ENH: Refactor code to name the package Pyseldonlib

.github/workflows/build_wheels.yml

@@ -20,7 +20,7 @@ jobs:
     outputs:
       message: ${{ steps.commit_message.outputs.message }}
     steps:
-      - name: Checkout pyseldon
+      - name: Checkout pyseldonlib
         uses: actions/checkout@v4
         # Gets the correct commit message for pull request
         with:

.pre-commit-config.yaml

@@ -9,4 +9,4 @@ repos:
     rev: v0.0.241
     hooks:
       - id: ruff
-        files: ^tests/|^pyseldon/
+        files: ^tests/|^pyseldonlib/

Project.md

@@ -1,6 +1,6 @@
-# PySeldon
-![pyseldon](https://raw.githubusercontent.com/User-DK/pyseldon/main/res/logotext.png)
-PySeldon is a Python Package for Opinion Dynamics Simulation, an extension of the [`Seldon Framework`](https://github.com/seldon-code/seldon). It provides:
+# PySeldonlib
+![pyseldonlib](https://raw.githubusercontent.com/User-DK/pyseldon/main/res/logotext.png)
+PySeldonlib is a Python Package for Opinion Dynamics Simulation, an extension of the [`Seldon Framework`](https://github.com/seldon-code/seldon). It provides:
 
 - Tools for the simulation of various Opinion Dynamics Models like the classical DeGroot Model, Deffuant Model, Activity Driven Model, etc.
 - Tools to create, manipulate, and study complex networks which are either randomly generated or provided by the user.
@@ -39,15 +39,15 @@ We can conclude that the agents have reached a consensus after the simulation.
 ### Usage
 
 ```python
-import pyseldon
+import pyseldonlib
 
 pyseldonlib.run_simulation_from_config_file(config_file_path = '/path/to/config/file')
 ```
 
 ```python
-import pyseldon
+import pyseldonlib
 
-model = pyseldon.DeGroot_Model(max_iterations=1000,
+model = pyseldonlib.DeGroot_Model(max_iterations=1000,
                                convergence_tol=1e-6,
                                rng_seed=120, 
                                other_settings=other_settings)

README.md

@@ -1,4 +1,4 @@
-# pyseldon
+# pyseldonlib
 ![](https://raw.githubusercontent.com/User-DK/pyseldon/main/res/logotext.png)
 
 ## Python bindings for the Seldon framework

bindings_package/__init__.py

@@ -1 +1 @@
-from pyseldon import seldoncore
+from pyseldonlib import seldoncore

docs/conf.py

@@ -1,9 +1,9 @@
 import os
 import sys
 
-sys.path.insert(0, os.path.abspath('../pyseldon'))
+sys.path.insert(0, os.path.abspath('../pyseldonlib'))
 
-project = 'pyseldon'
+project = 'pyseldonlib'
 copyright = '2024, PySeldon Developers'
 author = 'Amrita Goswami, Daivik Karbhari, Moritz Sallermann, Rohit Goswami'
 release = '1.0'
@@ -51,10 +51,10 @@
 html_theme_options = {
   "show_toc_level": 2,
     "icon_links": [
-        {"name": "Home Page", "url": "https://github.com/seldon-code/pyseldon", "icon": "fas fa-home"},
+        {"name": "Home Page", "url": "https://github.com/seldon-code/pyseldonlib", "icon": "fas fa-home"},
         {
             "name": "GitHub",
-            "url": "https://github.com/seldon-code/pyseldon",
+            "url": "https://github.com/seldon-code/pyseldonlib",
             "icon": "fab fa-github-square",
         },
     ],

docs/examples/degrootmodel.ipynb

@@ -20,7 +20,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import pyseldon\n",
+    "import pyseldonlib\n",
     "import pathlib\n",
     "import shutil"
    ]
@@ -38,7 +38,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "other_settings = pyseldon.Other_Settings(n_output_agents=10,\n",
+    "other_settings = pyseldonlib.Other_Settings(n_output_agents=10,\n",
     "                                         n_output_network= None, \n",
     "                                         print_progress= True, \n",
     "                                         output_initial=True, \n",
@@ -106,7 +106,7 @@
     }
    ],
    "source": [
-    "model = pyseldon.DeGroot_Model(max_iterations=1000,\n",
+    "model = pyseldonlib.DeGroot_Model(max_iterations=1000,\n",
     "                               convergence_tol=1e-6,\n",
     "                               rng_seed=120, \n",
     "                               other_settings=other_settings)\n",

docs/examples/network.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Example Usage of the Network Class from the pyseldon Package"
+    "# Example Usage of the Network Class from the pyseldonlib Package"
    ]
   },
   {
@@ -14,7 +14,7 @@
    "outputs": [],
    "source": [
     "# Import necessary modules\n",
-    "import pyseldon"
+    "import pyseldonlib"
    ]
   },
   {
@@ -24,7 +24,7 @@
    "outputs": [],
    "source": [
     "# Initialize the Network object\n",
-    "network = pyseldon.Network(\n",
+    "network = pyseldonlib.Network(\n",
     "    model_string=\"DeGroot\",\n",
     "    neighbour_list=[[1, 2], [0, 2], [0, 1], [4], [3]],\n",
     "    weight_list=[[0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [1], [1]],\n",

docs/index.rst

@@ -1,12 +1,12 @@
 .. image:: ../res/PySeldon_1.svg
    :align: left
    :width: 800px
-   :alt: PySeldon
+   :alt: PySeldonlib
 
-PySeldon Documentation
-=======================
+PySeldonlib Documentation
+=========================
 
-Welcome to the **PySeldon** Documentation. PySeldon is a Python Package for Opinion Dynamics Simulation, an extension of the `Seldon Framework <https://github.com/seldon-code/seldon>`_.
+Welcome to the **PySeldonlib** Documentation. PySeldonlib is a Python Package for Opinion Dynamics Simulation, an extension of the `Seldon Framework <https://github.com/seldon-code/seldon>`_.
 It provides:
 
 - tools for simulation of various Opinion Dynamics Models like the classical DeGroot Model, Deffuant Model, Activity Driven Model, etc.

docs/install.rst

@@ -7,7 +7,7 @@ You can install the package from PYPI using `pip`:
 
 .. code-block:: bash
 
-    $ pip install pyseldon
+    $ pip install pyseldonlib
 
 
 From Source

docs/quickstart.rst

@@ -1,7 +1,7 @@
 Quick Start Guide
 =================
 
-This guide will help you get started with the basics of using the `pyseldon` package.
+This guide will help you get started with the basics of using the `pyseldonlib` package.
 
 Installation
 ------------
@@ -16,9 +16,9 @@ Usage
 
 .. code-block:: python
 
-    import pyseldon
+    import pyseldonlib
 
-    pyseldon.run_simulation_from_config_file(
+    pyseldonlib.run_simulation_from_config_file(
         config_file_path="path/to/config.toml",
         agent_file_path="path/to/agent.csv",
         network_file_path="path/to/network.csv",

docs/source/reference/activitydriven.rst

@@ -1,7 +1,7 @@
 Activity Driven Model
 =====================
 
-.. automodule:: pyseldon.ActivityDrivenModel
+.. automodule:: pyseldonlib.ActivityDrivenModel
    :members: True
    :undoc-members: True
    :show-inheritance: True

docs/source/reference/deffuant.rst

@@ -1,7 +1,7 @@
 Deffuant Model
 ==============
 
-.. automodule:: pyseldon.DeffuantModel
+.. automodule:: pyseldonlib.DeffuantModel
    :members: True
    :undoc-members: True
    :show-inheritance: True

docs/source/reference/deffuantvector.rst

@@ -1,7 +1,7 @@
 Deffuant Vector Model
 ======================
 
-.. automodule:: pyseldon.DeffuantVectorModel
+.. automodule:: pyseldonlib.DeffuantVectorModel
    :members: True
    :undoc-members: True
    :show-inheritance: True

docs/source/reference/degroot.rst

@@ -1,7 +1,7 @@
 DeGroot Model
 =============
 
-.. automodule:: pyseldon.DeGrootModel
+.. automodule:: pyseldonlib.DeGrootModel
    :members: True
    :undoc-members: True
    :show-inheritance: True

docs/source/reference/index.rst

@@ -9,4 +9,5 @@ This is the class and function reference of PySeldon.
     introduction
     models
     network
+    util
     packagereference

docs/source/reference/inertial.rst

@@ -1,7 +1,7 @@
 Activity Driven Inertial Model
 ==============================
 
-.. automodule:: pyseldon.InertialModel
+.. automodule:: pyseldonlib.InertialModel
    :members: True
    :undoc-members: True
    :show-inheritance: True

docs/source/reference/models.rst

@@ -1,6 +1,6 @@
 Models
 ======
-The following models are available in the `pyseldon` package:
+The following models are available in the `pyseldonlib` package:
 
 ..  toctree::
     :maxdepth: 4

docs/source/reference/network.rst

@@ -1,7 +1,7 @@
 network
 =======
 
-.. automodule:: pyseldon.network
+.. automodule:: pyseldonlib.network
    :members: True
    :undoc-members: True
    :show-inheritance: True

docs/source/reference/packagereference.rst

@@ -1,7 +1,7 @@
 Complete Api Reference
 ======================
 
-.. automodule:: pyseldon.__init__
+.. automodule:: pyseldonlib.__init__
    :members: True
    :undoc-members: True
    :show-inheritance: True

docs/source/reference/util.rst

@@ -0,0 +1,8 @@
+util
+====
+
+.. automodule:: pyseldonlib.utils
+   :members: True
+   :undoc-members: True
+   :show-inheritance: True
+   :inherited-members: True

meson.build

@@ -1,4 +1,4 @@
-project('pyseldon', 'cpp', 
+project('pyseldonlib', 'cpp', 
     version: '1.0.0',
     default_options: ['cpp_std=c++20', 'warning_level=3'])
 
@@ -32,17 +32,19 @@ py.extension_module(
 
 py.install_sources(
    [
-    'pyseldon/__init__.py',
-    'pyseldon/_basemodel.py',
-    'pyseldon/DeGrootModel.py',
-    'pyseldon/DeffuantModel.py',
-    'pyseldon/DeffuantVectorModel.py',
-    'pyseldon/ActivityDrivenModel.py',
-    'pyseldon/InertialModel.py',
-    'pyseldon/network.py',
-    'pyseldon/_othersettings.py',
-    'pyseldon/_run_simulation.py',
+    'pyseldonlib/__init__.py',
+    'pyseldonlib/_basemodel.py',
+    'pyseldonlib/DeGrootModel.py',
+    'pyseldonlib/DeffuantModel.py',
+    'pyseldonlib/DeffuantVectorModel.py',
+    'pyseldonlib/ActivityDrivenModel.py',
+    'pyseldonlib/InertialModel.py',
+    'pyseldonlib/network.py',
+    'pyseldonlib/_othersettings.py',
+    'pyseldonlib/_run_simulation.py',
+    'pyseldonlib/utils.py',
+
   ],
   pure: false, # do not install next to compiled extension
-  subdir: 'pyseldon'
+  subdir: 'pyseldonlib'
 )

pyproject.toml

@@ -39,8 +39,8 @@ classifiers = [
 ]
 
 [project.urls]
-"Source Code" = "https://github.com/seldon-code/pyseldon"
-Documentation = "https://seldon-code.github.io/pyseldon"
+"Source Code" = "https://github.com/seldon-code/pyseldonlib"
+Documentation = "https://seldon-code.github.io/pyseldonlib/"
 
 [build-system]
 requires = ["pybind11","meson-python","setuptools>=42", "wheel", "setuptools_scm"]

pyseldon/ActivityDrivenModel.py → pyseldonlib/ActivityDrivenModel.py

@@ -9,7 +9,6 @@
 
 Temporal Dynamics
 -----------------
-
 max_iterations:
     Limits the total number of simulation steps.
     If set to None, the model runs indefinitely, allowing for long-term analysis of opinion evolution.
@@ -20,7 +19,6 @@
 
 Agent Behavior and Interaction
 ------------------------------
-
 m:
     Determines how many agents an active agent interacts with during each time step.
     Influences the rate of opinion spreading; higher values mean more interactions and potentially faster consensus or polarization.
@@ -47,14 +45,12 @@
 
 Social Context and Controversialness
 ------------------------------------
-
 alpha:
     Controls the degree of controversialness of the issue being simulated.
     A higher alpha can lead to more polarized opinions, as agents might have stronger reactions to the issue.
 
 Bots and External Influence
 ---------------------------
-
 n_bots:
     Specifies the number of bots in the simulation, which are fixed in their opinions.
     Bots influence the network without being influenced, potentially driving opinion shifts or reinforcing certain views.
@@ -65,7 +61,6 @@
 
 Reluctance and Activity Correlation
 -----------------------------------
-
 use_reluctances:
     Activates the feature where agents have a reluctance to change their opinions.
     Adds complexity by simulating resistance to change, affecting how quickly or slowly opinions evolve.
@@ -80,7 +75,7 @@
 
 Example:
 ---------
->>> from pyseldon import Activity_Driven_Model
+>>> from pyseldonlib import Activity_Driven_Model
 >>> # Create the Activity Driven Model
 >>> model = Activity_Driven_Model(max_iterations=1000, convergence_tol=1e-6)
 >>> # Run the simulation

pyseldon/DeGrootModel.py → pyseldonlib/DeGrootModel.py

@@ -7,7 +7,6 @@
 
 Key features
 ------------
-
 Opinion Averaging:
   Agents update their opinions based on the average opinions of their neighbors, fostering convergence and consensus.
 
@@ -21,7 +20,7 @@
 
 Example:
 ---------
->>> from pyseldon import DeGroot_Model
+>>> from pyseldonlib import DeGroot_Model
 >>> # Create the DeGroot Model
 >>> model = DeGroot_Model(max_iterations=1000, convergence_tol=1e-6)
 >>> # Run the simulation

pyseldon/DeffuantModel.py → pyseldonlib/DeffuantModel.py

@@ -3,7 +3,6 @@
 
 Model Dynamics
 --------------
-
 Homophily Threshold:
   If the difference in opinions between two interacting agents is less than this threshold, they will update their opinions towards each other. This process leads to opinion convergence or clustering depending on the value of the threshold.
 
@@ -15,7 +14,7 @@
 
 Example:
 ---------
->>> from pyseldon import Deffuant_Model
+>>> from pyseldonlib import Deffuant_Model
 >>> # Create the Deffuant Model
 >>> deffuant = Deffuant_Model(max_iterations=1000, homophily_threshold=0.2, mu=0.5)
 >>> # Run the simulation