## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = '#>',
  eval = FALSE
)

## -----------------------------------------------------------------------------
# library(gp3tools)
# 
# data("gazepoint_example_master")
# data("gazepoint_example_fixations")
# data("gazepoint_example_aoi_geometry")
# data("gazepoint_example_aoi_windows")
# 
# master <- gazepoint_example_master
# all_fix <- gazepoint_example_fixations
# aoi_geometry <- gazepoint_example_aoi_geometry
# aoi_windows <- gazepoint_example_aoi_windows

## -----------------------------------------------------------------------------
# export_dir <- "C:/Users/YourName/Desktop/gp3_test_exports"
# output_dir <- "C:/Users/YourName/Desktop/gp3_outputs"
# 
# results <- run_gazepoint_workflow(
#   export_dir = export_dir,
#   output_dir = output_dir,
#   prefix = "study1",
#   save_plots = TRUE,
#   create_report = TRUE
# )
# 
# all_gaze <- results$all_gaze
# all_fix <- results$all_fix
# master <- create_gazepoint_master(all_gaze)

## -----------------------------------------------------------------------------
# master_audit <- audit_gazepoint_master(master)
# 
# validation <- validate_gazepoint_master(master)
# 
# master_audit$overview
# validation$summary
# validation$checks

## -----------------------------------------------------------------------------
# aoi_geometry_template <- tibble::tibble(
#   media_id = c("stim1", "stim1"),
#   aoi = c("logo", "product"),
#   x_min = c(0.10, 0.50),
#   y_min = c(0.10, 0.50),
#   x_max = c(0.30, 0.70),
#   y_max = c(0.30, 0.70)
# )
# 
# aoi_geometry_template

## -----------------------------------------------------------------------------
# aoi_geometry_audit <- audit_gazepoint_aoi_geometry(
#   aoi_geometry,
#   aoi_col = "aoi",
#   stimulus_col = "media_id",
#   x_min_col = "x_min",
#   y_min_col = "y_min",
#   x_max_col = "x_max",
#   y_max_col = "y_max",
#   screen_x_range = c(0, 1),
#   screen_y_range = c(0, 1)
# )
# 
# aoi_geometry_audit$overview
# aoi_geometry_audit$flagged_aois

## -----------------------------------------------------------------------------
# aoi_overlap_audit <- audit_gazepoint_aoi_overlap(
#   aoi_geometry,
#   aoi_col = "aoi",
#   stimulus_col = "media_id",
#   x_min_col = "x_min",
#   y_min_col = "y_min",
#   x_max_col = "x_max",
#   y_max_col = "y_max",
#   min_overlap_area = 0,
#   min_overlap_prop = 0
# )
# 
# aoi_overlap_audit$overview
# aoi_overlap_audit$flagged_overlaps

## -----------------------------------------------------------------------------
# aoi_coding_audit <- audit_gazepoint_aoi_coding_matrix(
#   gaze_data = master,
#   aoi_geometry = aoi_geometry,
#   observed_aoi_col = "aoi_current",
#   gaze_x_col = "x",
#   gaze_y_col = "y",
#   gaze_stimulus_col = "MEDIA_ID",
#   sample_id_cols = c("subject", "MEDIA_ID", "trial_global"),
#   geometry_aoi_col = "aoi",
#   geometry_stimulus_col = "media_id",
#   x_min_col = "x_min",
#   y_min_col = "y_min",
#   x_max_col = "x_max",
#   y_max_col = "y_max"
# )
# 
# aoi_coding_audit$overview
# aoi_coding_audit$coding_matrix

## -----------------------------------------------------------------------------
# aoi_verification_plot <- plot_gazepoint_aoi_verification(
#   aoi_geometry = aoi_geometry,
#   gaze_data = master,
#   geometry_aoi_col = "aoi",
#   geometry_stimulus_col = "media_id",
#   x_min_col = "x_min",
#   y_min_col = "y_min",
#   x_max_col = "x_max",
#   y_max_col = "y_max",
#   gaze_x_col = "x",
#   gaze_y_col = "y",
#   gaze_stimulus_col = "MEDIA_ID"
# )
# 
# aoi_verification_plot

## -----------------------------------------------------------------------------
# aoi_entries <- summarise_gazepoint_aoi_entries(
#   master,
#   time_col = "time",
#   aoi_col = "aoi_current",
#   group_cols = c("subject", "MEDIA_ID", "trial_global")
# )
# 
# dplyr::glimpse(aoi_entries)

## -----------------------------------------------------------------------------
# aoi_windows <- summarise_gazepoint_aoi_windows(
#   master,
#   windows = c(0, 500, 1000, 2000, 5000, 10000),
#   time_col = "time",
#   aoi_col = "aoi_current",
#   subject_col = "subject",
#   condition_col = "condition",
#   group_cols = c("subject", "MEDIA_ID", "trial_global"),
#   target_aoi_values = "AOI 2",
#   distractor_aoi_values = c("AOI 0", "AOI 1")
# )
# 
# dplyr::glimpse(aoi_windows)

## -----------------------------------------------------------------------------
# dplyr::select(
#   aoi_windows,
#   subject,
#   condition,
#   MEDIA_ID,
#   trial_global,
#   window_label,
#   n_window_samples,
#   n_target_samples,
#   n_distractor_samples,
#   n_valid_denominator_samples,
#   target_sample_prop_valid,
#   aoi_window_status
# )

## -----------------------------------------------------------------------------
# aoi_window_denominator_audit <- audit_gazepoint_aoi_window_denominators(
#   aoi_windows,
#   min_denominator_samples = 5,
#   min_valid_denominator_prop = 0.70,
#   max_denominator_cv = 0.25,
#   max_condition_ratio = 2
# )
# 
# aoi_window_denominator_audit$overview
# aoi_window_denominator_audit$window_summary
# aoi_window_denominator_audit$condition_window_summary

## -----------------------------------------------------------------------------
# aoi_glmm_data <- prepare_gazepoint_aoi_glmm_data(
#   aoi_windows,
#   success_col = "n_target_samples",
#   denominator = "valid",
#   subject_col = "subject",
#   condition_col = "condition",
#   window_col = "window_label",
#   window_start_col = "window_start_ms",
#   window_end_col = "window_end_ms",
#   min_denominator_samples = 5,
#   outcome_label = "target"
# )
# 
# dplyr::count(
#   aoi_glmm_data,
#   aoi_glmm_condition,
#   aoi_glmm_window,
#   aoi_glmm_status
# )

## -----------------------------------------------------------------------------
# aoi_glmm_fit <- fit_gazepoint_aoi_window_glmm(
#   aoi_glmm_data,
#   random_window_slopes = FALSE
# )
# 
# aoi_glmm_fit$model_status
# aoi_glmm_fit$formula
# aoi_glmm_fit$comparison
# aoi_glmm_fit$fixed_effects

## -----------------------------------------------------------------------------
# aoi_emp_logit <- transform_gazepoint_aoi_empirical_logit(
#   aoi_glmm_data,
#   numerator_col = "aoi_glmm_success",
#   denominator_col = "aoi_glmm_denominator",
#   correction = 0.5
# )
# 
# attr(aoi_emp_logit, "gp3_empirical_logit_overview")

## -----------------------------------------------------------------------------
# aoi_sensitivity <- fit_gazepoint_aoi_model_sensitivity(
#   aoi_glmm_data,
#   model_types = c(
#     "binomial_glmm",
#     "empirical_logit_lmm",
#     "proportion_lmm",
#     "quasibinomial_glm"
#   ),
#   include_condition = TRUE,
#   include_window = TRUE,
#   include_interaction = TRUE,
#   random_intercept = TRUE
# )
# 
# aoi_sensitivity$comparison
# aoi_sensitivity$fixed_effects

## -----------------------------------------------------------------------------
# aoi_sequences <- prepare_gazepoint_aoi_sequences(
#   master,
#   time_col = "time",
#   aoi_col = "aoi_current",
#   group_cols = c("subject", "MEDIA_ID", "trial_global")
# )
# 
# dplyr::glimpse(aoi_sequences)

## -----------------------------------------------------------------------------
# aoi_transition_summary <- summarise_gazepoint_aoi_transitions(
#   master,
#   time_col = "time",
#   aoi_col = "aoi_current",
#   group_cols = c("subject", "MEDIA_ID", "trial_global"),
#   target_aoi_values = "AOI 2",
#   distractor_aoi_values = c("AOI 0", "AOI 1")
# )
# 
# aoi_transition_summary

## -----------------------------------------------------------------------------
# aoi_transition_matrix <- compute_gazepoint_aoi_transition_matrix(
#   master,
#   time_col = "time",
#   aoi_col = "aoi_current",
#   group_cols = c("subject", "MEDIA_ID", "trial_global"),
#   target_aoi_values = "AOI 2",
#   distractor_aoi_values = c("AOI 0", "AOI 1")
# )
# 
# aoi_transition_matrix$count_matrix
# aoi_transition_matrix$probability_matrix
# aoi_transition_matrix$long_table

## -----------------------------------------------------------------------------
# time_varying_transition_matrix <- compute_gazepoint_time_varying_transition_matrix(
#   master,
#   time_col = "time",
#   state_col = "aoi_current",
#   group_cols = c("subject", "MEDIA_ID", "trial_global"),
#   windows = c(0, 500, 1000, 2000, 5000)
# )
# 
# time_varying_transition_matrix$overview
# time_varying_transition_matrix$transition_summary

## -----------------------------------------------------------------------------
# aoi_trial_features <- summarise_gazepoint_aoi_trial_features(
#   master,
#   time_col = "time",
#   aoi_col = "aoi_current",
#   group_cols = c("subject", "MEDIA_ID", "trial_global"),
#   target_aoi_values = "AOI 2",
#   distractor_aoi_values = c("AOI 0", "AOI 1")
# )
# 
# aoi_trial_features

## -----------------------------------------------------------------------------
# fixation_trial_features <- summarise_gazepoint_fixation_trials(
#   all_fix,
#   target_aoi_values = "AOI 2",
#   distractor_aoi_values = c("AOI 0", "AOI 1")
# )
# 
# fixation_trial_features

## -----------------------------------------------------------------------------
# fixation_aligned <- prepare_gazepoint_fixation_aligned_data(
#   master,
#   time_col = "time",
#   participant_col = "subject",
#   trial_col = "trial_global",
#   aoi_col = "aoi_current",
#   target_aoi = "AOI 2",
#   fixation_col = "is_fixation",
#   alignment_event = "first_fixation_to_target",
#   baseline_window = c(-200, 0),
#   analysis_window = c(0, 800)
# )
# 
# fixation_aligned$overview
# fixation_aligned$event_table
# fixation_aligned$trial_summary

## -----------------------------------------------------------------------------
# markov_obj <- create_gazepoint_markovchain_object(
#   aoi_sequences,
#   state_col = "aoi"
# )
# 
# semimarkov_data <- prepare_gazepoint_semimarkov_data(
#   aoi_sequences,
#   state_col = "aoi",
#   time_col = "time"
# )
# 
# hmm_data <- prepare_gazepoint_hmm_data(
#   aoi_sequences,
#   state_col = "aoi",
#   observation_cols = c("x", "y", "pupil")
# )
# 
# markov_obj$overview
# semimarkov_data$overview
# hmm_data$overview

## -----------------------------------------------------------------------------
# aoi_gamm_data <- prepare_gazepoint_aoi_gamm_data(
#   master,
#   aoi_col = "aoi_current",
#   target_aoi_values = "AOI 2",
#   subject_col = "subject",
#   condition_col = "condition",
#   time_col = "time",
#   trial_col = "trial_global",
#   time_window = c(0, 2000),
#   bin_size_ms = 50,
#   denominator = "valid",
#   min_denominator_samples = 1,
#   outcome_label = "target_aoi"
# )
# 
# dplyr::count(
#   aoi_gamm_data,
#   .gp3_aoi_gamm_condition,
#   .gp3_aoi_gamm_condition_status,
#   .gp3_aoi_gamm_status
# )

## -----------------------------------------------------------------------------
# aoi_gamm_fit <- fit_gazepoint_aoi_gamm(
#   aoi_gamm_data,
#   include_condition = TRUE,
#   condition_smooths = TRUE,
#   random_subject = TRUE,
#   random_subject_time = FALSE,
#   time_k = 10
# )
# 
# aoi_gamm_fit$model_status
# aoi_gamm_fit$condition_status
# aoi_gamm_fit$formula_text
# aoi_gamm_fit$diagnostics
# aoi_gamm_fit$smooth_table

## -----------------------------------------------------------------------------
# aoi_gamm_plot <- plot_gazepoint_aoi_gamm(
#   aoi_gamm_fit,
#   n_time_points = 100,
#   include_observed = TRUE,
#   include_fitted = TRUE,
#   show_ci = TRUE
# )
# 
# aoi_gamm_plot

## -----------------------------------------------------------------------------
# aoi_diagnostics <- diagnose_gazepoint_glmm(
#   aoi_glmm_fit,
#   model_name = "aoi_window_glmm",
#   use_dharma = FALSE
# )
# 
# aoi_diagnostics$overview
# aoi_diagnostics$convergence
# aoi_diagnostics$singularity
# aoi_diagnostics$overdispersion

## -----------------------------------------------------------------------------
# aoi_model_summary <- tidy_gazepoint_model_summary(
#   aoi_glmm_fit,
#   model_name = "aoi_window_glmm",
#   exponentiate = TRUE,
#   use_dharma = FALSE
# )
# 
# aoi_model_summary$overview
# aoi_model_summary$fixed_effects

## -----------------------------------------------------------------------------
# aoi_emmeans <- summarise_gazepoint_emmeans(
#   aoi_glmm_fit,
#   specs = "aoi_glmm_condition",
#   by = "aoi_glmm_window",
#   model_name = "aoi_window_glmm",
#   type = "response"
# )
# 
# aoi_emmeans$overview
# aoi_emmeans$emmeans
# aoi_emmeans$contrasts

## -----------------------------------------------------------------------------
# model_table_files <- export_gazepoint_model_tables(
#   model_summary = aoi_model_summary,
#   emmeans_summary = aoi_emmeans,
#   output_dir = output_dir,
#   prefix = "aoi_window_glmm"
# )
# 
# model_table_files

## -----------------------------------------------------------------------------
# reporting <- create_gazepoint_reporting_checklist(
#   data = master,
#   objects = list(
#     validation = validation,
#     aoi_geometry_audit = aoi_geometry_audit,
#     aoi_denominator_audit = aoi_window_denominator_audit,
#     aoi_model = aoi_glmm_fit,
#     diagnostics = aoi_diagnostics
#   ),
#   analysis_type = "aoi",
#   study_title = "Gazepoint AOI study"
# )
# 
# reporting$overview
# reporting$checklist

