README.Rmd

---
output: github_document
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-"
)
```
# parscanlogreader <img src="man/figures/logo.png" align="right" width="120"/>

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## Overview

The goal of parscanlogreader is to read and process raw log files from Scikit-learn's [RandomizedSearchCV](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.RandomizedSearchCV.html).

## Installation

<!-- You can install the released version of parscanlogreader from [CRAN](https://CRAN.R-project.org) with: -->

<!-- ``` r -->
<!-- install.packages("parscanlogreader") -->
<!-- ``` -->

<!-- And  -->
The development version can be installed from [GitHub](https://github.com/) with:

``` r
devtools::install_github("kreh-team/parscanlogreader")
```

## Examples

### Basic example

This is a basic example which shows you how the data pipeline works:

```r
library(parscanlogreader)

src_file <- "logs/cnn-gru-scan.log"
```

```r
log_data_raw <- src_file %>%
  read_raw_log() %>% 
  clean_log_data()

log_data <- log_data_raw %>%
  summarise_log_data()
```

Note that the functions are able to automatically parse the parameters `params_list`, `numeric_params`, `num_folds`, and `num_models` from the raw log files. 

### Manual parameter settings

If you want, you can manually set them yourself, as shown in the example below:

```r
src_params_list <- c(
  "optimizers", "opt_recurrent_regs", "opt_kernel_regs", "opt_go_backwards",
  "opt_dropout_recurrent", "opt_dropout", "maxpool_size", "kernel_size",
  "gru_hidden_units", "filter_conv", "epochs", "batch_size", "activation_conv"
)
src_numeric_params <- c(
  "opt_dropout_recurrent", "opt_dropout", "maxpool_size", "kernel_size",
  "gru_hidden_units", "filter_conv", "epochs", "batch_size"
)
```

```r
log_data_raw <- src_file %>%
  read_raw_log(
    params_list = src_params_list, 
    numeric_params = src_numeric_params
  ) %>%
  clean_log_data()

log_data <- log_data_raw %>%
  tidyr::drop_na() %>%
  summarise_log_data(
    params_list = src_params_list,
    num_folds = 5, 
    num_models = 50
  )
```