diff --git a/.github/workflows/testing.yml b/.github/workflows/testing.yml
index 47fbb10..0bce8d7 100644
--- a/.github/workflows/testing.yml
+++ b/.github/workflows/testing.yml
@@ -1,4 +1,4 @@
-name: CI
+name: Testing
 
 on: [push, pull_request]
 
@@ -13,17 +13,20 @@ jobs:
     - name: Set up Python
       uses: actions/setup-python@v2
       with:
-        python-version: '3.x'  # Specify the Python version you want to use
+        python-version: '3.x'
 
-    - name: Install dependencies
-      run: |
-        python -m pip install --upgrade pip
-        pip install .
+    - name: Install uv
+      uses: astral-sh/setup-uv@v4
+
+    - name: "Set up Python"
+      uses: actions/setup-python@v5
+      with:
+        python-version-file: "pyproject.toml"
+
+    - name: Install the project
+      run: uv sync --all-extras --dev
 
     - name: Run tests
       run: |
-        python -m unittest discover -s . -p "test_*.py"
+        uv run python -m unittest discover -s tests -p "test_*.py"
 
-    - name: Run doctests
-      run: |
-        python -m doctest utils.py
\ No newline at end of file
diff --git a/.github/workflows/update_readme.yml b/.github/workflows/update_readme.yml
index 0d1d2ce..74f3f11 100644
--- a/.github/workflows/update_readme.yml
+++ b/.github/workflows/update_readme.yml
@@ -21,16 +21,33 @@ jobs:
       with:
         python-version: '3.x'
 
-    - name: Install dependencies
-      run: |
-        python -m pip install --upgrade pip
-        pip install .
+    - name: Install uv
+      uses: astral-sh/setup-uv@v4
+
+    - name: "Set up Python"
+      uses: actions/setup-python@v5
+      with:
+        python-version-file: "pyproject.toml"
+
+    - name: Install the project
+      run: uv sync --all-extras --dev
 
     - name: Update README
       run: |
-        python update_readme.py
+        uv run docs/update_readme.py
+
+
+    - name: Check for changes
+      id: check_changes
+      run: |
+        if git diff --exit-code README.md > /dev/null; then
+          echo "no_changes=true" >> $GITHUB_ENV
+        else
+          echo "no_changes=false" >> $GITHUB_ENV
+        fi
 
     - name: Commit and push changes
+      if: env.no_changes == 'false'
       run: |
         git config --global user.name 'github-actions[bot]'
         git config --global user.email 'github-actions[bot]@users.noreply.github.com'
@@ -38,4 +55,5 @@ jobs:
         git commit -m "Update README.md with function docstrings"
         git push
       env:
-        GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
\ No newline at end of file
+        GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
diff --git a/README.md b/README.md
index a04ef6d..ce81663 100644
--- a/README.md
+++ b/README.md
@@ -38,8 +38,8 @@ fig = plot_hipp_surf(label_gii.format(density=density), hemi=None, density=densi
 fig = plot_hipp_surf(label_gii.format(density=density), hemi=None, density=density, view='ventral')
 
 ```
-![png](doc/example1_0.png)
-![png](doc/example1_1.png)
+![png](docs/example1_0.png)
+![png](docs/example1_1.png)
     
 ### Example 2: Plot Left and Right Hemispheres Separately
 
@@ -59,8 +59,8 @@ fig = plot_hipp_surf(label_gii.format(density=density), hemi='right', density=de
 
 ```
     
-![png](doc/example2_0.png)
-![png](doc/example2_1.png)
+![png](docs/example2_0.png)
+![png](docs/example2_1.png)
 
 ### Example 3: Plot unfolded and canonical space separately
 
@@ -79,37 +79,67 @@ fig = plot_hipp_surf(label_gii.format(density=density), space='unfold', density=
 fig = plot_hipp_surf(label_gii.format(density=density), space='canonical', density=density, view='dorsal')
 ```
     
-![png](doc/example3_0.png)
-![png](doc/example3_1.png)
+![png](docs/example3_0.png)
+![png](docs/example3_1.png)
 
 ## 🛠️ Functions
 
 ### `plot_hipp_surf`
 
-```python
-def plot_hipp_surf(surf_map: Union[str, list], 
-                   density: str = '0p5mm', 
-                   hemi: str = 'left', 
-                   space: Optional[str] = None, 
-                   figsize: Tuple[int, int] = (12, 8), 
-                   dpi: int = 300, 
-                   vmin: Optional[float] = None, 
-                   vmax: Optional[float] = None, 
-                   colorbar: bool = False, 
-                   colorbar_shrink: float = 0.25, 
-                   cmap: Optional[Union[str, plt.cm.ScalarMappable]] = None, 
-                   view: str = 'dorsal', 
-                   avg_method: str = 'median', 
-                   bg_on_data: bool = True, 
-                   alpha: float = 0.1, 
-                   darkness: float = 2, 
-                   **kwargs) -> plt.Figure:
-    """
-    This function plots a surface map of the hippocampus, which can be a label-hippdentate shape.gii, func.gii, or a Vx1 array 
-    (where V is the number of vertices in the hippocampus and dentate). Any arguments that can be supplied to nilearn's plot_surf() 
-    can also be applied here, overriding the defaults set below.    """
-```
-
+Plot hippocampal surface map.
+
+This function plots a surface map of the hippocampus, which can be a label-hippdentate shape.gii, func.gii, or a Vx1 array
+(where V is the number of vertices in the hippocampus and dentate). Any arguments that can be supplied to nilearn's plot_surf()
+can also be applied here, overriding the defaults set below.
+
+###### Parameters
+ - **surf_map** (str or array-like):
+   The surface map to plot. This can be a file path to a .gii file or a Vx1 array.
+ - **density** (str, optional):
+   The density of the surface map. Can be 'unfoldiso', '0p5mm', '1mm', or '2mm'. Default is '0p5mm'.
+ - **hemi** (str, optional):
+   The hemisphere to plot. Can be 'left', 'right', or None (in which case both are plotted). Default is 'left'.
+ - **space** (str, optional):
+   The space of the surface map. Can be 'canonical', 'unfold', or None (in which case both are plotted). Default is None.
+ - **figsize** (tuple, optional):
+   The size of the figure. Default is (12, 8).
+ - **dpi** (int, optional):
+   The resolution of the figure in dots per inch. Default is 300.
+ - **vmin** (float, optional):
+   The minimum value for the color scale. Default is None.
+ - **vmax** (float, optional):
+   The maximum value for the color scale. Default is None.
+ - **colorbar** (bool, optional):
+   Whether to display a colorbar. Default is False.
+ - **colorbar_shrink** (float, optional):
+   The shrink factor for the colorbar. Default is 0.25.
+ - **cmap** (str or colormap, optional):
+   The colormap to use. Default is None.
+ - **view** (str, optional):
+   The view of the surface plot. Default is 'dorsal'.
+ - **avg_method** (str, optional):
+   The method to average the data. Default is 'median'.
+ - **bg_on_data** (bool, optional):
+   Whether to display the background on the data. Default is True.
+ - **alpha** (float, optional):
+   The alpha transparency level. Default is 0.1.
+ - **darkness** (float, optional):
+   The darkness level of the background. Default is 2.
+ - **axes** (matplotlib.axes.Axes or list of matplotlib.axes.Axes, optional):
+   Axes to plot on. If None, new axes will be created. If a single axis is provided, it will be used for a single plot.
+   If multiple plots are to be made, a list of axes should be provided.
+ - **figure** (matplotlib.figure.Figure, optional):
+   The figure to plot on. If None, a new figure will be created.
+ - ****kwargs** (dict):
+   Additional arguments to pass to nilearn's plot_surf().
+
+###### Returns
+ - **figure** (matplotlib.figure.Figure):
+   The figure object.
+
+###### Notes
+By default, this function will plot one hemisphere (left by default) in both canonical and unfolded space.
+Both surfaces can be plotted with hemi=None, but the same surf_map will be plotted on both.
 ## 🧪 Testing
 
 To run the tests, including unit tests and docstring tests, use the following command:
diff --git a/doc/example1_0.png b/docs/example1_0.png
similarity index 100%
rename from doc/example1_0.png
rename to docs/example1_0.png
diff --git a/doc/example1_1.png b/docs/example1_1.png
similarity index 100%
rename from doc/example1_1.png
rename to docs/example1_1.png
diff --git a/doc/example2_0.png b/docs/example2_0.png
similarity index 100%
rename from doc/example2_0.png
rename to docs/example2_0.png
diff --git a/doc/example2_1.png b/docs/example2_1.png
similarity index 100%
rename from doc/example2_1.png
rename to docs/example2_1.png
diff --git a/doc/example3_0.png b/docs/example3_0.png
similarity index 100%
rename from doc/example3_0.png
rename to docs/example3_0.png
diff --git a/doc/example3_1.png b/docs/example3_1.png
similarity index 100%
rename from doc/example3_1.png
rename to docs/example3_1.png
diff --git a/docs/update_readme.py b/docs/update_readme.py
new file mode 100644
index 0000000..19c3a7c
--- /dev/null
+++ b/docs/update_readme.py
@@ -0,0 +1,52 @@
+import ast
+import inspect
+import os
+from pdoc.docstrings import numpy as numpy_docstring_to_markdown
+
+
+
+def get_function_docstrings(module, function_names=None):
+    """
+    Get docstrings for specific functions in a module or all functions if no names are specified.
+
+    Args:
+        module: The module object containing the functions.
+        function_names (list of str, optional): List of function names to retrieve docstrings for. 
+                                                If None, retrieves all functions.
+
+    Returns:
+        dict: A dictionary mapping function names to their docstrings.
+    """
+    # Get all functions in the module
+    functions = [obj for name, obj in inspect.getmembers(module) if inspect.isfunction(obj)]
+    
+    docstrings = {}
+    for func in functions:
+        # If a list of function names is provided, filter functions
+        if function_names is None or func.__name__ in function_names:
+            docstrings[func.__name__] = numpy_docstring_to_markdown(inspect.getdoc(func))
+    
+    return docstrings
+
+def update_readme(readme_path, docstrings):
+    with open(readme_path, 'r') as file:
+        lines = file.readlines()
+
+    start_functions = lines.index("## 🛠️ Functions\n")
+    end_functions = lines.index("## 🧪 Testing\n")
+
+    new_lines = lines[:start_functions + 2]
+    for func_name, docstring in docstrings.items():
+        new_lines.append(f"### `{func_name}`\n\n")
+        new_lines.append(f"{docstring}\n")
+
+    new_lines.extend(lines[end_functions:])
+
+    with open(readme_path, 'w') as file:
+        file.writelines(new_lines)
+
+if __name__ == "__main__":
+    import hippunfold_plot.plotting as plotting
+    readme_path = 'README.md'
+    docstrings = get_function_docstrings(plotting,['plot_hipp_surf'])
+    update_readme(readme_path, docstrings)
diff --git a/hippunfold_plot/plotting.py b/hippunfold_plot/plotting.py
index 1c98773..8f14f44 100644
--- a/hippunfold_plot/plotting.py
+++ b/hippunfold_plot/plotting.py
@@ -1,32 +1,41 @@
 import matplotlib.pyplot as plt
-from nilearn.plotting import plot_surf 
-from hippunfold_plot.utils import get_surf_limits, get_data_limits, get_resource_path, check_surf_map_is_label_gii, get_legend_elements_from_label_gii
+from nilearn.plotting import plot_surf
+from hippunfold_plot.utils import (
+    get_surf_limits,
+    get_data_limits,
+    get_resource_path,
+    check_surf_map_is_label_gii,
+    get_legend_elements_from_label_gii,
+)
 from typing import Union, Tuple, Optional, List
 import numpy as np
 
-def plot_hipp_surf(surf_map: Union[str, list], 
-                   density: str = '0p5mm', 
-                   hemi: str = 'left', 
-                   space: Optional[str] = None, 
-                   figsize: Tuple[int, int] = (12, 8), 
-                   dpi: int = 300, 
-                   vmin: Optional[float] = None, 
-                   vmax: Optional[float] = None, 
-                   colorbar: bool = False, 
-                   colorbar_shrink: float = 0.25, 
-                   cmap: Optional[Union[str, plt.cm.ScalarMappable]] = None, 
-                   view: str = 'dorsal', 
-                   avg_method: str = 'median', 
-                   bg_on_data: bool = True, 
-                   alpha: float = 0.1, 
-                   darkness: float = 2, 
-                   axes: Optional[Union[plt.Axes, List[plt.Axes]]] = None, 
-                   figure: Optional[plt.Figure] = None,
-                   **kwargs) -> plt.Figure:
+
+def plot_hipp_surf(
+    surf_map: Union[str, list],
+    density: str = "0p5mm",
+    hemi: str = "left",
+    space: Optional[str] = None,
+    figsize: Tuple[int, int] = (12, 8),
+    dpi: int = 300,
+    vmin: Optional[float] = None,
+    vmax: Optional[float] = None,
+    colorbar: bool = False,
+    colorbar_shrink: float = 0.25,
+    cmap: Optional[Union[str, plt.cm.ScalarMappable]] = None,
+    view: str = "dorsal",
+    avg_method: str = "median",
+    bg_on_data: bool = True,
+    alpha: float = 0.1,
+    darkness: float = 2,
+    axes: Optional[Union[plt.Axes, List[plt.Axes]]] = None,
+    figure: Optional[plt.Figure] = None,
+    **kwargs,
+) -> plt.Figure:
     """Plot hippocampal surface map.
 
-    This function plots a surface map of the hippocampus, which can be a label-hippdentate shape.gii, func.gii, or a Vx1 array 
-    (where V is the number of vertices in the hippocampus and dentate). Any arguments that can be supplied to nilearn's plot_surf() 
+    This function plots a surface map of the hippocampus, which can be a label-hippdentate shape.gii, func.gii, or a Vx1 array
+    (where V is the number of vertices in the hippocampus and dentate). Any arguments that can be supplied to nilearn's plot_surf()
     can also be applied here, overriding the defaults set below.
 
     Parameters
@@ -83,36 +92,40 @@ def plot_hipp_surf(surf_map: Union[str, list],
 
     """
     # Validate inputs
-    valid_densities = ['unfoldiso', '0p5mm', '1mm', '2mm']
-    valid_spaces = ['canonical', 'unfold', None]
+    valid_densities = ["unfoldiso", "0p5mm", "1mm", "2mm"]
+    valid_spaces = ["canonical", "unfold", None]
     if density not in valid_densities:
-        raise ValueError(f"Invalid value for 'density'. Expected one of {valid_densities}.")
-    if hemi not in ['left', 'right', None]:
+        raise ValueError(
+            f"Invalid value for 'density'. Expected one of {valid_densities}."
+        )
+    if hemi not in ["left", "right", None]:
         raise ValueError("Invalid value for 'hemi'. Expected 'left', 'right', or None.")
     if space not in valid_spaces:
         raise ValueError(f"Invalid value for 'space'. Expected one of {valid_spaces}.")
 
+    surf_gii = get_resource_path(
+        "tpl-avg_hemi-{hemi}_space-{space}_label-hippdentate_density-{density}_midthickness.surf.gii"
+    )
+    curv_gii = get_resource_path(
+        "tpl-avg_label-hippdentate_density-{density}_curvature.shape.gii"
+    )
+
+    plot_kwargs = {
+        "surf_map": surf_map,
+        "bg_map": curv_gii.format(density=density),
+        "alpha": alpha,
+        "bg_on_data": bg_on_data,
+        "darkness": darkness,
+        "avg_method": avg_method,
+        "cmap": cmap,
+        "view": view,
+    }
 
-    surf_gii = get_resource_path('tpl-avg_hemi-{hemi}_space-{space}_label-hippdentate_density-{density}_midthickness.surf.gii')
-    curv_gii = get_resource_path('tpl-avg_label-hippdentate_density-{density}_curvature.shape.gii')
-
-    plot_kwargs = {'surf_map': surf_map,
-                   'bg_map': curv_gii.format(density=density),
-                   'alpha': alpha,
-                   'bg_on_data': bg_on_data,
-                   'darkness': darkness,
-                   'avg_method': avg_method,
-                   'cmap': cmap,
-                   'view': view}
-
-    #add any user arguments
+    # add any user arguments
     plot_kwargs.update(kwargs)
 
     # Define the plotting order for each hemisphere
-    hemi_space_map = {
-        'left': ['unfold', 'canonical'],
-        'right': ['canonical', 'unfold']
-    }
+    hemi_space_map = {"left": ["unfold", "canonical"], "right": ["canonical", "unfold"]}
 
     # Determine the number of plots to be made
     hemis_to_plot = [hemi] if hemi else hemi_space_map.keys()
@@ -122,14 +135,17 @@ def plot_hipp_surf(surf_map: Union[str, list],
     if axes is not None:
         if isinstance(axes, plt.Axes):
             if num_plots > 1:
-                raise ValueError("Multiple plots requested, but only one axis provided.")
+                raise ValueError(
+                    "Multiple plots requested, but only one axis provided."
+                )
             axes = [axes]
         elif isinstance(axes, np.ndarray):
             if len(axes) != num_plots:
                 raise ValueError(f"Expected {num_plots} axes, but got {len(axes)}.")
         else:
-            raise ValueError("Invalid type for 'axes'. Expected matplotlib.axes.Axes or array of matplotlib.axes.Axes.")
-
+            raise ValueError(
+                "Invalid type for 'axes'. Expected matplotlib.axes.Axes or array of matplotlib.axes.Axes."
+            )
 
     # Create a figure if not provided
     if figure is None:
@@ -137,42 +153,49 @@ def plot_hipp_surf(surf_map: Union[str, list],
 
     # Define positions for 4 tall side-by-side axes
     positions = [
-    [0.05, 0.1, 0.2, 0.8],  # Left, bottom, width, height
-    [0.18, 0.1, 0.2, 0.8],
-    [0.30, 0.1, 0.2, 0.8],
-    [0.43, 0.1, 0.2, 0.8],
-    [0.55, 0.1, 0.2, 0.8],
+        [0.05, 0.1, 0.2, 0.8],  # Left, bottom, width, height
+        [0.18, 0.1, 0.2, 0.8],
+        [0.30, 0.1, 0.2, 0.8],
+        [0.43, 0.1, 0.2, 0.8],
+        [0.55, 0.1, 0.2, 0.8],
     ]
-    
+
     # Create axes if not provided
     if axes is None:
-        axes = [figure.add_axes(positions[i], projection='3d') for i in range(num_plots)]
-               
-    pos=0
-    
+        axes = [
+            figure.add_axes(positions[i], projection="3d") for i in range(num_plots)
+        ]
+
+    pos = 0
+
     # Build the composite plot
     for h in hemis_to_plot:
         spaces_to_plot = [space] if space else hemi_space_map[h]
         for s in spaces_to_plot:
-            ax = axes[pos] 
-            plot_surf(surf_mesh=surf_gii.format(hemi=h,space=s,density=density),
-                          axes=ax,
-                          figure=figure,
-                          **plot_kwargs)
-            (xlim_kwargs,ylim_kwargs) = get_surf_limits(surf_mesh=surf_gii.format(hemi=h,space=s,density=density))
+            ax = axes[pos]
+            plot_surf(
+                surf_mesh=surf_gii.format(hemi=h, space=s, density=density),
+                axes=ax,
+                figure=figure,
+                **plot_kwargs,
+            )
+            (xlim_kwargs, ylim_kwargs) = get_surf_limits(
+                surf_mesh=surf_gii.format(hemi=h, space=s, density=density)
+            )
             ax.set_xlim(**xlim_kwargs)
             ax.set_ylim(**ylim_kwargs)
             ax.set_facecolor((0, 0, 0, 0))  # RGBA: last value is alpha for transparency
-            pos=pos+1
-
+            pos = pos + 1
 
-    if colorbar: #custom colorbar
+    if colorbar:  # custom colorbar
         import matplotlib as mpl
+
         (datamin, datamax) = get_data_limits(surf_map)
-        norm = mpl.colors.Normalize(vmin=vmin if vmin else datamin, vmax=vmax if vmax else datamax)  # Match your data range
+        norm = mpl.colors.Normalize(
+            vmin=vmin if vmin else datamin, vmax=vmax if vmax else datamax
+        )  # Match your data range
         sm = mpl.cm.ScalarMappable(cmap=cmap, norm=norm)
         sm.set_array([])  # Dummy array for ScalarMappable
-        plt.colorbar(sm,ax=figure.axes,shrink=colorbar_shrink)
-        
-    return figure
+        plt.colorbar(sm, ax=figure.axes, shrink=colorbar_shrink)
 
+    return figure
diff --git a/hippunfold_plot/update_readme.py b/hippunfold_plot/update_readme.py
deleted file mode 100644
index a43b9ef..0000000
--- a/hippunfold_plot/update_readme.py
+++ /dev/null
@@ -1,35 +0,0 @@
-import ast
-import inspect
-import os
-
-def get_function_docstrings(module):
-    functions = [obj for name, obj in inspect.getmembers(module) if inspect.isfunction(obj)]
-    docstrings = {}
-    for func in functions:
-        docstrings[func.__name__] = inspect.getdoc(func)
-    return docstrings
-
-def update_readme(readme_path, docstrings):
-    with open(readme_path, 'r') as file:
-        lines = file.readlines()
-
-    start_functions = lines.index("## 🛠️ Functions\n")
-    end_functions = lines.index("## 🧪 Testing\n")
-
-    new_lines = lines[:start_functions + 2]
-    for func_name, docstring in docstrings.items():
-        new_lines.append(f"### `{func_name}`\n\n")
-        new_lines.append("```python\n")
-        new_lines.append(f"{docstring}\n")
-        new_lines.append("```\n\n")
-
-    new_lines.extend(lines[end_functions:])
-
-    with open(readme_path, 'w') as file:
-        file.writelines(new_lines)
-
-if __name__ == "__main__":
-    import plotting
-    readme_path = 'README.md'
-    docstrings = get_function_docstrings(plotting)
-    update_readme(readme_path, docstrings)
\ No newline at end of file
diff --git a/hippunfold_plot/utils.py b/hippunfold_plot/utils.py
index b8a111b..49eb26b 100644
--- a/hippunfold_plot/utils.py
+++ b/hippunfold_plot/utils.py
@@ -4,6 +4,7 @@
 import numpy as np
 from typing import Union, Tuple, List
 
+
 def get_resource_path(file_name: str) -> str:
     """Get the path to a resource file.
 
@@ -22,7 +23,8 @@ def get_resource_path(file_name: str) -> str:
     >>> get_resource_path('example.txt')
     'path/to/resources/example.txt'
     """
-    return str(resources.files("hippunfold_plot") / 'resources' / file_name)
+    return str(resources.files("hippunfold_plot") / "resources" / file_name)
+
 
 def check_surf_map_is_label_gii(surf_map: Union[str, np.ndarray]) -> bool:
     """Check if the surface map is a label GIFTI file.
@@ -45,10 +47,13 @@ def check_surf_map_is_label_gii(surf_map: Union[str, np.ndarray]) -> bool:
     False
     """
     if isinstance(surf_map, str):
-        return surf_map.endswith('label.gii')
+        return surf_map.endswith("label.gii")
     return False
 
-def read_pointset_from_surf_mesh(surf_mesh: Union[str, Tuple[np.ndarray, np.ndarray]]) -> np.ndarray:
+
+def read_pointset_from_surf_mesh(
+    surf_mesh: Union[str, Tuple[np.ndarray, np.ndarray]]
+) -> np.ndarray:
     """Read pointset from a surface mesh.
 
     Parameters
@@ -68,8 +73,12 @@ def read_pointset_from_surf_mesh(surf_mesh: Union[str, Tuple[np.ndarray, np.ndar
     (1000, 3)
     """
     if isinstance(surf_mesh, str):
-        if surf_mesh.endswith('surf.gii'):
-            points = nib.load(surf_mesh).get_arrays_from_intent('NIFTI_INTENT_POINTSET')[0].data
+        if surf_mesh.endswith("surf.gii"):
+            points = (
+                nib.load(surf_mesh)
+                .get_arrays_from_intent("NIFTI_INTENT_POINTSET")[0]
+                .data
+            )
         else:
             raise TypeError("surf_mesh string not recognized as surf.gii")
     elif isinstance(surf_mesh, tuple):
@@ -77,6 +86,7 @@ def read_pointset_from_surf_mesh(surf_mesh: Union[str, Tuple[np.ndarray, np.ndar
             points = surf_mesh[0]
     return points
 
+
 def read_data_from_surf_map(surf_map: Union[str, np.ndarray]) -> np.ndarray:
     """Read data from a surface map.
 
@@ -97,7 +107,7 @@ def read_data_from_surf_map(surf_map: Union[str, np.ndarray]) -> np.ndarray:
     (1000,)
     """
     if isinstance(surf_map, str):
-        if surf_map.endswith('.gii'):
+        if surf_map.endswith(".gii"):
             data = nib.load(surf_map).darrays[0].data
         else:
             raise TypeError("surf_map string not recognized as metric gii")
@@ -105,6 +115,7 @@ def read_data_from_surf_map(surf_map: Union[str, np.ndarray]) -> np.ndarray:
         data = surf_map
     return data
 
+
 def get_data_limits(surf_map: Union[str, np.ndarray]) -> Tuple[float, float]:
     """Get the data limits from a surface map.
 
@@ -126,7 +137,10 @@ def get_data_limits(surf_map: Union[str, np.ndarray]) -> Tuple[float, float]:
     data = read_data_from_surf_map(surf_map)
     return data.min(), data.max()
 
-def get_surf_limits(surf_mesh: Union[str, Tuple[np.ndarray, np.ndarray]]) -> Tuple[dict, dict]:
+
+def get_surf_limits(
+    surf_mesh: Union[str, Tuple[np.ndarray, np.ndarray]]
+) -> Tuple[dict, dict]:
     """Get the surface limits from a surface mesh.
 
     Parameters
@@ -148,27 +162,28 @@ def get_surf_limits(surf_mesh: Union[str, Tuple[np.ndarray, np.ndarray]]) -> Tup
     {'bottom': -50.0, 'top': 50.0}
     """
     points = read_pointset_from_surf_mesh(surf_mesh)
-        
+
     # Calculate the ranges for each dimension
     x_min, x_max = points[:, 0].min(), points[:, 0].max()
     y_min, y_max = points[:, 1].min(), points[:, 1].max()
 
     x_range = x_max - x_min
     y_range = y_max - y_min
-    
+
     # Adjust the ranges to match the desired aspect ratio by cropping
-    target_y_range = x_range 
+    target_y_range = x_range
     y_mid = (y_max + y_min) / 2
     y_min_cropped = y_mid - target_y_range / 2
     y_max_cropped = y_mid + target_y_range / 2
     x_min_cropped, x_max_cropped = x_min, x_max
 
     # Return the cropped limits
-    xlim_kwargs = {'left': x_min_cropped, 'right': x_max_cropped}
-    ylim_kwargs = {'bottom': y_min_cropped, 'top': y_max_cropped}
+    xlim_kwargs = {"left": x_min_cropped, "right": x_max_cropped}
+    ylim_kwargs = {"bottom": y_min_cropped, "top": y_max_cropped}
 
     return xlim_kwargs, ylim_kwargs
 
+
 def get_legend_elements_from_label_gii(label_map: str) -> List:
     """Get legend elements from a label GIFTI file.
 
@@ -189,20 +204,26 @@ def get_legend_elements_from_label_gii(label_map: str) -> List:
     True
     """
     from matplotlib.patches import Patch
-    
+
     # Load the GIFTI file
     label_gii = nib.load(label_map)
-    
+
     # Extract the label table (LUT)
     label_table = label_gii.labeltable.labels
-    
+
     # Create legend elements
     legend_elements = [
         Patch(
-            facecolor=(label.red/255.0, label.green/255.0, label.blue/255.0, label.alpha/255.0),  # RGBA from LUT
+            facecolor=(
+                label.red / 255.0,
+                label.green / 255.0,
+                label.blue / 255.0,
+                label.alpha / 255.0,
+            ),  # RGBA from LUT
             edgecolor="black",
-            label=label.label  # The name of the label
+            label=label.label,  # The name of the label
         )
-        for label in label_table if label.label  # Skip empty labels if any
+        for label in label_table
+        if label.label  # Skip empty labels if any
     ]
     return legend_elements
diff --git a/pyproject.toml b/pyproject.toml
index 8b776b2..c7b1095 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -9,3 +9,12 @@ dependencies = [
     "nilearn>=0.10.4",
 ]
 
+[dependency-groups]
+dev = [
+    "black>=24.10.0",
+    "pdoc>=15.0.0",
+]
+
+[build-system]
+requires = ["setuptools>=61"]
+build-backend = "setuptools.build_meta"
diff --git a/uv.lock b/uv.lock
index 7860c0b..78e8019 100644
--- a/uv.lock
+++ b/uv.lock
@@ -6,6 +6,44 @@ resolution-markers = [
     "python_full_version >= '3.12'",
 ]
 
+[[package]]
+name = "black"
+version = "24.10.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "click" },
+    { name = "mypy-extensions" },
+    { name = "packaging" },
+    { name = "pathspec" },
+    { name = "platformdirs" },
+    { name = "tomli", marker = "python_full_version < '3.11'" },
+    { name = "typing-extensions", marker = "python_full_version < '3.11'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/d8/0d/cc2fb42b8c50d80143221515dd7e4766995bd07c56c9a3ed30baf080b6dc/black-24.10.0.tar.gz", hash = "sha256:846ea64c97afe3bc677b761787993be4991810ecc7a4a937816dd6bddedc4875", size = 645813 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/a3/f3/465c0eb5cddf7dbbfe1fecd9b875d1dcf51b88923cd2c1d7e9ab95c6336b/black-24.10.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e6668650ea4b685440857138e5fe40cde4d652633b1bdffc62933d0db4ed9812", size = 1623211 },
+    { url = "https://files.pythonhosted.org/packages/df/57/b6d2da7d200773fdfcc224ffb87052cf283cec4d7102fab450b4a05996d8/black-24.10.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:1c536fcf674217e87b8cc3657b81809d3c085d7bf3ef262ead700da345bfa6ea", size = 1457139 },
+    { url = "https://files.pythonhosted.org/packages/6e/c5/9023b7673904a5188f9be81f5e129fff69f51f5515655fbd1d5a4e80a47b/black-24.10.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:649fff99a20bd06c6f727d2a27f401331dc0cc861fb69cde910fe95b01b5928f", size = 1753774 },
+    { url = "https://files.pythonhosted.org/packages/e1/32/df7f18bd0e724e0d9748829765455d6643ec847b3f87e77456fc99d0edab/black-24.10.0-cp310-cp310-win_amd64.whl", hash = "sha256:fe4d6476887de70546212c99ac9bd803d90b42fc4767f058a0baa895013fbb3e", size = 1414209 },
+    { url = "https://files.pythonhosted.org/packages/c2/cc/7496bb63a9b06a954d3d0ac9fe7a73f3bf1cd92d7a58877c27f4ad1e9d41/black-24.10.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:5a2221696a8224e335c28816a9d331a6c2ae15a2ee34ec857dcf3e45dbfa99ad", size = 1607468 },
+    { url = "https://files.pythonhosted.org/packages/2b/e3/69a738fb5ba18b5422f50b4f143544c664d7da40f09c13969b2fd52900e0/black-24.10.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f9da3333530dbcecc1be13e69c250ed8dfa67f43c4005fb537bb426e19200d50", size = 1437270 },
+    { url = "https://files.pythonhosted.org/packages/c9/9b/2db8045b45844665c720dcfe292fdaf2e49825810c0103e1191515fc101a/black-24.10.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:4007b1393d902b48b36958a216c20c4482f601569d19ed1df294a496eb366392", size = 1737061 },
+    { url = "https://files.pythonhosted.org/packages/a3/95/17d4a09a5be5f8c65aa4a361444d95edc45def0de887810f508d3f65db7a/black-24.10.0-cp311-cp311-win_amd64.whl", hash = "sha256:394d4ddc64782e51153eadcaaca95144ac4c35e27ef9b0a42e121ae7e57a9175", size = 1423293 },
+    { url = "https://files.pythonhosted.org/packages/90/04/bf74c71f592bcd761610bbf67e23e6a3cff824780761f536512437f1e655/black-24.10.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:b5e39e0fae001df40f95bd8cc36b9165c5e2ea88900167bddf258bacef9bbdc3", size = 1644256 },
+    { url = "https://files.pythonhosted.org/packages/4c/ea/a77bab4cf1887f4b2e0bce5516ea0b3ff7d04ba96af21d65024629afedb6/black-24.10.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:d37d422772111794b26757c5b55a3eade028aa3fde43121ab7b673d050949d65", size = 1448534 },
+    { url = "https://files.pythonhosted.org/packages/4e/3e/443ef8bc1fbda78e61f79157f303893f3fddf19ca3c8989b163eb3469a12/black-24.10.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:14b3502784f09ce2443830e3133dacf2c0110d45191ed470ecb04d0f5f6fcb0f", size = 1761892 },
+    { url = "https://files.pythonhosted.org/packages/52/93/eac95ff229049a6901bc84fec6908a5124b8a0b7c26ea766b3b8a5debd22/black-24.10.0-cp312-cp312-win_amd64.whl", hash = "sha256:30d2c30dc5139211dda799758559d1b049f7f14c580c409d6ad925b74a4208a8", size = 1434796 },
+    { url = "https://files.pythonhosted.org/packages/d0/a0/a993f58d4ecfba035e61fca4e9f64a2ecae838fc9f33ab798c62173ed75c/black-24.10.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:1cbacacb19e922a1d75ef2b6ccaefcd6e93a2c05ede32f06a21386a04cedb981", size = 1643986 },
+    { url = "https://files.pythonhosted.org/packages/37/d5/602d0ef5dfcace3fb4f79c436762f130abd9ee8d950fa2abdbf8bbc555e0/black-24.10.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:1f93102e0c5bb3907451063e08b9876dbeac810e7da5a8bfb7aeb5a9ef89066b", size = 1448085 },
+    { url = "https://files.pythonhosted.org/packages/47/6d/a3a239e938960df1a662b93d6230d4f3e9b4a22982d060fc38c42f45a56b/black-24.10.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ddacb691cdcdf77b96f549cf9591701d8db36b2f19519373d60d31746068dbf2", size = 1760928 },
+    { url = "https://files.pythonhosted.org/packages/dd/cf/af018e13b0eddfb434df4d9cd1b2b7892bab119f7a20123e93f6910982e8/black-24.10.0-cp313-cp313-win_amd64.whl", hash = "sha256:680359d932801c76d2e9c9068d05c6b107f2584b2a5b88831c83962eb9984c1b", size = 1436875 },
+    { url = "https://files.pythonhosted.org/packages/fe/02/f408c804e0ee78c367dcea0a01aedde4f1712af93b8b6e60df981e0228c7/black-24.10.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:17374989640fbca88b6a448129cd1745c5eb8d9547b464f281b251dd00155ccd", size = 1622516 },
+    { url = "https://files.pythonhosted.org/packages/f8/b9/9b706ed2f55bfb28b436225a9c57da35990c9005b90b8c91f03924454ad7/black-24.10.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:63f626344343083322233f175aaf372d326de8436f5928c042639a4afbbf1d3f", size = 1456181 },
+    { url = "https://files.pythonhosted.org/packages/0a/1c/314d7f17434a5375682ad097f6f4cc0e3f414f3c95a9b1bb4df14a0f11f9/black-24.10.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ccfa1d0cb6200857f1923b602f978386a3a2758a65b52e0950299ea014be6800", size = 1752801 },
+    { url = "https://files.pythonhosted.org/packages/39/a7/20e5cd9237d28ad0b31438de5d9f01c8b99814576f4c0cda1edd62caf4b0/black-24.10.0-cp39-cp39-win_amd64.whl", hash = "sha256:2cd9c95431d94adc56600710f8813ee27eea544dd118d45896bb734e9d7a0dc7", size = 1413626 },
+    { url = "https://files.pythonhosted.org/packages/8d/a7/4b27c50537ebca8bec139b872861f9d2bf501c5ec51fcf897cb924d9e264/black-24.10.0-py3-none-any.whl", hash = "sha256:3bb2b7a1f7b685f85b11fed1ef10f8a9148bceb49853e47a294a3dd963c1dd7d", size = 206898 },
+]
+
 [[package]]
 name = "certifi"
 version = "2024.8.30"
@@ -99,6 +137,27 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/bf/9b/08c0432272d77b04803958a4598a51e2a4b51c06640af8b8f0f908c18bf2/charset_normalizer-3.4.0-py3-none-any.whl", hash = "sha256:fe9f97feb71aa9896b81973a7bbada8c49501dc73e58a10fcef6663af95e5079", size = 49446 },
 ]
 
+[[package]]
+name = "click"
+version = "8.1.7"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "colorama", marker = "platform_system == 'Windows'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/96/d3/f04c7bfcf5c1862a2a5b845c6b2b360488cf47af55dfa79c98f6a6bf98b5/click-8.1.7.tar.gz", hash = "sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de", size = 336121 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/00/2e/d53fa4befbf2cfa713304affc7ca780ce4fc1fd8710527771b58311a3229/click-8.1.7-py3-none-any.whl", hash = "sha256:ae74fb96c20a0277a1d615f1e4d73c8414f5a98db8b799a7931d1582f3390c28", size = 97941 },
+]
+
+[[package]]
+name = "colorama"
+version = "0.4.6"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/d8/53/6f443c9a4a8358a93a6792e2acffb9d9d5cb0a5cfd8802644b7b1c9a02e4/colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44", size = 27697 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6", size = 25335 },
+]
+
 [[package]]
 name = "contourpy"
 version = "1.3.0"
@@ -234,19 +293,31 @@ wheels = [
 
 [[package]]
 name = "hippunfold-plot"
-version = "0.1.0"
-source = { virtual = "." }
+version = "0.1.1"
+source = { editable = "." }
 dependencies = [
     { name = "matplotlib" },
     { name = "nilearn" },
 ]
 
+[package.dev-dependencies]
+dev = [
+    { name = "black" },
+    { name = "pdoc" },
+]
+
 [package.metadata]
 requires-dist = [
     { name = "matplotlib", specifier = ">=3.9.2" },
     { name = "nilearn", specifier = ">=0.10.4" },
 ]
 
+[package.metadata.requires-dev]
+dev = [
+    { name = "black", specifier = ">=24.10.0" },
+    { name = "pdoc", specifier = ">=15.0.0" },
+]
+
 [[package]]
 name = "idna"
 version = "3.10"
@@ -268,6 +339,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/e1/6a/4604f9ae2fa62ef47b9de2fa5ad599589d28c9fd1d335f32759813dfa91e/importlib_resources-6.4.5-py3-none-any.whl", hash = "sha256:ac29d5f956f01d5e4bb63102a5a19957f1b9175e45649977264a1416783bb717", size = 36115 },
 ]
 
+[[package]]
+name = "jinja2"
+version = "3.1.4"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "markupsafe" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ed/55/39036716d19cab0747a5020fc7e907f362fbf48c984b14e62127f7e68e5d/jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369", size = 240245 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/31/80/3a54838c3fb461f6fec263ebf3a3a41771bd05190238de3486aae8540c36/jinja2-3.1.4-py3-none-any.whl", hash = "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d", size = 133271 },
+]
+
 [[package]]
 name = "joblib"
 version = "1.4.2"
@@ -482,6 +565,74 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/17/45/0fe53cb16a704b35b5ec93af305f77a14ec65830fc399e6634a81f17a1ea/lxml-5.3.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:516f491c834eb320d6c843156440fe7fc0d50b33e44387fcec5b02f0bc118a4c", size = 3486287 },
 ]
 
+[[package]]
+name = "markupsafe"
+version = "3.0.2"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/b2/97/5d42485e71dfc078108a86d6de8fa46db44a1a9295e89c5d6d4a06e23a62/markupsafe-3.0.2.tar.gz", hash = "sha256:ee55d3edf80167e48ea11a923c7386f4669df67d7994554387f84e7d8b0a2bf0", size = 20537 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/04/90/d08277ce111dd22f77149fd1a5d4653eeb3b3eaacbdfcbae5afb2600eebd/MarkupSafe-3.0.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7e94c425039cde14257288fd61dcfb01963e658efbc0ff54f5306b06054700f8", size = 14357 },
+    { url = "https://files.pythonhosted.org/packages/04/e1/6e2194baeae0bca1fae6629dc0cbbb968d4d941469cbab11a3872edff374/MarkupSafe-3.0.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:9e2d922824181480953426608b81967de705c3cef4d1af983af849d7bd619158", size = 12393 },
+    { url = "https://files.pythonhosted.org/packages/1d/69/35fa85a8ece0a437493dc61ce0bb6d459dcba482c34197e3efc829aa357f/MarkupSafe-3.0.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:38a9ef736c01fccdd6600705b09dc574584b89bea478200c5fbf112a6b0d5579", size = 21732 },
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