## ----echo = FALSE, message = FALSE--------------------------------------------
library("rprime")
library("knitr")
opts_chunk$set(
  comment = "#>",
  error = FALSE,
  tidy = FALSE,
  collapse = TRUE)
options(str = strOptions(vec.len = 2))

## ----eval = FALSE-------------------------------------------------------------
# install.packages("rprime")

## -----------------------------------------------------------------------------
library("rprime")
# Read in an Eprime text file
experiment_lines <- read_eprime("data/SAILS/SAILS_001X00XS1.txt")

# Extract and parse the log-frames from the file
experiment_data <- FrameList(experiment_lines)

## -----------------------------------------------------------------------------
# There are six different kinds of frames in this file
preview_levels(experiment_data)

## -----------------------------------------------------------------------------
preview_frames(experiment_data)

## -----------------------------------------------------------------------------
# Filter (out) by depth of nesting
not_level_1 <- drop_levels(experiment_data, 1)
preview_levels(not_level_1)

# Filter (in) by depth of nesting
just_level_3 <- keep_levels(experiment_data, 3)
preview_levels(just_level_3)

## -----------------------------------------------------------------------------
# Filter (out) by attribute values
no_header <- filter_out(experiment_data, "Running", values = "Header")
preview_levels(no_header)

# Filter (in) by attribute values
not_practice <- filter_in(experiment_data, "Running", "TrialLists")
preview_levels(not_practice)

# Drill down further into the trials by filtering again
sue_trials <- filter_in(not_practice, "Module", "SUE")
preview_eprime(sue_trials)

## -----------------------------------------------------------------------------
# Export to dataframe
sue_trials_df <- to_data_frame(sue_trials)
str(sue_trials_df)

# Don't need every column
columns_to_keep <- c("Eprime.Basename", "Module", "Sample", 
                     "Correct", "Response")
sue_trials_df <- sue_trials_df[columns_to_keep]
head(sue_trials_df)

## -----------------------------------------------------------------------------
# Right now the sample numbers are stored as character values
str(sue_trials_df)

library("readr")
sue_trials_df <- type_convert(sue_trials_df)
# Now, they are stored as integers...
str(sue_trials_df)