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colormaps module

Module for commonly used colormaps and palettes for visualizing geospatial data.

create_colormap(cmap='gray', colors=None, discrete=False, label=None, width=8.0, height=0.4, orientation='horizontal', vmin=0, vmax=1.0, axis_off=False, show_name=False, font_size=12, **kwargs)

Plot a matplotlib colormap.

Parameters:

Name Type Description Default
cmap str

Matplotlib colormap. Defaults to "gray". See https://matplotlib.org/3.3.4/tutorials/colors/colormaps.html#sphx-glr-tutorials-colors-colormaps-py for options.

'gray'
colors list

A list of custom colors to create a colormap. Defaults to None.

None
discrete bool

Whether to create a discrete colorbar. Defaults to False.

False
label str

Label for the colorbar. Defaults to None.

None
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 False.

False
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
Source code in leafmap/colormaps.py
def create_colormap(
    cmap="gray",
    colors=None,
    discrete=False,
    label=None,
    width=8.0,
    height=0.4,
    orientation="horizontal",
    vmin=0,
    vmax=1.0,
    axis_off=False,
    show_name=False,
    font_size=12,
    **kwargs
):
    """Plot a matplotlib colormap.

    Args:
        cmap (str, optional): Matplotlib colormap. Defaults to "gray". See https://matplotlib.org/3.3.4/tutorials/colors/colormaps.html#sphx-glr-tutorials-colors-colormaps-py for options.
        colors (list, optional): A list of custom colors to create a colormap. Defaults to None.
        discrete (bool, optional): Whether to create a discrete colorbar. Defaults to False.
        label (str, optional): Label for the colorbar. Defaults to None.
        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 False.
        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.
    """
    fig, ax = plt.subplots(figsize=(width, height))

    if colors is not None and (isinstance(colors, list) or isinstance(colors, tuple)):
        hexcodes = to_hex_colors(list(colors))
        if discrete:
            col_map = mpl.colors.ListedColormap(hexcodes)
            vals = np.linspace(vmin, vmax, col_map.N + 1)
            norm = mpl.colors.BoundaryNorm(vals, col_map.N)

        else:
            col_map = mpl.colors.LinearSegmentedColormap.from_list(
                "custom", hexcodes, N=256
            )
            norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
    else:

        col_map = plt.get_cmap(cmap)
        norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)

    cb = mpl.colorbar.ColorbarBase(
        ax, norm=norm, cmap=col_map, orientation=orientation, **kwargs
    )

    if label is not None and isinstance(label, str):
        cb.set_label(label, fontsize=font_size)

    if axis_off:
        ax.set_axis_off()
    ax.tick_params(labelsize=font_size)

    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)

    return fig

get_colorbar(colors, vmin=0, vmax=1, width=6.0, height=0.4, orientation='horizontal', discrete=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
Source code in leafmap/colormaps.py
def get_colorbar(
    colors,
    vmin=0,
    vmax=1,
    width=6.0,
    height=0.4,
    orientation="horizontal",
    discrete=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.
    """
    hexcodes = [i if i[0] == "#" else "#" + i for i in colors]
    _, 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)
    plt.show()

get_palette(cmap_name=None, n_class=None)

Get a palette from a matplotlib colormap. 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

Returns:

Type Description
list

A list of hex colors.

Source code in leafmap/colormaps.py
def get_palette(cmap_name=None, n_class=None):
    """Get a palette from a matplotlib colormap. 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.

    Returns:
        list: A list of hex colors.
    """
    cmap = plt.cm.get_cmap(cmap_name, n_class)
    colors = [mpl.colors.rgb2hex(cmap(i))[1:] for i in range(cmap.N)]
    return colors

list_colormaps()

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

Returns:

Type Description
list

The list of colormap names.

Source code in leafmap/colormaps.py
def list_colormaps():
    """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.
    """
    return plt.colormaps()

plot_colormap(cmap='gray', colors=None, discrete=False, label=None, width=8.0, height=0.4, orientation='horizontal', vmin=0, vmax=1.0, axis_off=False, show_name=False, font_size=12, **kwargs)

Plot a matplotlib colormap.

Parameters:

Name Type Description Default
cmap str

Matplotlib colormap. Defaults to "gray". See https://matplotlib.org/3.3.4/tutorials/colors/colormaps.html#sphx-glr-tutorials-colors-colormaps-py for options.

'gray'
colors list

A list of custom colors to create a colormap. Defaults to None.

None
discrete bool

Whether to create a discrete colorbar. Defaults to False.

False
label str

Label for the colorbar. Defaults to None.

None
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 False.

False
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
Source code in leafmap/colormaps.py
def plot_colormap(
    cmap="gray",
    colors=None,
    discrete=False,
    label=None,
    width=8.0,
    height=0.4,
    orientation="horizontal",
    vmin=0,
    vmax=1.0,
    axis_off=False,
    show_name=False,
    font_size=12,
    **kwargs
):
    """Plot a matplotlib colormap.

    Args:
        cmap (str, optional): Matplotlib colormap. Defaults to "gray". See https://matplotlib.org/3.3.4/tutorials/colors/colormaps.html#sphx-glr-tutorials-colors-colormaps-py for options.
        colors (list, optional): A list of custom colors to create a colormap. Defaults to None.
        discrete (bool, optional): Whether to create a discrete colorbar. Defaults to False.
        label (str, optional): Label for the colorbar. Defaults to None.
        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 False.
        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.
    """
    fig, ax = plt.subplots(figsize=(width, height))

    if colors is not None and (isinstance(colors, list) or isinstance(colors, tuple)):
        hexcodes = to_hex_colors(list(colors))
        if discrete:
            col_map = mpl.colors.ListedColormap(hexcodes)
            vals = np.linspace(vmin, vmax, col_map.N + 1)
            norm = mpl.colors.BoundaryNorm(vals, col_map.N)

        else:
            col_map = mpl.colors.LinearSegmentedColormap.from_list(
                "custom", hexcodes, N=256
            )
            norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
    else:

        col_map = plt.get_cmap(cmap)
        norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)

    cb = mpl.colorbar.ColorbarBase(
        ax, norm=norm, cmap=col_map, orientation=orientation, **kwargs
    )

    if label is not None and isinstance(label, str):
        cb.set_label(label, fontsize=font_size)

    if axis_off:
        ax.set_axis_off()
    ax.tick_params(labelsize=font_size)

    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)

    plt.show()

plot_colormaps(width=8.0, height=0.4, return_fig=False, **kwargs)

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
return_fig bool

Whether to return the figure. Defaults to False.

False
Source code in leafmap/colormaps.py
def plot_colormaps(width=8.0, height=0.4, return_fig=False, **kwargs):
    """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.
        return_fig (bool, optional): Whether to return the figure. Defaults to False.
    """
    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=plt.get_cmap(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()

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

Last update: 2021-10-19