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a/.Rbuildignore b/.Rbuildignore index 61a7b2ef..0e3b3d58 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -11,6 +11,8 @@ ^cran-comments\.md$ ^CRAN-SUBMISSION$ ^README\.Rmd$ +^README\.qmd$ ^tools$ ^scratch.R$ ^altdoc$ +^_quarto$ diff --git a/.gitignore b/.gitignore index 6a764e83..290c2cf2 100644 --- a/.gitignore +++ b/.gitignore @@ -14,3 +14,4 @@ inst/doc scratch* *.psd altdoc/freeze.rds +^_quarto$ diff --git a/README.md b/README.md index dc2b2677..c74838b9 100644 --- a/README.md +++ b/README.md @@ -1,27 +1,52 @@ - - - - # handwriter + -The handwriter package performs writership analysis of a handwritten -*questioned document* where the questioned document was written by one -of *closed-set* of potential writers. For example, a handwritten bomb -threat is found in a science classroom, and the police are able to -determine that the note could only have been written by one of the -students in 4th period science. The handwriter package builds a -statistical model to estimate a *writer profile* from known handwriting -samples from each writer in the closed-set. A writer profile is also -estimated from the questioned document. The statistical model compares -the writer profile from the questioned document with each of the writer -profiles from the closed-set of potential writers and estimates the -posterior probability that each closed-set writer wrote the questioned -document. - -## Installation +Handwriter is designed to assist forensic examiners by analyzing +handwritten documents against a *closed set* of potential writers. It +determines the probability that each writer wrote the document. Whether +you are a forensic document examiner, legal professional, academic, or +simply curious about how statistics are applied to handwriting, +handwriter provides an automated way to evaluate handwriting samples. + +## Quick Start + +### VIEW A DEMO + +View a demo of handwriter on handwritten documents from the CSAFE +Handwriting Database. Go to +[demo](https://csafe.shinyapps.io/handwriterAppDemo/). + +### SIMULATE CASEWORK WITH EXAMPLE DOCUMENTS + +#### INSTALLATION + +Handwriter requires R, RStudio IDE, and JAGS. + +- Install R and RStudio from + [POSIT](https://posit.co/download/rstudio-desktop/) +- Install JAGS from + [SourceForge](https://sourceforge.net/projects/mcmc-jags/files/) + +#### LAUNCH THE APP + +Open RStudio, navigate to the console window, and type: + +``` r +install.packages("devtools") +devtools::install_github("CSAFE-ISU/handwriterApp") +library(handwriterApp) +handwriterApp() +``` + +In the pop-up window, click **Open in Browser**. If you use the app in +the pop-up window instead of in a browser, some links will not work. + +Click **Simulate Casework** and follow the instructions in the app. + +## Advanced You can install handwriter from CRAN with: @@ -195,7 +220,7 @@ template_data <- format_template_data(template = template) plot_cluster_fill_counts(template_data, facet = TRUE) ``` - ### STEP 3: Fit a Hierarchical Model @@ -260,7 +285,7 @@ but the model data is already in the correct format.) plot_cluster_fill_counts(formatted_data=model, facet = TRUE) ``` - The bars across the top of each graph show the Writer ID. Each graph has @@ -301,7 +326,7 @@ View a trace plot of a variable. plot_trace(variable = "mu[1,1]", model = model) ``` - If we need to, we can drop the beginning MCMC iterations for burn-in. @@ -373,7 +398,7 @@ the cluster fill counts observed in each questioned document. plot_cluster_fill_counts(analysis, facet = TRUE) ``` - View the posterior probabilities of writership. diff --git a/README.Rmd b/README.qmd similarity index 89% rename from README.Rmd rename to README.qmd index 7b057253..dc1d7dde 100644 --- a/README.Rmd +++ b/README.qmd @@ -1,9 +1,9 @@ --- -output: github_document +title: "handwriter" +format: html +editor: visual --- - - ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, @@ -13,14 +13,43 @@ knitr::opts_chunk$set( ) ``` -# handwriter - -The handwriter package performs writership analysis of a handwritten *questioned document* where the questioned document was written by one of *closed-set* of potential writers. For example, a handwritten bomb threat is found in a science classroom, and the police are able to determine that the note could only have been written by one of the students in 4th period science. The handwriter package builds a statistical model to estimate a *writer profile* from known handwriting samples from each writer in the closed-set. A writer profile is also estimated from the questioned document. The statistical model compares the writer profile from the questioned document with each of the writer profiles from the closed-set of potential writers and estimates the posterior probability that each closed-set writer wrote the questioned document. +Handwriter is designed to assist forensic examiners by analyzing handwritten documents against a *closed set* of potential writers. It determines the probability that each writer wrote the document. Whether you are a forensic document examiner, legal professional, academic, or simply curious about how statistics are applied to handwriting, handwriter provides an automated way to evaluate handwriting samples. + +## Quick Start + +### VIEW A DEMO + +View a demo of handwriter on handwritten documents from the CSAFE Handwriting Database. Go to [demo](https://csafe.shinyapps.io/handwriterAppDemo/). + +### SIMULATE CASEWORK WITH EXAMPLE DOCUMENTS + +#### INSTALLATION + +Handwriter requires R, RStudio IDE, and JAGS. + +- Install R and RStudio from [POSIT](https://posit.co/download/rstudio-desktop/) +- Install JAGS from [SourceForge](https://sourceforge.net/projects/mcmc-jags/files/) + +#### LAUNCH THE APP + +Open RStudio, navigate to the console window, and type: + +```{r, eval = FALSE} +install.packages("devtools") +devtools::install_github("CSAFE-ISU/handwriterApp") +library(handwriterApp) +handwriterApp() +``` + +In the pop-up window, click **Open in Browser**. If you use the app in the pop-up window +instead of in a browser, some links will not work. + +Click **Simulate Casework** and follow the instructions in the app. -## Installation +## Advanced You can install handwriter from CRAN with: ``` r install.packages("handwriter") diff --git a/_quarto/.gitignore b/_quarto/.gitignore new file mode 100644 index 00000000..075b2542 --- /dev/null +++ b/_quarto/.gitignore @@ -0,0 +1 @@ +/.quarto/ diff --git a/docs/CITATION.md b/_quarto/CITATION.md similarity index 63% rename from docs/CITATION.md rename to _quarto/CITATION.md index 34da771f..f7721c54 100644 --- a/docs/CITATION.md +++ b/_quarto/CITATION.md @@ -3,11 +3,10 @@ ```verbatim To cite package ‘handwriter’ in publications use: - Iowa State University of Science and Technology on behalf of its - Center for Statistics and Applications in Forensic Evidence, Berry - N, Reinders S, Taylor J (2024). _handwriter: Handwriting Analysis in - R_. R package version 3.1.1.9000, commit - 2ca3187a3e750fed34d373eae7dd587483c96b75, + Iowa State University of Science and Technology on behalf of its Center for + Statistics and Applications in Forensic Evidence, Berry N, Reinders S, Taylor + J (2024). _handwriter: Handwriting Analysis in R_. R package version + 3.1.1.9000, commit 3b29e861c4bcaed6062f79ebb75c000f9bd86413, . A BibTeX entry for LaTeX users is @@ -16,7 +15,7 @@ A BibTeX entry for LaTeX users is title = {handwriter: Handwriting Analysis in R}, author = {{Iowa State University of Science and Technology on behalf of its Center for Statistics and Applications in Forensic Evidence} and Nick Berry and Stephanie Reinders and James Taylor}, year = {2024}, - note = {R package version 3.1.1.9000, commit 2ca3187a3e750fed34d373eae7dd587483c96b75}, + note = {R package version 3.1.1.9000, commit 3b29e861c4bcaed6062f79ebb75c000f9bd86413}, url = {https://github.com/CSAFE-ISU/handwriter}, } ``` diff --git a/docs/LICENSE.md b/_quarto/LICENSE.md similarity index 100% rename from docs/LICENSE.md rename to _quarto/LICENSE.md diff --git a/docs/NEWS.md b/_quarto/NEWS.md similarity index 94% rename from docs/NEWS.md rename to _quarto/NEWS.md index c4d0ec2c..bd61112b 100644 --- a/docs/NEWS.md +++ b/_quarto/NEWS.md @@ -15,6 +15,8 @@ * Fixed bug in `format_template_data()` where the function coerced writer IDs to integers even if the writer IDs contained characters. +* Fixed bug in `get_clusters_batch()` where the function would stall but not return an error message if a document had a graph with a large number of edges (paths). Now the function deletes graphs with more than 30 edges. + # handwriter 3.1.1 ## Patches diff --git a/_quarto/_quarto.yml b/_quarto/_quarto.yml new file mode 100644 index 00000000..9697e7f4 --- /dev/null +++ b/_quarto/_quarto.yml @@ -0,0 +1,117 @@ +project: + type: website +website: + title: handwriter + navbar: + search: true + right: + - icon: github + href: https://github.com/CSAFE-ISU/handwriter + aria-label: handwriter GitHub + sidebar: + collapse-level: 1 + contents: + - text: Home + file: index.qmd + - section: Articles + contents: + - vignettes/handwriter.Rmd + - section: Reference + contents: + - text: about_variable + file: man/about_variable.qmd + - text: addToFeatures + file: man/addToFeatures.qmd + - text: analyze_questioned_documents + file: man/analyze_questioned_documents.qmd + - text: calculate_accuracy + file: man/calculate_accuracy.qmd + - text: cleanBinaryImage + file: man/cleanBinaryImage.qmd + - text: csafe + file: man/csafe.qmd + - text: drop_burnin + file: man/drop_burnin.qmd + - text: example_analysis + file: man/example_analysis.qmd + - text: example_cluster_template + file: man/example_cluster_template.qmd + - text: example_model + file: man/example_model.qmd + - text: extractGraphs + file: man/extractGraphs.qmd + - text: fit_model + file: man/fit_model.qmd + - text: format_template_data + file: man/format_template_data.qmd + - text: get_cluster_fill_counts + file: man/get_cluster_fill_counts.qmd + - text: get_clusters_batch + file: man/get_clusters_batch.qmd + - text: get_credible_intervals + file: man/get_credible_intervals.qmd + - text: get_posterior_probabilities + file: man/get_posterior_probabilities.qmd + - text: graphToPrototype + file: man/graphToPrototype.qmd + - text: london + file: man/london.qmd + - text: make_clustering_template + file: man/make_clustering_template.qmd + - text: message + file: man/message.qmd + - text: nature1 + file: man/nature1.qmd + - text: plot_cluster_centers + file: man/plot_cluster_centers.qmd + - text: plot_cluster_fill_counts + file: man/plot_cluster_fill_counts.qmd + - text: plot_cluster_fill_rates + file: man/plot_cluster_fill_rates.qmd + - text: plot_credible_intervals + file: man/plot_credible_intervals.qmd + - text: plot_posterior_probabilities + file: man/plot_posterior_probabilities.qmd + - text: plot_trace + file: man/plot_trace.qmd + - text: plotImage + file: man/plotImage.qmd + - text: plotImageThinned + file: man/plotImageThinned.qmd + - text: plotLetter + file: man/plotLetter.qmd + - text: plotLine + file: man/plotLine.qmd + - text: plotNodes + file: man/plotNodes.qmd + - text: process_batch_dir + file: man/process_batch_dir.qmd + - text: process_batch_list + file: man/process_batch_list.qmd + - text: processDocument + file: man/processDocument.qmd + - text: processHandwriting + file: man/processHandwriting.qmd + - text: read_and_process + file: man/read_and_process.qmd + - text: readPNGBinary + file: man/readPNGBinary.qmd + - text: rgb2grayscale + file: man/rgb2grayscale.qmd + - text: rgba2rgb + file: man/rgba2rgb.qmd + - text: thinImage + file: man/thinImage.qmd + - text: twoSent + file: man/twoSent.qmd + - text: whichToFill + file: man/whichToFill.qmd + - text: News + file: NEWS.md + - text: License + file: LICENSE.md + - text: Citation + file: CITATION.md +format: + html: + css: styles.css diff --git a/_quarto/freeze.rds b/_quarto/freeze.rds new file mode 100644 index 0000000000000000000000000000000000000000..cb809a7c4eab85529e73978925039844d310ccae GIT binary patch literal 1538 zcmV+d2L1UTiwFP!000001BF#xuOmkhbvC;XM0^AU1cV5PJSX&5^~WP9*?T``;i6j<(t!85jkwhl;MI6XFY$x9 z3WREC(N%zu@LV>ekjKnQ!dKsNG0Yi6W0^Sj0-LfG%vgb9-5HmAhbJ=B1YEE_ zL8B2r1oh;6(E;c*1s*6_U=1EjFp*Di2Oo;j%iJKI1Zi|53?^$~#tUh7SJ#TAB_9|w zk-I`Ecw-2R8B+_@^`hA${W6bA+Co#!utqp9qE;bnvRKceyjnef2HZPu@h^6~)x+x9 z>iQ-5-dCUf;nTl<_Q}`VGmSsn^6vLs$K$mAhW7*4jehdgIr!64P~_G4Qh7S=^>B%O zbc*eG^YCw7e|^-$G>kiywT$h!)!lRj{pAd8ylKY`PrByTj(cto7r+N6z(#rZ$6?3& zhd*!m?y8LMpTY-lbUFLUd?x$xeqE3I-LSh!rvKvY{RVf<1s;a0Vt#WSZkyv_(*1f; z{6uXxt)F4rQFQa2*n}pg&-Z-)`YQeVbF2^3?K8hRosau1Ps?p<;fXJh4`;}oPD@pN z*lgBqJbstVE7W0Kd1|jOfL||wy~==ju7@3P-|*%t%kR#h`*BV(jQjQdeuR$?n_(KR z=X|2`Ztn8c_~m|_#_8eyil-mU;mx>{ad*Sv#~rhPiyo#bY3 z_`BbX7j~M?ZQV}x5#&h%KYSXtM`=%^{s)a8EvWy?TFo$oYw3cCiqqoQL&2X45fS+FhK7G6V zPe1-A-pQLic-h_Ew7FLn?5eEaB5!tW4uAQ@=ii#cZS1Z($n)U<{9 literal 0 HcmV?d00001 diff --git a/_quarto/index.qmd b/_quarto/index.qmd new file mode 100644 index 00000000..dc1d7dde --- /dev/null +++ b/_quarto/index.qmd @@ -0,0 +1,265 @@ +--- +title: "handwriter" +format: html +editor: visual +--- + +```{r, include = FALSE} +knitr::opts_chunk$set( + collapse = TRUE, + comment = "#>", + fig.path = "man/figures/README-", + out.width = "100%" +) +``` + + + + +Handwriter is designed to assist forensic examiners by analyzing handwritten documents against a *closed set* of potential writers. It determines the probability that each writer wrote the document. Whether you are a forensic document examiner, legal professional, academic, or simply curious about how statistics are applied to handwriting, handwriter provides an automated way to evaluate handwriting samples. + +## Quick Start + +### VIEW A DEMO + +View a demo of handwriter on handwritten documents from the CSAFE Handwriting Database. Go to [demo](https://csafe.shinyapps.io/handwriterAppDemo/). + +### SIMULATE CASEWORK WITH EXAMPLE DOCUMENTS + +#### INSTALLATION + +Handwriter requires R, RStudio IDE, and JAGS. + +- Install R and RStudio from [POSIT](https://posit.co/download/rstudio-desktop/) +- Install JAGS from [SourceForge](https://sourceforge.net/projects/mcmc-jags/files/) + +#### LAUNCH THE APP + +Open RStudio, navigate to the console window, and type: + +```{r, eval = FALSE} +install.packages("devtools") +devtools::install_github("CSAFE-ISU/handwriterApp") +library(handwriterApp) +handwriterApp() +``` + +In the pop-up window, click **Open in Browser**. If you use the app in the pop-up window +instead of in a browser, some links will not work. + +Click **Simulate Casework** and follow the instructions in the app. + +## Advanced +You can install handwriter from CRAN with: +``` r +install.packages("handwriter") +``` + +You can install the development version of handwriter from [GitHub](https://github.com/) with: + +``` r +# install.packages("devtools") +devtools::install_github("CSAFE-ISU/handwriter") +``` + +## Process a Handwriting Example + +The file "phrase_example.png" is a scanned PNG of handwriting from the CSAFE Handwriting Database. This PNG image is included in the handwriter package in a folder called "extdata." Use the helper function `handwriter_example()` to find the path to where "phrase_example.png" is saved on your computer. + +Use `processDocument()` to + +1. read the PNG file +2. convert the writing to black and white +3. thin it to a one-pixel-wide skeleton +4. place nodes to break the writing into component shapes called *graphs* + +```{r example1} +library(handwriter) +phrase <- system.file("extdata", "phrase_example.png", package = "handwriter") +doc <- processDocument(phrase) +``` +We can view the image: + +```{r image} +plotImage(doc) +``` + +We can view the thinned image: +```{r thin} +plotImageThinned(doc) +``` + +We can also view the nodes: +```{r nodes} +plotNodes(doc) +``` + +## Perform Writership Analysis +This section explains how to perform handwriting analysis on questioned documents using handwriter. In particular, handwriter addresses the scenario where an investigator has a questioned handwritten document, a group of persons of interest has been identified, and the questioned document had to have been written by one of the persons of interest. For example, imagine that a handwritten bomb threat was left at a office building's main desk and the police discover that the note had to have been written by one of the one hundred employees working that day. More details on this method can be found in [Crawford 2022]. + +### STEP 1: Create the Main Directory and Subdirectories + +Create a new folder called `main_dir` on your computer to hold the handwriting documents to be analyzed. When we create a new clustering template and fit a statistical model, those files will also be stored in this folder. Create a sub-folder in `main_dir` called `data`. In the `data` folder, create sub-folders called `model_docs`, `questioned_docs`, and `template_docs`. The folder structure will look like this: +```bash +├── main_dir +│ ├── data +│ │ ├── model_docs +│ │ ├── questioned_docs +│ │ ├── template_docs +``` + +### STEP 2: Create a Cluster Template + +Save the handwritten documents that you want to use to train a new cluster template as PNG images in `main_dir > data > template_docs`. The template training documents need to be from writers that are NOT people of interest. Name all of the PNG images with a consistent format that includes an ID for the writer. For example, the PNG images could be named "writer0001.png", "writer0002.png", "writer0003.png" and so on. + +Next, create a new cluster template from the documents in `main_dir > data > template_docs` with the function `make_clustering_template`. This function + +1. Processes the template training documents in `template_docs`, decomposing the handwriting into component shapes called *graphs*. The processed graphs are saved in RDS files in `main_dir \> data \> template_graphs`. +2. Deletes graphs with more than 30 edges. +3. Randomly selects `K` starting cluster centers using seed `centers_seed` for reproducibility. +5. Runs a K-means algorithm with the `K` starting cluster centers and the selected graphs. The algorithm iteratively groups the selected graphs into `K` clusters. The final grouping of `K` clusters is the cluster template. +6. Stores the writer ID for each training document. `writer_indices` is a vector of the start and stop characters of the writer ID in the PNG image file name. For example, if the PNG images are named "writer0001.png", "writer0002.png", "writer0003.png", and so on, `writer_indices = c(7,10)` +7. Performs some of the processes in parallel. Set the number of cores for parallel processing with `num_dist_cores`. + +```{r, eval=FALSE} +template <- make_clustering_template( + main_dir = "path/to/main_dir", + template_docs = "path/to/main_dir/data/template_docs", + writer_indices = c(7,10), + centers_seed = 100, + K = 40, + num_dist_cores = 4, + max_iters = 25) +``` + +Type `?make_clustering_template` in the RStudio console for more information about the function's arguments. + +For the remainder of this tutorial, we use a small example cluster template, `example_cluster_template` included in handwriter. +```{r} +template <- example_cluster_template +``` + +The idea behind the cluster template and the hierarchical model is that we can decompose a handwritten document into component graphs, assign each graph to the *nearest* cluster, the cluster with the closest shape, in the cluster template, and count the number of graphs in each cluster. We characterize writers by the number of a writer's graphs that are assigned to each cluster. We refer to this as a writer's *cluster fill counts* and it serves as writer profile. + +We can plot the cluster fill counts for each writer in the template training set. First we format the template data to get the cluster fill counts in the proper format for the plotting function. + +```{r} +template_data <- format_template_data(template = template) +plot_cluster_fill_counts(template_data, facet = TRUE) +``` + + +### STEP 3: Fit a Hierarchical Model + +We will use handwriting samples from each person of interest, calculate the cluster fill counts from each sample using the cluster template, and fit a hierarchical model to estimate each person of interest's true cluster fill counts. + +Save your known handwriting samples from the persons of interest in `main_dir \> data \> model_docs` as PNG images. The model requires three handwriting samples from each person of interest. Each sample should be at least one paragraph in length. Name the PNG images with a consistent format so that all file names are the same length and the writer ID's are in the same location. For example, "writer0001_doc1.png", "writer0001_doc2.png", "writer0001_doc3.png", "writer0002_doc1.png", and so on. + +We fit a hierarchical model with the function `fit_model`. This function does the following: + +1. Processes the model training documents in `model_docs`, decomposing the handwriting into component graphs. The processed graphs are saved in RDS files in `main_dir \> data \> model_graphs`. +2. Calculates the cluster fill counts for each document by assigning each graph to the nearest cluster in the cluster template and counting the number of graphs assigned to each cluster. The cluster assignments are saved in main_dir \> data \> model_clusters.rds +3. Fits a hierarchical model to the cluster fill counts using the RJAGS package and draws posterior samples of model parameters with the coda package. + +In this example, we use 4000 MCMC iterations for the model. The inputs `writer_indices` and `doc_indices` are the starting and stopping characters in the model training documents file names that contains the writer ID and a document name. + +```{r, eval = FALSE} +model <- fit_model(main_dir = "path/to/main_dir", + model_docs = "path/to/main_dir/data/model_docs", + num_iters = 4000, + num_chains = 1, + num_cores = 2, + writer_indices = c(7, 10), + doc_indices = c(11, 14)) +``` + +For this tutorial, we will use the small example model, `example_model`, included in handwriter. This model was trained from three documents each from writers 9, 30, 203, 238, and 400 from the [CSAFE handwriting database](https://data.csafe.iastate.edu/HandwritingDatabase/). +```{r} +model <- example_model +``` + + +We can plot the cluster fill counts for each person of interest. (NOTE: We had to format the template data to work with the plotting function, but the model data is already in the correct format.) + +```{r} +plot_cluster_fill_counts(formatted_data=model, facet = TRUE) +``` +The bars across the top of each graph show the Writer ID. Each graph has a line for each known handwriting sample from a given writer. + +#### Hierarchical Model Variables and Burn-in +If you are interested in the variables used by the hierarchical model, continue reading this section. Otherwise, feel free to skip to the next section to learn how to analyze questioned documents. + +We can list the variables in the model: +```{r} +names(as.data.frame(coda::as.mcmc(model$fitted_model[[1]]))) +``` + +View a description of a variable with the `about_variable` function. + +```{r} +about_variable(variable = "mu[1,1]", model = model) +``` + +View a trace plot of a variable. + +```{r} +plot_trace(variable = "mu[1,1]", model = model) +``` + +If we need to, we can drop the beginning MCMC iterations for burn-in. For example, if we want to drop the first 25 iterations, we use + +```{r} +model <- drop_burnin(model, burn_in = 25) +``` + +If we want to save the updated model as the current model for this project, replace `model.rds` in the `data` folder with +```{r, eval=FALSE} +saveRDS(model, file='data/model.rds') +``` + +### Analyze Questioned Documents +Save your questioned document(s) in `main_dir > data > questioned_docs` as PNG images. Assign a new writer ID to the questioned documents and name the documents consistently. E.g. "unknown1000_doc1.png", "unknown1001_doc1.png", and so on. + +We estimate the posterior probability of writership for each of the questioned documents with the function `analyze_questioned_documents`. This function does the following: + +1. **Process Questioned Document(s):** Processes the questioned documents in `questioned_docs`, decomposing the handwriting into component graphs. The processed graphs are saved in RDS files in `main_dir \> data \> questioned_graphs`. +2. **Estimate the Writer Profile of the Questioned Document(s):** Calculates the cluster fill counts for each questioned document by assigning each graph to the nearest cluster in the cluster template and counting the number of graphs assigned to each cluster. The cluster assignments are saved in `main_dir \> data \> questioned_clusters.rds`. +3. **Estimate the Posterior Probability of Writership:** Uses the fitted model from Step 3 to estimate the posterior probability of writership for each questioned document and each person of interest. The results are saved in `main_dir \> data \> analysis.rds`. + +```{r, eval = FALSE} +analysis <- analyze_questioned_documents( + main_dir = "path/to/main_dir", + questioned_docs = "path/to/main_dir/questioned_docs", + model = model, + writer_indices = c(8,11), + doc_indices = c(13,16), + num_cores = 2) +``` + +Let's pretend that a handwriting sample from each of the 5 "persons of interest" is a questioned document. These documents are also from the [CSAFE handwriting database](https://data.csafe.iastate.edu/HandwritingDatabase/) and have already been analyzed with `example_model` and the results are included in handwriter as `example_analysis`. + +```{r} +analysis <- example_analysis +``` + + +View the cluster fill counts for each questioned document. Intuitively, the model assesses which writer's cluster fill counts look the most like the cluster fill counts observed in each questioned document. + +```{r} +plot_cluster_fill_counts(analysis, facet = TRUE) +``` + +View the posterior probabilities of writership. + +```{r} +analysis$posterior_probabilities +``` + + +#### For Research Only +In practice, we would not know who wrote a questioned document, but in research we often perform tests to evaluate models using data where we know the ground truth. Because in this example, we know the true writer of each questioned document, we can measure the accuracy of the model. We define accuracy as the average posterior probability assigned to the true writer. The accuracy of our model is + +```{r} +calculate_accuracy(analysis) +``` + diff --git a/_quarto/man/about_variable.qmd b/_quarto/man/about_variable.qmd new file mode 100644 index 00000000..2673a7b9 --- /dev/null +++ b/_quarto/man/about_variable.qmd @@ -0,0 +1,47 @@ +## About Varialbe {.unnumbered} + + +### Description + +about_variable() returns information about the model variable. + + + +### Usage + +
about_variable(variable, model)
+
+ + +### Arguments + + + + + + +
variable +A variable in the fitted model output by fit_model() +
model +A fitted model created by fit_model() +
+ + +### Value + +Text that explains the variable + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +about_variable( + variable = "mu[1,2]", + model = example_model +) + + + +``` diff --git a/_quarto/man/addToFeatures.qmd b/_quarto/man/addToFeatures.qmd new file mode 100644 index 00000000..0dd25aee --- /dev/null +++ b/_quarto/man/addToFeatures.qmd @@ -0,0 +1,39 @@ + +## addToFeatures {.unnumbered} + + +### Description + +addToFeatures + + + +### Usage + +
addToFeatures(FeatureSet, LetterList, vectorDims)
+
+ + +### Arguments + + + + + + + + +
FeatureSet +The current list of features that have been calculated +
LetterList +List of all letters and their information +
vectorDims +Vectors with image Dims +
+ + +### Value + +A list consisting of current features calculated in FeatureSet as well as measures of compactness, loop count, and loop dimensions + + diff --git a/_quarto/man/analyze_questioned_documents.qmd b/_quarto/man/analyze_questioned_documents.qmd new file mode 100644 index 00000000..a6002642 --- /dev/null +++ b/_quarto/man/analyze_questioned_documents.qmd @@ -0,0 +1,82 @@ +## Analyze Questioned Documents {.unnumbered} + + +### Description + +analyze_questioned_documents() estimates the posterior probability of +writership for the questioned documents using Markov Chain Monte Carlo (MCMC) draws from a hierarchical +model created with fit_model(). + + + +### Usage + +
analyze_questioned_documents(
+  main_dir,
+  questioned_docs,
+  model,
+  num_cores,
+  writer_indices,
+  doc_indices
+)
+
+ + +### Arguments + + + + + + + + + + + + + + +
main_dir +A directory that contains a cluster template created by make_clustering_template() +
questioned_docs +A directory containing questioned documents +
model +A fitted model created by fit_model() +
num_cores +An integer number of cores to use for parallel processing +with the doParallel package. +
writer_indices +A vector of start and stop characters for writer IDs in file names +
doc_indices +A vector of start and stop characters for document names in file names +
+ + +### Value + +A list of likelihoods, votes, and posterior probabilities of +writership for each questioned document. + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=FALSE} +library(handwriter) + +main_dir <- "/path/to/main_dir" +questioned_docs <- "/path/to/questioned_images" +analysis <- analyze_questioned_documents( + main_dir = main_dir, + questioned_docs = questioned_docs, + model = model, + num_cores = 2, + writer_indices = c(2, 5), + doc_indices = c(7, 18) +) +analysis$posterior_probabilities + + + + +``` diff --git a/_quarto/man/calculate_accuracy.qmd b/_quarto/man/calculate_accuracy.qmd new file mode 100644 index 00000000..354e748c --- /dev/null +++ b/_quarto/man/calculate_accuracy.qmd @@ -0,0 +1,59 @@ +## Calculate Accuracy {.unnumbered} + + +### Description + +Fit a model with fit_model() and calculate posterior probabilities of +writership with analyze_questioned_documents() of a set of test documents +where the ground truth is known. Then use calculate_accuracy() to measure +the accuracy of the fitted model on the test documents. Accuracy is calculated as +the average posterior probability assigned to the true writer. + + + +### Usage + +
calculate_accuracy(analysis)
+
+ + +### Arguments + + + + +
analysis +Writership analysis output by +analyze_questioned_documents +
+ + +### Value + +The model's accuracy on the test set as a number + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=FALSE} +library(handwriter) + +# calculate the accuracy for example analysis performed on test documents and a model with 1 chain +calculate_accuracy(example_analysis) + +main_dir <- "/path/to/main_dir" +test_images_dir <- "/path/to/test_images" +analysis <- analyze_questioned_documents( + main_dir = main_dir, + questioned_docs = test_images_dir, + model = model, + num_cores = 2, + writer_indices = c(2, 5), + doc_indices = c(7, 18) +) +calculate_accuracy(analysis) + + + + +``` diff --git a/_quarto/man/cleanBinaryImage.qmd b/_quarto/man/cleanBinaryImage.qmd new file mode 100644 index 00000000..d6621b30 --- /dev/null +++ b/_quarto/man/cleanBinaryImage.qmd @@ -0,0 +1,31 @@ + +## cleanBinaryImage {.unnumbered} + + +### Description + +Removes alpha channel from png image. + + + +### Usage + +
cleanBinaryImage(img)
+
+ + +### Arguments + + + + +
img +A matrix of 1s and 0s. +
+ + +### Value + +png image with the alpha channel removed + + diff --git a/docs/man/csafe.md b/_quarto/man/csafe.qmd similarity index 62% rename from docs/man/csafe.md rename to _quarto/man/csafe.qmd index f21c4e58..fbecbddb 100644 --- a/docs/man/csafe.md +++ b/_quarto/man/csafe.qmd @@ -1,39 +1,34 @@ +## Cursive written word: csafe {.unnumbered} -# Cursive written word: csafe - -## Description +### Description Cursive written word: csafe -## Usage + + +### Usage
csafe
 
-## Format + +### Format Binary image matrix. 111 rows and 410 columns. -## Examples -``` r + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} library(handwriter) csafe_document <- list() csafe_document$image <- csafe plotImage(csafe_document) -``` - -![](csafe.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) - -``` r csafe_document$thin <- thinImage(csafe_document$image) plotImageThinned(csafe_document) -``` +csafe_processList <- processHandwriting(csafe_document$thin, dim(csafe_document$image)) -![](csafe.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-2.png) -``` r -csafe_processList <- processHandwriting(csafe_document$thin, dim(csafe_document$image)) ``` diff --git a/_quarto/man/drop_burnin.qmd b/_quarto/man/drop_burnin.qmd new file mode 100644 index 00000000..621d6ee0 --- /dev/null +++ b/_quarto/man/drop_burnin.qmd @@ -0,0 +1,45 @@ +## Drop Burn-In {.unnumbered} + + +### Description + +drop_burnin() removes the burn-in from the Markov Chain Monte Carlo (MCMC) draws. + + + +### Usage + +
drop_burnin(model, burn_in)
+
+ + +### Arguments + + + + + + +
model +A list of MCMC draws from a model fit with fit_model(). +
burn_in +An integer number of starting iterations to drop from each MCMC chain. +
+ + +### Value + +A list of data frames of MCMC draws with burn-in dropped. + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +model <- drop_burnin(model = example_model, burn_in = 25) +plot_trace(variable = "mu[1,2]", model = example_model) + + + +``` diff --git a/_quarto/man/example_analysis.qmd b/_quarto/man/example_analysis.qmd new file mode 100644 index 00000000..92e651b1 --- /dev/null +++ b/_quarto/man/example_analysis.qmd @@ -0,0 +1,50 @@ +## Example of writership analysis {.unnumbered} + + +### Description + +Example of writership analysis + + + +### Usage + +
example_analysis
+
+ + +### Format + +The results of analyze_questioned_documents() stored in a named list with 5 items: + + +
+
graph_measurements
A data frame of that shows the writer, document name, cluster assignment, +slope, principle component rotation angle, and wrapped principle component rotation angle for each training graph in each +questioned documents. +
+
cluster_fill_counts
A data frame of the cluster fill counts for each questioned document. +
+
likelihoods
A list of data frames where each data frame +contains the likelihoods for a questioned document for each MCMC iteration. +
+
votes
A list of vote tallies for each questioned document. +
+
posterior_probabilites
A list of posterior probabilities of writership +for each questioned document and each known writer in the closed set used to train the +hierarchical model. +
+
+ + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +plot_cluster_fill_counts(formatted_data = example_analysis) +plot_posterior_probabilities(analysis = example_analysis) + + + +``` diff --git a/_quarto/man/example_cluster_template.qmd b/_quarto/man/example_cluster_template.qmd new file mode 100644 index 00000000..b75de27c --- /dev/null +++ b/_quarto/man/example_cluster_template.qmd @@ -0,0 +1,79 @@ +## Example cluster template {.unnumbered} + + +### Description + +An example cluster template created with make_clustering_template(). The +cluster template was created from handwriting samples +"w0016_s01_pLND_r01.png", "w0080_s01_pLND_r01.png", "w0124_s01_pLND_r01.png", +"w0138_s01_pLND_r01.png", and "w0299_s01_pLND_r01.png" from the CSAFE Handwriting +Database. The template has K=5 clusters. + + + +### Usage + +
example_cluster_template
+
+ + +### Format + +A list containing a single cluster template created by +make_clustering_template(). The cluster template was created by sorting +a random sample of 1000 graphs from 10 training documents into 10 clusters +with a K-means algorithm. The cluster template is a named list with 16 +items: + + +
+
centers_seed
An integer for the random number generator. +
+
cluster
A vector of cluster assignments +for each graph used to create the cluster template. +
+
centers
The final cluster centers produced by the K-Means algorithm. +
+
K
The number of clusters to build (10) with the K-means algorithm. +
+
n
The number of training graphs to use (1000) in the K-means +algorithm. +
+
docnames
A vector that lists the training document from which each graph originated. +
+
writers
A vector that lists the writer of each graph. +
+
iters
The maximum number of iterations for the K-means +algorithm (3). +
+
changes
A vector of the number of graphs that +changed clusters on each iteration of the K-means algorithm. +
+
outlierCutoff
A vector of the outlier cutoff values calculated on +each iteration of the K-means algorithm. +
+
stop_reason
The reason the +K-means algorithm terminated. +
+
wcd
A matrix of the within cluster +distances on each iteration of the K-means algorithm. More specifically, +the distance between each graph and the center of the cluster to which it +was assigned on each iteration. +
+
wcss
A vector of the +within-cluster sum of squares on each iteration of the K-means algorithm. +
+ + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +# view cluster fill counts for template training documents +template_data <- format_template_data(example_cluster_template) +plot_cluster_fill_counts(template_data, facet = TRUE) + + + +``` diff --git a/_quarto/man/example_model.qmd b/_quarto/man/example_model.qmd new file mode 100644 index 00000000..e370dfd5 --- /dev/null +++ b/_quarto/man/example_model.qmd @@ -0,0 +1,65 @@ +## Example of a hierarchical model {.unnumbered} + + +### Description + +Example of a hierarchical model + + + +### Usage + +
example_model
+
+ + +### Format + +A hierarchical model created by fit_model with a single chain of 100 MCMC iterations. It is a named +list of 4 objects: + + +
+
graph_measurements
A data frame of model training data that shows the writer, document name, cluster assignment, +slope, principle component rotation angle, and wrapped principle component rotation angle for each training graph. +
+
cluster_fill_counts
A data frame of the cluster fill counts for each model training document. +
+
rjags_data
The model training information from graph_measurements and cluster_fill_counts formatted for RJAGS. +
+
fitted_model
A model fit using the rjags_data and the RJAGS and coda packages. It is an MCMC list that contains a single +MCMC object. +
+
+ + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=FALSE} +library(handwriter) + +# convert to a data frame and view all variable names +df <- as.data.frame(coda::as.mcmc(example_model$fitted_model)) +colnames(df) + +# view a trace plot +plot_trace(variable = "mu[1,1]", model = example_model) + +# drop the first 25 MCMC iterations for burn-in +model <- drop_burnin(model = example_model, burn_in = 25) + +# analyze questioned documents +main_dir <- /path/to/main_dir +questioned_docs <- /path/to/questioned_documents_directory +analysis <- analyze_questioned_documents( + main_dir = main_dir, + questioned_docs = questioned_docs + model = example_model + num_cores = 2 +) +analysis$posterior_probabilities + + + + +``` diff --git a/_quarto/man/extractGraphs.qmd b/_quarto/man/extractGraphs.qmd new file mode 100644 index 00000000..2944334b --- /dev/null +++ b/_quarto/man/extractGraphs.qmd @@ -0,0 +1,54 @@ +## Extract Graphs {.unnumbered} + + +### Description + +'r lifecycle::badge("superseded")' + + + +### Usage + +
extractGraphs(source_folder = getwd(), save_folder = getwd())
+
+ + +### Arguments + + + + + + +
source_folder +path to folder containing .png images +
save_folder +path to folder where graphs are saved to +
+ + +### Details + +Development on 'extractGraphs()' is complete. We recommend using 'process_batch_dir()' instead. + +Extracts graphs from .png images and saves each by their respective writer. + + + +### Value + +saves graphs in an rds file + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=FALSE} +library(handwriter) + +sof = "path to folder containing .png images" +saf = "path to folder where graphs will be saved to" +extractGraphs(sof, saf) + + + +``` diff --git a/_quarto/man/figures/README-image-1.png b/_quarto/man/figures/README-image-1.png new file mode 100644 index 0000000000000000000000000000000000000000..047eecad6cb4f1c49f0d655d2ff20007590ee6c8 GIT binary patch literal 33134 zcmeHwdpy%^_`g#{N2Q~4d87kL$obHT=Siibvng|IX`wj{Un&>fBgRW{j)#3UZ2-zpWUD9zV7RKU+?RE-?(}FnDvUK z@=L|U#8&+E=fRU=Vv8)r#3ZYv7Xx=jy_(y_#H3dG9yo9ua=`ik^a3>C)TMJ^PixPM zo&mn#lh*si#0=x&&baz0o>^=DsI+kBAH*vySy}g1PU}A?x^VKt)sFsY&qBXW&HERM z_T8x)>`L?9s>_&s;=A2^?LOHz&${n-&p5x)*nB>ReOv3FqT~NaUD-C)G-3Vt;|3X4 zscvD}{SpYSzH_`Ul^e;V1#)Q1?v!XcC(zU-H0ATPdYgL+34PVo#+TnjG_8ne(%KpS 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zc=O4kx1N9=>pe0|1nEEA!sW7X@rv^bAhgBDauc{*CUk?(8!~nf^Ndo{9y95U1G|Z{ zJ9zwOyo3_aFv*7R8J_(4OY#7)m0?|$A@)?7{5(;F`RvUuPH`k7P`SF2j# z<}kDIXqC17&P;hpNlBIK&8soWxm>8t4@lT5m%Z0)|1jM!BvdE~Gd`3*^Tgu~>v*{O z7WjM1(%EY3_OgR_E-o$>mC^JXDsSI@=5#*oPnfKGXWbvY$@AqKD92Ts<5dV(WPA~*N-LXCUiqL9m;iFoOft~0CJ0}|!UYNn z)>DN4m0V^+xVhs@P7amR?wkj=F6gc*;c_{z>O=H4o2nYfr_8|sg*fXkin__8BO}!e zDjH>=&bS@p_E*DH=y&_vZalAQ%`%S;EJ**12MWdzfnviNU=h2yCXcxqKqb|Pi<)vR zvM{Ptnk9ht%DdX2B(HN11;4C7t@cG%nOu{cNB6ibSNTlFtgU)&-G=K>rj-3b_D2^G zi@!{jmzTe=oNv*r+y128d@txgxGy0V3Q_`2|1!M-l%+t3C^W=A9d9yu=6>g|9(w^# zL#FeC*Kt%O3Q9}^Ee$5 zGl%jtdwTfcBY7w*P;?c^e9UYVFvQoilP#nHs4~BO>zq1$k1D z%ei%GxEPeg&m)i5N2rZWOl)SKnvmPWIX~1KDK$JGby*po-juDz*8aQPUqQ(Emk<6U z1|%?`VI{+IedWdv4*Da@zdru~1IyFwvMTV$DgKQgJWw9+z$OBBgWFU8j_qf(`FRYU zDiDJ$2ps>$zrSLk@(_Ln$0oj9*jxSU$N%{Xm5vAM`IL|PpGE%T4fit_model() fits a Bayesian hierarchical model to the model training data +in model_docs and draws samples from the model as Markov Chain Monte +Carlo (MCMC) estimates. + + + +### Usage + +

fit_model(
+  main_dir,
+  model_docs,
+  num_iters,
+  num_chains = 1,
+  num_cores,
+  writer_indices,
+  doc_indices,
+  a = 2,
+  b = 0.25,
+  c = 2,
+  d = 2,
+  e = 0.5
+)
+
+ + +### Arguments + + + + + + + + + + + + + + + + + + + + + + + + + + +
main_dir +A directory that contains a cluster template created by +make_clustering_template() +
model_docs +A directory containing model training documents +
num_iters +An integer number of iterations of MCMC. +
num_chains +An integer number of chains to use. +
num_cores +An integer number of cores to use for parallel processing +clustering assignments. The model fitting is not done in parallel. +
writer_indices +A vector of the start and stop character of the writer +ID in the model training file names. E.g., if the file names are +writer0195_doc1, writer0210_doc1, writer0033_doc1 then writer_indices is +'c(7,10)'. +
doc_indices +A vector of the start and stop character of the "document +name" in the model training file names. This is used to distinguish between +two documents written by the same writer. E.g., if the file names are +writer0195_doc1, writer0195_doc2, writer0033_doc1, writer0033_doc2 then +doc_indices are 'c(12,15)'. +
a +The shape parameter for the Gamma distribution in the hierarchical +model +
b +The rate parameter for the Gamma distribution in the hierarchical +model +
c +The first shape parameter for the Beta distribution in the +hierarchical model +
d +The second shape parameter for the Beta distribution in the +hierarchical model +
e +The scale parameter for the hyper prior for mu in the hierarchical +model +
+ + +### Value + +A list of training data used to fit the model and the fitted model + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=FALSE} +library(handwriter) + +main_dir <- "/path/to/main_dir" +model_docs <- "path/to/model_training_docs" +questioned_docs <- "path/to/questioned_docs" + +model <- fit_model( + main_dir = main_dir, + model_docs = model_docs, + num_iters = 100, + num_chains = 1, + num_cores = 2, + writer_indices = c(2, 5), + doc_indices = c(7, 18) +) + +model <- drop_burnin(model = model, burn_in = 25) + +analysis <- analyze_questioned_documents( + main_dir = main_dir, + questioned_docs = questioned_docs, + model = model, + num_cores = 2 +) +analysis$posterior_probabilities + + + + +``` diff --git a/_quarto/man/format_template_data.qmd b/_quarto/man/format_template_data.qmd new file mode 100644 index 00000000..8dd5db99 --- /dev/null +++ b/_quarto/man/format_template_data.qmd @@ -0,0 +1,44 @@ +## Format Template Data {.unnumbered} + + +### Description + +format_template_data() formats the template data for use with +plot_cluster_fill_counts(). The output is a list that contains a data frame +called cluster_fill_counts. + + + +### Usage + +
format_template_data(template)
+
+ + +### Arguments + + + + +
template +A single cluster template created by +make_clustering_template() +
+ + +### Value + +List that contains the cluster fill counts + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +template_data <- format_template_data(template = example_cluster_template) +plot_cluster_fill_counts(formatted_data = template_data, facet = TRUE) + + + +``` diff --git a/_quarto/man/get_cluster_fill_counts.qmd b/_quarto/man/get_cluster_fill_counts.qmd new file mode 100644 index 00000000..04af73de --- /dev/null +++ b/_quarto/man/get_cluster_fill_counts.qmd @@ -0,0 +1,48 @@ +## get_cluster_fill_counts {.unnumbered} + + +### Description + +get_cluster_fill_counts() creates a data frame that shows the number of +graphs in each cluster for each input document. + + + +### Usage + +
get_cluster_fill_counts(df)
+
+ + +### Arguments + + + + +
df +A data frame with columns writer, doc, and cluster. Each +row corresponding to a graph and lists the writer of that graph, the document +from which the graph was obtained, and the cluster to which that graph is assigned. +
+ + +### Value + +A dataframe of cluster fill counts for each document in the input data frame. + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +writer <- c(rep(1, 20), rep(2, 20), rep(3, 20)) +docname <- c(rep('doc1',20), rep('doc2', 20), rep('doc3', 20)) +doc <- c(rep(1, 20), rep(2, 20), rep(3, 20)) +cluster <- sample(3, 60, replace=TRUE) +df <- data.frame(docname, writer, doc, cluster) +get_cluster_fill_counts(df) + + + +``` diff --git a/_quarto/man/get_clusters_batch.qmd b/_quarto/man/get_clusters_batch.qmd new file mode 100644 index 00000000..f8ed70b1 --- /dev/null +++ b/_quarto/man/get_clusters_batch.qmd @@ -0,0 +1,75 @@ +## get_clusters_batch {.unnumbered} + + +### Description + +get_clusters_batch + + + +### Usage + +
get_clusters_batch(
+  template,
+  input_dir,
+  output_dir,
+  writer_indices,
+  doc_indices,
+  num_cores = 1
+)
+
+ + +### Arguments + + + + + + + + + + + + + + +
template +A cluster template created with make_clustering_template +
input_dir +A directory containing graphs created with process_batch_dir +
output_dir +Output directory for cluster assignments +
writer_indices +Vector of start and end indices for the writer id in +the graph file names +
doc_indices +Vector of start and end indices for the document id in the +graph file names +
num_cores +Integer number of cores to use for parallel processing +
+ + +### Value + +A list of cluster assignments + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=FALSE} +library(handwriter) + +template <- readRDS('path/to/template.rds') +get_clusters_batch(template=template, input_dir='path/to/dir', output_dir='path/to/dir', +writer_indices=c(2,5), doc_indices=c(7,18), num_cores=1) + +get_clusters_batch(template=template, input_dir='path/to/dir', output_dir='path/to/dir', +writer_indices=c(1,4), doc_indices=c(5,10), num_cores=5) + + + + +``` diff --git a/_quarto/man/get_credible_intervals.qmd b/_quarto/man/get_credible_intervals.qmd new file mode 100644 index 00000000..b9189582 --- /dev/null +++ b/_quarto/man/get_credible_intervals.qmd @@ -0,0 +1,54 @@ +## Get Credible Intervals {.unnumbered} + + +### Description + +In a model created with fit_model() the pi parameters are the estimate of +the true cluster fill count for a particular writer and cluster. The function +get_credible_intervals() calculates the credible intervals of the pi +parameters for each writer in the model. + + + +### Usage + +
get_credible_intervals(model, interval_min = 0.05, interval_max = 0.95)
+
+ + +### Arguments + + + + + + + + +
model +A model output by fit_model() +
interval_min +The lower bound for the credible interval. The number +must be between 0 and 1. +
interval_max +The upper bound for the credible interval. The number +must be greater than interval_min and must be less than 1. +
+ + +### Value + +A list of data frames. Each data frame lists the credible intervals for a single writer. + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +get_credible_intervals(model=example_model) +get_credible_intervals(model=example_model, interval_min=0.05, interval_max=0.95) + + + +``` diff --git a/_quarto/man/get_posterior_probabilities.qmd b/_quarto/man/get_posterior_probabilities.qmd new file mode 100644 index 00000000..ba5c2b8d --- /dev/null +++ b/_quarto/man/get_posterior_probabilities.qmd @@ -0,0 +1,52 @@ +## Get Posterior Probabilities {.unnumbered} + + +### Description + +Get the posterior probabilities for questioned document analyzed with analyze_questioned_documents(). + + + +### Usage + +
get_posterior_probabilities(analysis, questioned_doc)
+
+ + +### Arguments + + + + + + +
analysis +The output of analyze_questioned_documents(). If more than +one questioned document was analyzed with this function, then the data frame +analysis\$posterior_probabilities lists the posterior probabilities for all +questioned documents. get_posterior_probabilities() creates a data frame of the +posterior probabilities for a single questioned document and sorts the known writers +from the most likely to least likely to have written the questioned document. +
questioned_doc +The filename of the questioned document +
+ + +### Value + +A data frame of posterior probabilities for the questioned document + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +get_posterior_probabilities( + analysis = example_analysis, + questioned_doc = "w0030_s03_pWOZ_r01" +) + + + +``` diff --git a/_quarto/man/graphToPrototype.qmd b/_quarto/man/graphToPrototype.qmd new file mode 100644 index 00000000..7929e71f --- /dev/null +++ b/_quarto/man/graphToPrototype.qmd @@ -0,0 +1,42 @@ + +## Convert graph to a prototype {.unnumbered} + + +### Description + +A graph prototype consists of the starting and ending points of each path in +the graph, as well as and evenly spaced points along each path. The prototype +also stores the center point of the graph. All points are represented as +xy-coordinates and the center point is at (0,0). + + + +### Usage + +
graphToPrototype(graph, numPathCuts = 8)
+
+ + +### Arguments + + + + + + +
graph +A graph from a handwriting sample +
numPathCuts +Number of segments to cut the path(s) into +
+ + +### Value + +List of pathEnds, pathQuarters, and pathCenters given as (x,y) +coordinates with the graph centroid at (0,0). The returned list also +contains path lengths. pathQuarters gives the (x,y) coordinates of the path +at the cut points and despite the name, the path might not be cut into +quarters. + + diff --git a/docs/man/london.md b/_quarto/man/london.qmd similarity index 62% rename from docs/man/london.md rename to _quarto/man/london.qmd index b57fea21..5c82b75f 100644 --- a/docs/man/london.md +++ b/_quarto/man/london.qmd @@ -1,39 +1,34 @@ +## Cursive written word: London {.unnumbered} -# Cursive written word: London - -## Description +### Description Cursive written word: London -## Usage + + +### Usage
london
 
-## Format + +### Format Binary image matrix. 148 rows and 481 columns. -## Examples -``` r + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} library(handwriter) london_document <- list() london_document$image <- london plotImage(london_document) -``` - -![](london.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) - -``` r london_document$thin <- thinImage(london_document$image) plotImageThinned(london_document) -``` +london_processList <- processHandwriting(london_document$thin, dim(london_document$image)) -![](london.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-2.png) -``` r -london_processList <- processHandwriting(london_document$thin, dim(london_document$image)) ``` diff --git a/_quarto/man/make_clustering_template.qmd b/_quarto/man/make_clustering_template.qmd new file mode 100644 index 00000000..6288cc79 --- /dev/null +++ b/_quarto/man/make_clustering_template.qmd @@ -0,0 +1,93 @@ +## Make Clustering Template {.unnumbered} + + +### Description + +make_clustering_template() applies a K-means clustering algorithm to the +input handwriting samples pre-processed with process_batch_dir() and saved +in the input folder main_dir > data > template_graphs. The K-means +algorithm sorts the graphs in the input handwriting samples into groups, or +clusters, of similar graphs. + + + +### Usage + +
make_clustering_template(
+  main_dir,
+  template_docs,
+  writer_indices,
+  centers_seed,
+  K = 40,
+  num_dist_cores = 1,
+  max_iters = 25
+)
+
+ + +### Arguments + + + + + + + + + + + + + + + + +
main_dir +Main directory that will store template files +
template_docs +A directory containing template training images +
writer_indices +A vector of the starting and ending location of the +writer ID in the file name. +
centers_seed +Integer seed for the random number generator when +selecting starting cluster centers. +
K +Integer number of clusters +
num_dist_cores +Integer number of cores to use for the distance +calculations in the K-means algorithm. Each iteration of the K-means +algorithm calculates the distance between each input graph and each cluster +center. +
max_iters +Maximum number of iterations to allow the K-means algorithm +to run +
+ + +### Value + +List containing the cluster template + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=FALSE} +library(handwriter) + +main_dir <- "path/to/folder" +template_docs <- "path/to/template_training_docs" +template_list <- make_clustering_template( + main_dir = main_dir, + template_docs = template_docs, + writer_indices = c(2, 5), + K = 10, + num_dist_cores = 2, + max_iters = 25, + centers_seed = 100, +) + + + + +``` diff --git a/docs/man/message.md b/_quarto/man/message.qmd similarity index 76% rename from docs/man/message.md rename to _quarto/man/message.qmd index 268d446a..e9ee4716 100644 --- a/docs/man/message.md +++ b/_quarto/man/message.qmd @@ -1,23 +1,26 @@ +## Full page image of the handwritten London letter. {.unnumbered} -# Full page image of the handwritten London letter. - -## Description +### Description Full page image of the handwritten London letter. -## Usage + + +### Usage
message
 
-## Format + +### Format Binary image matrix. 1262 rows and 1162 columns. -## Examples -``` r + +### Examples +```{r, warning=FALSE, message=FALSE, eval=FALSE} library(handwriter) message_document <- list() @@ -30,4 +33,7 @@ plotImage(message_document) message_document$thin <- thinImage(message_document$image) plotImageThinned(message_document) message_processList <- processHandwriting(message_document$thin, dim(message_document$image)) + + + ``` diff --git a/docs/man/nature1.md b/_quarto/man/nature1.qmd similarity index 72% rename from docs/man/nature1.md rename to _quarto/man/nature1.qmd index 7366561b..b1e94e21 100644 --- a/docs/man/nature1.md +++ b/_quarto/man/nature1.qmd @@ -1,24 +1,26 @@ +## Full page image of the 4th sample (nature) of handwriting from the first writer. {.unnumbered} -# Full page image of the 4th sample (nature) of handwriting from the first writer. +### Description -## Description +Full page image of the 4th sample (nature) of handwriting from the first writer. -Full page image of the 4th sample (nature) of handwriting from the first -writer. -## Usage + +### Usage
nature1
 
-## Format + +### Format Binary image matrix. 811 rows and 1590 columns. -## Examples -``` r + +### Examples +```{r, warning=FALSE, message=FALSE, eval=FALSE} library(handwriter) nature1_document <- list() @@ -31,4 +33,7 @@ plotImage(nature1_document) nature1_document$thin <- thinImage(nature1_document$image) plotImageThinned(nature1_document) nature1_processList <- processHandwriting(nature1_document$thin, dim(nature1_document$image)) + + + ``` diff --git a/docs/man/plotImage.md b/_quarto/man/plotImage.qmd similarity index 54% rename from docs/man/plotImage.md rename to _quarto/man/plotImage.qmd index 674e344b..98519831 100644 --- a/docs/man/plotImage.md +++ b/_quarto/man/plotImage.qmd @@ -1,39 +1,36 @@ +## Plot Image {.unnumbered} -# Plot Image +### Description -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) +This function plots a basic black and white image. -## Description -This function plots a basic black and white image. -## Usage +### Usage
plotImage(doc)
 
-## Arguments + +### Arguments - - + - +A document processed with processDocument() or a binary matrix (all entries are 0 or 1) +
-doc -
doc -A document processed with processDocument() or a binary -matrix (all entries are 0 or 1) -
-## Value + +### Value ggplot plot -## Examples -``` r + +### Examples +```{r, warning=FALSE, message=FALSE, eval=FALSE} library(handwriter) csafe_document <- list() @@ -42,4 +39,8 @@ plotImage(csafe_document) document <- processDocument('path/to/image.png') plotImage(document) + + + + ``` diff --git a/_quarto/man/plotImageThinned.qmd b/_quarto/man/plotImageThinned.qmd new file mode 100644 index 00000000..fa30178e --- /dev/null +++ b/_quarto/man/plotImageThinned.qmd @@ -0,0 +1,43 @@ +## Plot Thinned Image {.unnumbered} + + +### Description + +This function returns a plot with the full image plotted in light gray and the thinned skeleton printed in black on top. + + + +### Usage + +
plotImageThinned(doc)
+
+ + +### Arguments + + + + +
doc +A document processed with processHandwriting() +
+ + +### Value + +gpplot plot of thinned image + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +csafe_document <- list() +csafe_document$image <- csafe +csafe_document$thin <- thinImage(csafe_document$image) +plotImageThinned(csafe_document) + + + +``` diff --git a/_quarto/man/plotLetter.qmd b/_quarto/man/plotLetter.qmd new file mode 100644 index 00000000..2dede798 --- /dev/null +++ b/_quarto/man/plotLetter.qmd @@ -0,0 +1,77 @@ +## Plot Letter {.unnumbered} + + +### Description + +This function returns a plot of a single graph extracted from a document. It +uses the letterList parameter from the processHandwriting() or processDocument() function and +accepts a single value as whichLetter. Dims requires the dimensions of the +entire document, since this isn't contained in processHandwriting() or processDocument(). + + + +### Usage + +
plotLetter(
+  doc,
+  whichLetter,
+  showPaths = TRUE,
+  showCentroid = TRUE,
+  showSlope = TRUE,
+  showNodes = TRUE
+)
+
+ + +### Arguments + + + + + + + + + + + + + + +
doc +A document processed with processHandwriting() or processDocument() +
whichLetter +Single value in 1:length(letterList) denoting which letter +to plot. +
showPaths +Whether the calculated paths on the letter should be shown +with numbers. +
showCentroid +Whether the centroid should be shown +
showSlope +Whether the slope should be shown +
showNodes +Whether the nodes should be shown +
+ + +### Value + +Plot of single letter. + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +twoSent_document = list() +twoSent_document$image = twoSent +twoSent_document$thin = thinImage(twoSent_document$image) +twoSent_document$process = processHandwriting(twoSent_document$thin, dim(twoSent_document$image)) +plotLetter(twoSent_document, 1) +plotLetter(twoSent_document, 4, showPaths = FALSE) + + + +``` diff --git a/_quarto/man/plotLine.qmd b/_quarto/man/plotLine.qmd new file mode 100644 index 00000000..bbf54e9b --- /dev/null +++ b/_quarto/man/plotLine.qmd @@ -0,0 +1,56 @@ +## Plot Line {.unnumbered} + + +### Description + +This function returns a plot of a single line extracted from a document. +It uses the letterList parameter from the processHandwriting function and accepts a single value as whichLetter. +Dims requires the dimensions of the entire document, since this isn't contained in processHandwriting. + + + +### Usage + +
plotLine(letterList, whichLine, dims)
+
+ + +### Arguments + + + + + + + + +
letterList +Letter list from processHandwriting function +
whichLine +Single value denoting which line to plot - checked if too big inside function. +
dims +Dimensions of the original document +
+ + +### Value + +ggplot plot of single line + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +twoSent_document = list() +twoSent_document$image = twoSent +twoSent_document$thin = thinImage(twoSent_document$image) +twoSent_processList = processHandwriting(twoSent_document$thin, dim(twoSent_document$image)) + +dims = dim(twoSent_document$image) +plotLine(twoSent_processList$letterList, 1, dims) + + + +``` diff --git a/_quarto/man/plotNodes.qmd b/_quarto/man/plotNodes.qmd new file mode 100644 index 00000000..d4e9c71b --- /dev/null +++ b/_quarto/man/plotNodes.qmd @@ -0,0 +1,58 @@ +## Plot Nodes {.unnumbered} + + +### Description + +This function returns a plot with the full image plotted in light gray and the skeleton printed in black, with red triangles over the vertices. +Also called from plotPath, which is a more useful function, in general. + + + +### Usage + +
plotNodes(doc, plot_break_pts = FALSE, nodeSize = 3, nodeColor = "red")
+
+ + +### Arguments + + + + + + + + + + +
doc +A document processed with processHandwriting() +
plot_break_pts +Logical value as to whether to plot nodes or break points. plot_break_pts=FALSE plots nodes and plot_break_pts=TRUE plots break point. +
nodeSize +Size of triangles printed. 3 by default. Move down to 2 or 1 for small text images. +
nodeColor +Which color the nodes should be +
+ + +### Value + +Plot of full and thinned image with vertices overlaid. + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +csafe_document <- list() +csafe_document$image <- csafe +csafe_document$thin <- thinImage(csafe_document$image) +csafe_document$process <- processHandwriting(csafe_document$thin, dim(csafe_document$image)) +plotNodes(csafe_document) +plotNodes(csafe_document, nodeSize=6, nodeColor="black") + + + +``` diff --git a/_quarto/man/plot_cluster_centers.qmd b/_quarto/man/plot_cluster_centers.qmd new file mode 100644 index 00000000..dac34107 --- /dev/null +++ b/_quarto/man/plot_cluster_centers.qmd @@ -0,0 +1,61 @@ +## Plot Template Cluster Centers {.unnumbered} + + +### Description + +Plot the cluster centers of a cluster template created with +make_clustering_template. This function uses a K-Means type algorithm to +sort graphs from training documents into clusters. On each iteration of the +algorithm, it calculates the mean graph of each cluster and finds the graph +in each cluster that is closest to the mean graph. The graphs closest to the +mean graphs are used as the cluster centers for the next iteration. +Handwriter stores the cluster centers of a cluster template as graph +prototypes. A graph prototype consists of the starting and ending points of +each path in the graph, as well as and evenly spaced points along each path. +The prototype also stores the center point of the graph. All points are +represented as xy-coordinates and the center point is at (0,0). + + + +### Usage + +
plot_cluster_centers(template, plot_graphs = FALSE, size = 100)
+
+ + +### Arguments + + + + + + + + +
template +A cluster template created with make_clustering_template +
plot_graphs +TRUE plots all graphs in each cluster in addition to the +cluster centers. FALSE only plots the cluster centers. +
size +The size of the output plot +
+ + +### Value + +A plot + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +# plot cluster centers from example template +plot_cluster_centers(example_cluster_template) +plot_cluster_centers(example_cluster_template, plot_graphs = TRUE) + + + +``` diff --git a/_quarto/man/plot_cluster_fill_counts.qmd b/_quarto/man/plot_cluster_fill_counts.qmd new file mode 100644 index 00000000..48bb3613 --- /dev/null +++ b/_quarto/man/plot_cluster_fill_counts.qmd @@ -0,0 +1,54 @@ +## Plot Cluster Fill Counts {.unnumbered} + + +### Description + +Plot the cluster fill counts for each document in formatted_data. + + + +### Usage + +
plot_cluster_fill_counts(formatted_data, facet = TRUE)
+
+ + +### Arguments + + + + + + +
formatted_data +Data created by format_template_data(), +fit_model(), or analyze_questioned_documents() +
facet +TRUE uses facet_wrap to create a subplot for each writer. +FALSE plots the data on a single plot. +
+ + +### Value + +ggplot plot of cluster fill counts + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +# Plot cluster fill counts for template training documents +template_data <- format_template_data(example_cluster_template) +plot_cluster_fill_counts(formatted_data = template_data, facet = TRUE) + +# Plot cluster fill counts for model training documents +plot_cluster_fill_counts(formatted_data = example_model, facet = TRUE) + +# Plot cluster fill counts for questioned documents +plot_cluster_fill_counts(formatted_data = example_analysis, facet = FALSE) + + + +``` diff --git a/_quarto/man/plot_cluster_fill_rates.qmd b/_quarto/man/plot_cluster_fill_rates.qmd new file mode 100644 index 00000000..47ee8551 --- /dev/null +++ b/_quarto/man/plot_cluster_fill_rates.qmd @@ -0,0 +1,54 @@ +## Plot Cluster Fill Rates {.unnumbered} + + +### Description + +Plot the cluster fill rates for each document in formatted_data. + + + +### Usage + +
plot_cluster_fill_rates(formatted_data, facet = FALSE)
+
+ + +### Arguments + + + + + + +
formatted_data +Data created by format_template_data(), +fit_model(), or analyze_questioned_documents() +
facet +TRUE uses facet_wrap to create a subplot for each writer. +FALSE plots the data on a single plot. +
+ + +### Value + +ggplot plot of cluster fill rates + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +# Plot cluster fill rates for template training documents +template_data <- format_template_data(example_cluster_template) +plot_cluster_fill_rates(formatted_data = template_data, facet = TRUE) + +# Plot cluster fill rates for model training documents +plot_cluster_fill_rates(formatted_data = example_model, facet = TRUE) + +# Plot cluster fill rates for questioned documents +plot_cluster_fill_rates(formatted_data = example_analysis, facet = FALSE) + + + +``` diff --git a/_quarto/man/plot_credible_intervals.qmd b/_quarto/man/plot_credible_intervals.qmd new file mode 100644 index 00000000..d80797db --- /dev/null +++ b/_quarto/man/plot_credible_intervals.qmd @@ -0,0 +1,60 @@ +## Plot Credible Intervals {.unnumbered} + + +### Description + +Plot credible intervals for the model's pi parameters that estimate the true writer +cluster fill counts. + + + +### Usage + +
plot_credible_intervals(
+  model,
+  interval_min = 0.025,
+  interval_max = 0.975,
+  facet = FALSE
+)
+
+ + +### Arguments + + + + + + + + + + +
model +A model created by fit_model() +
interval_min +The lower bound of the credible interval. It must be greater than zero and less than 1. +
interval_max +The upper bound of the credible interval. It must be greater than the interval minimum and less than 1. +
facet +TRUE uses facet_wrap to create a subplot for each writer. +FALSE plots the data on a single plot. +
+ + +### Value + +ggplot plot credible intervals + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +plot_credible_intervals(model = example_model) +plot_credible_intervals(model = example_model, facet = TRUE) + + + +``` diff --git a/_quarto/man/plot_posterior_probabilities.qmd b/_quarto/man/plot_posterior_probabilities.qmd new file mode 100644 index 00000000..f03ff0fe --- /dev/null +++ b/_quarto/man/plot_posterior_probabilities.qmd @@ -0,0 +1,42 @@ +## Plot Posterior Probabilities {.unnumbered} + + +### Description + +Creates a tile plot of posterior probabilities of writership for each +questioned document and each known writer analyzed with +analyze_questioned_documents(). + + + +### Usage + +
plot_posterior_probabilities(analysis)
+
+ + +### Arguments + + + + +
analysis +A named list of analysis results from analyze_questioned_documents(). +
+ + +### Value + +A tile plot of posterior probabilities of writership. + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +plot_posterior_probabilities(analysis = example_analysis) + + + +``` diff --git a/_quarto/man/plot_trace.qmd b/_quarto/man/plot_trace.qmd new file mode 100644 index 00000000..da5c9fc9 --- /dev/null +++ b/_quarto/man/plot_trace.qmd @@ -0,0 +1,47 @@ +## Plot Trace {.unnumbered} + + +### Description + +Create a trace plot for all chains for a single variable of a fitted model +created by fit_model(). If the model contains more than one chain, the +chains will be combined by pasting them together. + + + +### Usage + +
plot_trace(variable, model)
+
+ + +### Arguments + + + + + + +
variable +The name of a variable in the model +
model +A model created by fit_model() +
+ + +### Value + +A trace plot + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +plot_trace(model = example_model, variable = "pi[1,1]") +plot_trace(model = example_model, variable = "mu[2,3]") + + + +``` diff --git a/_quarto/man/processDocument.qmd b/_quarto/man/processDocument.qmd new file mode 100644 index 00000000..e8981ffa --- /dev/null +++ b/_quarto/man/processDocument.qmd @@ -0,0 +1,46 @@ +## Process Document {.unnumbered} + + +### Description + +Load a handwriting sample from a PNG image. Then binarize, thin, and split +the handwriting into graphs. + + + +### Usage + +
processDocument(path)
+
+ + +### Arguments + + + + +
path +File path for handwriting document. The document must be in PNG +file format. +
+ + +### Value + +The processed document as a list + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +image_path <- system.file("extdata", "phrase_example.png", package = "handwriter") +doc <- processDocument(image_path) +plotImage(doc) +plotImageThinned(doc) +plotNodes(doc) + + + +``` diff --git a/_quarto/man/processHandwriting.qmd b/_quarto/man/processHandwriting.qmd new file mode 100644 index 00000000..fb339b34 --- /dev/null +++ b/_quarto/man/processHandwriting.qmd @@ -0,0 +1,51 @@ +## Process Handwriting by Component {.unnumbered} + + +### Description + +The main driver of handwriting processing. Takes in an image of thinned +handwriting created with thinImage() and splits the the handwriting into +shapes called graphs. Instead of processing the entire document at once, +the thinned writing is separated into connected components and each component +is split into graphs. + + + +### Usage + +
processHandwriting(img, dims)
+
+ + +### Arguments + + + + + + +
img +Thinned binary image created with thinImage(). +
dims +Dimensions of thinned binary image. +
+ + +### Value + +A list of the processed image + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +twoSent_document <- list() +twoSent_document$image <- twoSent +twoSent_document$thin <- thinImage(twoSent_document$image) +twoSent_processList <- processHandwriting(twoSent_document$thin, dim(twoSent_document$image)) + + + +``` diff --git a/_quarto/man/process_batch_dir.qmd b/_quarto/man/process_batch_dir.qmd new file mode 100644 index 00000000..c55576d2 --- /dev/null +++ b/_quarto/man/process_batch_dir.qmd @@ -0,0 +1,59 @@ +## Process Batch Directory {.unnumbered} + + +### Description + +Process a list of handwriting samples saved as PNG images in a directory: +(1) Load the image and convert it to black and white with readPNGBinary() +(2) Thin the handwriting to one pixel in width with thinImage() +(3) Run processHandwriting() to split the handwriting into parts called edges and place nodes at the ends of +edges. Then combine edges into component shapes called graphs. +(4) Save the processed document in an RDS file. +(5) Optional. Return a list of the processed documents. + + + +### Usage + +
process_batch_dir(input_dir, output_dir = ".", skip_docs_on_retry = TRUE)
+
+ + +### Arguments + + + + + + + + +
input_dir +Input directory that contains images +
output_dir +A directory to save the processed images +
skip_docs_on_retry +Logical whether to skip documents in input_dir that +caused errors on a previous run. The errors and document names are stored +in output_dir > problems.txt. If this is the first run, +process_batch_list will attempt to process all documents in input_dir. +
+ + +### Value + +A list of processed documents + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=FALSE} +library(handwriter) + +process_batch_list("path/to/input_dir", "path/to/output_dir") +docs <- process_batch_list("path/to/input_dir", "path/to/output_dir") + + + + +``` diff --git a/_quarto/man/process_batch_list.qmd b/_quarto/man/process_batch_list.qmd new file mode 100644 index 00000000..858e61d1 --- /dev/null +++ b/_quarto/man/process_batch_list.qmd @@ -0,0 +1,60 @@ +## Process Batch List {.unnumbered} + + +### Description + +Process a list of handwriting samples saved as PNG images: (1) Load the image +and convert it to black and white with readPNGBinary() (2) Thin the +handwriting to one pixel in width with thinImage() (3) Run +processHandwriting() to split the handwriting into parts called edges +and place nodes at the ends of edges. Then combine edges into component +shapes called graphs. (4) Save the processed document in an RDS file. (5) +Optional. Return a list of the processed documents. + + + +### Usage + +
process_batch_list(images, output_dir, skip_docs_on_retry = TRUE)
+
+ + +### Arguments + + + + + + + + +
images +A vector of image file paths +
output_dir +A directory to save the processed images +
skip_docs_on_retry +Logical whether to skip documents in the images arguement that +caused errors on a previous run. The errors and document names are stored +in output_dir > problems.txt. If this is the first run, +process_batch_list will attempt to process all documents in the images arguement. +
+ + +### Value + +A list of processed documents + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=FALSE} +library(handwriter) + +images <- c('path/to/image1.png', 'path/to/image2.png', 'path/to/image3.png') +process_batch_list(images, "path/to/output_dir", FALSE) +docs <- process_batch_list(images, "path/to/output_dir", TRUE) + + + + +``` diff --git a/_quarto/man/readPNGBinary.qmd b/_quarto/man/readPNGBinary.qmd new file mode 100644 index 00000000..8d959f6b --- /dev/null +++ b/_quarto/man/readPNGBinary.qmd @@ -0,0 +1,65 @@ +## Read PNG Binary {.unnumbered} + + +### Description + +This function reads in and binarizes a PNG image. + + + +### Usage + +
readPNGBinary(
+  path,
+  cutoffAdjust = 0,
+  clean = TRUE,
+  crop = TRUE,
+  inversion = FALSE
+)
+
+ + +### Arguments + + + + + + + + + + + + +
path +File path for image. +
cutoffAdjust +Multiplicative adjustment to the K-means estimated binarization cutoff. +
clean +Whether to fill in white pixels with 7 or 8 neighbors. This will help a lot when thinning – keeps from getting little white bubbles in text. +
crop +Logical value dictating whether or not to crop the white out around the image. TRUE by default. +
inversion +Logical value dictating whether or not to flip each pixel of binarized image. Flipping happens after binarization. FALSE by default. +
+ + +### Value + +Returns image from path. 0 represents black, and 1 represents white by default. + + + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} +library(handwriter) + +image_path <- system.file("extdata", "phrase_example.png", package = "handwriter") +csafe_document <- list() +csafe_document$image = readPNGBinary(image_path) +plotImage(csafe_document) + + + +``` diff --git a/docs/man/read_and_process.md b/_quarto/man/read_and_process.qmd similarity index 51% rename from docs/man/read_and_process.md rename to _quarto/man/read_and_process.qmd index 96fbb81a..b9f2fdef 100644 --- a/docs/man/read_and_process.md +++ b/_quarto/man/read_and_process.qmd @@ -1,54 +1,49 @@ +## Read and Process {.unnumbered} -# Read and Process +### Description -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) +
[Superseded] -## Description +Development on read_and_process() is complete. We recommend using processDocument(). +read_and_process(image_name, "document") is equivalent to processDocument(image_name). -[Superseded] -Development on read_and_process() is complete. We recommend -using processDocument(). read_and_process(image_name, -“document”) is equivalent to -processDocument(image_name). -## Usage +### Usage
read_and_process(image_name, transform_output)
 
-## Arguments + +### Arguments - - + - - - + + - +
-image_name -
image_name The file path to an image -
-transform_output -
transform_output The type of transformation to perform on the output -
-## Value + +### Value A list of the processed image components -## Examples -``` r + +### Examples +```{r, warning=FALSE, message=FALSE, eval=TRUE} library(handwriter) # use handwriting example from handwriter package image_path <- system.file("extdata", "phrase_example.png", package = "handwriter") doc <- read_and_process(image_path, "document") + + + ``` diff --git a/_quarto/man/rgb2grayscale.qmd b/_quarto/man/rgb2grayscale.qmd new file mode 100644 index 00000000..6e0aa6bd --- /dev/null +++ b/_quarto/man/rgb2grayscale.qmd @@ -0,0 +1,31 @@ + +## rgba2grayscale {.unnumbered} + + +### Description + +Changes RGB image to grayscale + + + +### Usage + +
rgb2grayscale(img)
+
+ + +### Arguments + + + + +
img +A 3D array with slices R, G, and B +
+ + +### Value + +img as a 3D array as grayscale + + diff --git a/_quarto/man/rgba2rgb.qmd b/_quarto/man/rgba2rgb.qmd new file mode 100644 index 00000000..0ff72440 --- /dev/null +++ b/_quarto/man/rgba2rgb.qmd @@ -0,0 +1,31 @@ + +## rgba2rgb {.unnumbered} + + +### Description + +Removes alpha channel from png image. + + + +### Usage + +
rgba2rgb(img)
+
+ + +### Arguments + + + + +
img +A 3-d array with slices R, G, B, and alpha. +
+ + +### Value + +img as a 3D array with alpha channel removed + + diff --git a/_quarto/man/thinImage.qmd b/_quarto/man/thinImage.qmd new file mode 100644 index 00000000..5beafa68 --- /dev/null +++ b/_quarto/man/thinImage.qmd @@ -0,0 +1,32 @@ + +## thinImage {.unnumbered} + + +### Description + +This function returns a vector of locations for black pixels in the thinned image. +Thinning done using Zhang - Suen algorithm. + + + +### Usage + +
thinImage(img)
+
+ + +### Arguments + + + + +
img +A binary matrix of the text that is to be thinned. +
+ + +### Value + +A thinned, one pixel wide, image. + + diff --git a/docs/man/twoSent.md b/_quarto/man/twoSent.qmd similarity index 76% rename from docs/man/twoSent.md rename to _quarto/man/twoSent.qmd index f87ba6ff..ea6c5834 100644 --- a/docs/man/twoSent.md +++ b/_quarto/man/twoSent.qmd @@ -1,23 +1,26 @@ +## Two sentence printed example handwriting {.unnumbered} -# Two sentence printed example handwriting - -## Description +### Description Two sentence printed example handwriting -## Usage + + +### Usage
twoSent
 
-## Format + +### Format Binary image matrix. 396 rows and 1947 columns -## Examples -``` r + +### Examples +```{r, warning=FALSE, message=FALSE, eval=FALSE} library(handwriter) twoSent_document <- list() @@ -30,4 +33,7 @@ plotImage(twoSent_document) twoSent_document$thin <- thinImage(twoSent_document$image) plotImageThinned(twoSent_document) twoSent_processList <- processHandwriting(twoSent_document$thin, dim(twoSent_document$image)) + + + ``` diff --git a/_quarto/man/whichToFill.qmd b/_quarto/man/whichToFill.qmd new file mode 100644 index 00000000..d6de9ffe --- /dev/null +++ b/_quarto/man/whichToFill.qmd @@ -0,0 +1,32 @@ + +## whichToFill {.unnumbered} + + +### Description + +Finds pixels in the plot that shouldn't be white and makes them black. +Quick and helpful cleaning for before the thinning algorithm runs. + + + +### Usage + +
whichToFill(img)
+
+ + +### Arguments + + + + +
img +A binary matrix. +
+ + +### Value + +A cleaned up image. + + diff --git a/_quarto/preamble_man_qmd.yml b/_quarto/preamble_man_qmd.yml new file mode 100644 index 00000000..cd2e598a --- /dev/null +++ b/_quarto/preamble_man_qmd.yml @@ -0,0 +1,6 @@ +--- +format: + md: + prefer-html: true +--- + diff --git a/_quarto/preamble_vignettes_qmd.yml b/_quarto/preamble_vignettes_qmd.yml new file mode 100644 index 00000000..1436a9e2 --- /dev/null +++ b/_quarto/preamble_vignettes_qmd.yml @@ -0,0 +1,6 @@ +--- +format: + md: + prefer_html: true +default-image-extension: "" +--- diff --git a/_quarto/preamble_vignettes_rmd.yml b/_quarto/preamble_vignettes_rmd.yml new file mode 100644 index 00000000..b47a68aa --- /dev/null +++ b/_quarto/preamble_vignettes_rmd.yml @@ -0,0 +1,4 @@ +--- +always_allow_html: yes +--- + diff --git a/_quarto/quarto_website.yml b/_quarto/quarto_website.yml new file mode 100644 index 00000000..abec99e4 --- /dev/null +++ b/_quarto/quarto_website.yml @@ -0,0 +1,34 @@ +project: + type: website + +website: + title: "$ALTDOC_PACKAGE_NAME" + navbar: + search: true + right: + - icon: github + href: $ALTDOC_PACKAGE_URL_GITHUB + aria-label: $ALTDOC_PACKAGE_NAME GitHub + sidebar: + collapse-level: 1 + contents: + - text: Home + file: index.qmd + - section: $ALTDOC_VIGNETTE_BLOCK + - section: $ALTDOC_MAN_BLOCK + - text: News + file: $ALTDOC_NEWS + - text: Changelog + file: $ALTDOC_CHANGELOG + - text: License + file: $ALTDOC_LICENSE + - text: Licence + file: $ALTDOC_LICENCE + - text: Code of conduct + file: $ALTDOC_CODE_OF_CONDUCT + - text: Citation + file: $ALTDOC_CITATION + +format: + html: + css: styles.css \ No newline at end of file diff --git a/_quarto/styles.css b/_quarto/styles.css new file mode 100755 index 00000000..ce09046e --- /dev/null +++ b/_quarto/styles.css @@ -0,0 +1,37 @@ +@import url('https://fonts.googleapis.com/css2?family=Montserrat:ital,wght@0,100..900;1,100..900&display=swap'); + +h4 { + font-family: 'Montserrat', sans-serif; + font-weight: 700; +/* color: #003A70;*/ +} + +h3 { + font-family: 'Montserrat', sans-serif; + font-weight: bold; + color: #545859; +} + +h2 { + font-family: 'Montserrat', sans-serif; + font-weight: bold; + color: #003A70; +} + +h1 { + font-family: 'Montserrat', sans-serif; + font-weight: bold; + font-size: 36px; + color: #003A70; +} + +body { + font-family: 'Montserrat', sans-serif; + font-weight: 500; + font-size: 16px; + color: #545859; +} + +html, body { + height: 100%; +} diff --git a/docs/vignettes/.gitignore b/_quarto/vignettes/.gitignore similarity index 100% rename from docs/vignettes/.gitignore rename to _quarto/vignettes/.gitignore diff --git a/docs/vignettes/handwriter.Rmd b/_quarto/vignettes/handwriter.Rmd similarity index 100% rename from docs/vignettes/handwriter.Rmd rename to _quarto/vignettes/handwriter.Rmd diff --git a/altdoc/.nojekyll b/altdoc/.nojekyll deleted file mode 100644 index e69de29b..00000000 diff --git a/altdoc/docsify.html b/altdoc/docsify.html deleted file mode 100644 index 1d994137..00000000 --- a/altdoc/docsify.html +++ /dev/null @@ -1,45 +0,0 @@ - - - - - - - - - - - -
- - - - - - - diff --git a/altdoc/docsify.md b/altdoc/docsify.md deleted file mode 100644 index 7265e210..00000000 --- a/altdoc/docsify.md +++ /dev/null @@ -1,9 +0,0 @@ -* [Home](/) -* Articles: $ALTDOC_VIGNETTE_BLOCK -* Reference: $ALTDOC_MAN_BLOCK -* [News]($ALTDOC_NEWS) -* [Changelog]($ALTDOC_CHANGELOG) -* [Code of Conduct]($ALTDOC_CODE_OF_CONDUCT) -* [License]($ALTDOC_LICENSE) -* [Licence]($ALTDOC_LICENCE) -* [Citation]($ALTDOC_CITATION) diff --git a/altdoc/quarto_website.yml b/altdoc/quarto_website.yml new file mode 100644 index 00000000..abec99e4 --- /dev/null +++ b/altdoc/quarto_website.yml @@ -0,0 +1,34 @@ +project: + type: website + +website: + title: "$ALTDOC_PACKAGE_NAME" + navbar: + search: true + right: + - icon: github + href: $ALTDOC_PACKAGE_URL_GITHUB + aria-label: $ALTDOC_PACKAGE_NAME GitHub + sidebar: + collapse-level: 1 + contents: + - text: Home + file: index.qmd + - section: $ALTDOC_VIGNETTE_BLOCK + - section: $ALTDOC_MAN_BLOCK + - text: News + file: $ALTDOC_NEWS + - text: Changelog + file: $ALTDOC_CHANGELOG + - text: License + file: $ALTDOC_LICENSE + - text: Licence + file: $ALTDOC_LICENCE + - text: Code of conduct + file: $ALTDOC_CODE_OF_CONDUCT + - text: Citation + file: $ALTDOC_CITATION + +format: + html: + css: styles.css \ No newline at end of file diff --git a/altdoc/styles.css b/altdoc/styles.css new file mode 100755 index 00000000..ce09046e --- /dev/null +++ b/altdoc/styles.css @@ -0,0 +1,37 @@ +@import url('https://fonts.googleapis.com/css2?family=Montserrat:ital,wght@0,100..900;1,100..900&display=swap'); + +h4 { + font-family: 'Montserrat', sans-serif; + font-weight: 700; +/* color: #003A70;*/ +} + +h3 { + font-family: 'Montserrat', sans-serif; + font-weight: bold; + color: #545859; +} + +h2 { + font-family: 'Montserrat', sans-serif; + font-weight: bold; + color: #003A70; +} + +h1 { + font-family: 'Montserrat', sans-serif; + font-weight: bold; + font-size: 36px; + color: #003A70; +} + +body { + font-family: 'Montserrat', sans-serif; + font-weight: 500; + font-size: 16px; + color: #545859; +} + +html, body { + height: 100%; +} diff --git a/docs/.nojekyll b/docs/.nojekyll deleted file mode 100644 index e69de29b..00000000 diff --git a/docs/CITATION.html b/docs/CITATION.html new file mode 100644 index 00000000..baa77dd5 --- /dev/null +++ b/docs/CITATION.html @@ -0,0 +1,885 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Citation

+
To cite package ‘handwriter’ in publications use:
+
+  Iowa State University of Science and Technology on behalf of its Center for
+  Statistics and Applications in Forensic Evidence, Berry N, Reinders S, Taylor
+  J (2024). _handwriter: Handwriting Analysis in R_. R package version
+  3.1.1.9000, commit 3b29e861c4bcaed6062f79ebb75c000f9bd86413,
+  <https://github.com/CSAFE-ISU/handwriter>.
+
+A BibTeX entry for LaTeX users is
+
+  @Manual{,
+    title = {handwriter: Handwriting Analysis in R},
+    author = {{Iowa State University of Science and Technology on behalf of its Center for Statistics and Applications in Forensic Evidence} and Nick Berry and Stephanie Reinders and James Taylor},
+    year = {2024},
+    note = {R package version 3.1.1.9000, commit 3b29e861c4bcaed6062f79ebb75c000f9bd86413},
+    url = {https://github.com/CSAFE-ISU/handwriter},
+  }
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/LICENSE.html b/docs/LICENSE.html new file mode 100644 index 00000000..bf68f068 --- /dev/null +++ b/docs/LICENSE.html @@ -0,0 +1,1099 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
                GNU AFFERO GENERAL PUBLIC LICENSE
+                   Version 3, 19 November 2007
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Copyright (C) 2007 Free Software Foundation, Inc. https://fsf.org/ Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed.

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To do so, attach the following notices to the program. It is safest to attach them to the start of each source file to most effectively state the exclusion of warranty; and each file should have at least the “copyright” line and a pointer to where the full notice is found.

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+(at your option) any later version.
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+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
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+

Also add information on how to contact you by electronic and paper mail.

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You should also get your employer (if you work as a programmer) or school, if any, to sign a “copyright disclaimer” for the program, if necessary. For more information on this, and how to apply and follow the GNU AGPL, see https://www.gnu.org/licenses/.

+ + + +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/NEWS.html b/docs/NEWS.html new file mode 100644 index 00000000..b5535b42 --- /dev/null +++ b/docs/NEWS.html @@ -0,0 +1,937 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

handwriter (development version)

+
+

New features

+
    +
  • The new function plotClusterCenters() creates a plot of the clusters centers from a cluster template. The cluster centers are displayed as orange shapes. The function also plots all graphs in each cluster as grey shapes with 5% transparency to depict the variability of graph shapes within each cluster.

  • +
  • The new function plotGraphs() plots every graph in a document processed with processDocument().

  • +
+
+
+

Minor improvements and fixes

+
    +
  • Fixed bug in processDocument() when the writing in the document is a single connected component, such as a single word written in cursive. Previously, the output of processDocument() for this kind of document was formatted incorrectly.

  • +
  • Fixed bug in get_credible_intervals() and plot_credible_intervals() where the model writers were numbered sequentially. Now these functions use the writer IDs.

  • +
  • Fixed bug in format_template_data() where the function coerced writer IDs to integers even if the writer IDs contained characters.

  • +
  • Fixed bug in get_clusters_batch() where the function would stall but not return an error message if a document had a graph with a large number of edges (paths). Now the function deletes graphs with more than 30 edges.

  • +
+
+
+
+

handwriter 3.1.1

+
+

Patches

+
    +
  • The functions fit_model() and analyze_questioned_documents() now allow writer IDs that contain numbers and letters.
  • +
+
+
+
+

handwriter 3.1.0

+
+

Minor improvements and fixes

+
    +
  • Increased the speed of processHandwriting() by changing the function to process a handwritten document in sections instead of all at once. Nodes created by processHandwriting() in version 3.1.0 might differ slightly in placement from previous versions.

  • +
  • Fixed bugs in fit_model() and analyze_questioned_documents() introduced by the changes to process_batch_list() in version 3.0.0.

  • +
+
+
+
+

handwriter 3.0.0

+
    +
  • Major reductions made to the memory required by process_batch_list() so it can now process paragraph length documents from the CSAFE Handwriting Database on machines with 8 GB of RAM.

  • +
  • process_batch_list() now skips to the next document if an error is returned while trying to process a document. A log file records the document name(s) and error message(s) of any problem documents. If the user reruns process_batch_list() they now have the option to either try a second time to process problem documents or skip them entirely.

  • +
  • New function get_clusters_batch() calculates cluster assignments of all files in a directory.

  • +
+
+
+

handwriter 2.0.3

+
    +
  • Fix initializer warning with arma::vec. Apparently different versions of gcc were raising warnings with the assignment of values in neighbors. The recommended fix was to use an initializer list.
  • +
+
+
+

handwriter 2.0.2

+
+

New features

+
    +
  • fit_model() allows the user to fit a statistical model to known handwriting samples collected from a closed-set of persons.

  • +
  • analyze_questioned_documents() in conjunction with a model created by fit_model() allows a user to calculate the posterior probability that each known writer in the model is the writer of the questioned document(s). analyze_questioned_documents() only works when the questioned document(s) had to have been written by one of the model writers. This function must NOT be used if someone other than one of the model writers could written the questioned document(s) as it could yield misleading results.

  • +
+
+
+

Minor improvements and fixes

+
    +
  • processDocument() is a new wrapper function that runs readPNGBinary(), thinImage(), and processHandwriting() so the user doesn’t need to run these functions individually.

  • +
  • plotImage(), plotImageThinned(), and plotNodes now only need one input, a document processed with processDocument()

  • +
  • processHandwriting() no longer crashes when the input writing is a single letter or word

  • +
  • read_and_process() superseded in favor of processDocument()

  • +
  • extractGraphs() superseded in favor of process_batch_dir()

  • +
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/OLDwritingsamples.html b/docs/OLDwritingsamples.html deleted file mode 100644 index b1602d72..00000000 --- a/docs/OLDwritingsamples.html +++ /dev/null @@ -1,21 +0,0 @@ - - - - - handwriter - - - - - - - - - - -

"csafe" in cursive

- Writing_csafe_single - - - diff --git a/docs/README.md b/docs/README.md deleted file mode 100644 index dc2b2677..00000000 --- a/docs/README.md +++ /dev/null @@ -1,401 +0,0 @@ - - - - -# handwriter - - - - -The handwriter package performs writership analysis of a handwritten -*questioned document* where the questioned document was written by one -of *closed-set* of potential writers. For example, a handwritten bomb -threat is found in a science classroom, and the police are able to -determine that the note could only have been written by one of the -students in 4th period science. The handwriter package builds a -statistical model to estimate a *writer profile* from known handwriting -samples from each writer in the closed-set. A writer profile is also -estimated from the questioned document. The statistical model compares -the writer profile from the questioned document with each of the writer -profiles from the closed-set of potential writers and estimates the -posterior probability that each closed-set writer wrote the questioned -document. - -## Installation - -You can install handwriter from CRAN with: - -``` r -install.packages("handwriter") -``` - -You can install the development version of handwriter from -[GitHub](https://github.com/) with: - -``` r -# install.packages("devtools") -devtools::install_github("CSAFE-ISU/handwriter") -``` - -## Process a Handwriting Example - -The file “phrase_example.png” is a scanned PNG of handwriting from the -CSAFE Handwriting Database. This PNG image is included in the handwriter -package in a folder called “extdata.” Use the helper function -`handwriter_example()` to find the path to where “phrase_example.png” is -saved on your computer. - -Use `processDocument()` to - -1. read the PNG file -2. convert the writing to black and white -3. thin it to a one-pixel-wide skeleton -4. place nodes to break the writing into component shapes called - *graphs* - -``` r -library(handwriter) -phrase <- system.file("extdata", "phrase_example.png", package = "handwriter") -doc <- processDocument(phrase) -#> path in readPNGBinary: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library/handwriter/extdata/phrase_example.png -#> Starting Processing... -#> Getting Nodes... -#> Skeletonizing writing... -#> Splitting document into components... -#> Merging nodes... -#> Finding paths... -#> Split paths into graphs... -#> Organizing graphs... -#> Creating graph lists... -#> Adding character features... -#> Document processing complete -``` - -We can view the image: - -``` r -plotImage(doc) -``` - - - -We can view the thinned image: - -``` r -plotImageThinned(doc) -``` - - - -We can also view the nodes: - -``` r -plotNodes(doc) -``` - - - -## Perform Writership Analysis - -This section explains how to perform handwriting analysis on questioned -documents using handwriter. In particular, handwriter addresses the -scenario where an investigator has a questioned handwritten document, a -group of persons of interest has been identified, and the questioned -document had to have been written by one of the persons of interest. For -example, imagine that a handwritten bomb threat was left at a office -building’s main desk and the police discover that the note had to have -been written by one of the one hundred employees working that day. More -details on this method can be found in \[Crawford 2022\]. - -### STEP 1: Create the Main Directory and Subdirectories - -Create a new folder called `main_dir` on your computer to hold the -handwriting documents to be analyzed. When we create a new clustering -template and fit a statistical model, those files will also be stored in -this folder. Create a sub-folder in `main_dir` called `data`. In the -`data` folder, create sub-folders called `model_docs`, -`questioned_docs`, and `template_docs`. The folder structure will look -like this: - -``` bash -├── main_dir -│ ├── data -│ │ ├── model_docs -│ │ ├── questioned_docs -│ │ ├── template_docs -``` - -### STEP 2: Create a Cluster Template - -Save the handwritten documents that you want to use to train a new -cluster template as PNG images in `main_dir > data > template_docs`. The -template training documents need to be from writers that are NOT people -of interest. Name all of the PNG images with a consistent format that -includes an ID for the writer. For example, the PNG images could be -named “writer0001.png”, “writer0002.png”, “writer0003.png” and so on. - -Next, create a new cluster template from the documents in -`main_dir > data > template_docs` with the function -`make_clustering_template`. This function - -1. Processes the template training documents in `template_docs`, - decomposing the handwriting into component shapes called *graphs*. - The processed graphs are saved in RDS files in - `main_dir \> data \> template_graphs`. -2. Deletes graphs with more than 30 edges. -3. Randomly selects `K` starting cluster centers using seed - `centers_seed` for reproducibility. -4. Runs a K-means algorithm with the `K` starting cluster centers and - the selected graphs. The algorithm iteratively groups the selected - graphs into `K` clusters. The final grouping of `K` clusters is the - cluster template. -5. Stores the writer ID for each training document. `writer_indices` is - a vector of the start and stop characters of the writer ID in the - PNG image file name. For example, if the PNG images are named - “writer0001.png”, “writer0002.png”, “writer0003.png”, and so on, - `writer_indices = c(7,10)` -6. Performs some of the processes in parallel. Set the number of cores - for parallel processing with `num_dist_cores`. - -``` r -template <- make_clustering_template( - main_dir = "path/to/main_dir", - template_docs = "path/to/main_dir/data/template_docs", - writer_indices = c(7,10), - centers_seed = 100, - K = 40, - num_dist_cores = 4, - max_iters = 25) -``` - -Type `?make_clustering_template` in the RStudio console for more -information about the function’s arguments. - -For the remainder of this tutorial, we use a small example cluster -template, `example_cluster_template` included in handwriter. - -``` r -template <- example_cluster_template -``` - -The idea behind the cluster template and the hierarchical model is that -we can decompose a handwritten document into component graphs, assign -each graph to the *nearest* cluster, the cluster with the closest shape, -in the cluster template, and count the number of graphs in each cluster. -We characterize writers by the number of a writer’s graphs that are -assigned to each cluster. We refer to this as a writer’s *cluster fill -counts* and it serves as writer profile. - -We can plot the cluster fill counts for each writer in the template -training set. First we format the template data to get the cluster fill -counts in the proper format for the plotting function. - -``` r -template_data <- format_template_data(template = template) -plot_cluster_fill_counts(template_data, facet = TRUE) -``` - - - -### STEP 3: Fit a Hierarchical Model - -We will use handwriting samples from each person of interest, calculate -the cluster fill counts from each sample using the cluster template, and -fit a hierarchical model to estimate each person of interest’s true -cluster fill counts. - -Save your known handwriting samples from the persons of interest in -`main_dir \> data \> model_docs` as PNG images. The model requires three -handwriting samples from each person of interest. Each sample should be -at least one paragraph in length. Name the PNG images with a consistent -format so that all file names are the same length and the writer ID’s -are in the same location. For example, “writer0001_doc1.png”, -“writer0001_doc2.png”, “writer0001_doc3.png”, “writer0002_doc1.png”, and -so on. - -We fit a hierarchical model with the function `fit_model`. This function -does the following: - -1. Processes the model training documents in `model_docs`, decomposing - the handwriting into component graphs. The processed graphs are - saved in RDS files in `main_dir \> data \> model_graphs`. -2. Calculates the cluster fill counts for each document by assigning - each graph to the nearest cluster in the cluster template and - counting the number of graphs assigned to each cluster. The cluster - assignments are saved in main_dir \> data \> model_clusters.rds -3. Fits a hierarchical model to the cluster fill counts using the RJAGS - package and draws posterior samples of model parameters with the - coda package. - -In this example, we use 4000 MCMC iterations for the model. The inputs -`writer_indices` and `doc_indices` are the starting and stopping -characters in the model training documents file names that contains the -writer ID and a document name. - -``` r -model <- fit_model(main_dir = "path/to/main_dir", - model_docs = "path/to/main_dir/data/model_docs", - num_iters = 4000, - num_chains = 1, - num_cores = 2, - writer_indices = c(7, 10), - doc_indices = c(11, 14)) -``` - -For this tutorial, we will use the small example model, `example_model`, -included in handwriter. This model was trained from three documents each -from writers 9, 30, 203, 238, and 400 from the [CSAFE handwriting -database](https://data.csafe.iastate.edu/HandwritingDatabase/). - -``` r -model <- example_model -``` - -We can plot the cluster fill counts for each person of interest. (NOTE: -We had to format the template data to work with the plotting function, -but the model data is already in the correct format.) - -``` r -plot_cluster_fill_counts(formatted_data=model, facet = TRUE) -``` - - - -The bars across the top of each graph show the Writer ID. Each graph has -a line for each known handwriting sample from a given writer. - -#### Hierarchical Model Variables and Burn-in - -If you are interested in the variables used by the hierarchical model, -continue reading this section. Otherwise, feel free to skip to the next -section to learn how to analyze questioned documents. - -We can list the variables in the model: - -``` r -names(as.data.frame(coda::as.mcmc(model$fitted_model[[1]]))) -#> [1] "eta[1]" "eta[2]" "eta[3]" "eta[4]" "eta[5]" "gamma[1]" -#> [7] "gamma[2]" "gamma[3]" "gamma[4]" "gamma[5]" "mu[1,1]" "mu[2,1]" -#> [13] "mu[3,1]" "mu[1,2]" "mu[2,2]" "mu[3,2]" "mu[1,3]" "mu[2,3]" -#> [19] "mu[3,3]" "mu[1,4]" "mu[2,4]" "mu[3,4]" "mu[1,5]" "mu[2,5]" -#> [25] "mu[3,5]" "pi[1,1]" "pi[2,1]" "pi[3,1]" "pi[1,2]" "pi[2,2]" -#> [31] "pi[3,2]" "pi[1,3]" "pi[2,3]" "pi[3,3]" "pi[1,4]" "pi[2,4]" -#> [37] "pi[3,4]" "pi[1,5]" "pi[2,5]" "pi[3,5]" "tau[1,1]" "tau[2,1]" -#> [43] "tau[3,1]" "tau[1,2]" "tau[2,2]" "tau[3,2]" "tau[1,3]" "tau[2,3]" -#> [49] "tau[3,3]" "tau[1,4]" "tau[2,4]" "tau[3,4]" "tau[1,5]" "tau[2,5]" -#> [55] "tau[3,5]" -``` - -View a description of a variable with the `about_variable` function. - -``` r -about_variable(variable = "mu[1,1]", model = model) -#> [1] "Mu is the location parameter of a wrapped-Cauchy distribution for writer ID w0009 and cluster 1" -``` - -View a trace plot of a variable. - -``` r -plot_trace(variable = "mu[1,1]", model = model) -``` - - - -If we need to, we can drop the beginning MCMC iterations for burn-in. -For example, if we want to drop the first 25 iterations, we use - -``` r -model <- drop_burnin(model, burn_in = 25) -``` - -If we want to save the updated model as the current model for this -project, replace `model.rds` in the `data` folder with - -``` r -saveRDS(model, file='data/model.rds') -``` - -### Analyze Questioned Documents - -Save your questioned document(s) in `main_dir > data > questioned_docs` -as PNG images. Assign a new writer ID to the questioned documents and -name the documents consistently. E.g. “unknown1000_doc1.png”, -“unknown1001_doc1.png”, and so on. - -We estimate the posterior probability of writership for each of the -questioned documents with the function `analyze_questioned_documents`. -This function does the following: - -1. **Process Questioned Document(s):** Processes the questioned - documents in `questioned_docs`, decomposing the handwriting into - component graphs. The processed graphs are saved in RDS files in - `main_dir \> data \> questioned_graphs`. -2. **Estimate the Writer Profile of the Questioned Document(s):** - Calculates the cluster fill counts for each questioned document by - assigning each graph to the nearest cluster in the cluster template - and counting the number of graphs assigned to each cluster. The - cluster assignments are saved in - `main_dir \> data \> questioned_clusters.rds`. -3. **Estimate the Posterior Probability of Writership:** Uses the - fitted model from Step 3 to estimate the posterior probability of - writership for each questioned document and each person of interest. - The results are saved in `main_dir \> data \> analysis.rds`. - -``` r -analysis <- analyze_questioned_documents( - main_dir = "path/to/main_dir", - questioned_docs = "path/to/main_dir/questioned_docs", - model = model, - writer_indices = c(8,11), - doc_indices = c(13,16), - num_cores = 2) -``` - -Let’s pretend that a handwriting sample from each of the 5 “persons of -interest” is a questioned document. These documents are also from the -[CSAFE handwriting -database](https://data.csafe.iastate.edu/HandwritingDatabase/) and have -already been analyzed with `example_model` and the results are included -in handwriter as `example_analysis`. - -``` r -analysis <- example_analysis -``` - -View the cluster fill counts for each questioned document. Intuitively, -the model assesses which writer’s cluster fill counts look the most like -the cluster fill counts observed in each questioned document. - -``` r -plot_cluster_fill_counts(analysis, facet = TRUE) -``` - - - -View the posterior probabilities of writership. - -``` r -analysis$posterior_probabilities -#> known_writer w0030_s03_pWOZ_r01 -#> 1 known_writer_w0009 0 -#> 2 known_writer_w0030 1 -#> 3 known_writer_w0238 0 -``` - -#### For Research Only - -In practice, we would not know who wrote a questioned document, but in -research we often perform tests to evaluate models using data where we -know the ground truth. Because in this example, we know the true writer -of each questioned document, we can measure the accuracy of the model. -We define accuracy as the average posterior probability assigned to the -true writer. The accuracy of our model is - -``` r -calculate_accuracy(analysis) -#> [1] 1 -``` diff --git a/docs/_sidebar.md b/docs/_sidebar.md deleted file mode 100644 index 334c9e2d..00000000 --- a/docs/_sidebar.md +++ /dev/null @@ -1,51 +0,0 @@ -* [Home](/) -* Articles: - - [analyze-writing](vignettes/handwriter.md) -* Reference: - - [about_variable](man/about_variable) - - [addToFeatures](man/addToFeatures) - - [analyze_questioned_documents](man/analyze_questioned_documents) - - [calculate_accuracy](man/calculate_accuracy) - - [cleanBinaryImage](man/cleanBinaryImage) - - [csafe](man/csafe) - - [drop_burnin](man/drop_burnin) - - [example_analysis](man/example_analysis) - - [example_cluster_template](man/example_cluster_template) - - [example_model](man/example_model) - - [extractGraphs](man/extractGraphs) - - [fit_model](man/fit_model) - - [format_template_data](man/format_template_data) - - [get_cluster_fill_counts](man/get_cluster_fill_counts) - - [get_clusters_batch](man/get_clusters_batch) - - [get_credible_intervals](man/get_credible_intervals) - - [get_posterior_probabilities](man/get_posterior_probabilities) - - [graphToPrototype](man/graphToPrototype) - - [london](man/london) - - [make_clustering_template](man/make_clustering_template) - - [message](man/message) - - [nature1](man/nature1) - - [plot_cluster_centers](man/plot_cluster_centers) - - [plot_cluster_fill_counts](man/plot_cluster_fill_counts) - - [plot_cluster_fill_rates](man/plot_cluster_fill_rates) - - [plot_credible_intervals](man/plot_credible_intervals) - - [plot_posterior_probabilities](man/plot_posterior_probabilities) - - [plot_trace](man/plot_trace) - - [plotImage](man/plotImage) - - [plotImageThinned](man/plotImageThinned) - - [plotLetter](man/plotLetter) - - [plotLine](man/plotLine) - - [plotNodes](man/plotNodes) - - [process_batch_dir](man/process_batch_dir) - - [process_batch_list](man/process_batch_list) - - [processDocument](man/processDocument) - - [processHandwriting](man/processHandwriting) - - [read_and_process](man/read_and_process) - - [readPNGBinary](man/readPNGBinary) - - [rgb2grayscale](man/rgb2grayscale) - - [rgba2rgb](man/rgba2rgb) - - [thinImage](man/thinImage) - - [twoSent](man/twoSent) - - [whichToFill](man/whichToFill) -* [News](NEWS.md) -* [License](LICENSE.md) -* [Citation](CITATION.md) diff --git a/docs/clustering.html b/docs/clustering.html deleted file mode 100644 index b3157501..00000000 --- a/docs/clustering.html +++ /dev/null @@ -1,192 +0,0 @@ - - - - - - - - - Handwriter - - - - - - - - -
- -
- - - -
-

Research Pipeline: K-means Clustering

- -

Handwriter also supports K-means clustering of graphs.

-

To create a clustering template you can use createClusterTemplates() -

createClusterTemplates() only has one required parameter, documentDirectory which is the folder where the documents to process reside. - Paths can also be provided for storage of log files, temp files, and results files. Otherwise, they will be stored within documentDirectory

- -

Typical use cases:

-
-                      #The most basic call, with only the documentDirectory provided
-                      createClusterTemplates("path/to/directory")
-                      
-                      #A call with the documentDirectory, resultsFile, 25 clusters and 5 cluster sets
-                      createClusterTemplates(documentDirectory = "path/to/directory", resultsFile = "path/to/resultsfile", K = 25, numberToRun = 5)
-                    
- -

The parameters for createClusterTemplates() include:

-
    -
  • - documentDirectory | STRING | REQUIRED -
      - The directory where the .png files are located. -
    -
  • -
  • - logDirectory | STRING | OPTIONAL | DEFAULT: documentDirectory -
      - Where the logs will be saved. -
    -
  • -
  • - dataDirectory | STRING | OPTIONAL | DEFAULT: documentDirectory -
      - The directory where the temporary data will be saved. -
    -
  • -
  • - resultsFile | STRING | OPTIONAL | DEFAULT: documentDirectory -
      - Representing the file where the results will be saved. -
    -
  • -
  • - K | INTEGER | OPTIONAL | DEFAULT: 40 -
      - How many clusters will be created -
    -
  • -
  • - numberToRun | INTEGER | OPTIONAL | DEFAULT: 1 -
      - How many cluster sets will be created. -
    -
  • -
  • - numCores | INTEGER | OPTIONAL | DEFAULT: 1 -
      - Number of cores. Each clustering template will be created on a different core. - If you have the necessary resources this can significantly improve processing time. -
    -
  • -
  • - numDistCores | INTEGER | OPTIONAL | DEFAULT: 1 -
      - Integer number of cores to use for distance calculations. - If you have the necessary resources this can significantly improve processing time. -
    -
  • -
  • - iter.max | INTEGER | OPTIONAL | DEFAULT: 500 -
      - Integer maximum number of iterations to allow cluster centers to converge -
    -
  • -
  • - gamma | INTEGER | OPTIONAL | DEFAULT: 3 -
      - Float parameter for calculating the outlier cutoff. If numOutliers is zero, gamma has no effect. -
    -
  • -
  • - meanGraph | STRING | OPTIONAL | DEFAULT: 'slow_change' -
      -
    • String choice of algorithm for calculating mean graphs. The choices are 'basic', 'slow_change' and 'kmeans'
    • -
    -
  • -
  • - meanGraphOrder | STRING | OPTIONAL | DEFAULT: 'sequential'. -
      - Chose the order in which to add graphs to the mean graph calculations. The options are 'sequential' and 'random' -
    -
  • -
  • - fillClusters | STRING | OPTIONAL | DEFAULT: 'farthest' -
      - String choice of how to choose which graph to reassign to an empty cluster. Choices are 'random' and 'farthest' -
    -
  • -
- - - - -
-
- - - - - - - diff --git a/docs/css/collapsiblestyle.css b/docs/css/collapsiblestyle.css deleted file mode 100644 index 67706c47..00000000 --- a/docs/css/collapsiblestyle.css +++ /dev/null @@ -1,47 +0,0 @@ -@charset "UTF-8"; - -.collapsible { -background-color: #01579b; -outline-color: #01579b; -color: white; -cursor: pointer; -padding: 18px; -width: 100%; -border: none; -text-align: left; -outline: none; -font-size: 15px; -} - -.collapsible:hover { -background-color: #0091ea; -} - -.collapsible:after { -content: '\002B'; -color: white; -font-weight: bold; -float: ight; -margin-left: 5px; -} - -.active:after { -content: "\2212"; -} - -.content { -padding: 0 18px; -max-height: 0; -overflow: hidden; -transition: max-height 0.2s ease-out; -outline-color: #f1f1f1; -} - - -code{ - font-family: var(--font-monospace); - background-color: #ededed; - font-size: 1em; - direction: ltr /* rtl:ignore */; - unicode-bidi: bidi-override; -} diff --git a/docs/css/styles.css b/docs/css/styles.css deleted file mode 100755 index a9b8f39b..00000000 --- a/docs/css/styles.css +++ /dev/null @@ -1,11019 +0,0 @@ -@charset "UTF-8"; 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-} - -.list-inline { - padding-left: 0; - list-style: none; -} - -.list-inline-item { - display: inline-block; -} -.list-inline-item:not(:last-child) { - margin-right: 0.5rem; -} - -.initialism { - font-size: 0.875em; - text-transform: uppercase; -} - -.blockquote { - margin-bottom: 1rem; - font-size: 1.25rem; -} -.blockquote > :last-child { - margin-bottom: 0; -} - -.blockquote-footer { - margin-top: -1rem; - margin-bottom: 1rem; - font-size: 0.875em; - color: #8A8A8D; -} -.blockquote-footer::before { - content: "— "; -} - -.img-fluid { - max-width: 100%; - height: auto; -} - -.center { - display: block; - margin-left: auto; - margin-right: auto; -} - -.img-thumbnail { - padding: 0.25rem; - background-color: #fff; - border: 1px solid #dee2e6; - border-radius: 0.25rem; - max-width: 100%; - height: auto; -} - -.figure { - display: inline-block; -} - -.figure-img { - margin-bottom: 0.5rem; - line-height: 1; -} - -.figure-caption { - font-size: 0.875em; - color: #8A8A8D; -} - -.container, -.container-fluid, -.container-xxl, -.container-xl, -.container-lg, -.container-md, -.container-sm { - width: 100%; - padding-right: var(--gutter-x, 1rem); - padding-left: var(--gutter-x, 1rem); - margin-right: auto; - margin-left: auto; -} - -@media (min-width: 576px) { - .container-sm, .container { - max-width: 540px; - } -} -@media (min-width: 768px) { - .container-md, .container-sm, .container { - max-width: 720px; - } -} -@media (min-width: 992px) { - .container-lg, .container-md, .container-sm, .container { - max-width: 960px; - } -} -@media (min-width: 1200px) { - .container-xl, .container-lg, .container-md, .container-sm, .container { - max-width: 1140px; - } -} -@media (min-width: 1400px) { - .container-xxl, .container-xl, .container-lg, .container-md, .container-sm, .container { - max-width: 1320px; - } -} -.row { - --gutter-x: 1.5rem; - --gutter-y: 0; - display: flex; - flex-wrap: wrap; - margin-top: calc(var(-gutter-y) * -1); - margin-right: calc(var(-gutter-x) * -.5); - margin-left: calc(var(-gutter-x) * -.5); -} -.row > * { - flex-shrink: 0; - width: 100%; - max-width: 100%; - padding-right: calc(var(--gutter-x) * .5); - padding-left: calc(var(--gutter-x) * .5); - margin-top: var(--gutter-y); -} - -.col { - flex: 1 0 0%; -} - -.row-cols-auto > * { - flex: 0 0 auto; - width: auto; -} - -.row-cols-1 > * { - flex: 0 0 auto; - width: 100%; -} - -.row-cols-2 > * { - flex: 0 0 auto; - width: 50%; -} - -.row-cols-3 > * { - flex: 0 0 auto; - width: 33.3333333333%; -} - -.row-cols-4 > * { - flex: 0 0 auto; - width: 25%; -} - -.row-cols-5 > * { - flex: 0 0 auto; - width: 20%; -} - -.row-cols-6 > * { - flex: 0 0 auto; - width: 16.6666666667%; -} - -@media (min-width: 576px) { - .col-sm { - flex: 1 0 0%; - } - - .row-cols-sm-auto > * { - flex: 0 0 auto; - width: auto; - } - - .row-cols-sm-1 > * { - flex: 0 0 auto; - width: 100%; - } - - .row-cols-sm-2 > * { - flex: 0 0 auto; - width: 50%; - } - - .row-cols-sm-3 > * { - flex: 0 0 auto; - width: 33.3333333333%; - } - - .row-cols-sm-4 > * { - flex: 0 0 auto; - width: 25%; - } - - .row-cols-sm-5 > * { - flex: 0 0 auto; - width: 20%; - } - - .row-cols-sm-6 > * { - flex: 0 0 auto; - width: 16.6666666667%; - } -} -@media (min-width: 768px) { - .col-md { - flex: 1 0 0%; - } - - .row-cols-md-auto > * { - flex: 0 0 auto; - width: auto; - } - - .row-cols-md-1 > * { - flex: 0 0 auto; - width: 100%; - } - - .row-cols-md-2 > * { - flex: 0 0 auto; - width: 50%; - } - - .row-cols-md-3 > * { - flex: 0 0 auto; - width: 33.3333333333%; - } - - .row-cols-md-4 > * { - flex: 0 0 auto; - width: 25%; - } - - .row-cols-md-5 > * { - flex: 0 0 auto; - width: 20%; - } - - .row-cols-md-6 > * { - flex: 0 0 auto; - width: 16.6666666667%; - } -} -@media (min-width: 992px) { - .col-lg { - flex: 1 0 0%; - } - - .row-cols-lg-auto > * { - flex: 0 0 auto; - width: auto; - } - - .row-cols-lg-1 > * { - flex: 0 0 auto; - width: 100%; - } - - .row-cols-lg-2 > * { - flex: 0 0 auto; - width: 50%; - } - - .row-cols-lg-3 > * { - flex: 0 0 auto; - width: 33.3333333333%; - } - - .row-cols-lg-4 > * { - flex: 0 0 auto; - width: 25%; - } - - .row-cols-lg-5 > * { - flex: 0 0 auto; - width: 20%; - } - - .row-cols-lg-6 > * { - flex: 0 0 auto; - width: 16.6666666667%; - } -} -@media (min-width: 1200px) { - .col-xl { - flex: 1 0 0%; - } - - .row-cols-xl-auto > * { - flex: 0 0 auto; - width: auto; - } - - .row-cols-xl-1 > * { - flex: 0 0 auto; - width: 100%; - } - - .row-cols-xl-2 > * { - flex: 0 0 auto; - width: 50%; - } - - .row-cols-xl-3 > * { - flex: 0 0 auto; - width: 33.3333333333%; - } - - .row-cols-xl-4 > * { - flex: 0 0 auto; - width: 25%; - } - - .row-cols-xl-5 > * { - flex: 0 0 auto; - width: 20%; - } - - .row-cols-xl-6 > * { - flex: 0 0 auto; - width: 16.6666666667%; - } -} -@media (min-width: 1400px) { - .col-xxl { - flex: 1 0 0%; - } - - .row-cols-xxl-auto > * { - flex: 0 0 auto; - width: auto; - } - - .row-cols-xxl-1 > * { - flex: 0 0 auto; - width: 100%; - } - - .row-cols-xxl-2 > * { - flex: 0 0 auto; - width: 50%; - } - - .row-cols-xxl-3 > * { - flex: 0 0 auto; - width: 33.3333333333%; - } - - .row-cols-xxl-4 > * { - flex: 0 0 auto; - width: 25%; - } - - .row-cols-xxl-5 > * { - flex: 0 0 auto; - width: 20%; - } - - .row-cols-xxl-6 > * { - flex: 0 0 auto; - width: 16.6666666667%; - } -} -.col-auto { - flex: 0 0 auto; - width: auto; -} - -.col-1 { - flex: 0 0 auto; - width: 8.33333333%; -} - -.col-2 { - flex: 0 0 auto; - width: 16.66666667%; -} - -.col-3 { - flex: 0 0 auto; - width: 25%; -} - -.col-4 { - flex: 0 0 auto; - width: 33.33333333%; -} - -.col-5 { - flex: 0 0 auto; - width: 41.66666667%; -} - -.col-6 { - flex: 0 0 auto; - width: 50%; -} - -.col-7 { - flex: 0 0 auto; - width: 58.33333333%; -} - -.col-8 { - flex: 0 0 auto; - width: 66.66666667%; -} - -.col-9 { - flex: 0 0 auto; - width: 75%; -} - -.col-10 { - flex: 0 0 auto; - width: 83.33333333%; -} - -.col-11 { - flex: 0 0 auto; - width: 91.66666667%; -} - -.col-12 { - flex: 0 0 auto; - width: 100%; -} - -.offset-1 { - margin-left: 8.33333333%; -} - -.offset-2 { - margin-left: 16.66666667%; -} - -.offset-3 { - margin-left: 25%; -} - -.offset-4 { - margin-left: 33.33333333%; -} - -.offset-5 { - margin-left: 41.66666667%; -} - -.offset-6 { - margin-left: 50%; -} - -.offset-7 { - margin-left: 58.33333333%; -} - -.offset-8 { - margin-left: 66.66666667%; -} - -.offset-9 { - margin-left: 75%; -} - -.offset-10 { - margin-left: 83.33333333%; -} - -.offset-11 { - margin-left: 91.66666667%; -} - -.g-0, -.gx-0 { - --gutter-x: 0; -} - -.g-0, -.gy-0 { - --gutter-y: 0; -} - -.g-1, -.gx-1 { - --gutter-x: 0.25rem; -} - -.g-1, -.gy-1 { - --gutter-y: 0.25rem; -} - -.g-2, -.gx-2 { - --gutter-x: 0.5rem; -} - -.g-2, -.gy-2 { - --gutter-y: 0.5rem; -} - -.g-3, -.gx-3 { - --gutter-x: 1rem; -} - -.g-3, -.gy-3 { - --gutter-y: 1rem; -} - -.g-4, -.gx-4 { - --gutter-x: 1.5rem; -} - -.g-4, -.gy-4 { - --gutter-y: 1.5rem; -} - -.g-5, -.gx-5 { - --gutter-x: 3rem; -} - -.g-5, -.gy-5 { - --gutter-y: 3rem; -} - -@media (min-width: 576px) { - .col-sm-auto { - flex: 0 0 auto; - width: auto; - } - - .col-sm-1 { - flex: 0 0 auto; - width: 8.33333333%; - } - - .col-sm-2 { - flex: 0 0 auto; - width: 16.66666667%; - } - - .col-sm-3 { - flex: 0 0 auto; - width: 25%; - } - - .col-sm-4 { - flex: 0 0 auto; - width: 33.33333333%; - } - - .col-sm-5 { - flex: 0 0 auto; - width: 41.66666667%; - } - - .col-sm-6 { - flex: 0 0 auto; - width: 50%; - } - - .col-sm-7 { - flex: 0 0 auto; - width: 58.33333333%; - } - - .col-sm-8 { - flex: 0 0 auto; - width: 66.66666667%; - } - - .col-sm-9 { - flex: 0 0 auto; - width: 75%; - } - - .col-sm-10 { - flex: 0 0 auto; - width: 83.33333333%; - } - - .col-sm-11 { - flex: 0 0 auto; - width: 91.66666667%; - } - - .col-sm-12 { - flex: 0 0 auto; - width: 100%; - } - - .offset-sm-0 { - margin-left: 0; - } - - .offset-sm-1 { - margin-left: 8.33333333%; - } - - .offset-sm-2 { - margin-left: 16.66666667%; - } - - .offset-sm-3 { - margin-left: 25%; - } - - .offset-sm-4 { - margin-left: 33.33333333%; - } - - .offset-sm-5 { - margin-left: 41.66666667%; - } - - .offset-sm-6 { - margin-left: 50%; - } - - .offset-sm-7 { - margin-left: 58.33333333%; - } - - .offset-sm-8 { - margin-left: 66.66666667%; - } - - .offset-sm-9 { - margin-left: 75%; - } - - .offset-sm-10 { - margin-left: 83.33333333%; - } - - .offset-sm-11 { - margin-left: 91.66666667%; - } - - .g-sm-0, -.gx-sm-0 { - --gutter-x: 0; - } - - .g-sm-0, -.gy-sm-0 { - --gutter-y: 0; - } - - .g-sm-1, -.gx-sm-1 { - --gutter-x: 0.25rem; - } - - .g-sm-1, -.gy-sm-1 { - --gutter-y: 0.25rem; - } - - .g-sm-2, -.gx-sm-2 { - --gutter-x: 0.5rem; - } - - .g-sm-2, -.gy-sm-2 { - --gutter-y: 0.5rem; - } - - .g-sm-3, -.gx-sm-3 { - --gutter-x: 1rem; - } - - .g-sm-3, -.gy-sm-3 { - --gutter-y: 1rem; - } - - .g-sm-4, -.gx-sm-4 { - --gutter-x: 1.5rem; - } - - .g-sm-4, -.gy-sm-4 { - --gutter-y: 1.5rem; - } - - .g-sm-5, -.gx-sm-5 { - --gutter-x: 3rem; - } - - .g-sm-5, -.gy-sm-5 { - --gutter-y: 3rem; - } -} -@media (min-width: 768px) { - .col-md-auto { - flex: 0 0 auto; - width: auto; - } - - .col-md-1 { - flex: 0 0 auto; - width: 8.33333333%; - } - - .col-md-2 { - flex: 0 0 auto; - width: 16.66666667%; - } - - .col-md-3 { - flex: 0 0 auto; - width: 25%; - } - - .col-md-4 { - flex: 0 0 auto; - width: 33.33333333%; - } - - .col-md-5 { - flex: 0 0 auto; - width: 41.66666667%; - } - - .col-md-6 { - flex: 0 0 auto; - width: 50%; - } - - .col-md-7 { - flex: 0 0 auto; - width: 58.33333333%; - } - - .col-md-8 { - flex: 0 0 auto; - width: 66.66666667%; - } - - .col-md-9 { - flex: 0 0 auto; - width: 75%; - } - - .col-md-10 { - flex: 0 0 auto; - width: 83.33333333%; - } - - .col-md-11 { - flex: 0 0 auto; - width: 91.66666667%; - } - - .col-md-12 { - flex: 0 0 auto; - width: 100%; - } - - .offset-md-0 { - margin-left: 0; - } - - .offset-md-1 { - margin-left: 8.33333333%; - } - - .offset-md-2 { - margin-left: 16.66666667%; - } - - .offset-md-3 { - margin-left: 25%; - } - - .offset-md-4 { - margin-left: 33.33333333%; - } - - .offset-md-5 { - margin-left: 41.66666667%; - } - - .offset-md-6 { - margin-left: 50%; - } - - .offset-md-7 { - margin-left: 58.33333333%; - } - - .offset-md-8 { - margin-left: 66.66666667%; - } - - .offset-md-9 { - margin-left: 75%; - } - - .offset-md-10 { - margin-left: 83.33333333%; - } - - .offset-md-11 { - margin-left: 91.66666667%; - } - - .g-md-0, -.gx-md-0 { - --gutter-x: 0; - } - - .g-md-0, -.gy-md-0 { - --gutter-y: 0; - } - - .g-md-1, -.gx-md-1 { - --gutter-x: 0.25rem; - } - - .g-md-1, -.gy-md-1 { - --gutter-y: 0.25rem; - } - - .g-md-2, -.gx-md-2 { - --gutter-x: 0.5rem; - } - - .g-md-2, -.gy-md-2 { - --gutter-y: 0.5rem; - } - - .g-md-3, -.gx-md-3 { - --gutter-x: 1rem; - } - - .g-md-3, -.gy-md-3 { - --gutter-y: 1rem; - } - - .g-md-4, -.gx-md-4 { - --gutter-x: 1.5rem; - } - - .g-md-4, -.gy-md-4 { - --gutter-y: 1.5rem; - } - - .g-md-5, -.gx-md-5 { - --gutter-x: 3rem; - } - - .g-md-5, -.gy-md-5 { - --gutter-y: 3rem; - } -} -@media (min-width: 992px) { - .col-lg-auto { - flex: 0 0 auto; - width: auto; - } - - .col-lg-1 { - flex: 0 0 auto; - width: 8.33333333%; - } - - .col-lg-2 { - flex: 0 0 auto; - width: 16.66666667%; - } - - .col-lg-3 { - flex: 0 0 auto; - width: 25%; - } - - .col-lg-4 { - flex: 0 0 auto; - width: 33.33333333%; - } - - .col-lg-5 { - flex: 0 0 auto; - width: 41.66666667%; - } - - .col-lg-6 { - flex: 0 0 auto; - width: 50%; - } - - .col-lg-7 { - flex: 0 0 auto; - width: 58.33333333%; - } - - .col-lg-8 { - flex: 0 0 auto; - width: 66.66666667%; - } - - .col-lg-9 { - flex: 0 0 auto; - width: 75%; - } - - .col-lg-10 { - flex: 0 0 auto; - width: 83.33333333%; - } - - .col-lg-11 { - flex: 0 0 auto; - width: 91.66666667%; - } - - .col-lg-12 { - flex: 0 0 auto; - width: 100%; - } - - .offset-lg-0 { - margin-left: 0; - } - - .offset-lg-1 { - margin-left: 8.33333333%; - } - - .offset-lg-2 { - margin-left: 16.66666667%; - } - - .offset-lg-3 { - margin-left: 25%; - } - - .offset-lg-4 { - margin-left: 33.33333333%; - } - - .offset-lg-5 { - margin-left: 41.66666667%; - } - - .offset-lg-6 { - margin-left: 50%; - } - - .offset-lg-7 { - margin-left: 58.33333333%; - } - - .offset-lg-8 { - margin-left: 66.66666667%; - } - - .offset-lg-9 { - margin-left: 75%; - } - - .offset-lg-10 { - margin-left: 83.33333333%; - } - - .offset-lg-11 { - margin-left: 91.66666667%; - } - - .g-lg-0, -.gx-lg-0 { - --gutter-x: 0; - } - - .g-lg-0, -.gy-lg-0 { - --gutter-y: 0; - } - - .g-lg-1, -.gx-lg-1 { - --gutter-x: 0.25rem; - } - - .g-lg-1, -.gy-lg-1 { - --gutter-y: 0.25rem; - } - - .g-lg-2, -.gx-lg-2 { - --gutter-x: 0.5rem; - } - - .g-lg-2, -.gy-lg-2 { - --gutter-y: 0.5rem; - } - - .g-lg-3, -.gx-lg-3 { - --gutter-x: 1rem; - } - - .g-lg-3, -.gy-lg-3 { - --gutter-y: 1rem; - } - - .g-lg-4, -.gx-lg-4 { - --gutter-x: 1.5rem; - } - - .g-lg-4, -.gy-lg-4 { - --gutter-y: 1.5rem; - } - - .g-lg-5, -.gx-lg-5 { - --gutter-x: 3rem; - } - - .g-lg-5, -.gy-lg-5 { - --gutter-y: 3rem; - } -} -@media (min-width: 1200px) { - .col-xl-auto { - flex: 0 0 auto; - width: auto; - } - - .col-xl-1 { - flex: 0 0 auto; - width: 8.33333333%; - } - - .col-xl-2 { - flex: 0 0 auto; - width: 16.66666667%; - } - - .col-xl-3 { - flex: 0 0 auto; - width: 25%; - } - - .col-xl-4 { - flex: 0 0 auto; - width: 33.33333333%; - } - - .col-xl-5 { - flex: 0 0 auto; - width: 41.66666667%; - } - - .col-xl-6 { - flex: 0 0 auto; - width: 50%; - } - - .col-xl-7 { - flex: 0 0 auto; - width: 58.33333333%; - } - - .col-xl-8 { - flex: 0 0 auto; - width: 66.66666667%; - } - - .col-xl-9 { - flex: 0 0 auto; - width: 75%; - } - - .col-xl-10 { - flex: 0 0 auto; - width: 83.33333333%; - } - - .col-xl-11 { - flex: 0 0 auto; - width: 91.66666667%; - } - - .col-xl-12 { - flex: 0 0 auto; - width: 100%; - } - - .offset-xl-0 { - margin-left: 0; - } - - .offset-xl-1 { - margin-left: 8.33333333%; - } - - .offset-xl-2 { - margin-left: 16.66666667%; - } - - .offset-xl-3 { - margin-left: 25%; - } - - .offset-xl-4 { - margin-left: 33.33333333%; - } - - .offset-xl-5 { - margin-left: 41.66666667%; - } - - .offset-xl-6 { - margin-left: 50%; - } - - .offset-xl-7 { - margin-left: 58.33333333%; - } - - .offset-xl-8 { - margin-left: 66.66666667%; - } - - .offset-xl-9 { - margin-left: 75%; - } - - .offset-xl-10 { - margin-left: 83.33333333%; - } - - .offset-xl-11 { - margin-left: 91.66666667%; - } - - .g-xl-0, -.gx-xl-0 { - --gutter-x: 0; - } - - .g-xl-0, -.gy-xl-0 { - --gutter-y: 0; - } - - .g-xl-1, -.gx-xl-1 { - --gutter-x: 0.25rem; - } - - .g-xl-1, -.gy-xl-1 { - --gutter-y: 0.25rem; - } - - .g-xl-2, -.gx-xl-2 { - --gutter-x: 0.5rem; - } - - .g-xl-2, -.gy-xl-2 { - --gutter-y: 0.5rem; - } - - .g-xl-3, -.gx-xl-3 { - --gutter-x: 1rem; - } - - .g-xl-3, -.gy-xl-3 { - --gutter-y: 1rem; - } - - .g-xl-4, -.gx-xl-4 { - --gutter-x: 1.5rem; - } - - .g-xl-4, -.gy-xl-4 { - --gutter-y: 1.5rem; - } - - .g-xl-5, -.gx-xl-5 { - --gutter-x: 3rem; - } - - .g-xl-5, -.gy-xl-5 { - --gutter-y: 3rem; - } -} -@media (min-width: 1400px) { - .col-xxl-auto { - flex: 0 0 auto; - width: auto; - } - - .col-xxl-1 { - flex: 0 0 auto; - width: 8.33333333%; - } - - .col-xxl-2 { - flex: 0 0 auto; - width: 16.66666667%; - } - - .col-xxl-3 { - flex: 0 0 auto; - width: 25%; - } - - .col-xxl-4 { - flex: 0 0 auto; - width: 33.33333333%; - } - - .col-xxl-5 { - flex: 0 0 auto; - width: 41.66666667%; - } - - .col-xxl-6 { - flex: 0 0 auto; - width: 50%; - } - - .col-xxl-7 { - flex: 0 0 auto; - width: 58.33333333%; - } - - .col-xxl-8 { - flex: 0 0 auto; - width: 66.66666667%; - } - - .col-xxl-9 { - flex: 0 0 auto; - width: 75%; - } - - .col-xxl-10 { - flex: 0 0 auto; - width: 83.33333333%; - } - - .col-xxl-11 { - flex: 0 0 auto; - width: 91.66666667%; - } - - .col-xxl-12 { - flex: 0 0 auto; - width: 100%; - } - - .offset-xxl-0 { - margin-left: 0; - } - - .offset-xxl-1 { - margin-left: 8.33333333%; - } - - .offset-xxl-2 { - margin-left: 16.66666667%; - } - - .offset-xxl-3 { - margin-left: 25%; - } - - .offset-xxl-4 { - margin-left: 33.33333333%; - } - - .offset-xxl-5 { - margin-left: 41.66666667%; - } - - .offset-xxl-6 { - margin-left: 50%; - } - - .offset-xxl-7 { - margin-left: 58.33333333%; - } - - .offset-xxl-8 { - margin-left: 66.66666667%; - } - - .offset-xxl-9 { - margin-left: 75%; - } - - .offset-xxl-10 { - margin-left: 83.33333333%; - } - - .offset-xxl-11 { - margin-left: 91.66666667%; - } - - .g-xxl-0, -.gx-xxl-0 { - --gutter-x: 0; - } - - .g-xxl-0, -.gy-xxl-0 { - --gutter-y: 0; - } - - .g-xxl-1, -.gx-xxl-1 { - --gutter-x: 0.25rem; - } - - .g-xxl-1, -.gy-xxl-1 { - --gutter-y: 0.25rem; - } - - .g-xxl-2, -.gx-xxl-2 { - --gutter-x: 0.5rem; - } - - .g-xxl-2, -.gy-xxl-2 { - --gutter-y: 0.5rem; - } - - .g-xxl-3, -.gx-xxl-3 { - --gutter-x: 1rem; - } - - .g-xxl-3, -.gy-xxl-3 { - --gutter-y: 1rem; - } - - .g-xxl-4, -.gx-xxl-4 { - --gutter-x: 1.5rem; - } - - .g-xxl-4, -.gy-xxl-4 { - --gutter-y: 1.5rem; - } - - .g-xxl-5, -.gx-xxl-5 { - --gutter-x: 3rem; - } - - .g-xxl-5, -.gy-xxl-5 { - --gutter-y: 3rem; - } -} -.table { - --table-bg: transparent; - --table-accent-bg: transparent; - --table-striped-color: #000000; - --table-striped-bg: rgba(0, 0, 0, 0.05); - --table-active-color: #000000; - --table-active-bg: rgba(0, 0, 0, 0.1); - --table-hover-color: #000000; - --table-hover-bg: rgba(0, 0, 0, 0.075); - width: 100%; - margin-bottom: 1rem; - color: #000000; - vertical-align: top; - border-color: #dee2e6; -} -.table > :not(caption) > * > * { - padding: 0.5rem 0.5rem; - background-color: var(--table-bg); - border-bottom-width: 1px; - box-shadow: inset 0 0 0 9999px var(--table-accent-bg); -} -.table > tbody { - vertical-align: inherit; -} -.table > thead { - vertical-align: bottom; -} -.table > :not(:last-child) > :last-child > * { - border-bottom-color: currentColor; -} - -.caption-top { - caption-side: top; -} - -.table-sm > :not(caption) > * > * { - padding: 0.25rem 0.25rem; -} - -.table-bordered > :not(caption) > * { - border-width: 1px 0; -} -.table-bordered > :not(caption) > * > * { - border-width: 0 1px; -} - -.table-borderless > :not(caption) > * > * { - border-bottom-width: 0; -} - -.table-striped > tbody > tr:nth-of-type(odd) { - --table-accent-bg: var(--table-striped-bg); - color: var(--table-striped-color); -} - -.table-active { - --table-accent-bg: var(--table-active-bg); - color: var(--table-active-color); -} - -.table-hover > tbody > tr:hover { - --table-accent-bg: var(--table-hover-bg); - color: var(--table-hover-color); -} - -.table-primary { - --table-bg: #40B4E5; - --table-striped-bg: #8A8A8D; - --table-striped-color: #000; - --table-active-bg: #555759; - --table-active-color: #000; - --table-hover-bg: #003A70; - --table-hover-color: #000; - color: #000; - border-color: #00833E; -} - -.table-secondary { - --table-bg: #40B4E5; - --table-striped-bg: #8A8A8D; - --table-striped-color: #000; - --table-active-bg: #555759; - --table-active-color: #000; - --table-hover-bg: #003A70; - --table-hover-color: #000; - color: #000; - border-color: #00833E; -} - -.table-success { - --table-bg: #40B4E5; - --table-striped-bg: #8A8A8D; - --table-striped-color: #000; - --table-active-bg: #555759; - --table-active-color: #000; - --table-hover-bg: #003A70; - --table-hover-color: #000; - color: #000; - border-color: #00833E; -} - -.table-info { - --table-bg: #40B4E5; - --table-striped-bg: #8A8A8D; - --table-striped-color: #000; - --table-active-bg: #555759; - --table-active-color: #000; - --table-hover-bg: #003A70; - --table-hover-color: #000; - color: #000; - border-color: #00833E; -} - -.table-warning { - --table-bg: #40B4E5; - --table-striped-bg: #8A8A8D; - --table-striped-color: #000; - --table-active-bg: #555759; - --table-active-color: #000; - --table-hover-bg: #003A70; - --table-hover-color: #000; - color: #000; - border-color: #00833E; -} - -.table-danger { - --table-bg: #40B4E5; - --table-striped-bg: #8A8A8D; - --table-striped-color: #000; - --table-active-bg: #555759; - --table-active-color: #000; - --table-hover-bg: #003A70; - --table-hover-color: #000; - color: #000; - border-color: #00833E; -} - -.table-light { - --table-bg: #40B4E5; - --table-striped-bg: #8A8A8D; - --table-striped-color: #000; - --table-active-bg: #555759; - --table-active-color: #000; - --table-hover-bg: #003A70; - --table-hover-color: #000; - color: #000; - border-color: #00833E; -} - -.table-dark { - --table-bg: #40B4E5; - --table-striped-bg: #8A8A8D; - --table-striped-color: #000; - --table-active-bg: #555759; - --table-active-color: #000; - --table-hover-bg: #003A70; - --table-hover-color: #000; - color: #000; - border-color: #00833E; -} - -.table-responsive { - overflow-x: auto; - -webkit-overflow-scrolling: touch; -} - -@media (max-width: 575.98px) { - .table-responsive-sm { - overflow-x: auto; - -webkit-overflow-scrolling: touch; - } -} -@media (max-width: 767.98px) { - .table-responsive-md { - overflow-x: auto; - -webkit-overflow-scrolling: touch; - } -} -@media (max-width: 991.98px) { - .table-responsive-lg { - overflow-x: auto; - -webkit-overflow-scrolling: touch; - } -} -@media (max-width: 1199.98px) { - .table-responsive-xl { - overflow-x: auto; - -webkit-overflow-scrolling: touch; - } -} -@media (max-width: 1399.98px) { - .table-responsive-xxl { - overflow-x: auto; - -webkit-overflow-scrolling: touch; - } -} -.form-label { - margin-bottom: 0.5rem; -} - -.col-form-label { - padding-top: calc(0.375rem + 1px); - padding-bottom: calc(0.375rem + 1px); - margin-bottom: 0; - font-size: inherit; - line-height: 1.5; -} - -.col-form-label-lg { - padding-top: calc(0.5rem + 1px); - padding-bottom: calc(0.5rem + 1px); - font-size: 1.25rem; -} - -.col-form-label-sm { - padding-top: calc(0.25rem + 1px); - padding-bottom: calc(0.25rem + 1px); - font-size: 0.875rem; -} - -.form-text { - margin-top: 0.25rem; - font-size: 0.875em; - color: #8A8A8D; -} - -.form-control { - display: block; - width: 100%; - padding: 0.375rem 0.75rem; - font-size: 1rem; - font-weight: 400; - line-height: 1.5; - color: #000000; - background-color: #fff; - background-clip: padding-box; - border: 1px solid #ced4da; - -webkit-appearance: none; - -moz-appearance: none; - appearance: none; - border-radius: 0.25rem; - transition: border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out; -} -@media (prefers-reduced-motion: reduce) { - .form-control { - transition: none; - } -} -.form-control[type=file] { - overflow: hidden; -} -.form-control[type=file]:not(:disabled):not([readonly]) { - cursor: pointer; -} -.form-control:focus { - color: #000000; - background-color: #fff; - border-color: #86b7fe; - outline: 0; - box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25); -} -.form-control::-webkit-date-and-time-value { - height: 1.5em; -} -.form-control::-moz-placeholder { - color: #8A8A8D; - opacity: 1; -} -.form-control:-ms-input-placeholder { - color: #8A8A8D; - opacity: 1; -} -.form-control::placeholder { - color: #8A8A8D; - opacity: 1; -} -.form-control:disabled, .form-control[readonly] { - background-color: #e9ecef; - opacity: 1; -} -.form-control::file-selector-button { - padding: 0.375rem 0.75rem; - margin: -0.375rem -0.75rem; - -webkit-margin-end: 0.75rem; - margin-inline-end: 0.75rem; - color: #000000; - background-color: #e9ecef; - pointer-events: none; - border-color: inherit; - border-style: solid; - border-width: 0; - border-inline-end-width: 1px; - border-radius: 0; - transition: color 0.15s ease-in-out, background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out; -} -@media (prefers-reduced-motion: reduce) { - .form-control::file-selector-button { - transition: none; - } -} -.form-control:hover:not(:disabled):not([readonly])::file-selector-button { - background-color: #dde0e3; -} -.form-control::-webkit-file-upload-button { - padding: 0.375rem 0.75rem; - margin: -0.375rem -0.75rem; - -webkit-margin-end: 0.75rem; - margin-inline-end: 0.75rem; - color: #000000; - background-color: #e9ecef; - pointer-events: none; - border-color: inherit; - border-style: solid; - border-width: 0; - border-inline-end-width: 1px; - border-radius: 0; - -webkit-transition: color 0.15s ease-in-out, background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out; - transition: color 0.15s ease-in-out, background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out; -} -@media (prefers-reduced-motion: reduce) { - .form-control::-webkit-file-upload-button { - -webkit-transition: none; - transition: none; - } -} -.form-control:hover:not(:disabled):not([readonly])::-webkit-file-upload-button { - background-color: #dde0e3; -} - -.form-control-plaintext { - display: block; - width: 100%; - padding: 0.375rem 0; - margin-bottom: 0; - line-height: 1.5; - color: #000000; - background-color: transparent; - border: solid transparent; - border-width: 1px 0; -} -.form-control-plaintext.form-control-sm, .form-control-plaintext.form-control-lg { - padding-right: 0; - padding-left: 0; -} - -.form-control-sm { - min-height: calc(1.5em + (0.5rem + 2px)); - padding: 0.25rem 0.5rem; - font-size: 0.875rem; - border-radius: 0.2rem; -} -.form-control-sm::file-selector-button { - padding: 0.25rem 0.5rem; - margin: -0.25rem -0.5rem; - -webkit-margin-end: 0.5rem; - margin-inline-end: 0.5rem; -} -.form-control-sm::-webkit-file-upload-button { - padding: 0.25rem 0.5rem; - margin: -0.25rem -0.5rem; - -webkit-margin-end: 0.5rem; - margin-inline-end: 0.5rem; -} - -.form-control-lg { - min-height: calc(1.5em + (1rem + 2px)); - padding: 0.5rem 1rem; - font-size: 1.25rem; - border-radius: 0.3rem; -} -.form-control-lg::file-selector-button { - padding: 0.5rem 1rem; - margin: -0.5rem -1rem; - -webkit-margin-end: 1rem; - margin-inline-end: 1rem; -} -.form-control-lg::-webkit-file-upload-button { - padding: 0.5rem 1rem; - margin: -0.5rem -1rem; - -webkit-margin-end: 1rem; - margin-inline-end: 1rem; -} - -textarea.form-control { - min-height: calc(1.5em + (0.75rem + 2px)); -} -textarea.form-control-sm { - min-height: calc(1.5em + (0.5rem + 2px)); -} -textarea.form-control-lg { - min-height: calc(1.5em + (1rem + 2px)); -} - -.form-control-color { - max-width: 3rem; - height: auto; - padding: 0.375rem; -} -.form-control-color:not(:disabled):not([readonly]) { - cursor: pointer; -} -.form-control-color::-moz-color-swatch { - height: 1.5em; - border-radius: 0.25rem; -} -.form-control-color::-webkit-color-swatch { - height: 1.5em; - border-radius: 0.25rem; -} - -.form-select { - display: block; - width: 100%; - padding: 0.375rem 2.25rem 0.375rem 0.75rem; - -moz-padding-start: calc(0.75rem - 3px); - font-size: 1rem; - font-weight: 400; - line-height: 1.5; - color: #000000; - background-color: #fff; - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16'%3e%3cpath fill='none' stroke='%23555759' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' d='M2 5l6 6 6-6'/%3e%3c/svg%3e"); - background-repeat: no-repeat; - background-position: right 0.75rem center; - background-size: 16px 12px; - border: 1px solid #ced4da; - border-radius: 0.25rem; - transition: border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out; - -webkit-appearance: none; - -moz-appearance: none; - appearance: none; -} -@media (prefers-reduced-motion: reduce) { - .form-select { - transition: none; - } -} -.form-select:focus { - border-color: #86b7fe; - outline: 0; - box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25); -} -.form-select[multiple], .form-select[size]:not([size="1"]) { - padding-right: 0.75rem; - background-image: none; -} -.form-select:disabled { - background-color: #e9ecef; -} -.form-select:-moz-focusring { - color: transparent; - text-shadow: 0 0 0 #000000; -} - -.form-select-sm { - padding-top: 0.25rem; - padding-bottom: 0.25rem; - padding-left: 0.5rem; - font-size: 0.875rem; -} - -.form-select-lg { - padding-top: 0.5rem; - padding-bottom: 0.5rem; - padding-left: 1rem; - font-size: 1.25rem; -} - -.form-check { - display: block; - min-height: 1.5rem; - padding-left: 1.5em; - margin-bottom: 0.125rem; -} -.form-check .form-check-input { - float: left; - margin-left: -1.5em; -} - -.form-check-input { - width: 1em; - height: 1em; - margin-top: 0.25em; - vertical-align: top; - background-color: #fff; - background-repeat: no-repeat; - background-position: center; - background-size: contain; - border: 1px solid rgba(0, 0, 0, 0.25); - -webkit-appearance: none; - -moz-appearance: none; - appearance: none; - -webkit-print-color-adjust: exact; - color-adjust: exact; -} -.form-check-input[type=checkbox] { - border-radius: 0.25em; -} -.form-check-input[type=radio] { - border-radius: 50%; -} -.form-check-input:active { - filter: brightness(90%); -} -.form-check-input:focus { - border-color: #86b7fe; - outline: 0; - box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25); -} -.form-check-input:checked { - background-color: #40B4E5; - border-color: #40B4E5; -} -.form-check-input:checked[type=checkbox] { - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 20 20'%3e%3cpath fill='none' stroke='%23fff' stroke-linecap='round' stroke-linejoin='round' stroke-width='3' d='M6 10l3 3l6-6'/%3e%3c/svg%3e"); -} -.form-check-input:checked[type=radio] { - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='-4 -4 8 8'%3e%3ccircle r='2' fill='%23fff'/%3e%3c/svg%3e"); -} -.form-check-input[type=checkbox]:indeterminate { - background-color: #40B4E5; - border-color: #40B4E5; - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 20 20'%3e%3cpath fill='none' stroke='%23fff' stroke-linecap='round' stroke-linejoin='round' stroke-width='3' d='M6 10h8'/%3e%3c/svg%3e"); -} -.form-check-input:disabled { - pointer-events: none; - filter: none; - opacity: 0.5; -} -.form-check-input[disabled] ~ .form-check-label, .form-check-input:disabled ~ .form-check-label { - opacity: 0.5; -} - -.form-switch { - padding-left: 2.5em; -} -.form-switch .form-check-input { - width: 2em; - margin-left: -2.5em; - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='-4 -4 8 8'%3e%3ccircle r='3' fill='rgba%280, 0, 0, 0.25%29'/%3e%3c/svg%3e"); - background-position: left center; - border-radius: 2em; - transition: background-position 0.15s ease-in-out; -} -@media (prefers-reduced-motion: reduce) { - .form-switch .form-check-input { - transition: none; - } -} -.form-switch .form-check-input:focus { - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='-4 -4 8 8'%3e%3ccircle r='3' fill='%2386b7fe'/%3e%3c/svg%3e"); -} -.form-switch .form-check-input:checked { - background-position: right center; - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='-4 -4 8 8'%3e%3ccircle r='3' fill='%23fff'/%3e%3c/svg%3e"); -} - -.form-check-inline { - display: inline-block; - margin-right: 1rem; -} - -.btn-check { - position: absolute; - clip: rect(0, 0, 0, 0); - pointer-events: none; -} -.btn-check[disabled] + .btn, .btn-check:disabled + .btn { - pointer-events: none; - filter: none; - opacity: 0.65; -} - -.form-range { - width: 100%; - height: 1.5rem; - padding: 0; - background-color: transparent; - -webkit-appearance: none; - -moz-appearance: none; - appearance: none; -} -.form-range:focus { - outline: 0; -} -.form-range:focus::-webkit-slider-thumb { - box-shadow: 0 0 0 1px #fff, 0 0 0 0.25rem rgba(13, 110, 253, 0.25); -} -.form-range:focus::-moz-range-thumb { - box-shadow: 0 0 0 1px #fff, 0 0 0 0.25rem rgba(13, 110, 253, 0.25); -} -.form-range::-moz-focus-outer { - border: 0; -} -.form-range::-webkit-slider-thumb { - width: 1rem; - height: 1rem; - margin-top: -0.25rem; - background-color: #40B4E5; - border: 0; - border-radius: 1rem; - -webkit-transition: background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out; - transition: background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out; - -webkit-appearance: none; - appearance: none; -} -@media (prefers-reduced-motion: reduce) { - .form-range::-webkit-slider-thumb { - -webkit-transition: none; - transition: none; - } -} -.form-range::-webkit-slider-thumb:active { - background-color: #b6d4fe; -} -.form-range::-webkit-slider-runnable-track { - width: 100%; - height: 0.5rem; - color: transparent; - cursor: pointer; - background-color: #dee2e6; - border-color: transparent; - border-radius: 1rem; -} -.form-range::-moz-range-thumb { - width: 1rem; - height: 1rem; - background-color: #40B4E5; - border: 0; - border-radius: 1rem; - -moz-transition: background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out; - transition: background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out; - -moz-appearance: none; - appearance: none; -} -@media (prefers-reduced-motion: reduce) { - .form-range::-moz-range-thumb { - -moz-transition: none; - transition: none; - } -} -.form-range::-moz-range-thumb:active { - background-color: #b6d4fe; -} -.form-range::-moz-range-track { - width: 100%; - height: 0.5rem; - color: transparent; - cursor: pointer; - background-color: #dee2e6; - border-color: transparent; - border-radius: 1rem; -} -.form-range:disabled { - pointer-events: none; -} -.form-range:disabled::-webkit-slider-thumb { - background-color: #adb5bd; -} -.form-range:disabled::-moz-range-thumb { - background-color: #adb5bd; -} - -.form-floating { - position: relative; -} -.form-floating > .form-control, -.form-floating > .form-select { - height: calc(3.5rem + 2px); - line-height: 1.25; -} -.form-floating > label { - position: absolute; - top: 0; - left: 0; - height: 100%; - padding: 1rem 0.75rem; - pointer-events: none; - border: 1px solid transparent; - transform-origin: 0 0; - transition: opacity 0.1s ease-in-out, transform 0.1s ease-in-out; -} -@media (prefers-reduced-motion: reduce) { - .form-floating > label { - transition: none; - } -} -.form-floating > .form-control { - padding: 1rem 0.75rem; -} -.form-floating > .form-control::-moz-placeholder { - color: transparent; -} -.form-floating > .form-control:-ms-input-placeholder { - color: transparent; -} -.form-floating > .form-control::placeholder { - color: transparent; -} -.form-floating > .form-control:not(:-moz-placeholder-shown) { - padding-top: 1.625rem; - padding-bottom: 0.625rem; -} -.form-floating > .form-control:not(:-ms-input-placeholder) { - padding-top: 1.625rem; - padding-bottom: 0.625rem; -} -.form-floating > .form-control:focus, .form-floating > .form-control:not(:placeholder-shown) { - padding-top: 1.625rem; - padding-bottom: 0.625rem; -} -.form-floating > .form-control:-webkit-autofill { - padding-top: 1.625rem; - padding-bottom: 0.625rem; -} -.form-floating > .form-select { - padding-top: 1.625rem; - padding-bottom: 0.625rem; -} -.form-floating > .form-control:not(:-moz-placeholder-shown) ~ label { - opacity: 0.65; - transform: scale(0.85) translateY(-0.5rem) translateX(0.15rem); -} -.form-floating > .form-control:not(:-ms-input-placeholder) ~ label { - opacity: 0.65; - transform: scale(0.85) translateY(-0.5rem) translateX(0.15rem); -} -.form-floating > .form-control:focus ~ label, -.form-floating > .form-control:not(:placeholder-shown) ~ label, -.form-floating > .form-select ~ label { - opacity: 0.65; - transform: scale(0.85) translateY(-0.5rem) translateX(0.15rem); -} -.form-floating > .form-control:-webkit-autofill ~ label { - opacity: 0.65; - transform: scale(0.85) translateY(-0.5rem) translateX(0.15rem); -} - -.input-group { - position: relative; - display: flex; - flex-wrap: wrap; - align-items: stretch; - width: 100%; -} -.input-group > .form-control, -.input-group > .form-select { - position: relative; - flex: 1 1 auto; - width: 1%; - min-width: 0; -} -.input-group > .form-control:focus, -.input-group > .form-select:focus { - z-index: 3; -} -.input-group .btn { - position: relative; - z-index: 2; -} -.input-group .btn:focus { - z-index: 3; -} - -.input-group-text { - display: flex; - align-items: center; - padding: 0.375rem 0.75rem; - font-size: 1rem; - font-weight: 400; - line-height: 1.5; - color: #000000; - text-align: center; - white-space: nowrap; - background-color: #e9ecef; - border: 1px solid #ced4da; - border-radius: 0.25rem; -} - -.input-group-lg > .form-control, -.input-group-lg > .form-select, -.input-group-lg > .input-group-text, -.input-group-lg > .btn { - padding: 0.5rem 1rem; - font-size: 1.25rem; - border-radius: 0.3rem; -} - -.input-group-sm > .form-control, -.input-group-sm > .form-select, -.input-group-sm > .input-group-text, -.input-group-sm > .btn { - padding: 0.25rem 0.5rem; - font-size: 0.875rem; - border-radius: 0.2rem; -} - -.input-group-lg > .form-select, -.input-group-sm > .form-select { - padding-right: 3rem; -} - -.input-group:not(.has-validation) > :not(:last-child):not(.dropdown-toggle):not(.dropdown-menu), -.input-group:not(.has-validation) > .dropdown-toggle:nth-last-child(n+3) { - border-top-right-radius: 0; - border-bottom-right-radius: 0; -} -.input-group.has-validation > :nth-last-child(n+3):not(.dropdown-toggle):not(.dropdown-menu), -.input-group.has-validation > .dropdown-toggle:nth-last-child(n+4) { - border-top-right-radius: 0; - border-bottom-right-radius: 0; -} -.input-group > :not(:first-child):not():not(.valid-tooltip):not(.valid-feedback):not(.invalid-tooltip):not(.invalid-feedback) { - margin-left: -1px; - border-top-left-radius: 0; - border-bottom-left-radius: 0; -} - -.valid-feedback { - display: none; - width: 100%; - margin-top: 0.25rem; - font-size: 0.875em; - color: #00833E; -} - -.valid-tooltip { - position: absolute; - top: 100%; - z-index: 5; - display: none; - max-width: 100%; - padding: 0.25rem 0.5rem; - margin-top: 0.1rem; - font-size: 0.875rem; - color: #fff; - background-color: rgba(25, 135, 84, 0.9); - border-radius: 0.25rem; -} - -.was-validated :valid ~ .valid-feedback, -.was-validated :valid ~ .valid-tooltip, -.is-valid ~ .valid-feedback, -.is-valid ~ .valid-tooltip { - display: block; -} - -.was-validated .form-control:valid, .form-control.is-valid { - border-color: #00833E; - padding-right: calc(1.5em + 0.75rem); - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 8 8'%3e%3cpath fill='%2300833E' d='M2.3 6.73L.6 4.53c-.4-1.04.46-1.4 1.1-.8l1.1 1.4 3.4-3.8c.6-.63 1.6-.27 1.2.7l-4 4.6c-.43.5-.8.4-1.1.1z'/%3e%3c/svg%3e"); - background-repeat: no-repeat; - background-position: right calc(0.375em + 0.1875rem) center; - background-size: calc(0.75em + 0.375rem) calc(0.75em + 0.375rem); -} -.was-validated .form-control:valid:focus, .form-control.is-valid:focus { - border-color: #00833E; - box-shadow: 0 0 0 0.25rem rgba(25, 135, 84, 0.25); -} - -.was-validated textarea.form-control:valid, textarea.form-control.is-valid { - padding-right: calc(1.5em + 0.75rem); - background-position: top calc(0.375em + 0.1875rem) right calc(0.375em + 0.1875rem); -} - -.was-validated .form-select:valid, .form-select.is-valid { - border-color: #00833E; -} -.was-validated .form-select:valid:not([multiple]):not([size]), .was-validated .form-select:valid:not([multiple])[size="1"], .form-select.is-valid:not([multiple]):not([size]), .form-select.is-valid:not([multiple])[size="1"] { - padding-right: 4.125rem; - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16'%3e%3cpath fill='none' stroke='%23555759' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' d='M2 5l6 6 6-6'/%3e%3c/svg%3e"), url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 8 8'%3e%3cpath fill='%2300833E' d='M2.3 6.73L.6 4.53c-.4-1.04.46-1.4 1.1-.8l1.1 1.4 3.4-3.8c.6-.63 1.6-.27 1.2.7l-4 4.6c-.43.5-.8.4-1.1.1z'/%3e%3c/svg%3e"); - background-position: right 0.75rem center, center right 2.25rem; - background-size: 16px 12px, calc(0.75em + 0.375rem) calc(0.75em + 0.375rem); -} -.was-validated .form-select:valid:focus, .form-select.is-valid:focus { - border-color: #00833E; - box-shadow: 0 0 0 0.25rem rgba(25, 135, 84, 0.25); -} - -.was-validated .form-check-input:valid, .form-check-input.is-valid { - border-color: #00833E; -} -.was-validated .form-check-input:valid:checked, .form-check-input.is-valid:checked { - background-color: #00833E; -} -.was-validated .form-check-input:valid:focus, .form-check-input.is-valid:focus { - box-shadow: 0 0 0 0.25rem rgba(25, 135, 84, 0.25); -} -.was-validated .form-check-input:valid ~ .form-check-label, .form-check-input.is-valid ~ .form-check-label { - color: #00833E; -} - -.form-check-inline .form-check-input ~ .valid-feedback { - margin-left: 0.5em; -} - -.was-validated .input-group .form-control:valid, .input-group .form-control.is-valid, -.was-validated .input-group .form-select:valid, -.input-group .form-select.is-valid { - z-index: 1; -} -.was-validated .input-group .form-control:valid:focus, .input-group .form-control.is-valid:focus, -.was-validated .input-group .form-select:valid:focus, -.input-group .form-select.is-valid:focus { - z-index: 3; -} - -.invalid-feedback { - display: none; - width: 100%; - margin-top: 0.25rem; - font-size: 0.875em; - color: #CF0A2C; -} - -.invalid-tooltip { - position: absolute; - top: 100%; - z-index: 5; - display: none; - max-width: 100%; - padding: 0.25rem 0.5rem; - margin-top: 0.1rem; - font-size: 0.875rem; - color: #fff; - background-color: rgba(220, 53, 69, 0.9); - border-radius: 0.25rem; -} - -.was-validated :invalid ~ .invalid-feedback, -.was-validated :invalid ~ .invalid-tooltip, -.is-invalid ~ .invalid-feedback, -.is-invalid ~ .invalid-tooltip { - display: block; -} - -.was-validated .form-control:invalid, .form-control.is-invalid { - border-color: #CF0A2C; - padding-right: calc(1.5em + 0.75rem); - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 12 12' width='12' height='12' fill='none' stroke='%23CF0A2C'%3e%3ccircle cx='6' cy='6' r='4.5'/%3e%3cpath stroke-linejoin='round' d='M5.8 3.6h.4L6 6.5z'/%3e%3ccircle cx='6' cy='8.2' r='.6' fill='%23CF0A2C' stroke='none'/%3e%3c/svg%3e"); - background-repeat: no-repeat; - background-position: right calc(0.375em + 0.1875rem) center; - background-size: calc(0.75em + 0.375rem) calc(0.75em + 0.375rem); -} -.was-validated .form-control:invalid:focus, .form-control.is-invalid:focus { - border-color: #CF0A2C; - box-shadow: 0 0 0 0.25rem rgba(220, 53, 69, 0.25); -} - -.was-validated textarea.form-control:invalid, textarea.form-control.is-invalid { - padding-right: calc(1.5em + 0.75rem); - background-position: top calc(0.375em + 0.1875rem) right calc(0.375em + 0.1875rem); -} - -.was-validated .form-select:invalid, .form-select.is-invalid { - border-color: #CF0A2C; -} -.was-validated .form-select:invalid:not([multiple]):not([size]), .was-validated .form-select:invalid:not([multiple])[size="1"], .form-select.is-invalid:not([multiple]):not([size]), .form-select.is-invalid:not([multiple])[size="1"] { - padding-right: 4.125rem; - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16'%3e%3cpath fill='none' stroke='%23555759' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' d='M2 5l6 6 6-6'/%3e%3c/svg%3e"), url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 12 12' width='12' height='12' fill='none' stroke='%23CF0A2C'%3e%3ccircle cx='6' cy='6' r='4.5'/%3e%3cpath stroke-linejoin='round' d='M5.8 3.6h.4L6 6.5z'/%3e%3ccircle cx='6' cy='8.2' r='.6' fill='%23CF0A2C' stroke='none'/%3e%3c/svg%3e"); - background-position: right 0.75rem center, center right 2.25rem; - background-size: 16px 12px, calc(0.75em + 0.375rem) calc(0.75em + 0.375rem); -} -.was-validated .form-select:invalid:focus, .form-select.is-invalid:focus { - border-color: #CF0A2C; - box-shadow: 0 0 0 0.25rem rgba(220, 53, 69, 0.25); -} - -.was-validated .form-check-input:invalid, .form-check-input.is-invalid { - border-color: #CF0A2C; -} -.was-validated .form-check-input:invalid:checked, .form-check-input.is-invalid:checked { - background-color: #CF0A2C; -} -.was-validated .form-check-input:invalid:focus, .form-check-input.is-invalid:focus { - box-shadow: 0 0 0 0.25rem rgba(220, 53, 69, 0.25); -} -.was-validated .form-check-input:invalid ~ .form-check-label, .form-check-input.is-invalid ~ .form-check-label { - color: #CF0A2C; -} - -.form-check-inline .form-check-input ~ .invalid-feedback { - margin-left: 0.5em; -} - -.was-validated .input-group .form-control:invalid, .input-group .form-control.is-invalid, -.was-validated .input-group .form-select:invalid, -.input-group .form-select.is-invalid { - z-index: 2; -} -.was-validated .input-group .form-control:invalid:focus, .input-group .form-control.is-invalid:focus, -.was-validated .input-group .form-select:invalid:focus, -.input-group .form-select.is-invalid:focus { - z-index: 3; -} - -.btn { - display: inline-block; - font-weight: 400; - line-height: 1.5; - color: #000000; - text-align: center; - text-decoration: none; - vertical-align: middle; - cursor: pointer; - -webkit-user-select: none; - -moz-user-select: none; - -ms-user-select: none; - user-select: none; - background-color: transparent; - border: 1px solid transparent; - padding: 0.375rem 0.75rem; - font-size: 1rem; - border-radius: 0.25rem; - transition: color 0.15s ease-in-out, background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out; -} -@media (prefers-reduced-motion: reduce) { - .btn { - transition: none; - } -} -.btn:hover { - color: #000000; -} -.btn-check:focus + .btn, .btn:focus { - outline: 0; - box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25); -} -.btn:disabled, .btn.disabled, fieldset:disabled .btn { - pointer-events: none; - opacity: 0.65; -} - -.btn-primary { - color: #fff; - background-color: #40B4E5; - border-color: #40B4E5; -} -.btn-primary:hover { - color: #fff; - background-color: #0b5ed7; - border-color: #0a58ca; -} -.btn-check:focus + .btn-primary, .btn-primary:focus { - color: #fff; - background-color: #0b5ed7; - border-color: #0a58ca; - box-shadow: 0 0 0 0.25rem rgba(49, 132, 253, 0.5); -} -.btn-check:checked + .btn-primary, .btn-check:active + .btn-primary, .btn-primary:active, .btn-primary.active, .show > .btn-primary.dropdown-toggle { - color: #fff; - background-color: #0a58ca; - border-color: #0a53be; -} -.btn-check:checked + .btn-primary:focus, .btn-check:active + .btn-primary:focus, .btn-primary:active:focus, .btn-primary.active:focus, .show > .btn-primary.dropdown-toggle:focus { - box-shadow: 0 0 0 0.25rem rgba(49, 132, 253, 0.5); -} -.btn-primary:disabled, .btn-primary.disabled { - color: #fff; - background-color: #40B4E5; - border-color: #40B4E5; -} - -.btn-secondary { - color: #fff; - background-color: #8A8A8D; - border-color: #8A8A8D; -} -.btn-secondary:hover { - color: #fff; - background-color: #5c636a; - border-color: #565e64; -} -.btn-check:focus + .btn-secondary, .btn-secondary:focus { - color: #fff; - background-color: #5c636a; - border-color: #565e64; - box-shadow: 0 0 0 0.25rem rgba(130, 138, 145, 0.5); -} -.btn-check:checked + .btn-secondary, .btn-check:active + .btn-secondary, .btn-secondary:active, .btn-secondary.active, .show > .btn-secondary.dropdown-toggle { - color: #fff; - background-color: #565e64; - border-color: #51585e; -} -.btn-check:checked + .btn-secondary:focus, .btn-check:active + .btn-secondary:focus, .btn-secondary:active:focus, .btn-secondary.active:focus, .show > .btn-secondary.dropdown-toggle:focus { - box-shadow: 0 0 0 0.25rem rgba(130, 138, 145, 0.5); -} -.btn-secondary:disabled, .btn-secondary.disabled { - color: #fff; - background-color: #8A8A8D; - border-color: #8A8A8D; -} - -.btn-success { - color: #fff; - background-color: #00833E; - border-color: #00833E; -} -.btn-success:hover { - color: #fff; - background-color: #157347; - border-color: #146c43; -} -.btn-check:focus + .btn-success, .btn-success:focus { - color: #fff; - background-color: #157347; - border-color: #146c43; - box-shadow: 0 0 0 0.25rem rgba(60, 153, 110, 0.5); -} -.btn-check:checked + .btn-success, .btn-check:active + .btn-success, .btn-success:active, .btn-success.active, .show > .btn-success.dropdown-toggle { - color: #fff; - background-color: #146c43; - border-color: #13653f; -} -.btn-check:checked + .btn-success:focus, .btn-check:active + .btn-success:focus, .btn-success:active:focus, .btn-success.active:focus, .show > .btn-success.dropdown-toggle:focus { - box-shadow: 0 0 0 0.25rem rgba(60, 153, 110, 0.5); -} -.btn-success:disabled, .btn-success.disabled { - color: #fff; - background-color: #00833E; - border-color: #00833E; -} - -.btn-info { - color: #000; - background-color: #40B4E5; - border-color: #40B4E5; -} -.btn-info:hover { - color: #000; - background-color: #31d2f2; - border-color: #25cff2; -} -.btn-check:focus + .btn-info, .btn-info:focus { - color: #000; - background-color: #31d2f2; - border-color: #25cff2; - box-shadow: 0 0 0 0.25rem rgba(11, 172, 204, 0.5); -} -.btn-check:checked + .btn-info, .btn-check:active + .btn-info, .btn-info:active, .btn-info.active, .show > .btn-info.dropdown-toggle { - color: #000; - background-color: #3dd5f3; - border-color: #25cff2; -} -.btn-check:checked + .btn-info:focus, .btn-check:active + .btn-info:focus, .btn-info:active:focus, .btn-info.active:focus, .show > .btn-info.dropdown-toggle:focus { - box-shadow: 0 0 0 0.25rem rgba(11, 172, 204, 0.5); -} -.btn-info:disabled, .btn-info.disabled { - color: #000; - background-color: #40B4E5; - border-color: #40B4E5; -} - -.btn-warning { - color: #000; - background-color: #00833E; - border-color: #00833E; -} -.btn-warning:hover { - color: #000; - background-color: #ffca2c; - border-color: #ffc720; -} -.btn-check:focus + .btn-warning, .btn-warning:focus { - color: #000; - background-color: #ffca2c; - border-color: #ffc720; - box-shadow: 0 0 0 0.25rem rgba(217, 164, 6, 0.5); -} -.btn-check:checked + .btn-warning, .btn-check:active + .btn-warning, .btn-warning:active, .btn-warning.active, .show > .btn-warning.dropdown-toggle { - color: #000; - background-color: #ffcd39; - border-color: #ffc720; -} -.btn-check:checked + .btn-warning:focus, .btn-check:active + .btn-warning:focus, .btn-warning:active:focus, .btn-warning.active:focus, .show > .btn-warning.dropdown-toggle:focus { - box-shadow: 0 0 0 0.25rem rgba(217, 164, 6, 0.5); -} -.btn-warning:disabled, .btn-warning.disabled { - color: #000; - background-color: #00833E; - border-color: #00833E; -} - -.btn-danger { - color: #fff; - background-color: #CF0A2C; - border-color: #CF0A2C; -} -.btn-danger:hover { - color: #fff; - background-color: #bb2d3b; - border-color: #b02a37; -} -.btn-check:focus + .btn-danger, .btn-danger:focus { - color: #fff; - background-color: #bb2d3b; - border-color: #b02a37; - box-shadow: 0 0 0 0.25rem rgba(225, 83, 97, 0.5); -} -.btn-check:checked + .btn-danger, .btn-check:active + .btn-danger, .btn-danger:active, .btn-danger.active, .show > .btn-danger.dropdown-toggle { - color: #fff; - background-color: #b02a37; - border-color: #a52834; -} -.btn-check:checked + .btn-danger:focus, .btn-check:active + .btn-danger:focus, .btn-danger:active:focus, .btn-danger.active:focus, .show > .btn-danger.dropdown-toggle:focus { - box-shadow: 0 0 0 0.25rem rgba(225, 83, 97, 0.5); -} -.btn-danger:disabled, .btn-danger.disabled { - color: #fff; - background-color: #CF0A2C; - border-color: #CF0A2C; -} - -.btn-light { - color: #000; - background-color: #ffffff; - border-color: #ffffff; -} -.btn-light:hover { - color: #000; - background-color: #f9fafb; - border-color: #f9fafb; -} -.btn-check:focus + .btn-light, .btn-light:focus { - color: #000; - background-color: #f9fafb; - border-color: #f9fafb; - box-shadow: 0 0 0 0.25rem rgba(211, 212, 213, 0.5); -} -.btn-check:checked + .btn-light, .btn-check:active + .btn-light, .btn-light:active, .btn-light.active, .show > .btn-light.dropdown-toggle { - color: #000; - background-color: #f9fafb; - border-color: #f9fafb; -} -.btn-check:checked + .btn-light:focus, .btn-check:active + .btn-light:focus, .btn-light:active:focus, .btn-light.active:focus, .show > .btn-light.dropdown-toggle:focus { - box-shadow: 0 0 0 0.25rem rgba(211, 212, 213, 0.5); -} -.btn-light:disabled, .btn-light.disabled { - color: #000; - background-color: #ffffff; - border-color: #ffffff; -} - -.btn-dark { - color: #fff; - background-color: #000000; - border-color: #000000; -} -.btn-dark:hover { - color: #fff; - background-color: #1c1f23; - border-color: #1a1e21; -} -.btn-check:focus + .btn-dark, .btn-dark:focus { - color: #fff; - background-color: #1c1f23; - border-color: #1a1e21; - box-shadow: 0 0 0 0.25rem rgba(66, 70, 73, 0.5); -} -.btn-check:checked + .btn-dark, .btn-check:active + .btn-dark, .btn-dark:active, .btn-dark.active, .show > .btn-dark.dropdown-toggle { - color: #fff; - background-color: #1a1e21; - border-color: #191c1f; -} -.btn-check:checked + .btn-dark:focus, .btn-check:active + .btn-dark:focus, .btn-dark:active:focus, .btn-dark.active:focus, .show > .btn-dark.dropdown-toggle:focus { - box-shadow: 0 0 0 0.25rem rgba(66, 70, 73, 0.5); -} -.btn-dark:disabled, .btn-dark.disabled { - color: #fff; - background-color: #000000; - border-color: #000000; -} - -.btn-outline-primary { - color: #40B4E5; - border-color: #40B4E5; -} -.btn-outline-primary:hover { - color: #fff; - background-color: #40B4E5; - border-color: #40B4E5; -} -.btn-check:focus + .btn-outline-primary, .btn-outline-primary:focus { - box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.5); -} -.btn-check:checked + .btn-outline-primary, .btn-check:active + .btn-outline-primary, .btn-outline-primary:active, .btn-outline-primary.active, .btn-outline-primary.dropdown-toggle.show { - color: #fff; - background-color: #40B4E5; - border-color: #40B4E5; -} -.btn-check:checked + .btn-outline-primary:focus, .btn-check:active + .btn-outline-primary:focus, .btn-outline-primary:active:focus, .btn-outline-primary.active:focus, .btn-outline-primary.dropdown-toggle.show:focus { - box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.5); -} -.btn-outline-primary:disabled, .btn-outline-primary.disabled { - color: #40B4E5; - background-color: transparent; -} - -.btn-outline-secondary { - color: #8A8A8D; - border-color: #8A8A8D; -} -.btn-outline-secondary:hover { - color: #fff; - background-color: #8A8A8D; - border-color: #8A8A8D; -} -.btn-check:focus + .btn-outline-secondary, .btn-outline-secondary:focus { - box-shadow: 0 0 0 0.25rem rgba(108, 117, 125, 0.5); -} -.btn-check:checked + .btn-outline-secondary, .btn-check:active + .btn-outline-secondary, .btn-outline-secondary:active, .btn-outline-secondary.active, .btn-outline-secondary.dropdown-toggle.show { - color: #fff; - background-color: #8A8A8D; - border-color: #8A8A8D; -} -.btn-check:checked + .btn-outline-secondary:focus, .btn-check:active + .btn-outline-secondary:focus, .btn-outline-secondary:active:focus, .btn-outline-secondary.active:focus, .btn-outline-secondary.dropdown-toggle.show:focus { - box-shadow: 0 0 0 0.25rem rgba(108, 117, 125, 0.5); -} -.btn-outline-secondary:disabled, .btn-outline-secondary.disabled { - color: #8A8A8D; - background-color: transparent; -} - -.btn-outline-success { - color: #00833E; - border-color: #00833E; -} -.btn-outline-success:hover { - color: #fff; - background-color: #00833E; - border-color: #00833E; -} -.btn-check:focus + .btn-outline-success, .btn-outline-success:focus { - box-shadow: 0 0 0 0.25rem rgba(25, 135, 84, 0.5); -} -.btn-check:checked + .btn-outline-success, .btn-check:active + .btn-outline-success, .btn-outline-success:active, .btn-outline-success.active, .btn-outline-success.dropdown-toggle.show { - color: #fff; - background-color: #00833E; - border-color: #00833E; -} -.btn-check:checked + .btn-outline-success:focus, .btn-check:active + .btn-outline-success:focus, .btn-outline-success:active:focus, .btn-outline-success.active:focus, .btn-outline-success.dropdown-toggle.show:focus { - box-shadow: 0 0 0 0.25rem rgba(25, 135, 84, 0.5); -} -.btn-outline-success:disabled, .btn-outline-success.disabled { - color: #00833E; - background-color: transparent; -} - -.btn-outline-info { - color: #40B4E5; - border-color: #40B4E5; -} -.btn-outline-info:hover { - color: #000; - background-color: #40B4E5; - border-color: #40B4E5; -} -.btn-check:focus + .btn-outline-info, .btn-outline-info:focus { - box-shadow: 0 0 0 0.25rem rgba(13, 202, 240, 0.5); -} -.btn-check:checked + .btn-outline-info, .btn-check:active + .btn-outline-info, .btn-outline-info:active, .btn-outline-info.active, .btn-outline-info.dropdown-toggle.show { - color: #000; - background-color: #40B4E5; - border-color: #40B4E5; -} -.btn-check:checked + .btn-outline-info:focus, .btn-check:active + .btn-outline-info:focus, .btn-outline-info:active:focus, .btn-outline-info.active:focus, .btn-outline-info.dropdown-toggle.show:focus { - box-shadow: 0 0 0 0.25rem rgba(13, 202, 240, 0.5); -} -.btn-outline-info:disabled, .btn-outline-info.disabled { - color: #40B4E5; - background-color: transparent; -} - -.btn-outline-warning { - color: #00833E; - border-color: #00833E; -} -.btn-outline-warning:hover { - color: #000; - background-color: #00833E; - border-color: #00833E; -} -.btn-check:focus + .btn-outline-warning, .btn-outline-warning:focus { - box-shadow: 0 0 0 0.25rem rgba(255, 193, 7, 0.5); -} -.btn-check:checked + .btn-outline-warning, .btn-check:active + .btn-outline-warning, .btn-outline-warning:active, .btn-outline-warning.active, .btn-outline-warning.dropdown-toggle.show { - color: #000; - background-color: #00833E; - border-color: #00833E; -} -.btn-check:checked + .btn-outline-warning:focus, .btn-check:active + .btn-outline-warning:focus, .btn-outline-warning:active:focus, .btn-outline-warning.active:focus, .btn-outline-warning.dropdown-toggle.show:focus { - box-shadow: 0 0 0 0.25rem rgba(255, 193, 7, 0.5); -} -.btn-outline-warning:disabled, .btn-outline-warning.disabled { - color: #00833E; - background-color: transparent; -} - -.btn-outline-danger { - color: #CF0A2C; - border-color: #CF0A2C; -} -.btn-outline-danger:hover { - color: #fff; - background-color: #CF0A2C; - border-color: #CF0A2C; -} -.btn-check:focus + .btn-outline-danger, .btn-outline-danger:focus { - box-shadow: 0 0 0 0.25rem rgba(220, 53, 69, 0.5); -} -.btn-check:checked + .btn-outline-danger, .btn-check:active + .btn-outline-danger, .btn-outline-danger:active, .btn-outline-danger.active, .btn-outline-danger.dropdown-toggle.show { - color: #fff; - background-color: #CF0A2C; - border-color: #CF0A2C; -} -.btn-check:checked + .btn-outline-danger:focus, .btn-check:active + .btn-outline-danger:focus, .btn-outline-danger:active:focus, .btn-outline-danger.active:focus, .btn-outline-danger.dropdown-toggle.show:focus { - box-shadow: 0 0 0 0.25rem rgba(220, 53, 69, 0.5); -} -.btn-outline-danger:disabled, .btn-outline-danger.disabled { - color: #CF0A2C; - background-color: transparent; -} - -.btn-outline-light { - color: #ffffff; - border-color: #ffffff; -} -.btn-outline-light:hover { - color: #000; - background-color: #ffffff; - border-color: #ffffff; -} -.btn-check:focus + .btn-outline-light, .btn-outline-light:focus { - box-shadow: 0 0 0 0.25rem rgba(248, 249, 250, 0.5); -} -.btn-check:checked + .btn-outline-light, .btn-check:active + .btn-outline-light, .btn-outline-light:active, .btn-outline-light.active, .btn-outline-light.dropdown-toggle.show { - color: #000; - background-color: #ffffff; - border-color: #ffffff; -} -.btn-check:checked + .btn-outline-light:focus, .btn-check:active + .btn-outline-light:focus, .btn-outline-light:active:focus, .btn-outline-light.active:focus, .btn-outline-light.dropdown-toggle.show:focus { - box-shadow: 0 0 0 0.25rem rgba(248, 249, 250, 0.5); -} -.btn-outline-light:disabled, .btn-outline-light.disabled { - color: #ffffff; - background-color: transparent; -} - -.btn-outline-dark { - color: #000000; - border-color: #000000; -} -.btn-outline-dark:hover { - color: #fff; - background-color: #000000; - border-color: #000000; -} -.btn-check:focus + .btn-outline-dark, .btn-outline-dark:focus { - box-shadow: 0 0 0 0.25rem rgba(33, 37, 41, 0.5); -} -.btn-check:checked + .btn-outline-dark, .btn-check:active + .btn-outline-dark, .btn-outline-dark:active, .btn-outline-dark.active, .btn-outline-dark.dropdown-toggle.show { - color: #fff; - background-color: #000000; - border-color: #000000; -} -.btn-check:checked + .btn-outline-dark:focus, .btn-check:active + .btn-outline-dark:focus, .btn-outline-dark:active:focus, .btn-outline-dark.active:focus, .btn-outline-dark.dropdown-toggle.show:focus { - box-shadow: 0 0 0 0.25rem rgba(33, 37, 41, 0.5); -} -.btn-outline-dark:disabled, .btn-outline-dark.disabled { - color: #000000; - background-color: transparent; -} - -.btn-link { - font-weight: 400; - color: #40B4E5; - text-decoration: underline; -} -.btn-link:hover { - color: #0a58ca; -} -.btn-link:disabled, .btn-link.disabled { - color: #8A8A8D; -} - -.btn-lg, .btn-group-lg > .btn { - padding: 0.5rem 1rem; - font-size: 1.25rem; - border-radius: 0.3rem; -} - -.btn-sm, .btn-group-sm > .btn { - padding: 0.25rem 0.5rem; - font-size: 0.875rem; - border-radius: 0.2rem; -} - -.fade { - transition: opacity 0.15s linear; -} -@media (prefers-reduced-motion: reduce) { - .fade { - transition: none; - } -} -.fade:not(.show) { - opacity: 0; -} - -.collapse:not(.show) { - display: none; -} - -.collapsing { - height: 0; - overflow: hidden; - transition: height 0.35s ease; -} -@media (prefers-reduced-motion: reduce) { - .collapsing { - transition: none; - } -} - -.dropup, -.dropend, -.dropdown, -.dropstart { - position: relative; -} - -.dropdown-toggle { - white-space: nowrap; -} -.dropdown-toggle::after { - display: inline-block; - margin-left: 0.255em; - vertical-align: 0.255em; - content: ""; - border-top: 0.3em solid; - border-right: 0.3em solid transparent; - border-bottom: 0; - border-left: 0.3em solid transparent; -} -.dropdown-toggle:empty::after { - margin-left: 0; -} - -.dropdown-menu { - position: absolute; - z-index: 1000; - display: none; - min-width: 10rem; - padding: 0.5rem 0; - margin: 0; - font-size: 1rem; - color: #fff; - text-align: left; - list-style: none; - background-color: #003A70; - background-clip: padding-box; - border: 1px solid rgba(0, 0, 0, 0.15); - border-radius: 0.25rem; -} -.dropdown-menu[data-bs-popper] { - top: 100%; - left: 0; - margin-top: 0.125rem; -} - -.dropdown-menu-start { - --position: start; -} -.dropdown-menu-start[data-bs-popper] { - right: auto; - left: 0; -} - -.dropdown-menu-end { - --position: end; -} -.dropdown-menu-end[data-bs-popper] { - right: 0; - left: auto; -} - -@media (min-width: 576px) { - .dropdown-menu-sm-start { - --position: start; - } - .dropdown-menu-sm-start[data-bs-popper] { - right: auto; - left: 0; - } - - .dropdown-menu-sm-end { - --position: end; - } - .dropdown-menu-sm-end[data-bs-popper] { - right: 0; - left: auto; - } -} -@media (min-width: 768px) { - .dropdown-menu-md-start { - --position: start; - } - .dropdown-menu-md-start[data-bs-popper] { - right: auto; - left: 0; - } - - .dropdown-menu-md-end { - --position: end; - } - .dropdown-menu-md-end[data-bs-popper] { - right: 0; - left: auto; - } -} -@media (min-width: 992px) { - .dropdown-menu-lg-start { - --position: start; - } - .dropdown-menu-lg-start[data-bs-popper] { - right: auto; - left: 0; - } - - .dropdown-menu-lg-end { - --position: end; - } - .dropdown-menu-lg-end[data-bs-popper] { - right: 0; - left: auto; - } -} -@media (min-width: 1200px) { - .dropdown-menu-xl-start { - --position: start; - } - .dropdown-menu-xl-start[data-bs-popper] { - right: auto; - left: 0; - } - - .dropdown-menu-xl-end { - --position: end; - } - .dropdown-menu-xl-end[data-bs-popper] { - right: 0; - left: auto; - } -} -@media (min-width: 1400px) { - .dropdown-menu-xxl-start { - --position: start; - } - .dropdown-menu-xxl-start[data-bs-popper] { - right: auto; - left: 0; - } - - .dropdown-menu-xxl-end { - --position: end; - } - .dropdown-menu-xxl-end[data-bs-popper] { - right: 0; - left: auto; - } -} -.dropup .dropdown-menu[data-bs-popper] { - top: auto; - bottom: 100%; - margin-top: 0; - margin-bottom: 0.125rem; -} -.dropup .dropdown-toggle::after { - display: inline-block; - margin-left: 0.255em; - vertical-align: 0.255em; - content: ""; - border-top: 0; - border-right: 0.3em solid transparent; - border-bottom: 0.3em solid; - border-left: 0.3em solid transparent; -} -.dropup .dropdown-toggle:empty::after { - margin-left: 0; -} - -.dropend .dropdown-menu[data-bs-popper] { - top: 0; - right: auto; - left: 100%; - margin-top: 0; - margin-left: 0.125rem; -} -.dropend .dropdown-toggle::after { - display: inline-block; - margin-left: 0.255em; - vertical-align: 0.255em; - content: ""; - border-top: 0.3em solid transparent; - border-right: 0; - border-bottom: 0.3em solid transparent; - border-left: 0.3em solid; -} -.dropend .dropdown-toggle:empty::after { - margin-left: 0; -} -.dropend .dropdown-toggle::after { - vertical-align: 0; -} - -.dropstart .dropdown-menu[data-bs-popper] { - top: 0; - right: 100%; - left: auto; - margin-top: 0; - margin-right: 0.125rem; -} -.dropstart .dropdown-toggle::after { - display: inline-block; - margin-left: 0.255em; - vertical-align: 0.255em; - content: ""; -} -.dropstart .dropdown-toggle::after { - display: none; -} -.dropstart .dropdown-toggle::before { - display: inline-block; - margin-right: 0.255em; - vertical-align: 0.255em; - content: ""; - border-top: 0.3em solid transparent; - border-right: 0.3em solid; - border-bottom: 0.3em solid transparent; -} -.dropstart .dropdown-toggle:empty::after { - margin-left: 0; -} -.dropstart .dropdown-toggle::before { - vertical-align: 0; -} - -.dropdown-divider { - height: 0; - margin: 0.5rem 0; - overflow: hidden; - border-top: 1px solid rgba(0, 0, 0, 0.15); -} - -.dropdown-item { - display: block; - width: 100%; - padding: 0.25rem 1rem; - clear: both; - font-weight: 400; - color: #fff; - text-align: inherit; - text-decoration: none; - white-space: nowrap; - background-color: transparent; - border: 0; -} -.dropdown-item:hover, .dropdown-item:focus { - color: #003A70; - background-color: #e9ecef; -} -.dropdown-item.active, .dropdown-item:active { - color: #fff; - text-decoration: none; - background-color: #003A70; -} -.dropdown-item.disabled, .dropdown-item:disabled { - color: #adb5bd; - pointer-events: none; - background-color: transparent; -} - -.dropdown-menu.show { - display: block; -} - -.dropdown-header { - display: block; - padding: 0.5rem 1rem; - margin-bottom: 0; - font-size: 0.875rem; - color: #8A8A8D; - white-space: nowrap; -} - -.dropdown-item-text { - display: block; - padding: 0.25rem 1rem; - color: #000000; -} - -.dropdown-menu-dark { - color: #dee2e6; - background-color: #555759; - border-color: rgba(0, 0, 0, 0.15); -} -.dropdown-menu-dark .dropdown-item { - color: #dee2e6; -} -.dropdown-menu-dark .dropdown-item:hover, .dropdown-menu-dark .dropdown-item:focus { - color: #fff; - background-color: rgba(255, 255, 255, 0.15); -} -.dropdown-menu-dark .dropdown-item.active, .dropdown-menu-dark .dropdown-item:active { - color: #fff; - background-color: #40B4E5; -} -.dropdown-menu-dark .dropdown-item.disabled, .dropdown-menu-dark .dropdown-item:disabled { - color: #adb5bd; -} -.dropdown-menu-dark .dropdown-divider { - border-color: rgba(0, 0, 0, 0.15); -} -.dropdown-menu-dark .dropdown-item-text { - color: #dee2e6; -} -.dropdown-menu-dark .dropdown-header { - color: #adb5bd; -} - -.btn-group, -.btn-group-vertical { - position: relative; - display: inline-flex; - vertical-align: middle; -} -.btn-group > .btn, -.btn-group-vertical > .btn { - position: relative; - flex: 1 1 auto; -} -.btn-group > .btn-check:checked + .btn, -.btn-group > .btn-check:focus + .btn, -.btn-group > .btn:hover, -.btn-group > .btn:focus, -.btn-group > .btn:active, -.btn-group > .btn.active, -.btn-group-vertical > .btn-check:checked + .btn, -.btn-group-vertical > .btn-check:focus + .btn, -.btn-group-vertical > .btn:hover, -.btn-group-vertical > .btn:focus, -.btn-group-vertical > .btn:active, -.btn-group-vertical > .btn.active { - z-index: 1; -} - -.btn-toolbar { - display: flex; - flex-wrap: wrap; - justify-content: flex-start; -} -.btn-toolbar .input-group { - width: auto; -} - -.btn-group > .btn:not(:first-child), -.btn-group > .btn-group:not(:first-child) { - margin-left: -1px; -} -.btn-group > .btn:not(:last-child):not(.dropdown-toggle), -.btn-group > .btn-group:not(:last-child) > .btn { - border-top-right-radius: 0; - border-bottom-right-radius: 0; -} -.btn-group > .btn:nth-child(n+3), -.btn-group > :not(.btn-check) + .btn, -.btn-group > .btn-group:not(:first-child) > .btn { - border-top-left-radius: 0; - border-bottom-left-radius: 0; -} - -.dropdown-toggle-split { - padding-right: 0.5625rem; - padding-left: 0.5625rem; -} -.dropdown-toggle-split::after, .dropup .dropdown-toggle-split::after, .dropend .dropdown-toggle-split::after { - margin-left: 0; -} -.dropstart .dropdown-toggle-split::before { - margin-right: 0; -} - -.btn-sm + .dropdown-toggle-split, .btn-group-sm > .btn + .dropdown-toggle-split { - padding-right: 0.375rem; - padding-left: 0.375rem; -} - -.btn-lg + .dropdown-toggle-split, .btn-group-lg > .btn + .dropdown-toggle-split { - padding-right: 0.75rem; - padding-left: 0.75rem; -} - -.btn-group-vertical { - flex-direction: column; - align-items: flex-start; - justify-content: center; -} -.btn-group-vertical > .btn, -.btn-group-vertical > .btn-group { - width: 100%; -} -.btn-group-vertical > .btn:not(:first-child), -.btn-group-vertical > .btn-group:not(:first-child) { - margin-top: -1px; -} -.btn-group-vertical > .btn:not(:last-child):not(.dropdown-toggle), -.btn-group-vertical > .btn-group:not(:last-child) > .btn { - border-bottom-right-radius: 0; - border-bottom-left-radius: 0; -} -.btn-group-vertical > .btn ~ .btn, -.btn-group-vertical > .btn-group:not(:first-child) > .btn { - border-top-left-radius: 0; - border-top-right-radius: 0; -} - -/* Color for title link */ -.title-link { - color: #fff; -} -.title-link:hover { - color: #40B4E5; -} - -.nav { - display: flex; - flex-wrap: wrap; - padding-left: 0; - margin-bottom: 0; - list-style: none; -} - -.nav-link { - display: block; - padding: 0.5rem 1rem; - color: #40B4E5; - text-decoration: none; - transition: color 0.15s ease-in-out, background-color 0.15s ease-in-out, border-color 0.15s ease-in-out; -} -@media (prefers-reduced-motion: reduce) { - .nav-link { - transition: none; - } -} -.nav-link:hover, .nav-link:focus { - color: #0a58ca; -} -.nav-link.disabled { - color: #8A8A8D; - pointer-events: none; - cursor: default; -} - -/* Top CSAFE logo */ -.logo-image{ - width: 225px; - height: 90px; - margin-top: 5px; - margin-left: 5px; - margin-bottom: 5px; - margin-right: 5px; -} - -/* footer logos */ -.foot-logo{ - width: auto; - height: auto; - margin-top: 10px; - margin-bottom: 10px; - margin-left: 20px; - margin-right: 20px; -} - -/* hex images */ -.hex-image{ - max-width: 100%; - height: auto; -} - - - -.nav-tabs { - border-bottom: 1px solid #dee2e6; -} -.nav-tabs .nav-link { - margin-bottom: -1px; - background: none; - border: 1px solid transparent; - border-top-left-radius: 0.25rem; - border-top-right-radius: 0.25rem; -} -.nav-tabs .nav-link:hover, .nav-tabs .nav-link:focus { - border-color: #e9ecef #e9ecef #dee2e6; - isolation: isolate; -} -.nav-tabs .nav-link.disabled { - color: #8A8A8D; - background-color: transparent; - border-color: transparent; -} -.nav-tabs .nav-link.active, -.nav-tabs .nav-item.show .nav-link { - color: #495057; - background-color: #fff; - border-color: #dee2e6 #dee2e6 #fff; -} -.nav-tabs .dropdown-menu { - margin-top: -1px; - border-top-left-radius: 0; - border-top-right-radius: 0; -} - -.nav-pills .nav-link { - background: none; - border: 0; - border-radius: 0.25rem; -} -.nav-pills .nav-link.active, -.nav-pills .show > .nav-link { - color: #fff; - background-color: #40B4E5; -} - -.nav-fill > .nav-link, -.nav-fill .nav-item { - flex: 1 1 auto; - text-align: center; -} - -.nav-justified > .nav-link, -.nav-justified .nav-item { - flex-basis: 0; - flex-grow: 1; - text-align: center; -} - -.nav-fill .nav-item .nav-link, -.nav-justified .nav-item .nav-link { - width: 100%; -} - -.tab-content > .tab-pane { - display: none; -} -.tab-content > .active { - display: block; -} - -/* Added for homepage formatting */ -.bands { - position: relative; - display: flex; - flex-wrap: wrap; - align-items: center; - justify-content: space-between; - padding-top: 0.5rem; - padding-bottom: 0.5rem; -} - -.foot { - position: relative; - display: flex; - flex-wrap: wrap; - align-items: center; - justify-content: space-between; - padding-top: 0.5rem; - padding-bottom: 0.5rem; -} - - -.navbar { - position: relative; - display: flex; - flex-wrap: wrap; - align-items: center; - justify-content: space-between; - padding-top: 0.5rem; - padding-bottom: 0.5rem; -} -.navbar > .container, -.navbar > .container-fluid, -.navbar > .container-sm, -.navbar > .container-md, -.navbar > .container-lg, -.navbar > .container-xl, -.navbar > .container-xxl { - display: flex; - flex-wrap: inherit; - align-items: center; - justify-content: space-between; -} -.navbar-brand { - padding-top: 0.3125rem; - padding-bottom: 0.3125rem; - margin-right: 1rem; - font-size: 1.25rem; - text-decoration: none; - white-space: nowrap; -} -.navbar-nav { - display: flex; - flex-direction: column; - padding-left: 0; - margin-bottom: 0; - list-style: none; -} -.navbar-nav .nav-link { - padding-right: 0; - padding-left: 0; -} -.navbar-nav .dropdown-menu { - position: static; -} - -.navbar-text { - padding-top: 0.5rem; - padding-bottom: 0.5rem; -} - -.navbar-collapse { - flex-basis: 100%; - flex-grow: 1; - align-items: center; -} - -.navbar-toggler { - padding: 0.25rem 0.75rem; - font-size: 1.25rem; - line-height: 1; - background-color: transparent; - border: 1px solid transparent; - border-radius: 0.25rem; - transition: box-shadow 0.15s ease-in-out; -} -@media (prefers-reduced-motion: reduce) { - .navbar-toggler { - transition: none; - } -} -.navbar-toggler:hover { - text-decoration: none; -} -.navbar-toggler:focus { - text-decoration: none; - outline: 0; - box-shadow: 0 0 0 0.25rem; -} - -.navbar-toggler-icon { - display: inline-block; - width: 1.5em; - height: 1.5em; - vertical-align: middle; - background-repeat: no-repeat; - background-position: center; - background-size: 100%; -} - -.navbar-nav-scroll { - max-height: var(--scroll-height, 75vh); - overflow-y: auto; -} - -@media (min-width: 576px) { - .navbar-expand-sm { - flex-wrap: nowrap; - justify-content: flex-start; - } - .navbar-expand-sm .navbar-nav { - flex-direction: row; - } - .navbar-expand-sm .navbar-nav .dropdown-menu { - position: absolute; - } - .navbar-expand-sm .navbar-nav .nav-link { - padding-right: 0.5rem; - padding-left: 0.5rem; - } - .navbar-expand-sm .navbar-nav-scroll { - overflow: visible; - } - .navbar-expand-sm .navbar-collapse { - display: flex !important; - flex-basis: auto; - } - .navbar-expand-sm .navbar-toggler { - display: none; - } -} -@media (min-width: 768px) { - .navbar-expand-md { - flex-wrap: nowrap; - justify-content: flex-start; - } - .navbar-expand-md .navbar-nav { - flex-direction: row; - } - .navbar-expand-md .navbar-nav .dropdown-menu { - position: absolute; - } - .navbar-expand-md .navbar-nav .nav-link { - padding-right: 0.5rem; - padding-left: 0.5rem; - } - .navbar-expand-md .navbar-nav-scroll { - overflow: visible; - } - .navbar-expand-md .navbar-collapse { - display: flex !important; - flex-basis: auto; - } - .navbar-expand-md .navbar-toggler { - display: none; - } -} -@media (min-width: 992px) { - .navbar-expand-lg { - flex-wrap: nowrap; - justify-content: flex-start; - } - .navbar-expand-lg .navbar-nav { - flex-direction: row; - } - .navbar-expand-lg .navbar-nav .dropdown-menu { - position: absolute; - } - .navbar-expand-lg .navbar-nav .nav-link { - padding-right: 0.5rem; - padding-left: 0.5rem; - } - .navbar-expand-lg .navbar-nav-scroll { - overflow: visible; - } - .navbar-expand-lg .navbar-collapse { - display: flex !important; - flex-basis: auto; - } - .navbar-expand-lg .navbar-toggler { - display: none; - } -} -@media (min-width: 1200px) { - .navbar-expand-xl { - flex-wrap: nowrap; - justify-content: flex-start; - } - .navbar-expand-xl .navbar-nav { - flex-direction: row; - } - .navbar-expand-xl .navbar-nav .dropdown-menu { - position: absolute; - } - .navbar-expand-xl .navbar-nav .nav-link { - padding-right: 0.5rem; - padding-left: 0.5rem; - } - .navbar-expand-xl .navbar-nav-scroll { - overflow: visible; - } - .navbar-expand-xl .navbar-collapse { - display: flex !important; - flex-basis: auto; - } - .navbar-expand-xl .navbar-toggler { - display: none; - } -} -@media (min-width: 1400px) { - .navbar-expand-xxl { - flex-wrap: nowrap; - justify-content: flex-start; - } - .navbar-expand-xxl .navbar-nav { - flex-direction: row; - } - .navbar-expand-xxl .navbar-nav .dropdown-menu { - position: absolute; - } - .navbar-expand-xxl .navbar-nav .nav-link { - padding-right: 0.5rem; - padding-left: 0.5rem; - } - .navbar-expand-xxl .navbar-nav-scroll { - overflow: visible; - } - .navbar-expand-xxl .navbar-collapse { - display: flex !important; - flex-basis: auto; - } - .navbar-expand-xxl .navbar-toggler { - display: none; - } -} -.navbar-expand { - flex-wrap: nowrap; - justify-content: flex-start; -} -.navbar-expand .navbar-nav { - flex-direction: row; -} -.navbar-expand .navbar-nav .dropdown-menu { - position: absolute; -} -.navbar-expand .navbar-nav .nav-link { - padding-right: 0.5rem; - padding-left: 0.5rem; -} -.navbar-expand .navbar-nav-scroll { - overflow: visible; -} -.navbar-expand .navbar-collapse { - display: flex !important; - flex-basis: auto; -} -.navbar-expand .navbar-toggler { - display: none; -} - -.navbar-light .navbar-brand { - color: rgba(0, 255, 0, 0.9); -} -.navbar-light .navbar-brand:hover, .navbar-light .navbar-brand:focus { - color: rgba(0, 0, 255, 0.9); -} -.navbar-light .navbar-nav .nav-link { - color: rgba(255, 255, 255, 0.9); -} -.navbar-light .navbar-nav .nav-link:hover, .navbar-light .navbar-nav .nav-link:focus { - color: rgba(64, 180, 229, 0.7); -} -.navbar-light .navbar-nav .nav-link.disabled { - color: rgba(255, 0, 0, 0.3); -} -.navbar-light .navbar-nav .show > .nav-link, -.navbar-light .navbar-nav .nav-link.active { - color: rgba(0, 255, 0, 0.9); -} -.navbar-light .navbar-toggler { - color: rgba(0, 58, 112, 0.55); - border-color: rgba(0, 58, 112, 0.1); -} -.navbar-light .navbar-toggler-icon { - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgba%28255, 255, 255, 0.9%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e"); -} -.navbar-light .navbar-text { - color: rgba(0, 0, 0, 0.55); -} -.navbar-light .navbar-text a, -.navbar-light .navbar-text a:hover, -.navbar-light .navbar-text a:focus { - color: rgba(0, 0, 0, 0.9); -} - -.navbar-dark .navbar-brand { - color: #000; -} -.navbar-dark .navbar-brand:hover, .navbar-dark .navbar-brand:focus { - color: #000; -} -.navbar-dark .navbar-nav .nav-link { - color: rgba(255, 255, 255, 0.55); -} -.navbar-dark .navbar-nav .nav-link:hover, .navbar-dark .navbar-nav .nav-link:focus { - color: rgba(255, 255, 255, 0.75); -} -.navbar-dark .navbar-nav .nav-link.disabled { - color: rgba(255, 255, 255, 0.25); -} -.navbar-dark .navbar-nav .show > .nav-link, -.navbar-dark .navbar-nav .nav-link.active { - color: #fff; -} -.navbar-dark .navbar-toggler { - color: rgba(255, 255, 255, 0.55); - border-color: rgba(255, 255, 255, 0.1); -} -.navbar-dark .navbar-toggler-icon { - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgba%28255, 255, 255, 0.55%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e"); -} -.navbar-dark .navbar-text { - color: rgba(255, 255, 255, 0.55); -} -.navbar-dark .navbar-text a, -.navbar-dark .navbar-text a:hover, -.navbar-dark .navbar-text a:focus { - color: #fff; -} - -.card { - position: relative; - display: flex; - flex-direction: column; - min-width: 0; - word-wrap: break-word; - background-color: #fff; - background-clip: border-box; - border: 1px solid rgba(0, 0, 0, 0.125); - border-radius: 0.25rem; -} -.card > hr { - margin-right: 0; - margin-left: 0; -} -.card > .list-group { - border-top: inherit; - border-bottom: inherit; -} -.card > .list-group:first-child { - border-top-width: 0; - border-top-left-radius: calc(0.25rem - 1px); - border-top-right-radius: calc(0.25rem - 1px); -} -.card > .list-group:last-child { - border-bottom-width: 0; - border-bottom-right-radius: calc(0.25rem - 1px); - border-bottom-left-radius: calc(0.25rem - 1px); -} -.card > .card-header + .list-group, -.card > .list-group + .card-footer { - border-top: 0; -} - -.card-body { - flex: 1 1 auto; - padding: 1rem 1rem; -} - -.card-title { - margin-bottom: 0.5rem; -} - -.card-subtitle { - margin-top: -0.25rem; - margin-bottom: 0; -} - -.card-text:last-child { - margin-bottom: 0; -} - -.card-link:hover { - text-decoration: none; -} -.card-link + .card-link { - margin-left: 1rem; -} - -.card-header { - padding: 0.5rem 1rem; - margin-bottom: 0; - background-color: rgba(0, 0, 0, 0.03); - border-bottom: 1px solid rgba(0, 0, 0, 0.125); -} -.card-header:first-child { - border-radius: calc(0.25rem - 1px) calc(0.25rem - 1px) 0 0; -} - -.card-footer { - padding: 0.5rem 1rem; - background-color: rgba(0, 0, 0, 0.03); - border-top: 1px solid rgba(0, 0, 0, 0.125); -} -.card-footer:last-child { - border-radius: 0 0 calc(0.25rem - 1px) calc(0.25rem - 1px); -} - -.card-header-tabs { - margin-right: -0.5rem; - margin-bottom: -0.5rem; - margin-left: -0.5rem; - border-bottom: 0; -} - -.card-header-pills { - margin-right: -0.5rem; - margin-left: -0.5rem; -} - -.card-img-overlay { - position: absolute; - top: 0; - right: 0; - bottom: 0; - left: 0; - padding: 1rem; - border-radius: calc(0.25rem - 1px); -} - -.card-img, -.card-img-top, -.card-img-bottom { - width: 100%; -} - -.card-img, -.card-img-top { - border-top-left-radius: calc(0.25rem - 1px); - border-top-right-radius: calc(0.25rem - 1px); -} - -.card-img, -.card-img-bottom { - border-bottom-right-radius: calc(0.25rem - 1px); - border-bottom-left-radius: calc(0.25rem - 1px); -} - -.card-group > .card { - margin-bottom: 0.75rem; -} -@media (min-width: 576px) { - .card-group { - display: flex; - flex-flow: row wrap; - } - .card-group > .card { - flex: 1 0 0%; - margin-bottom: 0; - } - .card-group > .card + .card { - margin-left: 0; - border-left: 0; - } - .card-group > .card:not(:last-child) { - border-top-right-radius: 0; - border-bottom-right-radius: 0; - } - .card-group > .card:not(:last-child) .card-img-top, -.card-group > .card:not(:last-child) .card-header { - border-top-right-radius: 0; - } - .card-group > .card:not(:last-child) .card-img-bottom, -.card-group > .card:not(:last-child) .card-footer { - border-bottom-right-radius: 0; - } - .card-group > .card:not(:first-child) { - border-top-left-radius: 0; - border-bottom-left-radius: 0; - } - .card-group > .card:not(:first-child) .card-img-top, -.card-group > .card:not(:first-child) .card-header { - border-top-left-radius: 0; - } - .card-group > .card:not(:first-child) .card-img-bottom, -.card-group > .card:not(:first-child) .card-footer { - border-bottom-left-radius: 0; - } -} - -.accordion-button { - position: relative; - display: flex; - align-items: center; - width: 100%; - padding: 1rem 1.25rem; - font-size: 1rem; - color: #000000; - text-align: left; - background-color: #fff; - border: 0; - border-radius: 0; - overflow-anchor: none; - transition: color 0.15s ease-in-out, background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out, border-radius 0.15s ease; -} -@media (prefers-reduced-motion: reduce) { - .accordion-button { - transition: none; - } -} -.accordion-button:not(.collapsed) { - color: #0c63e4; - background-color: #e7f1ff; - box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.125); -} -.accordion-button:not(.collapsed)::after { - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%230c63e4'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e"); - transform: rotate(-180deg); -} -.accordion-button::after { - flex-shrink: 0; - width: 1.25rem; - height: 1.25rem; - margin-left: auto; - content: ""; - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23000000'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e"); - background-repeat: no-repeat; - background-size: 1.25rem; - transition: transform 0.2s ease-in-out; -} -@media (prefers-reduced-motion: reduce) { - .accordion-button::after { - transition: none; - } -} -.accordion-button:hover { - z-index: 2; -} -.accordion-button:focus { - z-index: 3; - border-color: #86b7fe; - outline: 0; - box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25); -} - -.accordion-header { - margin-bottom: 0; -} - -.accordion-item { - background-color: #fff; - border: 1px solid rgba(0, 0, 0, 0.125); -} -.accordion-item:first-of-type { - border-top-left-radius: 0.25rem; - border-top-right-radius: 0.25rem; -} -.accordion-item:first-of-type .accordion-button { - border-top-left-radius: calc(0.25rem - 1px); - border-top-right-radius: calc(0.25rem - 1px); -} -.accordion-item:not(:first-of-type) { - border-top: 0; -} -.accordion-item:last-of-type { - border-bottom-right-radius: 0.25rem; - border-bottom-left-radius: 0.25rem; -} -.accordion-item:last-of-type .accordion-button.collapsed { - border-bottom-right-radius: calc(0.25rem - 1px); - border-bottom-left-radius: calc(0.25rem - 1px); -} -.accordion-item:last-of-type .accordion-collapse { - border-bottom-right-radius: 0.25rem; - border-bottom-left-radius: 0.25rem; -} - -.accordion-body { - padding: 1rem 1.25rem; -} - -.accordion-flush .accordion-collapse { - border-width: 0; -} -.accordion-flush .accordion-item { - border-right: 0; - border-left: 0; - border-radius: 0; -} -.accordion-flush .accordion-item:first-child { - border-top: 0; -} -.accordion-flush .accordion-item:last-child { - border-bottom: 0; -} -.accordion-flush .accordion-item .accordion-button { - border-radius: 0; -} - -.breadcrumb { - display: flex; - flex-wrap: wrap; - padding: 0 0; - margin-bottom: 1rem; - list-style: none; -} - -.breadcrumb-item + .breadcrumb-item { - padding-left: 0.5rem; -} -.breadcrumb-item + .breadcrumb-item::before { - float: left; - padding-right: 0.5rem; - color: #8A8A8D; - content: var(--breadcrumb-divider, "/") /* rtl: var(--breadcrumb-divider, "/") */; -} -.breadcrumb-item.active { - color: #8A8A8D; -} - -.pagination { - display: flex; - padding-left: 0; - list-style: none; -} - -.page-link { - position: relative; - display: block; - color: #40B4E5; - text-decoration: none; - background-color: #fff; - border: 1px solid #dee2e6; - transition: color 0.15s ease-in-out, background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out; -} -@media (prefers-reduced-motion: reduce) { - .page-link { - transition: none; - } -} -.page-link:hover { - z-index: 2; - color: #0a58ca; - background-color: #e9ecef; - border-color: #dee2e6; -} -.page-link:focus { - z-index: 3; - color: #0a58ca; - background-color: #e9ecef; - outline: 0; - box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25); -} - -.page-item:not(:first-child) .page-link { - margin-left: -1px; -} -.page-item.active .page-link { - z-index: 3; - color: #fff; - background-color: #40B4E5; - border-color: #40B4E5; -} -.page-item.disabled .page-link { - color: #8A8A8D; - pointer-events: none; - background-color: #fff; - border-color: #dee2e6; -} - -.page-link { - padding: 0.375rem 0.75rem; -} - -.page-item:first-child .page-link { - border-top-left-radius: 0.25rem; - border-bottom-left-radius: 0.25rem; -} -.page-item:last-child .page-link { - border-top-right-radius: 0.25rem; - border-bottom-right-radius: 0.25rem; -} - -.pagination-lg .page-link { - padding: 0.75rem 1.5rem; - font-size: 1.25rem; -} -.pagination-lg .page-item:first-child .page-link { - border-top-left-radius: 0.3rem; - border-bottom-left-radius: 0.3rem; -} -.pagination-lg .page-item:last-child .page-link { - border-top-right-radius: 0.3rem; - border-bottom-right-radius: 0.3rem; -} - -.pagination-sm .page-link { - padding: 0.25rem 0.5rem; - font-size: 0.875rem; -} -.pagination-sm .page-item:first-child .page-link { - border-top-left-radius: 0.2rem; - border-bottom-left-radius: 0.2rem; -} -.pagination-sm .page-item:last-child .page-link { - border-top-right-radius: 0.2rem; - border-bottom-right-radius: 0.2rem; -} - -.badge { - display: inline-block; - padding: 0.35em 0.65em; - font-size: 0.75em; - font-weight: 700; - line-height: 1; - color: #fff; - text-align: center; - white-space: nowrap; - vertical-align: baseline; - border-radius: 0.25rem; -} -.badge:empty { - display: none; -} - -.btn .badge { - position: relative; - top: -1px; -} - -.alert { - position: relative; - padding: 1rem 1rem; - margin-bottom: 1rem; - border: 1px solid transparent; - border-radius: 0.25rem; -} - -.alert-heading { - color: inherit; -} - -.alert-link { - font-weight: 700; -} - -.alert-dismissible { - padding-right: 3rem; -} -.alert-dismissible .btn-close { - position: absolute; - top: 0; - right: 0; - z-index: 2; - padding: 1.25rem 1rem; -} - -.alert-primary { - color: #084298; - background-color: #cfe2ff; - border-color: #b6d4fe; -} -.alert-primary .alert-link { - color: #06357a; -} - -.alert-secondary { - color: #41464b; - background-color: #e2e3e5; - border-color: #d3d6d8; -} -.alert-secondary .alert-link { - color: #34383c; -} - -.alert-success { - color: #0f5132; - background-color: #d1e7dd; - border-color: #badbcc; -} -.alert-success .alert-link { - color: #0c4128; -} - -.alert-info { - color: #055160; - background-color: #cff4fc; - border-color: #b6effb; -} -.alert-info .alert-link { - color: #04414d; -} - -.alert-warning { - color: #664d03; - background-color: #fff3cd; - border-color: #ffecb5; -} -.alert-warning .alert-link { - color: #523e02; -} - -.alert-danger { - color: #842029; - background-color: #f8d7da; - border-color: #f5c2c7; -} -.alert-danger .alert-link { - color: #6a1a21; -} - -.alert-light { - color: #636464; - background-color: #fefefe; - border-color: #fdfdfe; -} -.alert-light .alert-link { - color: #4f5050; -} - -.alert-dark { - color: #141619; - background-color: #d3d3d4; - border-color: #bcbebf; -} -.alert-dark .alert-link { - color: #101214; -} - -@-webkit-keyframes progress-bar-stripes { - 0% { - background-position-x: 1rem; - } -} - -@keyframes progress-bar-stripes { - 0% { - background-position-x: 1rem; - } -} -.progress { - display: flex; - height: 1rem; - overflow: hidden; - font-size: 0.75rem; - background-color: #e9ecef; - border-radius: 0.25rem; -} - -.progress-bar { - display: flex; - flex-direction: column; - justify-content: center; - overflow: hidden; - color: #fff; - text-align: center; - white-space: nowrap; - background-color: #40B4E5; - transition: width 0.6s ease; -} -@media (prefers-reduced-motion: reduce) { - .progress-bar { - transition: none; - } -} - -.progress-bar-striped { - background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); - background-size: 1rem 1rem; -} - -.progress-bar-animated { - -webkit-animation: 1s linear infinite progress-bar-stripes; - animation: 1s linear infinite progress-bar-stripes; -} -@media (prefers-reduced-motion: reduce) { - .progress-bar-animated { - -webkit-animation: none; - animation: none; - } -} - -.list-group { - display: flex; - flex-direction: column; - padding-left: 0; - margin-bottom: 0; - border-radius: 0.25rem; -} - -.list-group-numbered { - list-style-type: none; - counter-reset: section; -} -.list-group-numbered > li::before { - content: counters(section, ".") ". "; - counter-increment: section; -} - -.list-group-item-action { - width: 100%; - color: #495057; - text-align: inherit; -} -.list-group-item-action:hover, .list-group-item-action:focus { - z-index: 1; - color: #495057; - text-decoration: none; - background-color: #ffffff; -} -.list-group-item-action:active { - color: #000000; - background-color: #e9ecef; -} - -.list-group-item { - position: relative; - display: block; - padding: 0.5rem 1rem; - color: #000000; - text-decoration: none; - background-color: #fff; - border: 1px solid rgba(0, 0, 0, 0.125); -} -.list-group-item:first-child { - border-top-left-radius: inherit; - border-top-right-radius: inherit; -} -.list-group-item:last-child { - border-bottom-right-radius: inherit; - border-bottom-left-radius: inherit; -} -.list-group-item.disabled, .list-group-item:disabled { - color: #8A8A8D; - pointer-events: none; - background-color: #fff; -} -.list-group-item.active { - z-index: 2; - color: #fff; - background-color: #40B4E5; - border-color: #40B4E5; -} -.list-group-item + .list-group-item { - border-top-width: 0; -} -.list-group-item + .list-group-item.active { - margin-top: -1px; - border-top-width: 1px; -} - -.list-group-horizontal { - flex-direction: row; -} -.list-group-horizontal > .list-group-item:first-child { - border-bottom-left-radius: 0.25rem; - border-top-right-radius: 0; -} -.list-group-horizontal > .list-group-item:last-child { - border-top-right-radius: 0.25rem; - border-bottom-left-radius: 0; -} -.list-group-horizontal > .list-group-item.active { - margin-top: 0; -} -.list-group-horizontal > .list-group-item + .list-group-item { - border-top-width: 1px; - border-left-width: 0; -} -.list-group-horizontal > .list-group-item + .list-group-item.active { - margin-left: -1px; - border-left-width: 1px; -} - -@media (min-width: 576px) { - .list-group-horizontal-sm { - flex-direction: row; - } - .list-group-horizontal-sm > .list-group-item:first-child { - border-bottom-left-radius: 0.25rem; - border-top-right-radius: 0; - } - .list-group-horizontal-sm > .list-group-item:last-child { - border-top-right-radius: 0.25rem; - border-bottom-left-radius: 0; - } - .list-group-horizontal-sm > .list-group-item.active { - margin-top: 0; - } - .list-group-horizontal-sm > .list-group-item + .list-group-item { - border-top-width: 1px; - border-left-width: 0; - } - .list-group-horizontal-sm > .list-group-item + .list-group-item.active { - margin-left: -1px; - border-left-width: 1px; - } -} -@media (min-width: 768px) { - .list-group-horizontal-md { - flex-direction: row; - } - .list-group-horizontal-md > .list-group-item:first-child { - border-bottom-left-radius: 0.25rem; - border-top-right-radius: 0; - } - .list-group-horizontal-md > .list-group-item:last-child { - border-top-right-radius: 0.25rem; - border-bottom-left-radius: 0; - } - .list-group-horizontal-md > .list-group-item.active { - margin-top: 0; - } - .list-group-horizontal-md > .list-group-item + .list-group-item { - border-top-width: 1px; - border-left-width: 0; - } - .list-group-horizontal-md > .list-group-item + .list-group-item.active { - margin-left: -1px; - border-left-width: 1px; - } -} -@media (min-width: 992px) { - .list-group-horizontal-lg { - flex-direction: row; - } - .list-group-horizontal-lg > .list-group-item:first-child { - border-bottom-left-radius: 0.25rem; - border-top-right-radius: 0; - } - .list-group-horizontal-lg > .list-group-item:last-child { - border-top-right-radius: 0.25rem; - border-bottom-left-radius: 0; - } - .list-group-horizontal-lg > .list-group-item.active { - margin-top: 0; - } - .list-group-horizontal-lg > .list-group-item + .list-group-item { - border-top-width: 1px; - border-left-width: 0; - } - .list-group-horizontal-lg > .list-group-item + .list-group-item.active { - margin-left: -1px; - border-left-width: 1px; - } -} -@media (min-width: 1200px) { - .list-group-horizontal-xl { - flex-direction: row; - } - .list-group-horizontal-xl > .list-group-item:first-child { - border-bottom-left-radius: 0.25rem; - border-top-right-radius: 0; - } - .list-group-horizontal-xl > .list-group-item:last-child { - border-top-right-radius: 0.25rem; - border-bottom-left-radius: 0; - } - .list-group-horizontal-xl > .list-group-item.active { - margin-top: 0; - } - .list-group-horizontal-xl > .list-group-item + .list-group-item { - border-top-width: 1px; - border-left-width: 0; - } - .list-group-horizontal-xl > .list-group-item + .list-group-item.active { - margin-left: -1px; - border-left-width: 1px; - } -} -@media (min-width: 1400px) { - .list-group-horizontal-xxl { - flex-direction: row; - } - .list-group-horizontal-xxl > .list-group-item:first-child { - border-bottom-left-radius: 0.25rem; - border-top-right-radius: 0; - } - .list-group-horizontal-xxl > .list-group-item:last-child { - border-top-right-radius: 0.25rem; - border-bottom-left-radius: 0; - } - .list-group-horizontal-xxl > .list-group-item.active { - margin-top: 0; - } - .list-group-horizontal-xxl > .list-group-item + .list-group-item { - border-top-width: 1px; - border-left-width: 0; - } - .list-group-horizontal-xxl > .list-group-item + .list-group-item.active { - margin-left: -1px; - border-left-width: 1px; - } -} -.list-group-flush { - border-radius: 0; -} -.list-group-flush > .list-group-item { - border-width: 0 0 1px; -} -.list-group-flush > .list-group-item:last-child { - border-bottom-width: 0; -} - -.list-group-item-primary { - color: #084298; - background-color: #cfe2ff; -} -.list-group-item-primary.list-group-item-action:hover, .list-group-item-primary.list-group-item-action:focus { - color: #084298; - background-color: #bacbe6; -} -.list-group-item-primary.list-group-item-action.active { - color: #fff; - background-color: #084298; - border-color: #084298; -} - -.list-group-item-secondary { - color: #41464b; - background-color: #e2e3e5; -} -.list-group-item-secondary.list-group-item-action:hover, .list-group-item-secondary.list-group-item-action:focus { - color: #41464b; - background-color: #cbccce; -} -.list-group-item-secondary.list-group-item-action.active { - color: #fff; - background-color: #41464b; - border-color: #41464b; -} - -.list-group-item-success { - color: #0f5132; - background-color: #d1e7dd; -} -.list-group-item-success.list-group-item-action:hover, .list-group-item-success.list-group-item-action:focus { - color: #0f5132; - background-color: #bcd0c7; -} -.list-group-item-success.list-group-item-action.active { - color: #fff; - background-color: #0f5132; - border-color: #0f5132; -} - -.list-group-item-info { - color: #055160; - background-color: #cff4fc; -} -.list-group-item-info.list-group-item-action:hover, .list-group-item-info.list-group-item-action:focus { - color: #055160; - background-color: #badce3; -} -.list-group-item-info.list-group-item-action.active { - color: #fff; - background-color: #055160; - border-color: #055160; -} - -.list-group-item-warning { - color: #664d03; - background-color: #fff3cd; -} -.list-group-item-warning.list-group-item-action:hover, .list-group-item-warning.list-group-item-action:focus { - color: #664d03; - background-color: #e6dbb9; -} -.list-group-item-warning.list-group-item-action.active { - color: #fff; - background-color: #664d03; - border-color: #664d03; -} - -.list-group-item-danger { - color: #842029; - background-color: #f8d7da; -} -.list-group-item-danger.list-group-item-action:hover, .list-group-item-danger.list-group-item-action:focus { - color: #842029; - background-color: #dfc2c4; -} -.list-group-item-danger.list-group-item-action.active { - color: #fff; - background-color: #842029; - border-color: #842029; -} - -.list-group-item-light { - color: #636464; - background-color: #fefefe; -} -.list-group-item-light.list-group-item-action:hover, .list-group-item-light.list-group-item-action:focus { - color: #636464; - background-color: #e5e5e5; -} -.list-group-item-light.list-group-item-action.active { - color: #fff; - background-color: #636464; - border-color: #636464; -} - -.list-group-item-dark { - color: #141619; - background-color: #d3d3d4; -} -.list-group-item-dark.list-group-item-action:hover, .list-group-item-dark.list-group-item-action:focus { - color: #141619; - background-color: #bebebf; -} -.list-group-item-dark.list-group-item-action.active { - color: #fff; - background-color: #141619; - border-color: #141619; -} - -.btn-close { - box-sizing: content-box; - width: 1em; - height: 1em; - padding: 0.25em 0.25em; - color: #000; - background: transparent url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23000'%3e%3cpath d='M.293.293a1 1 0 011.414 0L8 6.586 14.293.293a1 1 0 111.414 1.414L9.414 8l6.293 6.293a1 1 0 01-1.414 1.414L8 9.414l-6.293 6.293a1 1 0 01-1.414-1.414L6.586 8 .293 1.707a1 1 0 010-1.414z'/%3e%3c/svg%3e") center/1em auto no-repeat; - border: 0; - border-radius: 0.25rem; - opacity: 0.5; -} -.btn-close:hover { - color: #000; - text-decoration: none; - opacity: 0.75; -} -.btn-close:focus { - outline: 0; - box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25); - opacity: 1; -} -.btn-close:disabled, .btn-close.disabled { - pointer-events: none; - -webkit-user-select: none; - -moz-user-select: none; - -ms-user-select: none; - user-select: none; - opacity: 0.25; -} - -.btn-close-white { - filter: invert(1) grayscale(100%) brightness(200%); -} - -.toast { - width: 350px; - max-width: 100%; - font-size: 0.875rem; - pointer-events: auto; - background-color: rgba(255, 255, 255, 0.85); - background-clip: padding-box; - border: 1px solid rgba(0, 0, 0, 0.1); - box-shadow: 0 0.5rem 1rem rgba(0, 0, 0, 0.15); - border-radius: 0.25rem; -} -.toast:not(.showing):not(.show) { - opacity: 0; -} -.toast.hide { - display: none; -} - -.toast-container { - width: -webkit-max-content; - width: -moz-max-content; - width: max-content; - max-width: 100%; - pointer-events: none; -} -.toast-container > :not(:last-child) { - margin-bottom: 0.75rem; -} - -.toast-header { - display: flex; - align-items: center; - padding: 0.5rem 0.75rem; - color: #8A8A8D; - background-color: rgba(255, 255, 255, 0.85); - background-clip: padding-box; - border-bottom: 1px solid rgba(0, 0, 0, 0.05); - border-top-left-radius: calc(0.25rem - 1px); - border-top-right-radius: calc(0.25rem - 1px); -} -.toast-header .btn-close { - margin-right: -0.375rem; - margin-left: 0.75rem; -} - -.toast-body { - padding: 0.75rem; - word-wrap: break-word; -} - -.modal { - position: fixed; - top: 0; - left: 0; - z-index: 1060; - display: none; - width: 100%; - height: 100%; - overflow-x: hidden; - overflow-y: auto; - outline: 0; -} - -.modal-dialog { - position: relative; - width: auto; - margin: 0.5rem; - pointer-events: none; -} -.modal.fade .modal-dialog { - transition: transform 0.3s ease-out; - transform: translate(0, -50px); -} -@media (prefers-reduced-motion: reduce) { - .modal.fade .modal-dialog { - transition: none; - } -} -.modal.show .modal-dialog { - transform: none; -} -.modal.modal-static .modal-dialog { - transform: scale(1.02); -} - -.modal-dialog-scrollable { - height: calc(100% - 1rem); -} -.modal-dialog-scrollable .modal-content { - max-height: 100%; - overflow: hidden; -} -.modal-dialog-scrollable .modal-body { - overflow-y: auto; -} - -.modal-dialog-centered { - display: flex; - align-items: center; - min-height: calc(100% - 1rem); -} - -.modal-content { - position: relative; - display: flex; - flex-direction: column; - width: 100%; - pointer-events: auto; - background-color: #fff; - background-clip: padding-box; - border: 1px solid rgba(0, 0, 0, 0.2); - border-radius: 0.3rem; - outline: 0; -} - -.modal-backdrop { - position: fixed; - top: 0; - left: 0; - z-index: 1040; - width: 100vw; - height: 100vh; - background-color: #000; -} -.modal-backdrop.fade { - opacity: 0; -} -.modal-backdrop.show { - opacity: 0.5; -} - -.modal-header { - display: flex; - flex-shrink: 0; - align-items: center; - justify-content: space-between; - padding: 1rem 1rem; - border-bottom: 1px solid #dee2e6; - border-top-left-radius: calc(0.3rem - 1px); - border-top-right-radius: calc(0.3rem - 1px); -} -.modal-header .btn-close { - padding: 0.5rem 0.5rem; - margin: -0.5rem -0.5rem -0.5rem auto; -} - -.modal-title { - margin-bottom: 0; - line-height: 1.5; -} - -.modal-body { - position: relative; - flex: 1 1 auto; - padding: 1rem; -} - -.modal-footer { - display: flex; - flex-wrap: wrap; - flex-shrink: 0; - align-items: center; - justify-content: flex-end; - padding: 0.75rem; - border-top: 1px solid #dee2e6; - border-bottom-right-radius: calc(0.3rem - 1px); - border-bottom-left-radius: calc(0.3rem - 1px); -} -.modal-footer > * { - margin: 0.25rem; -} - -@media (min-width: 576px) { - .modal-dialog { - max-width: 500px; - margin: 1.75rem auto; - } - - .modal-dialog-scrollable { - height: calc(100% - 3.5rem); - } - - .modal-dialog-centered { - min-height: calc(100% - 3.5rem); - } - - .modal-sm { - max-width: 300px; - } -} -@media (min-width: 992px) { - .modal-lg, -.modal-xl { - max-width: 800px; - } -} -@media (min-width: 1200px) { - .modal-xl { - max-width: 1140px; - } -} -.modal-fullscreen { - width: 100vw; - max-width: none; - height: 100%; - margin: 0; -} -.modal-fullscreen .modal-content { - height: 100%; - border: 0; - border-radius: 0; -} -.modal-fullscreen .modal-header { - border-radius: 0; -} -.modal-fullscreen .modal-body { - overflow-y: auto; -} -.modal-fullscreen .modal-footer { - border-radius: 0; -} - -@media (max-width: 575.98px) { - .modal-fullscreen-sm-down { - width: 100vw; - max-width: none; - height: 100%; - margin: 0; - } - .modal-fullscreen-sm-down .modal-content { - height: 100%; - border: 0; - border-radius: 0; - } - .modal-fullscreen-sm-down .modal-header { - border-radius: 0; - } - .modal-fullscreen-sm-down .modal-body { - overflow-y: auto; - } - .modal-fullscreen-sm-down .modal-footer { - border-radius: 0; - } -} -@media (max-width: 767.98px) { - .modal-fullscreen-md-down { - width: 100vw; - max-width: none; - height: 100%; - margin: 0; - } - .modal-fullscreen-md-down .modal-content { - height: 100%; - border: 0; - border-radius: 0; - } - .modal-fullscreen-md-down .modal-header { - border-radius: 0; - } - .modal-fullscreen-md-down .modal-body { - overflow-y: auto; - } - .modal-fullscreen-md-down .modal-footer { - border-radius: 0; - } -} -@media (max-width: 991.98px) { - .modal-fullscreen-lg-down { - width: 100vw; - max-width: none; - height: 100%; - margin: 0; - } - .modal-fullscreen-lg-down .modal-content { - height: 100%; - border: 0; - border-radius: 0; - } - .modal-fullscreen-lg-down .modal-header { - border-radius: 0; - } - .modal-fullscreen-lg-down .modal-body { - overflow-y: auto; - } - .modal-fullscreen-lg-down .modal-footer { - border-radius: 0; - } -} -@media (max-width: 1199.98px) { - .modal-fullscreen-xl-down { - width: 100vw; - max-width: none; - height: 100%; - margin: 0; - } - .modal-fullscreen-xl-down .modal-content { - height: 100%; - border: 0; - border-radius: 0; - } - .modal-fullscreen-xl-down .modal-header { - border-radius: 0; - } - .modal-fullscreen-xl-down .modal-body { - overflow-y: auto; - } - .modal-fullscreen-xl-down .modal-footer { - border-radius: 0; - } -} -@media (max-width: 1399.98px) { - .modal-fullscreen-xxl-down { - width: 100vw; - max-width: none; - height: 100%; - margin: 0; - } - .modal-fullscreen-xxl-down .modal-content { - height: 100%; - border: 0; - border-radius: 0; - } - .modal-fullscreen-xxl-down .modal-header { - border-radius: 0; - } - .modal-fullscreen-xxl-down .modal-body { - overflow-y: auto; - } - .modal-fullscreen-xxl-down .modal-footer { - border-radius: 0; - } -} -.tooltip { - position: absolute; - z-index: 1080; - display: block; - margin: 0; - font-family: var(--font-sans-serif); - font-style: normal; - font-weight: 400; - line-height: 1.5; - text-align: left; - text-align: start; - text-decoration: none; - text-shadow: none; - text-transform: none; - letter-spacing: normal; - word-break: normal; - word-spacing: normal; - white-space: normal; - line-break: auto; - font-size: 0.875rem; - word-wrap: break-word; - opacity: 0; -} -.tooltip.show { - opacity: 0.9; -} -.tooltip .tooltip-arrow { - position: absolute; - display: block; - width: 0.8rem; - height: 0.4rem; -} -.tooltip .tooltip-arrow::before { - position: absolute; - content: ""; - border-color: transparent; - border-style: solid; -} - -.bs-tooltip-top, .bs-tooltip-auto[data-popper-placement^=top] { - padding: 0.4rem 0; -} -.bs-tooltip-top .tooltip-arrow, .bs-tooltip-auto[data-popper-placement^=top] .tooltip-arrow { - bottom: 0; -} -.bs-tooltip-top .tooltip-arrow::before, .bs-tooltip-auto[data-popper-placement^=top] .tooltip-arrow::before { - top: -1px; - border-width: 0.4rem 0.4rem 0; - border-top-color: #000; -} - -.bs-tooltip-end, .bs-tooltip-auto[data-popper-placement^=right] { - padding: 0 0.4rem; -} -.bs-tooltip-end .tooltip-arrow, .bs-tooltip-auto[data-popper-placement^=right] .tooltip-arrow { - left: 0; - width: 0.4rem; - height: 0.8rem; -} -.bs-tooltip-end .tooltip-arrow::before, .bs-tooltip-auto[data-popper-placement^=right] .tooltip-arrow::before { - right: -1px; - border-width: 0.4rem 0.4rem 0.4rem 0; - border-right-color: #000; -} - -.bs-tooltip-bottom, .bs-tooltip-auto[data-popper-placement^=bottom] { - padding: 0.4rem 0; -} -.bs-tooltip-bottom .tooltip-arrow, .bs-tooltip-auto[data-popper-placement^=bottom] .tooltip-arrow { - top: 0; -} -.bs-tooltip-bottom .tooltip-arrow::before, .bs-tooltip-auto[data-popper-placement^=bottom] .tooltip-arrow::before { - bottom: -1px; - border-width: 0 0.4rem 0.4rem; - border-bottom-color: #000; -} - -.bs-tooltip-start, .bs-tooltip-auto[data-popper-placement^=left] { - padding: 0 0.4rem; -} -.bs-tooltip-start .tooltip-arrow, .bs-tooltip-auto[data-popper-placement^=left] .tooltip-arrow { - right: 0; - width: 0.4rem; - height: 0.8rem; -} -.bs-tooltip-start .tooltip-arrow::before, .bs-tooltip-auto[data-popper-placement^=left] .tooltip-arrow::before { - left: -1px; - border-width: 0.4rem 0 0.4rem 0.4rem; - border-left-color: #000; -} - -.tooltip-inner { - max-width: 200px; - padding: 0.25rem 0.5rem; - color: #fff; - text-align: center; - background-color: #000; - border-radius: 0.25rem; -} - -.popover { - position: absolute; - top: 0; - left: 0 /* rtl:ignore */; - z-index: 1070; - display: block; - max-width: 276px; - font-family: var(--font-sans-serif); - font-style: normal; - font-weight: 400; - line-height: 1.5; - text-align: left; - text-align: start; - text-decoration: none; - text-shadow: none; - text-transform: none; - letter-spacing: normal; - word-break: normal; - word-spacing: normal; - white-space: normal; - line-break: auto; - font-size: 0.875rem; - word-wrap: break-word; - background-color: #fff; - background-clip: padding-box; - border: 1px solid rgba(0, 0, 0, 0.2); - border-radius: 0.3rem; -} -.popover .popover-arrow { - position: absolute; - display: block; - width: 1rem; - height: 0.5rem; -} -.popover .popover-arrow::before, .popover .popover-arrow::after { - position: absolute; - display: block; - content: ""; - border-color: transparent; - border-style: solid; -} - -.bs-popover-top > .popover-arrow, .bs-popover-auto[data-popper-placement^=top] > .popover-arrow { - bottom: calc(-0.5rem - 1px); -} -.bs-popover-top > .popover-arrow::before, .bs-popover-auto[data-popper-placement^=top] > .popover-arrow::before { - bottom: 0; - border-width: 0.5rem 0.5rem 0; - border-top-color: rgba(0, 0, 0, 0.25); -} -.bs-popover-top > .popover-arrow::after, .bs-popover-auto[data-popper-placement^=top] > .popover-arrow::after { - bottom: 1px; - border-width: 0.5rem 0.5rem 0; - border-top-color: #fff; -} - -.bs-popover-end > .popover-arrow, .bs-popover-auto[data-popper-placement^=right] > .popover-arrow { - left: calc(-0.5rem - 1px); - width: 0.5rem; - height: 1rem; -} -.bs-popover-end > .popover-arrow::before, .bs-popover-auto[data-popper-placement^=right] > .popover-arrow::before { - left: 0; - border-width: 0.5rem 0.5rem 0.5rem 0; - border-right-color: rgba(0, 0, 0, 0.25); -} -.bs-popover-end > .popover-arrow::after, .bs-popover-auto[data-popper-placement^=right] > .popover-arrow::after { - left: 1px; - border-width: 0.5rem 0.5rem 0.5rem 0; - border-right-color: #fff; -} - -.bs-popover-bottom > .popover-arrow, .bs-popover-auto[data-popper-placement^=bottom] > .popover-arrow { - top: calc(-0.5rem - 1px); -} -.bs-popover-bottom > .popover-arrow::before, .bs-popover-auto[data-popper-placement^=bottom] > .popover-arrow::before { - top: 0; - border-width: 0 0.5rem 0.5rem 0.5rem; - border-bottom-color: rgba(0, 0, 0, 0.25); -} -.bs-popover-bottom > .popover-arrow::after, .bs-popover-auto[data-popper-placement^=bottom] > .popover-arrow::after { - top: 1px; - border-width: 0 0.5rem 0.5rem 0.5rem; - border-bottom-color: #fff; -} -.bs-popover-bottom .popover-header::before, .bs-popover-auto[data-popper-placement^=bottom] .popover-header::before { - position: absolute; - top: 0; - left: 50%; - display: block; - width: 1rem; - margin-left: -0.5rem; - content: ""; - border-bottom: 1px solid #f0f0f0; -} - -.bs-popover-start > .popover-arrow, .bs-popover-auto[data-popper-placement^=left] > .popover-arrow { - right: calc(-0.5rem - 1px); - width: 0.5rem; - height: 1rem; -} -.bs-popover-start > .popover-arrow::before, .bs-popover-auto[data-popper-placement^=left] > .popover-arrow::before { - right: 0; - border-width: 0.5rem 0 0.5rem 0.5rem; - border-left-color: rgba(0, 0, 0, 0.25); -} -.bs-popover-start > .popover-arrow::after, .bs-popover-auto[data-popper-placement^=left] > .popover-arrow::after { - right: 1px; - border-width: 0.5rem 0 0.5rem 0.5rem; - border-left-color: #fff; -} - -.popover-header { - padding: 0.5rem 1rem; - margin-bottom: 0; - font-size: 1rem; - background-color: #f0f0f0; - border-bottom: 1px solid rgba(0, 0, 0, 0.2); - border-top-left-radius: calc(0.3rem - 1px); - border-top-right-radius: calc(0.3rem - 1px); -} -.popover-header:empty { - display: none; -} - -.popover-body { - padding: 1rem 1rem; - color: #000000; -} - -.carousel { - position: relative; -} - -.carousel.pointer-event { - touch-action: pan-y; -} - -.carousel-inner { - position: relative; - width: 100%; - overflow: hidden; -} -.carousel-inner::after { - display: block; - clear: both; - content: ""; -} - -.carousel-item { - position: relative; - display: none; - float: left; - width: 100%; - margin-right: -100%; - -webkit-backface-visibility: hidden; - backface-visibility: hidden; - transition: transform 0.6s ease-in-out; -} -@media (prefers-reduced-motion: reduce) { - .carousel-item { - transition: none; - } -} - -.carousel-item.active, -.carousel-item-next, -.carousel-item-prev { - display: block; -} - -/* rtl:begin:ignore */ -.carousel-item-next:not(.carousel-item-start), -.active.carousel-item-end { - transform: translateX(100%); -} - -.carousel-item-prev:not(.carousel-item-end), -.active.carousel-item-start { - transform: translateX(-100%); -} - -/* rtl:end:ignore */ -.carousel-fade .carousel-item { - opacity: 0; - transition-property: opacity; - transform: none; -} -.carousel-fade .carousel-item.active, -.carousel-fade .carousel-item-next.carousel-item-start, -.carousel-fade .carousel-item-prev.carousel-item-end { - z-index: 1; - opacity: 1; -} -.carousel-fade .active.carousel-item-start, -.carousel-fade .active.carousel-item-end { - z-index: 0; - opacity: 0; - transition: opacity 0s 0.6s; -} -@media (prefers-reduced-motion: reduce) { - .carousel-fade .active.carousel-item-start, -.carousel-fade .active.carousel-item-end { - transition: none; - } -} - -.carousel-control-prev, -.carousel-control-next { - position: absolute; - top: 0; - bottom: 0; - z-index: 1; - display: flex; - align-items: center; - justify-content: center; - width: 15%; - padding: 0; - color: #fff; - text-align: center; - background: none; - border: 0; - opacity: 0.5; - transition: opacity 0.15s ease; -} -@media (prefers-reduced-motion: reduce) { - .carousel-control-prev, -.carousel-control-next { - transition: none; - } -} -.carousel-control-prev:hover, .carousel-control-prev:focus, -.carousel-control-next:hover, -.carousel-control-next:focus { - color: #fff; - text-decoration: none; - outline: 0; - opacity: 0.9; -} - -.carousel-control-prev { - left: 0; -} - -.carousel-control-next { - right: 0; -} - -.carousel-control-prev-icon, -.carousel-control-next-icon { - display: inline-block; - width: 2rem; - height: 2rem; - background-repeat: no-repeat; - background-position: 50%; - background-size: 100% 100%; -} - -/* rtl:options: { - "autoRename": true, - "stringMap":[ { - "name" : "prev-next", - "search" : "prev", - "replace" : "next" - } ] -} */ -.carousel-control-prev-icon { - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23fff'%3e%3cpath d='M11.354 1.646a.5.5 0 0 1 0 .708L5.707 8l5.647 5.646a.5.5 0 0 1-.708.708l-6-6a.5.5 0 0 1 0-.708l6-6a.5.5 0 0 1 .708 0z'/%3e%3c/svg%3e"); -} - -.carousel-control-next-icon { - background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23fff'%3e%3cpath d='M4.646 1.646a.5.5 0 0 1 .708 0l6 6a.5.5 0 0 1 0 .708l-6 6a.5.5 0 0 1-.708-.708L10.293 8 4.646 2.354a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e"); -} - -.carousel-indicators { - position: absolute; - right: 0; - bottom: 0; - left: 0; - z-index: 2; - display: flex; - justify-content: center; - padding: 0; - margin-right: 15%; - margin-bottom: 1rem; - margin-left: 15%; - list-style: none; -} -.carousel-indicators [data-bs-target] { - box-sizing: content-box; - flex: 0 1 auto; - width: 30px; - height: 3px; - padding: 0; - margin-right: 3px; - margin-left: 3px; - text-indent: -999px; - cursor: pointer; - background-color: #fff; - background-clip: padding-box; - border: 0; - border-top: 10px solid transparent; - border-bottom: 10px solid transparent; - opacity: 0.5; - transition: opacity 0.6s ease; -} -@media (prefers-reduced-motion: reduce) { - .carousel-indicators [data-bs-target] { - transition: none; - } -} -.carousel-indicators .active { - opacity: 1; -} - -.carousel-caption { - position: absolute; - right: 15%; - bottom: 1.25rem; - left: 15%; - padding-top: 1.25rem; - padding-bottom: 1.25rem; - color: #fff; - text-align: center; -} - -.carousel-dark .carousel-control-prev-icon, -.carousel-dark .carousel-control-next-icon { - filter: invert(1) grayscale(100); -} -.carousel-dark .carousel-indicators [data-bs-target] { - background-color: #000; -} -.carousel-dark .carousel-caption { - color: #000; -} - -@-webkit-keyframes spinner-border { - to { - transform: rotate(360deg) /* rtl:ignore */; - } -} - -@keyframes spinner-border { - to { - transform: rotate(360deg) /* rtl:ignore */; - } -} -.spinner-border { - display: inline-block; - width: 2rem; - height: 2rem; - vertical-align: -0.125em; - border: 0.25em solid currentColor; - border-right-color: transparent; - border-radius: 50%; - -webkit-animation: 0.75s linear infinite spinner-border; - animation: 0.75s linear infinite spinner-border; -} - -.spinner-border-sm { - width: 1rem; - height: 1rem; - border-width: 0.2em; -} - -@-webkit-keyframes spinner-grow { - 0% { - transform: scale(0); - } - 50% { - opacity: 1; - transform: none; - } -} - -@keyframes spinner-grow { - 0% { - transform: scale(0); - } - 50% { - opacity: 1; - transform: none; - } -} -.spinner-grow { - display: inline-block; - width: 2rem; - height: 2rem; - vertical-align: -0.125em; - background-color: currentColor; - border-radius: 50%; - opacity: 0; - -webkit-animation: 0.75s linear infinite spinner-grow; - animation: 0.75s linear infinite spinner-grow; -} - -.spinner-grow-sm { - width: 1rem; - height: 1rem; -} - -@media (prefers-reduced-motion: reduce) { - .spinner-border, -.spinner-grow { - -webkit-animation-duration: 1.5s; - animation-duration: 1.5s; - } -} -.offcanvas { - position: fixed; - bottom: 0; - z-index: 1050; - display: flex; - flex-direction: column; - max-width: 100%; - visibility: hidden; - background-color: #fff; - background-clip: padding-box; - outline: 0; - transition: transform 0.3s ease-in-out; -} -@media (prefers-reduced-motion: reduce) { - .offcanvas { - transition: none; - } -} - -.offcanvas-header { - display: flex; - align-items: center; - justify-content: space-between; - padding: 1rem 1rem; -} -.offcanvas-header .btn-close { - padding: 0.5rem 0.5rem; - margin-top: -0.5rem; - margin-right: -0.5rem; - margin-bottom: -0.5rem; -} - -.offcanvas-title { - margin-bottom: 0; - line-height: 1.5; -} - -.offcanvas-body { - flex-grow: 1; - padding: 1rem 1rem; - overflow-y: auto; -} - -.offcanvas-start { - top: 0; - left: 0; - width: 400px; - border-right: 1px solid rgba(0, 0, 0, 0.2); - transform: translateX(-100%); -} - -.offcanvas-end { - top: 0; - right: 0; - width: 400px; - border-left: 1px solid rgba(0, 0, 0, 0.2); - transform: translateX(100%); -} - -.offcanvas-top { - top: 0; - right: 0; - left: 0; - height: 30vh; - max-height: 100%; - border-bottom: 1px solid rgba(0, 0, 0, 0.2); - transform: translateY(-100%); -} - -.offcanvas-bottom { - right: 0; - left: 0; - height: 30vh; - max-height: 100%; - border-top: 1px solid rgba(0, 0, 0, 0.2); - transform: translateY(100%); -} - -.offcanvas.show { - transform: none; -} - -.clearfix::after { - display: block; - clear: both; - content: ""; -} - -.link-primary { - color: #40B4E5; -} -.link-primary:hover, .link-primary:focus { - color: #0a58ca; -} - -.link-secondary { - color: #8A8A8D; -} -.link-secondary:hover, .link-secondary:focus { - color: #565e64; -} - -.link-success { - color: #00833E; -} -.link-success:hover, .link-success:focus { - color: #146c43; -} - -.link-info { - color: #40B4E5; -} -.link-info:hover, .link-info:focus { - color: #3dd5f3; -} - -.link-warning { - color: #00833E; -} -.link-warning:hover, .link-warning:focus { - color: #ffcd39; -} - -.link-danger { - color: #CF0A2C; -} -.link-danger:hover, .link-danger:focus { - color: #b02a37; -} - -.link-light { - color: #ffffff; -} -.link-light:hover, .link-light:focus { - color: #f9fafb; -} - -.link-dark { - color: #000000; -} -.link-dark:hover, .link-dark:focus { - color: #1a1e21; -} - -.ratio { - position: relative; - width: 100%; -} -.ratio::before { - display: block; - padding-top: var(--aspect-ratio); - content: ""; -} -.ratio > * { - position: absolute; - top: 0; - left: 0; - width: 100%; - height: 100%; -} - -.ratio-1x1 { - --aspect-ratio: 100%; -} - -.ratio-4x3 { - --aspect-ratio: calc(3 / 4 * 100%); -} - -.ratio-16x9 { - --aspect-ratio: calc(9 / 16 * 100%); -} - -.ratio-21x9 { - --aspect-ratio: calc(9 / 21 * 100%); -} - -.fixed-top { - position: fixed; - top: 0; - right: 0; - left: 0; - z-index: 1030; -} - -.fixed-bottom { - position: fixed; - right: 0; - bottom: 0; - left: 0; - z-index: 1030; -} - -.sticky-top { - position: sticky; - top: 0; - z-index: 1020; -} - -@media (min-width: 576px) { - .sticky-sm-top { - position: sticky; - top: 0; - z-index: 1020; - } -} -@media (min-width: 768px) { - .sticky-md-top { - position: sticky; - top: 0; - z-index: 1020; - } -} -@media (min-width: 992px) { - .sticky-lg-top { - position: sticky; - top: 0; - z-index: 1020; - } -} -@media (min-width: 1200px) { - .sticky-xl-top { - position: sticky; - top: 0; - z-index: 1020; - } -} -@media (min-width: 1400px) { - .sticky-xxl-top { - position: sticky; - top: 0; - z-index: 1020; - } -} -.visually-hidden, -.visually-hidden-focusable:not(:focus):not(:focus-within) { - position: absolute !important; - width: 1px !important; - height: 1px !important; - padding: 0 !important; - margin: -1px !important; - overflow: hidden !important; - clip: rect(0, 0, 0, 0) !important; - white-space: nowrap !important; - border: 0 !important; -} - -.stretched-link::after { - position: absolute; - top: 0; - right: 0; - bottom: 0; - left: 0; - z-index: 1; - content: ""; -} - -.text-truncate { - overflow: hidden; - text-overflow: ellipsis; - white-space: nowrap; -} - -.align-baseline { - vertical-align: baseline !important; -} - -.align-top { - vertical-align: top !important; -} - -.align-middle { - vertical-align: middle !important; -} - -.align-bottom { - vertical-align: bottom !important; -} - -.align-text-bottom { - vertical-align: text-bottom !important; -} - -.align-text-top { - vertical-align: text-top !important; -} - -.float-start { - float: left !important; -} - -.float-end { - float: right !important; -} - -.float-none { - float: none !important; -} - -.overflow-auto { - overflow: auto !important; -} - -.overflow-hidden { - overflow: hidden !important; -} - -.overflow-visible { - overflow: visible !important; -} - -.overflow-scroll { - overflow: scroll !important; -} - -.d-inline { - display: inline !important; -} - -.d-inline-block { - display: inline-block !important; -} - -.d-block { - display: block !important; -} - -.d-grid { - display: grid !important; -} - -.d-table { - display: table !important; -} - -.d-table-row { - display: table-row !important; -} - -.d-table-cell { - display: table-cell !important; -} - -.d-flex { - display: flex !important; -} - -.d-inline-flex { - display: inline-flex !important; -} - -.d-none { - display: none !important; -} - -.shadow { - box-shadow: 0 0.5rem 1rem rgba(0, 0, 0, 0.15) !important; -} - -.shadow-sm { - box-shadow: 0 0.125rem 0.25rem rgba(0, 0, 0, 0.075) !important; -} - -.shadow-lg { - box-shadow: 0 1rem 3rem rgba(0, 0, 0, 0.175) !important; -} - -.shadow-none { - box-shadow: none !important; -} - -.position-static { - position: static !important; -} - -.position-relative { - position: relative !important; -} - -.position-absolute { - position: absolute !important; -} - -.position-fixed { - position: fixed !important; -} - -.position-sticky { - position: sticky !important; -} - -.top-0 { - top: 0 !important; -} - -.top-50 { - top: 50% !important; -} - -.top-100 { - top: 100% !important; -} - -.bottom-0 { - bottom: 0 !important; -} - -.bottom-50 { - bottom: 50% !important; -} - -.bottom-100 { - bottom: 100% !important; -} - -.start-0 { - left: 0 !important; -} - -.start-50 { - left: 50% !important; -} - -.start-100 { - left: 100% !important; -} - -.end-0 { - right: 0 !important; -} - -.end-50 { - right: 50% !important; -} - -.end-100 { - right: 100% !important; -} - -.translate-middle { - transform: translate(-50%, -50%) !important; -} - -.translate-middle-x { - transform: translateX(-50%) !important; -} - -.translate-middle-y { - transform: translateY(-50%) !important; -} - -.border { - border: 1px solid #dee2e6 !important; -} - -.border-0 { - border: 0 !important; -} - -.border-top { - border-top: 1px solid #dee2e6 !important; -} - -.border-top-0 { - border-top: 0 !important; -} - -.border-end { - border-right: 1px solid #dee2e6 !important; -} - -.border-end-0 { - border-right: 0 !important; -} - -.border-bottom { - border-bottom: 1px solid #dee2e6 !important; -} - -.border-bottom-0 { - border-bottom: 0 !important; -} - -.border-start { - border-left: 1px solid #dee2e6 !important; -} - -.border-start-0 { - border-left: 0 !important; -} - -.border-primary { - border-color: #40B4E5 !important; -} - -.border-secondary { - border-color: #8A8A8D !important; -} - -.border-success { - border-color: #00833E !important; -} - -.border-info { - border-color: #40B4E5 !important; -} - -.border-warning { - border-color: #00833E !important; -} - -.border-danger { - border-color: #CF0A2C !important; -} - -.border-light { - border-color: #ffffff !important; -} - -.border-dark { - border-color: #000000 !important; -} - -.border-white { - border-color: #fff !important; -} - -.border-1 { - border-width: 1px !important; -} - -.border-2 { - border-width: 2px !important; -} - -.border-3 { - border-width: 3px !important; -} - -.border-4 { - border-width: 4px !important; -} - -.border-5 { - border-width: 5px !important; -} - -.w-25 { - width: 25% !important; -} - -.w-50 { - width: 50% !important; -} - -.w-75 { - width: 75% !important; -} - -.w-100 { - width: 100% !important; -} - -.w-auto { - width: auto !important; -} - -.mw-100 { - max-width: 100% !important; -} - -.vw-100 { - width: 100vw !important; -} - -.min-vw-100 { - min-width: 100vw !important; -} - -.h-25 { - height: 25% !important; -} - -.h-50 { - height: 50% !important; -} - -.h-75 { - height: 75% !important; -} - -.h-100 { - height: 100% !important; -} - -.h-auto { - height: auto !important; -} - -.mh-100 { - max-height: 100% !important; -} - -.vh-100 { - height: 100vh !important; -} - -.min-vh-100 { - min-height: 100vh !important; -} - -.flex-fill { - flex: 1 1 auto !important; -} - -.flex-row { - flex-direction: row !important; -} - -.flex-column { - flex-direction: column !important; -} - -.flex-row-reverse { - flex-direction: row-reverse !important; -} - -.flex-column-reverse { - flex-direction: column-reverse !important; -} - -.flex-grow-0 { - flex-grow: 0 !important; -} - -.flex-grow-1 { - flex-grow: 1 !important; -} - -.flex-shrink-0 { - flex-shrink: 0 !important; -} - -.flex-shrink-1 { - flex-shrink: 1 !important; -} - -.flex-wrap { - flex-wrap: wrap !important; -} - -.flex-nowrap { - flex-wrap: nowrap !important; -} - -.flex-wrap-reverse { - flex-wrap: wrap-reverse !important; -} - -.gap-0 { - gap: 0 !important; -} - -.gap-1 { - gap: 0.25rem !important; -} - -.gap-2 { - gap: 0.5rem !important; -} - -.gap-3 { - gap: 1rem !important; -} - -.gap-4 { - gap: 1.5rem !important; -} - -.gap-5 { - gap: 3rem !important; -} - -.justify-content-start { - justify-content: flex-start !important; -} - -.justify-content-end { - justify-content: flex-end !important; -} - -.justify-content-center { - justify-content: center !important; -} - -.justify-content-between { - justify-content: space-between !important; -} - -.justify-content-around { - justify-content: space-around !important; -} - -.justify-content-evenly { - justify-content: space-evenly !important; -} - -.align-items-start { - align-items: flex-start !important; -} - -.align-items-end { - align-items: flex-end !important; -} - -.align-items-center { - align-items: center !important; -} - -.align-items-baseline { - align-items: baseline !important; -} - -.align-items-stretch { - align-items: stretch !important; -} - -.align-content-start { - align-content: flex-start !important; -} - -.align-content-end { - align-content: flex-end !important; -} - -.align-content-center { - align-content: center !important; -} - -.align-content-between { - align-content: space-between !important; -} - -.align-content-around { - align-content: space-around !important; -} - -.align-content-stretch { - align-content: stretch !important; -} - -.align-self-auto { - align-self: auto !important; -} - -.align-self-start { - align-self: flex-start !important; -} - -.align-self-end { - align-self: flex-end !important; -} - -.align-self-center { - align-self: center !important; -} - -.align-self-baseline { - align-self: baseline !important; -} - -.align-self-stretch { - align-self: stretch !important; -} - -.order-first { - order: -1 !important; -} - -.order-0 { - order: 0 !important; -} - -.order-1 { - order: 1 !important; -} - -.order-2 { - order: 2 !important; -} - -.order-3 { - order: 3 !important; -} - -.order-4 { - order: 4 !important; -} - -.order-5 { - order: 5 !important; -} - -.order-last { - order: 6 !important; -} - -.m-0 { - margin: 0 !important; -} - -.m-1 { - margin: 0.25rem !important; -} - -.m-2 { - margin: 0.5rem !important; -} - -.m-3 { - margin: 1rem !important; -} - -.m-4 { - margin: 1.5rem !important; -} - -.m-5 { - margin: 3rem !important; -} - -.m-auto { - margin: auto !important; -} - -.mx-0 { - margin-right: 0 !important; - margin-left: 0 !important; -} - -.mx-1 { - margin-right: 0.25rem !important; - margin-left: 0.25rem !important; -} - -.mx-2 { - margin-right: 0.5rem !important; - margin-left: 0.5rem !important; -} - -.mx-3 { - margin-right: 1rem !important; - margin-left: 1rem !important; -} - -.mx-4 { - margin-right: 1.5rem !important; - margin-left: 1.5rem !important; -} - -.mx-5 { - margin-right: 3rem !important; - margin-left: 3rem !important; -} - -.mx-auto { - margin-right: auto !important; - margin-left: auto !important; -} - -.my-0 { - margin-top: 0 !important; - margin-bottom: 0 !important; -} - -.my-1 { - margin-top: 0.25rem !important; - margin-bottom: 0.25rem !important; -} - -.my-2 { - margin-top: 0.5rem !important; - margin-bottom: 0.5rem !important; -} - -.my-3 { - margin-top: 1rem !important; - margin-bottom: 1rem !important; -} - -.my-4 { - margin-top: 1.5rem !important; - margin-bottom: 1.5rem !important; -} - -.my-5 { - margin-top: 3rem !important; - margin-bottom: 3rem !important; -} - -.my-auto { - margin-top: auto !important; - margin-bottom: auto !important; -} - -.mt-0 { - margin-top: 0 !important; -} - -.mt-1 { - margin-top: 0.25rem !important; -} - -.mt-2 { - margin-top: 0.5rem !important; -} - -.mt-3 { - margin-top: 1rem !important; -} - -.mt-4 { - margin-top: 1.5rem !important; -} - -.mt-5 { - margin-top: 3rem !important; -} - -.mt-auto { - margin-top: auto !important; -} - -.me-0 { - margin-right: 0 !important; -} - -.me-1 { - margin-right: 0.25rem !important; -} - -.me-2 { - margin-right: 0.5rem !important; -} - -.me-3 { - margin-right: 1rem !important; -} - -.me-4 { - margin-right: 1.5rem !important; -} - -.me-5 { - margin-right: 3rem !important; -} - -.me-auto { - margin-right: auto !important; -} - -.mb-0 { - margin-bottom: 0 !important; -} - -.mb-1 { - margin-bottom: 0.25rem !important; -} - -.mb-2 { - margin-bottom: 0.5rem !important; -} - -.mb-3 { - margin-bottom: 1rem !important; -} - -.mb-4 { - margin-bottom: 1.5rem !important; -} - -.mb-5 { - margin-bottom: 3rem !important; -} - -.mb-auto { - margin-bottom: auto !important; -} - -.ms-0 { - margin-left: 0 !important; -} - -.ms-1 { - margin-left: 0.25rem !important; -} - -.ms-2 { - margin-left: 0.5rem !important; -} - -.ms-3 { - margin-left: 1rem !important; -} - -.ms-4 { - margin-left: 1.5rem !important; -} - -.ms-5 { - margin-left: 3rem !important; -} - -.ms-auto { - margin-left: auto !important; -} - -.p-0 { - padding: 0 !important; -} - -.p-1 { - padding: 0.25rem !important; -} - -.p-2 { - padding: 0.5rem !important; -} - -.p-3 { - padding: 1rem !important; -} - -.p-4 { - padding: 1.5rem !important; -} - -.p-5 { - padding: 3rem !important; -} - -.px-0 { - padding-right: 0 !important; - padding-left: 0 !important; -} - -.px-1 { - padding-right: 0.25rem !important; - padding-left: 0.25rem !important; -} - -.px-2 { - padding-right: 0.5rem !important; - padding-left: 0.5rem !important; -} - -.px-3 { - padding-right: 1rem !important; - padding-left: 1rem !important; -} - -.px-4 { - padding-right: 1.5rem !important; - padding-left: 1.5rem !important; -} - -.px-5 { - padding-right: 3rem !important; - padding-left: 3rem !important; -} - -.py-0 { - padding-top: 0 !important; - padding-bottom: 0 !important; -} - -.py-1 { - padding-top: 0.25rem !important; - padding-bottom: 0.25rem !important; -} - -.py-2 { - padding-top: 0.5rem !important; - padding-bottom: 0.5rem !important; -} - -.py-3 { - padding-top: 1rem !important; - padding-bottom: 1rem !important; -} - -.py-4 { - padding-top: 1.5rem !important; - padding-bottom: 1.5rem !important; -} - -.py-5 { - padding-top: 3rem !important; - padding-bottom: 3rem !important; -} - -.pt-0 { - padding-top: 0 !important; -} - -.pt-1 { - padding-top: 0.25rem !important; -} - -.pt-2 { - padding-top: 0.5rem !important; -} - -.pt-3 { - padding-top: 1rem !important; -} - -.pt-4 { - padding-top: 1.5rem !important; -} - -.pt-5 { - padding-top: 3rem !important; -} - -.pe-0 { - padding-right: 0 !important; -} - -.pe-1 { - padding-right: 0.25rem !important; -} - -.pe-2 { - padding-right: 0.5rem !important; -} - -.pe-3 { - padding-right: 1rem !important; -} - -.pe-4 { - padding-right: 1.5rem !important; -} - -.pe-5 { - padding-right: 3rem !important; -} - -.pb-0 { - padding-bottom: 0 !important; -} - -.pb-1 { - padding-bottom: 0.25rem !important; -} - -.pb-2 { - padding-bottom: 0.5rem !important; -} - -.pb-3 { - padding-bottom: 1rem !important; -} - -.pb-4 { - padding-bottom: 1.5rem !important; -} - -.pb-5 { - padding-bottom: 3rem !important; -} - -.ps-0 { - padding-left: 0 !important; -} - -.ps-1 { - padding-left: 0.25rem !important; -} - -.ps-2 { - padding-left: 0.5rem !important; -} - -.ps-3 { - padding-left: 1rem !important; -} - -.ps-4 { - padding-left: 1.5rem !important; -} - -.ps-5 { - padding-left: 3rem !important; -} - -.font-monospace { - font-family: var(--font-monospace) !important; -} - -.fs-1 { - font-size: calc(1.375rem + 1.5vw) !important; -} - -.fs-2 { - font-size: calc(1.325rem + 0.9vw) !important; -} - -.fs-3 { - font-size: calc(1.3rem + 0.6vw) !important; -} - -.fs-4 { - font-size: calc(1.275rem + 0.3vw) !important; -} - -.fs-5 { - font-size: 1.25rem !important; -} - -.fs-6 { - font-size: 1rem !important; -} - -.fst-italic { - font-style: italic !important; -} - -.fst-normal { - font-style: normal !important; -} - -.fw-light { - font-weight: 300 !important; -} - -.fw-lighter { - font-weight: lighter !important; -} - -.fw-normal { - font-weight: 400 !important; -} - -.fw-bold { - font-weight: 700 !important; -} - -.fw-bolder { - font-weight: bolder !important; -} - -.lh-1 { - line-height: 1 !important; -} - -.lh-sm { - line-height: 1.25 !important; -} - -.lh-base { - line-height: 1.5 !important; -} - -.lh-lg { - line-height: 2 !important; -} - -.text-start { - text-align: left !important; -} - -.text-end { - text-align: right !important; -} - -.text-center { - text-align: center !important; -} - -.text-decoration-none { - text-decoration: none !important; -} - -.title-text-center { - text-align: center !important; - color: #fff !important; - font-family: "Indie Flower"; - margin-left: 40px; - margin-top: 5px; -} - -.text-decoration-underline { - text-decoration: underline !important; -} - -.text-decoration-line-through { - text-decoration: line-through !important; -} - -.text-lowercase { - text-transform: lowercase !important; -} - -.text-uppercase { - text-transform: uppercase !important; -} - -.text-capitalize { - text-transform: capitalize !important; -} - -.text-wrap { - white-space: normal !important; -} - -.text-nowrap { - white-space: nowrap !important; -} - -/* rtl:begin:remove */ -.text-break { - word-wrap: break-word !important; - word-break: break-word !important; -} - -/* rtl:end:remove */ -.text-primary { - color: #40B4E5 !important; -} - -.text-secondary { - color: #8A8A8D !important; -} - -.text-success { - color: #00833E !important; -} - -.text-info { - color: #40B4E5 !important; -} - -.text-warning { - color: #00833E !important; -} - -.text-danger { - color: #CF0A2C !important; -} - -.text-light { - color: #ffffff !important; -} - -.text-dark { - color: #000000 !important; -} - -.text-white { - color: #fff !important; -} - -.text-body { - color: #000000 !important; -} - -.text-muted { - color: #8A8A8D !important; -} - -.text-black-50 { - color: rgba(0, 0, 0, 0.5) !important; -} - -.text-white-50 { - color: rgba(255, 255, 255, 0.5) !important; -} - -.text-reset { - color: inherit !important; -} - -.bg-primary { - background-color: #40B4E5 !important; -} - -.bg-secondary { - background-color: #8A8A8D !important; -} - -.bg-success { - background-color: #00833E !important; -} - -.bg-info { - background-color: #40B4E5 !important; -} - -.bg-warning { - background-color: #00833E !important; -} - -.bg-danger { - background-color: #CF0A2C !important; -} - -.bg-light { - background-color: #ffffff !important; -} - -/* Custom backgrounds */ -.bg-navy { - background-color: #003A70 !important; -} - -.bg-green { - background-color: #00833E !important; -} - -.bg-lblue { - background-color: #40B4E5 !important; -} - -.bg-llblue { - background-color: #b0e1f5 !important; -} - -.bg-dark { - background-color: #000000 !important; -} - -.bg-body { - background-color: #fff !important; -} - -.bg-white { - background-color: #fff !important; -} - -.bg-transparent { - background-color: transparent !important; -} - -.bg-gradient { - background-image: var(--gradient) !important; -} - -.user-select-all { - -webkit-user-select: all !important; - -moz-user-select: all !important; - user-select: all !important; -} - -.user-select-auto { - -webkit-user-select: auto !important; - -moz-user-select: auto !important; - -ms-user-select: auto !important; - user-select: auto !important; -} - -.user-select-none { - -webkit-user-select: none !important; - -moz-user-select: none !important; - -ms-user-select: none !important; - user-select: none !important; -} - -.pe-none { - pointer-events: none !important; -} - -.pe-auto { - pointer-events: auto !important; -} - -.rounded { - border-radius: 0.25rem !important; -} - -.rounded-0 { - border-radius: 0 !important; -} - -.rounded-1 { - border-radius: 0.2rem !important; -} - -.rounded-2 { - border-radius: 0.25rem !important; -} - -.rounded-3 { - border-radius: 0.3rem !important; -} - -.rounded-circle { - border-radius: 50% !important; -} - -.rounded-pill { - border-radius: 50rem !important; -} - -.rounded-top { - border-top-left-radius: 0.25rem !important; - border-top-right-radius: 0.25rem !important; -} - -.rounded-end { - border-top-right-radius: 0.25rem !important; - border-bottom-right-radius: 0.25rem !important; -} - -.rounded-bottom { - border-bottom-right-radius: 0.25rem !important; - border-bottom-left-radius: 0.25rem !important; -} - -.rounded-start { - border-bottom-left-radius: 0.25rem !important; - border-top-left-radius: 0.25rem !important; -} - -.visible { - visibility: visible !important; -} - -.invisible { - visibility: hidden !important; -} - -@media (min-width: 576px) { - .float-sm-start { - float: left !important; - } - - .float-sm-end { - float: right !important; - } - - .float-sm-none { - float: none !important; - } - - .d-sm-inline { - display: inline !important; - } - - .d-sm-inline-block { - display: inline-block !important; - } - - .d-sm-block { - display: block !important; - } - - .d-sm-grid { - display: grid !important; - } - - .d-sm-table { - display: table !important; - } - - .d-sm-table-row { - display: table-row !important; - } - - .d-sm-table-cell { - display: table-cell !important; - } - - .d-sm-flex { - display: flex !important; - } - - .d-sm-inline-flex { - display: inline-flex !important; - } - - .d-sm-none { - display: none !important; - } - - .flex-sm-fill { - flex: 1 1 auto !important; - } - - .flex-sm-row { - flex-direction: row !important; - } - - .flex-sm-column { - flex-direction: column !important; - } - - .flex-sm-row-reverse { - flex-direction: row-reverse !important; - } - - .flex-sm-column-reverse { - flex-direction: column-reverse !important; - } - - .flex-sm-grow-0 { - flex-grow: 0 !important; - } - - .flex-sm-grow-1 { - flex-grow: 1 !important; - } - - .flex-sm-shrink-0 { - flex-shrink: 0 !important; - } - - .flex-sm-shrink-1 { - flex-shrink: 1 !important; - } - - .flex-sm-wrap { - flex-wrap: wrap !important; - } - - .flex-sm-nowrap { - flex-wrap: nowrap !important; - } - - .flex-sm-wrap-reverse { - flex-wrap: wrap-reverse !important; - } - - .gap-sm-0 { - gap: 0 !important; - } - - .gap-sm-1 { - gap: 0.25rem !important; - } - - .gap-sm-2 { - gap: 0.5rem !important; - } - - .gap-sm-3 { - gap: 1rem !important; - } - - .gap-sm-4 { - gap: 1.5rem !important; - } - - .gap-sm-5 { - gap: 3rem !important; - } - - .justify-content-sm-start { - justify-content: flex-start !important; - } - - .justify-content-sm-end { - justify-content: flex-end !important; - } - - .justify-content-sm-center { - justify-content: center !important; - } - - .justify-content-sm-between { - justify-content: space-between !important; - } - - .justify-content-sm-around { - justify-content: space-around !important; - } - - .justify-content-sm-evenly { - justify-content: space-evenly !important; - } - - .align-items-sm-start { - align-items: flex-start !important; - } - - .align-items-sm-end { - align-items: flex-end !important; - } - - .align-items-sm-center { - align-items: center !important; - } - - .align-items-sm-baseline { - align-items: baseline !important; - } - - .align-items-sm-stretch { - align-items: stretch !important; - } - - .align-content-sm-start { - align-content: flex-start !important; - } - - .align-content-sm-end { - align-content: flex-end !important; - } - - .align-content-sm-center { - align-content: center !important; - } - - .align-content-sm-between { - align-content: space-between !important; - } - - .align-content-sm-around { - align-content: space-around !important; - } - - .align-content-sm-stretch { - align-content: stretch !important; - } - - .align-self-sm-auto { - align-self: auto !important; - } - - .align-self-sm-start { - align-self: flex-start !important; - } - - .align-self-sm-end { - align-self: flex-end !important; - } - - .align-self-sm-center { - align-self: center !important; - } - - .align-self-sm-baseline { - align-self: baseline !important; - } - - .align-self-sm-stretch { - align-self: stretch !important; - } - - .order-sm-first { - order: -1 !important; - } - - .order-sm-0 { - order: 0 !important; - } - - .order-sm-1 { - order: 1 !important; - } - - .order-sm-2 { - order: 2 !important; - } - - .order-sm-3 { - order: 3 !important; - } - - .order-sm-4 { - order: 4 !important; - } - - .order-sm-5 { - order: 5 !important; - } - - .order-sm-last { - order: 6 !important; - } - - .m-sm-0 { - margin: 0 !important; - } - - .m-sm-1 { - margin: 0.25rem !important; - } - - .m-sm-2 { - margin: 0.5rem !important; - } - - .m-sm-3 { - margin: 1rem !important; - } - - .m-sm-4 { - margin: 1.5rem !important; - } - - .m-sm-5 { - margin: 3rem !important; - } - - .m-sm-auto { - margin: auto !important; - } - - .mx-sm-0 { - margin-right: 0 !important; - margin-left: 0 !important; - } - - .mx-sm-1 { - margin-right: 0.25rem !important; - margin-left: 0.25rem !important; - } - - .mx-sm-2 { - margin-right: 0.5rem !important; - margin-left: 0.5rem !important; - } - - .mx-sm-3 { - margin-right: 1rem !important; - margin-left: 1rem !important; - } - - .mx-sm-4 { - margin-right: 1.5rem !important; - margin-left: 1.5rem !important; - } - - .mx-sm-5 { - margin-right: 3rem !important; - margin-left: 3rem !important; - } - - .mx-sm-auto { - margin-right: auto !important; - margin-left: auto !important; - } - - .my-sm-0 { - margin-top: 0 !important; - margin-bottom: 0 !important; - } - - .my-sm-1 { - margin-top: 0.25rem !important; - margin-bottom: 0.25rem !important; - } - - .my-sm-2 { - margin-top: 0.5rem !important; - margin-bottom: 0.5rem !important; - } - - .my-sm-3 { - margin-top: 1rem !important; - margin-bottom: 1rem !important; - } - - .my-sm-4 { - margin-top: 1.5rem !important; - margin-bottom: 1.5rem !important; - } - - .my-sm-5 { - margin-top: 3rem !important; - margin-bottom: 3rem !important; - } - - .my-sm-auto { - margin-top: auto !important; - margin-bottom: auto !important; - } - - .mt-sm-0 { - margin-top: 0 !important; - } - - .mt-sm-1 { - margin-top: 0.25rem !important; - } - - .mt-sm-2 { - margin-top: 0.5rem !important; - } - - .mt-sm-3 { - margin-top: 1rem !important; - } - - .mt-sm-4 { - margin-top: 1.5rem !important; - } - - .mt-sm-5 { - margin-top: 3rem !important; - } - - .mt-sm-auto { - margin-top: auto !important; - } - - .me-sm-0 { - margin-right: 0 !important; - } - - .me-sm-1 { - margin-right: 0.25rem !important; - } - - .me-sm-2 { - margin-right: 0.5rem !important; - } - - .me-sm-3 { - margin-right: 1rem !important; - } - - .me-sm-4 { - margin-right: 1.5rem !important; - } - - .me-sm-5 { - margin-right: 3rem !important; - } - - .me-sm-auto { - margin-right: auto !important; - } - - .mb-sm-0 { - margin-bottom: 0 !important; - } - - .mb-sm-1 { - margin-bottom: 0.25rem !important; - } - - .mb-sm-2 { - margin-bottom: 0.5rem !important; - } - - .mb-sm-3 { - margin-bottom: 1rem !important; - } - - .mb-sm-4 { - margin-bottom: 1.5rem !important; - } - - .mb-sm-5 { - margin-bottom: 3rem !important; - } - - .mb-sm-auto { - margin-bottom: auto !important; - } - - .ms-sm-0 { - margin-left: 0 !important; - } - - .ms-sm-1 { - margin-left: 0.25rem !important; - } - - .ms-sm-2 { - margin-left: 0.5rem !important; - } - - .ms-sm-3 { - margin-left: 1rem !important; - } - - .ms-sm-4 { - margin-left: 1.5rem !important; - } - - .ms-sm-5 { - margin-left: 3rem !important; - } - - .ms-sm-auto { - margin-left: auto !important; - } - - .p-sm-0 { - padding: 0 !important; - } - - .p-sm-1 { - padding: 0.25rem !important; - } - - .p-sm-2 { - padding: 0.5rem !important; - } - - .p-sm-3 { - padding: 1rem !important; - } - - .p-sm-4 { - padding: 1.5rem !important; - } - - .p-sm-5 { - padding: 3rem !important; - } - - .px-sm-0 { - padding-right: 0 !important; - padding-left: 0 !important; - } - - .px-sm-1 { - padding-right: 0.25rem !important; - padding-left: 0.25rem !important; - } - - .px-sm-2 { - padding-right: 0.5rem !important; - padding-left: 0.5rem !important; - } - - .px-sm-3 { - padding-right: 1rem !important; - padding-left: 1rem !important; - } - - .px-sm-4 { - padding-right: 1.5rem !important; - padding-left: 1.5rem !important; - } - - .px-sm-5 { - padding-right: 3rem !important; - padding-left: 3rem !important; - } - - .py-sm-0 { - padding-top: 0 !important; - padding-bottom: 0 !important; - } - - .py-sm-1 { - padding-top: 0.25rem !important; - padding-bottom: 0.25rem !important; - } - - .py-sm-2 { - padding-top: 0.5rem !important; - padding-bottom: 0.5rem !important; - } - - .py-sm-3 { - padding-top: 1rem !important; - padding-bottom: 1rem !important; - } - - .py-sm-4 { - padding-top: 1.5rem !important; - padding-bottom: 1.5rem !important; - } - - .py-sm-5 { - padding-top: 3rem !important; - padding-bottom: 3rem !important; - } - - .pt-sm-0 { - padding-top: 0 !important; - } - - .pt-sm-1 { - padding-top: 0.25rem !important; - } - - .pt-sm-2 { - padding-top: 0.5rem !important; - } - - .pt-sm-3 { - padding-top: 1rem !important; - } - - .pt-sm-4 { - padding-top: 1.5rem !important; - } - - .pt-sm-5 { - padding-top: 3rem !important; - } - - .pe-sm-0 { - padding-right: 0 !important; - } - - .pe-sm-1 { - padding-right: 0.25rem !important; - } - - .pe-sm-2 { - padding-right: 0.5rem !important; - } - - .pe-sm-3 { - padding-right: 1rem !important; - } - - .pe-sm-4 { - padding-right: 1.5rem !important; - } - - .pe-sm-5 { - padding-right: 3rem !important; - } - - .pb-sm-0 { - padding-bottom: 0 !important; - } - - .pb-sm-1 { - padding-bottom: 0.25rem !important; - } - - .pb-sm-2 { - padding-bottom: 0.5rem !important; - } - - .pb-sm-3 { - padding-bottom: 1rem !important; - } - - .pb-sm-4 { - padding-bottom: 1.5rem !important; - } - - .pb-sm-5 { - padding-bottom: 3rem !important; - } - - .ps-sm-0 { - padding-left: 0 !important; - } - - .ps-sm-1 { - padding-left: 0.25rem !important; - } - - .ps-sm-2 { - padding-left: 0.5rem !important; - } - - .ps-sm-3 { - padding-left: 1rem !important; - } - - .ps-sm-4 { - padding-left: 1.5rem !important; - } - - .ps-sm-5 { - padding-left: 3rem !important; - } - - .text-sm-start { - text-align: left !important; - } - - .text-sm-end { - text-align: right !important; - } - - .text-sm-center { - text-align: center !important; - } -} -@media (min-width: 768px) { - .float-md-start { - float: left !important; - } - - .float-md-end { - float: right !important; - } - - .float-md-none { - float: none !important; - } - - .d-md-inline { - display: inline !important; - } - - .d-md-inline-block { - display: inline-block !important; - } - - .d-md-block { - display: block !important; - } - - .d-md-grid { - display: grid !important; - } - - .d-md-table { - display: table !important; - } - - .d-md-table-row { - display: table-row !important; - } - - .d-md-table-cell { - display: table-cell !important; - } - - .d-md-flex { - display: flex !important; - } - - .d-md-inline-flex { - display: inline-flex !important; - } - - .d-md-none { - display: none !important; - } - - .flex-md-fill { - flex: 1 1 auto !important; - } - - .flex-md-row { - flex-direction: row !important; - } - - .flex-md-column { - flex-direction: column !important; - } - - .flex-md-row-reverse { - flex-direction: row-reverse !important; - } - - .flex-md-column-reverse { - flex-direction: column-reverse !important; - } - - .flex-md-grow-0 { - flex-grow: 0 !important; - } - - .flex-md-grow-1 { - flex-grow: 1 !important; - } - - .flex-md-shrink-0 { - flex-shrink: 0 !important; - } - - .flex-md-shrink-1 { - flex-shrink: 1 !important; - } - - .flex-md-wrap { - flex-wrap: wrap !important; - } - - .flex-md-nowrap { - flex-wrap: nowrap !important; - } - - .flex-md-wrap-reverse { - flex-wrap: wrap-reverse !important; - } - - .gap-md-0 { - gap: 0 !important; - } - - .gap-md-1 { - gap: 0.25rem !important; - } - - .gap-md-2 { - gap: 0.5rem !important; - } - - .gap-md-3 { - gap: 1rem !important; - } - - .gap-md-4 { - gap: 1.5rem !important; - } - - .gap-md-5 { - gap: 3rem !important; - } - - .justify-content-md-start { - justify-content: flex-start !important; - } - - .justify-content-md-end { - justify-content: flex-end !important; - } - - .justify-content-md-center { - justify-content: center !important; - } - - .justify-content-md-between { - justify-content: space-between !important; - } - - .justify-content-md-around { - justify-content: space-around !important; - } - - .justify-content-md-evenly { - justify-content: space-evenly !important; - } - - .align-items-md-start { - align-items: flex-start !important; - } - - .align-items-md-end { - align-items: flex-end !important; - } - - .align-items-md-center { - align-items: center !important; - } - - .align-items-md-baseline { - align-items: baseline !important; - } - - .align-items-md-stretch { - align-items: stretch !important; - } - - .align-content-md-start { - align-content: flex-start !important; - } - - .align-content-md-end { - align-content: flex-end !important; - } - - .align-content-md-center { - align-content: center !important; - } - - .align-content-md-between { - align-content: space-between !important; - } - - .align-content-md-around { - align-content: space-around !important; - } - - .align-content-md-stretch { - align-content: stretch !important; - } - - .align-self-md-auto { - align-self: auto !important; - } - - .align-self-md-start { - align-self: flex-start !important; - } - - .align-self-md-end { - align-self: flex-end !important; - } - - .align-self-md-center { - align-self: center !important; - } - - .align-self-md-baseline { - align-self: baseline !important; - } - - .align-self-md-stretch { - align-self: stretch !important; - } - - .order-md-first { - order: -1 !important; - } - - .order-md-0 { - order: 0 !important; - } - - .order-md-1 { - order: 1 !important; - } - - .order-md-2 { - order: 2 !important; - } - - .order-md-3 { - order: 3 !important; - } - - .order-md-4 { - order: 4 !important; - } - - .order-md-5 { - order: 5 !important; - } - - .order-md-last { - order: 6 !important; - } - - .m-md-0 { - margin: 0 !important; - } - - .m-md-1 { - margin: 0.25rem !important; - } - - .m-md-2 { - margin: 0.5rem !important; - } - - .m-md-3 { - margin: 1rem !important; - } - - .m-md-4 { - margin: 1.5rem !important; - } - - .m-md-5 { - margin: 3rem !important; - } - - .m-md-auto { - margin: auto !important; - } - - .mx-md-0 { - margin-right: 0 !important; - margin-left: 0 !important; - } - - .mx-md-1 { - margin-right: 0.25rem !important; - margin-left: 0.25rem !important; - } - - .mx-md-2 { - margin-right: 0.5rem !important; - margin-left: 0.5rem !important; - } - - .mx-md-3 { - margin-right: 1rem !important; - margin-left: 1rem !important; - } - - .mx-md-4 { - margin-right: 1.5rem !important; - margin-left: 1.5rem !important; - } - - .mx-md-5 { - margin-right: 3rem !important; - margin-left: 3rem !important; - } - - .mx-md-auto { - margin-right: auto !important; - margin-left: auto !important; - } - - .my-md-0 { - margin-top: 0 !important; - margin-bottom: 0 !important; - } - - .my-md-1 { - margin-top: 0.25rem !important; - margin-bottom: 0.25rem !important; - } - - .my-md-2 { - margin-top: 0.5rem !important; - margin-bottom: 0.5rem !important; - } - - .my-md-3 { - margin-top: 1rem !important; - margin-bottom: 1rem !important; - } - - .my-md-4 { - margin-top: 1.5rem !important; - margin-bottom: 1.5rem !important; - } - - .my-md-5 { - margin-top: 3rem !important; - margin-bottom: 3rem !important; - } - - .my-md-auto { - margin-top: auto !important; - margin-bottom: auto !important; - } - - .mt-md-0 { - margin-top: 0 !important; - } - - .mt-md-1 { - margin-top: 0.25rem !important; - } - - .mt-md-2 { - margin-top: 0.5rem !important; - } - - .mt-md-3 { - margin-top: 1rem !important; - } - - .mt-md-4 { - margin-top: 1.5rem !important; - } - - .mt-md-5 { - margin-top: 3rem !important; - } - - .mt-md-auto { - margin-top: auto !important; - } - - .me-md-0 { - margin-right: 0 !important; - } - - .me-md-1 { - margin-right: 0.25rem !important; - } - - .me-md-2 { - margin-right: 0.5rem !important; - } - - .me-md-3 { - margin-right: 1rem !important; - } - - .me-md-4 { - margin-right: 1.5rem !important; - } - - .me-md-5 { - margin-right: 3rem !important; - } - - .me-md-auto { - margin-right: auto !important; - } - - .mb-md-0 { - margin-bottom: 0 !important; - } - - .mb-md-1 { - margin-bottom: 0.25rem !important; - } - - .mb-md-2 { - margin-bottom: 0.5rem !important; - } - - .mb-md-3 { - margin-bottom: 1rem !important; - } - - .mb-md-4 { - margin-bottom: 1.5rem !important; - } - - .mb-md-5 { - margin-bottom: 3rem !important; - } - - .mb-md-auto { - margin-bottom: auto !important; - } - - .ms-md-0 { - margin-left: 0 !important; - } - - .ms-md-1 { - margin-left: 0.25rem !important; - } - - .ms-md-2 { - margin-left: 0.5rem !important; - } - - .ms-md-3 { - margin-left: 1rem !important; - } - - .ms-md-4 { - margin-left: 1.5rem !important; - } - - .ms-md-5 { - margin-left: 3rem !important; - } - - .ms-md-auto { - margin-left: auto !important; - } - - .p-md-0 { - padding: 0 !important; - } - - .p-md-1 { - padding: 0.25rem !important; - } - - .p-md-2 { - padding: 0.5rem !important; - } - - .p-md-3 { - padding: 1rem !important; - } - - .p-md-4 { - padding: 1.5rem !important; - } - - .p-md-5 { - padding: 3rem !important; - } - - .px-md-0 { - padding-right: 0 !important; - padding-left: 0 !important; - } - - .px-md-1 { - padding-right: 0.25rem !important; - padding-left: 0.25rem !important; - } - - .px-md-2 { - padding-right: 0.5rem !important; - padding-left: 0.5rem !important; - } - - .px-md-3 { - padding-right: 1rem !important; - padding-left: 1rem !important; - } - - .px-md-4 { - padding-right: 1.5rem !important; - padding-left: 1.5rem !important; - } - - .px-md-5 { - padding-right: 3rem !important; - padding-left: 3rem !important; - } - - .py-md-0 { - padding-top: 0 !important; - padding-bottom: 0 !important; - } - - .py-md-1 { - padding-top: 0.25rem !important; - padding-bottom: 0.25rem !important; - } - - .py-md-2 { - padding-top: 0.5rem !important; - padding-bottom: 0.5rem !important; - } - - .py-md-3 { - padding-top: 1rem !important; - padding-bottom: 1rem !important; - } - - .py-md-4 { - padding-top: 1.5rem !important; - padding-bottom: 1.5rem !important; - } - - .py-md-5 { - padding-top: 3rem !important; - padding-bottom: 3rem !important; - } - - .pt-md-0 { - padding-top: 0 !important; - } - - .pt-md-1 { - padding-top: 0.25rem !important; - } - - .pt-md-2 { - padding-top: 0.5rem !important; - } - - .pt-md-3 { - padding-top: 1rem !important; - } - - .pt-md-4 { - padding-top: 1.5rem !important; - } - - .pt-md-5 { - padding-top: 3rem !important; - } - - .pe-md-0 { - padding-right: 0 !important; - } - - .pe-md-1 { - padding-right: 0.25rem !important; - } - - .pe-md-2 { - padding-right: 0.5rem !important; - } - - .pe-md-3 { - padding-right: 1rem !important; - } - - .pe-md-4 { - padding-right: 1.5rem !important; - } - - .pe-md-5 { - padding-right: 3rem !important; - } - - .pb-md-0 { - padding-bottom: 0 !important; - } - - .pb-md-1 { - padding-bottom: 0.25rem !important; - } - - .pb-md-2 { - padding-bottom: 0.5rem !important; - } - - .pb-md-3 { - padding-bottom: 1rem !important; - } - - .pb-md-4 { - padding-bottom: 1.5rem !important; - } - - .pb-md-5 { - padding-bottom: 3rem !important; - } - - .ps-md-0 { - padding-left: 0 !important; - } - - .ps-md-1 { - padding-left: 0.25rem !important; - } - - .ps-md-2 { - padding-left: 0.5rem !important; - } - - .ps-md-3 { - padding-left: 1rem !important; - } - - .ps-md-4 { - padding-left: 1.5rem !important; - } - - .ps-md-5 { - padding-left: 3rem !important; - } - - .text-md-start { - text-align: left !important; - } - - .text-md-end { - text-align: right !important; - } - - .text-md-center { - text-align: center !important; - } -} -@media (min-width: 992px) { - .float-lg-start { - float: left !important; - } - - .float-lg-end { - float: right !important; - } - - .float-lg-none { - float: none !important; - } - - .d-lg-inline { - display: inline !important; - } - - .d-lg-inline-block { - display: inline-block !important; - } - - .d-lg-block { - display: block !important; - } - - .d-lg-grid { - display: grid !important; - } - - .d-lg-table { - display: table !important; - } - - .d-lg-table-row { - display: table-row !important; - } - - .d-lg-table-cell { - display: table-cell !important; - } - - .d-lg-flex { - display: flex !important; - } - - .d-lg-inline-flex { - display: inline-flex !important; - } - - .d-lg-none { - display: none !important; - } - - .flex-lg-fill { - flex: 1 1 auto !important; - } - - .flex-lg-row { - flex-direction: row !important; - } - - .flex-lg-column { - flex-direction: column !important; - } - - .flex-lg-row-reverse { - flex-direction: row-reverse !important; - } - - .flex-lg-column-reverse { - flex-direction: column-reverse !important; - } - - .flex-lg-grow-0 { - flex-grow: 0 !important; - } - - .flex-lg-grow-1 { - flex-grow: 1 !important; - } - - .flex-lg-shrink-0 { - flex-shrink: 0 !important; - } - - .flex-lg-shrink-1 { - flex-shrink: 1 !important; - } - - .flex-lg-wrap { - flex-wrap: wrap !important; - } - - .flex-lg-nowrap { - flex-wrap: nowrap !important; - } - - .flex-lg-wrap-reverse { - flex-wrap: wrap-reverse !important; - } - - .gap-lg-0 { - gap: 0 !important; - } - - .gap-lg-1 { - gap: 0.25rem !important; - } - - .gap-lg-2 { - gap: 0.5rem !important; - } - - .gap-lg-3 { - gap: 1rem !important; - } - - .gap-lg-4 { - gap: 1.5rem !important; - } - - .gap-lg-5 { - gap: 3rem !important; - } - - .justify-content-lg-start { - justify-content: flex-start !important; - } - - .justify-content-lg-end { - justify-content: flex-end !important; - } - - .justify-content-lg-center { - justify-content: center !important; - } - - .justify-content-lg-between { - justify-content: space-between !important; - } - - .justify-content-lg-around { - justify-content: space-around !important; - } - - .justify-content-lg-evenly { - justify-content: space-evenly !important; - } - - .align-items-lg-start { - align-items: flex-start !important; - } - - .align-items-lg-end { - align-items: flex-end !important; - } - - .align-items-lg-center { - align-items: center !important; - } - - .align-items-lg-baseline { - align-items: baseline !important; - } - - .align-items-lg-stretch { - align-items: stretch !important; - } - - .align-content-lg-start { - align-content: flex-start !important; - } - - .align-content-lg-end { - align-content: flex-end !important; - } - - .align-content-lg-center { - align-content: center !important; - } - - .align-content-lg-between { - align-content: space-between !important; - } - - .align-content-lg-around { - align-content: space-around !important; - } - - .align-content-lg-stretch { - align-content: stretch !important; - } - - .align-self-lg-auto { - align-self: auto !important; - } - - .align-self-lg-start { - align-self: flex-start !important; - } - - .align-self-lg-end { - align-self: flex-end !important; - } - - .align-self-lg-center { - align-self: center !important; - } - - .align-self-lg-baseline { - align-self: baseline !important; - } - - .align-self-lg-stretch { - align-self: stretch !important; - } - - .order-lg-first { - order: -1 !important; - } - - .order-lg-0 { - order: 0 !important; - } - - .order-lg-1 { - order: 1 !important; - } - - .order-lg-2 { - order: 2 !important; - } - - .order-lg-3 { - order: 3 !important; - } - - .order-lg-4 { - order: 4 !important; - } - - .order-lg-5 { - order: 5 !important; - } - - .order-lg-last { - order: 6 !important; - } - - .m-lg-0 { - margin: 0 !important; - } - - .m-lg-1 { - margin: 0.25rem !important; - } - - .m-lg-2 { - margin: 0.5rem !important; - } - - .m-lg-3 { - margin: 1rem !important; - } - - .m-lg-4 { - margin: 1.5rem !important; - } - - .m-lg-5 { - margin: 3rem !important; - } - - .m-lg-auto { - margin: auto !important; - } - - .mx-lg-0 { - margin-right: 0 !important; - margin-left: 0 !important; - } - - .mx-lg-1 { - margin-right: 0.25rem !important; - margin-left: 0.25rem !important; - } - - .mx-lg-2 { - margin-right: 0.5rem !important; - margin-left: 0.5rem !important; - } - - .mx-lg-3 { - margin-right: 1rem !important; - margin-left: 1rem !important; - } - - .mx-lg-4 { - margin-right: 1.5rem !important; - margin-left: 1.5rem !important; - } - - .mx-lg-5 { - margin-right: 3rem !important; - margin-left: 3rem !important; - } - - .mx-lg-auto { - margin-right: auto !important; - margin-left: auto !important; - } - - .my-lg-0 { - margin-top: 0 !important; - margin-bottom: 0 !important; - } - - .my-lg-1 { - margin-top: 0.25rem !important; - margin-bottom: 0.25rem !important; - } - - .my-lg-2 { - margin-top: 0.5rem !important; - margin-bottom: 0.5rem !important; - } - - .my-lg-3 { - margin-top: 1rem !important; - margin-bottom: 1rem !important; - } - - .my-lg-4 { - margin-top: 1.5rem !important; - margin-bottom: 1.5rem !important; - } - - .my-lg-5 { - margin-top: 3rem !important; - margin-bottom: 3rem !important; - } - - .my-lg-auto { - margin-top: auto !important; - margin-bottom: auto !important; - } - - .mt-lg-0 { - margin-top: 0 !important; - } - - .mt-lg-1 { - margin-top: 0.25rem !important; - } - - .mt-lg-2 { - margin-top: 0.5rem !important; - } - - .mt-lg-3 { - margin-top: 1rem !important; - } - - .mt-lg-4 { - margin-top: 1.5rem !important; - } - - .mt-lg-5 { - margin-top: 3rem !important; - } - - .mt-lg-auto { - margin-top: auto !important; - } - - .me-lg-0 { - margin-right: 0 !important; - } - - .me-lg-1 { - margin-right: 0.25rem !important; - } - - .me-lg-2 { - margin-right: 0.5rem !important; - } - - .me-lg-3 { - margin-right: 1rem !important; - } - - .me-lg-4 { - margin-right: 1.5rem !important; - } - - .me-lg-5 { - margin-right: 3rem !important; - } - - .me-lg-auto { - margin-right: auto !important; - } - - .mb-lg-0 { - margin-bottom: 0 !important; - } - - .mb-lg-1 { - margin-bottom: 0.25rem !important; - } - - .mb-lg-2 { - margin-bottom: 0.5rem !important; - } - - .mb-lg-3 { - margin-bottom: 1rem !important; - } - - .mb-lg-4 { - margin-bottom: 1.5rem !important; - } - - .mb-lg-5 { - margin-bottom: 3rem !important; - } - - .mb-lg-auto { - margin-bottom: auto !important; - } - - .ms-lg-0 { - margin-left: 0 !important; - } - - .ms-lg-1 { - margin-left: 0.25rem !important; - } - - .ms-lg-2 { - margin-left: 0.5rem !important; - } - - .ms-lg-3 { - margin-left: 1rem !important; - } - - .ms-lg-4 { - margin-left: 1.5rem !important; - } - - .ms-lg-5 { - margin-left: 3rem !important; - } - - .ms-lg-auto { - margin-left: auto !important; - } - - .p-lg-0 { - padding: 0 !important; - } - - .p-lg-1 { - padding: 0.25rem !important; - } - - .p-lg-2 { - padding: 0.5rem !important; - } - - .p-lg-3 { - padding: 1rem !important; - } - - .p-lg-4 { - padding: 1.5rem !important; - } - - .p-lg-5 { - padding: 3rem !important; - } - - .px-lg-0 { - padding-right: 0 !important; - padding-left: 0 !important; - } - - .px-lg-1 { - padding-right: 0.25rem !important; - padding-left: 0.25rem !important; - } - - .px-lg-2 { - padding-right: 0.5rem !important; - padding-left: 0.5rem !important; - } - - .px-lg-3 { - padding-right: 1rem !important; - padding-left: 1rem !important; - } - - .px-lg-4 { - padding-right: 1.5rem !important; - padding-left: 1.5rem !important; - } - - .px-lg-5 { - padding-right: 3rem !important; - padding-left: 3rem !important; - } - - .py-lg-0 { - padding-top: 0 !important; - padding-bottom: 0 !important; - } - - .py-lg-1 { - padding-top: 0.25rem !important; - padding-bottom: 0.25rem !important; - } - - .py-lg-2 { - padding-top: 0.5rem !important; - padding-bottom: 0.5rem !important; - } - - .py-lg-3 { - padding-top: 1rem !important; - padding-bottom: 1rem !important; - } - - .py-lg-4 { - padding-top: 1.5rem !important; - padding-bottom: 1.5rem !important; - } - - .py-lg-5 { - padding-top: 3rem !important; - padding-bottom: 3rem !important; - } - - .pt-lg-0 { - padding-top: 0 !important; - } - - .pt-lg-1 { - padding-top: 0.25rem !important; - } - - .pt-lg-2 { - padding-top: 0.5rem !important; - } - - .pt-lg-3 { - padding-top: 1rem !important; - } - - .pt-lg-4 { - padding-top: 1.5rem !important; - } - - .pt-lg-5 { - padding-top: 3rem !important; - } - - .pe-lg-0 { - padding-right: 0 !important; - } - - .pe-lg-1 { - padding-right: 0.25rem !important; - } - - .pe-lg-2 { - padding-right: 0.5rem !important; - } - - .pe-lg-3 { - padding-right: 1rem !important; - } - - .pe-lg-4 { - padding-right: 1.5rem !important; - } - - .pe-lg-5 { - padding-right: 3rem !important; - } - - .pb-lg-0 { - padding-bottom: 0 !important; - } - - .pb-lg-1 { - padding-bottom: 0.25rem !important; - } - - .pb-lg-2 { - padding-bottom: 0.5rem !important; - } - - .pb-lg-3 { - padding-bottom: 1rem !important; - } - - .pb-lg-4 { - padding-bottom: 1.5rem !important; - } - - .pb-lg-5 { - padding-bottom: 3rem !important; - } - - .ps-lg-0 { - padding-left: 0 !important; - } - - .ps-lg-1 { - padding-left: 0.25rem !important; - } - - .ps-lg-2 { - padding-left: 0.5rem !important; - } - - .ps-lg-3 { - padding-left: 1rem !important; - } - - .ps-lg-4 { - padding-left: 1.5rem !important; - } - - .ps-lg-5 { - padding-left: 3rem !important; - } - - .text-lg-start { - text-align: left !important; - } - - .text-lg-end { - text-align: right !important; - } - - .text-lg-center { - text-align: center !important; - } -} -@media (min-width: 1200px) { - .float-xl-start { - float: left !important; - } - - .float-xl-end { - float: right !important; - } - - .float-xl-none { - float: none !important; - } - - .d-xl-inline { - display: inline !important; - } - - .d-xl-inline-block { - display: inline-block !important; - } - - .d-xl-block { - display: block !important; - } - - .d-xl-grid { - display: grid !important; - } - - .d-xl-table { - display: table !important; - } - - .d-xl-table-row { - display: table-row !important; - } - - .d-xl-table-cell { - display: table-cell !important; - } - - .d-xl-flex { - display: flex !important; - } - - .d-xl-inline-flex { - display: inline-flex !important; - } - - .d-xl-none { - display: none !important; - } - - .flex-xl-fill { - flex: 1 1 auto !important; - } - - .flex-xl-row { - flex-direction: row !important; - } - - .flex-xl-column { - flex-direction: column !important; - } - - .flex-xl-row-reverse { - flex-direction: row-reverse !important; - } - - .flex-xl-column-reverse { - flex-direction: column-reverse !important; - } - - .flex-xl-grow-0 { - flex-grow: 0 !important; - } - - .flex-xl-grow-1 { - flex-grow: 1 !important; - } - - .flex-xl-shrink-0 { - flex-shrink: 0 !important; - } - - .flex-xl-shrink-1 { - flex-shrink: 1 !important; - } - - .flex-xl-wrap { - flex-wrap: wrap !important; - } - - .flex-xl-nowrap { - flex-wrap: nowrap !important; - } - - .flex-xl-wrap-reverse { - flex-wrap: wrap-reverse !important; - } - - .gap-xl-0 { - gap: 0 !important; - } - - .gap-xl-1 { - gap: 0.25rem !important; - } - - .gap-xl-2 { - gap: 0.5rem !important; - } - - .gap-xl-3 { - gap: 1rem !important; - } - - .gap-xl-4 { - gap: 1.5rem !important; - } - - .gap-xl-5 { - gap: 3rem !important; - } - - .justify-content-xl-start { - justify-content: flex-start !important; - } - - .justify-content-xl-end { - justify-content: flex-end !important; - } - - .justify-content-xl-center { - justify-content: center !important; - } - - .justify-content-xl-between { - justify-content: space-between !important; - } - - .justify-content-xl-around { - justify-content: space-around !important; - } - - .justify-content-xl-evenly { - justify-content: space-evenly !important; - } - - .align-items-xl-start { - align-items: flex-start !important; - } - - .align-items-xl-end { - align-items: flex-end !important; - } - - .align-items-xl-center { - align-items: center !important; - } - - .align-items-xl-baseline { - align-items: baseline !important; - } - - .align-items-xl-stretch { - align-items: stretch !important; - } - - .align-content-xl-start { - align-content: flex-start !important; - } - - .align-content-xl-end { - align-content: flex-end !important; - } - - .align-content-xl-center { - align-content: center !important; - } - - .align-content-xl-between { - align-content: space-between !important; - } - - .align-content-xl-around { - align-content: space-around !important; - } - - .align-content-xl-stretch { - align-content: stretch !important; - } - - .align-self-xl-auto { - align-self: auto !important; - } - - .align-self-xl-start { - align-self: flex-start !important; - } - - .align-self-xl-end { - align-self: flex-end !important; - } - - .align-self-xl-center { - align-self: center !important; - } - - .align-self-xl-baseline { - align-self: baseline !important; - } - - .align-self-xl-stretch { - align-self: stretch !important; - } - - .order-xl-first { - order: -1 !important; - } - - .order-xl-0 { - order: 0 !important; - } - - .order-xl-1 { - order: 1 !important; - } - - .order-xl-2 { - order: 2 !important; - } - - .order-xl-3 { - order: 3 !important; - } - - .order-xl-4 { - order: 4 !important; - } - - .order-xl-5 { - order: 5 !important; - } - - .order-xl-last { - order: 6 !important; - } - - .m-xl-0 { - margin: 0 !important; - } - - .m-xl-1 { - margin: 0.25rem !important; - } - - .m-xl-2 { - margin: 0.5rem !important; - } - - .m-xl-3 { - margin: 1rem !important; - } - - .m-xl-4 { - margin: 1.5rem !important; - } - - .m-xl-5 { - margin: 3rem !important; - } - - .m-xl-auto { - margin: auto !important; - } - - .mx-xl-0 { - margin-right: 0 !important; - margin-left: 0 !important; - } - - .mx-xl-1 { - margin-right: 0.25rem !important; - margin-left: 0.25rem !important; - } - - .mx-xl-2 { - margin-right: 0.5rem !important; - margin-left: 0.5rem !important; - } - - .mx-xl-3 { - margin-right: 1rem !important; - margin-left: 1rem !important; - } - - .mx-xl-4 { - margin-right: 1.5rem !important; - margin-left: 1.5rem !important; - } - - .mx-xl-5 { - margin-right: 3rem !important; - margin-left: 3rem !important; - } - - .mx-xl-auto { - margin-right: auto !important; - margin-left: auto !important; - } - - .my-xl-0 { - margin-top: 0 !important; - margin-bottom: 0 !important; - } - - .my-xl-1 { - margin-top: 0.25rem !important; - margin-bottom: 0.25rem !important; - } - - .my-xl-2 { - margin-top: 0.5rem !important; - margin-bottom: 0.5rem !important; - } - - .my-xl-3 { - margin-top: 1rem !important; - margin-bottom: 1rem !important; - } - - .my-xl-4 { - margin-top: 1.5rem !important; - margin-bottom: 1.5rem !important; - } - - .my-xl-5 { - margin-top: 3rem !important; - margin-bottom: 3rem !important; - } - - .my-xl-auto { - margin-top: auto !important; - margin-bottom: auto !important; - } - - .mt-xl-0 { - margin-top: 0 !important; - } - - .mt-xl-1 { - margin-top: 0.25rem !important; - } - - .mt-xl-2 { - margin-top: 0.5rem !important; - } - - .mt-xl-3 { - margin-top: 1rem !important; - } - - .mt-xl-4 { - margin-top: 1.5rem !important; - } - - .mt-xl-5 { - margin-top: 3rem !important; - } - - .mt-xl-auto { - margin-top: auto !important; - } - - .me-xl-0 { - margin-right: 0 !important; - } - - .me-xl-1 { - margin-right: 0.25rem !important; - } - - .me-xl-2 { - margin-right: 0.5rem !important; - } - - .me-xl-3 { - margin-right: 1rem !important; - } - - .me-xl-4 { - margin-right: 1.5rem !important; - } - - .me-xl-5 { - margin-right: 3rem !important; - } - - .me-xl-auto { - margin-right: auto !important; - } - - .mb-xl-0 { - margin-bottom: 0 !important; - } - - .mb-xl-1 { - margin-bottom: 0.25rem !important; - } - - .mb-xl-2 { - margin-bottom: 0.5rem !important; - } - - .mb-xl-3 { - margin-bottom: 1rem !important; - } - - .mb-xl-4 { - margin-bottom: 1.5rem !important; - } - - .mb-xl-5 { - margin-bottom: 3rem !important; - } - - .mb-xl-auto { - margin-bottom: auto !important; - } - - .ms-xl-0 { - margin-left: 0 !important; - } - - .ms-xl-1 { - margin-left: 0.25rem !important; - } - - .ms-xl-2 { - margin-left: 0.5rem !important; - } - - .ms-xl-3 { - margin-left: 1rem !important; - } - - .ms-xl-4 { - margin-left: 1.5rem !important; - } - - .ms-xl-5 { - margin-left: 3rem !important; - } - - .ms-xl-auto { - margin-left: auto !important; - } - - .p-xl-0 { - padding: 0 !important; - } - - .p-xl-1 { - padding: 0.25rem !important; - } - - .p-xl-2 { - padding: 0.5rem !important; - } - - .p-xl-3 { - padding: 1rem !important; - } - - .p-xl-4 { - padding: 1.5rem !important; - } - - .p-xl-5 { - padding: 3rem !important; - } - - .px-xl-0 { - padding-right: 0 !important; - padding-left: 0 !important; - } - - .px-xl-1 { - padding-right: 0.25rem !important; - padding-left: 0.25rem !important; - } - - .px-xl-2 { - padding-right: 0.5rem !important; - padding-left: 0.5rem !important; - } - - .px-xl-3 { - padding-right: 1rem !important; - padding-left: 1rem !important; - } - - .px-xl-4 { - padding-right: 1.5rem !important; - padding-left: 1.5rem !important; - } - - .px-xl-5 { - padding-right: 3rem !important; - padding-left: 3rem !important; - } - - .py-xl-0 { - padding-top: 0 !important; - padding-bottom: 0 !important; - } - - .py-xl-1 { - padding-top: 0.25rem !important; - padding-bottom: 0.25rem !important; - } - - .py-xl-2 { - padding-top: 0.5rem !important; - padding-bottom: 0.5rem !important; - } - - .py-xl-3 { - padding-top: 1rem !important; - padding-bottom: 1rem !important; - } - - .py-xl-4 { - padding-top: 1.5rem !important; - padding-bottom: 1.5rem !important; - } - - .py-xl-5 { - padding-top: 3rem !important; - padding-bottom: 3rem !important; - } - - .pt-xl-0 { - padding-top: 0 !important; - } - - .pt-xl-1 { - padding-top: 0.25rem !important; - } - - .pt-xl-2 { - padding-top: 0.5rem !important; - } - - .pt-xl-3 { - padding-top: 1rem !important; - } - - .pt-xl-4 { - padding-top: 1.5rem !important; - } - - .pt-xl-5 { - padding-top: 3rem !important; - } - - .pe-xl-0 { - padding-right: 0 !important; - } - - .pe-xl-1 { - padding-right: 0.25rem !important; - } - - .pe-xl-2 { - padding-right: 0.5rem !important; - } - - .pe-xl-3 { - padding-right: 1rem !important; - } - - .pe-xl-4 { - padding-right: 1.5rem !important; - } - - .pe-xl-5 { - padding-right: 3rem !important; - } - - .pb-xl-0 { - padding-bottom: 0 !important; - } - - .pb-xl-1 { - padding-bottom: 0.25rem !important; - } - - .pb-xl-2 { - padding-bottom: 0.5rem !important; - } - - .pb-xl-3 { - padding-bottom: 1rem !important; - } - - .pb-xl-4 { - padding-bottom: 1.5rem !important; - } - - .pb-xl-5 { - padding-bottom: 3rem !important; - } - - .ps-xl-0 { - padding-left: 0 !important; - } - - .ps-xl-1 { - padding-left: 0.25rem !important; - } - - .ps-xl-2 { - padding-left: 0.5rem !important; - } - - .ps-xl-3 { - padding-left: 1rem !important; - } - - .ps-xl-4 { - padding-left: 1.5rem !important; - } - - .ps-xl-5 { - padding-left: 3rem !important; - } - - .text-xl-start { - text-align: left !important; - } - - .text-xl-end { - text-align: right !important; - } - - .text-xl-center { - text-align: center !important; - } -} -@media (min-width: 1400px) { - .float-xxl-start { - float: left !important; - } - - .float-xxl-end { - float: right !important; - } - - .float-xxl-none { - float: none !important; - } - - .d-xxl-inline { - display: inline !important; - } - - .d-xxl-inline-block { - display: inline-block !important; - } - - .d-xxl-block { - display: block !important; - } - - .d-xxl-grid { - display: grid !important; - } - - .d-xxl-table { - display: table !important; - } - - .d-xxl-table-row { - display: table-row !important; - } - - .d-xxl-table-cell { - display: table-cell !important; - } - - .d-xxl-flex { - display: flex !important; - } - - .d-xxl-inline-flex { - display: inline-flex !important; - } - - .d-xxl-none { - display: none !important; - } - - .flex-xxl-fill { - flex: 1 1 auto !important; - } - - .flex-xxl-row { - flex-direction: row !important; - } - - .flex-xxl-column { - flex-direction: column !important; - } - - .flex-xxl-row-reverse { - flex-direction: row-reverse !important; - } - - .flex-xxl-column-reverse { - flex-direction: column-reverse !important; - } - - .flex-xxl-grow-0 { - flex-grow: 0 !important; - } - - .flex-xxl-grow-1 { - flex-grow: 1 !important; - } - - .flex-xxl-shrink-0 { - flex-shrink: 0 !important; - } - - .flex-xxl-shrink-1 { - flex-shrink: 1 !important; - } - - .flex-xxl-wrap { - flex-wrap: wrap !important; - } - - .flex-xxl-nowrap { - flex-wrap: nowrap !important; - } - - .flex-xxl-wrap-reverse { - flex-wrap: wrap-reverse !important; - } - - .gap-xxl-0 { - gap: 0 !important; - } - - .gap-xxl-1 { - gap: 0.25rem !important; - } - - .gap-xxl-2 { - gap: 0.5rem !important; - } - - .gap-xxl-3 { - gap: 1rem !important; - } - - .gap-xxl-4 { - gap: 1.5rem !important; - } - - .gap-xxl-5 { - gap: 3rem !important; - } - - .justify-content-xxl-start { - justify-content: flex-start !important; - } - - .justify-content-xxl-end { - justify-content: flex-end !important; - } - - .justify-content-xxl-center { - justify-content: center !important; - } - - .justify-content-xxl-between { - justify-content: space-between !important; - } - - .justify-content-xxl-around { - justify-content: space-around !important; - } - - .justify-content-xxl-evenly { - justify-content: space-evenly !important; - } - - .align-items-xxl-start { - align-items: flex-start !important; - } - - .align-items-xxl-end { - align-items: flex-end !important; - } - - .align-items-xxl-center { - align-items: center !important; - } - - .align-items-xxl-baseline { - align-items: baseline !important; - } - - .align-items-xxl-stretch { - align-items: stretch !important; - } - - .align-content-xxl-start { - align-content: flex-start !important; - } - - .align-content-xxl-end { - align-content: flex-end !important; - } - - .align-content-xxl-center { - align-content: center !important; - } - - .align-content-xxl-between { - align-content: space-between !important; - } - - .align-content-xxl-around { - align-content: space-around !important; - } - - .align-content-xxl-stretch { - align-content: stretch !important; - } - - .align-self-xxl-auto { - align-self: auto !important; - } - - .align-self-xxl-start { - align-self: flex-start !important; - } - - .align-self-xxl-end { - align-self: flex-end !important; - } - - .align-self-xxl-center { - align-self: center !important; - } - - .align-self-xxl-baseline { - align-self: baseline !important; - } - - .align-self-xxl-stretch { - align-self: stretch !important; - } - - .order-xxl-first { - order: -1 !important; - } - - .order-xxl-0 { - order: 0 !important; - } - - .order-xxl-1 { - order: 1 !important; - } - - .order-xxl-2 { - order: 2 !important; - } - - .order-xxl-3 { - order: 3 !important; - } - - .order-xxl-4 { - order: 4 !important; - } - - .order-xxl-5 { - order: 5 !important; - } - - .order-xxl-last { - order: 6 !important; - } - - .m-xxl-0 { - margin: 0 !important; - } - - .m-xxl-1 { - margin: 0.25rem !important; - } - - .m-xxl-2 { - margin: 0.5rem !important; - } - - .m-xxl-3 { - margin: 1rem !important; - } - - .m-xxl-4 { - margin: 1.5rem !important; - } - - .m-xxl-5 { - margin: 3rem !important; - } - - .m-xxl-auto { - margin: auto !important; - } - - .mx-xxl-0 { - margin-right: 0 !important; - margin-left: 0 !important; - } - - .mx-xxl-1 { - margin-right: 0.25rem !important; - margin-left: 0.25rem !important; - } - - .mx-xxl-2 { - margin-right: 0.5rem !important; - margin-left: 0.5rem !important; - } - - .mx-xxl-3 { - margin-right: 1rem !important; - margin-left: 1rem !important; - } - - .mx-xxl-4 { - margin-right: 1.5rem !important; - margin-left: 1.5rem !important; - } - - .mx-xxl-5 { - margin-right: 3rem !important; - margin-left: 3rem !important; - } - - .mx-xxl-auto { - margin-right: auto !important; - margin-left: auto !important; - } - - .my-xxl-0 { - margin-top: 0 !important; - margin-bottom: 0 !important; - } - - .my-xxl-1 { - margin-top: 0.25rem !important; - margin-bottom: 0.25rem !important; - } - - .my-xxl-2 { - margin-top: 0.5rem !important; - margin-bottom: 0.5rem !important; - } - - .my-xxl-3 { - margin-top: 1rem !important; - margin-bottom: 1rem !important; - } - - .my-xxl-4 { - margin-top: 1.5rem !important; - margin-bottom: 1.5rem !important; - } - - .my-xxl-5 { - margin-top: 3rem !important; - margin-bottom: 3rem !important; - } - - .my-xxl-auto { - margin-top: auto !important; - margin-bottom: auto !important; - } - - .mt-xxl-0 { - margin-top: 0 !important; - } - - .mt-xxl-1 { - margin-top: 0.25rem !important; - } - - .mt-xxl-2 { - margin-top: 0.5rem !important; - } - - .mt-xxl-3 { - margin-top: 1rem !important; - } - - .mt-xxl-4 { - margin-top: 1.5rem !important; - } - - .mt-xxl-5 { - margin-top: 3rem !important; - } - - .mt-xxl-auto { - margin-top: auto !important; - } - - .me-xxl-0 { - margin-right: 0 !important; - } - - .me-xxl-1 { - margin-right: 0.25rem !important; - } - - .me-xxl-2 { - margin-right: 0.5rem !important; - } - - .me-xxl-3 { - margin-right: 1rem !important; - } - - .me-xxl-4 { - margin-right: 1.5rem !important; - } - - .me-xxl-5 { - margin-right: 3rem !important; - } - - .me-xxl-auto { - margin-right: auto !important; - } - - .mb-xxl-0 { - margin-bottom: 0 !important; - } - - .mb-xxl-1 { - margin-bottom: 0.25rem !important; - } - - .mb-xxl-2 { - margin-bottom: 0.5rem !important; - } - - .mb-xxl-3 { - margin-bottom: 1rem !important; - } - - .mb-xxl-4 { - margin-bottom: 1.5rem !important; - } - - .mb-xxl-5 { - margin-bottom: 3rem !important; - } - - .mb-xxl-auto { - margin-bottom: auto !important; - } - - .ms-xxl-0 { - margin-left: 0 !important; - } - - .ms-xxl-1 { - margin-left: 0.25rem !important; - } - - .ms-xxl-2 { - margin-left: 0.5rem !important; - } - - .ms-xxl-3 { - margin-left: 1rem !important; - } - - .ms-xxl-4 { - margin-left: 1.5rem !important; - } - - .ms-xxl-5 { - margin-left: 3rem !important; - } - - .ms-xxl-auto { - margin-left: auto !important; - } - - .p-xxl-0 { - padding: 0 !important; - } - - .p-xxl-1 { - padding: 0.25rem !important; - } - - .p-xxl-2 { - padding: 0.5rem !important; - } - - .p-xxl-3 { - padding: 1rem !important; - } - - .p-xxl-4 { - padding: 1.5rem !important; - } - - .p-xxl-5 { - padding: 3rem !important; - } - - .px-xxl-0 { - padding-right: 0 !important; - padding-left: 0 !important; - } - - .px-xxl-1 { - padding-right: 0.25rem !important; - padding-left: 0.25rem !important; - } - - .px-xxl-2 { - padding-right: 0.5rem !important; - padding-left: 0.5rem !important; - } - - .px-xxl-3 { - padding-right: 1rem !important; - padding-left: 1rem !important; - } - - .px-xxl-4 { - padding-right: 1.5rem !important; - padding-left: 1.5rem !important; - } - - .px-xxl-5 { - padding-right: 3rem !important; - padding-left: 3rem !important; - } - - .py-xxl-0 { - padding-top: 0 !important; - padding-bottom: 0 !important; - } - - .py-xxl-1 { - padding-top: 0.25rem !important; - padding-bottom: 0.25rem !important; - } - - .py-xxl-2 { - padding-top: 0.5rem !important; - padding-bottom: 0.5rem !important; - } - - .py-xxl-3 { - padding-top: 1rem !important; - padding-bottom: 1rem !important; - } - - .py-xxl-4 { - padding-top: 1.5rem !important; - padding-bottom: 1.5rem !important; - } - - .py-xxl-5 { - padding-top: 3rem !important; - padding-bottom: 3rem !important; - } - - .pt-xxl-0 { - padding-top: 0 !important; - } - - .pt-xxl-1 { - padding-top: 0.25rem !important; - } - - .pt-xxl-2 { - padding-top: 0.5rem !important; - } - - .pt-xxl-3 { - padding-top: 1rem !important; - } - - .pt-xxl-4 { - padding-top: 1.5rem !important; - } - - .pt-xxl-5 { - padding-top: 3rem !important; - } - - .pe-xxl-0 { - padding-right: 0 !important; - } - - .pe-xxl-1 { - padding-right: 0.25rem !important; - } - - .pe-xxl-2 { - padding-right: 0.5rem !important; - } - - .pe-xxl-3 { - padding-right: 1rem !important; - } - - .pe-xxl-4 { - padding-right: 1.5rem !important; - } - - .pe-xxl-5 { - padding-right: 3rem !important; - } - - .pb-xxl-0 { - padding-bottom: 0 !important; - } - - .pb-xxl-1 { - padding-bottom: 0.25rem !important; - } - - .pb-xxl-2 { - padding-bottom: 0.5rem !important; - } - - .pb-xxl-3 { - padding-bottom: 1rem !important; - } - - .pb-xxl-4 { - padding-bottom: 1.5rem !important; - } - - .pb-xxl-5 { - padding-bottom: 3rem !important; - } - - .ps-xxl-0 { - padding-left: 0 !important; - } - - .ps-xxl-1 { - padding-left: 0.25rem !important; - } - - .ps-xxl-2 { - padding-left: 0.5rem !important; - } - - .ps-xxl-3 { - padding-left: 1rem !important; - } - - .ps-xxl-4 { - padding-left: 1.5rem !important; - } - - .ps-xxl-5 { - padding-left: 3rem !important; - } - - .text-xxl-start { - text-align: left !important; - } - - .text-xxl-end { - text-align: right !important; - } - - .text-xxl-center { - text-align: center !important; - } -} -@media (min-width: 1200px) { - .fs-1 { - font-size: 2.5rem !important; - } - - .fs-2 { - font-size: 2rem !important; - } - - .fs-3 { - font-size: 1.75rem !important; - } - - .fs-4 { - font-size: 1.5rem !important; - } -} -@media print { - .d-print-inline { - display: inline !important; - } - - .d-print-inline-block { - display: inline-block !important; - } - - .d-print-block { - display: block !important; - } - - .d-print-grid { - display: grid !important; - } - - .d-print-table { - display: table !important; - } - - .d-print-table-row { - display: table-row !important; - } - - .d-print-table-cell { - display: table-cell !important; - } - - .d-print-flex { - display: flex !important; - } - - .d-print-inline-flex { - display: inline-flex !important; - } - - .d-print-none { - display: none !important; - } -} -#wrapper { - overflow-x: hidden; -} - -#sidebar-wrapper { - min-height: 100vh; - margin-left: -15rem; - transition: margin 0.25s ease-out; -} - -#sidebar-wrapper .sidebar-heading { - padding: 0.875rem 1.25rem; - font-size: 1.2rem; -} - -#sidebar-wrapper .list-group { - width: 15rem; -} - -#page-content-wrapper { - min-width: 100vw; -} - -body.sb-sidenav-toggled #wrapper #sidebar-wrapper { - margin-left: 0; -} - -@media (min-width: 768px) { - #sidebar-wrapper { - margin-left: 0; - } - - #page-content-wrapper { - min-width: 0; - width: 100%; - } - - body.sb-sidenav-toggled #wrapper #sidebar-wrapper { - margin-left: -15rem; - } -} diff --git a/docs/decomposition.html b/docs/decomposition.html deleted file mode 100644 index adbe7e60..00000000 --- a/docs/decomposition.html +++ /dev/null @@ -1,96 +0,0 @@ - - - - - - - - - Handwriter - - - - - - - - -
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Research Pipeline: Triangle Decomposition

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More coming soon!

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- - - - - - - diff --git a/docs/dev.html b/docs/dev.html deleted file mode 100644 index aa50e41f..00000000 --- a/docs/dev.html +++ /dev/null @@ -1,210 +0,0 @@ - - - - - - - - - Handwriter - - - - - - - -
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How to use the Handwriter package

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Interested in trying it out yourself?

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While we work on something interactive and web-based, you can download the package yourself and give it a try. The following is a step by step tutorial to help you along the way.

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Things you'll need:

-
    -
  • The R software enviroment, downloadable from - The R Project. - You may use this mirror from Iowa State if you wish. -
  • -
  • - RStudio Desktop, an IDE that should simplify the experience.
  • -
  • A sample of handwriting in .png format, you can: -
      -
    • Write something up (black and white works best) and scan it digitally.
    • -
    • - Use an online tool like - Sketch.io - create and export some handwriting easily.
    • -
    • Use one of our images to get started.
    • -
    -
  • -
-
-

Getting started

-

Once you have R installed, you'll want to install and load our package from Github using: -

-                      install.packages("devtools") //You may have to install again after working through some GUIs
-                        devtools::install_github("csafe-isu/handwriter")
-                        library(handwriter)
-                    
-

- Get your image as a .png (we'll use this one, available - here): -

- Writing_csafe_single -
-

- Once you have that, read in the image: - The image is also cropped as part of this process. -

-
-                        csafe = list()
-                          csafe$image = readPNGBinary("path/to/the/picture.png")
-                      
-
-

Preparing the image for processing

-

- Plot the original, cropped image: -

-
-                        plotImage(csafe$image)
-                      
-
- Writing_csafe_single -
-

-
thin the image and you can plot it again: -

-
-                        csafe$thin = thinImage(csafe$image)
-                          plotImageThinned(csafe$image, csafe$thin)
-                      
-
- Writing_csafe_single -
-

Processing the image and save off information

-

- Process the image

-
-                        csafe_processlist = processHandwriting(csafe$thin, dim(csafe$image))
-                      
-

Save information for plotting

-
-                        csafe$nodes = csafe_processlist$nodes
-                          csafe$breaks = csafe_processlist$breakPoints
-                          dims = dim(csafe$image)
-                      
-


Plotting processed writing

-

- Plot all nodes found during processing

-
-                        plotNodes(csafe$image, csafe$thin, csafe$nodes)
-                      
-
- Writing_csafe_single -
-

Plot all glyph breaks found during processing

-
-                        plotNodes(csafe$image, csafe$thin, csafe$breaks)
-                      
-
- Writing_csafe_single -
-

Also included is the ability to plot individual glyphs from the sample of writing, using - plotLetter(). First lets look at the parameters and options, and then run through a few examples.

-

The parameters include:

-
    -
  • - letterList Object -
  • -
  • - The index of the glyph you wish to plot -
  • -
  • - dims Object -
  • -
  • - OPTIONAL: Boolean - Number the paths within the glyph -
  • -
  • - OPTIONAL: Boolean - Plot the centroid of the glyph -
  • -
  • - OPTIONAL: Boolean - Plot the slope of the glyph -
  • -
-

The following will result in the first glyph being plotted with all optional paramters:

-
-                        plotLetter(csafe_processList$letterlist, 1, dims)
-
-                          #Note: No optional parameters specified is the same as:
-                          #plotLetter(csafe_processlist$letterList, 1, dims, TRUE, TRUE, TRUE)
-                      
-
- c_all_features -
-

This will plot the fifth glyph with just the slope and centroid:

-
-                        plotLetter(csafe_processlist$letterList, 5, dims, FALSE, TRUE, TRUE)
-                      
-
- c_all_features -
-
- -
- -
-
- - - - - - diff --git a/docs/docsify.html b/docs/docsify.html deleted file mode 100644 index 1d994137..00000000 --- a/docs/docsify.html +++ /dev/null @@ -1,45 +0,0 @@ - - - - - - - - - - - -
- - - - - - - diff --git a/docs/docsify.md b/docs/docsify.md deleted file mode 100644 index 7265e210..00000000 --- a/docs/docsify.md +++ /dev/null @@ -1,9 +0,0 @@ -* [Home](/) -* Articles: $ALTDOC_VIGNETTE_BLOCK -* Reference: $ALTDOC_MAN_BLOCK -* [News]($ALTDOC_NEWS) -* [Changelog]($ALTDOC_CHANGELOG) -* [Code of Conduct]($ALTDOC_CODE_OF_CONDUCT) -* [License]($ALTDOC_LICENSE) -* [Licence]($ALTDOC_LICENCE) -* [Citation]($ALTDOC_CITATION) diff --git a/docs/freeze.rds b/docs/freeze.rds index 1fdc8f5fa85246e9a393fbcb528432bb36a788e7..cb809a7c4eab85529e73978925039844d310ccae 100644 GIT binary patch literal 1538 zcmV+d2L1UTiwFP!000001BF#xuOmkhbvC;XM0^AU1cV5PJSX&5^~WP9*?T``;i6j<(t!85jkwhl;MI6XFY$x9 z3WREC(N%zu@LV>ekjKnQ!dKsNG0Yi6W0^Sj0-LfG%vgb9-5HmAhbJ=B1YEE_ zL8B2r1oh;6(E;c*1s*6_U=1EjFp*Di2Oo;j%iJKI1Zi|53?^$~#tUh7SJ#TAB_9|w zk-I`Ecw-2R8B+_@^`hA${W6bA+Co#!utqp9qE;bnvRKceyjnef2HZPu@h^6~)x+x9 z>iQ-5-dCUf;nTl<_Q}`VGmSsn^6vLs$K$mAhW7*4jehdgIr!64P~_G4Qh7S=^>B%O zbc*eG^YCw7e|^-$G>kiywT$h!)!lRj{pAd8ylKY`PrByTj(cto7r+N6z(#rZ$6?3& zhd*!m?y8LMpTY-lbUFLUd?x$xeqE3I-LSh!rvKvY{RVf<1s;a0Vt#WSZkyv_(*1f; z{6uXxt)F4rQFQa2*n}pg&-Z-)`YQeVbF2^3?K8hRosau1Ps?p<;fXJh4`;}oPD@pN z*lgBqJbstVE7W0Kd1|jOfL||wy~==ju7@3P-|*%t%kR#h`*BV(jQjQdeuR$?n_(KR z=X|2`Ztn8c_~m|_#_8eyil-mU;mx>{ad*Sv#~rhPiyo#bY3 z_`BbX7j~M?ZQV}x5#&h%KYSXtM`=%^{s)a8EvWy?TFo$oYw3cCiqqoQL&2X45fS+FhK7G6V zPe1-A-pQLic-h_Ew7FLn?5eEaB5!tW4uAQ@=ii#cZS1Z($n)U<{9 literal 1572 zcmV+<2HW``iwFP!000001BF#xk0VzRbvC;XL3{)h2nZ1nd1iCJKORBJ1|*20ut>aF zb#K+3X<>H{?VeqRACEZgtgk)J2{P}yE_g~=a=EdJ$ zzxrL;JbU&b9$s#qZ$7~P-(-%ha%ehb(yAF}U8+)=l1Q!=-*GMwCzWi;rs=@Wrx0qT zP<=9`(Fx~W7SmKw%^H&CbycM(&q}gQA=wiy)XjnQ8^fozNxw#Tno{v zoDIc5=lV?bCI`B**;<8U&3Uoe z^|=}45+)gCO{HwWTtab)iH(X<%Lx~~*IpZyS^$3#fl=(04`iJ7P1inO%B>lph(??P zWl{So6;sJU1si+6;)^I(sU&Ygp~57}));J~Y$WvhyeU3lY+4|Otl3$PCW26aZR>rM zh`N#qSqGD->VoEpi>Vlh!o^(&E_jSI<*2oHUa^i@C7-QN+IidiwFOEbh#*yVO1$+A zw37seP?hhxau5>UOUeu6v9c2J)z(z0lIMPJL8s1Fr%lkMC?|vA@|HqY(@) z$4ovHG}4sQs#q`7d1l<%LWs?AbC5ecfNiN@3D!|;*Om5OInk8hDWr4_5e*UEF;Pcj zy6!P6N8s6+lti^0EvU|ra??nwTGwgRWR!$;cv$Oowwasp5o5E?^?h@&KU1)^96Ve@ zT1hqPy7f~$`w%1tCEWO_tRmm|VCD5Ep zkb{9n9gK!0YBrnA^Jl=l_YVJJq`e$A&o-AorXPIs#qU4=%NH;AC$@jOr|~l?)BUo2 zL-RmoCojJ_1wT3lnO{$@gqHhR4(HgX$Jj`_hkwiVpZ9WDhG`Vu@>K8lGA@Y4EXp6*a?k)7)F{O{s*?lLrpo!(nneJ{c(to(d+OS-| z^ULG;H1BEYw{4jgIzv8LAvd!0s@kyIZR>RZT{16Fhi##y-kt%!>VR2zz&y9Z2;3Xm zU1a&~33NBDNrq|O-pv#2e%KAma5?8Aoi}Tjucxo)X_=OXy9=Ivu!eWj$kTYm@t*$C z2_D9qCpiA$5hjPjqiG*c$D`cz6@PcT>C8@*wXN&PK7u?+;3rSRW|a0c>VMGqX-EBE z9)H}St8U~ByT^&dYve|AeXWxTm+a~5LkDsSH*uXb$>fBn^$- - - - - - - - - Handwriter - - - - - - - - -
- -
- - - -
-

How to use the handwriter package

-
-

Interested in trying it out yourself?

-

While we work on something interactive and web-based, you can download the package yourself and give it a try. - The following is a step by step tutorial to help you along the way.

- -

Recently we have been incorporating our research work built on top of handwriter so that you may also use those. - See the Research Pipelines section for more.

-
-

Things you'll need:

-
    -
  • The R software environment, downloadable from - The R Project. - You may use this mirror from Iowa State if you wish. -
  • -
  • - RStudio Desktop, an IDE that should simplify the experience.
  • -
  • A sample of handwriting in .png format, you can: -
      -
    • Write something up (black and white works best) and scan it digitally.
    • -
    • - Use an online tool like - Sketch.io - create and export some handwriting easily.
    • -
    • Use one of our images to get started.
    • -
    -
  • -
-

Terms to know

-
    -
  • Graphs | Often letters, but not always due to the separation algorithm used.
  • -
  • Index | Top to bottom and left to right, our way of keeping track where a pixel sits on the document as a whole.
  • -
-
-

Getting started

-

Once you have R installed, you'll want to install and load our package from CRAN using: -

-                      install.packages("handwriter")
-                        library(handwriter)
-                    
-

- Get your image as a .png (we'll use this one, available - here): -

- Writing_csafe_single -
-

- Once you have that, read in the image: - The image is also cropped as part of this process. -

-
-                        csafe = list()
-                          csafe$image = readPNGBinary("path/to/the/picture.png")
-                      
-

-

Preparing the image for processing

-

Plot the original, cropped image:

-
-                        plotImage(csafe$image)
-                      
-
- Writing_csafe_single -
-

-
thin the image and you can plot it again: -

-
-                        csafe$thin = thinImage(csafe$image)
-                          plotImageThinned(csafe$image, csafe$thin)
-                      
-
- Writing_csafe_single -
-

Processing the image exploring the results

-

- Process the image

-
-                        csafe_processlist = processHandwriting(csafe$thin, dim(csafe$image))
-                      
- - - -
- -

Handwriter uses the RCPP package, an R package that allows RStudio to compile the C++ code in the handwriter program. When a Mac user runs handwriter, the machine will use its default C++ compiler called clang. This default will produce an error that says: "ld: warning: directory not found for option '-L/usr/local/gfortran/lib/gcc/x86_64-apple-darwin15/6.1.0'"

- -

The following steps will help you to fix this issue:

-
    -
  • If you have previously used clang4, clang6, clang7, clang8, or the macos-rtools, consider deleting the old components that - were installed. To do this, execute the following lines in the Terminal app: - -

    # Delete the clang4,6,7 binary

  • - -
    • sudo rm -rf /usr/local/clang{4,6,7}
    -

    # Delete the prior version of gfortran installed

    -
    • sudo rm -rf /usr/local/gfortran
    • -
    • sudo rm -rf /usr/local/bin/gfortran
    - -

    # Remove the gfortran install receipts (run after the above commands)

    - -
    • sudo rm /private/var/db/receipts/com.gnu.gfortran.bom
    • -
    • sudo rm /private/var/db/receipts/com.gnu.gfortran.plist
    -

    -

    # Remove the clang4 installer receipt

    -
    • sudo rm /private/var/db/receipts/com.rbinaries.clang4.bom
    • -
    • sudo rm /private/var/db/receipts/com.rbinaries.clang4.plist
    -

    -
  • You will need to remove both the ~/.R/Makevars and ~/.Renviron files before continuing. You can do this by using:
  • -
    • unlink (“~/.R/Makevars”)
    • -
    • unlink (“~/.Renviron”)
    -

    -
  • Next, still in the Terminal, you will need to install the Xcode Command Line Tools or Xcode CLI. To do this execute: xcode-select --install
  • -

    -
  • If you encounter an error while installing, the Xcode CLI might already be installed. This may mean that a software update of the tools is in order, execute the following line: softwareupdate --install -a.
  • -

    -
  • After installing the Xcode CLI, you will need to install OS-specific GFortran Binary. To do this, you will first need to verify your macOS version.
  • -

    -
  • Knowing what version of macOS your computer is running, you will then go to: GFortran-for-macOs-Repo. This link will direct you to a GitHub page that will contain installation packages containing GFortran binary for different macOS versions. After downloading the folder, open the GFortran folder inside and run the gfortran.pkg. This will prompt an installation window that will help you successfully install the binary.
  • - -
-
-

processHandwriting() will return tons of information about the document. It is worth exploring, and we've provided a handy list here of what each element of the list means

- -
-

On a document level:

-
    -
  • nodes | A list of all 'points of interest'
  • -
  • connectingNodes | A list of all nodes where graphs connect
  • -
  • terminalNodes | A list of all nodes where a path in a graphs ends
  • -
  • breakPoints | A list of calculated points to break graphs apart (based on connectingNodes)
  • -
- -

As well as a letterList for each letter/graph that includes:

-
    -
  • path | A list of all points
  • -
  • nodes | A list of all 'points of interest'
  • -
  • allPaths | A list of lists of calculated 'paths'
  • -
  • adjMatrix | Adjacency matrix
  • -
  • letterCode | A unique letter code
  • -
  • connectingNodes | A list of all nodes where the graph connects
  • -
  • terminalNodes | A list of all nodes where a path in the graph ends
  • -
  • characterFeatures | A list of all 'points of interest' in the document
  • -
      -
    • aspect_ratio | Height to width ratio
    • -
    • height | Height of the graph, measured in pixels
    • -
    • width | Width of the graph, measured in pixels
    • -
    • topmost_row | The top-most row, as its y coordinate
    • -
    • bottom_row | The bottom-most row, as its y coordinate
    • -
    • leftmost_col | The left-most column, as its x coordinate
    • -
    • rightmost_col | The left-most column, as its x coordinate
    • -
    • centroid_index | The centroid of the graph, as its index
    • -
    • centroid_y | The y coordinate of the centroid
    • -
    • centroid_x | The x coordinate of the centroid
    • -
    • centroid_horiz_location |
    • -
    • centroid_vert_location |
    • -
    • lHalf | List of all points on the left half of the graph
    • -
    • rHalf | List of all points on the right half of the graph
    • -
    • disjoint_centroids | The centroids of the left and right halves, as their indicies
    • -
    • slope | The slope of the graph as it runs through the centroid
    • -
    • pixel_density |
    • -
    • box_density |
    • -
    • uniqueid | A unique numerical identifier for the graph
    • -
    • down_dist | Distance from the lowest point of a graph to the next graph, measured in pixels
    • -
    • line_number | The position of the graph in the line
    • -
    • order_within_line | The ordered within the line the graph falls in
    • -
    • l_neighbor_dist | Distance from the left-most point in the graph to its left neighbor, measured in pixels
    • -
    • r_neighbor_dist | Distance from the right-most point in the graph to its left neighbor, measured in pixels
    • -
    • xvar | Variance of X, used to calculate the covariance in covar
    • -
    • yvar | Variance of Y, used to calculate the covariance in covar
    • -
    • covar | Covarience of the graph
    • -
    • wordIndex | Word number the graph belongs to
    • -
    -
-
-
- -

Exploring processed writing

-

Using the information returned from processHandwriting(), Handwriter allows plotting on a letter (or graph), word, sentence, or the entire document.

-

Make sure to save this information so that the plotting functions work correctly

-
-                        csafe$nodes = csafe_processlist$nodes
-                          csafe$breaks = csafe_processlist$breakPoints
-                          dims = dim(csafe$image)
-                      
- -
-

Also included is the ability to plot individual graphs from the sample of writing, using - plotLetter(). First lets look at the parameters and options, and then run through a few examples.

-

The parameters include:

-
    -
  • - letterList Object -
  • -
  • - The index of the graph you wish to plot -
  • -
  • - dims Object -
  • -
  • - OPTIONAL: Boolean - Number the paths within the graph -
  • -
  • - OPTIONAL: Boolean - Plot the centroid of the graph -
  • -
  • - OPTIONAL: Boolean - Plot the slope of the graph -
  • -
-

The following will result in the first graph being plotted with all optional paramters:

-
-                        plotLetter(csafe_processList$letterlist, 1, dims)
-
-                          #Note: No optional parameters specified is the same as:
-                          #plotLetter(csafe_processlist$letterList, 1, dims, TRUE, TRUE, TRUE)
-                      
-
- c_all_features -
-

This will plot the fifth graph with just the slope and centroid:

-
-                        plotLetter(csafe_processlist$letterList, 5, dims, FALSE, TRUE, TRUE)
-                      
-
- c_all_features -
-
- - -
-

To plot words, a little bit of extra processing must be done:

-
-                        words = create_words(csafe_processList)
-                              words_after_processing = process_words(words, dim(csafe_document$image), TRUE)
-                      
- -

Then you can plot just the word with plotWord

-
-                          plotWord(csafe_processList$letterList, 1, dims)
-                        
- -

Or optionally, use the plotColorNodes function to show some additional information.

-
-                          plotColorNodes(csafe_processList$letterList, 1, dims, words_after_processing)
-                        
-
- Writing_csafe_single -
-
- - -
-

Plot the line, where the second parameters is the line_number

-
-                        plotLine(csafe_processList$letterList, 1, dims)
-                      
-
- - -
-

Plot the original, cropped image

-
-                        plotImage(csafe$image)
-                      
-
- Writing_csafe_single -
-

Plot the thinned image

-
-                        plotImageThinned(csafe$image, csafe$thin)
-                      
-
- Writing_csafe_single -
-

- Plot all nodes found during processing

-
-                        plotNodes(csafe$image, csafe$thin, csafe$nodes)
-                      
-
- Writing_csafe_single -
-

Plot all graph breaks found during processing

-
-                        plotNodes(csafe$image, csafe$thin, csafe$breaks)
-                      
-
- Writing_csafe_single -
-
-

Research Pipelines

-

K-means Clustering | Perform K-means clustering on a graph level | Read more

-

Triangle Decomposition | Perform triangle decomposition on a word level | Read more

-
- - -
- -
- -
-
- - - - - - - diff --git a/docs/index.html b/docs/index.html old mode 100755 new mode 100644 index 44523b29..f1eea1a4 --- a/docs/index.html +++ b/docs/index.html @@ -1,44 +1,1200 @@ - - - - - - - - + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + - -
- - - - - - - + // Attach click handler to the DT + const annoteDls = window.document.querySelectorAll('dt[data-target-cell]'); + for (const annoteDlNode of annoteDls) { + annoteDlNode.addEventListener('click', (event) => { + const clickedEl = event.target; + if (clickedEl !== selectedAnnoteEl) { + unselectCodeLines(); + const activeEl = window.document.querySelector('dt[data-target-cell].code-annotation-active'); + if (activeEl) { + activeEl.classList.remove('code-annotation-active'); + } + selectCodeLines(clickedEl); + clickedEl.classList.add('code-annotation-active'); + } else { + // Unselect the line + unselectCodeLines(); + clickedEl.classList.remove('code-annotation-active'); + } + }); + } + const findCites = (el) => { + const parentEl = el.parentElement; + if (parentEl) { + const cites = parentEl.dataset.cites; + if (cites) { + return { + el, + cites: cites.split(' ') + }; + } else { + return findCites(el.parentElement) + } + } else { + return undefined; + } + }; + var bibliorefs = window.document.querySelectorAll('a[role="doc-biblioref"]'); + for (var i=0; i + + + + + + \ No newline at end of file diff --git a/docs/man/about_variable.html b/docs/man/about_variable.html new file mode 100644 index 00000000..13955a59 --- /dev/null +++ b/docs/man/about_variable.html @@ -0,0 +1,950 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

About Varialbe

+
+

Description

+

about_variable() returns information about the model variable.

+
+
+

Usage

+
about_variable(variable, model)
+
+
+
+

Arguments

+ + + + + + + + + +
+variable + +A variable in the fitted model output by fit_model() +
+model + +A fitted model created by fit_model() +
+
+
+

Value

+

Text that explains the variable

+
+
+

Examples

+
+
library(handwriter)
+
+about_variable(
+  variable = "mu[1,2]",
+  model = example_model
+)
+
+
[1] "Mu is the location parameter of a wrapped-Cauchy distribution for writer ID w0009 and cluster 2"
+
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/about_variable.md b/docs/man/about_variable.md deleted file mode 100644 index f44324de..00000000 --- a/docs/man/about_variable.md +++ /dev/null @@ -1,53 +0,0 @@ - - -# About Varialbe - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -about_variable() returns information about the model -variable. - -## Usage - -
about_variable(variable, model)
-
- -## Arguments - - - - - - - - - - -
-variable - -A variable in the fitted model output by fit_model() -
-model - -A fitted model created by fit_model() -
- -## Value - -Text that explains the variable - -## Examples - -``` r -library(handwriter) - -about_variable( - variable = "mu[1,2]", - model = example_model -) -``` - - [1] "Mu is the location parameter of a wrapped-Cauchy distribution for writer ID w0009 and cluster 2" diff --git a/docs/man/addToFeatures.html b/docs/man/addToFeatures.html new file mode 100644 index 00000000..0ca0e1a3 --- /dev/null +++ b/docs/man/addToFeatures.html @@ -0,0 +1,910 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

addToFeatures

+
+

Description

+

addToFeatures

+
+
+

Usage

+
addToFeatures(FeatureSet, LetterList, vectorDims)
+
+
+
+

Arguments

+ + + + + + + + + + + + + +
+FeatureSet + +The current list of features that have been calculated +
+LetterList + +List of all letters and their information +
+vectorDims + +Vectors with image Dims +
+
+
+

Value

+

A list consisting of current features calculated in FeatureSet as well as measures of compactness, loop count, and loop dimensions

+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/addToFeatures.md b/docs/man/addToFeatures.md deleted file mode 100644 index 113b6f06..00000000 --- a/docs/man/addToFeatures.md +++ /dev/null @@ -1,48 +0,0 @@ - - -# addToFeatures - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -addToFeatures - -## Usage - -
addToFeatures(FeatureSet, LetterList, vectorDims)
-
- -## Arguments - - - - - - - - - - - - - - -
-FeatureSet - -The current list of features that have been calculated -
-LetterList - -List of all letters and their information -
-vectorDims - -Vectors with image Dims -
- -## Value - -A list consisting of current features calculated in FeatureSet as well -as measures of compactness, loop count, and loop dimensions diff --git a/docs/man/analyze_questioned_documents.html b/docs/man/analyze_questioned_documents.html new file mode 100644 index 00000000..2a6c2975 --- /dev/null +++ b/docs/man/analyze_questioned_documents.html @@ -0,0 +1,993 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Analyze Questioned Documents

+
+

Description

+

analyze_questioned_documents() estimates the posterior probability of writership for the questioned documents using Markov Chain Monte Carlo (MCMC) draws from a hierarchical model created with fit_model().

+
+
+

Usage

+
analyze_questioned_documents(
+  main_dir,
+  questioned_docs,
+  model,
+  num_cores,
+  writer_indices,
+  doc_indices
+)
+
+
+
+

Arguments

+ + + + + + + + + + + + + + + + + + + + + + + + + +
+main_dir + +A directory that contains a cluster template created by make_clustering_template() +
+questioned_docs + +A directory containing questioned documents +
+model + +A fitted model created by fit_model() +
+num_cores + +An integer number of cores to use for parallel processing with the doParallel package. +
+writer_indices + +A vector of start and stop characters for writer IDs in file names +
+doc_indices + +A vector of start and stop characters for document names in file names +
+
+
+

Value

+

A list of likelihoods, votes, and posterior probabilities of writership for each questioned document.

+
+
+

Examples

+
+
library(handwriter)
+
+main_dir <- "/path/to/main_dir"
+questioned_docs <- "/path/to/questioned_images"
+analysis <- analyze_questioned_documents(
+  main_dir = main_dir,
+  questioned_docs = questioned_docs,
+  model = model,
+  num_cores = 2,
+  writer_indices = c(2, 5),
+  doc_indices = c(7, 18)
+)
+analysis$posterior_probabilities
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/analyze_questioned_documents.md b/docs/man/analyze_questioned_documents.md deleted file mode 100644 index 48f24fa1..00000000 --- a/docs/man/analyze_questioned_documents.md +++ /dev/null @@ -1,102 +0,0 @@ - - -# Analyze Questioned Documents - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -analyze_questioned_documents() estimates the posterior -probability of writership for the questioned documents using Markov -Chain Monte Carlo (MCMC) draws from a hierarchical model created with -fit_model(). - -## Usage - -
analyze_questioned_documents(
-  main_dir,
-  questioned_docs,
-  model,
-  num_cores,
-  writer_indices,
-  doc_indices
-)
-
- -## Arguments - - - - - - - - - - - - - - - - - - - - - - - - - - -
-main_dir - -A directory that contains a cluster template created by -make_clustering_template() -
-questioned_docs - -A directory containing questioned documents -
-model - -A fitted model created by fit_model() -
-num_cores - -An integer number of cores to use for parallel processing with the -doParallel package. -
-writer_indices - -A vector of start and stop characters for writer IDs in file names -
-doc_indices - -A vector of start and stop characters for document names in file names -
- -## Value - -A list of likelihoods, votes, and posterior probabilities of writership -for each questioned document. - -## Examples - -``` r -library(handwriter) - -main_dir <- "/path/to/main_dir" -questioned_docs <- "/path/to/questioned_images" -analysis <- analyze_questioned_documents( - main_dir = main_dir, - questioned_docs = questioned_docs, - model = model, - num_cores = 2, - writer_indices = c(2, 5), - doc_indices = c(7, 18) -) -analysis$posterior_probabilities -``` diff --git a/docs/man/calculate_accuracy.html b/docs/man/calculate_accuracy.html new file mode 100644 index 00000000..b4d1fb95 --- /dev/null +++ b/docs/man/calculate_accuracy.html @@ -0,0 +1,949 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Calculate Accuracy

+
+

Description

+

Fit a model with fit_model() and calculate posterior probabilities of writership with analyze_questioned_documents() of a set of test documents where the ground truth is known. Then use calculate_accuracy() to measure the accuracy of the fitted model on the test documents. Accuracy is calculated as the average posterior probability assigned to the true writer.

+
+
+

Usage

+
calculate_accuracy(analysis)
+
+
+
+

Arguments

+ + + + + +
+analysis + +Writership analysis output by analyze_questioned_documents +
+
+
+

Value

+

The model’s accuracy on the test set as a number

+
+
+

Examples

+
+
library(handwriter)
+
+# calculate the accuracy for example analysis performed on test documents and a model with 1 chain
+calculate_accuracy(example_analysis)
+
+main_dir <- "/path/to/main_dir"
+test_images_dir <- "/path/to/test_images"
+analysis <- analyze_questioned_documents(
+  main_dir = main_dir,
+  questioned_docs = test_images_dir,
+  model = model,
+  num_cores = 2,
+  writer_indices = c(2, 5),
+  doc_indices = c(7, 18)
+)
+calculate_accuracy(analysis)
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/calculate_accuracy.md b/docs/man/calculate_accuracy.md deleted file mode 100644 index 2a38d4c4..00000000 --- a/docs/man/calculate_accuracy.md +++ /dev/null @@ -1,58 +0,0 @@ - - -# Calculate Accuracy - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -Fit a model with fit_model() and calculate posterior -probabilities of writership with -analyze_questioned_documents() of a set of test documents -where the ground truth is known. Then use -calculate_accuracy() to measure the accuracy of the fitted -model on the test documents. Accuracy is calculated as the average -posterior probability assigned to the true writer. - -## Usage - -
calculate_accuracy(analysis)
-
- -## Arguments - - - - - - -
-analysis - -Writership analysis output by analyze_questioned_documents -
- -## Value - -The model’s accuracy on the test set as a number - -## Examples - -``` r -library(handwriter) - -# calculate the accuracy for example analysis performed on test documents and a model with 1 chain -calculate_accuracy(example_analysis) - -main_dir <- "/path/to/main_dir" -test_images_dir <- "/path/to/test_images" -analysis <- analyze_questioned_documents( - main_dir = main_dir, - questioned_docs = test_images_dir, - model = model, - num_cores = 2, - writer_indices = c(2, 5), - doc_indices = c(7, 18) -) -calculate_accuracy(analysis) -``` diff --git a/docs/man/cleanBinaryImage.html b/docs/man/cleanBinaryImage.html new file mode 100644 index 00000000..4284c410 --- /dev/null +++ b/docs/man/cleanBinaryImage.html @@ -0,0 +1,894 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

cleanBinaryImage

+
+

Description

+

Removes alpha channel from png image.

+
+
+

Usage

+
cleanBinaryImage(img)
+
+
+
+

Arguments

+ + + + + +
+img + +A matrix of 1s and 0s. +
+
+
+

Value

+

png image with the alpha channel removed

+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/cleanBinaryImage.md b/docs/man/cleanBinaryImage.md deleted file mode 100644 index dbc5cc0b..00000000 --- a/docs/man/cleanBinaryImage.md +++ /dev/null @@ -1,31 +0,0 @@ - - -# cleanBinaryImage - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -Removes alpha channel from png image. - -## Usage - -
cleanBinaryImage(img)
-
- -## Arguments - - - - - - -
-img - -A matrix of 1s and 0s. -
- -## Value - -png image with the alpha channel removed diff --git a/docs/man/csafe.html b/docs/man/csafe.html new file mode 100644 index 00000000..7e92bf97 --- /dev/null +++ b/docs/man/csafe.html @@ -0,0 +1,942 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Cursive written word: csafe

+
+

Description

+

Cursive written word: csafe

+
+
+

Usage

+
csafe
+
+
+
+

Format

+

Binary image matrix. 111 rows and 410 columns.

+
+
+

Examples

+
+
library(handwriter)
+
+csafe_document <- list()
+csafe_document$image <- csafe
+plotImage(csafe_document)
+
+
+
+

+
+
+
+
csafe_document$thin <- thinImage(csafe_document$image)
+plotImageThinned(csafe_document)
+
+
+
+

+
+
+
+
csafe_processList <- processHandwriting(csafe_document$thin, dim(csafe_document$image))
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/csafe.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png b/docs/man/csafe.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png deleted file mode 100644 index 73dc30ce8c16197a86e3b1f75d65f940a3e55e86..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 11625 zcmeHNdpy(a-=A4UNp#Z5AxkukPwV%*UeCYJU(c&Q_ImC5ey{6uzCNG#=d;~DYiYJ}`KIL% z2xR4{KaZb>K%f~Ah)lQKQt%`^j(q?Efhk@wH9dL;EL;c zvttm*p?mjioIJPKtTldCUbK5#Q*29i_Cv)5y~JYg^I!gHA6#%R^6A|3$h-LH{f3dQ zv@6^9_s;)&WvB7lqe^dHc0cNtpx$V2^&;@@B3=}qeF2NzG5dMW?DF}Ad3=pJ7IUUlAo1W9oHdiV)ph+_{-KYWJ?@Z&b?*zEqG3lx_43S1v+}iu-l-Zr ztKX3!b{o=HjTO?LKKSDn`ox|cd2tK19k-To;4==eWr1TI@kjJt5_f9SPBa`Oq*%h6 zsj(tl$%!sZZAYwCLXmFdTDEN2%;Q}F$=`1(;cfalgKm-bUMYI7BylglB0mm?I8iFE z2P_{qu64D+R&E&#%FWaNQnNd!<*A1fJ2o`<&5@6FqsQmT`_QS&gQL!;Dh#YrgLL=o zLc9tWz|~$^T-kMtcF)f9;D?D@vtCO(edb`489t_ssHRF^+!BMvX8*&p7r@08A| zhq1F;G#~ZpZrqxw@ldh8(S1@Nj$5 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+ + + + +
+

Drop Burn-In

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+

Description

+

drop_burnin() removes the burn-in from the Markov Chain Monte Carlo (MCMC) draws.

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+

Usage

+
drop_burnin(model, burn_in)
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+
+
+

Arguments

+ + + + + + + + + +
+model + +A list of MCMC draws from a model fit with fit_model(). +
+burn_in + +An integer number of starting iterations to drop from each MCMC chain. +
+
+
+

Value

+

A list of data frames of MCMC draws with burn-in dropped.

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+
+

Examples

+
+
library(handwriter)
+
+model <- drop_burnin(model = example_model, burn_in = 25)
+plot_trace(variable = "mu[1,2]", model = example_model)
+
+
+
+

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zz})Y#N8_aprC&~CbfE!q2+7?$p2QPN~yhgCXBuTS2UF*qMb_|N#> zMlKJrGckR>AUbAj%!%YAPIEKB`WYThG!7h^o!ft%o;G~oGt@9M-38p{26O11s&UR- zy|+D4S&)^Rn_L>VK3XDbvLYd;gVhDj_Eq;AoHss^z%F=?(q=@`@|mNqQc_Ns>`I>mmMx{QP{3sNNrH=y{cVKz&*EE?`=re)_tIy-iy9_IP=2 zp-KG+-9W9YwV;*Gb0d0XTFKR#0bp6Y-}3c;rf60^^ih`+xNKHCj$N1_MC3IEHU^4s z=o@X6r1?{S=|77GG5SkiMS8tC0 z^=2?1Q_NuX|DWpy&Q>1dRcS>(!2&P&=k)wP-UOT;g}d*F|1*4BxPjB-$j&~15qE#3 dw%3EXK<({(p9zZi6bSsID696M_?~(2{{i8z@tXhu diff --git a/docs/man/drop_burnin.md b/docs/man/drop_burnin.md deleted file mode 100644 index af44cb85..00000000 --- a/docs/man/drop_burnin.md +++ /dev/null @@ -1,51 +0,0 @@ - - -# Drop Burn-In - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -drop_burnin() removes the burn-in from the Markov Chain -Monte Carlo (MCMC) draws. - -## Usage - -
drop_burnin(model, burn_in)
-
- -## Arguments - - - - - - - - - - -
-model - -A list of MCMC draws from a model fit with fit_model(). -
-burn_in - -An integer number of starting iterations to drop from each MCMC chain. -
- -## Value - -A list of data frames of MCMC draws with burn-in dropped. - -## Examples - -``` r -library(handwriter) - -model <- drop_burnin(model = example_model, burn_in = 25) -plot_trace(variable = "mu[1,2]", model = example_model) -``` - -![](drop_burnin.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) diff --git a/docs/man/drop_burnin_files/figure-html/unnamed-chunk-1-1.png b/docs/man/drop_burnin_files/figure-html/unnamed-chunk-1-1.png new file mode 100644 index 0000000000000000000000000000000000000000..c6062dcce26821e14e22dcbf13445374b7bf0561 GIT binary patch literal 175081 zcmeFZ^;=Y7v_DEIA_58u0wSn{w9*n1N_UrlNDhrKGy{?%AU#NTcQ;6vgfv48-NTSG zzz}zH;@sg#e)uC@Jc1u;H zvA-__&J+s_yj(HEx_;7KY2b?|j_D(q{&GgpC1jIKw?f)kgQfj6mE@puBq56HyOAW@ z>%y?>uDS2{o3BuMc=%2Sb3cW7^Gldt4odd(6(uUY8gKE(_|!@+Sa;3&D@Rnl@qP@) ztw+VPe1$FtKTOkHn|J*4sqR&UWhAI1@QLVF2#L9f1;#|xCc3N8+)w)UyZ4Bbm z`>rRy!u!SA1KjtXy!lM_F_Ml1PEAKwlmSx6Pj%CK#2br~33u#QYH9qT&7oVa;yu?EroWb|N4n+G_#e)U%#2tM#7)~73VPdV zhc-!Rr8P}CZ9CIjP+74%_rWGozK+~<7;R3M8*TFIJ-Eh);QH*&Y1Q%W^8C@d@7-vx z-z9x4qGb9$hh5XgxGF1CmsjfohjtLlyTPsLp2c1L%QbYrXtZ@dI+~WzXLWJy{qnF= z+SfEkxNo1q6317guSSlvPHECs6YfYJ>;1BL zPl5snj5$4A_>0KGDGZwK_Lke57I_!@QWQAt*%en!EsJVMLGLno<*p*Rah2>=1769B zQoandZSn{}oaVYf%Y@q?>25VJ^PzWToZ4(j#ci-CD36ndwoSQ=bmHcly+C( zl1T`ySNo1+sTg+@V>!s@Yq8pb#43KD>xNQuW9s?>#}SzH?`+prrWz@t-96QJvtwAq zn(=Beyun;~cpu|Vz_IGnZ*XrI+z7i(rUromAz-E>Yp$q>#R9y(hlL#s!omYyVFO=O zz!w%4PCCwizjH?{9rwRqt{9mC1<(jbkPH6~HrtO&O||JtV@e=PZ>;8$ti*RjY(pLGD2 zU3Zyx>`f=~=pbNvpkQO)uufh#rDxs1UN`^s^UBAM|5`9HPJ(j0*7)kI@@nS`Z=|Qu ziRlWWX4-Jq&|^F2bH#+3d;+Os4cyn`Tn3-~ zJ4BT6ba3EI2MffgAZj~@2+?b|d*-K;+OFIq!c|TCjl1*qkYj2K&kuGL-Q-HJP~DA1 zPb9c*(Zl)-gMr`dSO3w^OS0Czrm`+xUOX*zHEV&M?-k^w-e106rM+=Da&5mu@xas6 z%11H9&}d5d_z(B~#cmmik6hYH)tDS>U|U@a!qzS~;evG}&9-)SUU0W~br|>-nO%r8 zivQg0w*e4(`#_Yt)GfFq>6=DL&i`O7eR^HJX>I61>vhl`X-^`0>EMT&)HYI7N}K+` zN*01^_peC${rxsEGbu5rWj+fjKv=&3lLkC@?0RGe_eR^wA^2MliCi~RTL$By zB<#<@uWMs`EBb7j4}12vvLakUIa}RIxe3@@;oh#U1I&5#n`u7p#~1EW+bj_aZl%*r z3_2gcI!%7Q>p=iZ-*CMp#vGW{qKN@5UT*L+waXvOg}CoGY|gv39@Dta7ze+jDU3Cv z7nrKVtOL>MS94?l%dhzRLeaXk!Tf0JuQV-~kgZ(oD2e+2Ebq5<>P;cuMG+T&p$0yi z!Dg!GKHhR(<{7H4twr|Ced!y1qaxpIw(J=*`v-!7F<203tlXIk@Hx$LwP2}Z2g3XH ztBC>7F@Y2_sBW|?eQ^xmN;v=GFX2%8=k9Bd>Xw738);nU9sNYdtaxA9%BQ&5;Xj%^ zHZ;m90d3GA-GUdOtv`~gbx8!4d>NPXh`%KAfYeqZcs>9rv`$B_`26d?qw~!-ps*9j zNFm$f+b-85UlaU&f3>aLbUJMW9|AVrZnvaPiPRH=sB3CL!C23)W=9}=Yzgrj>D6~~ zLeA>iuGlTf6W?f1{S2msxE=jmP)K{f07Q+sF=cJ4VgeU~B@as&Q<@joJuc41t(QPq z84T3UW^Vi|MSVx;xU+Q3G!{!+%1<3su?U_vP%_?aVJ)riC;_6m{d(3S4LoO472bq` zS$850Z<e=;VIQ0=py8xxxbsyt`K>fL|kUl`Z7Y0WLEcX1}Ed>~ah zYIU570`HQIh+w-O+_xD z(30z}#jt>>F}Ci1LH0MtSH5?*p03pg1j9JT0@CCv158Ni24pN~(!8TF z#YrPR*T?-PAZIx;Zob~383#UzhL_mU;{iplh0FpL%u5boB)^tAM|IL(j}D36TrM9jxWZ|8 zY)ts)Km3y}Tqa>rrJJabRzKFy3)-Y4_)xQ_CtnXfa+_)wJZ!S}7*ASBGj_lHuMU=Dln^c6U--+vsXX+rNpBqy9Id z4h{)KekS-Ae)L2E3HrA0^vv|AdCkg4h2~{;n{bv0OHJDbL;R<)wU4kw^J;~KKL8gY zgAUFii;IYLqH9fHTW{#NSxc(bVo-%5%0@NGiwc*mBD*L}i6u_2Wx{2wESLKoyM*%bc(Oa@j0P$0V@-f8Dt0_*(&LlbOEy-vQ72+(*ggO(t@EUYP%y;kQa z?4Pw43t+bHu}^%hNL0EJK+X{T9VfqgPpm0L z{fy*)Zqo1aM`F0nGhd7S&&)w@a$6eEi=Le!J1{~XTW6gpXir)F$`7T%Quxg^8h=RI zi61mZ-vo9cZFnvdQ>|{oG`8!FAS(1$nB%Q5w`xM7U@gRjTroLj)-H#d`lMZUCa4Ob z{TKgW_P+(l0Q?+oxY2{<0Tso>&gVGTQ;5=|XK&F8n~ zNi%%Q8@)gwWW9S`V()FeViSaB4tW0_ES8cnE^~k< z5Hj^xD-SC2FHC?yu54IWyGA#9JxLiZWXN$nEi9_0@ziXP_^Ar+i=%(B_;f}b?#VTh z#RqS{0Zfl4qel5{bCpsOg$pZbtyc*6|FvMB z?-9^p(R3&j2@MD?^@Ty(M1i$HRc&9KtwsnD?ASFSYI8S9XSz2II!RphqS;@ucatdz zyr@;$zd4F;tGD;T%=IGy6c%il#t23&66=hC_TXnd{E4V$o?e*$$#L3^7b#~;6`+xR zovM6dD2`<;P5^540FCEf#qE6nXc)hx0R*9d7U-~TScfXwoxFPgSXN@qx~#>;kNWvP zfk%}Ih^h&v`i~cUi*6rojyB(LnX}#GgL@s*J!k<^V*x%osNQvn8m3%j{ZfIbey8&mfb;}*mV7CJcVYi~*YF4&?v338ih!&hfQk$4__TX2KtdiAqUK|RjG?*? z?RWe~RTDGEPGbLFdF+-#RnOy|g}FG97?+-9CvobKZ&yNV6`kkb;8U zY5~H`IQLK(2;6;u<=MJHI*Iu4N*g%8VE@ko2>1g50H(f*j?#?DU|1b{6Z?i|kgZ`Y z+HOPy?M(X9u6{Xa{}t`I%!)!V2`B_?ldb9juB!C)eGwHi$s7tlzvbA0R#AF@GZB~~4pUzH1mDdu;M7mEKxCW|E*C==- zm_Z$pZoNYD&Bw!YwMK`8dOHwc3xh>L92@{pD&eTit#Z5QJ9DzDq_Ft_>OD~8&6BoU z=wdJbjU!n`RFYD^@O6-VAIP7iBtUf}6DO!aWZuk|{#`7+Aah;E{&zXS18byhUsx3b>=l7EE>OU~#Op)f-@k5!RxYJ-<-cI$R=N=1;`#@U z7^!~=8vuI3m~Tto|NjX8-&h6n=fNMN|0@)J=Rb5i>StQGxq{y`B$y}mvsZMH?%UdX zCMCI>CmyTz!;KYtPqxPwfaaI1Nl{W zLX*21an~|YCc@`d^SQ(@D#~4J^uND48P73s1l%V^kEPVh^(V*fCuH-5+~%L!t`PRh<+K6#RP=h!0JI(z|E^Zz=mwa53q<_$Z`wy7@$m$Y zR@z6&`dF<$q?K#n>^C1Pp-Wv`25%Gm){t`m^l++Yuh8OhEaU;+z{9g`WuL@qAs>Ly z3^tFA4Z*Kb{QrSY?3H~l?EnSp0$2yRbAXCiU@0nI*+_9Utn0YXS`U=zp#n0YA5x&Y zS}&dPU)mgiU`wF4_1tf;K+I~_><{lM3j=^8+kAs*yJ{)At-$S1|7 z;hMFkG*?C;t&z4IK%rgJhXJ_C`0;ZJcuID!#&TMrD`hUWgY0$AxA)LzDWvN4IZlE*+k5Zo`;SV+_ySN6q)v138BtRDtVU&jS#= zFM7QyI)60CN!uzOw+uKs;l}e$z=|hT{VcmDCL}eTLSf`}DCs(-YY~UKq-Z;n1l28k z&HqtLyO9z6{60}Mi`$>ik48Vc&YH!8Z(Wsu@25r03g7RMNcoAW>QaZ`wL_*%H;4eB2k;6o2GK#%&)wi$^O>R%1K%Jv?_-0$S{IUnTc$xfbD+r4%6I*c0lcN}v_J`#x8Ow1E5v8Mpbp=roIXled>9z`

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+ + + + + + + + + + + +

+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Example of writership analysis

+
+

Description

+

Example of writership analysis

+
+
+

Usage

+
example_analysis
+
+
+
+

Format

+

The results of analyze_questioned_documents() stored in a named list with 5 items:

+
+
+graph_measurements +
+
+A data frame of that shows the writer, document name, cluster assignment, slope, principle component rotation angle, and wrapped principle component rotation angle for each training graph in each questioned documents. +
+
+cluster_fill_counts +
+
+A data frame of the cluster fill counts for each questioned document. +
+
+likelihoods +
+
+A list of data frames where each data frame contains the likelihoods for a questioned document for each MCMC iteration. +
+
+votes +
+
+A list of vote tallies for each questioned document. +
+
+posterior_probabilites +
+
+A list of posterior probabilities of writership for each questioned document and each known writer in the closed set used to train the hierarchical model. +
+
+
+
+

Examples

+
+
library(handwriter)
+
+plot_cluster_fill_counts(formatted_data = example_analysis)
+
+
+
+

+
+
+
+
plot_posterior_probabilities(analysis = example_analysis)
+
+
+
+

+
+
+
+
+ + +
+
+ +
+ +
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example_analysis
-
- -## Format - -The results of analyze_questioned_documents() stored in a -named list with 5 items: - -
-
-graph_measurements -
-
-A data frame of that shows the writer, document name, cluster -assignment, slope, principle component rotation angle, and wrapped -principle component rotation angle for each training graph in each -questioned documents. -
-
-cluster_fill_counts -
-
-A data frame of the cluster fill counts for each questioned document. -
-
-likelihoods -
-
-A list of data frames where each data frame contains the likelihoods for -a questioned document for each MCMC iteration. -
-
-votes -
-
-A list of vote tallies for each questioned document. -
-
-posterior_probabilites -
-
-A list of posterior probabilities of writership for each questioned -document and each known writer in the closed set used to train the -hierarchical model. -
-
- -## Examples - -``` r -library(handwriter) - -plot_cluster_fill_counts(formatted_data = example_analysis) -``` - -![](example_analysis.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) - -``` r -plot_posterior_probabilities(analysis = example_analysis) -``` - -![](example_analysis.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-2.png) diff --git a/docs/man/example_analysis_files/figure-html/unnamed-chunk-1-1.png b/docs/man/example_analysis_files/figure-html/unnamed-chunk-1-1.png new file mode 100644 index 0000000000000000000000000000000000000000..d1b3dbad7a2d2760a447bdf8c8589e8bba8372db GIT binary patch literal 73416 zcmeFZbx@UW)Hb@=(x8BppaKRUAfSYV#0Es9Q;=5a5R~o^J4gX(R760!8!WmTNfqf5 z>HO9MD)@VSXTF&;=dW}AkYU{H=ec9uYhCMF*Sa4nDM;-nq$Nb5Q2V7XT~I-xa4;y; zzH)qA_@8;>)@~FE`+%8*gp!4Xl!UdVwT!xek27Ntp%5c| zmoOMKxTXD$`I!0JsmJUuvz11UH9~Dte#+GK!WLVrBIvxnOz`o%WhBGbgCBBG8i%4uW-}YZ z0=ORNOP)TJ^knm6&jY-X6N_5dc($`WzCyeSDJ;ipC9BW94OckPTH>?jnJd|6@v+B8 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+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Example cluster template

+
+

Description

+

An example cluster template created with make_clustering_template(). The cluster template was created from handwriting samples "w0016_s01_pLND_r01.png", "w0080_s01_pLND_r01.png", "w0124_s01_pLND_r01.png", "w0138_s01_pLND_r01.png", and "w0299_s01_pLND_r01.png" from the CSAFE Handwriting Database. The template has K=5 clusters.

+
+
+

Usage

+
example_cluster_template
+
+
+
+

Format

+

A list containing a single cluster template created by make_clustering_template(). The cluster template was created by sorting a random sample of 1000 graphs from 10 training documents into 10 clusters with a K-means algorithm. The cluster template is a named list with 16 items:

+
+
+centers_seed +
+
+An integer for the random number generator. +
+
+cluster +
+
+A vector of cluster assignments for each graph used to create the cluster template. +
+
+centers +
+
+The final cluster centers produced by the K-Means algorithm. +
+
+K +
+
+The number of clusters to build (10) with the K-means algorithm. +
+
+n +
+
+The number of training graphs to use (1000) in the K-means algorithm. +
+
+docnames +
+
+A vector that lists the training document from which each graph originated. +
+
+writers +
+
+A vector that lists the writer of each graph. +
+
+iters +
+
+The maximum number of iterations for the K-means algorithm (3). +
+
+changes +
+
+A vector of the number of graphs that changed clusters on each iteration of the K-means algorithm. +
+
+outlierCutoff +
+
+A vector of the outlier cutoff values calculated on each iteration of the K-means algorithm. +
+
+stop_reason +
+
+The reason the K-means algorithm terminated. +
+
+wcd +
+
+A matrix of the within cluster distances on each iteration of the K-means algorithm. More specifically, the distance between each graph and the center of the cluster to which it was assigned on each iteration. +
+
+wcss +
+
+A vector of the within-cluster sum of squares on each iteration of the K-means algorithm. +
+
+
+
+

Examples

+
+
library(handwriter)
+
+# view cluster fill counts for template training documents
+template_data <- format_template_data(example_cluster_template)
+plot_cluster_fill_counts(template_data, facet = TRUE)
+
+
+
+

+
+
+
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/example_cluster_template.md b/docs/man/example_cluster_template.md deleted file mode 100644 index 4a526fce..00000000 --- a/docs/man/example_cluster_template.md +++ /dev/null @@ -1,126 +0,0 @@ - - -# Example cluster template - -## Description - -An example cluster template created with -make_clustering_template(). The cluster template was -created from handwriting samples "w0016_s01_pLND_r01.png", -"w0080_s01_pLND_r01.png", "w0124_s01_pLND_r01.png", -"w0138_s01_pLND_r01.png", and "w0299_s01_pLND_r01.png" from the CSAFE -Handwriting Database. The template has K=5 clusters. - -## Usage - -
example_cluster_template
-
- -## Format - -A list containing a single cluster template created by -make_clustering_template(). The cluster template was -created by sorting a random sample of 1000 graphs from 10 training -documents into 10 clusters with a K-means algorithm. The cluster -template is a named list with 16 items: - -
-
-centers_seed -
-
-An integer for the random number generator. -
-
-cluster -
-
-A vector of cluster assignments for each graph used to create the -cluster template. -
-
-centers -
-
-The final cluster centers produced by the K-Means algorithm. -
-
-K -
-
-The number of clusters to build (10) with the K-means algorithm. -
-
-n -
-
-The number of training graphs to use (1000) in the K-means algorithm. -
-
-docnames -
-
-A vector that lists the training document from which each graph -originated. -
-
-writers -
-
-A vector that lists the writer of each graph. -
-
-iters -
-
-The maximum number of iterations for the K-means algorithm (3). -
-
-changes -
-
-A vector of the number of graphs that changed clusters on each iteration -of the K-means algorithm. -
-
-outlierCutoff -
-
-A vector of the outlier cutoff values calculated on each iteration of -the K-means algorithm. -
-
-stop_reason -
-
-The reason the K-means algorithm terminated. -
-
-wcd -
-
-A matrix of the within cluster distances on each iteration of the -K-means algorithm. More specifically, the distance between each graph -and the center of the cluster to which it was assigned on each -iteration. -
-
-wcss -
-
-A vector of the within-cluster sum of squares on each iteration of the -K-means algorithm. -
-
- -## Examples - -``` r -library(handwriter) - -# view cluster fill counts for template training documents -template_data <- format_template_data(example_cluster_template) -plot_cluster_fill_counts(template_data, facet = TRUE) -``` - -![](example_cluster_template.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) diff --git a/docs/man/example_cluster_template_files/figure-html/unnamed-chunk-1-1.png b/docs/man/example_cluster_template_files/figure-html/unnamed-chunk-1-1.png new file mode 100644 index 0000000000000000000000000000000000000000..e932fcf1daaa62fd988473bc1ed5f0490b313a83 GIT binary patch literal 93034 zcmbrmby!s0_dYzNgb0F&(n^Vxk^%yQA|Wj$=zvNNsdR@JC@Cr3UD6#YjYu=nNC^xf z-SFE(=sfSo?_ck8T@TkdXZAUJ@3r=dd)@22Q&Ny3BA_IIKp;di(h?6K5F983f>n!$ z3%*%1=TWD|Oex)WTBb`BPneDSdN&OStX>sXGwJEni%skhVClQUAN+U!zOiuo{IhjH(V}^ zVwG-$UAGMV`IaPBZF0!kE0+^qP)~BGUk1ltW`MvdDqmX?EQ{9ZsyS6s&se8t2z1u6 zrS^myl8k!V+kC#=(y%D8S9DV+ionM8LDbo4Vp_=9_;rp?j++d$pXA}!y;^-WjQAT@ 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z$ct*!7{C4k-cqq2csfOJ<6~fb`Lrr1>!V`6;$qMc@v%Nx=@XZ?=f_tAuf+uI6>|Tw zCFDRzWS?;q%%y&IeZ5jhpO$zcB_@U7-s5&n2+O}wWyk7fm-Modfv!PA4;jD%o|9t-h5^WZ^xT`6#MV6u<%nX8LK8l6;G?YGX_ z#k82q0d$2*VmI(QuizZu4Q$I4e{uP}ySMjt*qVsMs2v{8w?p@}J$)@G^CzTnZS?lC zy>8i8RtRd`e|_*(t_5(bt&d|EYn|znILElDZ+T||hi)Ig1*X;wz+L>$xaz8oe-=h0 z?=oPSc`WakAX2gtxS-??9HlSct0S5LYKA$bUzAzI)wb&UvZ~6e;u5#$6>WQfv)yga zvMY9rsRi|4$hZV-J>>(p78T}pY?-v1X&={yRe4c0p1FK+XYFPcPh>|}2ioj&!tM>y z`ZMINhdj3d%e~{`{i_fq5uy?Sc7IcVxpQLejc#}VLkdnP*ACd_c=fp39jPgcD6xS9 zy@c!r?*96Cbnz=hNFcKWB7t3!6!~w642kTrhJIj+;Mb2wfu-;o0q$pz2Rn3tJ*`dr z)rd+G*<}Zg18eNsnvW~2;B^6t4_$yBle*cy7uh`spFc6l)KXq45OJW6Hlbh@%7se2T3G7%EpNi0&WtCd&%-esB13 Qg8>LUUHx3vIVCg!0D4>8AOHXW literal 0 HcmV?d00001 diff --git a/docs/man/example_model.html b/docs/man/example_model.html new file mode 100644 index 00000000..91bffa38 --- /dev/null +++ b/docs/man/example_model.html @@ -0,0 +1,968 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Example of a hierarchical model

+
+

Description

+

Example of a hierarchical model

+
+
+

Usage

+
example_model
+
+
+
+

Format

+

A hierarchical model created by fit_model with a single chain of 100 MCMC iterations. It is a named list of 4 objects:

+
+
+graph_measurements +
+
+A data frame of model training data that shows the writer, document name, cluster assignment, slope, principle component rotation angle, and wrapped principle component rotation angle for each training graph. +
+
+cluster_fill_counts +
+
+A data frame of the cluster fill counts for each model training document. +
+
+rjags_data +
+
+The model training information from graph_measurements and cluster_fill_counts formatted for RJAGS. +
+
+fitted_model +
+
+A model fit using the rjags_data and the RJAGS and coda packages. It is an MCMC list that contains a single MCMC object. +
+
+
+
+

Examples

+
+
library(handwriter)
+
+# convert to a data frame and view all variable names
+df <- as.data.frame(coda::as.mcmc(example_model$fitted_model))
+colnames(df)
+
+# view a trace plot
+plot_trace(variable = "mu[1,1]", model = example_model)
+
+# drop the first 25 MCMC iterations for burn-in
+model <- drop_burnin(model = example_model, burn_in = 25)
+
+# analyze questioned documents
+main_dir <- /path/to/main_dir
+questioned_docs <- /path/to/questioned_documents_directory
+analysis <- analyze_questioned_documents(
+   main_dir = main_dir,
+   questioned_docs = questioned_docs
+   model = example_model
+   num_cores = 2
+)
+analysis$posterior_probabilities
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/example_model.md b/docs/man/example_model.md deleted file mode 100644 index 4be26f2d..00000000 --- a/docs/man/example_model.md +++ /dev/null @@ -1,76 +0,0 @@ - - -# Example of a hierarchical model - -## Description - -Example of a hierarchical model - -## Usage - -
example_model
-
- -## Format - -A hierarchical model created by fit_model with a single -chain of 100 MCMC iterations. It is a named list of 4 objects: - -
-
-graph_measurements -
-
-A data frame of model training data that shows the writer, document -name, cluster assignment, slope, principle component rotation angle, and -wrapped principle component rotation angle for each training graph. -
-
-cluster_fill_counts -
-
-A data frame of the cluster fill counts for each model training -document. -
-
-rjags_data -
-
-The model training information from graph_measurements and -cluster_fill_counts formatted for RJAGS. -
-
-fitted_model -
-
-A model fit using the rjags_data and the RJAGS and coda -packages. It is an MCMC list that contains a single MCMC object. -
-
- -## Examples - -``` r -library(handwriter) - -# convert to a data frame and view all variable names -df <- as.data.frame(coda::as.mcmc(example_model$fitted_model)) -colnames(df) - -# view a trace plot -plot_trace(variable = "mu[1,1]", model = example_model) - -# drop the first 25 MCMC iterations for burn-in -model <- drop_burnin(model = example_model, burn_in = 25) - -# analyze questioned documents -main_dir <- /path/to/main_dir -questioned_docs <- /path/to/questioned_documents_directory -analysis <- analyze_questioned_documents( - main_dir = main_dir, - questioned_docs = questioned_docs - model = example_model - num_cores = 2 -) -analysis$posterior_probabilities -``` diff --git a/docs/man/extractGraphs.html b/docs/man/extractGraphs.html new file mode 100644 index 00000000..3f33520d --- /dev/null +++ b/docs/man/extractGraphs.html @@ -0,0 +1,951 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Extract Graphs

+
+

Description

+

‘r lifecycle::badge("superseded")’

+
+
+

Usage

+
extractGraphs(source_folder = getwd(), save_folder = getwd())
+
+
+
+

Arguments

+ + + + + + + + + +
+source_folder + +path to folder containing .png images +
+save_folder + +path to folder where graphs are saved to +
+
+
+

Details

+

Development on ‘extractGraphs()’ is complete. We recommend using ‘process_batch_dir()’ instead.

+

Extracts graphs from .png images and saves each by their respective writer.

+
+
+

Value

+

saves graphs in an rds file

+
+
+

Examples

+
+
library(handwriter)
+
+sof = "path to folder containing .png images"
+saf = "path to folder where graphs will be saved to"
+extractGraphs(sof, saf)
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/extractGraphs.md b/docs/man/extractGraphs.md deleted file mode 100644 index 0400bd11..00000000 --- a/docs/man/extractGraphs.md +++ /dev/null @@ -1,57 +0,0 @@ - - -# Extract Graphs - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -‘r lifecycle::badge("superseded")’ - -## Usage - -
extractGraphs(source_folder = getwd(), save_folder = getwd())
-
- -## Arguments - - - - - - - - - - -
-source_folder - -path to folder containing .png images -
-save_folder - -path to folder where graphs are saved to -
- -## Details - -Development on ‘extractGraphs()’ is complete. We recommend using -‘process_batch_dir()’ instead. - -Extracts graphs from .png images and saves each by their respective -writer. - -## Value - -saves graphs in an rds file - -## Examples - -``` r -library(handwriter) - -sof = "path to folder containing .png images" -saf = "path to folder where graphs will be saved to" -extractGraphs(sof, saf) -``` diff --git a/docs/man/figures/README-image-1.png b/docs/man/figures/README-image-1.png index b8f0d40333a1c928b2a8b30e117149ae3fb0d9c0..047eecad6cb4f1c49f0d655d2ff20007590ee6c8 100644 GIT binary patch literal 33134 zcmeHwdpy%^_`g#{N2Q~4d87kL$obHT=Siibvng|IX`wj{Un&>fBgRW{j)#3UZ2-zpWUD9zV7RKU+?RE-?(}FnDvUK z@=L|U#8&+E=fRU=Vv8)r#3ZYv7Xx=jy_(y_#H3dG9yo9ua=`ik^a3>C)TMJ^PixPM zo&mn#lh*si#0=x&&baz0o>^=DsI+kBAH*vySy}g1PU}A?x^VKt)sFsY&qBXW&HERM z_T8x)>`L?9s>_&s;=A2^?LOHz&${n-&p5x)*nB>ReOv3FqT~NaUD-C)G-3Vt;|3X4 zscvD}{SpYSzH_`Ul^e;V1#)Q1?v!XcC(zU-H0ATPdYgL+34PVo#+TnjG_8ne(%KpS zaL2=~;tGtnl^txZDxOB+V+Awbto-BF;xS#<+HwuwZ|U(An_gG*$~8)ApRiVj;yxx* 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zc=O4kx1N9=>pe0|1nEEA!sW7X@rv^bAhgBDauc{*CUk?(8!~nf^Ndo{9y95U1G|Z{ zJ9zwOyo3_aFv*7R8J_(4OY#7)m0?|$A@)?7{5(;F`RvUuPH`k7P`SF2j# z<}kDIXqC17&P;hpNlBIK&8soWxm>8t4@lT5m%Z0)|1jM!BvdE~Gd`3*^Tgu~>v*{O z7WjM1(%EY3_OgR_E-o$>mC^JXDsSI@=5#*oPnfKGXWbvY$@AqKD92Ts<5dV(WPA~*N-LXCUiqL9m;iFoOft~0CJ0}|!UYNn z)>DN4m0V^+xVhs@P7amR?wkj=F6gc*;c_{z>O=H4o2nYfr_8|sg*fXkin__8BO}!e zDjH>=&bS@p_E*DH=y&_vZalAQ%`%S;EJ**12MWdzfnviNU=h2yCXcxqKqb|Pi<)vR zvM{Ptnk9ht%DdX2B(HN11;4C7t@cG%nOu{cNB6ibSNTlFtgU)&-G=K>rj-3b_D2^G zi@!{jmzTe=oNv*r+y128d@txgxGy0V3Q_`2|1!M-l%+t3C^W=A9d9yu=6>g|9(w^# zL#FeC*Kt%O3Q9}^Ee$5 zGl%jtdwTfcBY7w*P;?c^e9UYVFvQoilP#nHs4~BO>zq1$k1D z%ei%GxEPeg&m)i5N2rZWOl)SKnvmPWIX~1KDK$JGby*po-juDz*8aQPUqQ(Emk<6U z1|%?`VI{+IedWdv4*Da@zdru~1IyFwvMTV$DgKQgJWw9+z$OBBgWFU8j_qf(`FRYU zDiDJ$2ps>$zrSLk@(_Ln$0oj9*jxSU$N%{Xm5vAM`IL|PpGE%T4 + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Fit Model

+
+

Description

+

fit_model() fits a Bayesian hierarchical model to the model training data in model_docs and draws samples from the model as Markov Chain Monte Carlo (MCMC) estimates.

+
+
+

Usage

+
fit_model(
+  main_dir,
+  model_docs,
+  num_iters,
+  num_chains = 1,
+  num_cores,
+  writer_indices,
+  doc_indices,
+  a = 2,
+  b = 0.25,
+  c = 2,
+  d = 2,
+  e = 0.5
+)
+
+
+
+

Arguments

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+main_dir + +A directory that contains a cluster template created by make_clustering_template() +
+model_docs + +A directory containing model training documents +
+num_iters + +An integer number of iterations of MCMC. +
+num_chains + +An integer number of chains to use. +
+num_cores + +An integer number of cores to use for parallel processing clustering assignments. The model fitting is not done in parallel. +
+writer_indices + +A vector of the start and stop character of the writer ID in the model training file names. E.g., if the file names are writer0195_doc1, writer0210_doc1, writer0033_doc1 then writer_indices is ‘c(7,10)’. +
+doc_indices + +A vector of the start and stop character of the "document name" in the model training file names. This is used to distinguish between two documents written by the same writer. E.g., if the file names are writer0195_doc1, writer0195_doc2, writer0033_doc1, writer0033_doc2 then doc_indices are ‘c(12,15)’. +
+a + +The shape parameter for the Gamma distribution in the hierarchical model +
+b + +The rate parameter for the Gamma distribution in the hierarchical model +
+c + +The first shape parameter for the Beta distribution in the hierarchical model +
+d + +The second shape parameter for the Beta distribution in the hierarchical model +
+e + +The scale parameter for the hyper prior for mu in the hierarchical model +
+
+
+

Value

+

A list of training data used to fit the model and the fitted model

+
+
+

Examples

+
+
library(handwriter)
+
+main_dir <- "/path/to/main_dir"
+model_docs <- "path/to/model_training_docs"
+questioned_docs <- "path/to/questioned_docs"
+
+model <- fit_model(
+  main_dir = main_dir,
+  model_docs = model_docs,
+  num_iters = 100,
+  num_chains = 1,
+  num_cores = 2,
+  writer_indices = c(2, 5),
+  doc_indices = c(7, 18)
+)
+
+model <- drop_burnin(model = model, burn_in = 25)
+
+analysis <- analyze_questioned_documents(
+  main_dir = main_dir,
+  questioned_docs = questioned_docs,
+  model = model,
+  num_cores = 2
+)
+analysis$posterior_probabilities
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/fit_model.md b/docs/man/fit_model.md deleted file mode 100644 index db53da2e..00000000 --- a/docs/man/fit_model.md +++ /dev/null @@ -1,174 +0,0 @@ - - -# Fit Model - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -fit_model() fits a Bayesian hierarchical model to the model -training data in model_docs and draws samples from the -model as Markov Chain Monte Carlo (MCMC) estimates. - -## Usage - -
fit_model(
-  main_dir,
-  model_docs,
-  num_iters,
-  num_chains = 1,
-  num_cores,
-  writer_indices,
-  doc_indices,
-  a = 2,
-  b = 0.25,
-  c = 2,
-  d = 2,
-  e = 0.5
-)
-
- -## Arguments - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
-main_dir - -A directory that contains a cluster template created by -make_clustering_template() -
-model_docs - -A directory containing model training documents -
-num_iters - -An integer number of iterations of MCMC. -
-num_chains - -An integer number of chains to use. -
-num_cores - -An integer number of cores to use for parallel processing clustering -assignments. The model fitting is not done in parallel. -
-writer_indices - -A vector of the start and stop character of the writer ID in the model -training file names. E.g., if the file names are writer0195_doc1, -writer0210_doc1, writer0033_doc1 then writer_indices is ‘c(7,10)’. -
-doc_indices - -A vector of the start and stop character of the "document name" in the -model training file names. This is used to distinguish between two -documents written by the same writer. E.g., if the file names are -writer0195_doc1, writer0195_doc2, writer0033_doc1, writer0033_doc2 then -doc_indices are ‘c(12,15)’. -
-a - -The shape parameter for the Gamma distribution in the hierarchical model -
-b - -The rate parameter for the Gamma distribution in the hierarchical model -
-c - -The first shape parameter for the Beta distribution in the hierarchical -model -
-d - -The second shape parameter for the Beta distribution in the hierarchical -model -
-e - -The scale parameter for the hyper prior for mu in the hierarchical model -
- -## Value - -A list of training data used to fit the model and the fitted model - -## Examples - -``` r -library(handwriter) - -main_dir <- "/path/to/main_dir" -model_docs <- "path/to/model_training_docs" -questioned_docs <- "path/to/questioned_docs" - -model <- fit_model( - main_dir = main_dir, - model_docs = model_docs, - num_iters = 100, - num_chains = 1, - num_cores = 2, - writer_indices = c(2, 5), - doc_indices = c(7, 18) -) - -model <- drop_burnin(model = model, burn_in = 25) - -analysis <- analyze_questioned_documents( - main_dir = main_dir, - questioned_docs = questioned_docs, - model = model, - num_cores = 2 -) -analysis$posterior_probabilities -``` diff --git a/docs/man/format_template_data.html b/docs/man/format_template_data.html new file mode 100644 index 00000000..217fdeb3 --- /dev/null +++ b/docs/man/format_template_data.html @@ -0,0 +1,944 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Format Template Data

+
+

Description

+

format_template_data() formats the template data for use with plot_cluster_fill_counts(). The output is a list that contains a data frame called cluster_fill_counts.

+
+
+

Usage

+
format_template_data(template)
+
+
+
+

Arguments

+ + + + + +
+template + +A single cluster template created by make_clustering_template() +
+
+
+

Value

+

List that contains the cluster fill counts

+
+
+

Examples

+
+
library(handwriter)
+
+template_data <- format_template_data(template = example_cluster_template)
+plot_cluster_fill_counts(formatted_data = template_data, facet = TRUE)
+
+
+
+

+
+
+
+
+ + +
+
+ +
+ +
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zw^-N%(RM!AFQap`n>=@(p7`W9*SQg%dwwawDeu3VMR>twb;i%_=A%5Oaz6c>k|eBk z2jj!d==+EW;1=cg0M#@P{msd1>q;y3|2X0yLNsR<_E%ld{`iDYCk#KOi?-E%xX|Hx aIdzuSH)&C3vgdUm1s_K{Hformat_template_data() formats the template data for use -with plot_cluster_fill_counts(). The output is a list that -contains a data frame called cluster_fill_counts. - -## Usage - -

format_template_data(template)
-
- -## Arguments - - - - - - -
-template - -A single cluster template created by -make_clustering_template() -
- -## Value - -List that contains the cluster fill counts - -## Examples - -``` r -library(handwriter) - -template_data <- format_template_data(template = example_cluster_template) -plot_cluster_fill_counts(formatted_data = template_data, facet = TRUE) -``` - -![](format_template_data.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) diff --git a/docs/man/format_template_data_files/figure-html/unnamed-chunk-1-1.png b/docs/man/format_template_data_files/figure-html/unnamed-chunk-1-1.png new file mode 100644 index 0000000000000000000000000000000000000000..e932fcf1daaa62fd988473bc1ed5f0490b313a83 GIT binary patch literal 93034 zcmbrmby!s0_dYzNgb0F&(n^Vxk^%yQA|Wj$=zvNNsdR@JC@Cr3UD6#YjYu=nNC^xf z-SFE(=sfSo?_ck8T@TkdXZAUJ@3r=dd)@22Q&Ny3BA_IIKp;di(h?6K5F983f>n!$ z3%*%1=TWD|Oex)WTBb`BPneDSdN&OStX>sXGwJEni%skhVClQUAN+U!zOiuo{IhjH(V}^ zVwG-$UAGMV`IaPBZF0!kE0+^qP)~BGUk1ltW`MvdDqmX?EQ{9ZsyS6s&se8t2z1u6 zrS^myl8k!V+kC#=(y%D8S9DV+ionM8LDbo4Vp_=9_;rp?j++d$pXA}!y;^-WjQAT@ 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z$ct*!7{C4k-cqq2csfOJ<6~fb`Lrr1>!V`6;$qMc@v%Nx=@XZ?=f_tAuf+uI6>|Tw zCFDRzWS?;q%%y&IeZ5jhpO$zcB_@U7-s5&n2+O}wWyk7fm-Modfv!PA4;jD%o|9t-h5^WZ^xT`6#MV6u<%nX8LK8l6;G?YGX_ z#k82q0d$2*VmI(QuizZu4Q$I4e{uP}ySMjt*qVsMs2v{8w?p@}J$)@G^CzTnZS?lC zy>8i8RtRd`e|_*(t_5(bt&d|EYn|znILElDZ+T||hi)Ig1*X;wz+L>$xaz8oe-=h0 z?=oPSc`WakAX2gtxS-??9HlSct0S5LYKA$bUzAzI)wb&UvZ~6e;u5#$6>WQfv)yga zvMY9rsRi|4$hZV-J>>(p78T}pY?-v1X&={yRe4c0p1FK+XYFPcPh>|}2ioj&!tM>y z`ZMINhdj3d%e~{`{i_fq5uy?Sc7IcVxpQLejc#}VLkdnP*ACd_c=fp39jPgcD6xS9 zy@c!r?*96Cbnz=hNFcKWB7t3!6!~w642kTrhJIj+;Mb2wfu-;o0q$pz2Rn3tJ*`dr z)rd+G*<}Zg18eNsnvW~2;B^6t4_$yBle*cy7uh`spFc6l)KXq45OJW6Hlbh@%7se2T3G7%EpNi0&WtCd&%-esB13 Qg8>LUUHx3vIVCg!0D4>8AOHXW literal 0 HcmV?d00001 diff --git a/docs/man/get_cluster_fill_counts.html b/docs/man/get_cluster_fill_counts.html new file mode 100644 index 00000000..01fc8683 --- /dev/null +++ b/docs/man/get_cluster_fill_counts.html @@ -0,0 +1,950 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

get_cluster_fill_counts

+
+

Description

+

get_cluster_fill_counts() creates a data frame that shows the number of graphs in each cluster for each input document.

+
+
+

Usage

+
get_cluster_fill_counts(df)
+
+
+
+

Arguments

+ + + + + +
+df + +A data frame with columns writer, doc, and cluster. Each row corresponding to a graph and lists the writer of that graph, the document from which the graph was obtained, and the cluster to which that graph is assigned. +
+
+
+

Value

+

A dataframe of cluster fill counts for each document in the input data frame.

+
+
+

Examples

+
+
library(handwriter)
+
+writer <- c(rep(1, 20), rep(2, 20), rep(3, 20))
+docname <- c(rep('doc1',20), rep('doc2', 20), rep('doc3', 20))
+doc <- c(rep(1, 20), rep(2, 20), rep(3, 20))
+cluster <- sample(3, 60, replace=TRUE)
+df <- data.frame(docname, writer, doc, cluster)
+get_cluster_fill_counts(df)
+
+
# A tibble: 3 × 6
+# Groups:   docname, writer, doc [3]
+  docname writer   doc   `1`   `2`   `3`
+  <chr>    <dbl> <dbl> <int> <int> <int>
+1 doc1         1     1     3     6    11
+2 doc2         2     2     5    10     5
+3 doc3         3     3     8     4     8
+
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/get_cluster_fill_counts.md b/docs/man/get_cluster_fill_counts.md deleted file mode 100644 index 80034185..00000000 --- a/docs/man/get_cluster_fill_counts.md +++ /dev/null @@ -1,57 +0,0 @@ - - -# get_cluster_fill_counts - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -get_cluster_fill_counts() creates a data frame that shows -the number of graphs in each cluster for each input document. - -## Usage - -
get_cluster_fill_counts(df)
-
- -## Arguments - - - - - - -
-df - -A data frame with columns writer, doc, and -cluster. Each row corresponding to a graph and lists the -writer of that graph, the document from which the graph was obtained, -and the cluster to which that graph is assigned. -
- -## Value - -A dataframe of cluster fill counts for each document in the input data -frame. - -## Examples - -``` r -library(handwriter) - -writer <- c(rep(1, 20), rep(2, 20), rep(3, 20)) -docname <- c(rep('doc1',20), rep('doc2', 20), rep('doc3', 20)) -doc <- c(rep(1, 20), rep(2, 20), rep(3, 20)) -cluster <- sample(3, 60, replace=TRUE) -df <- data.frame(docname, writer, doc, cluster) -get_cluster_fill_counts(df) -``` - - # A tibble: 3 × 6 - # Groups: docname, writer, doc [3] - docname writer doc `1` `2` `3` - - 1 doc1 1 1 6 6 8 - 2 doc2 2 2 4 8 8 - 3 doc3 3 3 6 4 10 diff --git a/docs/man/get_clusters_batch.html b/docs/man/get_clusters_batch.html new file mode 100644 index 00000000..6ab7c858 --- /dev/null +++ b/docs/man/get_clusters_batch.html @@ -0,0 +1,988 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

get_clusters_batch

+
+

Description

+

get_clusters_batch

+
+
+

Usage

+
get_clusters_batch(
+  template,
+  input_dir,
+  output_dir,
+  writer_indices,
+  doc_indices,
+  num_cores = 1
+)
+
+
+
+

Arguments

+ + + + + + + + + + + + + + + + + + + + + + + + + +
+template + +A cluster template created with make_clustering_template +
+input_dir + +A directory containing graphs created with process_batch_dir +
+output_dir + +Output directory for cluster assignments +
+writer_indices + +Vector of start and end indices for the writer id in the graph file names +
+doc_indices + +Vector of start and end indices for the document id in the graph file names +
+num_cores + +Integer number of cores to use for parallel processing +
+
+
+

Value

+

A list of cluster assignments

+
+
+

Examples

+
+
library(handwriter)
+
+template <- readRDS('path/to/template.rds')
+get_clusters_batch(template=template, input_dir='path/to/dir', output_dir='path/to/dir',
+writer_indices=c(2,5), doc_indices=c(7,18), num_cores=1)
+
+get_clusters_batch(template=template, input_dir='path/to/dir', output_dir='path/to/dir',
+writer_indices=c(1,4), doc_indices=c(5,10), num_cores=5)
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/get_clusters_batch.md b/docs/man/get_clusters_batch.md deleted file mode 100644 index ef96404e..00000000 --- a/docs/man/get_clusters_batch.md +++ /dev/null @@ -1,94 +0,0 @@ - - -# get_clusters_batch - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -get_clusters_batch - -## Usage - -
get_clusters_batch(
-  template,
-  input_dir,
-  output_dir,
-  writer_indices,
-  doc_indices,
-  num_cores = 1
-)
-
- -## Arguments - - - - - - - - - - - - - - - - - - - - - - - - - - -
-template - -A cluster template created with make_clustering_template -
-input_dir - -A directory containing graphs created with -process_batch_dir -
-output_dir - -Output directory for cluster assignments -
-writer_indices - -Vector of start and end indices for the writer id in the graph file -names -
-doc_indices - -Vector of start and end indices for the document id in the graph file -names -
-num_cores - -Integer number of cores to use for parallel processing -
- -## Value - -A list of cluster assignments - -## Examples - -``` r -library(handwriter) - -template <- readRDS('path/to/template.rds') -get_clusters_batch(template=template, input_dir='path/to/dir', output_dir='path/to/dir', -writer_indices=c(2,5), doc_indices=c(7,18), num_cores=1) - -get_clusters_batch(template=template, input_dir='path/to/dir', output_dir='path/to/dir', -writer_indices=c(1,4), doc_indices=c(5,10), num_cores=5) -``` diff --git a/docs/man/get_credible_intervals.html b/docs/man/get_credible_intervals.html new file mode 100644 index 00000000..2925c76f --- /dev/null +++ b/docs/man/get_credible_intervals.html @@ -0,0 +1,991 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Get Credible Intervals

+
+

Description

+

In a model created with fit_model() the pi parameters are the estimate of the true cluster fill count for a particular writer and cluster. The function get_credible_intervals() calculates the credible intervals of the pi parameters for each writer in the model.

+
+
+

Usage

+
get_credible_intervals(model, interval_min = 0.05, interval_max = 0.95)
+
+
+
+

Arguments

+ + + + + + + + + + + + + +
+model + +A model output by fit_model() +
+interval_min + +The lower bound for the credible interval. The number must be between 0 and 1. +
+interval_max + +The upper bound for the credible interval. The number must be greater than interval_min and must be less than 1. +
+
+
+

Value

+

A list of data frames. Each data frame lists the credible intervals for a single writer.

+
+
+

Examples

+
+
library(handwriter)
+
+get_credible_intervals(model=example_model)
+
+
[[1]]
+  quantile  cluster_1  cluster_2 cluster_3 cluster_4 cluster_5 writer
+1       5% 0.06042425 0.02493705 0.1418073 0.5529695 0.1306786  w0009
+2      50% 0.07366519 0.03478669 0.1647020 0.5782510 0.1489102  w0009
+3      95% 0.08875836 0.04671823 0.1840218 0.6088443 0.1701284  w0009
+
+[[2]]
+  quantile   cluster_1    cluster_2 cluster_3 cluster_4 cluster_5 writer
+1       5% 0.008342953 5.982238e-05 0.2480043 0.4153643 0.2096460  w0030
+2      50% 0.017026968 1.492831e-03 0.2840930 0.4549356 0.2402698  w0030
+3      95% 0.029416108 8.076710e-03 0.3161589 0.4931652 0.2830293  w0030
+
+[[3]]
+  quantile  cluster_1  cluster_2  cluster_3 cluster_4  cluster_5 writer
+1       5% 0.02039637 0.01621031 0.08938908 0.7044609 0.08201707  w0238
+2      50% 0.02877164 0.02494265 0.10993121 0.7323968 0.10357189  w0238
+3      95% 0.04086654 0.03510818 0.12997545 0.7596250 0.12387242  w0238
+
+
get_credible_intervals(model=example_model, interval_min=0.05, interval_max=0.95)
+
+
[[1]]
+  quantile  cluster_1  cluster_2 cluster_3 cluster_4 cluster_5 writer
+1       5% 0.06042425 0.02493705 0.1418073 0.5529695 0.1306786  w0009
+2      50% 0.07366519 0.03478669 0.1647020 0.5782510 0.1489102  w0009
+3      95% 0.08875836 0.04671823 0.1840218 0.6088443 0.1701284  w0009
+
+[[2]]
+  quantile   cluster_1    cluster_2 cluster_3 cluster_4 cluster_5 writer
+1       5% 0.008342953 5.982238e-05 0.2480043 0.4153643 0.2096460  w0030
+2      50% 0.017026968 1.492831e-03 0.2840930 0.4549356 0.2402698  w0030
+3      95% 0.029416108 8.076710e-03 0.3161589 0.4931652 0.2830293  w0030
+
+[[3]]
+  quantile  cluster_1  cluster_2  cluster_3 cluster_4  cluster_5 writer
+1       5% 0.02039637 0.01621031 0.08938908 0.7044609 0.08201707  w0238
+2      50% 0.02877164 0.02494265 0.10993121 0.7323968 0.10357189  w0238
+3      95% 0.04086654 0.03510818 0.12997545 0.7596250 0.12387242  w0238
+
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/get_credible_intervals.md b/docs/man/get_credible_intervals.md deleted file mode 100644 index def6a94b..00000000 --- a/docs/man/get_credible_intervals.md +++ /dev/null @@ -1,102 +0,0 @@ - - -# Get Credible Intervals - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -In a model created with fit_model() the pi parameters are -the estimate of the true cluster fill count for a particular writer and -cluster. The function get_credible_intervals() calculates -the credible intervals of the pi parameters for each writer in the -model. - -## Usage - -
get_credible_intervals(model, interval_min = 0.05, interval_max = 0.95)
-
- -## Arguments - - - - - - - - - - - - - - -
-model - -A model output by fit_model() -
-interval_min - -The lower bound for the credible interval. The number must be between 0 -and 1. -
-interval_max - -The upper bound for the credible interval. The number must be greater -than interval_min and must be less than 1. -
- -## Value - -A list of data frames. Each data frame lists the credible intervals for -a single writer. - -## Examples - -``` r -library(handwriter) - -get_credible_intervals(model=example_model) -``` - - [[1]] - quantile cluster_1 cluster_2 cluster_3 cluster_4 cluster_5 writer - 1 5% 0.06042425 0.02493705 0.1418073 0.5529695 0.1306786 w0009 - 2 50% 0.07366519 0.03478669 0.1647020 0.5782510 0.1489102 w0009 - 3 95% 0.08875836 0.04671823 0.1840218 0.6088443 0.1701284 w0009 - - [[2]] - quantile cluster_1 cluster_2 cluster_3 cluster_4 cluster_5 writer - 1 5% 0.008342953 5.982238e-05 0.2480043 0.4153643 0.2096460 w0030 - 2 50% 0.017026968 1.492831e-03 0.2840930 0.4549356 0.2402698 w0030 - 3 95% 0.029416108 8.076710e-03 0.3161589 0.4931652 0.2830293 w0030 - - [[3]] - quantile cluster_1 cluster_2 cluster_3 cluster_4 cluster_5 writer - 1 5% 0.02039637 0.01621031 0.08938908 0.7044609 0.08201707 w0238 - 2 50% 0.02877164 0.02494265 0.10993121 0.7323968 0.10357189 w0238 - 3 95% 0.04086654 0.03510818 0.12997545 0.7596250 0.12387242 w0238 - -``` r -get_credible_intervals(model=example_model, interval_min=0.05, interval_max=0.95) -``` - - [[1]] - quantile cluster_1 cluster_2 cluster_3 cluster_4 cluster_5 writer - 1 5% 0.06042425 0.02493705 0.1418073 0.5529695 0.1306786 w0009 - 2 50% 0.07366519 0.03478669 0.1647020 0.5782510 0.1489102 w0009 - 3 95% 0.08875836 0.04671823 0.1840218 0.6088443 0.1701284 w0009 - - [[2]] - quantile cluster_1 cluster_2 cluster_3 cluster_4 cluster_5 writer - 1 5% 0.008342953 5.982238e-05 0.2480043 0.4153643 0.2096460 w0030 - 2 50% 0.017026968 1.492831e-03 0.2840930 0.4549356 0.2402698 w0030 - 3 95% 0.029416108 8.076710e-03 0.3161589 0.4931652 0.2830293 w0030 - - [[3]] - quantile cluster_1 cluster_2 cluster_3 cluster_4 cluster_5 writer - 1 5% 0.02039637 0.01621031 0.08938908 0.7044609 0.08201707 w0238 - 2 50% 0.02877164 0.02494265 0.10993121 0.7323968 0.10357189 w0238 - 3 95% 0.04086654 0.03510818 0.12997545 0.7596250 0.12387242 w0238 diff --git a/docs/man/get_posterior_probabilities.html b/docs/man/get_posterior_probabilities.html new file mode 100644 index 00000000..94a30f68 --- /dev/null +++ b/docs/man/get_posterior_probabilities.html @@ -0,0 +1,953 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Get Posterior Probabilities

+
+

Description

+

Get the posterior probabilities for questioned document analyzed with analyze_questioned_documents().

+
+
+

Usage

+
get_posterior_probabilities(analysis, questioned_doc)
+
+
+
+

Arguments

+ + + + + + + + + +
+analysis + +The output of analyze_questioned_documents(). If more than one questioned document was analyzed with this function, then the data frame analysis$posterior_probabilities lists the posterior probabilities for all questioned documents. get_posterior_probabilities() creates a data frame of the posterior probabilities for a single questioned document and sorts the known writers from the most likely to least likely to have written the questioned document. +
+questioned_doc + +The filename of the questioned document +
+
+
+

Value

+

A data frame of posterior probabilities for the questioned document

+
+
+

Examples

+
+
library(handwriter)
+
+get_posterior_probabilities(
+  analysis = example_analysis,
+  questioned_doc = "w0030_s03_pWOZ_r01"
+)
+
+
        known_writer w0030_s03_pWOZ_r01
+2 known_writer_w0030                  1
+1 known_writer_w0009                  0
+3 known_writer_w0238                  0
+
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/get_posterior_probabilities.md b/docs/man/get_posterior_probabilities.md deleted file mode 100644 index 143d1046..00000000 --- a/docs/man/get_posterior_probabilities.md +++ /dev/null @@ -1,62 +0,0 @@ - - -# Get Posterior Probabilities - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -Get the posterior probabilities for questioned document analyzed with -analyze_questioned_documents(). - -## Usage - -
get_posterior_probabilities(analysis, questioned_doc)
-
- -## Arguments - - - - - - - - - - -
-analysis - -The output of analyze_questioned_documents(). If more than -one questioned document was analyzed with this function, then the data -frame analysis$posterior_probabilities lists the posterior probabilities -for all questioned documents. get_posterior_probabilities() -creates a data frame of the posterior probabilities for a single -questioned document and sorts the known writers from the most likely to -least likely to have written the questioned document. -
-questioned_doc - -The filename of the questioned document -
- -## Value - -A data frame of posterior probabilities for the questioned document - -## Examples - -``` r -library(handwriter) - -get_posterior_probabilities( - analysis = example_analysis, - questioned_doc = "w0030_s03_pWOZ_r01" -) -``` - - known_writer w0030_s03_pWOZ_r01 - 2 known_writer_w0030 1 - 1 known_writer_w0009 0 - 3 known_writer_w0238 0 diff --git a/docs/man/graphToPrototype.html b/docs/man/graphToPrototype.html new file mode 100644 index 00000000..e3272f96 --- /dev/null +++ b/docs/man/graphToPrototype.html @@ -0,0 +1,902 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Convert graph to a prototype

+
+

Description

+

A graph prototype consists of the starting and ending points of each path in the graph, as well as and evenly spaced points along each path. The prototype also stores the center point of the graph. All points are represented as xy-coordinates and the center point is at (0,0).

+
+
+

Usage

+
graphToPrototype(graph, numPathCuts = 8)
+
+
+
+

Arguments

+ + + + + + + + + +
+graph + +A graph from a handwriting sample +
+numPathCuts + +Number of segments to cut the path(s) into +
+
+
+

Value

+

List of pathEnds, pathQuarters, and pathCenters given as (x,y) coordinates with the graph centroid at (0,0). The returned list also contains path lengths. pathQuarters gives the (x,y) coordinates of the path at the cut points and despite the name, the path might not be cut into quarters.

+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/graphToPrototype.md b/docs/man/graphToPrototype.md deleted file mode 100644 index 0b602fc0..00000000 --- a/docs/man/graphToPrototype.md +++ /dev/null @@ -1,46 +0,0 @@ - - -# Convert graph to a prototype - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -A graph prototype consists of the starting and ending points of each -path in the graph, as well as and evenly spaced points along each path. -The prototype also stores the center point of the graph. All points are -represented as xy-coordinates and the center point is at (0,0). - -## Usage - -
graphToPrototype(graph, numPathCuts = 8)
-
- -## Arguments - - - - - - - - - - -
-graph - -A graph from a handwriting sample -
-numPathCuts - -Number of segments to cut the path(s) into -
- -## Value - -List of pathEnds, pathQuarters, and pathCenters given as (x,y) -coordinates with the graph centroid at (0,0). The returned list also -contains path lengths. pathQuarters gives the (x,y) coordinates of the -path at the cut points and despite the name, the path might not be cut -into quarters. diff --git a/docs/man/london.html b/docs/man/london.html new file mode 100644 index 00000000..89289ffa --- /dev/null +++ b/docs/man/london.html @@ -0,0 +1,942 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Cursive written word: London

+
+

Description

+

Cursive written word: London

+
+
+

Usage

+
london
+
+
+
+

Format

+

Binary image matrix. 148 rows and 481 columns.

+
+
+

Examples

+
+
library(handwriter)
+
+london_document <- list()
+london_document$image <- london
+plotImage(london_document)
+
+
+
+

+
+
+
+
london_document$thin <- thinImage(london_document$image)
+plotImageThinned(london_document)
+
+
+
+

+
+
+
+
london_processList <- processHandwriting(london_document$thin, dim(london_document$image))
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/london.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png b/docs/man/london.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png deleted file mode 100644 index 95bf811141360b18fdc63c54d49cec882e273206..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 12768 zcmeHNX*`r~)Mk=ULW>YBB-xTZvP_gIB_T`ph{0I0j%_TZlC^bYo6%p9Y+1(G#!{H< zWEty>jIlHrOZH{nr<1-im!`Z4Lc(SCbu1m+=irHxfWl3-Z(v+>U>t7y!qZ) zT;s@P?%IzduSVz=wPL4TvS*^D|0}-zAIqb2s~zi*ci)e(Q_JLwDqfYsaLq$&<0-U| z38MEbasTsDDGMY~6eJ~(Cr#-ZEy9o2)v5Z_B04w`9nz9+Qavz3JJmoW zEMr&bP-@<72y^7{CdD~8FG55+ZC z*q-=8F4E?z)VWVF+jWDH`zAz|%~|$&&ke?@DSpfq7jC}VsFa;_OQZ|;Xd|@b>M*Qs z@R5Fe(FMd2(w@@g1PL$XkEh&dcL{=T(pO%1bGHZig`DIC5bhA9WexlS;Rj7ms<4qOpA@mbGV zBCWPzhRFHqzK54WjB# ztWys7e7oSgxwP(QnwrQq`cmcCet{TK857LB*0)eojM#f_n-ZVU_|c(ndV{Z;n9Z!;{%ay+3PabUp`tD6n-^!f&X;+ zsh47nM)zaxcdF_hRKz2Nz3(rUb#@0Zix{Gnqbs8);g=h>q4(d86t~ywqLsP(+WXpJ 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+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Make Clustering Template

+
+

Description

+

make_clustering_template() applies a K-means clustering algorithm to the input handwriting samples pre-processed with process_batch_dir() and saved in the input folder main_dir > data > template_graphs. The K-means algorithm sorts the graphs in the input handwriting samples into groups, or clusters, of similar graphs.

+
+
+

Usage

+
make_clustering_template(
+  main_dir,
+  template_docs,
+  writer_indices,
+  centers_seed,
+  K = 40,
+  num_dist_cores = 1,
+  max_iters = 25
+)
+
+
+
+

Arguments

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+main_dir + +Main directory that will store template files +
+template_docs + +A directory containing template training images +
+writer_indices + +A vector of the starting and ending location of the writer ID in the file name. +
+centers_seed + +Integer seed for the random number generator when selecting starting cluster centers. +
+K + +Integer number of clusters +
+num_dist_cores + +Integer number of cores to use for the distance calculations in the K-means algorithm. Each iteration of the K-means algorithm calculates the distance between each input graph and each cluster center. +
+max_iters + +Maximum number of iterations to allow the K-means algorithm to run +
+
+
+

Value

+

List containing the cluster template

+
+
+

Examples

+
+
library(handwriter)
+
+main_dir <- "path/to/folder"
+template_docs <- "path/to/template_training_docs"
+template_list <- make_clustering_template(
+  main_dir = main_dir,
+  template_docs = template_docs,
+  writer_indices = c(2, 5),
+  K = 10,
+  num_dist_cores = 2,
+  max_iters = 25,
+  centers_seed = 100,
+)
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/make_clustering_template.md b/docs/man/make_clustering_template.md deleted file mode 100644 index c659eb1b..00000000 --- a/docs/man/make_clustering_template.md +++ /dev/null @@ -1,115 +0,0 @@ - - -# Make Clustering Template - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -make_clustering_template() applies a K-means clustering -algorithm to the input handwriting samples pre-processed with -process_batch_dir() and saved in the input folder -main_dir \> data \> -template_graphs. The K-means algorithm sorts the graphs in the -input handwriting samples into groups, or clusters, of similar -graphs. - -## Usage - -
make_clustering_template(
-  main_dir,
-  template_docs,
-  writer_indices,
-  centers_seed,
-  K = 40,
-  num_dist_cores = 1,
-  max_iters = 25
-)
-
- -## Arguments - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
-main_dir - -Main directory that will store template files -
-template_docs - -A directory containing template training images -
-writer_indices - -A vector of the starting and ending location of the writer ID in the -file name. -
-centers_seed - -Integer seed for the random number generator when selecting starting -cluster centers. -
-K - -Integer number of clusters -
-num_dist_cores - -Integer number of cores to use for the distance calculations in the -K-means algorithm. Each iteration of the K-means algorithm calculates -the distance between each input graph and each cluster center. -
-max_iters - -Maximum number of iterations to allow the K-means algorithm to run -
- -## Value - -List containing the cluster template - -## Examples - -``` r -library(handwriter) - -main_dir <- "path/to/folder" -template_docs <- "path/to/template_training_docs" -template_list <- make_clustering_template( - main_dir = main_dir, - template_docs = template_docs, - writer_indices = c(2, 5), - K = 10, - num_dist_cores = 2, - max_iters = 25, - centers_seed = 100, -) -``` diff --git a/docs/man/message.html b/docs/man/message.html new file mode 100644 index 00000000..bb705a4a --- /dev/null +++ b/docs/man/message.html @@ -0,0 +1,932 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Full page image of the handwritten London letter.

+
+

Description

+

Full page image of the handwritten London letter.

+
+
+

Usage

+
message
+
+
+
+

Format

+

Binary image matrix. 1262 rows and 1162 columns.

+
+
+

Examples

+
+
library(handwriter)
+
+message_document <- list()
+message_document$image <- message
+plotImage(message_document)
+
+message_document <- list()
+message_document$image <- message
+plotImage(message_document)
+message_document$thin <- thinImage(message_document$image)
+plotImageThinned(message_document)
+message_processList <- processHandwriting(message_document$thin, dim(message_document$image))
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/nature1.html b/docs/man/nature1.html new file mode 100644 index 00000000..128a41a9 --- /dev/null +++ b/docs/man/nature1.html @@ -0,0 +1,932 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Full page image of the 4th sample (nature) of handwriting from the first writer.

+
+

Description

+

Full page image of the 4th sample (nature) of handwriting from the first writer.

+
+
+

Usage

+
nature1
+
+
+
+

Format

+

Binary image matrix. 811 rows and 1590 columns.

+
+
+

Examples

+
+
library(handwriter)
+
+nature1_document <- list()
+nature1_document$image <- nature1
+plotImage(nature1_document)
+
+nature1_document <- list()
+nature1_document$image <- nature1
+plotImage(nature1_document)
+nature1_document$thin <- thinImage(nature1_document$image)
+plotImageThinned(nature1_document)
+nature1_processList <- processHandwriting(nature1_document$thin, dim(nature1_document$image))
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/plotImage.html b/docs/man/plotImage.html new file mode 100644 index 00000000..cb18fd34 --- /dev/null +++ b/docs/man/plotImage.html @@ -0,0 +1,941 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Plot Image

+
+

Description

+

This function plots a basic black and white image.

+
+
+

Usage

+
plotImage(doc)
+
+
+
+

Arguments

+ + + + + +
+doc + +A document processed with processDocument() or a binary matrix (all entries are 0 or 1) +
+
+
+

Value

+

ggplot plot

+
+
+

Examples

+
+
library(handwriter)
+
+csafe_document <- list()
+csafe_document$image <- csafe
+plotImage(csafe_document)
+
+document <- processDocument('path/to/image.png')
+plotImage(document)
+
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/docs/man/plotImageThinned.html b/docs/man/plotImageThinned.html new file mode 100644 index 00000000..a2c1af6c --- /dev/null +++ b/docs/man/plotImageThinned.html @@ -0,0 +1,946 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ + + + +
+

Plot Thinned Image

+
+

Description

+

This function returns a plot with the full image plotted in light gray and the thinned skeleton printed in black on top.

+
+
+

Usage

+
plotImageThinned(doc)
+
+
+
+

Arguments

+ + + + + +
+doc + +A document processed with processHandwriting() +
+
+
+

Value

+

gpplot plot of thinned image

+
+
+

Examples

+
+
library(handwriter)
+
+csafe_document <- list()
+csafe_document$image <- csafe
+csafe_document$thin <- thinImage(csafe_document$image)
+plotImageThinned(csafe_document)
+
+
+
+

+
+
+
+
+ + +
+
+ +
+ +
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with the full image plotted in light gray -and the thinned skeleton printed in black on top. - -## Usage - -
plotImageThinned(doc)
-
- -## Arguments - - - - - - -
-doc - -A document processed with processHandwriting() -
- -## Value - -gpplot plot of thinned image - -## Examples - -``` r -library(handwriter) - -csafe_document <- list() -csafe_document$image <- csafe -csafe_document$thin <- thinImage(csafe_document$image) -plotImageThinned(csafe_document) -``` - -![](plotImageThinned.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) diff --git a/docs/man/plotImageThinned_files/figure-html/unnamed-chunk-1-1.png b/docs/man/plotImageThinned_files/figure-html/unnamed-chunk-1-1.png new file mode 100644 index 0000000000000000000000000000000000000000..dada27ee0b543fd30634ab1a5458ac1f6934746c GIT binary patch literal 32326 zcmeHvcTiK?zi&YB0G5LV6bqoJC`uP8(mX2YLBK+h7Ens0D@AGuId(vb2nYhvqk<$9 zCDKbc7CJ;xh}58zNRdblfsou4Fo3_a@BQQ5nK$$1#TjO{N!DK9^(~)o-TTgIBmFf( zTZCXR*qW0kj-7?U_;q2h6%_(2!6y?=A6sECzO~LrkDhits(;ke&C~1Lrs zUe5Ms_5Xmu)b8FjwYjv-bffmeBK-bcjn_VA(4|?VWx-k94hyE<9ir-?f|fz?N*;zK>t=RsC<@YWVzve7^?yUUq+E zoJ`yvo~=Ev32oo0l9gSgsR9}cF_e8;pXYYxjnA2CwL8B$!k8lOa&1ESj?7jIk}ggQ 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z`h42r)MKcw4nV#sTt);Gv!*fNJ+VvJwkU%6x4Zl@VqSsd^J)*uD=TaI(cZORY+;BC zuvm*7Ha&^VUAAj2GBqtfrX4f0jHA5h!6$hl1W3BaaG5T9n8)3;G84Hi-ecaE8Ufi%^ z7q1SA$xvF~-bL8u#d$=q+l=i?OpA6ypg=bqlxY9^2aH6gt>Ub5A+%+LJ)jlTY?Tl3 zoyTs_7{_@TEIoX*L|_@PRH~_GE9d;n#8emuyiQiFtOZAvm+_MZW|qp#%N(IjV8*We z%M>_3iN*kk20j@tyX;mRJFx-)-i7VB2NBU+mIsih^8Fc@qz z-=wFz@EwII5UHT!LSexFe~QC1LYZMR!8G<)O_lnoi^!jNms z$3;1I^uYxME+{Pcc`hh$LE&e5$pr;2C~!exF*oK$3fxHHXSI!+K5)~ApY>#JO@W&} zEYxqgpuhzME+{P3gt_ShH+|ry58U)&vAfAlAGqnm(zFG)(D;A1(8!nNQ5^bL)M_cv Q=7pU+ZgedB54*qq3!$3dxc~qF literal 0 HcmV?d00001 diff --git a/docs/man/plotLetter.html b/docs/man/plotLetter.html new file mode 100644 index 00000000..e4484c1c --- /dev/null +++ b/docs/man/plotLetter.html @@ -0,0 +1,1002 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ +
+ + +
+ + + +
+ + + + +
+

Plot Letter

+
+

Description

+

This function returns a plot of a single graph extracted from a document. It uses the letterList parameter from the processHandwriting() or processDocument() function and accepts a single value as whichLetter. Dims requires the dimensions of the entire document, since this isn’t contained in processHandwriting() or processDocument().

+
+
+

Usage

+
plotLetter(
+  doc,
+  whichLetter,
+  showPaths = TRUE,
+  showCentroid = TRUE,
+  showSlope = TRUE,
+  showNodes = TRUE
+)
+
+
+
+

Arguments

+ + + + + + + + + + + + + + + + + + + + + + + + + +
+doc + +A document processed with processHandwriting() or processDocument() +
+whichLetter + +Single value in 1:length(letterList) denoting which letter to plot. +
+showPaths + +Whether the calculated paths on the letter should be shown with numbers. +
+showCentroid + +Whether the centroid should be shown +
+showSlope + +Whether the slope should be shown +
+showNodes + +Whether the nodes should be shown +
+
+
+

Value

+

Plot of single letter.

+
+
+

Examples

+
+
library(handwriter)
+
+twoSent_document = list()
+twoSent_document$image = twoSent
+twoSent_document$thin = thinImage(twoSent_document$image)
+twoSent_document$process = processHandwriting(twoSent_document$thin, dim(twoSent_document$image))
+plotLetter(twoSent_document, 1)
+
+
+
+

+
+
+
+
plotLetter(twoSent_document, 4, showPaths = FALSE)
+
+
+
+

+
+
+
+
+ + +
+
+ +
+ +
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z5vdfA7dT!J|H%pQn}|l>#XtV=`^6VPkE+WY%wXru7xi!x(zwso5;od=@y|~-e!uVl zm-hH}Ci?eo0MtmxIUvf=~E!MNABa9_s_hfVQ3$@jH(xmdw zF{Bz-EaGvQ?v*!v#|l%ALks^YbNo}pU!USv$`s?(TxVD5_%wEnJ^wrq&@Kt+|4-MR zEhZa3Gn_m!p5fK^=+7@4^Wo=W1^2U&-t}dX$&TfKbIywCRd2s$BHhneko%cL_dXar z#-4kjX_?dc(v!J`3oM&kQ_f79oX=v1XJHN~T7or}zxHazKede=>yWQXDjv_5J5StX z#OCmWlGM4$U`SqlOry=%Dpp^?3r;fq0|W3wPI1Wlzv;x_JHm!fThFg6Nb4WTi2s`jsFwdxprocessHandwriting() or processDocument() -function and accepts a single value as whichLetter. Dims -requires the dimensions of the entire document, since this isn’t -contained in processHandwriting() or -processDocument(). - -## Usage - -
plotLetter(
-  doc,
-  whichLetter,
-  showPaths = TRUE,
-  showCentroid = TRUE,
-  showSlope = TRUE,
-  showNodes = TRUE
-)
-
- -## Arguments - - - - - - - - - - - - - - - - - - - - - - - - - - -
-doc - -A document processed with processHandwriting() or -processDocument() -
-whichLetter - -Single value in 1:length(letterList) denoting which letter to plot. -
-showPaths - -Whether the calculated paths on the letter should be shown with numbers. -
-showCentroid - -Whether the centroid should be shown -
-showSlope - -Whether the slope should be shown -
-showNodes - -Whether the nodes should be shown -
- -## Value - -Plot of single letter. - -## Examples - -``` r -library(handwriter) - -twoSent_document = list() -twoSent_document$image = twoSent -twoSent_document$thin = thinImage(twoSent_document$image) -twoSent_document$process = processHandwriting(twoSent_document$thin, dim(twoSent_document$image)) -plotLetter(twoSent_document, 1) -``` - -![](plotLetter.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) - -``` r -plotLetter(twoSent_document, 4, showPaths = FALSE) -``` - -![](plotLetter.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-2.png) diff --git a/docs/man/plotLetter_files/figure-html/unnamed-chunk-1-1.png b/docs/man/plotLetter_files/figure-html/unnamed-chunk-1-1.png new file mode 100644 index 0000000000000000000000000000000000000000..dc9ae5085bcd9c00ffc03b7ed7aa254c13c2d48b GIT binary patch literal 65695 zcmeEu^xeb0T*{SWRB@IjdQ&faUUwVr1^Yi)y6m1QpwT_wW7!MPy!NLmdChd>es z=S;)-v*0(|roTsUaPUbj9z0OBd?5S4*2>mi{nfJBskk_9W@%u%|xTm 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zpx~!g!I>KteuE}k256+!7Vl+oaA?CNfJuA{_s;p>l1>6}RHghSBypC9h7o}_*aV5O ze1*93zh)*^Ic_`uoG|@SaDt4GSk?o>6Rrl0G>N5m@pJvn2&l;e%jIaU1O5h(MxX*j n{;%kMm-}DQ&7rh9gnqJFi&w^o_UoS*@IT!h23jeaHmCjvBdtI? literal 0 HcmV?d00001 diff --git a/docs/man/plotLine.html b/docs/man/plotLine.html new file mode 100644 index 00000000..c2613699 --- /dev/null +++ b/docs/man/plotLine.html @@ -0,0 +1,965 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + +
    + + +
    + + + +
    + + + + +
    +

    Plot Line

    +
    +

    Description

    +

    This function returns a plot of a single line extracted from a document. It uses the letterList parameter from the processHandwriting function and accepts a single value as whichLetter. Dims requires the dimensions of the entire document, since this isn’t contained in processHandwriting.

    +
    +
    +

    Usage

    +
    plotLine(letterList, whichLine, dims)
    +
    +
    +
    +

    Arguments

    + + + + + + + + + + + + + +
    +letterList + +Letter list from processHandwriting function +
    +whichLine + +Single value denoting which line to plot - checked if too big inside function. +
    +dims + +Dimensions of the original document +
    +
    +
    +

    Value

    +

    ggplot plot of single line

    +
    +
    +

    Examples

    +
    +
    library(handwriter)
    +
    +twoSent_document = list()
    +twoSent_document$image = twoSent
    +twoSent_document$thin = thinImage(twoSent_document$image)
    +twoSent_processList = processHandwriting(twoSent_document$thin, dim(twoSent_document$image))
    +
    +dims = dim(twoSent_document$image)
    +plotLine(twoSent_processList$letterList, 1, dims)
    +
    +
    +
    +

    +
    +
    +
    +
    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/man/plotLine.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png b/docs/man/plotLine.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png deleted file mode 100644 index 2d7f9f300e169c11167bec7d409575da8c1e9bc9..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 10515 zcmeHNcTiK?w@yMpiXdJ^x2N)F=2&Ab`@I5X$$z4khLuf5jyefuQ;Id5$) zDl8)m0)a#=&X`>Ufgrgc5O`Ej0BDIyrXB%-pkm&prspxH=BEC>{y~=l+^>0>d-{0> zd0)F|ei8&SxOdOa1ubW{8~&uW{NRDEo4xt@55#zSe^vNi{FE@n;CYr`Cm(v~TXEuk z$J9ucx3cc|>ObCU@ZBfG-@X`qIJ)liR%M@05$mqTvx@W2pf^<)yO+(MewGws*6NlM z9@b#$-;#;`8)A-&suMxIYp2Q zp)N5 zepS~fi{dKoEwl1gzy1E61Nvy&kK2niv^`#sm}w1^x6weiVV>8W6Njenj{n$cUjT1$ zD9lbjxrWrJ-rcHXoaCChJ)~Vbbai1l%pvP#M^|(DG6=2U1s-TJG`Tv+@2Q*%P`PS z8F}cZi+!V0)F!nh9;n*Zhu6+ze9}Idzpgmj{jzBWZKqhbJvI_u6xuE16`^+@UR&D!U=Mcfr`|}g;>8^OyLERN;U`*oD38aZ z6{L4(bM(arNrNOz=c55XSECp|hr5K+_Bn+9;K`5!C>bA(koKY8tRT{Q6OukqhNSB| zZs%=_<%?qu+gIx`k9@Efj(Own)MCyyw)TMMY1sL?mp^}YMbCa2qVOIRQyW1LLoH>G-#y@{0O!H2^ zK+ZYoIH+-4)g#fkskzC+(uN_Clpy4;6&0pmwCkRv3qhc*%-^FZrWhw#7(C@yT;4xs zVtYDGKqWeVd`6eg+HX8T(ZWP}f8upQR03-uKP=YLcnBZg8a(HFod0SxGWrO7w@FjL zO=;@gh6_`3y+M<&--~@s_RgxP%=mt%xnpAdsxV$heb4r9#9US88wNq{Q@&VbI{F)^ z469?%xGpIEyJb}ohBFcbdVV$JK_FZydG#PXtC;c1y(8(5O;Kqrf#wJ?3X9Gj z(#%o0s(xy7*rFPs7zO@U6eB}++I3wa&p&@k?Z2lEL35ovZfyFG#|jDNa))e+_HCwM zh!zYNR(6Vq;>!EpP}_tkPY8q|>+^P2G^OD8J{{wSc4q~+{;P7!Y!ILkI?WF78<9z5 zu1ilW(A!R2)&@gv0hY}P!how$9>jDsdJSWNH=)KY*q^~6s&JqTjW@5dZFU~LA#IIA z?24}?PV)LZ4jxeo5CMbd_Y9+V0v-))+|u|Xpu9}>rFF(XBu+Tp2Lgs`PVM^L;7;8BuX@j-3n2<#I3a*4avRNG-w ze5s^3aPv3I)XZcT8{rIp@7gRa0!gw^`J`J7LgyD`3jZMnZ=JO3>$monAW#MEj ze5z#4Sm2mrid}wo54|n0f$BtTpkm`nrd@%hx2;Ti4b9Pf9}m@}_S~;{n((v{+VA+f z)KF(Uwm0NGGpH|;F7(1Iw;q^7#168ctUs}Xb!$x`>Bs#mv@2e=->;kWccEA{+ZFW$ z#UD$GBj_&HjYbqu+f1-1)mUFY_M={W_`T07hn=>Q2AjF%>_hQPVc(^ZH`D4LGePku zfWU=_b=7<-Ei{Ba(;Jt0g|@^IPeHqCQV*?(3`^H*Hu+{i{SIy{Y$#8b6=H-UM+|VX zyWWk*@h=(*L3yfcMM{`BdfIflm&dZvxW8ioMfQ zek>;11MGw;k#6+*&~KP?A($zbtP-FPq{rJ7PKYl1^vEa(9r=({|IEaEtoQ26cmQirQt!8QdWO(gDwo5GPR%iO41bu7O{G_q1&V9}* zZaMvi*QMWu-0g38^?Ys!R1-$-|B}pp5jD~eZ`}nG7g>acyk!*2(yxR{ri}sBsRfB$ zch!CnD|fB{iRJrRkST+7@NNVAZzB05Y5Kimqp>6m0Yu6U zZzF5&gW1xqU-B>%AfcTp$+r6e42;)>uI^mD@lwBrUn*Vbh`5xACkOilgtP zXX9QT07GgaH&CSoKEUhH8ZcZH1-vG-36(o`i6a!M#?mY|(R{1_e-IzyiTKpi)SD7@ znFs*<9GNAuKflJDkz8C|J%=xZ#p?n)ryJS_;PWrwUsQ(SVig19f78I|Ie;|Ixm5n% z4QK;EZ`3o+n~a-%VASO6OX_uS1;yF?CnMh1gqgkj$MQ5!v2;)qn*gxU%e_C}2@5cc z&kKmEO?38Xf-p`U?L6|!XZ$tD416-0OMX@AY7D?hS7FUB4%AeJAzXZ$_rhJk^JCkH zKYmZ44-#jue|%_WVFpe9M&-B;99blLx|nl^m>U*u1mbM=*BB4N@T_py3Yk;)JqSFX z(r6p*+>_nR(EFLs&O~fyps7Tc~$ECh2GX0jZrI z-&2rlJd;){3W2-`{$=c^sx6wQ@BB>3Ifk#E6szwY zdJ5#SZ-!Wk&`H>cXNJ(BM5`Gjvf87=TTa5*B!#_Jg9E*3>W+7g_Ym9&Qi#gvS`k6R zBB$GKUC9(=Wg@&H^5()+HTx_C$`RS_?}lHW!cROh7IxOl&Gd{^Np;t7_$a1eqQZ;p zS1$TlAp?7)sKxbm^Mq6fv3-o*jdw+Hi&}#BB^apW}A96cLBm74PrXG8;)Rcy_t?2;D@<)T`g$W)hKRJIiok%Hr#SI;0LbEH(d4jRcwK8H!TEMc%CtxeFX)ZHj zt*8?B8I@2hGQ8g?s&KgHi#+E=!BS?eIfNlFatBE%kgF4&0_0r44Fqk?x5nSIA6rfC z#7+!i7U8^AKR=W)x0Fku(`erblt2u7^l9I&|rNmo`Qk4wOd;<;r^I1gIW;AO)a( zB7X|Ghf>cO36`WeW-d!X3z*q(*F)OumOlr&{#uFg&ScJr>{xX#lb7!j`-bHNW)5dn zp9YQ85Kszt%9;MorDOM?X?~Y22V||v|6zU3xW%+2Jvuj~Y?V^C)IdPiWBm?}*l{8s z(?dp3OJYe5fnVNGQK=+K0lJ|_cjvtvEH4y~jLVkAKEgm4c43{z6_mNs!+hSWI}_(%tW&I=2|k0C^n^$BAX+QSbn z7faiom~}M89gX}kRFu46sC+;4bZWoh^0HE5`FG8Q;I%J+yeQ|c&wd{%6WbMgaMr9R zS#O7465f@UI5ph*raKYQdgcA)Gg|D&rFjF9R`kia1^!j}ZZU2^v?43O2bn){dLdDf z^;SH$G)O>aPgY<`t4tHBHD&(FIAf+|aoM%2of4VMG{B_0(nG`W<^8$SdH`r-t@M7E zWV=wqNi1jDaC$xE1w|}+_92!#VNqp1U?fHA8^o-Sjt}`xVmLnJalLCuNu3l0y0J^5KgqJ(r?3 zs6c$UfBQ_V1LK>ZT>Z9WJoUAMQ>$2!vo3GsaX9IlYAOD6kfsI}FRAn6EQBYX75krK8FAq(*_obxOMR;XjZa}OLKyOVnDgV|Ff(6G*Kn@I$1xwWYu;Kjem}(CI`<+o@=I$a+gW((oxI5 z;Ohx7hgw=Q8xijfyMu7$qt6bN;8VYwup(n^h69;Oz`EEQN`}pe?z?mAyqaLiGo9PN zXmU_>G<8(}hMid4n#ZfxGu@Vp#d`*Ru2Jx~IlvDQ_%`uDo!em_u5Ab$fI5k%0NNGt zB}^out~lNz%k;C$1j(F5h5Qr%M}*x`L#aaSrvv$G85R8MNmNx;5hVmhR?sh zv1|?B3f)%PY?aJU%-e#CEvWo;q}!s2EsETb5L@zKOCJ0`ln3kEWWT(Zv5rBzZ~Pz0 N;*_;n=}EU6{{=Vfkx2jm diff --git a/docs/man/plotLine.md b/docs/man/plotLine.md deleted file mode 100644 index 89b42e69..00000000 --- a/docs/man/plotLine.md +++ /dev/null @@ -1,68 +0,0 @@ - - -# Plot Line - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -This function returns a plot of a single line extracted from a document. -It uses the letterList parameter from the processHandwriting function -and accepts a single value as whichLetter. Dims requires the dimensions -of the entire document, since this isn’t contained in -processHandwriting. - -## Usage - -
    plotLine(letterList, whichLine, dims)
    -
    - -## Arguments - - - - - - - - - - - - - - -
    -letterList - -Letter list from processHandwriting function -
    -whichLine - -Single value denoting which line to plot - checked if too big inside -function. -
    -dims - -Dimensions of the original document -
    - -## Value - -ggplot plot of single line - -## Examples - -``` r -library(handwriter) - -twoSent_document = list() -twoSent_document$image = twoSent -twoSent_document$thin = thinImage(twoSent_document$image) -twoSent_processList = processHandwriting(twoSent_document$thin, dim(twoSent_document$image)) - -dims = dim(twoSent_document$image) -plotLine(twoSent_processList$letterList, 1, dims) -``` - -![](plotLine.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) diff --git a/docs/man/plotLine_files/figure-html/unnamed-chunk-1-1.png b/docs/man/plotLine_files/figure-html/unnamed-chunk-1-1.png new file mode 100644 index 0000000000000000000000000000000000000000..c76e931b5d4a8329b85aecd13a890ceba5c78ba4 GIT binary patch literal 32289 zcmeHwXHb(}6lM|wQbZ9&0TmDgl%gOa<%1AK!A4P}S4Dc2h|~bF7mA7^NC}FHN(o9Y z2~kv#5=0=89z+NbdPtBK_6S z=p6=u)FLBIY+SaRY=$Ki<;d+KTy1>$^1*th%EMfbGxgV6`k0P6o^A3m9=V6^eHm;| za+Ox@o_+4R2e$bT|NB?u81lT;dzqbX=|guFp5+=ngI?YJ>+7`M({Ee3sYS{;B{7BW 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    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    Plot Nodes

    +
    +

    Description

    +

    This function returns a plot with the full image plotted in light gray and the skeleton printed in black, with red triangles over the vertices. Also called from plotPath, which is a more useful function, in general.

    +
    +
    +

    Usage

    +
    plotNodes(doc, plot_break_pts = FALSE, nodeSize = 3, nodeColor = "red")
    +
    +
    +
    +

    Arguments

    + + + + + + + + + + + + + + + + + +
    +doc + +A document processed with processHandwriting() +
    +plot_break_pts + +Logical value as to whether to plot nodes or break points. plot_break_pts=FALSE plots nodes and plot_break_pts=TRUE plots break point. +
    +nodeSize + +Size of triangles printed. 3 by default. Move down to 2 or 1 for small text images. +
    +nodeColor + +Which color the nodes should be +
    +
    +
    +

    Value

    +

    Plot of full and thinned image with vertices overlaid.

    +
    +
    +

    Examples

    +
    +
    library(handwriter)
    +
    +csafe_document <- list()
    +csafe_document$image <- csafe
    +csafe_document$thin <- thinImage(csafe_document$image)
    +csafe_document$process <- processHandwriting(csafe_document$thin, dim(csafe_document$image))
    +plotNodes(csafe_document)
    +
    +
    +
    +

    +
    +
    +
    +
    plotNodes(csafe_document, nodeSize=6, nodeColor="black")
    +
    +
    +
    +

    +
    +
    +
    +
    + + +
    +
    + +
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zmQl4^z{=yUxeTgKV^u;t<;*QP@XiW;I$8#lmXv*DRqEVGjRgMxKPv?T$iC_)y6=E5 zFeg4vhE=T$88_!)q&(Gu2QJnEj|15%^FWPM|M80?0`~Yb{`jB$-wKu3*gK`NxHiYk z!`Xq!{Bx&)uO3jslGJp7;-}Tc_vWzw=@`h= z2Fep+^z2&xcS7O9XMvn=9rGqP0kM~A?2+{Wd4{v%yo#d2*xmSBZ0wX%KuLv&PCjet zEI4fr18%R#03F4$$VzsrjQ^XEJR5q(d_zVNn4pO}OW$Q5#)XS>IoICUKI8%wfVDQg?fEqL{AjM6!Zpaj)v9OOS8x%>@IKohP4`*XJ)lLQooo&kzfNeFW&P`SsNLqTLK%OL$TkZ21{5aN4VoVez* zEzVq^svwt!jJ*I5?iBWau0Fw^8bzO2-6t$j z`R|e!mhl|;?=~AiFaEo>hh-f8yPt?plotNodes(doc, plot_break_pts = FALSE, nodeSize = 3, nodeColor = "red") - - -## Arguments - - - - - - - - - - - - - - - - - - -
    -doc - -A document processed with processHandwriting() -
    -plot_break_pts - -Logical value as to whether to plot nodes or break points. -plot_break_pts=FALSE plots nodes and plot_break_pts=TRUE plots break -point. -
    -nodeSize - -Size of triangles printed. 3 by default. Move down to 2 or 1 for small -text images. -
    -nodeColor - -Which color the nodes should be -
    - -## Value - -Plot of full and thinned image with vertices overlaid. - -## Examples - -``` r -library(handwriter) - -csafe_document <- list() -csafe_document$image <- csafe -csafe_document$thin <- thinImage(csafe_document$image) -csafe_document$process <- processHandwriting(csafe_document$thin, dim(csafe_document$image)) -plotNodes(csafe_document) -``` - -![](plotNodes.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) - -``` r -plotNodes(csafe_document, nodeSize=6, nodeColor="black") -``` - -![](plotNodes.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-2.png) diff --git a/docs/man/plotNodes_files/figure-html/unnamed-chunk-1-1.png b/docs/man/plotNodes_files/figure-html/unnamed-chunk-1-1.png new file mode 100644 index 0000000000000000000000000000000000000000..8217e259ed4b65077a7ec533189df042cc8525d7 GIT binary patch literal 45026 zcmeGFc|4Tw_XmzMQCg*vQjC&>LfLmM$T}fQmLallW#49oSFcu~vX#9sLQz@9HYg(N 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+ + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    Plot Template Cluster Centers

    +
    +

    Description

    +

    Plot the cluster centers of a cluster template created with make_clustering_template. This function uses a K-Means type algorithm to sort graphs from training documents into clusters. On each iteration of the algorithm, it calculates the mean graph of each cluster and finds the graph in each cluster that is closest to the mean graph. The graphs closest to the mean graphs are used as the cluster centers for the next iteration. Handwriter stores the cluster centers of a cluster template as graph prototypes. A graph prototype consists of the starting and ending points of each path in the graph, as well as and evenly spaced points along each path. The prototype also stores the center point of the graph. All points are represented as xy-coordinates and the center point is at (0,0).

    +
    +
    +

    Usage

    +
    plot_cluster_centers(template, plot_graphs = FALSE, size = 100)
    +
    +
    +
    +

    Arguments

    + + + + + + + + + + + + + +
    +template + +A cluster template created with make_clustering_template +
    +plot_graphs + +TRUE plots all graphs in each cluster in addition to the cluster centers. FALSE only plots the cluster centers. +
    +size + +The size of the output plot +
    +
    +
    +

    Value

    +

    A plot

    +
    +
    +

    Examples

    +
    +
    library(handwriter)
    +
    +# plot cluster centers from example template
    +plot_cluster_centers(example_cluster_template)
    +
    +
    +
    +

    +
    +
    +
    +
    plot_cluster_centers(example_cluster_template, plot_graphs = TRUE)
    +
    +
    +
    +

    +
    +
    +
    +
    + + +
    +
    + +
    + +
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a/docs/man/plot_cluster_centers.md +++ /dev/null @@ -1,76 +0,0 @@ - - -# Plot Template Cluster Centers - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -Plot the cluster centers of a cluster template created with -make_clustering_template. This function uses a K-Means type -algorithm to sort graphs from training documents into clusters. On each -iteration of the algorithm, it calculates the mean graph of each cluster -and finds the graph in each cluster that is closest to the mean graph. -The graphs closest to the mean graphs are used as the cluster centers -for the next iteration. Handwriter stores the cluster centers of a -cluster template as graph prototypes. A graph prototype consists of the -starting and ending points of each path in the graph, as well as and -evenly spaced points along each path. The prototype also stores the -center point of the graph. All points are represented as xy-coordinates -and the center point is at (0,0). - -## Usage - -
    plot_cluster_centers(template, plot_graphs = FALSE, size = 100)
    -
    - -## Arguments - - - - - - - - - - - - - - -
    -template - -A cluster template created with make_clustering_template -
    -plot_graphs - -TRUE plots all graphs in each cluster in addition to the cluster -centers. FALSE only plots the cluster centers. -
    -size - -The size of the output plot -
    - -## Value - -A plot - -## Examples - -``` r -library(handwriter) - -# plot cluster centers from example template -plot_cluster_centers(example_cluster_template) -``` - -![](plot_cluster_centers.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) - -``` r -plot_cluster_centers(example_cluster_template, plot_graphs = TRUE) -``` - -![](plot_cluster_centers.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-2.png) diff --git a/docs/man/plot_cluster_centers_files/figure-html/unnamed-chunk-1-1.png b/docs/man/plot_cluster_centers_files/figure-html/unnamed-chunk-1-1.png new file mode 100644 index 0000000000000000000000000000000000000000..ad0188f30c26fd42a047a33e6565f5afe82b63f4 GIT binary patch literal 37702 zcmeHwc{G%5{5Mjhq8^n*RGx@v2-#;yrL09LVnhs)$ri>kc|0xlr0k3mvL#WnjA^k% z7}?h$W1YbmjAfXa_Z~e|PtSS(c+c-W=Y7u^=Q!s+bKi5_*ZsY|-|y%1y{_y2OvnX8 zogF;;dDz(4cAP(V+L(=PvnCtcruW=ifKTQfTD#fUIC-74wJ$hp>uAGW;O-{3uG!h^ 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zf`W~Q2<aQ9N!n) z-zES5CXLIsF$r0Dk9^3LtN*ZhR7Ue>gFRb5_6sHzslB?|yuZ51Wwk z1pw{WU%CI^DhK@Xhh}mA>wP{S<>#aPKdY4|+x}gpqOv~a#J5MztO)RD4gIX4pN;MR zC%?J0%pWNDw~C5NYvnR^Onv%ygxa2UN{1ezY3-2J82Uf`+Ky2byBptrbV(lzp`X9? zsf+x)8=rUMv!;ANn=PO1#z!=M<@0X553N^ + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + +
    + + +
    + + + +
    + + + + +
    +

    Plot Cluster Fill Counts

    +
    +

    Description

    +

    Plot the cluster fill counts for each document in formatted_data.

    +
    +
    +

    Usage

    +
    plot_cluster_fill_counts(formatted_data, facet = TRUE)
    +
    +
    +
    +

    Arguments

    + + + + + + + + + +
    +formatted_data + +Data created by format_template_data(), fit_model(), or analyze_questioned_documents() +
    +facet + +TRUE uses facet_wrap to create a subplot for each writer. FALSE plots the data on a single plot. +
    +
    +
    +

    Value

    +

    ggplot plot of cluster fill counts

    +
    +
    +

    Examples

    +
    +
    library(handwriter)
    +
    +# Plot cluster fill counts for template training documents
    +template_data <- format_template_data(example_cluster_template)
    +plot_cluster_fill_counts(formatted_data = template_data, facet = TRUE)
    +
    +
    +
    +

    +
    +
    +
    +
    # Plot cluster fill counts for model training documents
    +plot_cluster_fill_counts(formatted_data = example_model, facet = TRUE)
    +
    +
    +
    +

    +
    +
    +
    +
    # Plot cluster fill counts for questioned documents
    +plot_cluster_fill_counts(formatted_data = example_analysis, facet = FALSE)
    +
    +
    +
    +

    +
    +
    +
    +
    + + +
    +
    + +
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zzDFE7f6=uNk9?Uz>q+s-h-kh?Q3{t-)kgiAqu~`!-_iB-lgv2I={U|u3*BV@4P{t6 r71rPHCyG1Zd)pKo|ND5k5dp`VHXVC~iJN#d9+RfJo?6yEi!1*JzaDtj diff --git a/docs/man/plot_cluster_fill_counts.md b/docs/man/plot_cluster_fill_counts.md deleted file mode 100644 index 3c828e89..00000000 --- a/docs/man/plot_cluster_fill_counts.md +++ /dev/null @@ -1,68 +0,0 @@ - - -# Plot Cluster Fill Counts - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -Plot the cluster fill counts for each document in -formatted_data. - -## Usage - -

    plot_cluster_fill_counts(formatted_data, facet = TRUE)
    -
    - -## Arguments - - - - - - - - - - -
    -formatted_data - -Data created by format_template_data(), -fit_model(), or analyze_questioned_documents() -
    -facet - -TRUE uses facet_wrap to create a subplot for -each writer. FALSE plots the data on a single plot. -
    - -## Value - -ggplot plot of cluster fill counts - -## Examples - -``` r -library(handwriter) - -# Plot cluster fill counts for template training documents -template_data <- format_template_data(example_cluster_template) -plot_cluster_fill_counts(formatted_data = template_data, facet = TRUE) -``` - -![](plot_cluster_fill_counts.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) - -``` r -# Plot cluster fill counts for model training documents -plot_cluster_fill_counts(formatted_data = example_model, facet = TRUE) -``` - -![](plot_cluster_fill_counts.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-2.png) - -``` r -# Plot cluster fill counts for questioned documents -plot_cluster_fill_counts(formatted_data = example_analysis, facet = FALSE) -``` - -![](plot_cluster_fill_counts.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-3.png) diff --git a/docs/man/plot_cluster_fill_counts_files/figure-html/unnamed-chunk-1-1.png 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b/docs/man/plot_cluster_fill_rates.html new file mode 100644 index 00000000..c96ee537 --- /dev/null +++ b/docs/man/plot_cluster_fill_rates.html @@ -0,0 +1,971 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +

    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    Plot Cluster Fill Rates

    +
    +

    Description

    +

    Plot the cluster fill rates for each document in formatted_data.

    +
    +
    +

    Usage

    +
    plot_cluster_fill_rates(formatted_data, facet = FALSE)
    +
    +
    +
    +

    Arguments

    + + + + + + + + + +
    +formatted_data + +Data created by format_template_data(), fit_model(), or analyze_questioned_documents() +
    +facet + +TRUE uses facet_wrap to create a subplot for each writer. FALSE plots the data on a single plot. +
    +
    +
    +

    Value

    +

    ggplot plot of cluster fill rates

    +
    +
    +

    Examples

    +
    +
    library(handwriter)
    +
    +# Plot cluster fill rates for template training documents
    +template_data <- format_template_data(example_cluster_template)
    +plot_cluster_fill_rates(formatted_data = template_data, facet = TRUE)
    +
    +
    +
    +

    +
    +
    +
    +
    # Plot cluster fill rates for model training documents
    +plot_cluster_fill_rates(formatted_data = example_model, facet = TRUE)
    +
    +
    +
    +

    +
    +
    +
    +
    # Plot cluster fill rates for questioned documents
    +plot_cluster_fill_rates(formatted_data = example_analysis, facet = FALSE)
    +
    +
    +
    +

    +
    +
    +
    +
    + + +
    +
    + +
    + +
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z(4A_QobVyq6bt|*1vdH@tg-3byh2fYDE4Gmu6|w{)56c%PG8EMxr}=aJh2j@NVNS|FqQlZ05~)_H@{8(Em10R*#Vq= z$E$G=VQediEG;YB8Tz?lh~3XNYRk8z(QhI#he=Q&nwFNsoMaj)V#@#fU|CFcl(Kb{ zc@Yeformatted_data. - -## Usage - -
    plot_cluster_fill_rates(formatted_data, facet = FALSE)
    -
    - -## Arguments - - - - - - - - - - -
    -formatted_data - -Data created by format_template_data(), -fit_model(), or analyze_questioned_documents() -
    -facet - -TRUE uses facet_wrap to create a subplot for -each writer. FALSE plots the data on a single plot. -
    - -## Value - -ggplot plot of cluster fill rates - -## Examples - -``` r -library(handwriter) - -# Plot cluster fill rates for template training documents -template_data <- format_template_data(example_cluster_template) -plot_cluster_fill_rates(formatted_data = template_data, facet = TRUE) -``` - -![](plot_cluster_fill_rates.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) - -``` r -# Plot cluster fill rates for model training documents -plot_cluster_fill_rates(formatted_data = example_model, facet = TRUE) -``` - -![](plot_cluster_fill_rates.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-2.png) - -``` r -# Plot cluster fill rates for questioned documents -plot_cluster_fill_rates(formatted_data = example_analysis, facet = FALSE) -``` - -![](plot_cluster_fill_rates.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-3.png) diff --git a/docs/man/plot_cluster_fill_rates_files/figure-html/unnamed-chunk-1-1.png 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    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    Plot Credible Intervals

    +
    +

    Description

    +

    Plot credible intervals for the model’s pi parameters that estimate the true writer cluster fill counts.

    +
    +
    +

    Usage

    +
    plot_credible_intervals(
    +  model,
    +  interval_min = 0.025,
    +  interval_max = 0.975,
    +  facet = FALSE
    +)
    +
    +
    +
    +

    Arguments

    + + + + + + + + + + + + + + + + + +
    +model + +A model created by fit_model() +
    +interval_min + +The lower bound of the credible interval. It must be greater than zero and less than 1. +
    +interval_max + +The upper bound of the credible interval. It must be greater than the interval minimum and less than 1. +
    +facet + +TRUE uses facet_wrap to create a subplot for each writer. FALSE plots the data on a single plot. +
    +
    +
    +

    Value

    +

    ggplot plot credible intervals

    +
    +
    +

    Examples

    +
    +
    library(handwriter)
    +
    +plot_credible_intervals(model = example_model)
    +
    +
    +
    +

    +
    +
    +
    +
    plot_credible_intervals(model = example_model, facet = TRUE)
    +
    +
    +
    +

    +
    +
    +
    +
    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/man/plot_credible_intervals.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png b/docs/man/plot_credible_intervals.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png deleted file mode 100644 index 12500ee87bf5ee5087cfc4ef2d24fbafd4c282f4..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 47775 zcmc$`Wl&vBvjz$q2o~HDJh($}f&|wP+}+*XHF$6d5Hz?$aM$4O?iSn~?%KTPJKuZm z?^|`N7FD}8iDu1d@cfusj3=C=&t#at-bc@Qr)KDk}s8 zG_skHkgSD}n2?R7jlF`co`I2=k+qS%nSs2RAOr;G_wPztrua&je5nn;X~{+crtN(FyUNmD%gMn-`OVGFdUmkmYZ4C7c5! z8%7Y%SUpu*zR&^>eekpTxA5KEmOqI%(7S3NRNkedoK}q{$1sQJh|p0LMLc&ehQRKU zUaLdHI-D*>@~{<@Qj-jd^s^VId?lT133%|S6L|l^V(%RGnH!pQw$cKIz4{0mzKD4BTzmIHI^CO}=idAK&}=I|AJf zv6yr*grkX3%se%8f8`_K?wMxo<(g*QPOlxVc2eIxL)0mnKldH%jWY@6y^x-c6?LAN zDv>t7^>#BYb{c~>wk4hVD8VQZ8*qzH61TAraG=hO&W&0OB+OcCfAX?c32zcr&S;u(*moo| z!8NCM>|2;hvmbrw)Y+Y_(AnisfBOvU4drvNs9eW(z&fOi;MHiO(Jgkt`_+&ymtM(I 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deleted file mode 100644 index 26c389a6..00000000 --- a/docs/man/plot_credible_intervals.md +++ /dev/null @@ -1,80 +0,0 @@ - - -# Plot Credible Intervals - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -Plot credible intervals for the model’s pi parameters that estimate the -true writer cluster fill counts. - -## Usage - -
    plot_credible_intervals(
    -  model,
    -  interval_min = 0.025,
    -  interval_max = 0.975,
    -  facet = FALSE
    -)
    -
    - -## Arguments - - - - - - - - - - - - - - - - - - -
    -model - -A model created by fit_model() -
    -interval_min - -The lower bound of the credible interval. It must be greater than zero -and less than 1. -
    -interval_max - -The upper bound of the credible interval. It must be greater than the -interval minimum and less than 1. -
    -facet - -TRUE uses facet_wrap to create a subplot for -each writer. FALSE plots the data on a single plot. -
    - -## Value - -ggplot plot credible intervals - -## Examples - -``` r -library(handwriter) - -plot_credible_intervals(model = example_model) -``` - -![](plot_credible_intervals.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) - -``` r -plot_credible_intervals(model = example_model, facet = TRUE) -``` - -![](plot_credible_intervals.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-2.png) diff --git a/docs/man/plot_credible_intervals_files/figure-html/unnamed-chunk-1-1.png b/docs/man/plot_credible_intervals_files/figure-html/unnamed-chunk-1-1.png new file mode 100644 index 0000000000000000000000000000000000000000..637b5e64b94c726abaf1db5058ad835f9a2b91a7 GIT binary patch literal 114263 zcmeEuXEzY7SWmyu!D})#r7$ov?Qfe3&IA9D6 ztVVoX;FVqT{t*le>p?u9N>x8$`*R%h9?5?EK~1n)#a~hrS!q+(F@Cs^0QFv+blR9C zdRNJSvztccvLL48)~xpACJn@50*%h94ggG>h3LFwRhXEyK{hoJ6|$xhFQ9 zFThxunr z)9d0CR^@&Smt*v=H)P40bK}kdg*U89zLA}pRap^iF=H6k)V^{g+>&TE)%2*ny5yXl 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100644 index 00000000..4f571c3d --- /dev/null +++ b/docs/man/plot_posterior_probabilities.html @@ -0,0 +1,943 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    Plot Posterior Probabilities

    +
    +

    Description

    +

    Creates a tile plot of posterior probabilities of writership for each questioned document and each known writer analyzed with analyze_questioned_documents().

    +
    +
    +

    Usage

    +
    plot_posterior_probabilities(analysis)
    +
    +
    +
    +

    Arguments

    + + + + + +
    +analysis + +A named list of analysis results from analyze_questioned_documents(). +
    +
    +
    +

    Value

    +

    A tile plot of posterior probabilities of writership.

    +
    +
    +

    Examples

    +
    +
    library(handwriter)
    +
    +plot_posterior_probabilities(analysis = example_analysis)
    +
    +
    +
    +

    +
    +
    +
    +
    + + +
    +
    + +
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probabilities of writership for each -questioned document and each known writer analyzed with -analyze_questioned_documents(). - -## Usage - -
    plot_posterior_probabilities(analysis)
    -
    - -## Arguments - - - - - - -
    -analysis - -A named list of analysis results from -analyze_questioned_documents(). -
    - -## Value - -A tile plot of posterior probabilities of writership. - -## Examples - -``` r -library(handwriter) - -plot_posterior_probabilities(analysis = example_analysis) -``` - -![](plot_posterior_probabilities.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) diff --git a/docs/man/plot_posterior_probabilities_files/figure-html/unnamed-chunk-1-1.png b/docs/man/plot_posterior_probabilities_files/figure-html/unnamed-chunk-1-1.png new file mode 100644 index 0000000000000000000000000000000000000000..5adc16b51a7986349577877549305a778385a256 GIT binary patch literal 61865 zcmeFacTiR7*Cl*GXax)?Nl}8Lk_5C#lCJ>}kR$?<6(lJ^GLq3Yfq;sDlI~S<5+w?f zRDy!!oDn4FoMHCEukEk4}-Vl7AVR5PUx3-}T<8;f86M+^PXP$f=>x?iz z&fm8dZO$o4dxrXBd{1D{rp`z9!#9$~eR*DIsJte-%du3mBKxY2fnqd=Km9}C`GC7J#<&f-k~BRpvNNk+D4GqID2l}_!dZLw zea^&b?vLCvl~(=o>8}qBq)%`pKHey9f4F^+Z9$uCyWLc~zqnw03g?ju>90abp-OD^ z`FB@6v!pw37PsG34oE-gPTRfh{Xz(rZSeO8)CBb(9rh1XdCk*Hs5gys%qgbXaC#r| 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z4R!TE=rFE6D^84NOzYBE)@^WYt0Aibfk*0FY_g`Qo@gJO0f|e0#!a<$V8zV{>Tr-# zM}ah7UK{LKspv(=+CH|*83{cXPcfR~yw|KvEu+NE161yAEa>)`odXfCRwrzj1mJ_5 zm#sv_qKAQlys^72RhI2agSKH+X`AeuuwJxR0uVJ(`i-FBfna6T5fB=%(s1X7hWDy+Q zOx3Al-g9$M-SjwjkW`nM!F|oOyGL5aZy1<*{haN;pA*ahUsnU{o}dnMOg}K=*;j}L zE8SBj?50*3)Vyi*Nj*Q>xSKZJWQH<;ekJ^SpdH2P?UVYnx7|+Su zv0s_JVZ_9d+C>R0njs|TdaM%UFXPYK!g`JRe7!p6I8joFW5s9VcmMR6PJ3gw8LuC0 znGCle3nxL?BVCi(d0`yr#jU|oauX2#_W*Y}SeTgv%9g)DOmr)^2!Te;7oRK}g0v`C zitluOkimUYSKeg|FkViMp{8PcJys^uqY`J?*S>THY{4f$C#1rOsuu;R6kO7~C%O-0 zySgW)=xPogEXKhqC#dbOnPdUPA458i-q_<1IlOVOU=81Bnp2q&TywcjEHbystB)Oc zC$aCv9yw{|acLKReaI?K^UT7b^${=Dj-WyrP5X~rb<-0GoV_#dR?S)fc74|`u;omn z!^h)B%J`40P3P>hOi#6zduup!y#9brmTVA!tt+f!2H)W56qmlhkL$J{`x9;HU}aVQ z_}DnBK6_T1Kktl6DUW7^og*t!(k@s!-ZLK~g#3@oPlcuD({+?;Z + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    Plot Trace

    +
    +

    Description

    +

    Create a trace plot for all chains for a single variable of a fitted model created by fit_model(). If the model contains more than one chain, the chains will be combined by pasting them together.

    +
    +
    +

    Usage

    +
    plot_trace(variable, model)
    +
    +
    +
    +

    Arguments

    + + + + + + + + + +
    +variable + +The name of a variable in the model +
    +model + +A model created by fit_model() +
    +
    +
    +

    Value

    +

    A trace plot

    +
    +
    +

    Examples

    +
    +
    library(handwriter)
    +
    +plot_trace(model = example_model, variable = "pi[1,1]")
    +
    +
    +
    +

    +
    +
    +
    +
    plot_trace(model = example_model, variable = "mu[2,3]")
    +
    +
    +
    +

    +
    +
    +
    +
    + + +
    +
    + +
    + +
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If the model contains more -than one chain, the chains will be combined by pasting them together. - -## Usage - -

    plot_trace(variable, model)
    -
    - -## Arguments - - - - - - - - - - -
    -variable - -The name of a variable in the model -
    -model - -A model created by fit_model() -
    - -## Value - -A trace plot - -## Examples - -``` r -library(handwriter) - -plot_trace(model = example_model, variable = "pi[1,1]") -``` - -![](plot_trace.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) - -``` r -plot_trace(model = example_model, variable = "mu[2,3]") -``` - -![](plot_trace.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-2.png) diff --git a/docs/man/plot_trace_files/figure-html/unnamed-chunk-1-1.png b/docs/man/plot_trace_files/figure-html/unnamed-chunk-1-1.png new file mode 100644 index 0000000000000000000000000000000000000000..e8c61d54ca23b91e67b989207ce3d2ae514c3203 GIT binary patch literal 171057 zcmeFZXIPV4^EVn$KtYPzf}#{f0qFt(rMp!SHS{7iq7opXD7}S%s8~RdDnW|UJJNep zRHQ^|XrU>+gwO*C31_kQv;XIMw!YW<>74W7ydTJwklgEDYu2op-~49gex|Rh&B@Nk z4uL>8b*^18gg{s{A&@;E_OXKhtRcDwAdtOWj+Za%qb_S-c6D-fGrDhk*G}8c#m>#~ zuA%my5Xgn_a1(2XlO~7N6RS%l&U_E)$;^!6VnAccoD4f34bCv^N}Y!!qn*kwMK&)C zCpn79k8h_to>M=3iRWYXSoGMAusdr`i@Aig>ZFW$#-*)ltpRblLt&Ofi 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--- /dev/null +++ b/docs/man/processDocument.html @@ -0,0 +1,961 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +

    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    Process Document

    +
    +

    Description

    +

    Load a handwriting sample from a PNG image. Then binarize, thin, and split the handwriting into graphs.

    +
    +
    +

    Usage

    +
    processDocument(path)
    +
    +
    +
    +

    Arguments

    + + + + + +
    +path + +File path for handwriting document. The document must be in PNG file format. +
    +
    +
    +

    Value

    +

    The processed document as a list

    +
    +
    +

    Examples

    +
    +
    library(handwriter)
    +
    +image_path <- system.file("extdata", "phrase_example.png", package = "handwriter")
    +doc <- processDocument(image_path)
    +plotImage(doc)
    +
    +
    +
    +

    +
    +
    +
    +
    plotImageThinned(doc)
    +
    +
    +
    +

    +
    +
    +
    +
    plotNodes(doc)
    +
    +
    +
    +

    +
    +
    +
    +
    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/man/processDocument.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png b/docs/man/processDocument.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png deleted file mode 100644 index b8f0d40333a1c928b2a8b30e117149ae3fb0d9c0..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 11832 zcmeHNX~dJd=_?og{9XJ* z{Ud_>PPyy@0QRJ%xqAn$abF2}R#Ck5_txb0SFi3bQQQ1ga{1KfYs?|Fe{o39wg;C> z_TK$8+WS0cqcunQGUyM;%Dqe9zwUd`r-8oTv@W=SpJMTM$%()9k~dGa$z5K2F6Nmw#Dc+i>>Jo zw>;da^Bd;_g~=DLt!FVLWl{~CS9roj=T`6a&bNCS*Z2Da)P{Bccqi)ZRWvMM_)aaT zb-0|lwtx9YBEVx+mciIRv?up=-hv(6wmCmlUE6(Y9v39>)SDMM)}8KX^BVuh`lf@Q zb{9N74*E(?R$xjG_9AM#lijezR_K*%-Ev9BmWW5+ZZ5^S5A;OcB5V&Tu3M_{uLxQo z0s*{9Ro5f*MUYxQcU0Ayp{O_cwx4UZ=Cwb8FJ&jkM!$D#tQQt zFaz}UZ?Sk6Ck2_kI~KI%R#Tcs;BM;pt*P=sqW~aUU;z)ZXSCVn2He@ZO_0JFUv@SR zQtR<1D`TGuW>L1XegpW1Pv)Yi2CHbLSbo*x`IGtm_w9@qnxt;9JWCYqYruFAH@#d6 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Process Document - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -Load a handwriting sample from a PNG image. Then binarize, thin, and -split the handwriting into graphs. - -## Usage - -
    processDocument(path)
    -
    - -## Arguments - - - - - - -
    -path - -File path for handwriting document. The document must be in PNG file -format. -
    - -## Value - -The processed document as a list - -## Examples - -``` r -library(handwriter) - -image_path <- system.file("extdata", "phrase_example.png", package = "handwriter") -doc <- processDocument(image_path) -plotImage(doc) -``` - -![](processDocument.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) - -``` r -plotImageThinned(doc) -``` - -![](processDocument.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-2.png) - -``` r -plotNodes(doc) -``` - -![](processDocument.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-3.png) diff --git a/docs/man/processDocument_files/figure-html/unnamed-chunk-1-1.png b/docs/man/processDocument_files/figure-html/unnamed-chunk-1-1.png new file mode 100644 index 0000000000000000000000000000000000000000..047eecad6cb4f1c49f0d655d2ff20007590ee6c8 GIT binary patch literal 33134 zcmeHwdpy%^_`g#{N2Q~4d87kL$obHT=Siibvng|IX`wj{Un&>fBgRW{j)#3UZ2-zpWUD9zV7RKU+?RE-?(}FnDvUK 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z-mtG_OuVxES<62PUj^7x^yOQ=f9tjv#{@Wh_6G4Ez4fzu_XcrqCGM@ne+e3U;dC#Y z?(K>H8}+ae(H^kb12+E>F}e28=^i@WqZt324ejy7J)XEn_V>vCPtyHYVUJ?$QH(u` zu}3lfzj0wNce+sJ=4_xJEkcXa65f` W(x>{D4i5I;)yrm=$}ir1@P7am%0KJ? literal 0 HcmV?d00001 diff --git a/docs/man/processHandwriting.html b/docs/man/processHandwriting.html new file mode 100644 index 00000000..4537e000 --- /dev/null +++ b/docs/man/processHandwriting.html @@ -0,0 +1,947 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + +
    + + +
    + + + +
    + + + + +
    +

    Process Handwriting by Component

    +
    +

    Description

    +

    The main driver of handwriting processing. Takes in an image of thinned handwriting created with thinImage() and splits the the handwriting into shapes called graphs. Instead of processing the entire document at once, the thinned writing is separated into connected components and each component is split into graphs.

    +
    +
    +

    Usage

    +
    processHandwriting(img, dims)
    +
    +
    +
    +

    Arguments

    + + + + + + + + + +
    +img + +Thinned binary image created with thinImage(). +
    +dims + +Dimensions of thinned binary image. +
    +
    +
    +

    Value

    +

    A list of the processed image

    +
    +
    +

    Examples

    +
    +
    library(handwriter)
    +
    +twoSent_document <- list()
    +twoSent_document$image <- twoSent
    +twoSent_document$thin <- thinImage(twoSent_document$image)
    +twoSent_processList <- processHandwriting(twoSent_document$thin, dim(twoSent_document$image))
    +
    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/man/processHandwriting.md b/docs/man/processHandwriting.md deleted file mode 100644 index 6fa4849e..00000000 --- a/docs/man/processHandwriting.md +++ /dev/null @@ -1,54 +0,0 @@ - - -# Process Handwriting by Component - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -The main driver of handwriting processing. Takes in an image of thinned -handwriting created with thinImage() and splits the the -handwriting into shapes called graphs. Instead of processing -the entire document at once, the thinned writing is separated into -connected components and each component is split into graphs. - -## Usage - -
    processHandwriting(img, dims)
    -
    - -## Arguments - - - - - - - - - - -
    -img - -Thinned binary image created with thinImage(). -
    -dims - -Dimensions of thinned binary image. -
    - -## Value - -A list of the processed image - -## Examples - -``` r -library(handwriter) - -twoSent_document <- list() -twoSent_document$image <- twoSent -twoSent_document$thin <- thinImage(twoSent_document$image) -twoSent_processList <- processHandwriting(twoSent_document$thin, dim(twoSent_document$image)) -``` diff --git a/docs/man/process_batch_dir.html b/docs/man/process_batch_dir.html new file mode 100644 index 00000000..83baef13 --- /dev/null +++ b/docs/man/process_batch_dir.html @@ -0,0 +1,953 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    Process Batch Directory

    +
    +

    Description

    +

    Process a list of handwriting samples saved as PNG images in a directory: (1) Load the image and convert it to black and white with readPNGBinary() (2) Thin the handwriting to one pixel in width with thinImage() (3) Run processHandwriting() to split the handwriting into parts called edges and place nodes at the ends of edges. Then combine edges into component shapes called graphs. (4) Save the processed document in an RDS file. (5) Optional. Return a list of the processed documents.

    +
    +
    +

    Usage

    +
    process_batch_dir(input_dir, output_dir = ".", skip_docs_on_retry = TRUE)
    +
    +
    +
    +

    Arguments

    + + + + + + + + + + + + + +
    +input_dir + +Input directory that contains images +
    +output_dir + +A directory to save the processed images +
    +skip_docs_on_retry + +Logical whether to skip documents in input_dir that caused errors on a previous run. The errors and document names are stored in output_dir > problems.txt. If this is the first run, process_batch_list will attempt to process all documents in input_dir. +
    +
    +
    +

    Value

    +

    A list of processed documents

    +
    +
    +

    Examples

    +
    +
    library(handwriter)
    +
    +process_batch_list("path/to/input_dir", "path/to/output_dir")
    +docs <- process_batch_list("path/to/input_dir", "path/to/output_dir")
    +
    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/man/process_batch_dir.md b/docs/man/process_batch_dir.md deleted file mode 100644 index 1ad07b5f..00000000 --- a/docs/man/process_batch_dir.md +++ /dev/null @@ -1,67 +0,0 @@ - - -# Process Batch Directory - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -Process a list of handwriting samples saved as PNG images in a -directory: (1) Load the image and convert it to black and white with -readPNGBinary() (2) Thin the handwriting to one pixel in -width with thinImage() (3) Run -processHandwriting() to split the handwriting into parts -called edges and place nodes at the ends of edges. -Then combine edges into component shapes called graphs. (4) -Save the processed document in an RDS file. (5) Optional. Return a list -of the processed documents. - -## Usage - -
    process_batch_dir(input_dir, output_dir = ".", skip_docs_on_retry = TRUE)
    -
    - -## Arguments - - - - - - - - - - - - - - -
    -input_dir - -Input directory that contains images -
    -output_dir - -A directory to save the processed images -
    -skip_docs_on_retry - -Logical whether to skip documents in input_dir that caused errors on a -previous run. The errors and document names are stored in output_dir \> -problems.txt. If this is the first run, process_batch_list -will attempt to process all documents in input_dir. -
    - -## Value - -A list of processed documents - -## Examples - -``` r -library(handwriter) - -process_batch_list("path/to/input_dir", "path/to/output_dir") -docs <- process_batch_list("path/to/input_dir", "path/to/output_dir") -``` diff --git a/docs/man/process_batch_list.html b/docs/man/process_batch_list.html new file mode 100644 index 00000000..7c2eb7c8 --- /dev/null +++ b/docs/man/process_batch_list.html @@ -0,0 +1,954 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    Process Batch List

    +
    +

    Description

    +

    Process a list of handwriting samples saved as PNG images: (1) Load the image and convert it to black and white with readPNGBinary() (2) Thin the handwriting to one pixel in width with thinImage() (3) Run processHandwriting() to split the handwriting into parts called edges and place nodes at the ends of edges. Then combine edges into component shapes called graphs. (4) Save the processed document in an RDS file. (5) Optional. Return a list of the processed documents.

    +
    +
    +

    Usage

    +
    process_batch_list(images, output_dir, skip_docs_on_retry = TRUE)
    +
    +
    +
    +

    Arguments

    + + + + + + + + + + + + + +
    +images + +A vector of image file paths +
    +output_dir + +A directory to save the processed images +
    +skip_docs_on_retry + +Logical whether to skip documents in the images arguement that caused errors on a previous run. The errors and document names are stored in output_dir > problems.txt. If this is the first run, process_batch_list will attempt to process all documents in the images arguement. +
    +
    +
    +

    Value

    +

    A list of processed documents

    +
    +
    +

    Examples

    +
    +
    library(handwriter)
    +
    +images <- c('path/to/image1.png', 'path/to/image2.png', 'path/to/image3.png')
    +process_batch_list(images, "path/to/output_dir", FALSE)
    +docs <- process_batch_list(images, "path/to/output_dir", TRUE)
    +
    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/man/process_batch_list.md b/docs/man/process_batch_list.md deleted file mode 100644 index 3005b552..00000000 --- a/docs/man/process_batch_list.md +++ /dev/null @@ -1,69 +0,0 @@ - - -# Process Batch List - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -Process a list of handwriting samples saved as PNG images: (1) Load the -image and convert it to black and white with -readPNGBinary() (2) Thin the handwriting to one pixel in -width with thinImage() (3) Run -processHandwriting() to split the handwriting into parts -called edges and place nodes at the ends of edges. -Then combine edges into component shapes called graphs. (4) -Save the processed document in an RDS file. (5) Optional. Return a list -of the processed documents. - -## Usage - -
    process_batch_list(images, output_dir, skip_docs_on_retry = TRUE)
    -
    - -## Arguments - - - - - - - - - - - - - - -
    -images - -A vector of image file paths -
    -output_dir - -A directory to save the processed images -
    -skip_docs_on_retry - -Logical whether to skip documents in the images arguement that caused -errors on a previous run. The errors and document names are stored in -output_dir \> problems.txt. If this is the first run, -process_batch_list will attempt to process all documents in -the images arguement. -
    - -## Value - -A list of processed documents - -## Examples - -``` r -library(handwriter) - -images <- c('path/to/image1.png', 'path/to/image2.png', 'path/to/image3.png') -process_batch_list(images, "path/to/output_dir", FALSE) -docs <- process_batch_list(images, "path/to/output_dir", TRUE) -``` diff --git a/docs/man/readPNGBinary.html b/docs/man/readPNGBinary.html new file mode 100644 index 00000000..195569a5 --- /dev/null +++ b/docs/man/readPNGBinary.html @@ -0,0 +1,984 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    Read PNG Binary

    +
    +

    Description

    +

    This function reads in and binarizes a PNG image.

    +
    +
    +

    Usage

    +
    readPNGBinary(
    +  path,
    +  cutoffAdjust = 0,
    +  clean = TRUE,
    +  crop = TRUE,
    +  inversion = FALSE
    +)
    +
    +
    +
    +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + +
    +path + +File path for image. +
    +cutoffAdjust + +Multiplicative adjustment to the K-means estimated binarization cutoff. +
    +clean + +Whether to fill in white pixels with 7 or 8 neighbors. This will help a lot when thinning – keeps from getting little white bubbles in text. +
    +crop + +Logical value dictating whether or not to crop the white out around the image. TRUE by default. +
    +inversion + +Logical value dictating whether or not to flip each pixel of binarized image. Flipping happens after binarization. FALSE by default. +
    +
    +
    +

    Value

    +

    Returns image from path. 0 represents black, and 1 represents white by default.

    +
    +
    +

    Examples

    +
    +
    library(handwriter)
    +
    +image_path <- system.file("extdata", "phrase_example.png", package = "handwriter")
    +csafe_document <- list()
    +csafe_document$image = readPNGBinary(image_path)
    +plotImage(csafe_document)
    +
    +
    +
    +

    +
    +
    +
    +
    + + +
    +
    + +
    + +
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    readPNGBinary(
    -  path,
    -  cutoffAdjust = 0,
    -  clean = TRUE,
    -  crop = TRUE,
    -  inversion = FALSE
    -)
    -
    - -## Arguments - - - - - - - - - - - - - - - - - - - - - - -
    -path - -File path for image. -
    -cutoffAdjust - -Multiplicative adjustment to the K-means estimated binarization cutoff. -
    -clean - -Whether to fill in white pixels with 7 or 8 neighbors. This will help a -lot when thinning – keeps from getting little white bubbles in text. -
    -crop - -Logical value dictating whether or not to crop the white out around the -image. TRUE by default. -
    -inversion - -Logical value dictating whether or not to flip each pixel of binarized -image. Flipping happens after binarization. FALSE by default. -
    - -## Value - -Returns image from path. 0 represents black, and 1 represents white by -default. - -## Examples - -``` r -library(handwriter) - -image_path <- system.file("extdata", "phrase_example.png", package = "handwriter") -csafe_document <- list() -csafe_document$image = readPNGBinary(image_path) -plotImage(csafe_document) -``` - -![](readPNGBinary.markdown_strict_files/figure-markdown_strict/unnamed-chunk-1-1.png) diff --git a/docs/man/readPNGBinary_files/figure-html/unnamed-chunk-1-1.png b/docs/man/readPNGBinary_files/figure-html/unnamed-chunk-1-1.png new file mode 100644 index 0000000000000000000000000000000000000000..047eecad6cb4f1c49f0d655d2ff20007590ee6c8 GIT binary patch literal 33134 zcmeHwdpy%^_`g#{N2Q~4d87kL$obHT=Siibvng|IX`wj{Un&>fBgRW{j)#3UZ2-zpWUD9zV7RKU+?RE-?(}FnDvUK z@=L|U#8&+E=fRU=Vv8)r#3ZYv7Xx=jy_(y_#H3dG9yo9ua=`ik^a3>C)TMJ^PixPM zo&mn#lh*si#0=x&&baz0o>^=DsI+kBAH*vySy}g1PU}A?x^VKt)sFsY&qBXW&HERM z_T8x)>`L?9s>_&s;=A2^?LOHz&${n-&p5x)*nB>ReOv3FqT~NaUD-C)G-3Vt;|3X4 zscvD}{SpYSzH_`Ul^e;V1#)Q1?v!XcC(zU-H0ATPdYgL+34PVo#+TnjG_8ne(%KpS zaL2=~;tGtnl^txZDxOB+V+Awbto-BF;xS#<+HwuwZ|U(An_gG*$~8)ApRiVj;yxx* zZE_)1wP(#cjF|n#^i@NzNXd8i#JC;O-1Z`Nx|$lZgsH}Nl3EftM2$Dqf0nm>OZ}m` zy*Vkz)S7WugoxrpU65+(6A~;&!zQ&X$qo-cC_Gxl%Grq32 z%QmmJf1aMWf67e@yB4o*b{&+u{BrGX*d%Wv$UZGuy62wJhGp`x>e_ag;r+D;dyK{t zS-0ZL2xL!Z?NRFe_u{BZlzi{;`zrU@F6PzilH%$t-&_qHT(|qI+`&7lt9-+q&t_&X zmGAd?-2c?)@mOp3ApPz3@o6#a>GRXIto{$X_h-$h4K=-Z%k?>6%b(Y}T-(u-7C@SL z>&B$KbYmJgEuUTzDT!cF?XdbRy#~9b5wD@n)z%|s$2`oRYMr@ot}yc-M}4~q36*-W zh|-WUY463(lb;237WW`^f_o}k5e(XA^H0P;Q~=7K9#!kwy(_>iz|CJJ5M_P7C6ucN z;h-}MmiGB3p6EpFcWToz-R5!4?Cra^9yYf9>#kpwIj0>KWRN2lx52e+G2tcDBPSv^ zYQyuu!Hci0%@GjLq7 zT=T3D{>c!HYInMXVe6H5Z|rU5NjWMko^!}Wb(&aPI1V%;oC=E=k!+!hm1N9F&Zvhh zs{xbi0e~>{bok5b=uxp9z_qlP_zhn%Dd0*R_>l*G#Ka^rBwhgX<1dvs9!H+7EQaoO?`6kx0^p6i=L5d5`)S9=R3g1f9}i>Pbn^1 zqxSn~-@a%m*|O-paN5osyLZb%M*+`fM=kC@X4xz=AFDs|R$4YB zANVW~qPFMXNBgSS64S{uY<1bHW8y2C(xS5DR4u#nBr0UWAicdufdg8hizeIkq3nal zz7+(%^d!#vRq3oJhRnq)yQd=b6LsdcW2!0_(Z(YDKTonKXvCG0{oQXQ%*7|Vd!*y$ zYRS){0t_4heE6C~x&T;Iepq!HZ*Y%qP`UZj-Pvco*2GwlCXM!5y%BcDup9R*Gg8=mgQ2yJh=rK>bH4~gJ$=thc%}cE2}m|o(inGm!N8S zcE31+f5bs=vz+RXb~K-fr;!q7Qck=2FbR1R6CL{C6-dBcZED@YQJfFDiSyR}v_IN< z*_c#+X8nkq%annag*_rYZ_2p{!$1Um{dOYOT;>6qQh|?L6M(c_8U59KhCk&Pe`Lh- zaS(x0BmfP0f6^gh*vVNubJ%D9sb-o^Ryxxt`iMktEFx@GXBwn@2}+UCW#x%j(WLO= z<>)1R33RjZXZqDnjd|kK?Gydf0aEZ}>dLmdvM48)Lm#OF<2?ncPjp1wx)&T-X>m1F6C6+JJyCQ`1oPb3o>eZXyBX%Nb@%-e8havtR- zvj9{+%@1j*z(rUURHqNO#Y5Z(9XjS9_~faxc~qZCR1Rq7Ma%f}0$22KAy~&zs66($ z#1n@R&K#Uc_mXWOX5RZnN!uKiTKk@|Eu+PAw>mRjbCavdb!w0jy^sU7^UL0@tm1m zM!ENZh4lMCZYCjNr{`IJT8||&c-^hElCY>WVpeXes6FF1ZP0$)TeU0ndche=ydyoRz^jP_!b3r=x1fN6J*3Uj>_ZIK8|}Ff$LK&3KUdK ze=ftn2tw*p8t9J*DdVf@DMq?TKh{fTd5u%vITuv>mzxEUDA4hT{N2c6)30~1aOG0| zwn)l1IIMao!A8M&wCTP$k5`PCYUo79^I~}Udikt~(F$INT4JU^kv;N&1+5os z=Q#HaA^t8p)Tp=s;z(u54#_m#e_!+&YUR$#oWY-Mq^-X44Vw(DGs2IWPp~G9?h*?I zK3XsmUSnC$TaB1!^8#IO>C;9nH1$vXSyayt9DjUd)Ur*C!qs(X(8Y z-}h0nwD%=+1@Aqs81JJTtt-_t)o*s`dcMAl3jkwZo|+^M;{-F=Fsndwwj-KCh3Xmf z(H;HMFq{*Maj^4=v?(lTCq}W| z^f3`PHV}f6WjrDstHb46hvscP^r?Jia%I!Vg}fubl=?YTu4`$L75B!(1WkaLg2DVI zVTur@mkRwgC$ISfD44uUGyc|N?6JXun!G$$oD~#3QNfgYCF2vd>sfz__Hy=yZ2iCu zSNA9ew3@#Y>nu5X){hMihucAIy8n)|Awu5^BtFhi|Ndh9#h^k!mYITIPO3>$_uhps z3Zzmz8#gK-aXJNp6oP{Wc}fo(dvn;+#Z;v+PRL8iEZ`++m?1;pr4I}lVX@gdsXI(cRW8EvD+9sQ=(^V2qBMw-&_I3_89ww)|(#8F!RoQjb$7j^Y_zZ zZr*-zY3Ap(<9<$6PYy}cj6E9}c@DB>7i@bjx#UnMD!}AY*<~Bd#ZRFJ|FNMsh2g=t zy?sv$62{q`6EJRMt`eNUN>-+}u~Kc6hhHlRt}3c!#SA+i(V3x zX)YHVi1ni7pW+t48cmq3;|=NcY4J9Kd|YMYbAs2iqjeewl<5P-qmi!kr-A%fp@$m> zGd%d5l2W?bz6?=^3HC$2ImL`$PBy&QsKp1FRHg|Mobq7C?%|M#>Xc0V0bI-FC!&>nkzzwrdq@1b)GE_89U-UDYnWJIai9!%DIpcgeYlb04CX`fz;(=i zL4yIkeML>B>)BD7yem5RmJWN|cw&+ar;V347H+Uf8s)_0V*(Qfo1Jr9vkkI<%HWyT zx=oOb77!1))+YzT0|udcBb_)fQ=H&HMEpPjkB2ow_(>M+8qK}&iMkmbIA}&Usl;YM zm`jWFsbN9&PZ zq2A!5Gzj@tfin@*;3`K=Dey*DZcWf7B$ztS=n72Ev!9V-3sgMMrd3#8wNA}I!-aOJ5hFLDCB`9H&qD}lpEMmYIZ&?W+y9?E}nvU z^%Vfw|1isL3-pv!f3nh7K6ELuGspa$jlh?YLoxh1j*Upb!#$3WJGM5Fzn)^h#|2Fm zyQ0%zmpk*`XcR(paTl><)gTb0AZu>{v%_plaiKEh^Ci3Gwk`$(FslpJsnHs(?3i%k zrHX(?Lv3q^B1{}c4W-79!I%;^U-D?Aj;xdLC&qW~Bv%aRxFcN#A{d|u_8>EOFf`~G zS!LNM(RCABF}4wi{%-4T%!($Jzl~6F6=R6^UiGQAEFQAKVCfi{y3x4yZFYo8G;J`m86kK;d^#yAUPmadPUO}R$Il1m7vJh0EoL$ z&x$T88iWl-oY}9f9R9?$%+57a?IyVEmD{*mdA!+x;d|T!EcPbBR^WbwtHXCOu2fPP z=?Q}(C!Au@XwR?;%rTp(^b2PwK@V)rvP_|b8dg~6{lN89GoVhd_GYHXeC0T~z-ghn z3GJ;CJUGR%%!wY^zGy&T&v)q!#zl?5aO3MtCX_Plw^6VBClY|R)L9B(#~%EhGks@S zbWN4jU?^9OY*uQDcC4^R72ZSQ{+aGAaJkLGMObv@5C|ze%+B=0F;0i@)+C=Z{5;aT zRH^i$BkR;k=ZFD)WNa|Rw6Fop^L`pK`Q-#CZCpQ;B`i+gusX-}&kG36>tY^d5ub7OV`tTw% zG;`QF-+H+X-)WDR&2nevgODxLd64Sz?B4bMX}pjpT?rehQ#ML)eIGOi&B7(7UvtPb zs0hxZy$h6JZ@M{huus5^xEK*1@H`FKnF$g+bI3a|mm4o#EhR6Pb*bo5p(*GwyaC@w z5MR|3S$>g#5r9((p;8?wyKYX#yiSau!a5u}gnk$394rGJ>DrSMc#D}?!iZF2`dl#c z;xlpONaFJ@#(4@xh+$C2oKYooB7_i{1^}a_M-or7C6v=xkc$b98;U2GvDnE9LO9U1 ze_t3w+bXV@8HxNJXia{K9&;C+n%#041{=C#*r>7RS9Hyj{jatvPz-y*ALtL*a@G<; 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    RPE<>+Po_)Rd;oZ#jSewL!17c;=5IePx$?@kZ-Gj2@i|6E<`-L0oyC% zuKsG+j}b(R^~7HdAPM42@Y0;0^CM{E%c&I7fmX3f_oQO%lX8X|%*&oo2?Lqsq{ z)cqSyim3ZMy%hCX^Yl{G6wlL3QByomFGUK*JiQbt81wW}Bscv+FGbqmyo@O#7$Sl( z?*S3P5UK7!?;=MzCB + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    Read and Process

    +
    +

    Description

    +

    [Superseded]

    +

    Development on read_and_process() is complete. We recommend using processDocument(). read_and_process(image_name, “document”) is equivalent to processDocument(image_name).

    +
    +
    +

    Usage

    +
    read_and_process(image_name, transform_output)
    +
    +
    +
    +

    Arguments

    + + + + + + + + + +
    +image_name + +The file path to an image +
    +transform_output + +The type of transformation to perform on the output +
    +
    +
    +

    Value

    +

    A list of the processed image components

    +
    +
    +

    Examples

    +
    +
    library(handwriter)
    +
    +# use handwriting example from handwriter package
    +image_path <- system.file("extdata", "phrase_example.png", package = "handwriter")
    +doc <- read_and_process(image_path, "document")
    +
    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/man/rgb2grayscale.html b/docs/man/rgb2grayscale.html new file mode 100644 index 00000000..e7a7e992 --- /dev/null +++ b/docs/man/rgb2grayscale.html @@ -0,0 +1,894 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    rgba2grayscale

    +
    +

    Description

    +

    Changes RGB image to grayscale

    +
    +
    +

    Usage

    +
    rgb2grayscale(img)
    +
    +
    +
    +

    Arguments

    + + + + + +
    +img + +A 3D array with slices R, G, and B +
    +
    +
    +

    Value

    +

    img as a 3D array as grayscale

    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/man/rgb2grayscale.md b/docs/man/rgb2grayscale.md deleted file mode 100644 index 113284c2..00000000 --- a/docs/man/rgb2grayscale.md +++ /dev/null @@ -1,31 +0,0 @@ - - -# rgba2grayscale - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -Changes RGB image to grayscale - -## Usage - -
    rgb2grayscale(img)
    -
    - -## Arguments - - - - - - -
    -img - -A 3D array with slices R, G, and B -
    - -## Value - -img as a 3D array as grayscale diff --git a/docs/man/rgba2rgb.html b/docs/man/rgba2rgb.html new file mode 100644 index 00000000..42e5bd04 --- /dev/null +++ b/docs/man/rgba2rgb.html @@ -0,0 +1,894 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    rgba2rgb

    +
    +

    Description

    +

    Removes alpha channel from png image.

    +
    +
    +

    Usage

    +
    rgba2rgb(img)
    +
    +
    +
    +

    Arguments

    + + + + + +
    +img + +A 3-d array with slices R, G, B, and alpha. +
    +
    +
    +

    Value

    +

    img as a 3D array with alpha channel removed

    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/man/rgba2rgb.md b/docs/man/rgba2rgb.md deleted file mode 100644 index 92e42c56..00000000 --- a/docs/man/rgba2rgb.md +++ /dev/null @@ -1,31 +0,0 @@ - - -# rgba2rgb - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -Removes alpha channel from png image. - -## Usage - -
    rgba2rgb(img)
    -
    - -## Arguments - - - - - - -
    -img - -A 3-d array with slices R, G, B, and alpha. -
    - -## Value - -img as a 3D array with alpha channel removed diff --git a/docs/man/thinImage.html b/docs/man/thinImage.html new file mode 100644 index 00000000..d1625d14 --- /dev/null +++ b/docs/man/thinImage.html @@ -0,0 +1,894 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    thinImage

    +
    +

    Description

    +

    This function returns a vector of locations for black pixels in the thinned image. Thinning done using Zhang - Suen algorithm.

    +
    +
    +

    Usage

    +
    thinImage(img)
    +
    +
    +
    +

    Arguments

    + + + + + +
    +img + +A binary matrix of the text that is to be thinned. +
    +
    +
    +

    Value

    +

    A thinned, one pixel wide, image.

    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/man/thinImage.md b/docs/man/thinImage.md deleted file mode 100644 index 481edccc..00000000 --- a/docs/man/thinImage.md +++ /dev/null @@ -1,32 +0,0 @@ - - -# thinImage - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -This function returns a vector of locations for black pixels in the -thinned image. Thinning done using Zhang - Suen algorithm. - -## Usage - -
    thinImage(img)
    -
    - -## Arguments - - - - - - -
    -img - -A binary matrix of the text that is to be thinned. -
    - -## Value - -A thinned, one pixel wide, image. diff --git a/docs/man/twoSent.html b/docs/man/twoSent.html new file mode 100644 index 00000000..c44016ec --- /dev/null +++ b/docs/man/twoSent.html @@ -0,0 +1,932 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    Two sentence printed example handwriting

    +
    +

    Description

    +

    Two sentence printed example handwriting

    +
    +
    +

    Usage

    +
    twoSent
    +
    +
    +
    +

    Format

    +

    Binary image matrix. 396 rows and 1947 columns

    +
    +
    +

    Examples

    +
    +
    library(handwriter)
    +
    +twoSent_document <- list()
    +twoSent_document$image <- twoSent
    +plotImage(twoSent_document)
    +
    +twoSent_document <- list()
    +twoSent_document$image <- twoSent
    +plotImage(twoSent_document)
    +twoSent_document$thin <- thinImage(twoSent_document$image)
    +plotImageThinned(twoSent_document)
    +twoSent_processList <- processHandwriting(twoSent_document$thin, dim(twoSent_document$image))
    +
    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/man/whichToFill.html b/docs/man/whichToFill.html new file mode 100644 index 00000000..7ab9f74e --- /dev/null +++ b/docs/man/whichToFill.html @@ -0,0 +1,894 @@ + + + + + + + + + +handwriter + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + +
    + +
    + + +
    + + + +
    + + + + +
    +

    whichToFill

    +
    +

    Description

    +

    Finds pixels in the plot that shouldn’t be white and makes them black. Quick and helpful cleaning for before the thinning algorithm runs.

    +
    +
    +

    Usage

    +
    whichToFill(img)
    +
    +
    +
    +

    Arguments

    + + + + + +
    +img + +A binary matrix. +
    +
    +
    +

    Value

    +

    A cleaned up image.

    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/man/whichToFill.md b/docs/man/whichToFill.md deleted file mode 100644 index 1ebb9652..00000000 --- a/docs/man/whichToFill.md +++ /dev/null @@ -1,32 +0,0 @@ - - -# whichToFill - -[**Source code**](https://github.com/CSAFE-ISU/handwriter/tree/176-automatic-documentation/R/#L) - -## Description - -Finds pixels in the plot that shouldn’t be white and makes them black. -Quick and helpful cleaning for before the thinning algorithm runs. - -## Usage - -
    whichToFill(img)
    -
    - -## Arguments - - - - - - -
    -img - -A binary matrix. -
    - -## Value - -A cleaned up image. diff --git a/docs/methods.html b/docs/methods.html deleted file mode 100755 index c5ba6bef..00000000 --- a/docs/methods.html +++ /dev/null @@ -1,146 +0,0 @@ - - - - - - - - - Handwriter - - - - - - - -
    - -
    - - - -
    -

    Methods

    -

    Handwriter is a developmental R package hosted at github.com/CSAFE-ISU/handwriter. - It is our major computational tool for the project. The package takes in scanned - handwritten documents and the following are performed:

    -
      -
    1. Binarize - Turn the image into pure black and white
    2. -
    3. Skeletonize - Reduce writing to a 1 pixel wide skeleton
    4. -
    5. Break - Connected writing is decomposed into small manageable pieces called graphs with nodes and edges that usually repond to Roman letters.
    6. -
    7. Measure - Measurements are taken on each graph
    8. -
    -

    Below is an example we commonly use, the word 'csafe' in cursive. In this example you can see the gray background of the writing, - a result of binarization. The colored lines is the single pixel skeleton. The change from green to blue marks - the changes after the piece of writing is broken into graphs. The red dots are the endpoints and intersections - of each graph.

    -
    - csafe_all_features -
    -

    From this point, measurements are taken on each graph individually. These measurements are calculated in - Rcpp, - a power package that allows for R functions to be implemented in C++. The measurements we looked at are Rotational Angle, Compactness, and Loops. - Rotation Angle is by far the most useful measurement, but we feel all are worth mentioning.

    -
    -

    Rotational Angle

    -

    The first principal component for each graph, or “letter”, is calculated through an eigendecomposition of the covariance matrix. - The first principal component enjoys the property of having two invariant directions, and so we take the vector that lies in the - upper half plane. The rotation angle of the graph is defined as the angle between the vector (0,1), and the unit principal component - vector on the upper half plane. The angle is measured in radians and is considered a feature of the graph defined on the interval (0,π).

    -

    Let's walk through an example of how rotational angle can help differentiate between two writers.

    -

    Here is the scanned writing of "Our London business is good," from our first writer, writer A:

    -
    - London_writing_1 -
    -

    These measurements are used to differentiate inside of each cluster, so we will look at the cluster of graphs most similar to the letter 'u' in the roman alphabet.

    -

    On the left is the cluster for this graph. On the right is 4 individual graphs from the writing, as well as a graph with each graphs direction of greatest variability.

    -
    - London_u_1 -
    -

    Now, the directions determined above are compiled for each cluster from each writer. The compiled graph for the graph closed to the letter u from our writer A is shown on the left below. - These data are then normalized to respect the polar coordinate system, and a curve is fit to approximate the distribuition of the rotation angle, show on the right

    -
    - London_Graph_1 -
    -
    -

    The same can be done for a writer B:

    -
    - London_writing_2 - London_u_2 - London_Graph_2 -
    -

    There is great disparity in the distribuition of the rotation angle between writer A and B when dealing with this cluster. We have found this measurement to be the most influential - in correctly identifying a writer.

    -
    -

    Compactness

    -

    Compactness is computed as:

    - compactness_equation -

    It can be thought of as the tightness of black pixels in each graph based on distance from the centroid

    -

    A compactness value is found, and can be plotted around the centroid as such:

    -
    - compactness_examples -
    -

    Unfortunatley, while informative for comparing like-sized graphs, this measurement suffers from the inherently - spatial dependence between pixels and (unfortunately) does not scale well for modelling.

    -
    -

    Loops

    -

    The number of loops in a given graph is found, as well as the height to width ratio of each.

    -

    Unfortunatley, we found that most loops in handwriting are generally about the same shape, and - didn't produce any useful information in differentiating between writers.

    -
    -

    What's next?

    -

    Once each graph's measrurements have been taken and saved, the job of handwriter is done. You can now take this information and integrate it into your specific workflow.

    -

    For an example of our workflow that involved handwriter, take a look at Our Workflow -

    - -
    - -
    - - - - - - - diff --git a/docs/quarto_website.yml b/docs/quarto_website.yml new file mode 100644 index 00000000..abec99e4 --- /dev/null +++ b/docs/quarto_website.yml @@ -0,0 +1,34 @@ +project: + type: website + +website: + title: "$ALTDOC_PACKAGE_NAME" + navbar: + search: true + right: + - icon: github + href: $ALTDOC_PACKAGE_URL_GITHUB + aria-label: $ALTDOC_PACKAGE_NAME GitHub + sidebar: + collapse-level: 1 + contents: + - text: Home + file: index.qmd + - section: $ALTDOC_VIGNETTE_BLOCK + - section: $ALTDOC_MAN_BLOCK + - text: News + file: $ALTDOC_NEWS + - text: Changelog + file: $ALTDOC_CHANGELOG + - text: License + file: $ALTDOC_LICENSE + - text: Licence + file: $ALTDOC_LICENCE + - text: Code of conduct + file: $ALTDOC_CODE_OF_CONDUCT + - text: Citation + file: $ALTDOC_CITATION + +format: + html: + css: styles.css \ No newline at end of file diff --git a/docs/research.html b/docs/research.html deleted file mode 100755 index 40dfe6df..00000000 --- a/docs/research.html +++ /dev/null @@ -1,117 +0,0 @@ - - - - - - - - - Handwriter - - - - - - - -
    - -
    - - - -
    -

    Publications

    -

    A rotation-based feature and Bayesian Hierarchichal model for the forensic evaluation of handwriting evidence in a closed set, - Crawford et al. (2022) - [PDF] -

    - -

    Handwriting Indentification using Random Forests and Score-based likelihood ratios, - Johnson and Ommen (2022) - [PDF] - [Wiley Online] -

    - -

    A clustering method for graphical handwriting components and statistical writership analysis, - Crawford et al. (2020) - [PDF] - [Wiley Online] -

    - -

    - A database of handwriting samples for applications in forensic statistics, - Crawford et al. (2019) - [PDF] - [Science Direct] -

    - -
    -

    Websites

    -

    Center for Statistics and Application in Forensic Evidence's (CSAFE) Homepage

    -

    GitHub Repo for Handwriter

    -
    -

    Posters

    - -

    Measurements Poster - Poster created by James Taylor for ISU Research Day 2020

    - -

    Handwriter Poster - Poster created by Félix Báez-Santiago and Julia Lundstrum for IAI Conference 2021

    -
    -
    - -
    - -
    - - - - - - - diff --git a/docs/resources/documents/Crawford2019.pdf b/docs/resources/documents/Crawford2019.pdf deleted file mode 100644 index b24e4dd53cfe39f0cadfad63a85049124e917286..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 532481 zcmbrm2Rzm7|37Y%5JDM=ve$9;IcE0Wd(UI>2_e}b$&QR{rLt20 z_c?UmZu)#a_xJbLL+^90^M1d^b-iBC*SM~OQ&U!65G;hGW^=c8 zq7)MYsXDr0th^k9Ft%)9kSZG-3W1@(APqK%FbpKe28M&tP!vd=4FS?+gF{d-C={f~ zX2J%6AQ5bEG|Wswf)e9qi>1YO;D?etzzbuy#|e$5Bp2TQ0VCLOuh`svk3mpKKp5=L z-(yf=H1fz87>YVNhJ+m%gCmaKhX8~<%max!`YZ~4R2DS)$g?o8F!V4z7z7MHG6n@7 zkp%{W9DNoJK_7V*0X-rg3<-lAxeo<7I))bh!x-v_d~jjJ5q;r*m}fWyd}KWUk>Q7B zfkTl;_`+fEqhoOBkvV`Pz<(G+ADII<^5~kwQShVpp^wfVLip&j0NW$-A;733>w$ov zj;tjD`Uf7+qxOe@qmJ-E3L}n=!C^<{8Hq$3kp+oH9Jvn#h8&R(1ra`CyD0cke?y_s zhh+gQ9Ddkdz`}6&VS51!Baf^b7z{-mwhb`&s9%D?D8%742Lo_(L>9ocj_`%TP>1IL z41*uBaWEVSKRgFu1nQ`KC}Hs7c?P2($Rm2707E!r_h2;gh%8u<57UDnfk{2|EWiPM zm>vWLh8><42pW0BXP^L!!}OqFDD?2WK;dZgVR}%&b`OuC;Bd%cKSCoRNAy4=k?_OM 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