(emotion, value, time, key)
ggplot(emo2) +
geom_line(aes(x=time, y=value, colour=emotion)) +
facet_wrap(~ key, ncol=1) +
labs(title ="Negative Affectiva Emotions Across Participants", subtitle="June 26, 2017 to July 28, 2017") +
theme_bw()
ggsave("emotionsneg.pdf", width = 20, height = 9, units = "in")
```

Positive Emotions Graphed
```{r}
library(tidyverse)
library(devtools)
library(ggplot2)

emo <- read.csv('C:/Users/huifa/Desktop/BCB Research/emotion_data2.csv', header=TRUE)
emo2 <- emo %>%
gather(
`emotions_joy`,
`emotions_surprise`,
key = "emotion",
value = "value") %>%
select(emotion, value, time, key)
ggplot(emo2) +
geom_line(aes(x=time, y=value, colour=emotion)) +
facet_wrap(~ key, ncol=1) +
labs(title ="Positive Affectiva Emotions Across Participants", subtitle="June 26, 2017 to July 28, 2017") +
theme_bw()
ggsave("emotionspos.pdf", width = 20, height = 10, units = "in")
```

Engagement and Valence Graphed
```{r}
library(tidyverse)
library(devtools)
library(ggplot2)

emo <- read.csv('C:/Users/huifa/Desktop/BCB Research/emotion_data2.csv', header=TRUE)
emo2 <- emo %>%
gather(
`emotions_valence`,
`emotions_engagement`,
key = "emotion",
value = "value") %>%
select(emotion, value, time, key)
ggplot(emo2) +
geom_line(aes(x=time, y=value, colour=emotion)) +
facet_wrap(~ key, ncol=1) +
labs(title ="Valence and Engagement Across Participants", subtitle="June 26, 2017 to July 28, 2017") +
theme_bw()
ggsave("emotionsvalandeng.pdf", width = 20, height = 9, units = "in")
```
Error Mean Values
```{r}
trial_data2 <- read_csv("C:/Users/huifa/Desktop/BCB Research/trial_data2.csv")

data_3_participants $ actualDifference <- as.numeric(as.character(data_3_participants $ actualDifference))
data_3_participants $ input <- as.numeric(as.character(data_3_participants $ input))

trial_data2 $ error <- trial_data2 $ actualDiff - trial_data2 $ input
trial_data2 $ absError = abs(trial_data2 $ error)
trial_data2 $ logError <- log2(abs(trial_data2 $ input - trial_data2 $ actualDiff) + 1/8)
trial_data2 $ logError <- abs(trial_data2 $ logError)
trial_data2 $ logError[trial_data2 $ logError == 3] <- 0

mean(trial_data2 $ logError)
```

Mean Negative Emotions
```{r}
emo <- read.csv('C:/Users/huifa/Desktop/BCB Research/emotion_data2.csv', header=TRUE)
emo2 <- emo %>%
gather(
`emotions_sadness`,
`emotions_disgust`,
`emotions_contempt`,
`emotions_anger`,
`emotions_fear`,
key = "emotion",
value = "value") %>%
select(emotion, value, time, key)

emo2 $ value <- as.numeric(as.character(emo2 $ value))

mean(emo2 $ value)

```

Another Way to Calculate Mean Negative Emotions
```{r}
y <- c(Jack$emotions_anger, Jack$emotions_contempt, Jack$emotions_disgust, Jack$emotions_fear, Jack$emotions_sadness)
mean(y)
```

Mean Positive Emotions
```{r}
emo <- read.csv('C:/Users/huifa/Desktop/BCB Research/emotion_data2.csv', header=TRUE)
emo2 <- emo %>%
gather(
`emotions_surprise`,
`emotions_joy`,
key = "emotion",
value = "value") %>%
select(emotion, value, time, key)

emo2 $ value <- as.numeric(as.character(emo2 $ value))

mean(emo2 $ value)
```

Another Way to Calculate Mean Positive Emotions
```{r}
x <- c(Jack$emotions_joy, Jack$emotions_surprise)
mean(x)
```