bupaverse / petrinetr

bupaverse

The bupaverse is an open-source, integrated suite of R-packages for handling and analysing business process data, developed by the Business Informatics research group at Hasselt University, Belgium. Profoundly inspired by the tidyverse package, the bupaverse package is designed to facilitate the installation and loading of multiple bupaverse packages in a single step. Learn more about bupaverse at the bupaR.net homepage.

Installation

You can install bupaverse from CRAN with:

install.packages("bupaverse")

Development Version

You can install the development version of bupaverse from GitHub with:

# install.packages("devtools")
devtools::install_github("bupaverse/bupaverse")

Usage

library(bupaverse) will load the core bupaverse packages:

• bupaR: Core package for business process analysis.
• edeaR: Exploratory and descriptive analysis of event-based data.
• eventdataR: Repository of sample process data.
• processcheckR: Rule-based conformance checking and filtering.
• processmapR: Visualise event-based data using, i.a., process maps.

An overview of the loaded packages and conflicts with other packages is shown after loading bupaverse:

library(bupaverse)
#> 
#> .______    __    __  .______      ___   ____    ____  _______ .______          _______. _______
#> |   _  \  |  |  |  | |   _  \    /   \  \   \  /   / |   ____||   _  \        /       ||   ____|
#> |  |_)  | |  |  |  | |  |_)  |  /  ^  \  \   \/   /  |  |__   |  |_)  |      |   (----`|  |__
#> |   _  <  |  |  |  | |   ___/  /  /_\  \  \      /   |   __|  |      /        \   \    |   __|
#> |  |_)  | |  `--'  | |  |     /  _____  \  \    /    |  |____ |  |\  \----.----)   |   |  |____
#> |______/   \______/  | _|    /__/     \__\  \__/     |_______|| _| `._____|_______/    |_______|
#>                                                                                                 
#> ── Attaching packages ─────────────────────────────────────── bupaverse 0.1.0 ──
#> ✔ bupaR         0.5.2     ✔ processcheckR 0.2.0
#> ✔ edeaR         0.9.1     ✔ processmapR   0.5.2
#> ✔ eventdataR    0.3.1     
#> ── Conflicts ────────────────────────────────────────── bupaverse_conflicts() ──
#> ✖ bupaR::filter()          masks stats::filter()
#> ✖ processmapR::frequency() masks stats::frequency()
#> ✖ edeaR::setdiff()         masks base::setdiff()
#> ✖ bupaR::timestamp()       masks utils::timestamp()
#> ✖ processcheckR::xor()     masks base::xor()

petrinetr's Issues

Installation of Petrinet & pm4py

I have problems in install and using this library. Cannot understand what could be the issue.
The problems is more related to pm4py. I have both miniconda and anaconda installed. Can you explain the steps for a person who is first time installing with any version of Python in their system.
Because of this unable to perform an important part of PM. Some video tutorial will also help.
Thanks. Dhiraj

Duplicate labels

Original issue:
gertjanssenswillen/petrinetR#3

Error reading in pnml file with petrinetR::read_pnml

@gertjanssenswillen Due to various reasons I can't use the graphical toolset of pm4py to visualize my petrinet. Therefore as alternative, I tried petrinetR to read and render the pnml file I exported with pm4py.

I tried loading the file with read_PN as follows:

> pn_file_name <- "PetriNet_simult.pnml"
> pn <- read_PN(paste0(output_dir, pn_file_name))

However, this resulted in the following error:

x Column `node` is a `xml_nodeset` object.
Run `rlang::last_error()` to see where the error occurred.

> rlang::last_error()
<error/tibble_error_column_scalar_type>
All columns in a tibble must be vectors.
x Column `node` is a `xml_nodeset` object.
Backtrace:
 1. petrinetR::read_PN(paste0(output_dir, pn_dir))
 5. tibble::data_frame(node = t)
 6. tibble::tibble(!!!quos(...))
 7. tibble:::tibble_quos(xs[!is.null], .rows, .name_repair)
 8. tibble:::check_valid_col(res, col_names[[j]], j)
 9. tibble:::check_valid_cols(set_names(list(x), name))
Run `rlang::last_trace()` to see the full context.

> rlang::last_trace()
<error/tibble_error_column_scalar_type>
All columns in a tibble must be vectors.
x Column `node` is a `xml_nodeset` object.
Backtrace:
    x
 1. \-petrinetR::read_PN(paste0(output_dir, pn_dir))
 2.   +-`%>%`(...)
 3.   | \-base::eval(lhs, parent, parent)
 4.   |   \-base::eval(lhs, parent, parent)
 5.   \-tibble::data_frame(node = t)
 6.     \-tibble::tibble(!!!quos(...))
 7.       \-tibble:::tibble_quos(xs[!is.null], .rows, .name_repair)
 8.         \-tibble:::check_valid_col(res, col_names[[j]], j)
 9.           \-tibble:::check_valid_cols(set_names(list(x), name))

I know it would be much easier to try to visualize the net directly in R with bupaR, however I turned to pm4py to try the inductive miner alternative algorithms which aren't installed in the R pm4py package or bupaR.

Any help is appreciated!

Woped saved PNML file does not have `page` element

I tried loading a PNML file saved by WopeD (https://woped.dhbw-karlsruhe.de/) and it failed in current petrinetR. The excepted page element is missing from the XML.

Final marking

gertjanssenswillen/petrinetR#2

Visible/invisible labels

gertjanssenswillen/petrinetR#4

IDs displayed instead of labels

I was able to get the simple example to run without issues except for the final render_PN call. The resulting graph displayed IDs instead of Labels

the transitions look like this... much different than the example
pn$petrinet$transitions
id label
1 skip_3
2 5206b1ce-0f6a-477b-907d-f462eb0480eb Blood test
3 ba589911-7d60-4a96-b627-0d2beb09534f Triage and Assessment
4 b6941ed6-e77c-40a3-ac2a-7d0b4d9a3dc7 MRI SCAN
5 071a9c6f-8b27-4953-9208-810775afcd9f Discuss Results
6 bc6bc5b0-bca2-43a4-8d7d-70c5c8fe8435 X-Ray
7 0cd8379a-d82b-49a6-b6a4-02141e55be75 Registration
8 878cb56a-9c24-412d-a59b-f7064827fb48 Check-out
9 skip_2
10 skip_1