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utils

deepdrivewe.ai.utils

Utility functions for the AI module.

LatentSpaceHistory

A class to store the latent space history.

Source code in deepdrivewe/ai/utils.py 
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class LatentSpaceHistory:
    """A class to store the latent space history."""

    def __init__(self) -> None:
        """Initialize the latent space history."""
        # A (n, d) array where n is the number of frames and d is
        # the latent space dimensionality
        self.z = np.array([])
        # A (n, 1) array of progress coordinates for each frame
        self.pcoords = np.array([])

    def __bool__(self) -> bool:
        """Return True if the history is not empty."""
        return bool(len(self.z))

    def update(self, z: ArrayLike, pcoords: ArrayLike) -> None:
        """Update the latent space history.

        Parameters
        ----------
        z : array-like
            The latent space coordinates (n_frames, d)
        pcoords : array-like
            The progress coordinates (n_frames, 1)
        """
        self.z = z
        self.pcoords = pcoords

    def plot(
        self,
        output_path: Path,
        color: ArrayLike | None = None,
        cblabel: str = 'Progress Coordinate',
        title: str = '',
    ) -> None:
        """Create a scatter plot.

        Parameters
        ----------
        output_path : Path
            Path to save the plot image.
        color : array-like, optional
            Data used for coloring the points. Defaults to
            progress coordinates.
        cblabel : str
            Label for the colorbar.
        title : str
            Title of the plot.
        """
        import matplotlib.pyplot as plt

        # Set the color data to the progress coordinates if not provided
        color = self.pcoords if color is None else color

        print(
            f'Plotting latent space with {len(self.z)} points '
            f'and color with shape {len(color)} frames to {output_path}',
        )

        # Create the 3D scatter plot
        fig = plt.figure(figsize=(10, 8))
        ax = fig.add_subplot(111, projection='3d')
        scatter = ax.scatter(
            xs=self.z[:, 0],
            ys=self.z[:, 1],
            zs=self.z[:, 2],
            c=color,
            cmap='viridis',
        )
        fig.colorbar(scatter, label=cblabel)
        ax.set_xlabel(r'$z_1$')
        ax.set_ylabel(r'$z_2$')
        ax.set_zlabel(r'$z_3$')
        ax.set_title(title)
        # plt.savefig(output_path, bbox_inches='tight', dpi=300)
        plt.savefig(output_path)
        plt.close()

__init__ 

__init__() -> None

Initialize the latent space history.

Source code in deepdrivewe/ai/utils.py 
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def __init__(self) -> None:
    """Initialize the latent space history."""
    # A (n, d) array where n is the number of frames and d is
    # the latent space dimensionality
    self.z = np.array([])
    # A (n, 1) array of progress coordinates for each frame
    self.pcoords = np.array([])

__bool__ 

__bool__() -> bool

Return True if the history is not empty.

Source code in deepdrivewe/ai/utils.py 
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def __bool__(self) -> bool:
    """Return True if the history is not empty."""
    return bool(len(self.z))

update 

update(z: ArrayLike, pcoords: ArrayLike) -> None

Update the latent space history.

Parameters:

Name Type Description Default
z array - like

The latent space coordinates (n_frames, d)

 required
pcoords array - like

The progress coordinates (n_frames, 1)

 required
Source code in deepdrivewe/ai/utils.py 
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def update(self, z: ArrayLike, pcoords: ArrayLike) -> None:
    """Update the latent space history.

    Parameters
    ----------
    z : array-like
        The latent space coordinates (n_frames, d)
    pcoords : array-like
        The progress coordinates (n_frames, 1)
    """
    self.z = z
    self.pcoords = pcoords

plot 

plot(
    output_path: Path,
    color: ArrayLike | None = None,
    cblabel: str = "Progress Coordinate",
    title: str = "",
) -> None

Create a scatter plot.

Parameters:

Name Type Description Default
output_path Path

Path to save the plot image.

 required
color array - like

Data used for coloring the points. Defaults to progress coordinates.

 None
cblabel str

Label for the colorbar.

 'Progress Coordinate'
title str

Title of the plot.

 ''
Source code in deepdrivewe/ai/utils.py 
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def plot(
    self,
    output_path: Path,
    color: ArrayLike | None = None,
    cblabel: str = 'Progress Coordinate',
    title: str = '',
) -> None:
    """Create a scatter plot.

    Parameters
    ----------
    output_path : Path
        Path to save the plot image.
    color : array-like, optional
        Data used for coloring the points. Defaults to
        progress coordinates.
    cblabel : str
        Label for the colorbar.
    title : str
        Title of the plot.
    """
    import matplotlib.pyplot as plt

    # Set the color data to the progress coordinates if not provided
    color = self.pcoords if color is None else color

    print(
        f'Plotting latent space with {len(self.z)} points '
        f'and color with shape {len(color)} frames to {output_path}',
    )

    # Create the 3D scatter plot
    fig = plt.figure(figsize=(10, 8))
    ax = fig.add_subplot(111, projection='3d')
    scatter = ax.scatter(
        xs=self.z[:, 0],
        ys=self.z[:, 1],
        zs=self.z[:, 2],
        c=color,
        cmap='viridis',
    )
    fig.colorbar(scatter, label=cblabel)
    ax.set_xlabel(r'$z_1$')
    ax.set_ylabel(r'$z_2$')
    ax.set_zlabel(r'$z_3$')
    ax.set_title(title)
    # plt.savefig(output_path, bbox_inches='tight', dpi=300)
    plt.savefig(output_path)
    plt.close()