How to format a large annotated codeblock when converting to pdf such that it formats properly, stays at the correct location? How to prevent code flowing off the page?

[Gewerd-Strauss]

Description

Hello,

I have a subsection of a larger document in which I need to display and annotate a large RCpp-function. This document gets rendered to both html and pdf. For html, this is not an issue.

For PDF, I observe the following issues:

1. The large annotated codeblock does not remain at its location. Instead, it gets moved to the bottom of the document.
2. Additionally, the codeblock flows off the page at the end.
3. Additionally, code within the codeblocks can run off the end of the line.

When I convert this to pdf, I get the following doc:

Section of the document where the codeblocks should be positioned:

Session-Info in the appendix prints up to page 13:

End of file, where they end up at page 14ff:

The annotated codeblock is already cut down in number of lines. However, some lines are too large and will run off the screen:

A sample doc can be found at the end.

---

I have already attempted cutting the large codeblock into multiple smaller ones, e.g.

::: {#lst-code_annotation-rectangularRange_HSV_iteronce_cpp}

```{Rcpp}
//| label: code_annotation-rectangularRange_HSV_iteronce_cpp
//| echo: TRUE
//| code-fold: FALSE
//| eval: FALSE
//| cache: FALSE
List rectangularRange_HSV_iteronce_cpp(NumericVector H, NumericVector S, NumericVector V, // <1>
        Nullable<NumericMatrix> upper_bound, Nullable<NumericMatrix> lower_bound, // <2>
        int image_width,bool check_V) {
    int repetitions = H.size();
    // a lot of validation of the inputs
    for (int j = 0; j < num_rows; j++) {
        // re-init vectors for the indices
        std::vector<int> row_indices; std::vector<int> col_indices;
        // Preallocate memory for indices vectors
        row_indices.reserve(repetitions); col_indices.reserve(repetitions); // <3>
        // store static bounds in variables
        double lower_bound_H = lower_bound_(j, 0);
        [...]
```


1. numerical vector of length $Width_{Image} \times Height_{Image}$ containing the respective color compontent of all pixels
2. numerical matrix of dimensions `[3,N]` containing for all `N` spectrums the respective color-component of the boundary triplet in HSV-colorspace
3. Pre-allocating memory for the results, under the assumption that every pixel is a match and will thus be recorded. The real number of matches is usually far smaller. Allocating for 100% of the image sidesteps the resource-intensive repetitive resizing of the vector-dimensions when adding new values.

```{Rcpp}
//| label: code_annotation-rectangularRange_HSV_iteronce_cpp2
//| echo: TRUE
//| code-fold: FALSE
//| eval: FALSE
//| cache: FALSE
        for (int i = 0; i < repetitions; i++) {
            if (check_V) {
                // Check bounds and add indices if condition is met
                if ((lower_bound_H <= H[i]) && (H[i] <= upper_bound_H) && (lower_bound_S <= S[i]) 
                && (S[i] <= upper_bound_S) && (lower_bound_V <= V[i]) && (V[i] <= upper_bound_V)) {
                    int row = (i % image_width) + 1; int col = (i / image_width) + 1; row_indices.push_back(row); col_indices.push_back(col);
                }
            } else {
               [...]
            }
        }
```

```{Rcpp}
//| label: code_annotation-rectangularRange_HSV_iteronce_cpp3
//| echo: TRUE
//| code-fold: FALSE
//| eval: FALSE
//| cache: FALSE
        // compute N, then create a matrix for the indices computed above, assign names to matrix-columns
        int n = row_indices.size();
        IntegerMatrix idx(n, 2); // <4>
        std::copy(row_indices.begin(), row_indices.end(), idx.column(0).begin()); std::copy(col_indices.begin(), col_indices.end(), idx.column(1).begin()); // <4>
        colnames(idx) = CharacterVector::create("x", "y"); // <4>
        // compute img.fraction
        double fraction = static_cast<double>(n) / (int)repetitions; // <5>

        // Init the return list
        List result_entry;
        // insert 'pixel.idx','pixel.count' & 'img.fraction'
        result_entry["pixel.idx"] = idx; // pixel.idx > results[[k]]$pixel.idx
        [...]
        // Push the entry into the results list
        results.push_back(result_entry); // <6>
    }
    return results;
}
```

4. Convert the vectors containing the x/y-coordinates of all $k$ pixels into a matrix of $k$ rows with the respective x- & y-coordinate.
5. Compute which fraction of the *image* constitutes a match.
6. Store the results for the currently analysed spectrum. These include the coordinates of the matches, the number of matches, and the percentage of the image which constitutes a match.

Annotated analysis-function used for pixel-analysis via 'duflor.gui'-application.

:::

My intention was to let the different codeblocks be smaller, and thus be able to be more easily positioned after one another by quarto. Unfortunately that didn't help.

How can I resolve this issue?

Thank you,
Sincerely,
~Gw

---

Complete qmd-doc used to render the pdf-file from which the screenshots above stem.

---
# metadata for the thesis-manuscript
# excessive changes to maka a proper formattting, particularly in the PDF-output.
format:
  pdf:
    author: Gewerd Strauss
    citation-location: document
    code-line-numbers: TRUE
    code-annotations: TRUE
    crossref:
      lst-prefix: ca.
      lst-title: Code annotation
      fig-prefix: fig.
      fig-title: Figure
      tbl-prefix: tbl.
      appendix-title: "App."
      appendix-delim: ":"
    classoption: []    
    csl: ../.pandoc/apa.csl
    date: last-modified
    df-print: paged
    embed-resources: TRUE
    #fig-cap-location: margin
    fig-cap-location: bottom
    fig-dpi: 96
    fig-format: png
    fig-height: 6
    fig-responsive: TRUE
    fig-width: 8
    fig-pos: H
    geometry:
      - inner=3cm
      - outer=4cm
      - top=3cm
      - bottom=4cm
      - headsep=22pt
      - headheight=11pt
      - footskip=33pt
      - ignorehead
      - ignorefoot
      - heightrounded
    include-in-header: 
      - text: |
          \usepackage{adjustbox}
          \usepackage{graphicx}
          \usepackage{subfig}
          \usepackage{caption}
          \usepackage{datetime}
    link-external-icon: FALSE
    link-external-newwindow: TRUE
    link-citations: TRUE
    lof: TRUE
    lot: TRUE
    number-depth: 3
    number-sections: TRUE
    reference-location: document
    papersize: a4
    standalone: TRUE
    subtitle: Thesis Project at Bex-Biotec
    tbl-cap-location: top
    title: "Working Title: Multivariate Analysis of plant-stress treatment interaction setups"
    title-block-style: default
    template-partials: 
      - ../.tex/before-body.tex
      - ../.tex/toc.tex
    toc-location: left
    toc: TRUE
 
author:
- acknowledgements: I acknowledge the help I received by a lot of people
  attributes:
    corresponding: 1
    deceased: 0
  email: redaced
  fnumber: number
  id: string
  metadata:
    date: now
    date-format: MMMM YYYY
  name: Gewerd Strauss
  note: string
  url: https://github.com/redacted
creation date: 2023-12-29 19:29
cssclasses:
- clean-embeds
- writing
date: last-modified
date-format: YYYY-MM-DD HH:mm:ss:SSS
dateISO: '2023-09-02'
disabled rules: []
filters:
- abstract-section
keywords:
- keywordA
- keyword B
license: MIT
modification date: 2024-08-15 10:08
obs.html.data:
  inclusion_references:
  - report/methods/introduction.md
page-layout: article
published-title: last modified
qv: '`r quarto::quarto_version()`'
subtitle: Thesis Project at Bex-Biotec
tags:
- BE31
title-block-style: default
version: 1.0.0.1
---

<!-- DO NOT EDIT THE `.qmd`-VERSION OF THIS FILE -->
<!-- THE QMD-FILE IS GENERATED BY RUNNING 'OK', -->
<!-- via `scripts/pre-render/run_OK_on_OKRequired.R`, -->
<!-- FOLLOWED BY `scripts/pre-render/fixUnderscorePrefixes_in_Paths.R`-->

{{< pagebreak >}}
<!-- R SETUP -->
[@10.1093/nar/gkaa913]  
[@Allaire_Quarto_2022]  
[@knitr2014]  
[@R-lubridate]

```{r}
#| label: setup2
#| include: FALSE
# cat("\014")  ## clear console
# remove (list=ls())  ## clear environment variables
 # library(dplyr)
 # library(forcats)
 # library(ggplot2)
 # library(lubridate)
 # library(purrr)
 # library(readr)
 # library(stringr)
 # library(tibble)
 # library(tidyr)
library(tidyverse)

# library(RColorBrewer)
# library(svDialogs)
# library(ggpubr)
# library(ggthemes)
# library(readxl)
# library(tufte)
# library(ini)
# library(psych)
# library(DescTools)
# library(units)
# library(formatdown)
# library(rstatix)
library(knitr)
# units_options(negative_power = TRUE)
knitr::opts_chunk$set(echo = TRUE)
```


```{r}
#| label: report-wide-get-project-root
#| include: FALSE
#| cache: TRUE
root <- fs::path_abs(".")
## This codeblock is used to obtain the root of the project for use in later relative code executions.
```


```{r}
#| label: report-source-functions
#| include: FALSE
#| cache: FALSE
# TODO: remove this section from the Script itself.
source(normalizePath(stringr::str_c(root, "\\scripts\\utility\\inline_value_rendering.R")))
source(normalizePath(stringr::str_c(root, "\\scripts\\utility\\fixpower.R")))
source(normalizePath(stringr::str_c(root, "\\scripts\\utility\\get_files_in_folder.R")))
```


```{r}
#| label: report-load-all-experimental-rdata-files
#| include: FALSE
#| cache: FALSE
load_experimental_rdata_files <- function(root,env = .GlobalEnv) {
    path <- normalizePath(stringr::str_c(root,"\\assets\\data\\results\\"))
    df_s <- get_files_in_folder(path,"RData")
    for (each in df_s) {
        load(each,envir = env)
    }
}
load_experimental_rdata_files(root,.GlobalEnv)
```


<!-- 1st page: Title page: Title, Subtitle, Author, (Date), Abstract, Keywords, Statements and Declarations - Competing Interests -->
<!-- End of Title Page Contents-->
<!--linebreak to newpage, word/pdf-->

<!-- ~~2nd page: NO TOC~~ -->

<!-- ~~End of TOC-Page~~ -->

<!-- Abstract is populated in YAML-block -->

<!-- 3rd page: start of document -->

# Abstract

<!-- Introduction and global reasons -->Climate change and resulting weather patterns warrant the development of increasingly drought-resistant cultivars and suitable plant-treatments to maintain global food-chains.<!-- /Introduction and global reasons -->  
<!-- Objectives -->To that end, the development of drought-susceptible _Triticum aestivum cv. Cornetto_ was observed under varying drought intensities and watering methods in two experiments, in order to establish a proper drought stress setup.<!-- /Objectives -->  
<!-- Methods and results --> Changes in the provided watering volumes and watering frequency had mostly predictable effects on plant-development, antiproportional to the stress intensity exhibited. The second experiment additionally examined the stress-relieving effects of exogenously applied abscisic acid (ABA) prior to stress-induction. A mix of short-term molecular and long-term plant-wide analytical methods were used. Proline and relative water content increased and decreased in stressed plants relative to their pre-stressed states after `r difftime(lubridate::dmy("31.03.2023"),lubridate::dmy("14.03.2023"),units = "days")` and `r difftime(lubridate::dmy("16.06.2023"),lubridate::dmy("29.05.2023"),units = "days")` days of water-stress respectively; except in ABA-treated plants which exhibited higher proline-levels prior to stress-initiation. Proline-levels in control plants remained constant in the first and increased in the second run. RWC was cut in half in stressed plants afters stress initiation in the first experiment. Leaf-area development determined via computer-aided pixel-counting on digital photos showed an antiproportional relationship between stress-duration/stress-intensity and leaf-area formation. Treatment with abscisic acid resulted in a small positive effect in leaf area development between `r difftime(lubridate::dmy("30.05.2023"),lubridate::dmy("15.05.2023"),units = "days")` and `r difftime(lubridate::dmy("26.06.2023"),lubridate::dmy("15.05.2023"),units = "days")` days post repotting, whereafter its effect became less noticeable.<!-- /Methods and Results -->  
<!-- Conclusions -->Stresses exhibited were found to negatively affect all assessed parameters to different degrees. Additionally, parameters were found to be of varying efficacy for creating short- and long-term predictions.<!-- /Conclusions -->

# Introduction

(ref: @fig-GRAINWEIGHTRESULTSEXP1).  
(ref: [-@fig-GRAINWEIGHTRESULTSEXP1]).  

{{< lipsum 3 >}}

This is an Introduction which displays that this webpage is compiled using Quarto v.`r quarto::quarto_version()` & R v.`r stringr::str_c(R.version$major, ".",R.version$minor)`.[^1]

```{r fig-GRAINWEIGHTRESULTSEXP1, cache=F, echo=F, message=F, warning=F, fig.cap=paste0(str_c('Experiment 1: Normalised ear wet weight per plant for stressed and unstressed plants for different drought stress periods, ', as.character(as.Date.character("09.05.2023",format="%d.%m.%Y")-as.Date.character("06.03.2023",format="%d.%m.%Y")),' days post repotting, as a function of the stress duration.')), fig.title=paste0(str_c('Experiment 1: Normalised ear wet weight per plant for stressed and unstressed plants for different drought stress periods, ', as.character(as.Date.character("09.05.2023",format="%d.%m.%Y")-as.Date.character("06.03.2023",format="%d.%m.%Y")),' days post repotting, as a function of the stress duration.'))}
mtcars$cyl <- as.factor(mtcars$cyl)
plot(mpg ~ hp , data=mtcars, 
     col=cyl, pch=c(4,6,8)[mtcars$cyl], cex=1.2)
legend("topright", legend=levels(mtcars$cyl),
       pch = c(4,6,8),
       col=levels(mtcars$cyl))
```



[^1]: A footnote in introduction.
  

# Materials and Methods

{{lorem 1}}
<!--
Structure:
Experiments are defined and planned under `root/experiments/XX.md`
These documents are only for internal use, and should not be part of the report/page rendering

The cleaned up, written versions will be organised into `report/experiments/XX.md`
Use the obsidian-templater-plugin for creation of these corresponding files

-->

## General setup of the photo-box

General
For each experiment, the setup of the photo-box is adjusted as necessary to ensure easy and reliable execution of the respective experiment.  
Thus, the setup can vary between experiments. The parameters of the baseline setup are listed in @tbl-report-methods-general-baseline-setup-parameters.  
For each performed experiment, parameters of this setup are modified to varying degrees as necessary.

```{r}
#| label: tbl-report-methods-general-baseline-setup-parameters
#| tbl-id: 'tbl-report-methods-general-baseline-setup-parameters'
#| echo: FALSE
#| warning: FALSE
#| cache: TRUE
source(normalizePath(str_c(root, "\\scripts\\utility\\setup_parameters.R")))
options(knitr.kable.NA = '')

# Combine the lists into a data frame
setup_df <- data.frame(
    parameter = unlist(setup_params_cleaned_names),
    default_value = unlist(setup_params),
    stringsAsFactors = FALSE
)
rownames(setup_df) <- c() # eliminate the 'variable_names'-column of the df.
knitr::kable(setup_df, col.names = c("parameter","default value"), align = 'l', caption = "Default parameters for the experimental setups. Modifications are made on a per-experiment basis to allow reliable and easy execution.")
```



<!-- Include indented with 2 before Abstract -->

## Positional Deviations

  
<!-- Include indented with 2 spaces into M&M -->
  

## Software and Dataset

<!-- 12. Software and Dataset -->

### Image-Analysis Algorithm

The image-analysis was performed via the shiny-application provided by the function `duflor_gui()` provided by package `duflor.gui`[@duflorgui].  
Internally, `duflor.gui` interacts with the analysis-backend of the `duflor`-package via the interface-function `duflor::extract_pixels_HSV()`, which is called configured as outlined in @lst-code_annotation-extract_pixels_HSV.
With the parameters configured as shown, `duflor::extract_pixels_HSV()` will always leverage the 'C++'-function `duflor:::rectangularRange_HSV_iteronce_cpp()` from `duflor`, as outlined in @lst-code_annotation-rectangularRange_HSV_iteronce_cpp.

Within `duflor:::rectangularRange_HSV_iteronce_cpp()`, the

{{< pagebreak >}}

::: {#lst-code_annotation-rectangularRange_HSV_iteronce_cpp}

```{Rcpp}
//| label: code_annotation-rectangularRange_HSV_iteronce_cpp
//| echo: TRUE
//| code-fold: FALSE
//| eval: FALSE
//| cache: FALSE
List rectangularRange_HSV_iteronce_cpp(NumericVector H, NumericVector S, NumericVector V, // <1>
        Nullable<NumericMatrix> upper_bound, Nullable<NumericMatrix> lower_bound, // <2>
        int image_width,bool check_V) {
    int repetitions = H.size();
    // a lot of validation of the inputs
    for (int j = 0; j < num_rows; j++) {
        // re-init vectors for the indices
        std::vector<int> row_indices; std::vector<int> col_indices;
        // Preallocate memory for indices vectors
        row_indices.reserve(repetitions); col_indices.reserve(repetitions); // <3>
        // store static bounds in variables
        double lower_bound_H = lower_bound_(j, 0);
        [...]
        for (int i = 0; i < repetitions; i++) {
            if (check_V) {
                // Check bounds and add indices if condition is met
                if ((lower_bound_H <= H[i]) && (H[i] <= upper_bound_H) && (lower_bound_S <= S[i]) 
                && (S[i] <= upper_bound_S) && (lower_bound_V <= V[i]) && (V[i] <= upper_bound_V)) {
                    int row = (i % image_width) + 1; int col = (i / image_width) + 1; row_indices.push_back(row); col_indices.push_back(col);
                }
            } else {
            }
        }
        // compute N, then create a matrix for the indices computed above, assign names to matrix-columns
        int n = row_indices.size();
        IntegerMatrix idx(n, 2); // <4>
        std::copy(row_indices.begin(), row_indices.end(), idx.column(0).begin()); std::copy(col_indices.begin(), col_indices.end(), idx.column(1).begin()); // <4>
        colnames(idx) = CharacterVector::create("x", "y"); // <4>
        // compute img.fraction
        double fraction = static_cast<double>(n) / (int)repetitions; // <5>

        // Init the return list
        List result_entry;
        // insert 'pixel.idx','pixel.count' & 'img.fraction'
        result_entry["pixel.idx"] = idx; // pixel.idx > results[[k]]$pixel.idx
        [...]
        // Push the entry into the results list
        results.push_back(result_entry); // <6>
    }
    return results;
}
```



1. numerical vector of length $Width_{Image} \times Height_{Image}$ containing the respective color compontent of all pixels
2. numerical matrix of dimensions `[3,N]` containing for all `N` spectrums the respective color-component of the boundary triplet in HSV-colorspace
3. Pre-allocating memory for the results, under the assumption that every pixel is a match and will thus be recorded. The real number of matches is usually far smaller. Allocating for 100% of the image sidesteps the resource-intensive repetitive resizing of the vector-dimensions when adding new values.
4. Convert the vectors containing the x/y-coordinates of all $k$ pixels into a matrix of $k$ rows with the respective x- & y-coordinate.
5. Compute which fraction of the *image* constitutes a match.
6. Store the results for the currently analysed spectrum. These include the coordinates of the matches, the number of matches, and the percentage of the image which constitutes a match.

Annotated analysis-function used for pixel-analysis via 'duflor.gui'-application.

:::

{{< pagebreak >}}

::: {#lst-code_annotation-extract_pixels_HSV}

```{r}
#| label: code_annotation-extract_pixels_HSV
#| echo: TRUE
#| code-fold: FALSE
#| eval: FALSE
#| cache: TRUE
hsv_results <- extract_pixels_HSV(
        pixel.array = im, # <1>
        lower_bound = DATA$spectrums$lower_bound, # <2>
        upper_bound = DATA$spectrums$upper_bound, # <2>
        fast_eval = T, # <3>
        bundle_pixelarray = F,
        check_value = T, # <4>
        use_single_iteration_cpp = T # <3>
    )
```



1. cImg-array object containing the color-data of a given image.
2. R-list object containing for each spectrum a vector of HSV-values for the respective bound.
3. These boolean flags combined result in the use of `duflor:::rectangularRange_HSV_iteronce_cpp()` for analysing an image.
4. This boolean flag is set to also consider the `HUE`-component of a pixel when checking it.

Call to `duflor::extract_pixels_HSV()` used internally by the 'duflor.gui'-application.

:::

{{< pagebreak >}}


### Dataset used for this report

<!-- The first experiment was cut short due to an extreme mildew infestation `r difftime(dmy("09.05.2023"),dmy("06.03.2023"),units = "days")` days after repotting, therefore only data recorded up to this point could be used within the scope of this report.  
In case of the second experiment, data collection was stopped `r difftime(dmy("17.07.2023"),dmy("15.05.2023"),units = "days")` days after repotting to allow time for writing this report.  
Nonetheless, experimental procedures continued to be executed by the author until the end of their internship, and beyond that by Isabella Weber until its conclusion. -->

### Statistical Analyses

<!-- 11. Statistical Analysis -->
<!-- what tests are used? -->
<!-- What thresholds of significance were used? -->
The statistical significance was assessed on a per-dataset-basis. The presence of a normal distribution is tested for using the shapiro-wilk test<!-- e.g. Proline-Eval,RWC -->.  
The variance homogeneity was tested for using the Bartlett-test in case of normally distributed data, and using the Levene's test<!-- e.g. Proline-eval --> in case of non-normally distributed data.  
Normally distributed data with homogeneous variance was analysed via an unpaired t-test for independent samples with equal variance.  
Normally distributed data with inhomogeneous variance was analysed via a Welch one-way ANOVA.  
Non-normally distributed data with homogeneous variance was analysed via an one-factor ANOVA.  
Non-normally distributed data with inhomogeneous variance was analysed via a Kruskal-Wallis' test.<!-- last 3 cases never occur? -->  
Significance levels were set to a p-threshold of $p=0.05$.  

### Software

```{r quarto_cite, include=FALSE}
library(quarto)
library(grateful)
```


Image-analysis was performed via the R-packages [@duflor] and [@duflorgui].  
Statistical analyses were performed via the statistical computing language R (v.`r paste0(str_c(version$major,".",version$minor))`, [@rcoreteamLanguageEnvironmentStatistical2023]), which was subsequently used for figure generation. The document was compiled using the open-source publishing system Quarto (v.`r quarto_version()`, [@Allaire_Quarto_2022], via its corresponding R-interface package [@quarto]).  
Explicitly loaded packages R-packages are listed in the appendix (table [-@tbl-PackageVersions]), packages loaded as dependencies of explicitly loaded packages are not listed.

{{< pagebreak >}}

# Results

{{< lipsum 1 >}}

# Discussion

{{< lipsum 2 >}}

## Effect of x-distance between ID-dot and center of camera-lens

<!-- Include idented with 2 spaces into discussion -->
  

# Conclusions

{{< lipsum 3 >}}

\appendix

# Appendix <!-- {.appendix} -->

{{< lipsum 4 >}}  

## Packages <!-- {.appendix} -->

```{r Package_Setup, message=FALSE,warning=FALSE,echo=F,include=F}
# library(grateful)
# pkgs <- get_pkgs_info(output = "table", out.dir = ".pandoc",cite.tidyverse = T,pkgs = "Session",include.RStudio = T,dependencies = F)
# pkgs2 <- cite_packages(output = "table", out.dir = ".pandoc",cite.tidyverse = T,pkgs = "All",include.RStudio = T,dependencies = F)
```


_R-packages loaded in the manuscript-generating session, compiling this report and its analyses. Internally loaded dependencies of any explicitly loaded package are not included._

```{r}
#| label: tbl-PackageVersions
#| echo: FALSE
#| warning: FALSE
#| cache: FALSE
#| tbl-cap: "Explicity loaded packages. Internally loaded dependencies are not shown for brevity. - get_pkgs_info"
bib.file <- "packages"
out.dir <- ".pandoc"
kable(cites <- cite_packages(
  output = "table",
  bib.file = bib.file,
  out.dir = out.dir,
  cite.tidyverse = TRUE,
  pkgs = "All",
  include.RStudio = TRUE,
  dependencies = FALSE
))
```


{{< pagebreak >}}

::: {.content-visible when-format="pdf"}

## References <!-- {.appendix} -->

::: {#refs}  
:::

:::

## SessionInfo <!-- {.appendix} -->

```{r}
sessionInfo()
```

[Gewerd-Strauss]

Edit:

If I drastically reduce the codeblock, it still gets rendered in a different place - not at the end, but still not where it should:

Within `duflor:::rectangularRange_HSV_iteronce_cpp()`, the


```{Rcpp}
//| label: code_annotation-rectangularRange_HSV_iteronce_cpp
//| lst-label: lst-code_annotation-rectangularRange_HSV_iteronce_cpp
//| lst-cap: Analysis-function used for pixel-analysis via 'duflor.gui'-application.
//| echo: TRUE
//| code-fold: FALSE
//| code-overflow: wrap
//| eval: FALSE
//| cache: FALSE
List rectangularRange_HSV_iteronce_cpp(NumericVector H, // <1>
                                       NumericVector S, // <1>
                                       NumericVector V, // <1>
                                       Nullable<NumericMatrix> upper_bound, // <2>
                                       Nullable<NumericMatrix> lower_bound, // <2>
                                       int image_width,bool check_V) {
    int repetitions = H.size();
    if (upper_bound.isNotNull()) {
        upper_bound_ = static_cast<NumericMatrix>(upper_bound);
        num_rows = upper_bound_.rows();
    }
    for (int j = 0; j < num_rows; j++) {
        for (int i = 0; i < repetitions; i++) {
            if (check_V) {
                // Check bounds and add indices if condition is met
                if ((lower_bound_H <= H[i]) && (H[i] <= upper_bound_H) 
                && (lower_bound_S <= S[i]) && (S[i] <= upper_bound_S)
                && (lower_bound_V <= V[i]) && (V[i] <= upper_bound_V)) {
                    int row = (i % image_width) + 1; int col = (i / image_width) + 1;
                    row_indices.push_back(row); col_indices.push_back(col);
                }
            } else {
                [...] // <3>
            }
        }
    }
    return results;
}
```

1. numerical vector of length $Width_{Image} \times Height_{Image}$ containing the respective color compontent of all pixels
2. numerical matrix of dimensions `[3,N]` containing for all `N` spectrums the respective color-component of the boundary triplet in HSV-colorspace
3. Same as above, except that the `V`-component is not part of the logical condition.
Annotated analysis-function used for pixel-analysis via 'duflor.gui'-application.



```{r}
#| label: code_annotation-extract_pixels_HSV
#| echo: TRUE
#| code-fold: FALSE
#| code-overflow: wrap
#| eval: FALSE
#| cache: TRUE
#| lst-label: lst-code_annotation-extract_pixels_HSV
#| lst-cap: Call to `duflor::extract_pixels_HSV()` used internally by the 'duflor.gui'-application.
hsv_results <- extract_pixels_HSV(
        pixel.array = im, # <1>
        lower_bound = DATA$spectrums$lower_bound, # <2>
        upper_bound = DATA$spectrums$upper_bound, # <2>
        fast_eval = T, # <3>
        bundle_pixelarray = F,
        check_value = T, # <4>
        use_single_iteration_cpp = T # <3>
    )
```

1. cImg-array object containing the color-data of a given image.
2. R-list object containing for each spectrum a vector of HSV-values for the respective bound.
3. These boolean flags combined result in the use of `duflor:::rectangularRange_HSV_iteronce_cpp()` for analysing an image.
4. This boolean flag is set to also consider the `HUE`-component of a pixel when checking it.



### Dataset used for this report
```

[mcanouil]

I am afraid you need to play with LaTeX and its rules.
I'm not sure Quarto is the right place to ask such advanced LaTeX as the solution if there is one is 100% a LaTeX one that you might be able to inject in a Quarto document but still within a raw block.

[Gewerd-Strauss]

Hmm. After a bit of fiddling I have come to a solution which kind of works for me; by ensuring the codeblock begins on a new page I can squeeze it all into the same page. If I make the annotations larger than the page the codeblock is on, shenanigans ensue again.

Weirdly enough, I now have a different problem P:

Annotations are rendereding fine in pdf, but in HTML they are not marked up correctly, or the comments are just missing completely:

---
# metadata for the thesis-manuscript
# excessive changes to maka a proper formattting, particularly in the PDF-output.
format:
  html:
    author: Gewerd Strauss
    toc: TRUE
  pdf:
    author: Gewerd Strauss
    toc: TRUE
---

---
aliases: 
creation date: "2024-08-14 10:17"
format-links: false
modification date: "2024-08-15 09:51"
tags:
  - report/parts
---

# Structure of the image - representation

`duflor` uses the `imager`- package **citation imager** to load images into a 4 - dimensional `cimg`- array.

# duflor_algorithm

The image-analysis was performed via the shiny-application provided by the function `duflor_gui()` provided by package `duflor.gui`[@duflorgui].  
Internally, `duflor.gui` interacts with the analysis-backend of the `duflor`-package via the interface-function `duflor::extract_pixels_HSV()`, which is called configured as outlined in @lst-code_annotation-extract_pixels_HSV.
With the parameters configured as shown, `duflor::extract_pixels_HSV()` will always leverage the 'C++'-function `duflor:::rectangularRange_HSV_iteronce_cpp()` from `duflor`, as outlined in @lst-code_annotation-rectangularRange_HSV_iteronce_cpp.

{{< pagebreak >}}

```{r}
#| label: code_annotation-extract_pixels_HSV
#| lst-label: lst-code_annotation-extract_pixels_HSV
#| lst-cap: Call to `duflor::extract_pixels_HSV()` used internally by the 'duflor.gui'-application.
#| echo: TRUE
#| code-fold: FALSE
#| eval: FALSE
#| cache: FALSE
hsv_results <- extract_pixels_HSV(
        pixel.array = im, # <1>
        lower_bound = DATA$spectrums$lower_bound, # <2>
        upper_bound = DATA$spectrums$upper_bound, # <2>
        fast_eval = T, # <3>
        bundle_pixelarray = F,
        check_value = T, # <4>
        use_single_iteration_cpp = T # <3>
    )
```

1. cImg-array object containing the color-data of a given image.
2. R-list object containing for each spectrum a vector of HSV-values for the respective bound.
3. These boolean flags combined result in the use of `duflor:::rectangularRange_HSV_iteronce_cpp()` for analysing an image.
4. This boolean flag is set to also consider the `HUE`-component of a pixel when checking it.

DDD

{{< pagebreak >}}

```{Rcpp}
//| label: code_annotation-rectangularRange_HSV_iteronce_cpp
//| lst-label: lst-code_annotation-rectangularRange_HSV_iteronce_cpp
//| lst-cap: Analysis-function used for pixel-analysis via 'duflor.gui'-application.
//| echo: TRUE
//| code-fold: FALSE
//| eval: FALSE
//| cache: FALSE
List rectangularRange_HSV_iteronce_cpp(H,S,V, // <1>
        upper_bound,lower_bound, // <2>
        image_width, check_V) {
    // preparation, input-validation
    List results; int repetitions = H.size(); int num_rows = 0; // <3>
    if (upper_bound.isNotNull()) {
        upper_bound_ = static_cast<NumericMatrix>(upper_bound);
        num_rows = upper_bound_.rows();
    }
    if (lower_bound.isNotNull()) {
        lower_bound_ = static_cast<NumericMatrix>(lower_bound);
    }
    for (int j = 0; j < num_rows; j++) {
        std::vector<int> row_indices; std::vector<int> col_indices;// <3>
        row_indices.reserve(repetitions);col_indices.reserve(repetitions);// <4>
        double lower_bound_H = lower_bound_(j, 0); // <5> 
        double upper_bound_H = upper_bound_(j, 0); // <5>
        double lower_bound_S = lower_bound_(j, 1); // <5>
        double upper_bound_S = upper_bound_(j, 1); // <5>
        double lower_bound_V = lower_bound_(j, 2); // <5>
        double upper_bound_V = upper_bound_(j, 2); // <5>
        for (int i = 0; i < repetitions; i++) {
            if (check_V) {
                // Check bounds and add indices if condition is met
                if ((lower_bound_H <= H[i]) && (H[i] <= upper_bound_H) &&
                    (lower_bound_S <= S[i]) && (S[i] <= upper_bound_S) &&
                    (lower_bound_V <= V[i]) && (V[i] <= upper_bound_V)) {
                    row_indices.push_back(int (i % image_width) + 1); // <6>
                    col_indices.push_back(int (i / image_width) + 1); // <6>
                }
            } else {
                // see above, but without checking VALUE
            }
        }
        [...] // <7>
    }
    return results;
}
```

1. numerical vector of length $Width_{Image} \times Height_{Image}$ containing the respective color compontent of all pixels
2. numerical matrix of dimensions `[3,N]` containing for all `N` spectrums the respective color-component of the boundary triplet in HSV-colorspace
3. Initialise various variables.
4. Pre-allocating memory for the results, under the assumption that every pixel is a match and will thus be recorded. The real number of matches is usually far smaller. Allocating for 100% of the image sidesteps the resource-intensive repetitive resizing of the vector-dimensions when adding new values.
5. Store current static bounds in variables.
6. Compute coordinate based on index in 1-dimensional vector and image-width.
7. Compute number of hits `pixel.count`, percentage of pixels matched, collect `results`.

{{< pagebreak >}}

(Let's ignore that in pdf this is mangled up again, I am not putting in the entire pdf-formatting config here. This is a quick copy-paste of a larger, much more complicated document setup, so yea.)

In pdf, this will render the line annotations correctly, and will also render the annotations below the codeblocks correctly for both the r- and the cpp-codeblock.

But now, in HTML,

• for the r-codeblock, the list of annotations below is rendered as just a normal list, and the annotation-numbers in the codeblock are missing completely:
  

• similarly for the cpp-codeblock, the annotations are just a normal markdown list. Here however, the line-annotation-comments // <1> are rendered as normal comments, instead of missing, and instead of being converted to actual annotation numbers:
  

---

compared to pdf:

And finally, I can't seem to enable line-numbers for the cpp-codeblock, although code-line-numbers: true is set for both formats on the directory-level - where both formats are completely defined at for this document.

For both formats, I do set code-line-numbers: true, and do not set code-annotations: below (as it is implicitly below by default acc. to quarto docs):

format:
  pdf:
    author: AAA BBB
    citation-location: document
    code-line-numbers: true
    crossref:
      lst-prefix: ca.
      lst-title: Code annotation
      fig-prefix: fig.
      fig-title: Figure
      tbl-prefix: tbl.
      appendix-title: "App."
      appendix-delim: ":"
    classoption: []    
    csl: ../.pandoc/apa.csl
    date: last-modified
    df-print: paged
    embed-resources: TRUE
    #fig-cap-location: margin
    fig-cap-location: bottom
    fig-dpi: 96
    fig-format: png
    fig-height: 6
    fig-responsive: TRUE
    fig-width: 8
    fig-pos: H
    geometry:
      - inner=3cm
      - outer=4cm
      - top=3cm
      - bottom=4cm
      - headsep=22pt
      - headheight=11pt
      - footskip=33pt
      - ignorehead
      - ignorefoot
      - heightrounded
    include-in-header: 
      - text: |
          \usepackage{adjustbox}
          \usepackage{graphicx}
          \usepackage{subfig}
          \usepackage{caption}
          \usepackage{datetime}
    link-external-icon: FALSE
    link-external-newwindow: TRUE
    link-citations: TRUE
    lof: TRUE
    lot: TRUE
    number-depth: 3
    number-sections: TRUE
    reference-location: document
    papersize: a4
    standalone: TRUE
    subtitle: BBB
    tbl-cap-location: top
    title: "AAA"
    title-block-style: default
    template-partials: 
      - ../.tex/before-body.tex
      - ../.tex/toc.tex
    toc-location: left
    toc: TRUE
  html:
    author: AAA BBB
    citations-hover: FALSE
    crossrefs-hover: TRUE
    footnotes-hover: TRUE
    citation-location: margin
    code-line-numbers: true
    fig-cap-location: margin
    reference-location: margin
    tbl-cap-location: margin
    code-fold: TRUE
    code-overflow: scroll
    crossref:
      lst-prefix: ca.
      lst-title: Code annotation
      fig-prefix: fig.
      fig-title: Figure
      tbl-prefix: tbl.
      tbl-title: Table
      appendix-title: "App."
      appendix-delim: ":"
    csl: ../.pandoc/apa.csl
    date-format: DD.MM.YYYY
    date: last-modified
    df-print: paged
    embed-resources: TRUE
    fig-height: 6
    fig-title: Figuring it out
    fig-width: 8
    link-external-icon: FALSE
    link-external-newwindow: TRUE
    number-depth: 2
    number-sections: TRUE
    subtitle: BBBB
    theme: cosmo
    toc-depth: 3
    toc-location: left
    toc-title: Table of Contents
    toc: TRUE
    title: "AAAA"
    title-block-style: default