ProcessGraph 1.26

Connecting Process Network Synthesis (PNS) to Modern Programming Ecosystems

Pgraph : Process Graphs for Process Network Synthesis (PNS)

Table of Contents

• About the Project
• Getting Started
• Usage Examples
• Contributing
• License
• Contact
• References

About The Project

This project aims at enabling the classical P-graph Framework (www.p-graph.org) to interface with modern Python programming ecosystems. The backend solver is the original executable from P-graph, staying true to the original implementation of P-graph. For manual network manipulation, the P-graph studio can be downloaded from this link: https://p-graph.org/downloads/.

Changelog

14/11/2024: Due to update of P-graph studio, mutual exclusion is not properly processed. This is now fixed. Custom solvers can now also be selected for advanced users.

18/10/2024: Due to update of networkx draw, older versions of Pgraph crashes when it draws the graph. This has now been fixed. Users now need to adjust axis size themselves.

Getting Started

Install this library either from the official PyPI or from this Github repository:

Install a Stable Version (PyPI)

pip install ProcessGraph

Install most updated version from Github

In a environment terminal or CMD:

pip install git+https://github.com/tsyet12/Pgraph

Usage Examples

See examples for all code examples.

Simple Example

from Pgraph.Pgraph import Pgraph #This is our Pgraph library
import networkx as nx
import matplotlib.pyplot as plt
##### STEP 1 : Problem Specification ######
G = nx.DiGraph()
G.add_node("M1",names="Product D",type='product',flow_rate_lower_bound=100, flow_rate_upper_bound=100)
G.add_node("M2",names="Chemical A",type='raw_material',price=200,flow_rate_lower_bound=0)
G.add_node("M3",names="Chemical B", type='raw_material',price=100,flow_rate_lower_bound=0)
G.add_node("M4",names="Chemical C", type='raw_material',price=10,flow_rate_lower_bound=0)
G.add_node("O1",names="Reactor 1",fix_cost=2000, proportional_cost=400)
G.add_node("O2", names="Reactor 2",fix_cost=1000, proportional_cost=400)
G.add_edge("M2","O1", weight = 1)
G.add_edge("M3","O2", weight = 1)
G.add_edge("M4","O2", weight = 2)
G.add_edge("O1","M1", weight = 0.7) 
G.add_edge("O2","M1", weight = 0.9) 
ME=[["O1","O2"]]  #Reactor 1 and Reactor 2 are mutually excluded. Only one can be chosen as solution.

#### Step 2:  Setup Solver ####
P=Pgraph(problem_network=G, mutual_exclusion=ME, solver="INSIDEOUT",max_sol=100)

#### Step 2.1:  Plot Problem #####
ax1=P.plot_problem(figsize=(5,5))
ax1.set_xlim(0,200)
plt.show()
##################################

#### Step 3: Run ####
P.run()
#### Step 3.1: Plot Solution########
total_sol_num=P.get_sol_num() 
for i in range(total_sol_num): # Here we loop through all the solutions to plot everything
    ax=P.plot_solution(sol_num=i) #Plot Solution Function
    ax.set_xlim(0,200)
    plt.show()

#### Step 3.2: Export to P-graph Studio ####
from google.colab import files #This is only for google colab
string = P.to_studio(path='./',verbose=False) #export to p-graph studio
files.download("./studio_file.pgsx") #download for google colab
#Note: Please be reminded to press "Generate Layout" button in P-graph Studio after opening

Press "Generate Layout" Button:

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b testbranch/prep)
3. Commit your Changes (git commit -m 'Improve testbranch/prep')
4. Push to the Branch (git push origin testbranch/prep)
5. Open a Pull Request

License

Distributed under the Open Sourced BSD-2-Clause License. See LICENSE for more information.

Contact

Main Developer:

Sin Yong Teng [e-mail] or [e-mail] Radboud University Nijmegen

References

Teng, S.Y., Orosz, Á., How, B.S., Pimentel, J., Friedler, F. and Jansen, J.J., 2022. Framework to Embed Machine Learning Algorithms in P-graph: Communication from the Chemical Process Perspectives. Chemical Engineering Research and Design. (Paper explaining the software)

Friedler, F., Tarjan, K., Huang, Y.W. and Fan, L.T., 1992. Graph-theoretic approach to process synthesis: axioms and theorems. Chemical Engineering Science, 47(8), pp.1973-1988.

Friedler, F., Tarjan, K., Huang, Y.W. and Fan, L.T., 1992. Combinatorial algorithms for process synthesis. Computers & chemical engineering, 16, pp.S313-S320.

Friedler, F., Tarjan, K., Huang, Y.W. and Fan, L.T., 1993. Graph-theoretic approach to process synthesis: polynomial algorithm for maximal structure generation. Computers & Chemical Engineering, 17(9), pp.929-942.

Acknowledgements

The research contribution from S.Y. Teng is supported by the European Union's Horizon Europe Research and Innovation Program, under Marie Skłodowska-Curie Actions grant agreement no. 101064585 (MoCEGS).

How to cite this software

S.Y. Teng (2022). tsyet12/Pgraph: Process Graphs for Process Network Synthesis (PNS), Zenodo Release 2 (v1.0-zenodo-2). Zenodo. https://doi.org/10.5281/zenodo.6778354