Functions for the construction of Petri Nets. Petri Nets can be replayed by firing enabled transitions. Silent transitions will be hidden by the execution handler. Also includes functionalities for the visualization of Petri Nets and export of Petri Nets to PNML-files.
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Original issue:
gertjanssenswillen/petrinetR#3
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.
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
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!
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
Final marking
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