HTML version of this notebook with outputs: https://statistikstadtzuerich.github.io/ssz-palette/example.html

SSZ Palette - colormaps in matplotlib

SSZ Palette provides commonly used colormaps of Statistik Stadt Zürich (SSZ) for matplotlib.

Import and register colormaps

import matplotlib.pyplot as plt
import numpy as np
from matplotlib import cm

import sszpalette

# register the ssz color palette
colorsmaps = sszpalette.register()
colorsmaps

['gray10',
 'gray10cool',
 'gray10warm',
 'harmonic6',
 'harmonic12',
 'harmonic6hell',
 'contrasting12',
 'contrasting12hell',
 'sequential9blau',
 'sequential5blau',
 'sequential9rot',
 'sequential5rot',
 'sequential9ocker',
 'sequential5ocker',
 'sequential9petrol',
 'sequential5petrol',
 'diverging5rotgruen',
 'diverging5rotblau',
 'gender4',
 'nation4']

# set the default colormap and the color cycle
plt.set_cmap('contrasting12') # or any other colormap
plt.rcParams['axes.prop_cycle'] = plt.cycler(color=plt.get_cmap().colors)

<Figure size 432x288 with 0 Axes>

Examples

Line plot

# This uses the default colormap and default prop cycle defined above
x = np.linspace(0, 20, 100)
fig, ax = plt.subplots()

for i in range(10):
    ax.plot(x, i * np.cos(x))

plt.show()

Pcolormesh plot

# create mock data
data = np.random.random([100, 100]) * 10

plt.figure(figsize=(7, 6))
plt.pcolormesh(data, cmap='sequential9petrol')
plt.colorbar(orientation='horizontal')

<matplotlib.colorbar.Colorbar at 0x27a398f4390>

Scatter plot

# create mock data
x,y,c = zip(*np.random.rand(30,3)*4-2)
norm = plt.Normalize(-2,2)

# scatter plot with harmonic6 colormap
plt.scatter(x,y,c=c, cmap='harmonic6', norm=norm)
plt.colorbar()
plt.show()

List of all colormaps of SSZ palette

# Indices to step through colormap.
x = np.linspace(0.0, 1.0, 100)

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


def plot_color_gradients(cmap_list):
    nrows = len(cmap_list)
    figh = 0.35 + 0.15 + (nrows + (nrows - 1) * 0.1) * 0.22
    fig, axs = plt.subplots(nrows=len(cmap_list), ncols=1, figsize=(6.4, figh))
    fig.subplots_adjust(top=0.95, bottom=0.01, left=0.2, right=0.99,
                        wspace=0.05)
    fig.suptitle('SSZ palette colormaps', fontsize=18, y=1.0, x=0.6)

    for ax, name in zip(axs, cmap_list):
        ax.imshow(gradient, aspect='auto', cmap=plt.get_cmap(name))
        pos = list(ax.get_position().bounds)
        x_text = pos[0] - 0.01
        y_text = pos[1] + pos[3]/2.
        fig.text(x_text, y_text, name, va='center', ha='right', fontsize=14)

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

    plt.show()


plot_color_gradients(colorsmaps)