From 082b4c697633bc292dca4e14ecdc6319ca4af7c8 Mon Sep 17 00:00:00 2001 From: Stephanie Reinders Date: Tue, 5 Nov 2024 09:47:53 -0600 Subject: [PATCH 1/4] Saved scores to random_forest list Previously, random_forest was a list that contained (1) distances, (2) a ranger random forest object, and (3) densities fit to similarity scores. Because we want to plot the similarity scores themselves and not the densities fit with KDE, I replaced the densities in random_forest with the scores. Now `train_rf()` returns a list of (1) distances, (2) a ranger random forest object, and (3) scores. The densities are only used to create SLRs so I updated `calculate_slr()` to fit the densities, instead of taking the pre-fit densities as input with the random forest. The densities are no longer available to users as a data object. If the user wants the densities, they can run `make_densities_from_rf(scores = rforest$scores)`. The densities are saved as a test fixture and used to test `make_densities_from_rf()`. --- R/slrs.R | 21 ++++++++++++++++++ R/train.R | 16 +++++-------- data-raw/random_forest.rds | Bin 534523 -> 245849 bytes data/random_forest.rda | Bin 551930 -> 234182 bytes tests/testthat/fixtures/make_fixtures.R | 17 ++++---------- tests/testthat/fixtures/slr/densities.csv | Bin 0 -> 294099 bytes tests/testthat/fixtures/train/rf1.rds | Bin 349838 -> 58717 bytes .../fixtures/train/rf_randomForest1.rds | Bin 753348 -> 0 bytes tests/testthat/test-slrs.R | 10 +++++++++ tests/testthat/test-train.R | 8 ------- 10 files changed, 41 insertions(+), 31 deletions(-) create mode 100644 tests/testthat/fixtures/slr/densities.csv delete mode 100644 tests/testthat/fixtures/train/rf_randomForest1.rds diff --git a/R/slrs.R b/R/slrs.R index ba4556bc..4daf9039 100644 --- a/R/slrs.R +++ b/R/slrs.R @@ -159,6 +159,7 @@ calculate_slr <- function(sample1_path, sample2_path, rforest = random_forest, p # SLR message("Calculating SLR for samples...\n") + rforest$densities <- make_densities_from_rf(scores = rforest$scores) numerator <- eval_density_at_point(den = rforest$densities$same_writer, x = score, type = "numerator") denominator <- eval_density_at_point(den = rforest$densities$diff_writer, x = score, type = "denominator") slr <- numerator / denominator @@ -255,3 +256,23 @@ eval_density_at_point <- function(den, x, type, zero_correction = 1e-10) { return(y) } + + +#' Make Densities from a Trained Random Forest +#' +#' Create densities of same writer and different writer scores produced by a +#' trained random forest. +#' +#' @param scores A list of reference scores created with \code{\link{make_scores_from_rf()}}. +#' +#' @return A list of densities +#' +#' @noRd +make_densities_from_rf <- function(scores) { + pdfs <- list() + pdfs$same_writer <- stats::density(scores$same_writer, kernel = 'gaussian', n = 10000) + pdfs$diff_writer <- stats::density(scores$diff_writer, kernel = 'gaussian', n = 10000) + + return(pdfs) +} + diff --git a/R/train.R b/R/train.R index c915f86d..be1ccfdc 100644 --- a/R/train.R +++ b/R/train.R @@ -90,7 +90,7 @@ train_rf <- function(df, rforest$dists <- dists # get densities from training data - rforest$densities <- make_densities_from_rf(rforest = rforest) + rforest$scores <- make_scores_from_rf(rforest = rforest) saveRDS(rforest, file.path(output_dir, paste0('rf', run_number, '.rds'))) @@ -135,17 +135,17 @@ get_csafe_train_set <- function(df, train_prompt_codes) { # Internal Functions ------------------------------------------------------ -#' Make Densities from a Trained Random Forest +#' Make Reference Scores from a Trained Random Forest #' -#' Create densities of same writer and different writer scores produced by a +#' Create reference scores of same writer and different writer scores produced by a #' trained random forest. #' #' @param rforest A \pkg{ranger} random forest created with \code{\link{train_rf}}. #' -#' @return A list of densities +#' @return A list scores #' #' @noRd -make_densities_from_rf <- function(rforest) { +make_scores_from_rf <- function(rforest) { # Prevent note 'no visible binding for global variable' score <- session <- prompt <- rep <- total_graphs <- NULL @@ -164,11 +164,7 @@ make_densities_from_rf <- function(rforest) { dplyr::filter(match == 'different') %>% dplyr::pull(score) - pdfs <- list() - pdfs$same_writer <- stats::density(scores$same_writer, kernel = 'gaussian', n = 10000) - pdfs$diff_writer <- stats::density(scores$diff_writer, kernel = 'gaussian', n = 10000) - - return(pdfs) + return(scores) } diff --git a/data-raw/random_forest.rds b/data-raw/random_forest.rds index 009386265b7c9e241b60b909eb414e9a28e87acf..d2070edfd841d21ffec9e02259cf4eeed4a45330 100644 GIT binary patch delta 198610 zcmZr%cRXC*)BdIkA`)G6q7x<2%SMUbYeXlAh)(pqLG<2irrW zdB01A-ijhz@B`&D-DkSVtUNqiTi+yjw{no*J;zPvj?QS?9KL5cT44@5Q9-bqc2Gdf z&bEPf?&0q4uG_eT?~V+gi(6Y70+PaF<38eC2`KkeeBYu|IIHUVP^dYc{)D#1X>G?x 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b/tests/testthat/fixtures/make_fixtures.R @@ -2,8 +2,6 @@ train_set <- get_csafe_train_set(df = cfr, train_prompt_codes = "pLND") write.csv(train_set, testthat::test_path("fixtures", "train", "train_set.csv"), row.names = FALSE) - -# ranger ---- # save ranger random forest random_forest1 <- train_rf( df = train_set, @@ -14,14 +12,7 @@ random_forest1 <- train_rf( downsample = TRUE ) - -# randomForest ---- -# save randomForest random forest -random_forest2 <- train_randomForest_rf( - df = train_set, - ntrees = 200, - distance_measures = "euc", - output_dir = testthat::test_path("fixtures", "train"), - run_number = 1, - downsample = TRUE -) +# save densities +rforest <- readRDS(testthat::test_path("fixtures", "train", "rf1.rds")) +densities <- make_densities_from_rf(scores = rforest$scores) +saveRDS(densities, testthat::test_path("fixtures", "slr", "densities.csv")) diff --git a/tests/testthat/fixtures/slr/densities.csv b/tests/testthat/fixtures/slr/densities.csv new file mode 100644 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z-W84Dtp-ym-ckeyCfRNoazn7Ksf>Tq6Tu4V1Y&eLf*R+?SG1ZU=x9Mv1StYR$uNwGZw*F@L*HpU|ei6aH;6TevnGO8;RTBUH4EV2_)S!3X1pc%3 zX5OZDz@I=)GtCxZV^etW!mv360%3yuQ^1+BT?t1t{N!BgtCqhua#a7u|9(^m1j{c3 zg0dokVD;sjw*HE8J$nr8zT)V&9GkCP`)|K8VZ0pGBFI8MpGjta`)~W@du`WiX=5e6 zdjI8_#HVt2biO%_$zX(wc}xMF_wTO0t~BX;CABe^Lfm&E86%1m@%IpWjHq*BXm(T% zhezX&MU<)Jn3yp>o<v;@>rybpBWGU-hq Date: Tue, 5 Nov 2024 11:49:21 -0600 Subject: [PATCH 2/4] Create histogram plot for reference scores --- R/plots.R | 69 +++++++++++++++++++++++++++++++++++++++++++++++++++++++ R/slrs.R | 1 - 2 files changed, 69 insertions(+), 1 deletion(-) create mode 100644 R/plots.R diff --git a/R/plots.R b/R/plots.R new file mode 100644 index 00000000..ee9bba54 --- /dev/null +++ b/R/plots.R @@ -0,0 +1,69 @@ +# The handwriterRF R package performs writership analysis of handwritten +# documents. Copyright (C) 2024 Iowa State University of Science and Technology +# on behalf of its Center for Statistics and Applications in Forensic Evidence +# +# This program is free software: you can redistribute it and/or modify it under +# the terms of the GNU General Public License as published by the Free Software +# Foundation, either version 3 of the License, or (at your option) any later +# version. +# +# This program is distributed in the hope that it will be useful, but WITHOUT +# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more +# details. +# +# You should have received a copy of the GNU General Public License along with +# this program. If not, see . + + +# External Functions ------------------------------------------------------ + + +#' Plot Histograms +#' +#' Plot histograms of same writer and different writers reference similarity +#' scores from a random forest created with [train_rf()]. Plot a vertical, +#' dashed line at a similarity score calculated with [calculate_slr()] to see +#' whether the score is more typical of the same writer or different writers +#' reference scores. +#' +#' @param rforest A random forest created with [train_rf()] +#' @param score A similarity score calculated with [calculate_slr()] +#' +#' @return A ggplot2 plot of histograms +#' @export +#' +#' @examples +#' plot_histograms(rforest = random_forest, score = 0.9) +#' +plot_histograms <- function(rforest, score) { + scores <- rforest$scores + + df <- data.frame( + Score = c(scores$same_writer, scores$diff_writer), + Group = rep(c("same writer", "different writers"), each = 300) + ) + + p <- df %>% ggplot2::ggplot(ggplot2::aes(x = Score)) + + ggplot2::geom_histogram(position = "identity", + ggplot2::aes(fill = Group), + alpha = 0.4, + bins = 30) + # Histograms with transparency + ggplot2::geom_vline(xintercept = score, + color = "black", + linetype = "dashed") + # Add vertical line + ggplot2::annotate("text", + x = score, + y = 75, # Dynamically position the label + label = paste("similarity score", score), + color = "black", + size = 3, + angle = 90, + vjust = -1, + hjust = 0.5) + # Add text annotation + ggplot2::scale_fill_manual(values = c("same writer" = "#6BA4B8", "different writers" = "#F68D2E")) + # Customize colors + ggplot2::labs(title = "Reference Similarity Scores", x = "Score", y = "Frequency") + + ggplot2::theme_bw() + + return(p) +} diff --git a/R/slrs.R b/R/slrs.R index 4daf9039..98346998 100644 --- a/R/slrs.R +++ b/R/slrs.R @@ -275,4 +275,3 @@ make_densities_from_rf <- function(scores) { return(pdfs) } - From 904d247397297aa8617141d8cf100e5d61c774bd Mon Sep 17 00:00:00 2001 From: Stephanie Reinders Date: Tue, 5 Nov 2024 13:35:06 -0600 Subject: [PATCH 3/4] Changed `score` to an optional argument in `plot_histogram()` The user might want to plot the reference scores without placing a vertical line at a particular score, so I changed the default for `score` to NULL. Now a vertical line is only plotted if `score` is not NULL. --- DESCRIPTION | 1 + NAMESPACE | 1 + NEWS.md | 4 ++++ R/data.R | 23 +++++++++------------ R/plots.R | 46 +++++++++++++++++++++++++++++------------- man/plot_histograms.Rd | 30 +++++++++++++++++++++++++++ man/random_forest.Rd | 23 +++++++++------------ 7 files changed, 86 insertions(+), 42 deletions(-) create mode 100644 man/plot_histograms.Rd diff --git a/DESCRIPTION b/DESCRIPTION index 99a57449..dc617e4b 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -11,6 +11,7 @@ Encoding: UTF-8 LazyData: true RoxygenNote: 7.3.2 Suggests: + ggplot2, knitr, rmarkdown, testthat (>= 3.0.0), diff --git a/NAMESPACE b/NAMESPACE index aeee1769..1331e0f6 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -6,5 +6,6 @@ export(get_cluster_fill_rates) export(get_csafe_train_set) export(get_distances) export(interpret_slr) +export(plot_histograms) export(train_rf) importFrom(magrittr,"%>%") diff --git a/NEWS.md b/NEWS.md index 1418ce62..b87f1d0e 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,5 +1,9 @@ # handwriterRF (development version) +## Minor improvements and bug fixes + +* Created `plot_histograms()` to plot histograms of the reference same writer and different writer similarity scores in `random_forest$scores`. + # handwriterRF 1.0.2 * Removed quotes around "same writer" and "different writer" in documentation. diff --git a/R/data.R b/R/data.R index c8b949a0..6ccc5603 100644 --- a/R/data.R +++ b/R/data.R @@ -185,11 +185,11 @@ "templateK40" -#' A \pkg{ranger} Random Forest, Distances, and Densities +#' A \pkg{ranger} Random Forest, Distances, and Similarity Scores #' -#' A list that contains a trained random forest created with \pkg{ranger}, the data -#' frame of distances used to train the random forest, and two densities -#' obtained from the random forest. +#' A list that contains a trained random forest created with \pkg{ranger}, the +#' data frame of distances used to train the random forest, and similarity +#' scores calculated from the training data. #' #' @format A list with the following components: #' \describe{ @@ -201,12 +201,9 @@ #' 300 'different' distances in the data frame.} #' \item{rf}{A random forest created with \pkg{ranger} with settings: #' importance = 'permutation', scale.permutation.importance = TRUE, and num.trees = 200.} -#' \item{densities}{A similarity score was obtained for each pair of handwriting samples in the +#' \item{scores}{A similarity score was obtained for each pair of handwriting samples in the #' training data frame, dists, by calculating the proportion of decision trees that voted 'same' -#' class for the pair. The 'same_writer' density was created by applying \code{\link[stats]{density}} -#' to the similarity scores for the 300 same writer pairs in dists. Similarly, the 'diff_writer' -#' density was created by applying the \code{\link[stats]{density}} function to the similarity scores for the 300 -#' different writer pairs in dists. The default settings were used with \code{\link[stats]{density}}.} +#' class for the pair.} #' } #' #' @examples @@ -216,11 +213,9 @@ #' # view the distances data frame #' random_forest$dists #' -#' # plot the same writer density -#' plot(random_forest$densities$same_writer) -#' -#' # plot the different writer density -#' plot(random_forest$densities$diff_writer) +#' # plot histograms of the similarity scores and place a vertical +#' # line at similarity score 0.9. +#' plot_histograms(random_forest, 0.9) #' #' @md "random_forest" diff --git a/R/plots.R b/R/plots.R index ee9bba54..aae699ee 100644 --- a/R/plots.R +++ b/R/plots.R @@ -34,9 +34,22 @@ #' @export #' #' @examples -#' plot_histograms(rforest = random_forest, score = 0.9) +#' plot_histograms(rforest = random_forest) #' -plot_histograms <- function(rforest, score) { +#' # Add a vertical line 0.1 on the horizontal axis. +#' plot_histograms(rforest = random_forest, score = 0.1) +#' +plot_histograms <- function(rforest, score = NULL) { + # Prevent note "no visible binding for global variable" + Score <- Group <- NULL + + if (!requireNamespace("ggplot2", quietly = TRUE)) { + stop( + "Package \"ggplot2\" must be installed to use this function.", + call. = FALSE + ) + } + scores <- rforest$scores df <- data.frame( @@ -49,21 +62,26 @@ plot_histograms <- function(rforest, score) { ggplot2::aes(fill = Group), alpha = 0.4, bins = 30) + # Histograms with transparency - ggplot2::geom_vline(xintercept = score, - color = "black", - linetype = "dashed") + # Add vertical line - ggplot2::annotate("text", - x = score, - y = 75, # Dynamically position the label - label = paste("similarity score", score), - color = "black", - size = 3, - angle = 90, - vjust = -1, - hjust = 0.5) + # Add text annotation ggplot2::scale_fill_manual(values = c("same writer" = "#6BA4B8", "different writers" = "#F68D2E")) + # Customize colors ggplot2::labs(title = "Reference Similarity Scores", x = "Score", y = "Frequency") + ggplot2::theme_bw() + # Optional - add vertical line at score + if (!is.null(score)) { + p <- p + + ggplot2::geom_vline(xintercept = score, + color = "black", + linetype = "dashed") + # Add vertical line + ggplot2::annotate("text", + x = score, + y = 75, # Dynamically position the label + label = paste("similarity score", score), + color = "black", + size = 3, + angle = 90, + vjust = -1, + hjust = 0.5) # Add text annotation + } + return(p) } diff --git a/man/plot_histograms.Rd b/man/plot_histograms.Rd new file mode 100644 index 00000000..d0642228 --- /dev/null +++ b/man/plot_histograms.Rd @@ -0,0 +1,30 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/plots.R +\name{plot_histograms} +\alias{plot_histograms} +\title{Plot Histograms} +\usage{ +plot_histograms(rforest, score = NULL) +} +\arguments{ +\item{rforest}{A random forest created with [train_rf()]} + +\item{score}{A similarity score calculated with [calculate_slr()]} +} +\value{ +A ggplot2 plot of histograms +} +\description{ +Plot histograms of same writer and different writers reference similarity +scores from a random forest created with [train_rf()]. Plot a vertical, +dashed line at a similarity score calculated with [calculate_slr()] to see +whether the score is more typical of the same writer or different writers +reference scores. +} +\examples{ +plot_histograms(rforest = random_forest) + +# Add a vertical line 0.1 on the horizontal axis. +plot_histograms(rforest = random_forest, score = 0.1) + +} diff --git a/man/random_forest.Rd b/man/random_forest.Rd index 6dbc14a5..1291d9c5 100644 --- a/man/random_forest.Rd +++ b/man/random_forest.Rd @@ -3,7 +3,7 @@ \docType{data} \name{random_forest} \alias{random_forest} -\title{A \pkg{ranger} Random Forest, Distances, and Densities} +\title{A \pkg{ranger} Random Forest, Distances, and Similarity Scores} \format{ A list with the following components: \describe{ @@ -15,21 +15,18 @@ different writers, the class is 'different'. There are 300 'same' distances and 300 'different' distances in the data frame.} \item{rf}{A random forest created with \pkg{ranger} with settings: importance = 'permutation', scale.permutation.importance = TRUE, and num.trees = 200.} -\item{densities}{A similarity score was obtained for each pair of handwriting samples in the +\item{scores}{A similarity score was obtained for each pair of handwriting samples in the training data frame, dists, by calculating the proportion of decision trees that voted 'same' -class for the pair. The 'same_writer' density was created by applying \code{\link[stats]{density}} -to the similarity scores for the 300 same writer pairs in dists. Similarly, the 'diff_writer' -density was created by applying the \code{\link[stats]{density}} function to the similarity scores for the 300 -different writer pairs in dists. The default settings were used with \code{\link[stats]{density}}.} +class for the pair.} } } \usage{ random_forest } \description{ -A list that contains a trained random forest created with \pkg{ranger}, the data -frame of distances used to train the random forest, and two densities -obtained from the random forest. +A list that contains a trained random forest created with \pkg{ranger}, the +data frame of distances used to train the random forest, and similarity +scores calculated from the training data. } \examples{ # view the random forest @@ -38,11 +35,9 @@ random_forest$rf # view the distances data frame random_forest$dists -# plot the same writer density -plot(random_forest$densities$same_writer) - -# plot the different writer density -plot(random_forest$densities$diff_writer) +# plot histograms of the similarity scores and place a vertical +# line at similarity score 0.9. +plot_histograms(random_forest, 0.9) } \keyword{datasets} From 7cc504cd6f79d3bfa74af84e130e03ac5d68ea4f Mon Sep 17 00:00:00 2001 From: Stephanie Reinders Date: Wed, 6 Nov 2024 08:58:51 -0600 Subject: [PATCH 4/4] Created `calculate_percent_rank()` Instead of returning an SLR, `calculate_percent_rank()` returns the percentile of the observed score within the same writer and different writer distributions. --- R/percent-rank.R | 185 +++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 185 insertions(+) create mode 100644 R/percent-rank.R diff --git a/R/percent-rank.R b/R/percent-rank.R new file mode 100644 index 00000000..35e2b561 --- /dev/null +++ b/R/percent-rank.R @@ -0,0 +1,185 @@ +# The handwriterRF R package performs writership analysis of handwritten +# documents. Copyright (C) 2024 Iowa State University of Science and Technology +# on behalf of its Center for Statistics and Applications in Forensic Evidence +# +# This program is free software: you can redistribute it and/or modify it under +# the terms of the GNU General Public License as published by the Free Software +# Foundation, either version 3 of the License, or (at your option) any later +# version. +# +# This program is distributed in the hope that it will be useful, but WITHOUT +# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more +# details. +# +# You should have received a copy of the GNU General Public License along with +# this program. If not, see . + + +# External Functions ------------------------------------------------------ + +#' Calculate Percent Ranks +#' +#' Compares two handwriting samples scanned and saved a PNG images with the +#' following steps: +#' \enumerate{ +#' \item \code{\link[handwriter]{processDocument}} splits the writing in both samples into component shapes, or graphs. +#' \item \code{\link[handwriter]{get_clusters_batch}} groups the graphs into clusters of similar shapes. +#' \item \code{\link[handwriter]{get_cluster_fill_counts}} counts the number of graphs assigned to each cluster. +#' \item \code{\link{get_cluster_fill_rates}} calculates the proportion of graphs assigned to each cluster. The cluster fill rates serve as a writer profile. +#' \item A similarity score is calculated between the cluster fill rates of the two documents using a random forest trained with \pkg{ranger}. +#' \item The similarity score is compared to reference samples of same writer and different +#' writer similarity scores. The percent rank of the observed similarity score is returned for each sample. The percent rank for score x is +#' calculated as the number of scores in the sample less than or equal to x divided by the total number of scores. +#' } +#' +#' @param sample1_path A file path to a handwriting sample saved in PNG file +#' format. +#' @param sample2_path A file path to a second handwriting sample saved in PNG +#' file format. +#' @param rforest Optional. A random forest trained with \pkg{ranger}. If +#' rforest is not given, the data object random_forest is used. +#' @param project_dir Optional. A path to a directory where helper files will be +#' saved. If no project directory is specified, the helper files will be saved +#' to tempdir() and deleted before the function terminates. +#' +#' @return A list of two numbers +#' +#' @export +#' +#' @examples +#' \donttest{ +#' # Compare two samples from the same writer +#' sample1 <- system.file(file.path("extdata", "w0030_s01_pWOZ_r01.png"), package = "handwriterRF") +#' sample2 <- system.file(file.path("extdata", "w0030_s01_pWOZ_r02.png"), package = "handwriterRF") +#' calculate_slr(sample1, sample2) +#' +#' # Compare samples from two writers +#' sample1 <- system.file(file.path("extdata", "w0030_s01_pWOZ_r01.png"), package = "handwriterRF") +#' sample2 <- system.file(file.path("extdata", "w0238_s01_pWOZ_r02.png"), package = "handwriterRF") +#' calculate_slr(sample1, sample2) +#' } +#' +calculate_percent_rank <- function(sample1_path, sample2_path, rforest = random_forest, project_dir = NULL) { + copy_samples_to_project_dir <- function(sample1_path, sample2_path, project_dir) { + # Copy samples to project_dir > docs + message("Copying samples to output directory > docs...\n") + create_dir(file.path(project_dir, "docs")) + + # rename samples if file paths are different but file names are the same + if (identical(basename(sample1_path), basename(sample2_path))){ + file.copy(sample1_path, file.path(project_dir, "docs", "sample1.png")) + file.copy(sample2_path, file.path(project_dir, "docs", "sample2.png")) + } else { + file.copy(sample1_path, file.path(project_dir, "docs", basename(sample1_path))) + file.copy(sample2_path, file.path(project_dir, "docs", basename(sample2_path))) + } + + # get the sample paths in the project directory + sample_paths <- list.files(file.path(project_dir, "docs"), full.names = TRUE) + return(sample_paths) + } + + skip_if_processed <- function(sample_path, project_dir) { + # process file if it hasn't already been processed and saved in project_dir + # > graph + outfile <- gsub(".png", "_proclist.rds", basename(sample_path)) + outfile_path <- file.path(project_dir, "graphs", outfile) + if (!file.exists(outfile_path)) { + doc <- handwriter::processDocument(sample_path) + saveRDS(doc, outfile_path) + } + return() + } + + process_and_save_samples <- function(sample1_path, sample2_path, project_dir) { + # Process samples and save in project_dir > graphs + message("Processing samples...") + + create_dir(file.path(project_dir, "graphs")) + + skip_if_processed(sample_path = sample1_path, project_dir = project_dir) + skip_if_processed(sample_path = sample2_path, project_dir = project_dir) + + return() + } + + get_percent_rank <- function(score, ref_scores) { + # Calculate the percent rank of score for a sample of reference scores + pr <- 100 * sum(ref_scores <= score) / length(ref_scores) + return(pr) + } + + # error if sample1_path == sample2_path + if (identical(sample1_path, sample2_path)) { + stop("sample1_path and sample2_path cannot be identical.") + } + + # set output directory as temp directory if NULL + if (is.null(project_dir)) { + project_dir <- file.path(tempdir(), "comparison") + } + + # keep original sample paths so they can be recorded in the data frame at the + # end + sample1_path_org <- sample1_path + sample2_path_org <- sample2_path + + # copy samples + sample_paths <- copy_samples_to_project_dir( + sample1_path = sample1_path, + sample2_path = sample2_path, + project_dir = project_dir + ) + sample1_path <- sample_paths[1] + sample2_path <- sample_paths[2] + + # process + process_and_save_samples( + sample1_path = sample1_path, + sample2_path = sample2_path, + project_dir = project_dir + ) + + # cluster + clusters <- handwriter::get_clusters_batch( + template = templateK40, + input_dir = file.path(project_dir, "graphs"), + output_dir = file.path(project_dir, "clusters"), + writer_indices = c(2, 5), + doc_indices = c(7, 18), + save_master_file = TRUE + ) + counts <- handwriter::get_cluster_fill_counts(clusters) + rates <- get_cluster_fill_rates(counts) + + # distance + message("Calculating distance between samples...\n") + dist_measures <- which_dists(rforest = rforest) + d <- get_distances(df = rates, distance_measures = dist_measures) + + # score + message("Calculating similarity score between samples...\n") + score <- get_score(rforest = rforest, d = d) + + # percent rank + message("Calculating percent ranks for samples...\n") + browser() + percent_rank_same_writer <- get_percent_rank(score = score, ref_scores = random_forest$scores$same_writer) + percent_rank_diff_writer <- get_percent_rank(score = score, ref_scores = random_forest$scores$diff_writer) + + # make data frame of results + df <- data.frame("sample1_path" = sample1_path_org, "sample2_path" = sample2_path_org, + "docname1" = basename(sample1_path_org), "docname2" = basename(sample2_path_org), + "score" = score, "percent_rank_same_writer" = percent_rank_same_writer, + "percent_rank_diff_writer" = percent_rank_diff_writer) + + # delete project folder from temp directory or save results to project folder + if (project_dir == file.path(tempdir(), "comparison")) { + unlink(project_dir, recursive = TRUE) + } else { + saveRDS(df, file.path(project_dir, "percent_rank.rds")) + } + + return(df) +}

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