Add installation (#12)

Co-authored-by: Thomas Pinder <[email protected]>

Author: thomaspinder

README.md

@@ -1,6 +1,9 @@
 # Causal Validation
 
-This package provides functionality to define your own causal data generation process and then simulate data from the process. Within the package, there is functionality to include complex components to your process, such as periodic and temporal trends, and all of these operations are fully composable with one another. 
+This package provides functionality to define your own causal data generation process
+and then simulate data from the process. Within the package, there is functionality to
+include complex components to your process, such as periodic and temporal trends, and
+all of these operations are fully composable with one another. 
 
 A short example is given below
 ```python
@@ -38,9 +41,12 @@ plot(inflated_data)
 
 ## Examples
 
-To supplement the above example, we have two more detailed notebooks which exhaustively present and explain the functionalty in this package, along with how the generated data may be integrated with [AZCausal](https://github.com/amazon-science/azcausal).
-1. [Basic notebook](): We here show the full range of available functions for data generation
-2. [AZCausal notebook](): We here show how the generated data may be used within an AZCausal model.
+To supplement the above example, we have two more detailed notebooks which exhaustively
+present and explain the functionalty in this package, along with how the generated data
+may be integrated with [AZCausal](https://github.com/amazon-science/azcausal).
+1. [Data Synthesis](https://amazon-science.github.io/causal-validation/examples/basic/): We here show the full range of available functions for data generation.
+2. [Placebo testing](https://amazon-science.github.io/causal-validation/examples/placebo_test/): Validate your model(s) using placebo tests.
+3. [AZCausal notebook](https://amazon-science.github.io/causal-validation/examples/azcausal/): We here show how the generated data may be used within an AZCausal model.
 
 ## Installation
 

docs/installation.md

@@ -0,0 +1,42 @@
+# Installation
+
+## Stable version
+
+The latest stable release of `causal-validation` can be installed via `pip`:
+
+```bash
+pip install causal-validation
+```
+
+!!! note "Check your installation"
+    We recommend you check your installation version:
+    ```
+    python -c 'import causal_validation; print(causal_validation.__version__)'
+    ```
+
+## Development version
+
+!!! warning
+    This version is possibly unstable and may contain bugs.
+
+    The latest development version of `causal_validation` can be installed via running following:
+
+    ```bash
+    git clone [email protected]:amazon-science/causal-validation.git
+    cd causal-validation
+    hatch shell create
+    ```
+
+!!! tip
+    We advise you create virtual environment before installing:
+
+    ```bash
+    conda create -n causal-validation python=3.11.0
+    conda activate causal-validation
+    ```
+
+    and recommend you check your installation passes the supplied unit tests:
+
+    ```bash
+    hatch run dev:test
+    ```

mkdocs.yml

@@ -5,6 +5,7 @@ repo_name: causal-validation
 
 nav:
   - Home: index.md
+  - Installation: installation.md
   - Examples:
     - Data Synthesis: examples/basic.ipynb
     - Placebo Testing: examples/placebo_test.ipynb