diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
new file mode 100644
index 0000000..bf1dfa5
--- /dev/null
+++ b/.pre-commit-config.yaml
@@ -0,0 +1,14 @@
+repos:
+-   repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.6.0
+    hooks:
+    -   id: check-ast
+    -   id: check-merge-conflict
+    -   id: end-of-file-fixer
+    -   id: trailing-whitespace
+        args: ["--markdown-linebreak-ext=md"]
+    -   id: mixed-line-ending
+-   repo: https://github.com/psf/black
+    rev: 22.3.0
+    hooks:
+    -   id: black
diff --git a/README.md b/README.md
index 30b5945..198bbf4 100644
--- a/README.md
+++ b/README.md
@@ -2,18 +2,17 @@
 <img src="https://raw.githubusercontent.com/Fanchengyan/FanInSAR/main/docs/source/_static/logo/logo.svg" width="400">
 </h1><br>
 
-[![Documentation Status](https://readthedocs.org/projects/faninsar/badge/?version=latest)](https://faninsar.readthedocs.io/en/latest/?badge=latest) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11398347.svg)](https://doi.org/10.5281/zenodo.11398347)
-
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11398347.svg)](https://doi.org/10.5281/zenodo.11398347) [![Documentation Status](https://readthedocs.org/projects/faninsar/badge/?version=latest)](https://faninsar.readthedocs.io/en/latest/?badge=latest)  [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
 FanInSAR is a Fancy Interferometric Synthetic Aperture Radar (InSAR) time series analysis library written in Python. It aims to provide a foundational library for the development of InSAR algorithms, facilitating efficient processing of InSAR time series data by offering a Pythonic, fast, and flexible approach. FanInSAR’s high-level API abstracts the complex processing pipeline and conceals the low-level programming details, enabling users to focus on algorithm development. For researchers and developers aiming to rapidly implement their own InSAR algorithms, FanInSAR offers a quick start for their projects.
 
 
 ## Highlight Features
 
-- **Pythonic**: FanInSAR is written in Python and provides a user-friendly API. Its API is designed to be simple and intuitive, by abstracting the complex processing pipeline and concealing the low-level programming details, which allows users to focus on algorithm development. For example, loading data from ``HyP3`` or ``LiCSAR`` products is as simple as providing the corresponding home directory. Filtering interferometric pairs can be performed by a time slice, similar to the ``pandas`` package. 
+- **Pythonic**: FanInSAR is written in Python and provides a user-friendly API. Its API is designed to be simple and intuitive, by abstracting the complex processing pipeline and concealing the low-level programming details, which allows users to focus on algorithm development. For example, loading data from ``HyP3`` or ``LiCSAR`` products is as simple as providing the corresponding home directory. Filtering interferometric pairs can be performed by a time slice, similar to the ``pandas`` package.
 - **Fast**: The core computation in FanInSAR is implemented using ``PyTorch``, a high-performance deep learning library. This allows for efficient processing on both CPU and GPU, enabling faster execution.
 - **Flexible**: FanInSAR is designed to be flexible, allowing for customization and extension. Users can easily inherit classes or customize the processing pipeline for their specific needs.
 
-## Installation 
+## Installation
 
 FanInSAR is a Python package, and requires ``Python >= 3.8``. You can install the latest release of FanInSAR using ``pip`` from the PyPI:
 
@@ -32,7 +31,7 @@ pip install git+https://github.com/Fanchengyan/FanInSAR.git
 The detailed documentation is available at: <https://faninsar.readthedocs.io/en/latest/>
 
 > :warning: **Note**
-> 
+>
 >FanInSAR is under active development and is currently in the alpha stage. Its API may change in the future until it reaches a stable version.
 
 ## Citation
@@ -43,7 +42,7 @@ The detailed documentation is available at: <https://faninsar.readthedocs.io/en/
 @software{fan_2024_11398347,
   author       = {Fan, Chengyan and
                   Liu, Lin},
-  title        = {{FanInSAR: A Fancy InSAR time series library, in a 
+  title        = {{FanInSAR: A Fancy InSAR time series library, in a
                    Pythonic, fast, and flexible way}},
   month        = may,
   year         = 2024,
@@ -53,4 +52,3 @@ The detailed documentation is available at: <https://faninsar.readthedocs.io/en/
   url          = {https://doi.org/10.5281/zenodo.11398347}
 }
 ```
-
diff --git a/docs/source/_static/custom.css b/docs/source/_static/custom.css
new file mode 100644
index 0000000..60313cd
--- /dev/null
+++ b/docs/source/_static/custom.css
@@ -0,0 +1,10 @@
+.bd-content {
+  flex-grow: 1;
+  max-width: 100%;
+}
+.bd-page-width {
+  max-width: 100rem;
+}
+.bd-main .bd-article-container {
+  max-width: 100%;
+}
diff --git a/docs/source/api/index.rst b/docs/source/api/index.rst
index 9c5cd3b..baf611a 100644
--- a/docs/source/api/index.rst
+++ b/docs/source/api/index.rst
@@ -1,3 +1,4 @@
+=============
 API Reference
 =============
 
@@ -11,5 +12,4 @@ API Reference
    samplers/index
    NSBAS/index
    insar_class/pairs
-   
-
+   insar_class/phase_deformation_converter
diff --git a/docs/source/api/insar_class/phase_deformation_converter.rst b/docs/source/api/insar_class/phase_deformation_converter.rst
index 0296219..9c53079 100644
--- a/docs/source/api/insar_class/phase_deformation_converter.rst
+++ b/docs/source/api/insar_class/phase_deformation_converter.rst
@@ -1,9 +1,12 @@
+===========================
+Phase Deformation Converter
+===========================
 
 
 PhaseDeformationConverter
 ^^^^^^^^^^^^^^^^^^^^^^^^^
 
-.. autoclass:: PhaseDeformationConverter
+.. autoclass:: faninsar.PhaseDeformationConverter
     :members:
     :undoc-members:
     :member-order: bysource
diff --git a/docs/source/conf.py b/docs/source/conf.py
index e95993c..470e7e1 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -42,11 +42,13 @@
 
 html_theme = "pydata_sphinx_theme"
 html_static_path = ["_static"]
+html_css_files = ["custom.css"]
 html_logo = "_static/logo/logo.png"
 
 html_theme_options = {
     "show_toc_level": 2,
     "show_nav_level": 2,
+    "header_links_before_dropdown": 10,
     "use_edit_page_button": True,
     "icon_links": [
         {
diff --git a/docs/source/index.rst b/docs/source/index.rst
index 294b906..86150be 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -2,10 +2,17 @@
 Welcome to FanInSAR's documentation!
 ====================================
 
+.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.11398347.svg
+  :target: https://doi.org/10.5281/zenodo.11398347
+  :alt: DOI
+
 .. image:: https://readthedocs.org/projects/faninsar/badge/?version=latest
     :target: https://faninsar.readthedocs.io/en/latest/?badge=latest
     :alt: Documentation Status
 
+.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
+    :target: https://github.com/psf/black
+
 Introduction
 ------------
 
@@ -15,7 +22,7 @@ FanInSAR is a Fancy Interferometric Synthetic Aperture Radar (InSAR) time series
 Highlight Features
 ------------------
 
-- **Pythonic**: FanInSAR is written in Python and provides a user-friendly API. The API is designed to be simple and intuitive, by abstracting the complex processing pipeline and concealing the low-level programming details, which allows users to focus on algorithm development. For example, loading data from ``HyP3`` or ``LiCSAR`` products is as simple as providing the corresponding home directory. Filtering interferometric pairs can be performed by a time slice, similar to the ``pandas`` package. 
+- **Pythonic**: FanInSAR is written in Python and provides a user-friendly API. The API is designed to be simple and intuitive, by abstracting the complex processing pipeline and concealing the low-level programming details, which allows users to focus on algorithm development. For example, loading data from ``HyP3`` or ``LiCSAR`` products is as simple as providing the corresponding home directory. Filtering interferometric pairs can be performed by a time slice, similar to the ``pandas`` package.
 - **Fast**: The core computation in FanInSAR is implemented using ``PyTorch``, a high-performance deep learning library. This allows for efficient processing on both CPU and GPU, enabling faster execution.
 - **Flexible**: FanInSAR is designed to be flexible, allowing for customization and extension. Users can easily inherit classes or customize the processing pipeline for their specific needs.
 
@@ -27,7 +34,7 @@ Highlight Features
 Citation
 --------
 
-.. code-block:: 
+.. code-block::
 
     Fan, C., & Liu, L. (2024). FanInSAR: A Fancy InSAR time series library, in a Pythonic, fast, and flexible way (0.0.1). Zenodo. https://doi.org/10.5281/zenodo.11398347
 
@@ -51,9 +58,6 @@ Citation
    :caption: Contents:
 
    install
-   User Guide <user_guide/index>
-   API Reference <api/index>
+   user_guide/index
+   api/index
    terminology
-
-
-
diff --git a/docs/source/user_guide/index.rst b/docs/source/user_guide/index.rst
index 4db22dd..5ff3fa4 100644
--- a/docs/source/user_guide/index.rst
+++ b/docs/source/user_guide/index.rst
@@ -1,6 +1,6 @@
-###########
+==========
 User Guide
-###########
+==========
 
 In this user guide, you will find detailed descriptions and
 examples that describe many common tasks that you can accomplish with FanInSAR.
@@ -15,5 +15,3 @@ examples that describe many common tasks that you can accomplish with FanInSAR.
    data_structures
    Indexing_data
    sampler
-
-