Add Seaborn.palplot Axes To Existing Figure For Visualisation Of Different Color Palettes

Adding seaborn figures to subplots is usually done by passing 'ax' when creating the figure. For instance: sns.kdeplot(x, y, cmap=cmap, shade=True, cut=5, ax=ax) This method, howe

Solution 1:

As you've probably already found, there's little documentation for the palplot function, but I've lifted directly from the seaborn github repo here:

defpalplot(pal, size=1):
    """Plot the values in a color palette as a horizontal array.
    Parameters
    ----------
    pal : sequence of matplotlib colors
        colors, i.e. as returned by seaborn.color_palette()
    size :
        scaling factor for size of plot
    """
    n = len(pal)
    f, ax = plt.subplots(1, 1, figsize=(n * size, size))
    ax.imshow(np.arange(n).reshape(1, n),
              cmap=mpl.colors.ListedColormap(list(pal)),
              interpolation="nearest", aspect="auto")
    ax.set_xticks(np.arange(n) - .5)
    ax.set_yticks([-.5, .5])
    # Ensure nice border between colors
    ax.set_xticklabels([""for _ inrange(n)])
    # The proper way to set no ticks
    ax.yaxis.set_major_locator(ticker.NullLocator())

So, it doesn't return any axes or figure objects, or allow you to specify an axes object to write into. You could make your own, as follows, by adding the ax argument and a conditional in case it's not provided. Depending on context, you may need the included imports as well.

defmy_palplot(pal, size=1, ax=None):
    """Plot the values in a color palette as a horizontal array.
    Parameters
    ----------
    pal : sequence of matplotlib colors
        colors, i.e. as returned by seaborn.color_palette()
    size :
        scaling factor for size of plot
    ax :
        an existing axes to use
    """import numpy as np
    import matplotlib as mpl
    import matplotlib.pyplot as plt
    import matplotlib.ticker as ticker

    n = len(pal)
    if ax isNone:
        f, ax = plt.subplots(1, 1, figsize=(n * size, size))
    ax.imshow(np.arange(n).reshape(1, n),
              cmap=mpl.colors.ListedColormap(list(pal)),
              interpolation="nearest", aspect="auto")
    ax.set_xticks(np.arange(n) - .5)
    ax.set_yticks([-.5, .5])
    # Ensure nice border between colors
    ax.set_xticklabels([""for _ inrange(n)])
    # The proper way to set no ticks
    ax.yaxis.set_major_locator(ticker.NullLocator())

This function should work like you expect when you include the 'ax' argument. To implement this in your example:

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt

fig1 = plt.figure()
length, n_colors = 12, 50# amount of subplots and colors per subplot
start_colors = np.linspace(0, 3, length)
for i, start_color inenumerate(start_colors):
    ax = fig1.add_subplot(length, 1, i + 1)
    colors = sns.cubehelix_palette(
        n_colors=n_colors, start=start_color, rot=0, light=0.4, dark=0.8
    )
    my_palplot(colors, ax=ax)
plt.show(fig1)