colormaps module

Module for commonly used colormaps and palettes for visualizing Earth Engine data.

get_colorbar(colors, vmin=0, vmax=1, width=6.0, height=0.4, orientation='horizontal', discrete=False, return_fig=False)

Creates a colorbar based on custom colors.

Parameters:

Name	Type	Description	Default
colors	list	A list of hex colors.	required
vmin	float	The minimum value range. Defaults to 0.	0
vmax	float	The maximum value range. Defaults to 1.0.	1
width	float	The width of the colormap. Defaults to 6.0.	6.0
height	float	The height of the colormap. Defaults to 0.4.	0.4
orientation	str	The orientation of the colormap. Defaults to "horizontal".	'horizontal'
discrete	bool	Whether to create a discrete colormap.	False
return_fig	bool	Whether to return the figure. Defaults to False.	False

Source code in geemap/colormaps.py

def get_colorbar(
    colors,
    vmin=0,
    vmax=1,
    width=6.0,
    height=0.4,
    orientation="horizontal",
    discrete=False,
    return_fig=False,
):
    """Creates a colorbar based on custom colors.

    Args:
        colors (list): A list of hex colors.
        vmin (float, optional): The minimum value range. Defaults to 0.
        vmax (float, optional): The maximum value range. Defaults to 1.0.
        width (float, optional): The width of the colormap. Defaults to 6.0.
        height (float, optional): The height of the colormap. Defaults to 0.4.
        orientation (str, optional): The orientation of the colormap. Defaults to "horizontal".
        discrete (bool, optional): Whether to create a discrete colormap.
        return_fig (bool, optional): Whether to return the figure. Defaults to False.
    """
    hexcodes = [i if i[0] == "#" else "#" + i for i in colors]
    fig, ax = plt.subplots(figsize=(width, height))
    if discrete:
        cmap = mpl.colors.ListedColormap(hexcodes)
        vals = np.linspace(vmin, vmax, cmap.N + 1)
        norm = mpl.colors.BoundaryNorm(vals, cmap.N)
    else:
        cmap = mpl.colors.LinearSegmentedColormap.from_list("custom", hexcodes, N=256)
        norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
    mpl.colorbar.ColorbarBase(ax, norm=norm, cmap=cmap, orientation=orientation)
    if return_fig:
        return fig
    else:
        plt.show()

get_palette(cmap_name=None, n_class=None, hashtag=False)

Get a palette from a matplotlib colormap.

WARNING: This function is inconsistent with how it handles hashes in the color names w.r.t. if there is a leading hash (#).

See the list of colormaps at https://matplotlib.org/stable/tutorials/colors/colormaps.html.

Parameters:

Name	Type	Description	Default
cmap_name	str	The name of the matplotlib colormap. Defaults to None.	None
n_class	int	The number of colors. Defaults to None.	None
hashtag	bool	Whether to return a list of hex colors. Defaults to False.	False

Returns:

Name	Type	Description
list	list[str]	A list of hex colors.

Source code in geemap/colormaps.py

def get_palette(
    cmap_name: str | None = None, n_class: int | None = None, hashtag: bool = False
) -> list[str]:
    """Get a palette from a matplotlib colormap.

    WARNING: This function is inconsistent with how it handles hashes in the
    color names w.r.t. if there is a leading hash (`#`).

    See the list of colormaps at
    https://matplotlib.org/stable/tutorials/colors/colormaps.html.

    Args:
        cmap_name (str, optional): The name of the matplotlib colormap. Defaults to None.
        n_class (int, optional): The number of colors. Defaults to None.
        hashtag (bool, optional): Whether to return a list of hex colors. Defaults to False.

    Returns:
        list: A list of hex colors.
    """

    if cmap_name in ["ndvi", "ndwi", "dem", "dw", "esri_lulc"]:
        colors = _palette_dict[cmap_name]
    else:
        cmap = mpl.colormaps[cmap_name]  # Retrieve colormap
        if n_class:
            colors = [
                mpl.colors.rgb2hex(cmap(i / (n_class - 1)))[1:] for i in range(n_class)
            ]
        else:
            colors = [mpl.colors.rgb2hex(cmap(i))[1:] for i in range(cmap.N)]

    def add_hashtag(color: str) -> str:
        if color.startswith("#"):
            return color
        else:
            return f"#{color}"

    if hashtag:
        colors = [add_hashtag(color) for color in colors]

    return colors

list_colormaps(add_extra=False, lowercase=False)

List all available colormaps. See a complete lost of colormaps at https://matplotlib.org/stable/tutorials/colors/colormaps.html.

Returns:

Name	Type	Description
list		The list of colormap names.

Source code in geemap/colormaps.py

def list_colormaps(add_extra=False, lowercase=False):
    """List all available colormaps. See a complete lost of colormaps at https://matplotlib.org/stable/tutorials/colors/colormaps.html.

    Returns:
        list: The list of colormap names.
    """
    result = plt.colormaps()
    if add_extra:
        result += ["dem", "ndvi", "ndwi"]
    if lowercase:
        result = [i.lower() for i in result]
    result.sort()
    return result

plot_colormap(cmap, width=8.0, height=0.4, orientation='horizontal', vmin=0, vmax=1.0, axis_off=True, show_name=False, font_size=12, return_fig=False)

Plot a matplotlib colormap.

Parameters:

Name	Type	Description	Default
cmap	str	The name of the colormap.	required
width	float	The width of the colormap. Defaults to 8.0.	8.0
height	float	The height of the colormap. Defaults to 0.4.	0.4
orientation	str	The orientation of the colormap. Defaults to "horizontal".	'horizontal'
vmin	float	The minimum value range. Defaults to 0.	0
vmax	float	The maximum value range. Defaults to 1.0.	1.0
axis_off	bool	Whether to turn axis off. Defaults to True.	True
show_name	bool	Whether to show the colormap name. Defaults to False.	False
font_size	int	Font size of the text. Defaults to 12.	12
return_fig	bool	Whether to return the figure. Defaults to False.	False

Source code in geemap/colormaps.py

def plot_colormap(
    cmap,
    width=8.0,
    height=0.4,
    orientation="horizontal",
    vmin=0,
    vmax=1.0,
    axis_off=True,
    show_name=False,
    font_size=12,
    return_fig=False,
):
    """Plot a matplotlib colormap.

    Args:
        cmap (str): The name of the colormap.
        width (float, optional): The width of the colormap. Defaults to 8.0.
        height (float, optional): The height of the colormap. Defaults to 0.4.
        orientation (str, optional): The orientation of the colormap. Defaults to "horizontal".
        vmin (float, optional): The minimum value range. Defaults to 0.
        vmax (float, optional): The maximum value range. Defaults to 1.0.
        axis_off (bool, optional): Whether to turn axis off. Defaults to True.
        show_name (bool, optional): Whether to show the colormap name. Defaults to False.
        font_size (int, optional): Font size of the text. Defaults to 12.
        return_fig (bool, optional): Whether to return the figure. Defaults to False.
    """
    fig, ax = plt.subplots(figsize=(width, height))
    col_map = mpl.colormaps[cmap]

    norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)

    mpl.colorbar.ColorbarBase(ax, norm=norm, cmap=col_map, orientation=orientation)
    if axis_off:
        ax.set_axis_off()

    if show_name:
        pos = list(ax.get_position().bounds)
        x_text = pos[0] - 0.01
        y_text = pos[1] + pos[3] / 2.0
        fig.text(x_text, y_text, cmap, va="center", ha="right", fontsize=font_size)

    if return_fig:
        return fig
    else:
        plt.show()

plot_colormaps(width=8.0, height=0.4)

Plot all available colormaps.

Parameters:

Name	Type	Description	Default
width	float	Width of the colormap. Defaults to 8.0.	8.0
height	float	Height of the colormap. Defaults to 0.4.	0.4

Source code in geemap/colormaps.py

def plot_colormaps(width=8.0, height=0.4):
    """Plot all available colormaps.

    Args:
        width (float, optional): Width of the colormap. Defaults to 8.0.
        height (float, optional): Height of the colormap. Defaults to 0.4.
    """
    cmap_list = list_colormaps()
    nrows = len(cmap_list)
    fig, axes = plt.subplots(nrows=nrows, figsize=(width, height * nrows))
    fig.subplots_adjust(top=0.95, bottom=0.01, left=0.2, right=0.99)

    gradient = np.linspace(0, 1, 256)
    gradient = np.vstack((gradient, gradient))

    for ax, name in zip(axes, cmap_list):
        ax.imshow(gradient, aspect="auto", cmap=mpl.colormaps[name])
        ax.set_axis_off()
        pos = list(ax.get_position().bounds)
        x_text = pos[0] - 0.01
        y_text = pos[1] + pos[3] / 2.0
        fig.text(x_text, y_text, name, va="center", ha="right", fontsize=12)

    # Turn off *all* ticks & spines, not just the ones with colormaps.
    for ax in axes:
        ax.set_axis_off()

    plt.show()