README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r setup, include=FALSE}
lgr::get_logger("mlr3")$set_threshold("warn")
lgr::get_logger("mlr3spatial")$set_threshold("warn")
set.seed(1)
options(width = 80)

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
REBUILD = TRUE
RECREATE_ALL_2DFIGS = FALSE
```

# vistool

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The goal of `vistool` is to visualize optimization traces and aid in teaching optimization-related concepts.

## Installation

You can install the development version of vistool from [GitHub](https://github.com/) with:

``` r
# install.packages("pak")
pak::pak("slds-lmu/vistool")
```

Please note that visualization features rely on [`plotly`]() which in turns relies on certain functionality provided by Python packages, which are accessed via reticulate.  
Most importantly this affects the `$save()` functionality for plots, which uses `plotly::save_image()` internally, and requires the `kaleido` Python package.

The following instructions are provided by `?plotly::save_image` and assume you do not have `miniconda` installed already:

```r
install.packages('reticulate')
reticulate::install_miniconda()
reticulate::conda_install('r-reticulate', 'python-kaleido')
reticulate::conda_install('r-reticulate', 'plotly', channel = 'plotly')
reticulate::use_miniconda('r-reticulate')
```

## Example

```{r example-setup}
library(vistool)
library(mlr3verse)
```


This examples shows how to visualize the prediction surface of an SVM on the `pima` task included in `mlr3`:

```{r example}
# Create an example task, add missing data imputation and select 2 features
task = tsk("pima")
task = po("imputemean")$train(list(task))[[1]]
task$select(c("insulin", "mass"))

# Select example learner
learner = lrn("classif.svm", predict_type = "prob")

# Create the Visualizer object from task and learner
vis = as_visualizer(task, learner)

# Define a 3D scene
vis$set_scene(x = 1.4, y = 1.4, z = 1.4)
```

View interactively:

```{r example-plot, eval=FALSE}
vis$plot()
```

![](man/figures/demo_1.png)

Save static version as png:

```{r example-save}
vis$save("man/figures/demo_1.png", width = 500, height = 500)
```

## Resources 

For visualization of...

* [Loss Functions](https://slds-lmu.github.io/vistool/articles/loss_functions.html)
* [Model Predictions](https://slds-lmu.github.io/vistool/articles/model.html)
* [Objective Functions](https://slds-lmu.github.io/vistool/articles/objective.html)