Updated figures and README

README.md

@@ -5,6 +5,7 @@
 [![Coverage
 Status](https://img.shields.io/codecov/c/github/MI2DataLab/modelDown/master.svg)](https://codecov.io/github/MI2DataLab/modelDown?branch=master)
 
+<a href="https://github.com/MI2DataLab/modelDown"><img src="misc/modelDownSticker.png" alt="" align="right" width="200px"/></a>
 
 `modelDown` generates a website with HTML summaries for predictive models.
 Is uses [DALEX](https://github.com/pbiecek/DALEX) explainers to compute and plot summaries of how given models behave.  We can see how well models behave (Model Performance, Auditor), how much each variable contributes to predictions (Variable Response) and which variables are the most important for a given model (Variable Importance). We can also compare Concept Drift for pairs of models (Drifter). Additionally, data available on the website can be easily recreated in current R session (using `archivist` package).
@@ -19,13 +20,13 @@ Do you want to start right now ? Check out our [getting started](https://mi2data
 
 ## Index page
 
-<center><img width="600" src="https://raw.githubusercontent.com/MI2DataLab/modelDown/master/misc/index.png"></center>
+<center><img width="600" src="misc/index.png"></center>
 
 Index page presents basic information about data provided in explainers. You can also see types of all explainers given as parameters. Additionally, summary statistics are available for numerical variables. For categorical variables, tables with frequencies of factor levels are presented.
 
 ## Auditor
 
-<center><img width="600" src="https://raw.githubusercontent.com/MI2DataLab/modelDown/master/misc/auditor.png"></center>
+<center><img width="600" src="misc/auditor.png"></center>
 
 Module shows plots generated by `auditor` package. 
 
@@ -35,19 +36,19 @@ Results of `drifter` package are displayed in this tab. In order to see the comp
 
 ## Model Performance
 
-<center><img width="600" src="https://raw.githubusercontent.com/MI2DataLab/modelDown/master/misc/performance.png"></center>
+<center><img width="600" src="misc/performance.png"></center>
 
 Module shows result of function `model_performance`. 
 
 ## Variable Importance
 
-<center><img width="600" src="https://raw.githubusercontent.com/MI2DataLab/modelDown/master/misc/importance.png"></center>
+<center><img width="600" src="misc/importance.png"></center>
 
 Output of function `variable_importance` is presented in form of a plot as well as a table.
 
 ## Variable Response
 
-<center><img width="600" src="https://raw.githubusercontent.com/MI2DataLab/modelDown/master/misc/response.png"></center>
+<center><img width="600" src="misc/response.png"></center>
 
 For each variable, plot is created by using function `variable_response`. Plots can be easily navigated using links on the left side. One can provide names of variables to include in the module with argument `vr.vars` (if argument is not used, plots for all variables of first explainer are generated).
 
@@ -56,4 +57,5 @@ For each variable, plot is created by using function `variable_response`. Plots
 In each tab you can find links with R commands. If you execute them, you can load relevant objects into current R session (`archivist` package is necessary). By default data is stored and loaded from local repository. If you wish to store data on GitHub repository, please provide argument `remote_repository_path`. After generating modelDown website, `repository` folder must be placed under this path.
 
 ## Acknowledgments 
+
 Work on this package is financially supported by Warsaw University of Technology, Faculty of Mathematics and Information Science.

_pkgdown.yml

@@ -0,0 +1,3 @@
+template:
+  package: DrWhyTemplate
+  default_assets: false