my_data <- read.csv(file='/Users/kaz/Desktop/CW Progress/word_trials.csv', header=TRUE)

data30wpm = my_data[my_data$WPM==30,]
fit30wpm <- lm(Percent.Correct ~ Day + I(Day^2), data30wpm)

print(data30wpm$Percent.Correct)
plot(data30wpm$Day, data30wpm$Percent.Correct)
abline(fit)

data24wpm = my_data[my_data$WPM==24,]
fit24wpm <- lm(Percent.Correct ~ Day + I(Day^2), data24wpm)
print(data24wpm$Percent.Correct)

data32t34 = my_data[my_data$WPM==32 | my_data$WPM==33 | my_data$WPM==34,]
fit32t34wpm <- lm(Percent.Correct ~ Day + I(Day^2), data32t34)

data36wpm = my_data[my_data$WPM==36,]
fit36wpm <- lm(Percent.Correct ~ Day + I(Day^2), data36wpm)

library(scatterplot3d) 

scatterplot3d(
  x=my_data$Percent.Correct, 
  y=my_data$Day, 
  z=my_data$WPM,
  xlab='Percent Correct', ylab='Day', zlab='WPM',
  zlim=c(0,50), angle=55, cex.symbols=.7,
  pch=16, highlight.3d=TRUE)


library(plotly)

### no trend lines
plot_ly(z=my_data$Percent.Correct, 
        x=my_data$Day, 
        y=my_data$WPM,
        marker = list(
          size = 5
        ),
        name='All',
        mode = 'lines+markers') %>%
  add_markers() %>%
  layout(title="Morse Code - Copying Random words\nSpeed and Accuracy Over time",
         scene = list(xaxis=list(title="Day"),
                      yaxis=list(title="WPM", range=c(15,40), mirror=FALSE),
                      zaxis=list(title="Correct %")))

plot_ly(z=my_data$Percent.Correct, 
        x=my_data$Day, 
        y=my_data$WPM,
        marker = list(
          size = 5
        ),
        name='All',
        mode = 'lines+markers') %>%
  add_markers() %>%
  layout(title="Morse Code - Copying Random words\nSpeed and Accuracy Over time",
         scene = list(xaxis=list(title="Day"),
                      yaxis=list(title="WPM", range=c(15,44), mirror=FALSE),
                      zaxis=list(title="Correct %"))) %>%
  add_trace(z=data24wpm$Percent.Correct, 
            x=data24wpm$Day, 
            y=data24wpm$WPM,
            line = list(color = 'rgb(255,165,0)', tickcolor = 'rgb(255,165,0)', width = 3),
            name='24 WPM') %>%
  add_trace(z=fitted(fit24wpm),
            y=data24wpm$WPM,
            x=data24wpm$Day, 
            showlegend = FALSE,
            marker=list(color='rgb(255,165,0)'),
            line = list(color = 'rgb(255,165,0)', width = 20),
            name='24wpm Regression') %>%
  add_trace(z=data30wpm$Percent.Correct, 
            x=data30wpm$Day, 
            y=data30wpm$WPM,
            line = list(color = 'rgb(255, 0, 0)', width = 3),
            name='30 WPM') %>%
  add_trace(z=fitted(fit30wpm),
            y=data30wpm$WPM,
            x=data30wpm$Day, 
            showlegend = FALSE,
            line = list(color = 'rgb(255, 0, 0)', width = 20),
            marker=list(color='rgb(255, 0, 0)'),
            name='30wpm Regression') %>%
  add_trace(z=data32t34$Percent.Correct, 
          x=data32t34$Day, 
          y=data32t34$WPM,
          line = list(color = 'rgb(0, 230, 0)', tickcolor = 'rgb(0, 230,0)', width = 3),
          marker=list(color='rgb(0,230,0)'),
          name='32-34 WPM') %>%
  add_trace(z=fitted(fit32t34wpm),
            y=rep(mean(data32t34$WPM),length(data32t34$WPM)),
            x=data32t34$Day, 
            showlegend = FALSE,
            line = list(color = 'rgb(0,230,0)', width = 20),
            marker=list(color='rgb(0,230,0)'),
            name='30wpm Regression') %>%
  add_trace(z=data36wpm$Percent.Correct, 
            x=data36wpm$Day, 
            y=data36wpm$WPM,
            line = list(color = 'rgb(50,165,0)', tickcolor = 'rgb(50,165,0)', width = 3),
            name='36 WPM') %>%
  add_trace(z=fitted(fit36wpm),
            y=data36wpm$WPM,
            x=data36wpm$Day, 
            showlegend = FALSE,
            marker=list(color='rgb(50,165,0)'),
            line = list(color = 'rgb(50,165,0)', width = 20),
            name='36wpm Regression')