#### NOTE [Go to the end](#sphx-glr-download-auto-examples-structure-analysis-plot-structure-analysis-py) to download the full example code. # Extract Synthesis Parameters This example demonstrates how to analyze the structure of a crosslinked polymer network to get the stoichiometric imbalance $r$, the crosslinker conversion $p$ or the functionality of the crosslinker $f$. ```none Stoichiometric imbalance (r): 1.16 Crosslinker conversion (p): 0.7241379310344828 Functionality of the crosslinker (f): 4 ```
```Python import os from pathlib import Path from collections import Counter import matplotlib.pyplot as plt from pylimer_tools.analyse_networks import ( compute_crosslinker_conversion, compute_stoichiometric_imbalance, ) from pylimer_tools.io.read_lammps_output_file import read_data_file from pylimer_tools_cpp import Universe # Replace with your crosslinker type crosslinker_type = 2 # Load your network (replace path accordingly) def _find_fixtures_dir() -> Path: for cur in ( [Path(__file__).resolve().parent] if "__file__" in globals() else [] ) + [Path.cwd()]: for p in [cur] + list(cur.parents): candidate = p / "tests" / "pylimer_tools" / "fixtures" if candidate.is_dir(): return candidate return Path("tests/pylimer_tools/fixtures").resolve() _fixtures_dir = _find_fixtures_dir() universe = read_data_file( str(_fixtures_dir / "structure/network_100_a_46.structure.out") ) assert isinstance(universe, Universe) # 1. Compute stoichiometric imbalance r = compute_stoichiometric_imbalance(universe, crosslinker_type) print(f"Stoichiometric imbalance (r): {r}") # 2. Compute crosslinker conversion p = compute_crosslinker_conversion(universe, crosslinker_type) print(f"Crosslinker conversion (p): {p}") # 3. Compute functionality of the crosslinker f = universe.determine_functionality_per_type()[crosslinker_type] print(f"Functionality of the crosslinker (f): {f}") # Count functionalities crosslinkers = universe.get_atoms_by_type(crosslinker_type) functionalities = universe.get_vertex_degrees() functionalities = [ functionalities[universe.get_vertex_idx_by_atom_id(a.get_id())] for a in crosslinkers ] functionality_counts = Counter(functionalities) # Plot the functionality counts plt.figure() plt.bar( [f"{k} ({v})" for k, v in functionality_counts.items()], list(functionality_counts.values()), ) plt.xlabel("Functionality") plt.ylabel("Count") plt.show() ``` **Total running time of the script:** (0 minutes 0.045 seconds) [`Download Jupyter notebook: plot_structure_analysis.ipynb`](_downloads/2d5803a363383a85865a76637ec3b117/plot_structure_analysis.ipynb) [`Download Python source code: plot_structure_analysis.py`](_downloads/4db712c424a7dc7c738c3614e4e732f3/plot_structure_analysis.py) [`Download zipped: plot_structure_analysis.zip`](_downloads/391a4c5bd12a1cc150e1e86e6c407978/plot_structure_analysis.zip) [Gallery generated by Sphinx-Gallery](https://sphinx-gallery.github.io)