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HPAC · Jun 17, 2024 · 48e8262 · 48e8262
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diff --git a/.github/workflows/pages.yml b/.github/workflows/pages.yml
@@ -28,7 +28,7 @@ jobs:
 
     - name: Build Sphinx documentation
       run: |
-        sudo apt-get install pandoc
+        sudo apt-get install -y pandoc
         cd docs
         ./sync_notebooks.sh
         ./autoapidoc.sh

diff --git a/README.md b/README.md
@@ -1,6 +1,6 @@
 # Partial Ranker
 
-Partial Ranker is a library that implements methodologies for ranking a given set of objects with a *strict partial order* relation. Full documentations can be found here (TODO:Add link).
+Partial Ranker is a library that implements methodologies for ranking a given set of objects that have a *strict partial order* relation. The Full documentations can be found [here](https://hpac.github.io/PartialRanker/).
 
 **Input**:
 
@@ -34,7 +34,7 @@ pip install git+https://github.com/HPAC/PartialRanker
 ```
 ## Examples
 
-For usage and application examples, please follow the jupyter notebooks under the folder ``examples/``.
+Details on the usage and application examples can be found [here](https://hpac.github.io/PartialRanker/notebooks-usage/01U_Usage.html). For a hands-on experience, please follow the jupyter notebooks under the folder ``examples/``.
 
 ## Reference
 
@@ -47,4 +47,8 @@ More details on partial ranking, the methodologies and applications can be found
   journal={arXiv preprint arXiv:2405.18259},
   year={2024}
 }
-```
+```
+
+## Acknowledgement
+
+Financial support from the Deutsche Forschungsgemeinschaft (German Research Foundation) through grants GSC 111 and IRTG 2379 is gratefully acknowledged.
diff --git a/docs/source/README.md b/docs/source/README.md
@@ -1,12 +1,12 @@
 ### Partial Ranker
 
-Partial Ranker is a library that implements methodologies for ranking a given set of objects with a *strict partial order* relation. 
+Partial Ranker is a library that implements methodologies for ranking a given set of objects that have a *strict partial order* relation. For details on Partial Ranking and its methodologies, refer to [this paper](https://arxiv.org/abs/2405.18259).
 
-**INPUT**:
+**Input**:
 
 At the moment, we support only vector objects as input. An example for a set of vector objects would be:
 
-```json
+```
 objects = {
     't0' : [0.1, 0.12, 0.11, 0.13 ],
     't1' : [0.10, 0.13, 0.10 ],
@@ -16,16 +16,27 @@ objects = {
 ```
 The *better-than relation* between a pair of objects with which the partial order is formed is implemented in the library. At the moment, we support better-than relation based on comparisons of the Inter-Quantile-Intervals of the objects.
 
-**OUTPUT**:
+**Output**:
 
 The output is an *ordered set partition* of the objects into ranks. For example:
 
-```json
+```
 Rank 0: ['t0', 't1'],
 Rank 1: ['t2']
 ```
 
-#### Reference
+## Installation
+
+Partial Ranker requires Python>=3.6 and can be installed using the command:
+
+```bash
+pip install git+https://github.com/HPAC/PartialRanker
+```
+## Examples
+
+For a hands-on experience, please clone the github repo ```https://github.com/HPAC/PartialRanker.git``` and follow the jupyter notebooks under the folder ``examples/``.
+
+## Cite
 
 More details on partial ranking, the methodologies and applications can be found in [this paper](https://arxiv.org/abs/2405.18259). If you are using this library, please cite:
 
@@ -36,4 +47,8 @@ More details on partial ranking, the methodologies and applications can be found
   journal={arXiv preprint arXiv:2405.18259},
   year={2024}
 }
-```
+```
+
+## Acknowledgement
+
+Financial support from the Deutsche Forschungsgemeinschaft (German Research Foundation) through grants GSC 111 and IRTG 2379 is gratefully acknowledged.
diff --git a/docs/source/_templates/breadcrumbs.html b/docs/source/_templates/breadcrumbs.html
@@ -0,0 +1,7 @@
+{% extends "!breadcrumbs.html" %}
+
+{% block breadcrumbs_aside %}
+  <li class="wy-breadcrumbs-aside">
+    <a href="{{ github_url }}" class="fa fa-github" target="_blank"> Click here for source code</a>
+  </li>
+{% endblock %}
diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -11,9 +11,9 @@
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information
 
 project = 'Partial Ranker'
-copyright = '2024, Aravind Sankaran'
+copyright = '2024, HPAC Group, RWTH Aachen and Umeå University'
 author = 'Aravind Sankaran'
-release = '0.2'
+version = '1.0.0'
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
@@ -45,6 +45,11 @@
     'sticky_navigation': False,
 }
 
+html_context = {
+    'display_github': True,
+    'github_url': 'https://github.com/HPAC/PartialRanker/tree/main',
+}
+
 # pip install git+https://github.com/bashtage/sphinx-material.git
 #html_theme = 'sphinx_material'
 

diff --git a/docs/source/index.md b/docs/source/index.md
@@ -13,13 +13,13 @@
 
 Installation <Installation>
 Usage <notebooks-usage/01U_Usage>
-Examples <notebooks-usage/index>
+Methodologies <notebooks-usage/index>
 Applications <notebooks-applications/index>
 API Reference <api/partial_ranker>
 ```
 
-## Indices and tables
+<!-- ## Indices and tables
 
 - {ref}`genindex`
 - {ref}`modindex`
-- {ref}`search`
+- {ref}`search` -->
diff --git a/docs/source/notebooks-usage/index.md b/docs/source/notebooks-usage/index.md
@@ -1,4 +1,4 @@
-## Examples
+## Methodologies
 
 ```{toctree}
 :maxdepth: 1

diff --git a/examples/01U_Usage.ipynb b/examples/01U_Usage.ipynb
@@ -11,23 +11,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The required **input** to use this library is a set of objects, each with a set of scalar values, represented as a dictionary. For example:\n",
-    "\n",
-    "```json\n",
-    "measurements = {\n",
-    "    't0' : [0.13, 0.21, 0.18, 0.12 ],\n",
-    "    't1' : [0.30, 0.33, 0.28 ],\n",
-    "    't1' : [0.32, 0.31, 0.38, 0.32, 0.37, 0.32 ],\n",
-    "    ...\n",
-    "}\n",
-    "```"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "For the purpose of demonstration, we simulate the measurement values by sampling from normal distribution. To this end, the module ``MeasurementsSimulator`` can be used. In the following example, we create 4 objects with measurements simulated from two normal distributions differing in mean and standard deviation."
+    "The required **input** to use this library is a set of objects, each with a set of scalar values, represented as a dictionary. For the purpose of demonstration, we simulate the measurement values by sampling from normal distribution. To this end, the module ``MeasurementsSimulator`` can be used. In the following example, we create 4 objects with measurements simulated from two normal distributions differing in mean and standard deviation."
    ]
   },
   {

diff --git a/examples/06A_RootCause_GLS.ipynb b/examples/06A_RootCause_GLS.ipynb
@@ -278,7 +278,7 @@
    "source": [
     "We consolidate the execution times of the shortlisted algorithms from all the repetitions and prepare the measurement data in the following format:\n",
     "\n",
-    "```json\n",
+    "```\n",
     "measurements = {\n",
     "    'algorithm2': [0.025, 0.024, ..., ],\n",
     "    'algorithm8': [0.023, 0.024, ..., ],\n",

diff --git a/examples/07A_RootCause_BPI.ipynb b/examples/07A_RootCause_BPI.ipynb
@@ -183,7 +183,7 @@
    "source": [
     "Each variant is assigned a unique ID. We then identify the variants that were observed in more than 100 cases, and prepare the durations data in the following format:\n",
     "\n",
-    "```json\n",
+    "```\n",
     "durations = {\n",
     "    0: [42032,76321,...],\n",
     "    1: [65434, 23432, ...],\n",