ENH: Remove Notebooks

docs/conf.py

@@ -16,7 +16,7 @@
     'sphinx.ext.autosummary',
     'sphinx.ext.viewcode',
     'sphinx.ext.coverage',
-    'nbsphinx',
+    # 'nbsphinx',
     'sphinxcontrib.bibtex',
     'myst_nb',
     'sphinx_copybutton',
@@ -26,7 +26,8 @@
 bibtex_bibfiles = [
   'refs.bib',
   ]
-nbsphinx_execute = 'never'
+
+jupyter_execute_notebooks = "auto"
 autosummary_generate = True
 numpydoc_show_class_members = False 
 

docs/examples/degrootmodel.md

@@ -0,0 +1,52 @@
+---
+jupytext:
+  text_representation:
+    extension: .md
+    format_name: myst
+    format_version: 0.13
+    jupytext_version: 1.16.4
+kernelspec:
+  display_name: Python 3
+  language: python
+  name: python3
+---
+
+# DeGroot Model (Reaching Consensus)
+
++++
+
+Import the packages
+
+```{code-cell} ipython3
+import pyseldonlib
+import pathlib
+import shutil
+```
+
+Initialize some other settings for the simulation
+
+```{code-cell} ipython3
+other_settings = pyseldonlib.Other_Settings(n_output_agents=10,
+                                         n_output_network= None, 
+                                         print_progress= True, 
+                                         output_initial=True, 
+                                         start_output=1, 
+                                         number_of_agents = 200, 
+                                         connections_per_agent = 10)
+```
+
+Initialize the model with parameters.
+
+```{code-cell} ipython3
+model = pyseldonlib.DeGroot_Model(max_iterations=1000,
+                               convergence_tol=1e-6,
+                               rng_seed=120, 
+                               other_settings=other_settings)
+output_dir_path = str("./output")
+if pathlib.Path(output_dir_path).exists():
+  shutil.rmtree(output_dir_path)
+model.run(output_dir_path)
+if pathlib.Path(output_dir_path).exists():
+  shutil.rmtree(output_dir_path)
+```
+### On your local machine you can see a C++ std::out

docs/examples/network.md

@@ -0,0 +1,38 @@
+---
+jupytext:
+  text_representation:
+    extension: .md
+    format_name: myst
+    format_version: 0.13
+    jupytext_version: 1.16.4
+kernelspec:
+  display_name: Python 3
+  language: python
+  name: python3
+---
+
+# Example Usage of the Network Class from the pyseldonlib Package
+
+```{code-cell} ipython3
+# Import necessary modules
+import pyseldonlib
+```
+
+```{code-cell} ipython3
+# Initialize the Network object
+network = pyseldonlib.Network(
+    model_string="DeGroot",
+    neighbour_list=[[1, 2], [0, 2], [0, 1], [4], [3]],
+    weight_list=[[0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [1], [1]],
+    direction="Incoming"
+)
+```
+
+```{code-cell} ipython3
+# Print the network details
+print(f"Number of agents: {network.n_agents}")
+print(f"Edges of 1st index agent: {network.n_edges(1)}")
+print(f"Direction: {network.get_direction}")
+print(f"Neighbour List: {network.get_neighbours(1)}")
+print(f"Weight List: {network.get_weights(1)}")
+```

visualisations/cytoscapenormalisation.py

@@ -20,5 +20,4 @@
         for target, weight in zip(indices_neighbours, weights):
             writer.writerow([idx_agent, target.strip(), weight.strip()])
 
-print("Edge list saved to edges.csv")
-
+print("Edge list saved to edges.csv")