docs: document all functions

README.md

@@ -65,15 +65,19 @@ writing Python code:
 python -m gen_surv dataset aft_ln --n 100 > data.csv
 ```
 
-## 🔧 Available Generators
-
-| Function     | Description                                |
-|--------------|--------------------------------------------|
-| `gen_cphm()` | Cox Proportional Hazards Model             |
-| `gen_cmm()`  | Continuous-Time Multi-State Markov Model   |
-| `gen_tdcm()` | Time-Dependent Covariate Model             |
-| `gen_thmm()` | Time-Homogeneous Markov Model              |
-| `gen_aft_log_normal()` | Accelerated Failure Time Log-Normal  |
+## 🔧 API Overview
+
+| Function | Description |
+|----------|-------------|
+| `generate()` | Unified interface that calls any generator |
+| `gen_cphm()` | Cox Proportional Hazards Model |
+| `gen_cmm()`  | Continuous-Time Multi-State Markov Model |
+| `gen_tdcm()` | Time-Dependent Covariate Model |
+| `gen_thmm()` | Time-Homogeneous Markov Model |
+| `gen_aft_log_normal()` | Accelerated Failure Time Log-Normal |
+| `sample_bivariate_distribution()` | Sample correlated Weibull or exponential times |
+| `runifcens()` | Generate uniform censoring times |
+| `rexpocens()` | Generate exponential censoring times |
 
 
 ```text

docs/source/conf.py

@@ -22,8 +22,11 @@
     "sphinx.ext.napoleon",
     "myst_parser",
     "sphinx.ext.viewcode",
+    "sphinx.ext.autosectionlabel",
 ]
 
+autosectionlabel_prefix_document = True
+
 # Point to index.md or index.rst as the root document
 master_doc = "index"
 
@@ -36,3 +39,4 @@
 html_theme = 'alabaster'
 html_static_path = ['_static']
 
+

docs/source/index.md

@@ -10,14 +10,21 @@ It includes generators for:
 - **Time-Homogeneous Hidden Markov Models (THMM)**
 - **Accelerated Failure Time (AFT) Log-Normal Models**
 
+Key functions include `generate()`, `gen_cphm()`, `gen_cmm()`, `gen_tdcm()`,
+`gen_thmm()`, `gen_aft_log_normal()`, `sample_bivariate_distribution()`,
+`runifcens()`, and `rexpocens()`.
+
 ---
 
+See the [Getting Started](usage) guide for installation instructions.
+
 ## 📚 Modules
 
 ```{toctree}
 :maxdepth: 2
 :caption: Contents
 
+usage
 modules
 theory
 ```
@@ -77,6 +84,7 @@ genSurvPy/
 - [License](https://github.com/DiogoRibeiro7/genSurvPy/blob/main/LICENCE)
 - [Code of Conduct](https://github.com/DiogoRibeiro7/genSurvPy/blob/main/CODE_OF_CONDUCT.md)
 
+
 ## Citation
 
 If you use **gen_surv** in your work, please cite it using the metadata in
@@ -89,3 +97,4 @@ If you use **gen_surv** in your work, please cite it using the metadata in
 - ORCID: <https://orcid.org/0009-0001-2022-7072>
 - Professional email: <[email protected]>
 - Personal email: <[email protected]>
+

docs/source/modules.md

@@ -29,3 +29,23 @@
     options:
       members: true
       undoc-members: true
+
+::: gen_surv.bivariate
+    options:
+      members: true
+      undoc-members: true
+
+::: gen_surv.censoring
+    options:
+      members: true
+      undoc-members: true
+
+::: gen_surv.cli
+    options:
+      members: true
+      undoc-members: true
+
+::: gen_surv.validate
+    options:
+      members: true
+      undoc-members: true

docs/source/usage.md

@@ -0,0 +1,33 @@
+# Getting Started
+
+This page offers a quick introduction to installing and using **gen_surv**.
+
+## Installation
+
+The project is managed with [Poetry](https://python-poetry.org). Clone the repository and install dependencies:
+
+```bash
+poetry install
+```
+
+This will create a virtual environment and install all required packages.
+
+## Basic Usage
+
+Generate datasets directly in Python:
+
+```python
+from gen_surv import generate
+
+# Cox Proportional Hazards example
+generate(model="cphm", n=100, model_cens="uniform", cens_par=1.0, beta=0.5, covar=2.0)
+```
+
+You can also generate data from the command line:
+
+```bash
+python -m gen_surv dataset aft_ln --n 100 > data.csv
+```
+
+For a full description of available models and parameters, see the API reference.
+